bmc health services research protocol paper

Protocols are peer-reviewed articles that offer detailed step-by-step descriptions of experimental techniques. Protocols must (1) provide sufficient details to enable researchers to easily perform the experiment successfully; (2) provide evidence that the protocol works by referencing at least one peer-reviewed publication where the protocol was employed to generate results; (3) describe an advance on what has been previously available. Protocols describing routine methods will not be considered for publication.

BMC Methods strongly supports open research, including transparency and openness in reporting. Further details of our Data availability policy can be found here .

Protocols.io partnership

We strongly recommend that authors share their step-by-step protocol on protocols.io before submitting their manuscript to BMC Methods. When shared on protocols.io , a digital object identifier (DOI) can be assigned to the protocol as a permanent link to the method, which can then be dynamically updated. To include a link to a protocols.io published protocol in the manuscript, first describe your step-by-step protocol on protocols.io and then follow the instructions here: https://www.protocols.io/help/publish-articles. In brief, either publish or reserve a DOI for your protocol, include the DOI links (and private link if generated) into your manuscript to provide editor and reviewer access.

Protocols will then consist of two interlinked components:

A step-by-step protocol posted on protocols.io, which includes methodological details, such as timing, reagents, measurements, formulae, video clips and dynamic flow charts.
A peer-reviewed BMC Methods article contextualising the protocol, with sections discussing background, advantages, applications, limitations, troubleshooting, expected results, benchmarking data and sample datasets from using the protocol.

Authors submitting a Protocol can also use the protocols.io’s protocol entry service at no cost: the team at protocols.io will enter the protocol for you and format it in a way that takes advantage of the platform’s features. Authors will have the opportunity to review and make further changes before the protocol is shared with anyone else. Authors who would like to use protocols.io's protocol entry service in connection with a Protocol submission, need to contact the BMC Methods in-house Editor to request the customer code.

Authors have the option to provide a protocols.io link later in the editorial process if they wish.

Preparing your manuscript

The title page should:

present a title, that succinctly describe the method, its purpose and, if appropriate, the model system or organism
list the full names and institutional addresses for all authors
if a collaboration group should be listed as an author, please list the Group name as an author. If you would like the names of the individual members of the Group to be searchable through their individual PubMed records, please include this information in the “Acknowledgements” section in accordance with the instructions below
Large Language Models (LLMs), such as ChatGPT , do not currently satisfy our authorship criteria . Notably an attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs. Use of an LLM should be properly documented in the Methods section (and if a Methods section is not available, in a suitable alternative part) of the manuscript
indicate the corresponding author

The Abstract should not exceed 350 words. Please minimise the use of abbreviations and do not cite references in the abstract. The abstract must include the following separate sections:

Background: the context and purpose of the study
Methods: a brief summary of the protocol
Discussion: potential implications, expected results and limitations

Three to ten keywords representing the main content of the article.

The ‘Background’ section should explain the context and the design of the study, including its aims and application, a summary of the existing literature, why this study is necessary or its contribution to the field and any limitations. The advantages and disadvantages of your protocol compared to other alternatives should be discussed. Provide references to key papers where the protocol has been used previously to generate data, including those published by your own group.

Materials

If a step-by-step protocol has already been published on protocols.io, the ‘Materials’ section should contain a link to the protocol on protocols.io. The following format should be used: “The protocol described in this peer-reviewed article is published on protocols.io, Updated February 9 2021 https://dx.doi.org/10.17504/protocols.io.xxxxxxx.”

If the Protocol has been submitted to BMC Methods without prior publication on protocols.io, the ‘Materials’ section should consist of a detailed list of all biological materials, reagents, solutions (with recipes), laboratory supplies and equipment required for the successful execution of the protocol, including manufacturer catalogue numbers, instructions on how to acquire/produce items that are not commercially available, and storage conditions/shelf-life for critical reagents. Organise this section according to the categories below:

Biological materials (include, e.g., bacterial and virus strains, cell lines, or biological samples)
Solutions
Recipes (provide details for preparing reagents and solutions, including storage temperature and shelf-life).
Laboratory supplies
Laboratory equipment (provide any information on the equipment setup).
Software or datasets (provide version and release date). Provide references for items that are not commercially available.

It can be combined in ‘Materials and Procedure’ section if a step-by-step protocol has already been published on protocols.io.

If the Protocol has been submitted to BMC Methods without prior publication on protocols.io, the ‘Procedure’ section should consist of a step-by-step description of the technique. This must be provided as a numbered list of direct experimental instructions. Please use the active tense rather than the passive tense. If the protocol naturally breaks into separate stages, then include subheadings and resume the numbered list. For each step include a timing, details for material and reagents used (e.g., volume added, specific container/tube, and incubation time) and the conditions in which the step is performed (e.g., temperature, agitation speed, and equipment settings). Subheadings are particularly appropriate after steps where the procedure can be stopped and resumed at a later date, which should be indicated with a PAUSE POINT flag followed by a brief description of the options available (e.g. "Can be left overnight at 4°C or frozen for up to a month at -20°C").

Highlight critical steps in the protocol that must be performed in a very precise manner to maximise the likelihood of success (e.g. where the time and temperature of a step is crucial or the use of RNase free solutions is required). Make these clear with a CRITICAL STEP flag followed by a brief explanation.

Where there are alternative routes to reach the next stage of the protocol, please provide enough information for readers to make an informed decision on the route to choose. Letters of the Latin alphabet (A), B), C)...) should be used to identify the different options, and Roman numerals (i), ii), iii)...) should be used to break down the appropriate steps. If you wish to include subheadings, add the subheading at the start of the first step within that section and make the text italic. This formatting can also be used to include second-level subheadings within the main procedure. If the protocol is complicated, consider including a flow diagram to demonstrate how the stages fit together. We encourage authors to submit images and videos for particularly complicated steps or stages.

A statement that all local safety guidelines have been followed should be provided.

General notes and troubleshooting

The ‘General notes and troubleshooting’ section includes comments that apply broadly to the protocol and are not fundamental to completing individual steps. For example, address any practical or operational issues involved in performing the study and discuss its applicability to other experimental systems or model organisms and any sources of variability.

We encourage authors to provide information on how to troubleshoot the most likely problems users will encounter with the protocol in the form of a table with the column headings ‘step’, ‘problem’, ‘possible reason’, and ‘solution’. The step number should be given for where the problem is first observed. The appropriate steps should also be highlighted in the procedure with TROUBLESHOOTING flags. If troubleshooting text refers to only one or two steps, it can also be formatted as normal text with subheadings referring to the relevant steps or sections.

Expected results

The ‘Expected results’ section includes information about the likely outcome of the protocol (for example, likely yield of protein, typical microscopy images, etc.). We encourage authors to provide one set of data from an experiment that worked well using the protocol, including information about the number of replicates and controls that were used. This data will serve as a benchmark demonstrating to a user exactly what they should achieve if they replicate the experiment correctly. If applicable, include advice on how to interpret and analyse raw data, including statistical tests and criteria for data inclusion/exclusion.

List of abbreviations

If abbreviations are used in the text they should be defined in the text at first use, and a list of abbreviations should be provided.

Declarations

All manuscripts must contain the following sections under the heading 'Declarations':

Ethics approval and consent to participate

Consent for publication, availability of data and materials, competing interests, authors' contributions, acknowledgements.

Authors' information (optional)

Please see below for details on the information to be included in these sections.

If any of the sections are not relevant to your manuscript, please include the heading and write 'Not applicable' for that section.

Manuscripts reporting studies involving human participants, human data or human tissue must:

include a statement on ethics approval and consent (even where the need for approval was waived)
include the name of the ethics committee that approved the study and the committee’s reference number if appropriate

Studies involving animals must include a statement on ethics approval and for experimental studies involving client-owned animals, authors must also include a statement on informed consent from the client or owner.

See our editorial policies for more information.

If your manuscript does not report on or involve the use of any animal or human data or tissue, please state “Not applicable” in this section.

If your manuscript contains any individual person’s data in any form (including any individual details, images or videos), consent for publication must be obtained from that person, or in the case of children, their parent or legal guardian. All presentations of case reports must have consent for publication.

You can use your institutional consent form or our consent form if you prefer. You should not send the form to us on submission, but we may request to see a copy at any stage (including after publication).

See our editorial policies for more information on consent for publication.

If your manuscript does not contain data from any individual person, please state “Not applicable” in this section.

All manuscripts must include an ‘Availability of data and materials’ statement. Data availability statements should include information on where data supporting the results reported in the article can be found including, where applicable, hyperlinks to publicly archived datasets analysed or generated during the study. By data we mean the minimal dataset that would be necessary to interpret, replicate and build upon the findings reported in the article. We recognise it is not always possible to share research data publicly, for instance when individual privacy could be compromised, and in such instances data availability should still be stated in the manuscript along with any conditions for access.

Authors are also encouraged to preserve search strings on searchRxiv https://searchrxiv.org/ , an archive to support researchers to report, store and share their searches consistently and to enable them to review and re-use existing searches. searchRxiv enables researchers to obtain a digital object identifier (DOI) for their search, allowing it to be cited.

Data availability statements can take one of the following forms (or a combination of more than one if required for multiple datasets):

The datasets generated and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
All data generated or analysed during this study are included in this published article [and its supplementary information files].
The datasets generated and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.
Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
The data that support the findings of this study are available from [third party name] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [third party name].
Not applicable. If your manuscript does not contain any data, please state 'Not applicable' in this section.

More examples of template data availability statements, which include examples of openly available and restricted access datasets, are available here .

BioMed Central strongly encourages the citation of any publicly available data on which the conclusions of the paper rely in the manuscript. Data citations should include a persistent identifier (such as a DOI) and should ideally be included in the reference list. Citations of datasets, when they appear in the reference list, should include the minimum information recommended by DataCite and follow journal style. Dataset identifiers including DOIs should be expressed as full URLs. For example:

Hao Z, AghaKouchak A, Nakhjiri N, Farahmand A. Global integrated drought monitoring and prediction system (GIDMaPS) data sets. figshare. 2014. http://dx.doi.org/10.6084/m9.figshare.853801

With the corresponding text in the Availability of data and materials statement:

The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]. [Reference number]

If you wish to co-submit a data note describing your data to be published in BMC Research Notes , you can do so by visiting our submission portal . Data notes support open data and help authors to comply with funder policies on data sharing. Co-published data notes will be linked to the research article the data support ( example ).

All financial and non-financial competing interests must be declared in this section.

See our editorial policies for a full explanation of competing interests. If you are unsure whether you or any of your co-authors have a competing interest please contact the editorial office.

Please use the authors initials to refer to each authors' competing interests in this section.

If you do not have any competing interests, please state "The authors declare that they have no competing interests" in this section.

All sources of funding for the research reported should be declared. If the funder has a specific role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript, this should be declared.

The individual contributions of authors to the manuscript should be specified in this section. Guidance and criteria for authorship can be found in our editorial policies .

Please use initials to refer to each author's contribution in this section, for example: "FC analyzed and interpreted the patient data regarding the hematological disease and the transplant. RH performed the histological examination of the kidney, and was a major contributor in writing the manuscript. All authors read and approved the final manuscript."

Please acknowledge anyone who contributed towards the article who does not meet the criteria for authorship including anyone who provided professional writing services or materials.

Authors should obtain permission to acknowledge from all those mentioned in the Acknowledgements section.

See our editorial policies for a full explanation of acknowledgements and authorship criteria.

If you do not have anyone to acknowledge, please write "Not applicable" in this section.

Group authorship (for manuscripts involving a collaboration group): if you would like the names of the individual members of a collaboration Group to be searchable through their individual PubMed records, please ensure that the title of the collaboration Group is included on the title page and in the submission system and also include collaborating author names as the last paragraph of the “Acknowledgements” section. Please add authors in the format First Name, Middle initial(s) (optional), Last Name. You can add institution or country information for each author if you wish, but this should be consistent across all authors.

Please note that individual names may not be present in the PubMed record at the time a published article is initially included in PubMed as it takes PubMed additional time to code this information.

Authors' information

This section is optional.

You may choose to use this section to include any relevant information about the author(s) that may aid the reader's interpretation of the article, and understand the standpoint of the author(s). This may include details about the authors' qualifications, current positions they hold at institutions or societies, or any other relevant background information. Please refer to authors using their initials. Note this section should not be used to describe any competing interests.

Footnotes can be used to give additional information, which may include the citation of a reference included in the reference list. They should not consist solely of a reference citation, and they should never include the bibliographic details of a reference. They should also not contain any figures or tables.

Footnotes to the text are numbered consecutively; those to tables should be indicated by superscript lower-case letters (or asterisks for significance values and other statistical data). Footnotes to the title or the authors of the article are not given reference symbols.

Always use footnotes instead of endnotes.

Examples of the Vancouver reference style are shown below.

See our editorial policies for author guidance on good citation practice

Web links and URLs: All web links and URLs, including links to the authors' own websites, should be given a reference number and included in the reference list rather than within the text of the manuscript. They should be provided in full, including both the title of the site and the URL, as well as the date the site was accessed, in the following format: The Mouse Tumor Biology Database. http://tumor.informatics.jax.org/mtbwi/index.do . Accessed 20 May 2013. If an author or group of authors can clearly be associated with a web link, such as for weblogs, then they should be included in the reference.

Example reference style:

Article within a journal

Smith JJ. The world of science. Am J Sci. 1999;36:234-5.

Article within a journal (no page numbers)

Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Medicine. 2013;11:63.

Article within a journal by DOI

Slifka MK, Whitton JL. Clinical implications of dysregulated cytokine production. Dig J Mol Med. 2000; doi:10.1007/s801090000086.

Article within a journal supplement

Frumin AM, Nussbaum J, Esposito M. Functional asplenia: demonstration of splenic activity by bone marrow scan. Blood 1979;59 Suppl 1:26-32.

Book chapter, or an article within a book

Wyllie AH, Kerr JFR, Currie AR. Cell death: the significance of apoptosis. In: Bourne GH, Danielli JF, Jeon KW, editors. International review of cytology. London: Academic; 1980. p. 251-306.

OnlineFirst chapter in a series (without a volume designation but with a DOI)

Saito Y, Hyuga H. Rate equation approaches to amplification of enantiomeric excess and chiral symmetry breaking. Top Curr Chem. 2007. doi:10.1007/128_2006_108.

Complete book, authored

Blenkinsopp A, Paxton P. Symptoms in the pharmacy: a guide to the management of common illness. 3rd ed. Oxford: Blackwell Science; 1998.

Online document

Doe J. Title of subordinate document. In: The dictionary of substances and their effects. Royal Society of Chemistry. 1999. http://www.rsc.org/dose/title of subordinate document. Accessed 15 Jan 1999.

Online database

Healthwise Knowledgebase. US Pharmacopeia, Rockville. 1998. http://www.healthwise.org. Accessed 21 Sept 1998.

Supplementary material/private homepage

Doe J. Title of supplementary material. 2000. http://www.privatehomepage.com. Accessed 22 Feb 2000.

University site

Doe, J: Title of preprint. http://www.uni-heidelberg.de/mydata.html (1999). Accessed 25 Dec 1999.

Doe, J: Trivial HTTP, RFC2169. ftp://ftp.isi.edu/in-notes/rfc2169.txt (1999). Accessed 12 Nov 1999.

Organization site

ISSN International Centre: The ISSN register. http://www.issn.org (2006). Accessed 20 Feb 2007.

Dataset with persistent identifier

Zheng L-Y, Guo X-S, He B, Sun L-J, Peng Y, Dong S-S, et al. Genome data from sweet and grain sorghum (Sorghum bicolor). GigaScience Database. 2011. http://dx.doi.org/10.5524/100012 .

Figures, tables and additional files

See General formatting guidelines for information on how to format figures, tables and additional files.

Submit manuscript

In partnership with:

BMC Methods works in partnership with protocols.io .

Discover more here .

Important information

For authors

For editorial board members

For reviewers

Editorial Board
Manuscript editing services

BMC Methods

ISSN: 3004-8729

Submission enquiries: [email protected]
General enquiries: [email protected]

Open access
Published: 27 June 2011

The case study approach

Sarah Crowe 1 ,
Kathrin Cresswell 2 ,
Ann Robertson 2 ,
Guro Huby 3 ,
Anthony Avery 1 &
Aziz Sheikh 2

BMC Medical Research Methodology volume 11 , Article number: 100 ( 2011 ) Cite this article

792k Accesses

1111 Citations

42 Altmetric

Metrics details

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Peer Review reports

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article CAS PubMed PubMed Central Google Scholar

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article Google Scholar

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article PubMed Google Scholar

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed PubMed Central Google Scholar

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article PubMed Central Google Scholar

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS PubMed PubMed Central Google Scholar

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article PubMed PubMed Central Google Scholar

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article CAS PubMed Google Scholar

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book Google Scholar

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

Pre-publication history

The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1471-2288/11/100/prepub

Download references

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

Author information

Authors and affiliations.

Division of Primary Care, The University of Nottingham, Nottingham, UK

Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Kathrin Cresswell, Ann Robertson & Aziz Sheikh

School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sarah Crowe .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article.

Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

Download citation

Received : 29 November 2010

Accepted : 27 June 2011

Published : 27 June 2011

DOI : https://doi.org/10.1186/1471-2288-11-100

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Case Study Approach
Electronic Health Record System
Case Study Design
Case Study Site
Case Study Report

BMC Medical Research Methodology

ISSN: 1471-2288

General enquiries: [email protected]

bmc health services research protocol paper

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

Search in PubMed
Search in NLM Catalog
Add to Search

The barriers and facilitators influencing the sustainability of hospital-based interventions: a systematic review

Affiliations.

1 Nursing, Midwifery and Allied Health Professions Research Unit (NMAHP RU), Glasgow Caledonian University, Govan Mbeki Building, Cowcaddens Road, Glasgow, G4 0BX, Scotland. [email protected].
2 Health Services Research Unit, University of Aberdeen, 2nd Floor, Health Sciences Building, Foresterhill, Aberdeen, AB25 2ZD, Scotland.
3 Department of Nursing and Health, School of Life Sciences, Glasgow Caledonian University, Govan Mbeki Building, Cowcaddens Road, Glasgow, G4 0BX, Scotland.
4 Nursing, Midwifery and Allied Health Professions Research Unit (NMAHP RU), Glasgow Caledonian University, Govan Mbeki Building, Cowcaddens Road, Glasgow, G4 0BX, Scotland.
5 Nursing, Midwifery and Allied Health Professions Research Unit (NMAHP RU), Unit 13 Scion House, University of Stirling Innovation Park, Stirling, FK9 4NF, Scotland.
PMID: 32594912
PMCID: PMC7321537
DOI: 10.1186/s12913-020-05434-9

Background: Identifying factors that influence sustained implementation of hospital-based interventions is key to ensuring evidence-based best practice is maintained across the NHS. This study aimed to identify, appraise and synthesise the barriers and facilitators that influenced the delivery of sustained healthcare interventions in a hospital-based setting.

Methods: A systematic review reported in accordance with PRISMA. Eight electronic databases were reviewed in addition to a hand search of Implementation Science journal and reference lists of included articles. Two reviewers were used to screen potential abstracts and full text papers against a selection criteria. Study quality was also independently assessed by two reviewers. Barriers and facilitators were extracted and mapped to a consolidated sustainability framework.

Results: Our searching identified 154,757 records. We screened 14,626 abstracts and retrieved 431 full text papers, of which 32 studies met the selection criteria. The majority of studies employed a qualitative design (23/32) and were conducted in the UK (8/32) and the USA (8/32). Interventions or programmes were all multicomponent, with the majority aimed at improving the quality of patient care and/ or safety (22/32). Sustainability was inconsistently reported across 30 studies. Barriers and facilitators were reported in all studies. The key facilitators included a clear accountability of roles and responsibilities (23/32); ensuring the availability of strong leadership and champions advocating the use of the intervention (22/32), and provision of adequate support available at an organisational level (21/32). The most frequently reported barrier to sustainability was inadequate staff resourcing (15/32). Our review also identified the importance of inwards spread and development of the initiative over time, as well as the unpredictability of sustainability and the need for multifaceted approaches.

Conclusions: This review has important implications for practice and research as it increases understanding of the factors that faciliate and hinder intervention sustainability. It also highlights the need for more consistent and complete reporting of sustainability to ensure that lessons learned can be of direct benefit to future implementation of interventions.

Trial registration: The review is registered on PROSPERO ( CRD42017081992 ).

Keywords: Barriers; Dynamic; Facilitators; Hospital-based interventions; Implementation; Sustainability; Systematic review.

PubMed Disclaimer

Conflict of interest statement

None to declare.

Consolidated framework for sustainability constructs…

Consolidated framework for sustainability constructs in healthcare

Flowchart of records identified for…

Flowchart of records identified for relevant studies for inclusion in the review

Bar chart showing the included…

Bar chart showing the included studies mapped to the five constructs of sustainability

Bar chart showing the volume…

Bar chart showing the volume of evidence for barriers and facilitators reported within…

Key barriers reported within each…

Key barriers reported within each of the themes from the Lennox (2018) Consolidated…

Key facilitators reported within each…

Key facilitators reported within each of the themes from the Lennox (2018) Consolidated…

Publication types

Search in MeSH

Related information

Cited in Books

Grants and funding

CGA/17/26/CSO_/Chief Scientist Office/United Kingdom
CGA/17/26/Chief Scientist Office, Scottish Government Health and Social Care Directorate

LinkOut - more resources

Full text sources.

BioMed Central
Europe PubMed Central
PubMed Central
MedlinePlus Health Information

Miscellaneous

NCI CPTAC Assay Portal

Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Study protocol
Open access
Published: 04 September 2024

Evaluating fentanyl test strips as a harm reduction strategy in rural and urban counties: study protocol for a randomized controlled trial

Ashley Short Mejia 1 ,
Gary A. Smith 1 , 2 ,
Soledad A. Fernandez 1 , 3 ,
Bridget Freisthler 1 , 4 ,
Christine Grella 5 &
Nichole L. Michaels ORCID: orcid.org/0000-0003-2618-6440 1 , 2

Trials volume 25 , Article number: 587 ( 2024 ) Cite this article

Metrics details

Opioid-related fatalities are a leading cause of death in Ohio and nationally, with an increasing number of overdoses attributable to fentanyl. Rapid fentanyl test strips can identify fentanyl and some fentanyl analogs in urine samples and are increasingly being used to check illicit drugs for fentanyl before they are used. Fentanyl test strips are a promising harm reduction strategy; however, little is known about the real-world acceptability and impact of fentanyl test strip use. This study investigates fentanyl test strip distribution and education as a harm reduction strategy to prevent overdoses among people who use drugs.

The research team will recruit 2400 individuals ≥ 18 years with self-reported use of illicit drugs or drugs purchased on the street within the past 6 months. Recruitment will occur at opioid overdose education and naloxone distribution programs in 16 urban and 12 rural Ohio counties. Participating sites will be randomized at the county level to the intervention or non-intervention study arm. A brief fentanyl test strip educational intervention and fentanyl test strips will be provided to participants recruited from sites in the intervention arm. These participants will be eligible to receive additional fentanyl test strips for 2 years post-enrollment. Participants recruited from sites in the non-intervention arm will not receive fentanyl test strip education or fentanyl test strips. All participants will be followed for 2 years post-enrollment using biweekly, quarterly, and 6-month surveys. Primary outcomes include (1) identification of perceived barriers and facilitating factors associated with incorporating fentanyl test strip education and distribution into opioid overdose education and naloxone distribution programs; (2) differences in knowledge and self-efficacy regarding how to test drugs for fentanyl and strategies for reducing overdose risk between the intervention and non-intervention groups; and (3) differences in non-fatal and fatal overdose rates between the intervention and non-intervention groups.

Findings from this cluster randomized controlled trial will contribute valuable information about the feasibility, acceptability, and impact of integrating fentanyl test strip drug checking in rural and urban communities in Ohio and help guide future overdose prevention interventions.

Trial registration

ClinicalTrials.gov NCT05463341. Registered on July 19, 2022. https://clinicaltrials.gov/study/NCT05463341

Peer Review reports

The United States (US) is experiencing an opioid-related public health crisis. In 2021, Ohio ranked 7th among all states for the highest age-adjusted drug overdose death rate, 48.1 per 100,000 population, which was 48.5% higher than that of the overall US (32.4 per 100,000 population) [ 1 , 2 ]. This drug overdose fatality rate is driven by the use of opioids [ 1 , 2 , 3 ]. An increasing number of opioid-related deaths in the US are attributable to fentanyl, a highly potent synthetic opioid pain medication [ 3 , 4 , 5 ]. Illicit fentanyl and its analogs may be manufactured and sold alone or added to other drugs, such as heroin, cocaine, and counterfeit prescription pills, with or without the user’s knowledge [ 3 , 4 , 5 ].

The increasing pervasiveness of highly lethal fentanyl and fentanyl analogs in the illicit drug supply in the US, including Ohio, has posed a substantial challenge for public health officials looking for strategies to reduce overdoses. While some effective harm reduction strategies, such as opioid overdose education and naloxone distribution (OEND) programs, are becoming more available and widely accepted, they may not be sufficient for preventing overdose deaths due to fentanyl.

Rapid fentanyl test strips (FTS), designed to test for the presence of fentanyl and some fentanyl analogs in urine samples, are increasingly being used off-label to test illicit drugs for fentanyl before they are consumed and are highly sensitive and specific in detecting fentanyl [ 6 , 7 , 8 , 9 ]. Research indicates that when people who use drugs (PWUD) receive a positive result from a fentanyl test strip, they are more likely to perform overdose risk reduction behaviors [ 9 ]. These behaviors (e.g., using less of the drug; using in the presence of someone else) may help to prevent an overdose, or ensure that assistance is nearby, if needed. In the US, access to FTS for home use is variable and is primarily being supported by public health departments and community-based harm reduction organizations. Because access to FTS is limited, little is known about (1) the feasibility and acceptability of this intervention among public health workers, community-based organizations, and PWUD and (2) how outcomes from this intervention compare with OEND-only programs.

This study protocol is designed to test an intervention to prevent drug overdoses among PWUD in rural and urban counties of Ohio. Rural populations are disproportionately burdened by the opioid crisis and face serious health disparities related to their ability to access substance use disorder treatment and emergency care, making them an important population for this research [ 10 , 11 ]. The proposed intervention will incorporate FTS education and distribution into a subset of OEND sites in Ohio. The long-term goal of this research is the reduction of overdose-related morbidity and mortality in Ohio and nationally.

Study objectives and aims

The research objectives of this study are:

Determine the feasibility and acceptability of providing FTS education and testing materials distribution in existing OEND programs.

Determine if adding FTS education and distribution to OEND programs decreases opioid overdose rates among PWUD.

Using a two-arm cluster-randomized trial design, we will answer the research objectives by testing the following specific aims:

Specific aim #1. Determine the perceived barriers and facilitating factors associated with incorporating FTS education and distribution in existing OEND programs in rural and urban counties.

Specific aim #2. Test the hypothesis that PWUD who receive FTS education and testing materials as part of an OEND program will have improved knowledge and self-efficacy regarding how to test drugs for fentanyl and strategies for lowering their risk of an opioid overdose.

Specific aim #3. Test the hypothesis that individuals who receive FTS education and testing materials as part of an OEND program will have a lower opioid overdose rate than individuals who receive OEND only (“usual practice”).

Methods/design

Study setting.

Ohio has an established infrastructure to streamline OEND that can aid in opioid overdose prevention. In an effort to prevent opioid overdose fatalities in the state, the Ohio Department of Health has partnered with local public health departments and community organizations in the state to establish a network of OEND sites. The initiative, called Project DAWN (Deaths Avoided With Naloxone), has more than 200 sites throughout the state, with many counties having multiple sites ( https://odh.ohio.gov/know-our-programs/project-dawn/project-dawn-programs ). Project DAWN sites use trained overdose prevention educators to provide OEND at no cost to clients. Recruitment for this study will occur at Project DAWN sites in Ohio.

Eligibility

Inclusion criteria for the study are (1) age 18 years or older; (2) visitor to a Project DAWN site in Ohio that has agreed to participate in the study; (3) self-reported use of illicit drugs or any drugs purchased on the street within the past 6 months; (4) has a phone number or email address to allow for follow-up contact; and (5) able to participate in study activities in English. Individuals will be excluded from the study if they are unwilling or unable to give informed consent due to altered mental status or other reasons or if they are currently incarcerated.

Study recruitment

Study recruitment will happen on a rolling basis. Periodically throughout the recruitment period, our study partner, Ohio Department of Health, will send recruitment invitations to Project DAWN sites on our behalf. A stratified sampling process will be used to select 12 rural and 16 urban counties from among those with Project DAWN sites that indicate interest in participating in the study and that are not distributing FTS at the time of study enrollment.

Participating counties will then be randomized into the intervention and non-intervention arms of the study, stratified by rural/urban status (Fig. 1 ). Randomization will occur at the county level, and all Project DAWN sites in the same county will be assigned to the same study arm (either intervention or non-intervention). Therefore, all participants enrolled in the same county will be in the same study arm. County randomization will be conducted by the biostatistician on the project (SAF), without influence by study principal investigators (PIs) or staff.

Method of assignment of counties to intervention and non-intervention study arms

To achieve our recruitment goal of 2400 participants, study staff will be on-site to enroll Project DAWN clients who wish to participate in the study. Informed written or e-consent and baseline data, contact information (i.e., locator form), and demographics will be obtained. Project DAWN sites vary in size and operate according to different schedules, but generally provide OEND at least once per week, and frequently see clients more than once. Research study staff will coordinate with each site to ensure rotating coverage of all study counties. Enrollment will begin upon Institutional Review Board (IRB) approval and follow-up will continue with each participant for 2 years. Six-month follow-up questionnaires will be administered to each participating client based on their date of enrollment. Clients who decline to participate will not be included in the study. Individuals who decline to participate but indicate they are interested in obtaining FTS will be offered a printed list of alternate sources of FTS.

Intervention

Fentanyl test strip intervention.

A brief 20-min FTS educational intervention will be provided by the study team to participants at Project DAWN sites in the intervention arm of the study following enrollment and collection of baseline data (Table 1 ). The education will be offered one-on-one with participants in the intervention arm using a curriculum developed by the study team. The curriculum contains the following components: education on the purpose, benefits, and limitations of FTS testing; a hands-on demonstration of how to use FTS for drug testing prior to consumption; diagrams explaining how to interpret FTS results; and what to do if the FTS is positive. Education will be provided on how to use FTS for different drug delivery methods (e.g., injection, snorted, pills). A brief video will be developed by the study team to demonstrate how to use and interpret the FTS. The video will be shown during the educational intervention and will also be accessible to participants in the intervention arm following enrollment. Participants will be advised of the possibility of false positive/negative results, as well as the possibility that their drugs could be mixed with other harmful and/or unanticipated substances not detectable with FTS. Participants will be encouraged to practice other harm reduction strategies (e.g., having someone with them when using drugs, keeping naloxone nearby).

Each study participant will be given 10 FTS upon enrollment. The strips will be packaged with instructions on how to use FTS, a QR code link to the video, harm reduction strategies, and contact information for the study team. Replacement FTS will be available to study participants in the intervention arm upon request throughout their 2-year follow-up period and participants will be asked if they need additional FTS during their biweekly surveys. Replacement FTS can be mailed to participants via US Postal Service or obtained from study staff during subsequent visits to the Project DAWN sites.

Non-intervention group

Participants in the non-intervention arm of the study will not receive FTS education or test strips upon enrollment, but will receive OEND from Project DAWN staff according to their usual practice. During the latter half of year 5, after data collection is complete, participants in the non-intervention arm will be offered the FTS educational intervention and a supply of FTS.

Data collection

Questionnaires.

Baseline and 6-month follow-up questionnaires will consist of true/false knowledge questions, 5-point Likert scale attitude and self-efficacy questions, and multiple-choice questions related to participant behaviors and characteristics. Participants will be asked to indicate their degree of interest in using or avoiding drugs containing fentanyl. Baseline questionnaires will be administered to Project DAWN clients who enroll in the study using iPads and the REDCap (Research Electronic Data Capture) data collection platform. Follow-up questionnaires will be administered at 6 months post-enrollment to study participants via email/text, in-person at Project DAWN sites, or via telephone. Data from paper questionnaires will be entered into REDCap by the research team upon completion and double-entry verification will be used.

Qualitative data

In the second quarter of year 5, qualitative data will be collected through interviews with Project DAWN personnel in the intervention arm to examine the feasibility and acceptability of offering FTS at Project DAWN sites. Topics of discussion will include (1) attitudes about the use of FTS; (2) perceptions of the FTS intervention that was offered at their Project DAWN site, including perceived benefits and harms; (3) barriers and enabling/reinforcing factors related to offering FTS at Project DAWN sites; and (4) interest in continuing to offer FTS at Project DAWN sites. Interviews will be conducted by study staff using an interview guide and will be audio recorded and transcribed. Coding and analysis of the transcripts will be conducted by the study team.

Statistical analyses

Study data will be analyzed using an intention-to-treat approach.

Specific aim #1: To determine the feasibility and acceptability of incorporating FTS education and distribution into existing OEND programs, a questionnaire will be administered to Project DAWN personnel, site supervisors, health commissioners, and other key intervention site personnel in year 5. Project DAWN clients in the intervention arm will be asked about the acceptability of the program as part of their 6-month follow-up questionnaire. Process measures will be collected throughout the study as another source of data on the feasibility and acceptability of the intervention. Quantitative data on process measures will include, but is not limited to, number of Project DAWN sites that express interest in participating in the study; number of Project DAWN sites that enroll; number of potential participants who request to enroll in the study; number of participants successfully enrolled; number of replacement FTS requested and distributed; proportion of participants who complete the brief biweekly surveys; and the proportion of participants who complete the 6-month follow-up questionnaire. Descriptive statistics will be calculated, including overall mean estimates with 95% confidence intervals. Analyses will also be performed by subgroups (e.g., rural/urban, Project DAWN site personnel/client, and demographic subgroups).

Specific aim #2: Measures will be taken at two time points (baseline and 6 months) to test specific aim #2. The instrument to test change in knowledge is composed of true/false items. Correct responses for each of the items will be assigned a value of 1, and incorrect responses will be given a value of 0. Total scores will be calculated. There are also items to test changes in attitudes and self-efficacy that use a 5-point Likert scale. We will also compute total scores for these items. We will fit a linear mixed model using total scores for knowledge as the response variable to test change in knowledge and will fit another linear mixed model using total scores for attitudes/self-efficacy as the response variable to test change in self-efficacy.

Random effects for county (rural/urban), Project DAWN site within county, and participant within county will be included, as well as fixed effects for time (baseline or 6 months) and treatment (intervention/non-intervention). A random variable for secular time will also be included to account for changes across time (e.g., new opioid overdose prevention initiatives, changes in drug supply). To test the hypothesis of change differences between the two time points between the two arms, we will include an interaction term “treatment × time (baseline, 6 months)” in the model. This model will include demographic variables (gender, age, and race) and other relevant covariates or confounding factors, such as education level completed, employment, previous receipt of FTS education and testing materials (Y/N), and previously experienced an overdose (Y/N). Other relevant interaction terms, such as “treatment × gender” and “treatment × race,” will be evaluated. Holm’s method will be used to adjust for ad hoc multiple comparisons. In addition, general linear mixed models (GLMM) with a logit link function will be used to study change differences for specific Y/N items or questions.

Specific aim #3: Non-fatal overdose measures will be taken every 2 weeks and fatal overdose measures will be taken quarterly to test specific aim #3. To study the odds of an experienced overdose (Y/N), a GLMM with logit function will be used. This model will include the same random and fixed effects as identified for the model used to test specific aim #2. At the end of the study period, the overall non-fatal overdose rate (with a 95% confidence interval) will be compared between intervention and non-intervention arms. The same comparison will be done separately for the overall fatal overdose rate (with a 95% confidence interval) between the intervention and non-intervention arms.

Missing data

The analyses will be conducted using an intention-to-treat approach. For the primary and secondary outcomes, every effort will be made to minimize missing data; however, in the event that data are missing, we will document the process that resulted in the missing data and consider model-based imputation methods to account for the missing data. Guidelines for handing missing data in clinical trials will be followed [ 12 ].

Sample size

We expect an enrollment rate of 65% of eligible participants and 30% attrition, a conservative estimate based on research with similar populations [ 13 ]. For the power calculations, we conservatively assumed one Project DAWN site per county. We also assumed that non-fatal overdose rates in the non-intervention and intervention groups are 20% and 10%, respectively, and the annual fatal overdose rate in the non-intervention group is 0.65% [ 14 ]. Based on our sample size calculations, we will enroll 1200 participants in each study arm for a total of 2400 participants. Assuming a 30% attrition rate, 840 participants in each arm will complete 2 years of follow-up, for a total of 1680 participants. This will permit detection of an effect size range of 0.3–0.4 for specific aim #2 and rate differences of 0.1 and 0.14, respectively, for non-fatal and fatal rates for specific aim #3, given the assumptions identified above.

Participant retention

Participant retention will be managed in a series of ongoing steps (Table 2 ). First, participants will receive “thank you” messages via email through an automated REDCap system or letter via US mail, if email is not available. Next, participants’ locator form contact information will be verified by the enrolling research assistant (RA) within 2 weeks of enrollment.

After this, participants will receive follow-up communication from the study team if they miss biweekly surveys or their 6-month survey. Participants receive automated reminders via REDCap every 3 days for up to four reminders for each biweekly survey via email or text, depending on the participant’s preference. Within 2 weeks of missing a second consecutive biweekly survey, RAs will send an email, call/voicemail, letter, and/or social media message depending on the participant’s preferences. Within 3 weeks of missing a second consecutive biweekly survey, the RAs will use the participant’s locator form to contact the participant’s friend or family. This process will be completed monthly until the individual has been successfully contacted or begins surveys. Participants also will receive automated reminders for the 6-month survey every 5 days with up to five reminders via their default survey delivery method through REDCap. Within 2 weeks of missing their 6-month survey, RAs will send an email, call/voicemail, letter, and/or message through social media. Within 3 weeks of missing the 6-month survey, RAs will use the participant’s locator form to contact the participant’s friends or family. This process will be completed for up to 2 months. Participants will also receive a participant newsletter and annual “New Year” and birthday cards.

Study timeline

We expect it will take approximately 24 months to enroll all study participants. After enrollment, study participants will complete follow-up activities for 2 years. Participants may choose to withdraw from the study at any time and will not receive further contact from the study team.

Data management

A Certificate of Confidentiality is in place for this study. Confidentiality will be promoted by assigning an identification number to each study participant. We will use only these identification numbers (and not participants' names) in the database used for study analyses. Study materials containing identifiers, including signed consent forms and gift card receipts, will be scanned and then paper copies will be shredded. Research records will be stored in a password protected computer file. Only study team members with a research need to view the data, appropriate research certifications, and IRB approval will have access. Identifiable data will be retained for 6 years after the research is complete. Upon acceptance of all study manuscripts, any electronic files with participant identifiers will be deleted.

The study team consists of two principal investigators who collaborate closely to oversee the day-to-day work of the study team and are responsible for all aspects of this research, as well as 3 co-investigators, a research coordinator, and 4 research associates. Study co-investigators assisted the principal investigators with the development of study protocols and processes in year 1 and contribute their expertise as needed throughout the study. The research coordinator oversees the implementation of participant recruitment, retention, and consent processes as well as data collection procedures conducted by the research associates. A principal investigator meets with the research coordinator at least weekly and meets with the research associates at least biweekly. The study also utilizes a community advisory board that consists of representatives from non-profit organizations active in the harm reduction community, representatives from government agencies, such as health departments and mental health services, and individuals with lived experience of drug use. The advisory committee meets approximately every 6 months.

Data safety and monitoring

A data safety and monitoring board (DSMB) will be used for this study. Collectively, the DSMB has expertise in medicine, harm reduction, behavioral science (including qualitative research expertise), biostatistics, and public health. The DSMB will review study protocols to identify whether appropriate safeguards are in place to prevent adverse events, such as fatal drug overdoses, and to determine whether the observed frequency and type of events exceed those expected in the study population. The DSMB will review the frequency of adverse events reported among intervention and non-intervention participants to identify any unanticipated problems that may increase the risk of harm among study participants or others and will make recommendations for additional safety measures, or in the case of severe unanticipated negative outcomes, stopping the trial. The DSMB will meet twice a year to review study progress and may convene additional meetings as necessary. Further details about the DSMB charter are available upon request.

Dissemination of study findings

Study findings will be shared with study participants and partnering Project DAWN sites. This study is registered on www.ClinicalTrials.gov , and summaries of study findings will be available on the website upon study completion. Study findings will also be shared through publication in peer-reviewed journals and presentation at scientific meetings and conferences. Publication authorship will be determined using International Committee of Medical Journal Editors guidelines.

Because opioid overdose is a tremendous problem in Ohio and nationally, more studies on the primary and secondary prevention of overdose are needed. Collaborating on this research project with public health officials at the state and local levels, as well as community-based harm reduction organizations, will give us insight into the real-world benefits, challenges, and unanswered questions associated with implementing FTS education and distribution programs and guide future studies.

We expect that the findings of this study will be used to inform decisions by public health leaders and policy makers on whether to support the continuation and expansion of fentanyl test strip education and distribution in Ohio. Using improved scientific rigor compared with previous research, the findings of this study will provide missing, fundamental information to our base of knowledge regarding the feasibility, acceptability, and associated benefits and harms of this emerging strategy for preventing opioid overdoses. In addition to Ohio, we believe that this program could serve as a model for other states.

Trial status

Protocol version 5, approved on October 11, 2023. Study recruitment began on September 9, 2022, and is ongoing. We anticipate study recruitment will be complete by December 31, 2024.

Availability of data and materials

The study PIs will oversee the management of all aspects of this research study and will determine access to the final trial dataset. Unique study resources and data will be made available for research purposes to qualified individuals within the scientific community after publication. Upon written request to the study contact PI (NLM), de-identified data used in publications will be made available to users under a data-sharing agreement. Along with the data, we also will make available the data instruments used to collect the data, methods of collection, variable definitions, and potential limitations for use.

Abbreviations

Fentanyl test strips

Data safety and monitoring board

General linear mixed models

Institutional Review Board

Opioid overdose education and naloxone distribution

Principal investigator

Project Deaths Avoided With Naloxone

People who use drugs

Research assistant

Research Electronic Data Capture

United States

Centers for Disease Control and Prevention. Ohio priority topic investments. Ohio overdose investment snapshot. CDC. https://www.cdc.gov/injury/budget-funding/ohio-aces-and-overdose-prevention-funding.html?CDC_AAref_Val=https://www.cdc.gov/injury/budget/policystatesnapshots/ohio.html . Accessed 27 Jul 2024.

Centers for Disease Control and Prevention. Drug overdose mortality by state. CDC/National Center for Health Statistics. 2021. https://www.cdc.gov/nchs/pressroom/sosmap/drug_poisoning_mortality/drug_poisoning.htm . Accessed 27 Jul 2024.

Centers for Disease Control and Prevention. Preventing opioid overdoses. 2024. https://www.cdc.gov/overdose-prevention/prevention/index.html . Accessed 27 Jul 2024.

Peterson AB, Gladden RM, Delcher C, Spies E, Garcia-Williams A, Wang Y, Halpin J, Zibbell J, McCarty CL, DeFiore-Hyrmer J, DiOrio M, Goldberger BA. Increases in fentanyl-related overdose deaths - Florida and Ohio, 2013–2015. MMWR Morb Mortal Wkly Rep. 2016;65(33):844–9. https://doi.org/10.15585/mmwr.mm6533a3 .

Article PubMed Google Scholar

Hedegaard H, Miniño AM, Warner M. Drug overdose deaths in the United States, 1999–2017. NCHS Data Brief. 2018(329):1-7. Hyattsville: National Center for Health Statistics. https://www.cdc.gov/nchs/data/databriefs/db329-h.pdf . Accessed 16 Jun 2024.

Goldman JE, Waye KM, Periera KA, Krieger MS, Yedinak JL, Marshall BDL. Perspectives on rapid fentanyl test strips as a harm reduction practice among young adults who use drugs: a qualitative study. Harm Reduct J. 2019;16(1):3.

Article PubMed PubMed Central Google Scholar

Krieger MS, Yedinak JL, Buxton JA, Lysyshyn M, Bernstein E, Rich JD, Green TC, Hadland SE, Marshall BDL. High willingness to use rapid fentanyl test strips among young adults who use drugs. Harm Reduct J. 2018;15(1):7.

Krieger MS, Goedel WC, Buxton JA, Lysyshyn M, Bernstein E, Sherman SG, Rich JD, Hadland SE, Green TC, Marshall BDL. Use of rapid fentanyl test strips among young adults who use drugs. Int J Drug Policy. 2018;61:52–8.

Peiper NC, Clarke SD, Vincent LB, Ciccarone D, Kral AH, Zibbell JE. Fentanyl test strips as an opioid overdose prevention strategy: findings from a syringe services program in the Southeastern United States. Int J Drug Policy. 2019;63:122–8.

Rembert M, Betz M, Feng B, Partridge M. Taking measure of Ohio’s opioid crisis. Swank program in rural-urban policy. The Ohio State University. 2017. https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/2/14548/files/2017/10/SWANK-Taking-Measure-of-Ohios-Opioid-Crisis-1vtx548.pdf . Accessed 27 Jul 2024.

Joudrey PJ, Edelman EJ, Wang EA. Drive times to opioid treatment programs in urban and rural counties in 5 US states. JAMA. 2019;322(13):1310–2.

National Research Council (US) Panel on Handling Missing Data in Clinical Trials. The prevention and treatment of missing data in clinical trials. Washington, DC: National Academies Press; 2010. https://doi.org/10.17226/12955 .

Karno MP, Rawson R, Rogers B, Spear S, Grella C, Mooney LJ, Saitz R, Kagan B, Glasner S. Effect of screening, brief intervention and referral to treatment for unhealthy alcohol and other drug use in mental health treatment settings: a randomized controlled trial. Addiction. 2021;116(1):159–69. https://doi.org/10.1111/add.15114 .

World Health Organization. Management of substance abuse: information sheet on opioid overdose. August 2018. https://www.who.int/substance_abuse/information-sheet/en/ Accessed 28 August 2024.

Download references

Acknowledgements

We would like to thank our colleagues Alexandra Antonova, Aleah Cumberbatch, Jacob Holycross, and Spencer Long for their contributions to this research.

Research reported in this publication was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number R01DA052580. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in the design of this study and will not have any role in the collection, management, analysis, and interpretation of data; writing of the report; or decision to submit the report for publication.

Author information

Authors and affiliations.

Center for Injury Research and Policy at the Abigail Wexner Research Institute at Nationwide Children’s Hospital, 575 Children’s Crossroad, Columbus, OH, 43215, USA

Ashley Short Mejia, Gary A. Smith, Soledad A. Fernandez, Bridget Freisthler & Nichole L. Michaels

Department of Pediatrics, College of Medicine, The Ohio State University, 370 W. 9th Avenue, Columbus, OH, 43210, USA

Gary A. Smith & Nichole L. Michaels

Department of Biomedical Informatics and Center for Biostatistics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA

Soledad A. Fernandez

College of Social Work, The Ohio State University, Columbus, OH, 43210, USA

Bridget Freisthler

Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, 90025, USA

Christine Grella

You can also search for this author in PubMed Google Scholar

Contributions

ASM led manuscript preparation. The research was conceptualized and the original study protocol was developed by NLM, GAS, and SAF. All authors provided feedback on the manuscript and approved the final draft of the manuscript for publication.

Corresponding author

Correspondence to Nichole L. Michaels .

Ethics declarations

Ethics approval and consent to participate.

The Nationwide Children’s Hospital Institutional Review Board has given ethical approval for this study (STUDY00001919). Any modifications to the study protocol are subject to approval by the IRB of record. Relevant modifications will be reported to the trial registry and other parties as necessary. Informed consent will be obtained from all study participants according to the IRB-approved study protocol. The consent process will take place on-site at the recruitment location and will be completed prior to any data collection. At the time of enrollment, a member of the research team will review the contents of the informed consent document with the potential participant and answer any questions they may have prior to obtaining written consent via e-signature or paper consent form. Consent will be documented in REDCap and a pdf file of the signed e-consent form will be emailed to the participant. If the participant does not have an email address, a paper copy will be signed and distributed to them. Paper consent forms will be used to obtain written consent in person at the time of enrollment only as necessary (e.g., due to technology failure). Participants will be able to leave the study or stop participating in study activities at any time.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

As the primary organization conducting this study and associated data analysis, Nationwide Children’s Hospital is the sponsor of this research. They can be contacted at 700 Children’s Drive, Columbus, OH 43205, USA; phone number: 614–722-2000.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: spirit checklist., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Short Mejia, A., Smith, G.A., Fernandez, S.A. et al. Evaluating fentanyl test strips as a harm reduction strategy in rural and urban counties: study protocol for a randomized controlled trial. Trials 25 , 587 (2024). https://doi.org/10.1186/s13063-024-08440-y

Download citation

Received : 01 August 2024

Accepted : 28 August 2024

Published : 04 September 2024

DOI : https://doi.org/10.1186/s13063-024-08440-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Harm reduction
Randomized controlled trial
Substance use

ISSN: 1745-6215

Submission enquiries: Access here and click Contact Us
General enquiries: [email protected]

Example of BMC Health Services Research - study protocol format

Recent searches

Institutions, conferences, journals gallery.

40,000+ journal templates to choose from for your next paper

Flexible pricing plans that caters to everyone’s needs

Journal Submission

Get accepted in top journals.

For Publishers

Streamline publishing process with automated workflows

Client Stories

Read what our clients have yielded with our products and services

Convert from Word

Word file to JATS XML, PMC XML, DOAJ XML and more

Convert from PDF

PDF file to SciELO XML, CrossRef XML and more

Convert from JATS XML

JATS XML to Redalyc XML, DataCite XML and more

Adhere to standard of all global publishing bodies

Compliance for medical journals in PubMed database

Generate standardized XML for SciELO indexed journals

BMC Health Services Research - study protocol — Template for authors

— or sign up using email —

BMC Health Services Research - study protocol

Guideline source: View

All company, product and service names used in this website are for identification purposes only. All product names, trademarks and registered trademarks are property of their respective owners.

Use of these names, trademarks and brands does not imply endorsement or affiliation. Disclaimer Notice

Approved by publishing and review experts on SciSpace, this template is built as per for BMC Health Services Research - study protocol formatting guidelines as mentioned in BMC author instructions. The current version was created on and has been used by 198 authors to write and format their manuscripts to this journal.

Healthcare systems



	[25]
	Blonder, G.E., Tinkham, M., Klapwijk, T.M.: Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B 25(7), 4515–4532 (1982)

Applied Numerical Mathematics template (Elsevier)

SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

What to expect from SciSpace?

Speed and accuracy over ms word.

With SciSpace, you do not need a word template for BMC Health Services Research - study protocol.

It automatically formats your research paper to BMC formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

Time taken to format a paper and Compliance with guidelines

Freedom from formatting guidelines

One editor, 100K journal formats – world's largest collection of journal templates

With such a huge verified library, what you need is already there.

Easy support from all your favorite tools

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. can i write bmc health services research - study protocol in latex.

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the BMC Health Services Research - study protocol guidelines and auto format it.

2. Do you follow the BMC Health Services Research - study protocol guidelines?

Yes, the template is compliant with the BMC Health Services Research - study protocol guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in BMC Health Services Research - study protocol?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the BMC Health Services Research - study protocol citation style.

4. Can I use the BMC Health Services Research - study protocol templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for BMC Health Services Research - study protocol.

5. Can I use a manuscript in BMC Health Services Research - study protocol that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper BMC Health Services Research - study protocol that you can download at the end.

6. How long does it usually take you to format my papers in BMC Health Services Research - study protocol?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in BMC Health Services Research - study protocol.

7. Where can I find the template for the BMC Health Services Research - study protocol?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per BMC Health Services Research - study protocol's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the BMC Health Services Research - study protocol's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. BMC Health Services Research - study protocol an online tool or is there a desktop version?

SciSpace's BMC Health Services Research - study protocol is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like BMC Health Services Research - study protocol?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like BMC Health Services Research - study protocol?”

11. What is the output that I would get after using BMC Health Services Research - study protocol?

After writing your paper autoformatting in BMC Health Services Research - study protocol, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is BMC Health Services Research - study protocol's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for BMC Health Services Research - study protocol?


Green	Can archive pre-print post-print or publisher's version/PDF
Blue	Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow	Can archive pre-print (ie pre-refereeing)
White	Archiving not formally supported

Pre-prints as being the version of the paper before peer review and
Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In BMC Health Services Research - study protocol?


1.	Author Year
2.	Numbered
3.	Numbered (Superscripted)
4.	Author Year (Cited Pages)
5.	Footnote

15. How do I submit my article to the BMC Health Services Research - study protocol?

16. can i download bmc health services research - study protocol in endnote format.

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in BMC Health Services Research - study protocol Endnote style according to Elsevier guidelines.

with BMC Health Services Research - study protocol format applied

Fast and reliable, built for complaince.

Instant formatting to 100% publisher guidelines on - SciSpace.

No word template required

Typset automatically formats your research paper to BMC Health Services Research - study protocol formatting guidelines and citation style.

Verifed journal formats

One editor, 100K journal formats. With the largest collection of verified journal formats, what you need is already there.

Trusted by academicians

I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

Open access
Published: 28 September 2023

Genotypic and phenotypic comparison of drug resistance profiles of clinical multidrug-resistant Mycobacterium tuberculosis isolates using whole genome sequencing in Latvia

Anda Vīksna 1 , 2 ,
Darja Sadovska 3 ,
Iveta Berge 1 ,
Ineta Bogdanova 1 ,
Annija Vaivode 3 ,
Lauma Freimane 3 ,
Inga Norvaiša 1 ,
Iveta Ozere 1 , 2 &
Renāte Ranka 3

BMC Infectious Diseases volume 23 , Article number: 638 ( 2023 ) Cite this article

2722 Accesses

6 Citations

2 Altmetric

Metrics details

Multidrug-resistant tuberculosis (MDR–TB) remains a major public health problem in many high tuberculosis (TB) burden countries. Phenotypic drug susceptibility testing (DST) take several weeks or months to result, but line probe assays and Xpert/Rif Ultra assay detect a limited number of resistance conferring gene mutations. Whole genome sequencing (WGS) is an advanced molecular testing method which theoretically can predict the resistance of M. tuberculosis (Mtb) isolates to all anti-TB agents through a single analysis.

Here, we aimed to identify the level of concordance between the phenotypic and WGS-based genotypic drug susceptibility (DS) patterns of MDR–TB isolates. Overall, data for 12 anti-TB medications were analyzed.

In total, 63 MDR–TB Mtb isolates were included in the analysis, representing 27.4% of the total number of MDR–TB cases in Latvia in 2012–2014. Among them, five different sublineages were detected, and 2.2.1 (Beijing group) and 4.3.3 (Latin American-Mediterranean group) were the most abundant. There were 100% agreement between phenotypic and genotypic DS pattern for isoniazid, rifampicin, and linezolid. High concordance rate (> 90%) between phenotypic and genotypic DST results was detected for ofloxacin (93.7%), pyrazinamide (93.7%) and streptomycin (95.4%). Phenotypic and genotypic DS patterns were poorly correlated for ethionamide (agreement 56.4%), ethambutol (85.7%), amikacin (82.5%), capreomycin (81.0%), kanamycin (85.4%), and moxifloxacin (77.8%). For capreomycin, resistance conferring mutations were not identified in several phenotypically resistant isolates, and, in contrary, for ethionamide, ethambutol, amikacin, kanamycin, and moxifloxacin the resistance-related mutations were identified in several phenotypically sensitive isolates.

Conclusions

WGS is a valuable tool for rapid genotypic DST for all anti-TB agents. For isoniazid and rifampicin phenotypic DST potentially can be replaced by genotypic DST based on 100% agreement between the tests. However, discrepant results for other anti-TB agents limit their prescription based solely on WGS data. For clinical decision, at the current level of knowledge, there is a need for combination of genotypic DST with modern, validated phenotypic DST methodologies for those medications which did not showed 100% agreement between the methods.

Peer Review reports

Tuberculosis (TB) remains a major public health problem and is still one of the main causes of death worldwide; in 2021, there were 1.6 million TB-related deaths [ 1 ]. Rifampicin and multidrug resistant tuberculosis (RR/MDR–TB) is a burden for healthcare system, mainly because the duration of treatment is longer than drug susceptible TB. The World Health Organization (WHO) reported that in 2021 there were 10.6 million people ill with TB, and 450,000 of them had RR/MDR–TB, which accounts to 3.6% of all new TB cases and 18% of the previously treated ones [ 1 ]. Drug susceptibility testing (DST) of Mycobacterium tuberculosis (Mtb) is crucial for clinicians to choose the most appropriate treatment for every individual TB patient, especially for MDR–TB cases. Phenotypic culture-based drug susceptibility tests have been the DST gold standard for a long time, but it takes several weeks or months to obtain the result; moreover, for some drugs, inappropriately high breakpoints have resulted in systematic false-susceptible DST results [ 2 , 3 ]. Molecular-based DST as line probe assays and the Xpert MTB/Rif assay are available in clinical laboratories and are widely used, however, these tests detect a limited number of gene mutations and do not show heteroresistance [ 2 , 4 ].

The advanced molecular drug resistance detection method is based on the whole genome sequencing (WGS), which theoretically can predict the resistance of Mtb isolates to all anti-TB agents through a single analysis [ 5 ]. Although the use of WGS analysis increases, its value is still limited due to incomplete databases which are used to prescribe predicted mutations for resistance of drugs, and due to lack of knowledge about all resistance-associated mutations [ 6 ]. Several databases have been developed recently specifically for analyzing Mtb WGS data, such as TB profiler, KvarQ, TGS-TB, CASTB, PhyResSe, MTBseq, and ReSeqTB-UVP [ 7 ]. Recently, based on systematic analysis of a large collection of Mtb isolates with WGS and phenotypic DST, WHO team has developed the high-quality, comprehensive catalogue of confidence-graded Mtb genetic markers [ 8 ]. For the isoniazid and rifampicin, WGS-based molecular drug resistance tests reach 91.3–97.5% sensitivity and 93.6–99.0% specificity [ 8 , 9 ]. On the other hand, according to the literature data, the genotype-phenotype correlation remains low for pyrazinamide, ethambutol, ethionamide, and fluoroquinolones [ 6 , 10 , 11 ]. Thus, simultaneous phenotypic and genotypic drug resistance analysis of Mtb isolates is of a great importance.

In Latvia, a Baltic state in Northern Europe, TB therapy is applied following the relevant WHO guidelines and according to the DST data of patient’s isolates. During the last decade, the total number of reported TB cases in the country had decreased. For example, in 2012 there were 880 TB cases (43 per 100,000), and 101 (11.5%) of them were RR/MDR–TB cases. But current situation is better: in 2021 only 261 TB cases (13.8 per 100,000) were reported, and 25 (9.6%) of them were MDR–TB [ 12 ]. Nevertheless, the proportion of MDR–TB cases in Latvia remains high, thus Mtb drug resistance studies are of a high importance. Here, we aimed to identify the level of concordance between the phenotypic DST data of Latvian MDR–TB isolates with the mutation profiles obtained by application of WGS analysis.

Materials and methods

Sample collection.

For this study, Mtb isolates were obtained from stock cultures of clinical isolates at the Riga East Clinical University Hospital, Centre of Tuberculosis and Lung Diseases of Latvia. Samples collected from 2012 to 2014 with confirmed phenotypic resistance to at least isoniazid and rifampicin were included. Second sample selection criterion was the availability of additional phenotypic DST data for, at least, ethambutol, amikacin, ofloxacin or levofloxacin, and pyrazinamide. One patient was represented with one isolate. The Mtb isolates and corresponding DNA samples were anonymized by code.

Phenotypic DST of anti-TB drugs was carried out based on WHO technical manual for DST of medicines used in the treatment of TB [ 13 , 14 ]. Phenotypic DST was performed using BACTEC MGIT 960 system (MGIT) and/or Lowenstein-Jensen (LJ) solid media for the following drugs: isoniazid, rifampicin, ethambutol, pyrazinamide, streptomycin, amikacin, kanamycin, capreomycin, ofloxacin, moxifloxacin, ethionamide, and linezolid. For this study, phenotypic data were critically reviewed to ensure matching the current WHO recommendations [ 14 ]. Kanamycin and capreomycin are no longer endorsed for TB treatment, however, they were included in the current study for historical interest and for additional interpretation of mutations that confer resistance to amikacin. Similarly, ofloxacin testing is no longer recommended; however, in our study, ofloxacin was tested in WHO-endorsed media at concentrations x (2.0 µg/ml MGIT and 4.0 µg/ml LJ) which are equivalent to testing levofloxacin at concentrations x/2 (1.0 µg/ml MGIT and 2.0 µg/ml LJ). For this reason, according to the WHO, phenotypic DST results for ofloxacin could be used to represent levofloxacin resistance [ 8 , 14 ].

Mycobacterium tuberculosis DNA samples, WGS and further sequencing data processing

Mtb isolate DNA was extracted using GenoLyse kit (Hain Lifescience, Germany) according to manufacturer’s protocol. All mycobacterial DNA samples were purified using Nucleomag magnetic beads (Macherey-Nagel, Netherlands) in ratio 1:2 prior to library preparation. DNA was eluted in 10 mM Tris buffer solution (pH = 8; AppliChem, Germany). Paired-end fragment libraries were prepared using the QIAseq FX DNA library kit (Qiagen, Germany), and sequenced on a MiSeq platform (Illumina, US). Reads of maximum 600 bp were produced.

Sequencing data were processed by using appropriate bioinformatics tools and pipelines. Bioinformatic operations were conducted on the Galaxy web platform [ 15 ]. The created pipeline was based on the one available at the Galaxy community hub [ 16 ]. The Trimmomatic tool (v0.38.0) was used for adapter sequences, low-quality ends (Phred quality score < 20), and sliding window trimming (average Phred quality score of 20 across the 10-base period), keeping sequences of at least 20 base pairs long. Outputs were mapped to the reference sequence using the snippy tool (v4.6.0). The genome of the inferred Mtb complex’s most recent common ancestor combined with the annotation of the H37Rv sequence (GenBank NC000962.3) was used as a reference [ 17 ]. Left aligning of indels was performed by BamLeftAlign (v1.3.6), while BAM filter (v0.5.9) was used to keep only properly paired mapped reads, and remove sequences marked as PCR duplicates. Generated BAM file was used as an input for the TB-Profiler tool (v4.1.1) which discriminated lineages and detected resistance associated mutations in studied isolates. Further, any detected changes in resistance-related genes were manually checked against the most recent WHO mutation catalogue data (WHO, 2021). Only mutations with allele frequency ≥ 10% supported by at least four sequencing reads were called. Mutation grading was applied based on WHO mutation catalogue data [ 8 ]. Genotyping DST result was assumed to be “Resistant” if group 1 “Associated with resistance”, group 2 “Associated with resistance, interim” or group 3 “Uncertain significance” mutations were detected. Genotyping DST result was assumed to be “Sensitive” if group 4 “Not associated with resistance, interim”, group 5 “Not associated with resistance”, or non-graded mutations were detected.

Additional amplification of Mtb pncA gene was performed to confirm indels detected by WGS. Polymerase chain reaction (PCR) was conducted based on previously published protocol [ 18 ]. Forward 5′-AACAGTTCATCCCGGTTC-3′ and reverse 5′-GCGTCATGGACCCTATATC-3′ primers targeting the whole gene (product length – 668 bp) were used. The PCR mixture (26 µL) was prepared as follows: 13 µL of 2x DreamTaq PCR Master Mix (Thermo Fisher Scientific, US), 0.2 µM of each primer, adding 2 µL of DNA template. Thermal cycling conditions were 95 °C for 3 min followed by 35 cycles of 30 s at 95 °C, 30 s at 58 °C, 1 min at 72 °C, and a final extension of 72 °C for 5 min. PCR product was visualized on 1.5% agarose gel (TopVision Agarose, Thermo Fisher Scientific, US). Sanger sequencing of positive amplicons was performed using BrilliantDye Terminator (v3.1) Cycle Sequencing Kit (NimaGen, Netherlands) on ABI Prism 3100 Genetic Analyzer (PerkinElmer, USA).

Genotyping analysis of drug resistant isolates

In total, 63 Mtb isolates were obtained, representing approximately 1/3 of the total number of MDR–TB cases in Latvia in the study period (63/230 cases, 27.4%, years 2012–2014). Among them, five different sublineages were detected (Table 1 ). According to the WGS-based data, more than a half of all MDR–TB samples belonged to the sublineage 2.2.1 (Beijing group, 34/63, 54.0%). The second most abundant sublineage was 4.3.3 (Latin American-Mediterranean (LAM) group, 23/63, 36.5%). Other sublineages were detected in much lower proportions: 4.2.1 (Ural) was detected in three cases (4.8%), 4.8 - in two cases (3.2%), and 4.3.3/4.2.1 sublineage was represented by only one isolate (1.6%).

Phenotypic drug resistance

Phenotypic resistance data were available for 12 anti-TB medications, however, not all Mtb isolates were tested for all drugs, and two methods (LJ media and MGIT) were used interchangeably (Table 1 ; Supplementary Table 1). According to the phenotypic DST, in addition to isoniazid and rifampicin, MDR Mtb isolates were resistant to streptomycin (95.4%), ethambutol (85.7%), amikacin (38.1%), kanamycin (36.6%), capreomycin (55.6%), ofloxacin (25.4%), moxifloxacin (16.7%), pyrazinamide (84.1%), and ethionamide (35.9%). Resistance to linezolid was tested in 11 isolates; the results showed that all of them were linezolid-susceptible.

Detection of resistance-associated genetic variants (RAVs)

All drug resistance-associated genetic variants (RAVs), which were identified in this study, are summarized in the Supplementary Table 2. Both phenotypic DST and genotypic DST data, as well as the analysis of the relationship between genotypic and phenotypic drug resistance profiles, are provided in Table 1 ; Fig. 1 , as well as in Supplementary Tables 1 and 2.

Concordance of the phenotypic and whole genome sequencing-based genotypic drug susceptibility testing results of the multidrug resistant M. tuberculosis isolates. Number of tested isolates for each drug is indicated. Abbreviations: INH, isoniazid; STM, streptomycin; RIF, rifampicin; ETO, ethambutol; AMK, amikacin; KAN, kanamycin; CAP, capreomycin; OFX, ofloxacin; PZA, pyrazinamide; ETO, ethionamide; LZD, linezolide

Isoniazid, rifampicin, ethionamide

High confidence group 1 RAVs in katG and rpoB genes, which were linked to resistance to isoniazid and rifampicin, respectively, were detected in all 63 isolates, thus the correlation of phenotypic/genotypic resistance data for both medications was 100%. In rpoB gene, nine different RAVs in five genomic positions were detected; in four lineage 2.2.1 isolates two different rpoB RAVs were detected simultaneously, and in two lineage 2.2.1 isolates RAV in rpoB gene was accompanied by a mutation in rpoC gene.

In contrary, all studied Mtb isolates harbored a single katG p.Ser315Thr RAV which determined the resistance to isoniazid. On the other hand, fabG1 c. -15 C > T, inhA gene promoter RAV (group 1 mutation), which has been attributed to the resistance to both isoniazid and ethionamide, was detected in 38 (60.3%) of MDR–TB isolates; among them, 13 were phenotypically-resistant to ethionamide, 8 were ethionamide-sensitive, and the phenotypic DST data for 17 MDR–TB isolates were not available. Also, fabG1 c.-17G > T RAV (group 3 mutation) was detected in two Mtb isolates; one was phenotypically ethionamide-sensitive, the status of the second one was unknown.

RAVs in ethA gene, which previously have also been linked to ethionamide resistance, were detected in 25 (39.7%) isolates; among them, 4 were phenotypically-resistant to ethionamide, 10 were ethionamide-sensitive, and the resistance status of 11 MDR–TB isolates was unknown. Seven different RAVs in ethA gene were observed, while ethA p.Ile338Ser was detected solely in 4.4.3 isolates. Two RAVs, namely ethA c.110-111insA and c.1290del, which are currently not included in WHO confidence grading mutation list, were detected along fabG1 c.-15 C > T group 1 mutation in four and one isolate, respectively. All five isolates belonged to the 2.2.1 sublineage; three were ethionamide-resistant, one – ethionamide-sensitive, and phenotypic DST data were not available for the fifth isolate. Overall, for ethionamide, phenotypic/genotypic data were poorly correlated, as the match was observed for 56.4% of the phenotypically-tested MDR–TB isolates.

RAVs in embB gene, which were linked to resistance to ethambutol, were detected in 61 (96.8%) isolates; overall, ten different RAVs in eight genome positions were observed. In four Mtb isolates two different RAVs occurred simultaneously; all four isolates were phenotypically-resistant. Among the phenotypically-sensitive isolates, ethambutol-related RAVs were detected in eight cases; six isolates harbored group 1 mutations in the e mbB gene, and two isolates – group 3 mutation. In contrary, none ethambutol-related RAVs were detected in one phenotypically-resistant 2.2.1 Mtb isolate; the resistance was confirmed using both LJ media (2 µg/ml) and MGIT (5.0 µg/ml) methods.

Discrepancies between phenotypic LJ and MGIT ethambutol DST data were observed in 4 isolates; in all cases, high confidence resistance-associated group 1 mutation was detected, namely p.Met306Ile, p.Met306Val and p.Gln497Arg (2 cases). The overall concordance between phenotypic/genotypic data for ethambutol resistance was 85.7%. RAV embA c.-43G > C, which is currently graded by WHO as “uncertain significance” (group 3), was present in nine 2.2.1 Mtb isolates; seven were phenotypically ethambutol-resistant, and two – phenotypically sensitive; therefore, a clear conclusion regarding the effect of this mutation could not be drawn. Two additional group 3 mutations, namely, p.Asp1024Asn and p.Asn296His, were detected in four isolates; however, in all cases additional group 1 mutation was present and all four isolates were phenotypically-resistant.

Pyrazinamide

RAVs in pncA gene, which were linked to resistance to pyrazinamide, were detected in 53 (84.1%) Mtb isolates. Overall, 20 different RAVs were observed; among them, ten were group 1, seven were group 2, one – group 3 mutation, and two RAVs were not graded in the current WHO resistance mutation list. Overall, in three phenotypically-resistant cases, WHO-classified mutations were not detected; however, two of these isolates harbored non-graded insertion/deletion mutations in pncA gene (namely, pncA c.157-158insCGATG and c.69-74del). In contrary, only in one case, group 1 mutation ( pncA p.Ser59Pro) was detected in phenotypically-sensitive Mtb isolate. The overall concordance between phenotypic/genotypic data for pyrazinamide resistance was 93.7%.

Streptomycin

Overall, streptomycin resistance-related rrs and rpsL RAVs were detected in 60 (95.2) of Mtb isolates. Among them, rpsL p.Lys43Arg was observed exclusively in sublineage 2.2.1 isolates (N = 34), and rrs r.514a > c – in Mtb isolates belonged to sublineages 4.3.3 (N = 23) and 4.2.1 (N = 2). Only in one case, no RAVs were detected in phenotypically-resistant Mtb isolate (sublineage 4.8), while in a single case rpsL p.Lys43Arg RAV was detected in phenotypically-sensitive 2.2.1 isolate. Thus, the overall concordance between phenotypic/genotypic data for streptomycin resistance in our study reached 95.4%.

Amikacin, Kanamycin, Capreomycin

According to the phenotypic DST data, 24/63 (38.1%), 15/41 (36.6%) and 35/63 (55.6%) isolates were resistant to amikacin, kanamycin and capreomycin, respectively (Table 1 ). The overall match between phenotypic/genotypic data for amikacin, kanamycin and capreomycin was 82.5%, 85.4% and 81.0%, respectively. The r.1401a > g RAV in rrs gene, which was previously linked to amikacin, kanamycin and capreomycin resistance, was detected in 23 (36.5%) isolates; the available phenotypic DST results confirmed phenotypic resistance to the aminoglycosides in all cases.

On the other hand, three different RAVs in eis gene (namely, c.-10G > A, c.-14 C > T and c.-37G > T), which were linked to amikacin and/or kanamycin resistance, were detected in 12 (19.1%) Mtb isolates; all of the isolates belonged to the sublineage 2.2.1. However, according to the phenotypic DST data, the vast majority of these samples were phenotypically-sensitive to kanamycin (6 of 8) and amikacin (11 of 12). Moreover, in one kanamycin- and amikacin-sensitive isolate two eis gene mutations (c.-14 C > T and c.-37G > T) were detected simultaneously. Similarly, the ambiguity between phenotypic/genotypic DST results for capreomycin were observed: in 12 phenotypically capreomycin-resistant isolates no resistance-related RAVs were detected; all but one these isolates were phenotypically sensitive to amikacin or both amikacin and kanamycin.

Fluoroquinolones

Based on the phenotypic DST data, ofloxacin resistance was detected in 16/63 (25.4%) isolates, while 3/18 (16.7%) isolates were moxifloxacin-resistant; all fluoroquinolone-resistant isolates belonged to either 2.2.1. or 4.3.3. sublineages. Discordance in the phenotypic DST results between the two fluoroquinolones were observed in five isolates; all were ofloxacin-resistant and moxifloxacin-sensitive.

Overall, in this study, phenotypic DST results did not absolutely correlate with the occurrence of RAVs; the overall match between phenotypic/genotypic data for ofloxacin was 93.7%, and for moxifloxacin − 77.8%. No fluoroquinolone-related RAVs were found in two ofloxacin-resistant isolates. Fluoroquinolone-related RAVs were detected in 16 (25.4%) isolates; all but one occurred in gyrA gene, and five different RAVs in four genome positions were observed; all detected gyrA RAVs belonged to the group 1 mutations. Among them, gyrA p.Ala90Val RAV was detected in one ofloxacin-sensitive and six ofloxacin-resistant isolates; four of these isolates with available moxifloxacin phenotypic DST data were moxifloxacin-sensitive.

In our study, no linezolid-resistant Mtb isolates were detected neither by phenotypic, nor genotypic analysis, thus the correlation of phenotypic/genotypic resistance data for this medication was 100%.

Confirmation of insertion/deletion mutations in pncA gene

In our study, WGS analysis revealed insertion/deletion mutations in pncA gene. Sanger sequencing analysis was applied to the four isolates in question (harboring mutations pncA c.157-158insCGATG and c.380-388del) to rule out the possible sequencing errors. Sanger sequencing results confirmed the presence of mutations in all four isolates (Fig. 2 ).

Visual representation of Sanger sequencing analysis of pncA gene fragments. The chromatograms presenting insertion/deletion mutations in four M. tuberculosis isolates are shown. A: c.157-158insCGATG was detected in one isolate. B: c.380-388del. was detected in three isolates

This is the first study presenting the results of comparison of the phenotypic and WGS-based genotypic DST results for MDR Mtb isolates in Latvia. Sublineages 2.2.1 and 4.3.3 were the most abundant among drug resistant isolates in our study. This is consistent with the previous study demonstrating that Beijing genotype is common in Latvia, and both Beijing and LAM Mtb isolates were associated with drug resistance more often than other genotypes [ 19 ]. Indeed, Beijing lineage strains are globally distributed and are associated with the spread of MDR–TB in Eurasia [ 20 ]. The Beijing lineage has highest prevalence in Asia and Europe, especially in Eastern European countries including Czech Republic, Moldova, Russia, and Ukraine [ 20 , 21 , 22 , 23 , 24 ]. The fact that Beijing strains are the main carriers of MDR–TB and extensively drug-resistant TB in Eastern Europe and Central Asia, and can lead to the occurrence of several serious outbreaks in close geographical areas [ 25 ], allows to predict MDR–TB spread in Europe due to increased migration of population. Moreover, surge of TB, along with HIV and COVID-19 feared amid war in Ukraine leading to a regional crisis [ 26 ].

There were 100% agreement between phenotypic and WGS - based genotypic DST results for isoniazid, rifampicin and linezolid in our study (Fig. 1 ; Table 1 ). Similarly, high concordance between both testing approaches has been demonstrated for isoniazid and rifampicin in other studies [ 27 , 28 , 29 , 30 ]. These observations potentially allow the replacement of phenotypic DST with WGS analysis for both medications. Regarding linezolid, there are known mutations in rplC and rrl genes which were associated with the resistance [ 31 , 32 ]. However, we did not identify any linezolid-resistant Mtb isolates, thus, in this study, the clinically-sound conclusions regarding the interchangeability of phenotypic DST and WGS for linezolid could not be drawn.

Phenotypic and genotypic concordance above 90% was obtained for streptomycin (95.4%), ofloxacin (93.7%) and pyrazinamide (93.7%) (Table 1 ; Fig. 1 ). For the other six medications, i.e. ethionamide, ethambutol, moxifloxacin, amikacin, kanamycin, and capreomycin, the phenotypic DST and WGS-based drug susceptibility patterns were poorly correlated as the observed concordance between the methods ranged from 56.4 to 85.7%.

The overall concordance of phenotypic and genotypic DST results for ethambutol was 85.7% However, the variability in the agreement among different spoligotypes was observed ranging from 85.3 to 100%; the lowest value was obtained for the sublineage 2.2.1. Inconsistent results of the phenotypic and genotypic DST agreement for ethambutol were also reported in other studies, ranging from 40% up to 94.6% [ 27 , 29 , 30 ]. RAVs in embB gene were identified in 61 (96.8%) of the studied isolates, however, eight (13.1%) of them were phenotypically sensitive (Table 1 ; Fig. 1 ). The most common mutation among the isolates with discrepant results occurred at the embB gene position 306 (four cases, including p.Met306Val, p.Met306Ile and p.Met306Leu), while in two other cases – at the embB gene position 497 (p.Gln497Arg). All these mutations have been graded as high confident resistance-related (group 1), thus it could be assumed that all six Mtb isolates were ethambutol-resistant [ 8 , 33 , 34 ]. This fact could be potentially related to the critical concentration (CC) of ethambutol used for the phenotypic DST, because many embB mutations confer minimum inhibitory concentrations (MICs) close to the CC, resulting in poor agreement between genotypic and phenotypic DST [ 30 , 35 ]. In contrary, none currently known ethambutol resistance-related RAVs were detected in a single phenotypically-resistant isolate (Table 1 ; Fig. 1 ), and the majority of isolates harbouring solely group 3 mutation embA c.-43G > C (7/9, 77.8%) were phenotypically-resistant. The discrepant results betwen phenotypic and genotypic DST for ethambutol deserve further investigation including studies on the correlation with treatment outcome.

Phenotypic DST and WGS data poorly correlated for ethionamide in our study; the concordant results were obtained only for approximately half of Mtb isolates for which both phenotypic and genotypic data were available (56.4%). For this medication the resistance rate detected by WGS was significantly higher compared to the phenotypic testing using LJ media (i.e. 84.1% vs. 35.9%); in contrary, the study of Faksri and colleagues reported moderate concordance rates (81.37%) mainly due to isolates that were phenotypically resistant on Middlebrook 7H10 agar plates but WGS-based susceptible [ 6 ]. In our study the discrepant results were observed for 17 phenotypically-sensitive MDR Mtb isolates where genotypic DST ethionamide resistance status was assigned based on the detection of a wide variety of resistance-associated mutations in fabG1 and/or ethA genes. In ten phenotypically-sensitive cases (58.8%), group 1 mutations ( fabG1 c.-15 C > T (n = 8) and ethA c.110del (n = 2)) were detected; moreover, in one case fabG1 c.-15 C > T coincided with the group 3 mutation ( ethA p.Ile338Ser). In six cases (35.3%) group 2 mutation was detected ( ethA c.1029del (n = 5), ethA c.768del (n = 1)), and the group 3 mutation ( fabG1 c.-17G > T) was detected in one case. These results could be explained by the fact that many ethionamide resistance mutations confer only modest increases in MIC [ 36 ]. These results suggest that, currently, mutation test results should be carefully evaluated, because ethA and fabG1 mutant strains could still be sensitive to ethionamide and may be effective for ethionamide treatment. This finding is in line with a study by Song and colleagues [ 37 ].

Phenotypic and genotypic DST results concordance for pyrazinamide reached 93.7% in our study, which is similar to the other reported results where the match for 91 − 93.8% of cases was observed [ 21 , 27 ]. Phenotypic pyrazinamide resistance of our MDR–TB isolates was slightly higher compared to that predicted by WGS (84.1% vs. 80.9%, respectively), because in several isolates no WHO-graded mutations were observed. On the other hand, in one phenotypically-sensitive isolate a high confidence RAV in the pncA gene was detected. This observation could be explained by well documented complexity and challenges associated with pyrazinamide in vitro susceptibility testing leading to either false-positive or false-negative results [ 38 ]. For pyrazinamide resistance detection WHO recommended genotypic DST assay includes mutation analysis solely in pncA gene, however, there are other RAVs reported in genes such as panD and rpsA [ 39 , 40 , 41 ]. Currently, several pyrazinamide resistance-related genes are included in Mtb databases used for WGS data analysis; nevertheless, in our study, only RAVs in the pncA gene were detected including 9-nucleotide deletion mutation (c.380-388del) in three isolates. In addition, two different, currently WHO non-graded insertion/deletion mutations ( pncA c.69-74del and c.157-158insCGATG) were observed in two phenotypically-resistant isolates (one isolate each).

For injectables variable concordance results for phenotypic and genotypic DST were identified, being high for streptomycin (95.4%), and considerably lower for amikacin (82.5%), kanamycin (85.4%), and capreomycin (81.0%). In contrary, in other studies, a full concordance between phenotypic and genotypic DST results for amikacin was reported [ 11 , 30 ]. Here, all Mtb isolates which had the r.1401a > g RAV in rrs gene were characterized as phenotypically cross-resistant either to amikacin and capreomycin, or amikacin, kanamycin and capreomycin; this observation is in agreement with other studies [ 6 , 9 , 42 ]. Overall, the r.1401a > g RAV in rrs gene was detected in 23/63 (36.5%) of our isolates. The discordant results for amikacin and kanamycin were mostly because the presence of the mutations in the eis gene in phenotypically-sensitive isolates. For example, among 11 isolates harboring solely amikacin group 3 eis gene mutations (namely, eis c.-10G > A, n = 9; eis c.-37G > T, n = 2) only one isolate was phenotypically amikacin-resistant. On the other hand, the same RAVs have been reported as a group 1 mutations for kanamycin; however, in our eight isolates with available phenotypic DST data, only two were kanamycin-resistant. Indeed, up-regulation of eis gene due to the promoter mutations has been shown to confer a low-level kanamycin resistance, and, to a lesser extent, increased amikacin MIC [ 43 , 44 ]. In addition, one amikacin and kanamycin phenotypically-sensitive isolate had both eis c.-14 C > T and c.-37G > T mutations. Recently, the study by Vargas and colleagues demonstrated that the eis C-14T promoter mutation cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function mutations in the coding region of eis [ 45 ]. However, whether the interaction of different eis promoter mutations may result in drug susceptibility remains to be deciphered. In contrary, for capreomycin, all discordant isolates were resistant according to the phenotypic testing, but drug-sensitive according to the WGS data.

Our results showed that there was also a high correlation for streptomycin (95.4%) between phenotypic and WGS-based data. However, some studies reported a moderate agreement for streptomycin between both methods [ 2 , 46 ]. In our study, all streptomycin-resistant sublineage 2.2.1 isolates had a single rpsL gene mutation p.Lys43Arg; in contrary, all but one streptomycin-resistant Mtb isolates of other sublineages harbored r.514a > c RAV in rrs gene, while p.Lys88Arg RAV in rpsL gene was detected in the single sublineage 4.2.1 isolate.

Overall match between phenotypic DST and WGS-based genotypic DST results for ofloxacin was 93.7% in this study; a full concordance was reported in other studies [ 11 , 30 ]. All ofloxacin/fluoroquinolones-resistant strains belonged to sublineages 2.2.1 and 4.3.3. Two 2.2.1 Mtb isolates were ofloxacin-sensitive according to the phenotypic DST data, while no specific RAVs were detected; however, one of these isolates was moxifloxacin-sensitive based on phenotypic DST results. Another phenotypic/genotypic discordance case could be explained by the presence of a group 3 mutation ( gyrB Arg446His, uncertain significance), which was detected in the ofloxacin-sensitive sublineage 4.3.3 isolate. In the fourth discordant case, gyrA Ala90Val RAV was detected in ofloxacin-sensitive isolate; for this mutation MIC equal to the CC have been reported, thus methodological variation in MIC testing likely accounted for these results [ 8 , 14 ]. It is usually assumed that all detected RAVs in gyrA and gyrB genes provide Mtb cross-resistance against several fluoroquinolones, however, in our study, some discordant results were obtained. According to the phenotypic DST data, four Mtb isolates were ofloxacin-resistant and moxifloxacin-sensitive; in all these cases gyrA Ala90Val RAV was detected. These results were also the main reason for lower phenotypic/genotypic data match for moxifloxacin. Additional MIC data are required to decipher if the observed mutation was associated with high or low MIC to moxifloxacin.

Our study has several limitations. First, the study period included years 2012–2014. The reason for the chosen study period was the availability of high quality stock cultures of MDR–TB isolates which were thoroughly tested for the phenotypic resistance against 12 anti-TB medications. While not all 63 Mtb isolates were tested for all drugs, phenotypic resistance data for isoniazid, rifampicin, ethambutol, amikacin, capreomycin, ofloxacin, and pyrazinamide were available for all samples. It should be also noted that since 2021 the laboratory of Centre of Tuberculosis and Lung Diseases of Latvia is using Xpert MTB/XDR which allows fast molecular DST for isoniazid, ethionamide, amikacin, kanamycin, capreomycin, and fluoroquinolones. For rifampicin, Xpert/Rif Ultra is used, while bedaquiline, linezolid, delamanid, clofazimine are tested using the BACTEC MGIT solution. However, for studied isolates, bedaquiline, clofazimine and delamanid resistance data were not available and thus were not included in study, and the linezolid-resistant isolates were lacking. However, this study represents a comprehensive analysis of both phenotypic and WGS-based MDR–TB resistance data which are highly relevant not only for our country, but also for other countries with a high burden of MDR–TB.

In conclusion, the results obtained in this study highlight WGS as a valuable tool for prediction of drug resistance in Mtb isolates. However, the observed discordance between phenotypic DST and WGS data for several medications requires further investigation to identify all resistance conferring gene mutations and correlate them with modern, MIC-based phenotypic DST results and treatment outcome. The endemic presence of Mtb Beijing and LAM genotypes associated with drug resistance, as well as the variability of circulating resistance-associated genetic variants, indicates the need to maintain MDR–TB strain data collection, and to continue MDR–TB studies in Latvia. Currently, for clinical decision, the discrepant results for several anti-TB agents limit their prescription based solely on WGS data, while challenges associated with phenotypic DST, especially on LJ solid media, could lead to either false-positive or false-negative results. Thus, for these medications, a combination of genotypic DST with modern, validated phenotypic DST methodologies is required for accurate detection of drug resistance.

Data availability

The raw sequencing reads obtained in the study were deposited in European Nucleotide Archive (ENA) under the project accession number PRJEB59824.

Abbreviations

critical concentration

minimal inhibitory concentration

tuberculosis

multidrug resistant tuberculosis

M. tuberculosis

drug susceptibility testing

World Health Organization

whole genome sequencing

Global tuberculosis report 2022. Licence: CC BY-NC-SA 3.0 IGO. Geneva: World Health Organization; 2022.

Google Scholar

Ko DH, Lee EJ, Lee SK, Kim HS, Shin SY, Hyun J, Kim JS, Song W, Kim HS. Application of next-generation sequencing to detect variants of drug-resistant Mycobacterium tuberculosis: genotype-phenotype correlation. Ann Clin Microbiol Antimicrob. 2019;18(1):2. https://doi.org/10.1186/s12941-018-0300-y .

Article PubMed PubMed Central Google Scholar

Antimycobacterial Susceptibility Testing Group. Updating the approaches to define susceptibility and resistance to anti-tuberculosis agents: implications for diagnosis and treatment. Eur Respir J. 2022;59(4):2200166. https://doi.org/10.1183/13993003.00166-2022 .

Article CAS Google Scholar

Walker TM, Kohl TA, Omar SV, Hedge J, Del Ojo Elias C, Bradley P, Iqbal Z, Feuerriegel S, Niehaus KE, Wilson DJ, Clifton DA, Kapatai G, Ip CLC, Bowden R, Drobniewski FA, Allix-Béguec C, Gaudin C, Parkhill J, Diel R, Supply P, Crook DW, Smith EG, Walker AS, Ismail N, Niemann S, Peto TEA. Modernizing Medical Microbiology (MMM) Informatics Group. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect Dis. 2015;15(10):1193–202. https://doi.org/10.1016/S1473-3099(15)00062-6 .

Article CAS PubMed PubMed Central Google Scholar

Sun L, Zhang L, Wang T, Jiao W, Li Q, Yin Q, Li J, Qi H, Xu F, Shen C, Xiao J, Liu S, Mokrousov I, Huang H, Shen A. Mutations of Mycobacterium tuberculosis induced by anti-tuberculosis treatment result in metabolism changes and elevation of ethambutol resistance. Infect Genet Evol. 2019;72:151–8. https://doi.org/10.1016/j.meegid.2018.09.027 .

Article CAS PubMed Google Scholar

Faksri K, Kaewprasert O, Ong RT, Suriyaphol P, Prammananan T, Teo YY, Srilohasin P, Chaiprasert A. Comparisons of whole-genome sequencing and phenotypic drug susceptibility testing for Mycobacterium tuberculosis causing MDR-TB and XDR-TB in Thailand. Int J Antimicrob Agents. 2019;54(2):109–16.

Yang T, Gan M, Liu Q, Liang W, Tang Q, Luo G, Zuo T, Guo Y, Hong C, Qibing Li Q, Tan W, Gao Q. SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission. Brief Bioinform. 2022;23(2):bbac030.

Catalogue of mutations in. Mycobacterium tuberculosis complex and their association with drug resistance. Geneva: World Health Organization; 2021. Licence: CC BY-NC-SA 3.0 IGO.

The CRyPTIC Consortium. Genome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms. PLoS Biol. 2022;20(8):e3001755. https://doi.org/10.1371/journal.pbio.3001755 .

Article CAS PubMed Central Google Scholar

Sun W, Gui X, Wu Z, Zhang Y, Yan L. Prediction of drug resistance profile of multidrug-resistant Mycobacterium tuberculosis (MDR-MTB) isolates from newly diagnosed case by whole genome sequencing (WGS): a study from a high tuberculosis burden country. BMC Infect Dis. 2022;22(1):499. https://doi.org/10.1186/s12879-022-07482-4 .

Yordanova S, Bachiyska E, Tagliani E, Baykova A, Atanasova Y, Spitaleri A, Cirillo DM. Whole genome sequencing of bulgarian rifampicin resistant Mycobacterium tuberculosis strains. Folia Med (Plovdiv). 2022;64(4):633–40. https://doi.org/10.3897/folmed.64.e70554 .

Centre for Disease Prevention and Control of Latvia. https://www.spkc.gov.lv/lv . Assessed 10 january 2023.

World Health Organisation. Policy guidance on drug-susceptibility testing (DST) of second-line antituberculosis drugs. Geneva: World Health Organization; 2008.

World Health Organisation. Technical Report on critical concentrations for drug susceptibility testing of medicines used in the treatment of drug-resistant tuberculosis. Geneva: World Health Organization; 2018.

Afgan E, Baker D, Batut B, van den Beek M, Bouvier D, et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res. 2018;46(W1):W537–44. https://doi.org/10.1093/nar/gky379 .

van Heusden P, Gladman S, Lose TM. tuberculosis Variant Analysis (Galaxy Training Materials). Available from: https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/tb-variant-analysis/tutorial.html .

Comas Ĩ, Chakravartti J, Small PM, Galagan J, Niemann S, et al. Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat Genet. 2010;42(6):498–503. https://doi.org/10.1038/ng.590 .

Pang Y, Zhu D, Zheng H, Shen J, Hu Y, Liu J, Zhao Y. Prevalence and molecular characterization of pyrazinamide resistance among multidrug-resistant Mycobacterium tuberculosis isolates from Southern China. BMC Infect Dis. 2017;17:711. https://doi.org/10.1186/s12879-017-2761-6 .

Pole I, Trofimova J, Norvaisa I, Supply P, Skenders G, Nodieva A, Ozere I, Riekstina V, Igumnova V, Storozenko J, Jansone I, Viksna L, Ranka R. Analysis of Mycobacterium tuberculosis genetic lineages circulating in Riga and Riga region, Latvia, isolated between 2008 and 2012. Infect Genet Evol. 2020;78:104126. https://doi.org/10.1016/j.meegid.2019.104126 .

Merker M, Blin C, Mona S, Duforet-Frebourg N, Lecher S, Willery E, Blum MG, Rüsch-Gerdes S, Mokrousov I, Aleksic E, Allix-Béguec C, Antierens A, Augustynowicz-Kopeć E, Ballif M, Barletta F, Beck HP, Barry CE 3rd, Bonnet M, Borroni E, Campos-Herrero I, Cirillo D, Cox H, Crowe S, Crudu V, Diel R, Drobniewski F, Fauville-Dufaux M, Gagneux S, Ghebremichael S, Hanekom M, Hoffner S, Jiao WW, Kalon S, Kohl TA, Kontsevaya I, Lillebæk T, Maeda S, Nikolayevskyy V, Rasmussen M, Rastogi N, Samper S, Sanchez-Padilla E, Savic B, Shamputa IC, Shen A, Sng LH, Stakenas P, Toit K, Varaine F, Vukovic D, Wahl C, Warren R, Supply P, Niemann S, Wirth T. Evolutionary history and global spread of the Mycobacterium tuberculosis Beijing lineage. Nat Genet. 2015;47(3):242–9. https://doi.org/10.1038/ng.3195 .

Dohál M, Dvořáková V, Šperková M, Pinková M, Spitaleri A, Norman A, Cabibbe AM, Rasmussen EM, Porvazník I, Škereňová M, Solovič I, Cirillo DM, Mokrý J. Whole genome sequencing of multidrug-resistant Mycobacterium tuberculosis isolates collected in the Czech Republic, 2005–2020. Sci Rep. 2022;12(1):7149. https://doi.org/10.1038/s41598-022-11287-5 .

Lagutkin D, Panova A, Vinokurov A, Gracheva A, Samoilova A, Vasilyeva I. Genome-wide study of drug resistant Mycobacterium tuberculosis and its Intra-Host evolution during treatment. Microorganisms. 2022;10(7):1440. https://doi.org/10.3390/microorganisms10071440 .

Yang C, Sobkowiak B, Naidu V, Codreanu A, Ciobanu N, Gunasekera KS, Chitwood MH, Alexandru S, Bivol S, Russi M, Havumaki J, Cudahy P, Fosburgh H, Allender CJ, Centner H, Engelthaler DM, Menzies NA, Warren JL, Crudu V, Colijn C, Cohen T. Phylogeography and transmission of M. tuberculosis in Moldova: a prospective genomic analysis. PLoS Med. 2022;19(2):e1003933. https://doi.org/10.1371/journal.pmed.1003933 .

Merker M, Nikolaevskaya E, Kohl TA, Molina-Moya B, Pavlovska O, Brännberg P, Dudnyk A, Stokich V, Barilar I, Marynova I, Filipova T, Prat C, Sjöstedt A, Dominguez J, Rzhepishevska O, Niemann S. Multidrug- and extensively drug-resistant Mycobacterium tuberculosis Beijing Clades, Ukraine, 2015. Emerg Infect Dis. 2020;26(3):481–90. https://doi.org/10.3201/eid2603.190525 .

Keikha M, Majidzadeh M. Beijing genotype of Mycobacterium tuberculosis is associated with extensively drug-resistant tuberculosis: a global analysis. New Microbes New Infect. 2021;43:100921. https://doi.org/10.1016/j.nmni.2021.100921 .

Roberts L. Surge of HIV, tuberculosis and COVID feared amid war in Ukraine. Nature. 2022;603(7902):557–8.

CRyPTIC Consortium and the 100,000 Genomes Project, Allix-Béguec C, Arandjelovic I, Bi L, Beckert P, Bonnet M, Bradley P, Cabibbe AM, Cancino-Muñoz I, Caulfield MJ, Chaiprasert A, Cirillo DM, Clifton DA, Comas I, Crook DW, De Filippo MR, de Neeling H, Diel R, Drobniewski FA, Faksri K, Farhat MR, Fleming J, Fowler P, Fowler TA, Gao Q, Gardy J, Gascoyne-Binzi D, Gibertoni-Cruz AL, Gil-Brusola A, Golubchik T, Gonzalo X, Grandjean L, He G, Guthrie JL, Hoosdally S, Hunt M, Iqbal Z, Ismail N, Johnston J, Khanzada FM, Khor CC, Kohl TA, Kong C, Lipworth S, Liu Q, Maphalala G, Martinez E, Mathys V, Merker M, Miotto P, Mistry N, Moore DAJ, Murray M, Niemann S, Omar SV, Ong RT, Peto TEA, Posey JE, Prammananan T, Pym A, Rodrigues C, Rodrigues M, Rodwell T, Rossolini GM, Sánchez Padilla E, Schito M, Shen X, Shendure J, Sintchenko V, Sloutsky A, Smith EG, Snyder M, Soetaert K, Starks AM, Supply P, Suriyapol P, Tahseen S, Tang P, Teo YY, Thuong TNT, Thwaites G, Tortoli E, van Soolingen D, Walker AS, Walker TM, Wilcox M, Wilson DJ, Wyllie D, Yang Y, Zhang H, Zhao Y, Zhu B. Prediction of susceptibility to First-Line tuberculosis drugs by DNA sequencing. N Engl J Med. 2018;379(15):1403–15. https://doi.org/10.1056/NEJMoa1800474 .

Article Google Scholar

Liu W, Chen J, Shen Y, Jin J, Wu J, Sun F, Wu Y, Xie L, Zhang Y, Zhang W. Phenotypic and genotypic characterization of pyrazinamide resistance among multidrug-resistant Mycobacterium tuberculosis clinical isolates in Hangzhou, China. Clin Microbiol Infect. 2018;24(9):1016. https://doi.org/10.1016/j.cmi.2017.12.012 .

Liu D, Huang F, Zhang G, He W, Ou X, He P, Zhao B, Zhu B, Liu F, Li Z, Liu C, Xia H, Wang S, Zhou Y, Walker TM, Liu L, Crook DW, Zhao Y. Whole-genome sequencing for surveillance of tuberculosis drug resistance and determination of resistance level in China. Clin Microbiol Infect. 2022;28(5):731. .e9-731.e15.

Korhonen V, Kivelä P, Haanperä M, Soini H, Vasankari T. Multidrug-resistant tuberculosis in Finland: treatment outcome and the role of whole-genome sequencing. ERJ Open Res. 2022;8(4):00214–2022. https://doi.org/10.1183/23120541.00214-2022 .

Kabahita JM, Kabugo J, Kakooza F, Adam I, Guido O, Byabajungu H, Namutebi J, Namaganda MM, Lutaaya P, Otim J, Kakembo FE, Kanyerezi S, Nabisubi P, Sserwadda I, Kasule GW, Nakato H, Musisi K, Oola D, Joloba ML, Mboowa G. First report of whole-genome analysis of an extensively drug-resistant Mycobacterium tuberculosis clinical isolate with bedaquiline, linezolid and clofazimine resistance from Uganda. Antimicrob Resist Infect Control. 2022;11(1):68. https://doi.org/10.1186/s13756-022-01101-2 .

Zade A, Shah S, Hirani N, Kondabagil K, Joshi A, Chatterjee A. Whole-genome sequencing of presumptive MDR-TB isolates from a tertiary healthcare setting in Mumbai. J Glob Antimicrob Resist. 2022;31:256–62. https://doi.org/10.1016/j.jgar.2022.10.004 .

Andres S, Gröschel MI, Hillemann D, Merker M, Niemann S, Kranzer K. A diagnostic algorithm to investigate pyrazinamide and Ethambutol Resistance in Rifampin-Resistant Mycobacterium tuberculosis isolates in a low-incidence setting. Antimicrob Agents Chemother. 2019;63(2):e01798–18. https://doi.org/10.1128/AAC.01798-18 .

Plinke C, Cox HS, Zarkua N, Karimovich HA, Braker K, Diel R, Rüsch-Gerdes S, Feuerriegel S, Niemann S. embCAB sequence variation among ethambutol-resistant Mycobacterium tuberculosis isolates without embB306 mutation. J Antimicrob Chemother. 2010;65(7):1359–67. https://doi.org/10.1093/jac/dkq120 .

Gygli SM, Keller PM, Ballif M, Blöchliger N, Hömke R, Reinhard M, Loiseau C, Ritter C, Sander P, Borrell S, Collantes Loo J, Avihingsanon A, Gnokoro J, Yotebieng M, Egger M, Gagneux S, Böttger EC. Whole-genome sequencing for Drug Resistance Profile Prediction in Mycobacterium tuberculosis. Antimicrob Agents Chemother. 2019;63(4):e02175–18. https://doi.org/10.1128/AAC.02175-18 .

Nonghanphithak D, Kaewprasert O, Chaiyachat P, Reechaipichitkul W, Chaiprasert A, Faksri K. Whole-genome sequence analysis and comparisons between drug-resistance mutations and minimum inhibitory concentrations of Mycobacterium tuberculosis isolates causing M/XDR-TB. PLoS ONE. 2020;15:e0244829.

Song Y, Wang G, Li Q, Liu R, Ma L, Li Q, Gao M. The value of the inhA Mutation Detection in Predicting Ethionamide Resistance using melting curve technology. Infect Drug Resist. 2021;14:329–34. PMID: 33551644; PMCID: PMC7856099.

Zhang Y, Permar S, Sun Z. Conditions that may affect the results of susceptibility testing of Mycobacterium tuberculosis to pyrazinamide. J Med Microbiol. 2002;51(1):42–9. https://doi.org/10.1099/0022-1317-51-1-42 .

Lam C, Martinez E, Crighton T, Furlong C, Donnan E, Marais BJ, Sintchenko V. Value of routine whole genome sequencing for Mycobacterium tuberculosis drug resistance detection. Int J Infect Dis. 2021;113(Suppl 1):48–S54. https://doi.org/10.1016/j.ijid.2021.03.033 .

Whitfield MG, Engelthaler DM, Allender C, Folkerts M, Heupink TH, Limberis J, Warren RM, Van Rie A, Metcalfe JZ. Comparative performance of genomic methods for the detection of Pyrazinamide Resistance and Heteroresistance in Mycobacterium tuberculosis. J Clin Microbiol. 2022;60(1):e0190721. https://doi.org/10.1128/JCM.01907-21 .

Article PubMed Google Scholar

Rajendran A, Palaniyandi K. Mutations Associated with Pyrazinamide Resistance in Mycobacterium tuberculosis: a review and update. Curr Microbiol. 2022;79(11):348. https://doi.org/10.1007/s00284-022-03032-y .

Finci I, Albertini A, Merker M, Andres S, Bablishvili N, Barilar I, Cáceres T, Crudu V, Gotuzzo E, Hapeela N, Hoffmann H, Hoogland C, Kohl TA, Kranzer K, Mantsoki A, Maurer FP, Nicol MP, Noroc E, Plesnik S, Rodwell T, Ruhwald M, Savidge T, Salfinger M, Streicher E, Tukvadze N, Warren R, Zemanay W, Zurek A, Niemann S, Denkinger CM. Investigating resistance in clinical Mycobacterium tuberculosis complex isolates with genomic and phenotypic antimicrobial susceptibility testing: a multicentre observational study. Lancet Microbe. 2022;3(9):e672–82. https://doi.org/10.1016/S2666-5247(22)00116-1 .

Perdigão J, Macedo R, Silva C, Machado D, Couto I, Viveiros M, Jordao L, Portugal I. From multidrug-resistant to extensively drug-resistant tuberculosis in Lisbon, Portugal: the stepwise mode of resistance acquisition. J Antimicrob Chemother. 2013;68(1):27–33. https://doi.org/10.1093/jac/dks371 .

Zaunbrecher MA, Sikes RD, Metchock B, Shinick TM, Posey JE. Overexpression of the chromosomally encoded aminoglycoside acetyltransferase eis confers kanamycin resistance in Mycobacterium tuberculosis. Proc Natl Acad Sci USA. 2009;106(47):20004–9. https://doi.org/10.1073/pnas.0907925106 .

Vargas R Jr, Freschi L, Spitaleri A, Tahseen S, Barilar I, Niemann S, Miotto P, Cirillo DM, Köser CU, Farhat MR. Role of epistasis in Amikacin, Kanamycin, Bedaquiline, and Clofazimine Resistance in Mycobacterium tuberculosis Complex. Antimicrob Agents Chemother. 2021;65(11):e0116421. https://doi.org/10.1128/AAC.01164-21 .

Xiao YX, Liu KH, Lin WH, Chan TH, Jou R. Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan. Sci Rep. 2023;13:2540. https://doi.org/10.1038/s41598-023-29652-3 .

Download references

Acknowledgements

We thank Genome Centre, a core facility of Latvian Biomedical Research and Study Centre for its contribution to next-generation sequencing.

This study was funded by the European Regional Development Fund grant No.1.1.1.1/20/A/046. This funding source had no role in the design of this study, analyses, interpretation of the data, or decision to submit results.

Author information

Authors and affiliations.

Riga East Clinical University Hospital, Centre of Tuberculosis and Lung Diseases, Ropaži Municipality, Stopiņi Parish, Upeslejas, Latvia

Anda Vīksna, Iveta Berge, Ineta Bogdanova, Inga Norvaiša & Iveta Ozere

Rīga Stradiņš University, Riga, Latvia

Anda Vīksna & Iveta Ozere

Latvian Biomedical Research and Study Centre, Ratsupites Str. 1, Riga, LV-1067, Latvia

Darja Sadovska, Annija Vaivode, Lauma Freimane & Renāte Ranka

You can also search for this author in PubMed Google Scholar

Contributions

A.Vi., I.O., R.R.: Conceptualization, methodology, data curation; A.Vi., D.S., I.Be., I.Bo., A.Va., L.F., I.N.: data acquisition and analysis; D.S.: WGS methodology and software; A.Vi. wrote the main manuscript text and prepared Table 1; Fig. 1; D.S. prepared Fig. 2; I.O. and R.R. revised the main manuscript text. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Renāte Ranka .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary material 2, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Vīksna, A., Sadovska, D., Berge, I. et al. Genotypic and phenotypic comparison of drug resistance profiles of clinical multidrug-resistant Mycobacterium tuberculosis isolates using whole genome sequencing in Latvia. BMC Infect Dis 23 , 638 (2023). https://doi.org/10.1186/s12879-023-08629-7

Download citation

Received : 28 February 2023

Accepted : 19 September 2023

Published : 28 September 2023

DOI : https://doi.org/10.1186/s12879-023-08629-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Drug-resistant tuberculosis
Whole genome sequencing
Drug susceptibility testing

BMC Infectious Diseases

ISSN: 1471-2334

General enquiries: [email protected]

Open access
Published: 02 September 2024

Air pollution: a latent key driving force of dementia

Mahdiyeh Mohammadzadeh 1 , 2 ,
Amir Hossein Khoshakhlagh ORCID: orcid.org/0000-0002-2265-5054 3 &
Jordan Grafman 4

BMC Public Health volume 24 , Article number: 2370 ( 2024 ) Cite this article

22 Altmetric

Metrics details

Many researchers have studied the role of air pollutants on cognitive function, changes in brain structure, and occurrence of dementia. Due to the wide range of studies and often contradictory results, the present systematic review was conducted to try and clarify the relationship between air pollutants and dementia. To identify studies for this review, a systematic search was conducted in Scopus, PubMed, and Web of Science databases (without historical restrictions) until May 22, 2023. The PECO statement was created to clarify the research question, and articles that did not meet the criteria of this statement were excluded. In this review, animal studies, laboratory studies, books, review articles, conference papers and letters to the editors were avoided. Also, studies focused on the effect of air pollutants on cellular and biochemical changes (without investigating dementia) were also excluded. A quality assessment was done according to the type of design of each article, using the checklist developed by the Joanna Briggs Institute (JBI). Finally, selected studies were reviewed and discussed in terms of Alzheimer's dementia and non-Alzheimer's dementia. We identified 14,924 articles through a systematic search in databases, and after comprehensive reviews, 53 articles were found to be eligible for inclusion in the current systematic review. The results showed that chronic exposure to higher levels of air pollutants was associated with adverse effects on cognitive abilities and the presence of dementia. Studies strongly supported the negative effects of PM 2.5 and then NO 2 on the brain and the development of neurodegenerative disorders in old age. Because the onset of brain structural changes due to dementia begins decades before the onset of disease symptoms, and that exposure to air pollution is considered a modifiable risk factor, taking preventive measures to reduce air pollution and introducing behavioral interventions to reduce people's exposure to pollutants is advisable.

Peer Review reports

Introduction

Technological development and the rapid expansion of mechanization during the last few decades have led to an increase in life expectancy in various societies, especially in developed countries [ 1 ]. An increase in the life expectancy can lead to the growth of neurological disorders [ 2 ]. According to statistics published worldwide, neurological disorders, including Parkinson's (PD), cognitive dysfunction, Alzheimer's (AD) and dementia, are a leading cause of disability and death [ 3 , 4 ]. Cognitive function also diminishes with age [ 5 ] and therefore, elderly people are disproportionately affected by cognitive disorders and, finally, dementia [ 6 , 7 ] which imposes a significant burden on health care systems. According to statistics published by the World Health Organization (WHO), approximately 55 million people worldwide suffered from dementia in 2019, which is estimated to more than double in 2050 [ 8 ]. Dementia is the cause of 2.4 million deaths and 28.8 million disability-adjusted life years (DALYs) in 2016 and is known as the third cause of neurological DALYs [ 3 , 9 ].

Various factors are involved in dementia, including anthropometric parameters (for example, body mass index), the APOE Ɛ4 allele [ 10 ], lack of weight [ 11 ], inactivity [ 12 ], non-Mediterranean diet [ 13 ], and the lack of specific micronutrients and macronutrients [ 14 ]. In addition, many epidemiological studies have shown that exposure to air pollution can also contribute to neuropathology through oxidative stress, hyperactivation of microglia, disruption of the blood–brain barrier (BBB) and neuroinflammation [ 15 , 16 ] and cause adverse effects on the brain, accelerate cognitive aging and even increase the occurrence of AD and other forms of dementia [ 17 , 18 , 19 ]. The 2020 Lancet Commission on dementia prevention, intervention and care, considered air pollution as a new modifiable risk factor for dementia, accounting for about 2% of cases worldwide [ 20 ]. Studies conducted in the United Kingdom showed that an increase of 1 µg/m 3 PM 2.5 (particles with a diameter of 2.5 µm or less) increases the risk of dementia by 6% and the risk of AD by 10% [ 21 ]. Mortamais et al. (2021) found that an increase of 5µg/m 3 in PM 2.5 level, increases 20% the risk for all-cause dementia, 20% for AD and 33% for Vascular Dementia (VaD) in elderly people over 70 years [ 22 ]. However, the adverse effects of air pollution on cognitive function are not limited to old age. Recent epidemiological studies support the hypothesis that public exposure to air pollutants can cause structural and functional changes in children's brains [ 23 , 24 ] and by causing negative effects on neuropsychological development, make them susceptible to neurological disorders in middle and old age [ 25 , 26 ].

Therefore, prevention of exposure to air pollution is a potentially correctable risk factor in the occurrence of cognitive decline and dementia in the elderly. The present systematic review was conducted to critically examine the published scientific literature related to the impact of exposure to air pollution on dementia. Specifically, the objectives were: (1) to evaluate the type and concentration of air pollutants including PM 10 (particles with a diameter of 10 µm or less), PM 2.5 , NO 2 , O 3 , black carbon (BC), polycyclic aromatic hydrocarbons (PAHs), benzene, toluene, ethylbenzene and xylenes (BTEX), formaldehyde (FA) in geographic areas and (2) to assess the risk of dementia in adults with chronic respiratory exposure to the mentioned pollutants.

This systematic review was guided by the PRISMA statement (Preferred Reporting Items for Systematic Review and Meta-analyses) and fully complied with the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO, CRD42023413916) .

PECO statement

In this study, the PECO (population, exposure, comparator, and outcome) [ 27 ] statement was used to develop the research question, search terms, and inclusion and exclusion criteria of the systematic review. Table 1 shows the PECO statement for understanding the adverse effects of respiratory exposure to pollutants PM 10 , PM 2.5 , NO 2 , O 3 , BC, PAHs, BTEX, and FA on dementia.

Search strategy and selection of studies

According to our knowledge, this is the first systematic review that investigated the effect of respiratory exposure to pollutants i.e. PM 10 , PM 2.5 , NO 2 , O 3 , BC, PAHs, BTEX, and FA on dementia. To obtain all published studies in this field, a systematic search was conducted in Scopus, PubMed, and Web of Science databases, without a date limit until May 22, 2023. The keywords used in this study include the following (the details of the search strategy used for the systematic search in the databases are shown in Appendix A1):

Exposure to pollutants: “air pollution”, “PM 10 ”, “PM 2.5 ”, “nitrogen dioxide”, “ozone”, “black carbon”, “diesel”, “diesel exhaust”, “PAH*”, “BTEX”, “toluene”, “ethylbenzene”, “xylene”, “benzene”, “formaldehyde”, “formal”, “formalin”, “methanol”, “methylene oxide”

Outcomes of exposure: “Alzheimer's disease”, “Neuromarker”, “Neuroinflammation”, “Dementia”, “Vascular dementia”, “Frontotemporal dementia”, “Frontotemporal lobar degeneration”, “Lewy body disease”, “Lewy body dementia”

The mentioned keywords were extracted by (M.M and A.H.Kh) and systematically searched by (A.H.Kh) in Title/Abstract and Mesh (if any). After merging the studies in EndNote X20 software, all duplicates were removed and the data were independently screened and extracted by two researchers (M.M and A.H.Kh). More contradictions and ambiguities were resolved with the intervention of the third author (J.G). In addition, to obtain additional studies that meet the inclusion criteria, additional to the hand searching, the reference list of selected studies was also systematically searched in parallel.

Criteria of entering and extracting studies

In this review, we excluded studies focused on the effects of exposure to air pollutants on neurological and biochemical changes (without examining dementia) and studies that investigated exposure to air pollutants as a dependent variable. Animal studies, laboratory studies, books, review articles, conference papers, and letters to the editors were also excluded. In this systematic review, only original peer-reviewed articles in English were reviewed.

Finally, the following information was extracted from the selected articles:

Authors, the year of publication, study design, country, the number of sample people, the age range of people, gender, the type of pollutant, the mean concentration of pollutant, diagnosis tool, and the type of dementia.

Quality control

The quality of the selected studies was checked by two researchers (M.M and A.H.Kh) using the Joanna Briggs Institute (JBI) checklist for cohort studies, case–control studies and analytical cross-sectional studies, independently. This checklist evaluates the risk of bias in studies by asking 2 questions from each of the sample areas including selection criteria, exposure assessment, confounding factors and results and appropriate statistical analysis. The defined answers for each question can be one of the options (yes, no, unclear, or not applicable). According to the total selection percentage of each of the 4 mentioned answers, the quality of articles is determined in the following 3 levels:

High-quality level and low risk of bias (Q1) (Yes ≥ 50–75%).

Moderate quality level and unclear risk of bias (Q2) (unclear ≥ 50–75%).

Low-quality and high risk of bias (Q3) (No ≥ 50–75%) [ 28 ].

All the articles that were of adequate quality were included in the study.

Result synthesis

Due to heterogeneity in study design, exposure (occupational/environmental) and the age of subjects, quantitative synthesis of studies in the form of meta-analysis was not possible. Therefore, the results obtained from the selected studies, which included the type of dementia, the age of the subjects, gender, the type of air pollutants, mean concentration, the instrument for detecting pollutants, and the diagnosis of dementia, and the outcome of exposure (Appendix A2), were narratively combined. This synthesis was done in two steps. The first stage included the initial synthesis using the general grouping of studies based on Alzheimer's and non-Alzheimer's dementia; therefore, the results of articles were carefully studied, and considered which of the types of Alzheimer's dementia (AD) (Appendix A2) and non-Alzheimer's dementia (VaD, FTD and PD) (Appendix A3) have been investigated. In the second step, the relationship between the type and concentration of each pollutant in dementia was investigated.

Figure 1 shows the process of conducting the present systematic review by the members of the research team, which includes six general steps:

Visualization of the systematic review guiding process comprising eight distinct stages

Topic selection, systematic search, screening and data extraction, quality control, resolving contradictions and ambiguities, and synthesis of results.

Results and Discussion

Selection process and characteristics of articles.

In this review, 14,924 articles were obtained through a systematic search in databases, of which 4532 studies were retrieved from PubMed, 5878 from Scopus, and 4514 from Web of Science. After entering the articles into EndNote X20 software, 6546 duplicates were removed and 8378 studies were screened for title and abstract. At this stage, 8289 articles were excluded and the entry and exit criteria and quality assessment were done for 88 full texts. Finally, after conducting additional reviews, 36 studies were excluded for the following reasons:

Nine studies were review articles, two studies only investigated brain volume, in twelve articles the type of air pollutant was not specified, five studies investigated the effect of other pollutants on dementia, five studies were excluded due to the high risk of bias and access to three full texts was not possible.

In addition, hand searching and systematic search of the selected articles' reference lists were also conducted to identify additional studies eligible for inclusion, which led to the identification of two studies through reference checking. Therefore, the total number of studies included in this systematic review increased to 53 articles (Fig. 2 ).

PRISMA flow diagram of the literature search

The studies in this systematic review included 6 case–control [ 29 , 30 , 31 , 32 , 33 , 34 ], 7 cross-sectional [ 19 , 35 , 36 , 37 , 38 , 39 , 40 ], and 40 cohort studies [ 1 , 2 , 18 , 21 , 22 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 ]. Specifically, selected studies have been conducted in 17 countries around the world:

19 in the United States of America, 7 in Sweden, 7 in Taiwan, 4 in Canada, 3 in France, 2 in Australia, 2 in Germany, 2 in Hong Kong, 2 in Mexico, 2 in the United Kingdom, 1 in each country of Netherlands, Spain, China, Denmark, England, Italy, and the Republic of Korea.

In total, 173,698,774 subjects were contained in the studies examined in this systematic review. The characteristics of the reviewed studies are shown in Table 2 .

Diagnostic methods in the types of dementia

When we examined the 53 selected studies, 39 diagnostic tools and methods for AD and other types of dementia had been used (Appendix A2 and A3); of these, 21 diagnostic tools were used for Alzheimer's dementia and 28 methods for non-Alzheimer's dementia. According to the investigations carried out in studies related to Alzheimer's dementia, the methods of medical records ( N = 11) and Mini-Mental Status Examination (MMSE) ( N = 8) were the most prevalent. Five studies also used medical imaging (such as MRI and CT scan) to investigate the changes made in brain structures, which indicate the onset of Alzheimer's disease. In addition, the most common diagnostic tools for non-Alzheimer's dementia were included medical reports ( N = 4), MMSE ( N = 10), Medical imaging ( N = 4), Clinical Dementia Rating Sum of Box (CDR-SB) ( N = 4), and the Montreal Cognitive Assessment (MoCA) ( N = 3).

MMSE and MoCA are among the most important reliable screening tools that are widely used for clinical and research purposes [ 76 , 77 ]. These tools have received a lot of attention due to the need for little training, ease of implementation, and the ability to differentiate dementia patients from healthy people [ 78 , 79 , 80 ]. MMSE is also widely used to describe a wide range of cognitive functions, including attention, memory, verbal ability, and visual-spatial cognitive function [ 81 ], and its total score is related to disease progression [ 82 ]. However, it has been found that the MMSE may be less reliable than the MoCA in the diagnosis of mild cognitive impairment (MCI) because this instrument had lower sensitivity among multiple study settings [ 83 , 84 , 85 , 86 , 87 ]. In addition, the MoCA can show differences in the cognitive profile of people diagnosed with MMSE in the normal range, which makes the MoCA a powerful, concise, and useful tool [ 77 , 88 , 89 ].

Although the use of questionnaire methods is a standard requirement for dementia researchers, the importance of medical imaging methods in diagnosing dementia types with high certainty should not be neglected to investigate the changes made in the brain structure and the speed of disease progression. Among the most important diagnostic imaging tools for dementia are PET imaging with 2-deoxy-positron emission tomography (PiB-PET), 2 [18F] fluoro-D-glucose tracer (FDG-PET) and Structural and Functional Magnetic Resonance Imaging (MRI) [ 90 ]. The first PET technique used to diagnose neurodegenerative disorders was 18F-fluorodeoxyglucose (18F-FDG) metabolic imaging, which is a measure of neuronal or synaptic integrity [ 91 , 92 ]. More recent advances using PET includes the detection of specific neural ligands, such as specific ligands for fibrillar Aβ [ 93 ], paired-helical filament tau [ 94 , 95 ], and synaptic vesicle protein 2A [ 96 ]. The PET technique, however, is only available in specialized centers due to its high cost.

In our systematic review, the main neuroimaging technique used was MRI. This tool can measure brain atrophy, especially in the mesial-temporal structures, and detect it even before appearing the first clinical symptoms [ 97 , 98 ]. This method is included in both the diagnostic criteria presented by Dubois [ 99 ] and NIA-AA [ 100 ] and has been used as a reliable diagnostic tool by many researchers [ 101 , 102 , 103 ]. The sensitivity of this method as an AD marker has been reported to be more than 85% [ 97 ], which is more than PiB-PET (70%) [ 104 ] and FDG-PET (80%) [ 105 , 106 ].

Atrophy in the medial temporal lobe, especially the hippocampus, and a decrease in the thickness of the cerebral cortex in vulnerable areas of AD are among the first signs detectable by MRI in the early stages of the disease [ 107 , 108 , 109 ]. This tool can show hippocampal volume reduction 2 to 3 years before the onset of dementia in asymptomatic carriers of APP mutations [ 110 ] and in elderly people up to 6 years before that [ 103 , 107 ]. In addition, entorhinal cortex volume reduction, which progresses up to four years before cognitive decline, can be detected by MRI up to 90% [ 107 ].

Alzheimer’s dementia

The characteristics and results extracted from the articles related to Alzheimer's dementia are shown in Appendix A2. Thirty-one studies investigated the effect of pollutants i.e. PM 10 , PM 2.5 , NO 2 , O 3 , BC, PAHs, BTEX, and FA on the occurrence of Alzheimer's dementia. These studies were published from 1995–2023, and most were since 2018, indicating the novelty of the subject under discussion. More than 80% of the studies investigated the incidence of Alzheimer's in people over 60 years old, but some studies included younger people, comprising Haisu Zhang (2023) [ 40 ], Lilian Calderón-Garcidueñas (2022) [ 38 , 39 ], Marta Crous-Bou (2020) [ 1 ], Anna Oudin (2019 and 2016) [ 44 , 53 ], and Ruo-Ling Li (2019) [ 51 ].

The results showed that chronic exposure to air pollutants, especially particulate matter (PMs), increases the number of hospitalizations due to the exacerbation of neurocognitive disorders caused by Alzheimer's dementia or related diseases. This finding is compatible with previous studies on the role of exposure to air pollutants on the development of this neurological disorder [ 18 , 74 , 75 ]. Results from human and animal studies have shown that air pollution is associated with atherosclerosis, increased blood inflammatory biomarkers, and oxidative stress, which may accelerate hospitalization for several neurological diseases [ 111 , 112 ]. In the United Kingdom, the results of a population-based cohort study showed that the risk of AD was associated with exposure to PM 2.5 (adjusted hazard ratio—HR 1.10, 95% CI 1.02–1.18) and NO 2 (1.23, 1.07–1.43) increases significantly so that an increase of 1 µg/m 3 PM 2.5 is associated with a 10% increase in the risk of AD. Exposure to O 3 reduced this risk [ 21 ]. Also Cerza et al. (2019) in a cohort study in Italy concluded that a positive association between exposure to O 3 and NO x and dementia hospitalizations, (O 3 : HR = 1.06; 95% CI: 1.04–1.09 per 10 μg/m 3 ; NO x : HR = 1.01; 95% CI: 1.00–1.02 per 20 μg/m 3 ) [ 52 ]. This study showed that exposure to NO x , NO 2 , PM 2.5 , and PM 10 , except for O 3 , has a significant negative relationship with AD [ 52 ].

He et al. (2022) also demonstrated in a population-based cohort study in China that exposure to PM 2.5 , PM 10 , and CO pollutants was significantly associated with an increased risk of AD, but there is no significant relationship between exposure to NO and SO 2 with the occurrence of this disorder. This study also showed an inverse relationship between O 3 exposure and AD [ 69 ]. Meanwhile, Jung et al. (2015) concluded that for an increase of 9.63 ppb in O 3 concentration, the risk of AD increases 1.06 times in the elderly ≥ 65 years (adjusted HR 1.06, 1.00–1.12) [ 43 ]. The difference between the results of these studies can be caused by different characteristics in the study population, study design, sample size, setting, and different measurements of exposure to air pollutants.

In addition, the researchers found evidence of the adverse effect of exposure to air pollutants on episodic memory. Several animal studies showed that exposure to inhaled PM 2.5 can impair neural systems that underlie episodic memory processes [ 113 , 114 , 115 ]. So far, limited longitudinal epidemiological studies have been conducted about PM 2.5 and episodic memory in humans [ 116 , 117 , 118 ]. The results of a prospective study on 998 elderly women aged 73 to 87 years old in the US showed that chronic exposure to PM 2.5 in residential environments was associated with a rapid decline in episodic memory, especially in measures of immediate recall and learning of new material [ 68 ]. A decrease in verbal episodic memory (such as the ability to remember details, with context, from daily and distant experiences) is prominent in AD and can be detected in the preclinical stage [ 119 , 120 ]. For example, impaired episodic memory is one of the main criteria for the classic diagnosis of AD by Dubois et al. (2007), which appears early in the course of the disease [ 99 ]. Studies have proven that the rapid decline of this memory is somewhat associated with an increase in the Alzheimer's disease pattern similarity (AD-PS) score [ 68 ]. AD-PS is a brain MRI-based structural biomarker that reflects high-dimensional gray matter atrophies in brain regions vulnerable to AD neuropathology [ 68 ]. In addition to exposure to environmental factors, natural aging can also lead to a decrease in episodic memory, which is related to the decrease in the volume of the hippocampus and other structures of the medial temporal lobe [ 121 ]. The medial temporal lobe and its structural components, especially the hippocampus, play an important role in encoding (learning, recalling) and retrieving (recalling) the details of events that make up episodic memories [ 121 ].

Zhao et al. (2019) showed in a human imaging study that atrophy in hippocampal subfields can impose a wide range of effects on measures of episodic memory (immediate recalls, delayed-recalls, and recognition) [ 122 ]. Although so far the relative roles of hippocampal subfields (e.g. cornu ammonis (CA, CA2-3), CA4-denate gyrus, presubiculum, subiculum) have not been determined in the processes related to encoding and retrieval, animal studies have proven the adverse effects of PMs on the morphology and functional changes in hippocampal subfields. Also, we can mention the decrease in apical dendritic spine density and dendritic branches in the CA1 and CA3 regions [ 123 ], decrease in synaptic function in CA1 neurons [ 114 , 124 ], decrease in basic protein in white matter, and increase in atrophy of neurites in the CA1 region [ 125 ]. Based on the studies, encoding is done by CA2, CA3, and dentate gyrus, while CA1 and subiculum are involved in retrieval [ 126 ]. According to the results obtained by Younan et al. (2020), it seems that the significant reduction of episodic memory processes (immediate recall/new learning) caused by exposure to PM 2.5 is more due to the adverse effects of this pollutant on hippocampal subfields associated with encoding, such as CA2, CA3, and dentate gyrus [ 68 ]. These neurotoxicological results indicate that some hippocampal subfields may be more sensitive to the adverse effects of particulate matter than other subfields.

So far, many studies have proven the existence of an inverse relationship between exposure to air pollutants and white matter volume, gray matter volume, and cerebral cortex thickness in brain areas affected by AD [ 127 , 128 , 129 , 130 ]. Wilker et al. (2015) showed in a study that with increasing PM 2.5 concentration, brain volume decreases by 0.32% [ 131 ], which was consistent with the results obtained by Chen et al. (2015) regarding the reduction of white matter volume and the volume of the whole brain due to exposure to high concentrations of this pollutant [ 128 ]. The results of the study by Crous-Bou et al. (2020) showed that chronic exposure to air pollutants, especially NO 2 and PM 10 , is associated with a decrease in the thickness of the cerebral cortex in brain areas affected by AD [ 1 ], which is consistent with the results of study done by Casanova et al. (2016) [ 127 ]. In a voxel-based morphometry study, they examined the local brain structure related to PMs in elderly women and concluded that exposure to PM 2.5 has an inverse relationship with the reduction of the frontal cortex [ 127 ]. Furthermore, Cho et al. (2023) showed that a 10 µg/m 3 increase in (β = -1.13; 95% CI, − 1.73 to − 0.53) PM 10 and a 10 ppb increase in (β = -1.09; 95% CI, − 1.40 to − 0.78) NO 2 are significantly associated with decreasing MoCA score. Also, these two pollutants were significantly associated with an increase in AD-like cortical atrophy scores and a decrease in the thickness of the cerebral cortex [ 129 ].

PET ligand studies indicate that gray matter atrophy of the brain can be caused by tau neuropathological processes, which can lead to cognitive decline in patients [ 132 , 133 , 134 ]. Several plausible biological mechanisms explain the rapid development or onset of neurological diseases caused by exposure to air pollution. After inhalation, air pollutants can pass through the BBB and enter the brain through the olfactory bulb or systemic circulation [ 135 ] causing oxidative stress and systemic inflammatory responses, disruption of the blood–brain barrier, deposition of peptides beta-amyloid (Aβ) and activation of microglia and as a result may exacerbate the disease progression of AD [ 136 , 137 ]. In addition, it has been reported that NO 2 is associated with inflammatory responses and markers such as increased serum concentration of systemic interleukin IL-6 [ 138 ]. Recent studies have shown that exposure to air pollutants can be effective in causing neurological and cognitive disorders by contributing to AD pathologies such as brain Aβ and tau burden [ 139 , 140 ]. Researchers use the levels of Aβ, total tau (t-tau) and phospho-tau (p-tau) in CSF as specific biomarkers for the clinical diagnosis of probable AD [ 99 ]. Some studies have proven that CSF Aβ, as the first marker of AD, shows abnormal levels several years before the appearance of impaired memory [ 141 , 142 ]. Diagnosis of early AD in patients with mild cognitive impairment (MCI) can be done by detecting low levels of Aβ and high levels of p-tau and t-tau in CSF [ 143 ].

Reports show that living in areas with high air pollution can lead to the accumulation of Aβ in neurons and astrocytes [ 144 ]. Also, the results obtained from the study of Fu et al. (2022) indicate that the increase in the concentration of each unit of ln-transformed Ʃ-OH PAHs in the urine of coke oven workers was associated with an increase of 9.416 units of P-Tau231 in plasma and a decrease of 0.281 in visuospatial/executive function [ 145 ]. Tau is a microtubule-associated protein that contributes to the stability of axonal microtubules in the brain [ 146 ]. The presence of hyperphosphorylated tau leads to the formation of neurofibrillary tangles, which is considered a pathological characteristic of AD [ 147 ]. Some researchers have reported changes in the concentration of phosphorylated tau as a possible sign of the progression of some neurological diseases [ 148 , 149 ]. This is consistent with the results of Nie et al.'s (2013) study, which showed that benzo[a]pyrene (B[a]P) leads to tau 231 hyperphosphorylation [ 150 ].

Non-Alzheimer’s dementia

Among the 53 selected articles, 41 studies investigated the effect of air pollutants on the incidence of non-Alzheimer's dementia (Appendix A3), which were published during the years 2014–2023. Except for the studies of Anna Oudin (2016) [ 44 ], Anna Oudin (2018) [ 49 ], Iain M Carey (2018) [ 21 ], Anna Oudin (2019) [ 53 ], Han-Wei Zhang (2019) [ 54 ], Zorana J. Andersen (2022) [ 67 ], Lilian Calderón-Garcidueñas (2022) [ 38 , 39 ], and Haisu Zhang (2023) [ 40 ], the rest of the articles included people over the age of 60 years old.

Non-Alzheimer's dementia accounts for almost half of dementia cases [ 151 ]. The most common non-Alzheimer's neurological disorders include vascular dementia (VaD) [ 152 , 153 ], Parkinson's disease (PD) [ 154 ], Fronto-Temporal Dementia (FTD) [ 155 ] and Dementia with Lewy Bodies (DLB) [ 92 ], which are characterized by the accumulation of natural proteins in the CNS, as proteinopathies [ 156 ].

Vascular Dementia

The present study showed that exposure to air pollutants may have a direct effect on the incidence and progression of VaD. In a longitudinal study, Oudin et al. (2016) concluded that the probability of VaD diagnosis, with HR = 1.43, was higher among citizens with the highest exposure to traffic-related air pollution than those with low exposure [ 44 ]. These results were consistent with the study conducted by Cerza et al. (2019) [ 52 ]. In a longitudinal study on elderly men and women in Italy, they reported that chronic exposure to NO x , NO 2 , PM 10 and PM 2.5 has a positive relationship with VaD. In addition, a direct relationship between exposure to O 3 and NO x with dementia hospitalization was also observed (O 3 : HR = 1.06 per 10 μg/m 3 ; NO x : HR = 1.01; per 20 μg/m 3 ) [ 52 ].

According to the studies, chronic exposure to air pollutants can cause vascular damage caused by large vessel atherosclerosis and small vessel arteriosclerosis and cause cortical and subcortical infarcts, sub-infarct ischemic lesions, and large and small cerebral hemorrhages [ 153 , 157 ]. Researchers identify these factors as responsible for the initiation of VaD [ 153 ]. Moreover, dysfunction and degeneration of the neurovascular unit, which consists of a network of pericytes, myocytes, astrocytes, neurons, oligodendrocytes, endothelial cells and cerebral microvessels, aggravate the pathogenesis of VaD by disrupting the BBB [ 158 ]; which require hospital care to treat and prevent further side effects.

Also, the results obtained from a case–control study in Taiwan indicate that exposure to high levels of NO 2 significantly increases the risk of developing VaD [ 31 ]. According to the studies, some researchers showed that for an increase of 5 μg/m 3 NO 2 , the risk of VaD increases by 1.62 [ 74 ]. However, some studies have reached contradictory results. A cohort study conducted in England estimated the prevalence of VaD among men and women aged 50–79 years old at 29%, but found little evidence of the effect of air pollution on this neurological disorder [ 21 ]. Differences in results could be due to differences in instruments used, study design, and sample population characteristics.

VaD is a pathological condition in the elderly characterized by progressive cognitive dysfunction and is the second most common form of dementia, after AD [ 159 ]. This disorder is manifested by the loss of rationality, judgment skills, and especially cognitive functions and memory, and patients usually survive only 5–7 years after its onset [ 160 ]. Multifactorial etiopathology, diverse clinical manifestations, and numerous clinical subgroups are among the characteristics of VaD [ 152 ]. Chronic reduction in cerebral blood flow is one of the main characteristics of this neurological disorder [ 161 ], which results in the departure of brain blood vessels from regulation. This causes functional damage to capillaries, arteries and venules and damage to myelinated axons, and by creating a lesion in the white matter, it starts the pathophysiological process of VaD [ 162 ]. Small vessel disease (leukoaraiosis and lacunar infarcts), microinfarcts, microhemorrhages, cerebral amyloid angiopathy, and mixed vascular lesions are among the most important debilitating lesions of VaD [ 163 , 164 ]. In addition, chronic cerebral hypoperfusion (CCH) has been reported as the main cause of this type of dementia [ 163 , 165 ]. The results obtained from the studies indicate that CCH is associated with both neurodegeneration and dementia [ 166 , 167 ]. Studies have shown that exposure to PMs can increase CCH-induced white matter neurotoxicity by enhancing pathophysiology [ 168 , 169 ]. In a recent epidemiological study, Chen et al. (2015) showed that exposure to PM 2.5 was associated with a decrease in regional white matter volume in the corpus callosum and frontal/temporal lobes of elderly women [ 128 ], which is consistent with the results of the study by Erickson et al. (2020) was matched [ 170 ]. In addition, experimental data obtained from animal studies showed that exposure to air pollutants, especially PMs, causes changes in myelin in the CA1 area of the hippocampus in rodents [ 171 ], which can increase the risk of developing neurological disorders and types of dementia.

Dementia due to Parkinson’s disease

The results of the studies retrieved in this systematic review showed that dementia due to PD, a dementia that begins 1 year or more after well-established Parkinson's disease [ 92 ], can be considered as one of the adverse effects of exposure to air pollutants, especially PMs. Shi et al. (2020) in a national cohort study in the USA showed that for an annual increase of 5 μg/m 3 PM 2.5 , the probability of the first hospital admission due to PD and other related dementias will increase by 1.13 times for the American Medicare population (HR = 1.13) [ 75 ]. In this regard, Yuchi et al. (2020) also obtained similar results [ 32 ]. In a population-based cohort study in Canada, they proved that exposure to air pollutants increases the risk of PD (HR for PMs = 1.09, HR for BC = 1.03, HR for NO 2 = 1.12), but no relationship was observed on the occurrence of AD [ 32 ]. These results were consistent with those obtained from the studies of Rhew et al. (2021) [ 33 ], Yitshak-Sade et al. (2021) [ 61 ] and Calderón-Garcidueñas et al. [ 39 ].

The studies have demonstrated that over 80% of individuals with Parkinson's disease develop dementia [ 172 ]. Generally, the point prevalence of dementia in patients with Parkinson's has been determined to be approximately 25%, which has a higher prevalence in men than in women [ 173 ]. Researchers have proven that the risk of dementia increased as the duration of the disease increased, so that this probability reached 50% 10 years after the diagnosis of Parkinson's [ 91 ]. Research indicates that dementia occurs in patients who survive for more than 10 years [ 93 ].

PD, containing Lewy bodies and Lewy neurites, is one of the common brain disorders associated with aging and is characterized by the accumulation of α-synuclein in intracellular inclusions [ 154 ]. The main pathological characteristic of PD is the progressive loss of nigrostriatal dopaminergic neurons in the substantia nigra pars compacta, which causes Parkinsonism in PD patients [ 174 ]. Parkinsonism is a clinical syndrome characterized by rest tremor, rigidity, bradykinesia and gait dysfunction with postural instability [ 174 ]. Neurological disorders such as progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), or FTD may overlap in their symptoms with PD [ 156 ]. Reports show that a significant number of people with PD suffer from cognitive impairment and PD dementia during their disease [ 172 , 175 ]. In some cases, co-existing pathology of TDP-43 can also be detected in PD patients [ 176 ]. TDP-43 is a protein biomarker whose accumulation can diagnose and classify neurological disorders [ 177 ]. The available evidence indicates that exposure to air pollutants plays a role in the accumulation of this protein [ 178 ]. Neuropathological examination of 44 children (average age 12.89 ± 4.9 years old) and 159 young adults (average age 29.2 ± 6.8 years old) living in Mexico City showed that exposure to PM 2.5 and O 3 pollutants can cause AD and PD in 23% of people. Furthermore, it causes TDP-43 pathology in 18.7% of cases [ 179 , 180 ], which is in line with the results of the present systematic review.

Fronto-Temporal Dementia

FTD is a group of neurodegenerative disorders and although clinically and pathologically heterogeneous, they mainly affect the frontal and/or temporal lobes of the brain [ 156 , 181 ]. This type of dementia is usually characterized by predominant frontal or temporal atrophy, and atrophy in the fronto-polar region is considered a special symptom of FTD [ 182 ]. The main clinical manifestations of FTD include two types of behavioral variant (bvFTD) and primary progressive aphasia (PPA). BvFTD mainly leads to personality changes and behavioral problems; While PPA causes gradual deterioration in speech/language and has a lower prevalence than bvFTD [ 183 ]. Primary Parkinsonism is observed in more than 20% of patients with FTD, mostly in bvFTD patients, and then non-fluent variant primary progressive aphasia occurs [ 184 ]. Each of the mentioned stages can have an effective role in reducing people's lives and increasing the economic burden for health systems by creating FTD.

In the current review, only two studies investigated FTD. Parra et al. (2022) concluded in a national cohort in the UK that there was a strong association between exposure to PM 2.5 , NO 2 , and NO x with the incidence of AD and VaD but not with FTD [ 73 ]. Meanwhile, Calderón-Garcidueñas et al. (2022) obtained completely contradictory results in the study of neurological disorders caused by exposure to PM 2.5 in young adults living in the metropolis of Mexico City [ 39 ]. They showed that chronic exposure to PM 2.5 higher than the values recommended by US-EPA causes a significant reduction of gray matter in higher-order cortical areas, which is usually associated with AD, PD and FTD in educated Mexicans [ 39 ]. The discrepancy in the results of these two studies can be explained by the difference in the number of cases, the age range of the cases, and the country under study.

Strengths and limitations of the study

Although several review studies related to exposure to air pollutants and the incidence of dementia have been published in recent years [ 135 , 185 , 186 , 187 ], the present systematic review has several notable strengths that distinguish our study from other review studies. First, this study is the most up-to-date systematic review published related to the role of chronic exposure to air pollutants on dementia (Alzheimer's/Non-Alzheimer's).

Second, unlike other studies, we did not impose any restrictions on publication time [ 135 ], study design [ 185 , 186 , 187 ], and geographic scope [ 185 ] in the systematic search, which allowed us to find more studies and more comprehensive results. In addition, we tried to perform a systematic search in the largest and the most reliable databases to ensure the inclusion of all eligible studies. This resulted in the extraction of 53 related studies that met the inclusion criteria for the present review. However, our investigations showed that none of the recent review articles discussed the current number of studies [ 135 , 185 , 186 , 187 ].

Third, due to the inclusion of an acceptable number of articles in the present systematic review, the results obtained from examining a substantial population of subjects, 173,698,774 people, were presented, which indicates the comprehensiveness and generalizability of the results of the present study.

Fourth, our study included types of dementia, such as Alzheimer's and non-Alzheimer's, and related dementias. This will help researchers to understand the impact of air pollution on each type of dementia and the action mechanism of pollutants in creating structural changes in the brain.

Fifth, in this study, in addition to criterion pollutants, other common and dangerous air pollutants, including FA, BTEX, and PAHs, were also investigated; these pollutants were not investigated in any of the published reviews.

However, the lack of access to the full texts of some studies and the examination of a limited number of pollutants were among the inevitable limitations of this systematic review.

Gaps and Recommendations

An in-depth review of published studies indicates the existence of some gaps in this important health field, including the lack of sufficient studies related to the role of air pollutants on FTD. As mentioned earlier, we could find only two studies related to the effect of exposure to PM 2.5 , PM 10 , NO 2 , and NO x on FTD [ 39 , 73 ], which makes it impossible to compare the results with each other. Therefore, it is recommended that more researchers investigate the impact of exposure to different pollutants in diverse populations on FTD, to cover this important gap.

Moreover, the presence of various confounding factors can also be effective in achieving contradictory results in studies. Researchers believe that factors such as aging, early retirement, smoking, body mass index (BMI), alcohol consumption, and physical inactivity are among the confounding factors that can accelerate the process of dementia [ 66 ]. Also, studies have proven that co-morbidities, such as cardiovascular diseases, cerebrovascular disease, diabetes and mental health, environmental tobacco smoke (ETS), chronic exposure to noise, insufficient sleep, and unhealthy diet can also play an effective role in occurring or developing dementia at an older age [ 188 ]. Research has identified several potential socioeconomic factors that can influence the relationship between air pollution exposure and neurological outcomes at the individual and regional levels. Based on this, living in deprived neighborhoods and on the outskirts of cities increases the possibility of exposure to high levels of air pollution [ 189 ]. Studies have also shown that lower levels of education, and poor access to socioeconomic benefits, such as health care, are associated with an increased risk of dementia in the future [ 190 , 191 ]. Therefore, it is necessary to consider strategies to control the impact of confounding factors to achieve more accurate results.

Also, due to the limited number of studies related to occupational exposure to pollutants in dementia, it is recommended to conduct more research to investigate occupational exposure in workers of different occupations and compare and analyze their results.

Since it has been proven that prenatal exposure is effective in the occurrence of some diseases in the future; therefore, it is recommended that cohort studies be designed and implemented to investigate the role of prenatal exposure to air pollutants and dementia at older ages.

The results of this systematic review showed that chronic exposure to air pollutants, especially PM 2.5 and NO 2 , could have a potential role in the development and progression of AD and non-Alzheimer's dementia in old age. The review of selected studies indicates that the relationship between exposure to PM 2.5 and then NO 2 and O 3 and suffering from dementia has been the focus of researchers in the last 5 years. No study was found that investigated the effect of FA on dementia and met the inclusion criteria for this study. In addition, BTEX and PAHs have been neglected by researchers, which is surprising due to the widespread presence of these pollutants in the environment and industries. Therefore, conducting more studies on the impact of other air pollutants, including FA, BTEX and PAHs, on the incidence of dementia and cognitive disorders is highly recommended. We believe that the identification and prevention of modifiable risk factors, such as exposure to toxic air in conjunction with behavioral interventions, can help prevent or delay the progression of neurodegenerative disorders and significantly reduce the burden of those disorders on society.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Code availability

Not applicable.

Abbreviations

Alzheimer's dementia

Blood-brain barrier

Black carbon

Benzene, Toluene, Ethylbenzene, and Xylenes

Chronic cerebral hypoperfusion

Dementia with Lewy Bodies

Disability-adjusted life years

Formaldehyde

Parkinson Disease

Particulate Matter

Particles with a diameter of 10 µm or less

Particles with a diameter of 2.5 µm or less

Polycyclic Aromatic Hydrocarbons

The Montreal Cognitive Assessment

World Health Organization

Crous-Bou M, Gascon M, Gispert JD, Cirach M, Sánchez-Benavides G, Falcon C, et al. Impact of urban environmental exposures on cognitive performance and brain structure of healthy individuals at risk for Alzheimer’s dementia. Environ Int. 2020;138:105546.

Article PubMed CAS Google Scholar

Shi L, Wu X, Danesh Yazdi M, Braun D, Abu Awad Y, Wei Y, et al. Long-term effects of PM2·5 on neurological disorders in the American Medicare population: a longitudinal cohort study. Lancet Planet Health. 2020;4(12):e557–65.

Article PubMed PubMed Central Google Scholar

Feigin VL, Nichols E, Alam T, Bannick MS, Beghi E, Blake N, et al. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459–80.

Article Google Scholar

Maragakis NJ, Rothstein JD. Mechanisms of Disease: astrocytes in neurodegenerative disease. Nat Clin Pract Neurol. 2006;2(12):679–89.

Lipnicki DM, Crawford JD, Dutta R, Thalamuthu A, Kochan NA, Andrews G, et al. Age-related cognitive decline and associations with sex, education and apolipoprotein E genotype across ethnocultural groups and geographic regions: a collaborative cohort study. PLoS Med. 2017;14(3):e1002261.

Gao Q, Zang E, Bi J, Dubrow R, Lowe SR, Chen H, et al. Long-term ozone exposure and cognitive impairment among Chinese older adults: A cohort study. Environ Int. 2022;160:107072.

Article PubMed PubMed Central CAS Google Scholar

Jia L, Quan M, Fu Y, Zhao T, Li Y, Wei C, et al. Dementia in China: epidemiology, clinical management, and research advances. Lancet Neurol. 2020;19(1):81–92.

Article PubMed Google Scholar

WHO. Global status report on the public health response to dementia 2021 [Available from: https://www.who.int/publications/i/item/9789240033245 .

Nichols E, Szoeke CE, Vollset SE, Abbasi N, Abd-Allah F, Abdela J, et al. Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):88–106.

Gachupin F, Romero MD, Ortega WJ, Jojola R, Hendrie H, Torres EP, et al. Cognition, Depressive Symptoms and Vascular Factors among Southwest Tribal Elders. Ethn Dis. 2016;26(2):235–44.

Park KM, Sung JM, Kim WJ, An SK, Namkoong K, Lee E, et al. Population-based dementia prediction model using Korean public health examination data: A cohort study. PLoS ONE. 2019;14(2):e0211957.

Ran J, Zhang Y, Han L, Sun S, Zhao S, Shen C, et al. The joint association of physical activity and fine particulate matter exposure with incident dementia in elderly Hong Kong residents. Environ Int. 2021;156.

Aridi Y S, Walker J L, Wright ORL. The Association between the Mediterranean Dietary Pattern and Cognitive Health: A Systematic Review. Nutrients [Internet]. 2017;9(7):674.

Solfrizzi V, Custodero C, Lozupone M, Imbimbo BP, Valiani V, Agosti P, et al. Relationships of Dietary Patterns, Foods, and Micro- and Macronutrients with Alzheimer’s Disease and Late-Life Cognitive Disorders: A Systematic Review. J Alzheimer’s Dis. 2017;59:815–49.

Article CAS Google Scholar

Block ML, Calderón-Garcidueñas L. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009;32(9):506–16.

Calderón-Garcidueñas L, Azzarelli B, Acuna H, Garcia R, Gambling TM, Osnaya N, et al. Air pollution and brain damage. Toxicol Pathol. 2002;30(3):373–89.

Jeremy W. Air pollution and brain health: an emerging issue. Lancet. 2017;390:1345–422.

Google Scholar

Mork D, Braun D, Zanobetti A. Time-lagged relationships between a decade of air pollution exposure and first hospitalization with Alzheimer’s disease and related dementias. Environ Int. 2023;171.

Li Z, Christensen GM, Lah JJ, Marcus M, Russell AG, Ebelt S, et al. Neighborhood characteristics as confounders and effect modifiers for the association between air pollution exposure and subjective cognitive functioning. Environ Res. 2022;212.

Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413–46.

Carey IM, Anderson HR, Atkinson RW, Beevers SD, Cook DG, Strachan DP, et al. Are noise and air pollution related to the incidence of dementia? A cohort study in London, England. BMJ Open. 2018;8(9).

Mortamais M, Gutierrez L-A, de Hoogh K, Chen J, Vienneau D, Carrière I, et al. Long-term exposure to ambient air pollution and risk of dementia: Results of the prospective Three-City Study. Environ Int. 2021;148.

Guxens M, Lubczyńska MJ, Muetzel RL, Dalmau-Bueno A, Jaddoe VWV, Hoek G, et al. Air Pollution Exposure During Fetal Life, Brain Morphology, and Cognitive Function in School-Age Children. Biol Psychiatry. 2018;84(4):295–303.

Pujol J, Martínez-Vilavella G, Macià D, Fenoll R, Alvarez-Pedrerol M, Rivas I, et al. Traffic pollution exposure is associated with altered brain connectivity in school children. Neuroimage. 2016;129:175–84.

Forns J, Dadvand P, Foraster M, Alvarez-Pedrerol M, Rivas I, López-Vicente M, et al. Traffic-Related Air Pollution, Noise at School, and Behavioral Problems in Barcelona Schoolchildren: A Cross-Sectional Study. Environ Health Perspect. 2016;124(4):529–35.

Suades-González E, Gascon M, Guxens M, Sunyer J. Air Pollution and Neuropsychological Development: A Review of the Latest Evidence. Endocrinology. 2015;156(10):3473–82.

Rethlefsen ML, Kirtley S, Waffenschmidt S, Ayala AP, Moher D, Page MJ, et al. PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst Rev. 2021;10(1):39.

Santos WMd, Secoli SR, Püschel VAdA. The Joanna Briggs Institute approach for systematic reviews. Revista latino-americana de enfermagem. 2018;26:3074.

Kukull WA, Larson EB, Bowen JD, McCormick WC, Teri L, Pfanschmidt ML, et al. Solvent Exposure as a Risk Factor for Alzheimer’s Disease: A Case-Control Study. Am J Epidemiol. 1995;141(11):1059–71.

Wu Y-C, Lin Y-C, Yu H-L, Chen J-H, Chen T-F, Sun Y, et al. Association between air pollutants and dementia risk in the elderly. Alzheimer’s Dement. Diagn Assess Dis Monit. 2015;1(2):220–8.

Li C-Y, Li C-H, Martini S, Hou W-H. Association between air pollution and risk of vascular dementia: A multipollutant analysis in Taiwan. Environ Int. 2019;133: 105233.

Yuchi W, Sbihi H, Davies H, Tamburic L, Brauer M. Road proximity, air pollution, noise, green space and neurologic disease incidence: a population-based cohort study. Environ Health. 2020;19(1):8.

Rhew SH, Kravchenko J, Lyerly HK. Exposure to low-dose ambient fine particulate matter PM2.5 and Alzheimer’s disease, non-Alzheimer’s dementia, and Parkinson’s disease in North Carolina. PLOS ONE. 2021;16(7):e0253253.

Lin FC, Chen CY, Lin CW, Wu MT, Chen HY, Huang P. Air Pollution Is Associated with Cognitive Deterioration of Alzheimer’s Disease. Gerontology. 2021;68(1):53–61.

Tan J, Li N, Wang X, Chen G, Yan L, Wang L, et al. Associations of particulate matter with dementia and mild cognitive impairment in China: A multicenter cross-sectional study. The Innovation. 2021;2(3).

Petkus AJ, Younan D, Wang X, Beavers DP, Espeland MA, Gatz M, et al. Associations Between Air Pollution Exposure and Empirically Derived Profiles of Cognitive Performance in Older Women. J Alzheimer’s Dis. 2021;84:1691–707.

Semmens EO, Leary CS, Fitzpatrick AL, Ilango SD, Park C, Adam CE, et al. Air pollution and dementia in older adults in the Ginkgo Evaluation of Memory Study. Alzheimers Dement. 2023;19(2):549–59.

Calderón-Garcidueñas L, Chávez-Franco DA, Luévano-Castro SC, Macías-Escobedo E, Hernández-Castillo A, Carlos-Hernández E, et al. Metals, Nanoparticles, Particulate Matter, and Cognitive Decline. Front neurol. 2022;12:794071.

Calderón-Garcidueñas L, Hernández-Luna J, Mukherjee P S, Styner M, Chávez-Franco D A, Luévano-Castro S C, et al. Hemispheric Cortical, Cerebellar and Caudate Atrophy Associated to Cognitive Impairment in Metropolitan Mexico City Young Adults Exposed to Fine Particulate Matter Air Pollution. Toxics [Internet]. 2022;10(4):156.

Zhang H, Shi L, Ebelt S T, D’Souza R R, Schwartz J D, Scovronick N, et al. Short-term associations between ambient air pollution and emergency department visits for Alzheimer’s disease and related dementias. Environmental Epidemiology. 2022;7(1):e237.

Ranft U, Schikowski T, Sugiri D, Krutmann J, Krämer U. Long-term exposure to traffic-related particulate matter impairs cognitive function in the elderly. Environ Res. 2009;109(8):1004–11.

Chang K-H, Chang M-Y, Muo C-H, Wu T-N, Chen C-Y, Kao C-H. Increased Risk of Dementia in Patients Exposed to Nitrogen Dioxide and Carbon Monoxide: A Population-Based Retrospective Cohort Study. PLoS ONE. 2014;9(8): e103078.

Jung C-R, Lin Y-T, Hwang B-F. Ozone, Particulate Matter, and Newly Diagnosed Alzheimer’s Disease: A Population-Based Cohort Study in Taiwan. J Alzheimer’s Dis. 2015;44:573–84.

Oudin A, Forsberg B, Adolfsson Annelie N, Lind N, Modig L, Nordin M, et al. Traffic-Related Air Pollution and Dementia Incidence in Northern Sweden: A Longitudinal Study. Environ Health Perspect. 2016;124(3):306–12.

Chen H, Kwong JC, Copes R, Hystad P, van Donkelaar A, Tu K, et al. Exposure to ambient air pollution and the incidence of dementia: A population-based cohort study. Environ Int. 2017;108:271–7.

Culqui DR, Linares C, Ortiz C, Carmona R, Díaz J. Association between environmental factors and emergency hospital admissions due to Alzheimer’s disease in Madrid. Sci Total Environ. 2017;592:451–7.

Chen J-C, Wang X, Serre M. Particulate Air Pollutants, Brain Structure, and Neurocognitive Disorders in Older Women. Res Rep Health Eff Inst. 2017;2017(193):1–65.

PubMed Google Scholar

Andersson J, Oudin A, Sundström A, Forsberg B, Adolfsson R, Nordin M. Road traffic noise, air pollution, and risk of dementia – results from the Betula project. Environ Res. 2018;166:334–9.

Oudin A, Segersson D, Adolfsson R, Forsberg B. Association between air pollution from residential wood burning and dementia incidence in a longitudinal study in Northern Sweden. PLoS ONE. 2018;13(6):e0198283.

Lee H, Kang JM, Myung W, Choi J, Lee C, Na DL, et al. Exposure to ambient fine particles and neuropsychiatric symptoms in cognitive disorder: A repeated measure analysis from the CREDOS (Clinical Research Center for Dementia of South Korea) study. Sci Total Environ. 2019;668:411–8.

Li R-L, Ho Y-C, Luo C-W, Lee S-S, Kuan Y-H. Influence of PM2.5 Exposure Level on the Association between Alzheimer’s Disease and Allergic Rhinitis: A National Population-Based Cohort Study. Int J Environ Res Public Health [Internet]. 2019;16(18):3357.

Cerza F, Renzi M, Gariazzo C, Davoli M, Michelozzi P, Forastiere F, et al. Long-term exposure to air pollution and hospitalization for dementia in the Rome longitudinal study. Environ Health. 2019;18(1):72.

Oudin A, Andersson J, Sundström A, Nordin Adolfsson A, Oudin Åström D, Adolfsson R, et al. Traffic-related air pollution as a risk factor for dementia: no clear modifying effects of APOE ɛ4 in the Betula cohort. J Alzheimer’s Dis. 2019;71(3):733–40.

Zhang H-W, Kok VC, Chuang S-C, Tseng C-H, Lin C-T, Li T-C, et al. Long-Term Exposure to Ambient Hydrocarbons Increases Dementia Risk in People Aged 50 Years and above in Taiwan. Curr Alzheimer Res. 2019;16(14):1276–89.

Smargiassi A, Sidi EAL, Robert L-E, Plante C, Haddad M, Gamache P, et al. Exposure to ambient air pollutants and the onset of dementia in Québec. Canada Environ Res. 2020;190:109870.

Ilango SD, Chen H, Hystad P, van Donkelaar A, Kwong JC, Tu K, et al. The role of cardiovascular disease in the relationship between air pollution and incident dementia: a population-based cohort study. Int J Epidemiol. 2020;49(1):36–44.

Paul KC, Haan M, Yu Y, Inoue K, Mayeda ER, Dang K, et al. Traffic-related air pollution and incident dementia: direct and indirect pathways through metabolic dysfunction. J Alzheimer’s Dis. 2020;76(4):1477–91.

Ran J, Schooling CM, Han L, Sun S, Zhao S, Zhang X, et al. Long-term exposure to fine particulate matter and dementia incidence: A cohort study in Hong Kong. Environ Pollut. 2021;271:116303.

Shaffer Rachel M, Blanco Magali N, Li G, Adar Sara D, Carone M, Szpiro Adam A, et al. Fine Particulate Matter and Dementia Incidence in the Adult Changes in Thought Study. Environ Health Perspect. 2021;129(8):087001.

Diana Y, Xinhui W, Ramon C, Ryan B, Sarah AG, Santiago S, et al. PM<sub>2.5</sub> Associated With Gray Matter Atrophy Reflecting Increased Alzheimer Risk in Older Women. Neurology. 2021;96(8):e1190.

Yitshak-Sade M, Nethery R, Schwartz J D, Mealli F, Dominici F, Di Q, et al. PM2.5 and hospital admissions among Medicare enrollees with chronic debilitating brain disorders. Sci Total Environ. 2021;755:142524.

Shaffer RM, Li G, Adar SD, Dirk Keene C, Latimer CS, Crane PK, et al. Fine Particulate Matter and Markers of Alzheimer’s Disease Neuropathology at Autopsy in a Community-Based Cohort. J Alzheimer’s Dis. 2021;79:1761–73.

Sullivan KJ, Ran X, Wu F, Chang C-CH, Sharma R, Jacobsen E, et al. Ambient fine particulate matter exposure and incident mild cognitive impairment and dementia. J Am Geriatr Soc. 2021;69(8):2185–94.

Kriit HK, Forsberg B, Åström DO, Oudin A. Annual dementia incidence and monetary burden attributable to fine particulate matter (PM2.5) exposure in Sweden. Environmental Health. 2021;20(1):65.

Shi L, Steenland K, Li H, Liu P, Zhang Y, Lyles RH, et al. A national cohort study (2000–2018) of long-term air pollution exposure and incident dementia in older adults in the United States. Nat Commun. 2021;12(1):6754.

Wu J, Grande G, Stafoggia M, Ljungman P, Laukka EJ, Eneroth K, et al. Air pollution as a risk factor for Cognitive Impairment no Dementia (CIND) and its progression to dementia: A longitudinal study. Environ Int. 2022;160: 107067.

Andersen ZJ, Zhang J, Jørgensen JT, Samoli E, Liu S, Chen J, et al. Long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in a large pooled European cohort: ELAPSE study. Environ Int. 2022;170:107581.

Younan D, Wang X, Gruenewald T, Gatz M, Serre ML, Vizuete W, et al. Racial/Ethnic Disparities in Alzheimer’s Disease Risk: Role of Exposure to Ambient Fine Particles. The Journals of Gerontology: Series A. 2022;77(5):977–85.

He F, Tang J, Zhang T, Lin J, Li F, Gu X, et al. Impact of air pollution exposure on the risk of Alzheimer’s disease in China: A community-based cohort study. Environ Res. 2022;205:112318.

Wood D, Evangelopoulos D, Beevers S, Kitwiroon N, Katsouyanni K. Exposure to Ambient Air Pollution and the Incidence of Dementia in the Elderly of England: The ELSA Cohort. Int J Environ Res Public Health [Internet]. 2022;19(23):15889.

Chen C, Whitsel EA, Espeland MA, Snetselaar L, Hayden KM, Lamichhane AP, et al. B vitamin intakes modify the association between particulate air pollutants and incidence of all-cause dementia: Findings from the Women’s Health Initiative Memory Study. Alzheimers Dement. 2022;18(11):2188–98.

Letellier N, Gutierrez L-A, Duchesne J, Chen C, Ilango S, Helmer C, et al. Air quality improvement and incident dementia: Effects of observed and hypothetical reductions in air pollutant using parametric g-computation. Alzheimers Dement. 2022;18(12):2509–17.

Parra KL, Alexander GE, Raichlen DA, Klimentidis YC, Furlong MA. Exposure to air pollution and risk of incident dementia in the UK Biobank. Environ Res. 2022;209: 112895.

Trevenen ML, Heyworth J, Almeida OP, Yeap BB, Hankey GJ, Golledge J, et al. Ambient air pollution and risk of incident dementia in older men living in a region with relatively low concentrations of pollutants: The Health in Men Study. Environ Res. 2022;215.

Shi L, Zhu Q, Wang Y, Hao H, Zhang H, Schwartz J, et al. Incident dementia and long-term exposure to constituents of fine particle air pollution: A national cohort study in the United States. Proc Natl Acad Sci. 2023;120(1).

Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.

Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. J Am Geriatr Soc. 2005;53(4):695–9.

Damian AM, Jacobson SA, Hentz JG, Belden CM, Shill HA, Sabbagh MN, et al. The Montreal Cognitive Assessment and the Mini-Mental State Examination as Screening Instruments for Cognitive Impairment: Item Analyses and Threshold Scores. Dement Geriatr Cogn Disord. 2011;31(2):126–31.

Freitas S, Simões MR, Alves L, Santana I. Montreal cognitive assessment: validation study for mild cognitive impairment and Alzheimer disease. Alzheimer Dis Assoc Disord. 2013;27(1):37–43.

Fasnacht JS, Wueest AS, Berres M, Thomann AE, Krumm S, Gutbrod K, et al. Conversion between the Montreal Cognitive Assessment and the Mini-Mental Status Examination. J Am Geriatr Soc. 2023;71(3):869–79.

Khachiyants N, Kim k. Mini-mental status examination mapping to the corresponding brain areas in dementia. Appl technol innov. 2012;12(3):60–3.

Tombaugh TN, McIntyre NJ. The Mini-Mental State Examination: A Comprehensive Review. J Am Geriatr Soc. 1992;40(9):922–35.

Ciesielska N, Sokołowski R, Mazur E, Podhorecka M, Polak-Szabela A, Kędziora-Kornatowska K. Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis Psychiatr Pol. 2016;50(5):1039–52.

Dong Y, Lee WY, Basri NA, Collinson SL, Merchant RA, Venketasubramanian N, et al. The Montreal Cognitive Assessment is superior to the Mini-Mental State Examination in detecting patients at higher risk of dementia. Int Psychogeriatr. 2012;24(11):1749–55.

Larner AJ. Screening utility of the Montreal Cognitive Assessment (MoCA): in place of – or as well as – the MMSE? Int Psychogeriatr. 2012;24(3):391–6.

Breton A, Casey D, Arnaoutoglou NA. Cognitive tests for the detection of mild cognitive impairment (MCI), the prodromal stage of dementia: Meta-analysis of diagnostic accuracy studies. Int J Geriatr Psychiatry. 2019;34(2):233–42.

Pinto TC, Machado L, Bulgacov TM, Rodrigues-Júnior AL, Costa ML, Ximenes RC, et al. Is the Montreal Cognitive Assessment (MoCA) screening superior to the Mini-Mental State Examination (MMSE) in the detection of mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) in the elderly? Int Psychogeriatr. 2019;31(4):491–504.

Pendlebury ST, Markwick A, de Jager CA, Zamboni G, Wilcock GK, Rothwell PM. Differences in Cognitive Profile between TIA, Stroke and Elderly Memory Research Subjects: A Comparison of the MMSE and MoCA. Cerebrovasc Dis. 2012;34(1):48–54.

Siqueira GSA, Hagemann PdMS, Coelho DdS, Santos FHD, Bertolucci PHF. Can MoCA and MMSE Be Interchangeable Cognitive Screening Tools? A Systematic Review. Gerontol. 2019;59(6):e743–63.

Lloret A, Esteve D, Lloret M-A, Cervera-Ferri A, Lopez B, Nepomuceno M, et al. When Does Alzheimer′s Disease Really Start? The Role of Biomarkers. Int J Mol Sci. 2019;20(22):5536.

Williams-Gray CH, Mason SL, Evans JR, Foltynie T, Brayne C, Robbins TW, et al. The CamPaIGN study of Parkinson’s disease: 10-year outlook in an incident population-based cohort. J Neurol Neurosurg Psychiatry. 2013;84(11):1258–64.

Walker Z, Possin KL, Boeve BF, Aarsland D. Lewy body dementias. Lancet. 2015;386(10004):1683–97.

Svenningsson P, Westman E, Ballard C, Aarsland D. Cognitive impairment in patients with Parkinson’s disease: diagnosis, biomarkers, and treatment. Lancet Neurol. 2012;11(8):697–707.

Pedersen KF, Larsen JP, Tysnes O-B, Alves G. Prognosis of Mild Cognitive Impairment in Early Parkinson Disease: The Norwegian ParkWest Study. JAMA Neurol. 2013;70(5):580–6.

Williams-Gray CH, Evans JR, Goris A, Foltynie T, Ban M, Robbins TW, et al. The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of the CamPaIGN cohort. Brain. 2009;132(11):2958–69.

Aarsland D, Kvaløy JT, Andersen K, Larsen JP, Tang MX, Lolk A, et al. The effect of age of onset of PD on risk of dementia. J Neurol. 2007;254(1):38–45.

Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer’s disease. Lancet. 2011;377(9770):1019–31.

Bobinski M, de Leon MJ, Wegiel J, DeSanti S, Convit A, Saint Louis LA, et al. The histological validation of post mortem magnetic resonance imaging-determined hippocampal volume in Alzheimer’s disease. Neuroscience. 1999;95(3):721–5.

Dubois B, Feldman HH, Jacova C, DeKosky ST, Barberger-Gateau P, Cummings J, et al. Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS–ADRDA criteria. Lancet Neurol. 2007;6(8):734–46.

Jack CR, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9(1):119–28.

Scheltens P, Blennow K, Breteler MMB, de Strooper B, Frisoni GB, Salloway S, et al. Alzheimer’s disease. Lancet. 2016;388(10043):505–17.

Frisoni GB, Fox NC, Jack CR, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010;6(2):67–77.

Fiandaca MS, Mapstone ME, Cheema AK, Federoff HJ. The critical need for defining preclinical biomarkers in Alzheimer’s disease. Alzheimers Dement. 2014;10(3S):S196–212.

Val JL, Bradley JK, Clifford R, Jack Jr, Matthew S, Stephen W, Maria S, et al. Comparison of 18 F-FDG and PiB PET in Cognitive Impairment. J Nucl Med. 2009;50(6):878.

Toledo JB, Xie SX, Trojanowski JQ, Shaw LM. Longitudinal change in CSF Tau and Aβ biomarkers for up to 48 months in ADNI. Acta Neuropathol. 2013;126(5):659–70.

Ewers M, Brendel M, Rizk-Jackson A, Rominger A, Bartenstein P, Schuff N, et al. Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects. Neuroimage Clin. 2014;4:45–52.

Martin SB, Smith CD, Collins HR, Schmitt FA, Gold BT. Evidence that volume of anterior medial temporal lobe is reduced in seniors destined for mild cognitive impairment. Neurobiol Aging. 2010;31(7):1099–106.

Dickerson BC, Stoub TR, Shah RC, Sperling RA, Killiany RJ, Albert MS, et al. Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults. Neurology. 2011;76(16):1395.

Bradford CD, David AW. MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults. Neurology. 2012;78(2):84.

Fox NC, Crum WR, Scahill RI, Stevens JM, Janssen JC, Rossor MN. Imaging of onset and progression of Alzheimer’s disease with voxel-compression mapping of serial magnetic resonance images. Lancet. 2001;358(9277):201–5.

Jayaraj RL, Rodriguez EA, Wang Y, Block ML. Outdoor Ambient Air Pollution and Neurodegenerative Diseases: the Neuroinflammation Hypothesis. Curr Environ Health Rep. 2017;4(2):166–79.

Araujo JA, Barajas B, Kleinman M, Wang X, Bennett BJ, Gong KW, et al. Ambient Particulate Pollutants in the Ultrafine Range Promote Early Atherosclerosis and Systemic Oxidative Stress. Circ Res. 2008;102(5):589–96.

Cheng L, Lau WKW, Fung TKH, Lau BWM, Chau BKH, Liang Y, et al. PM 2.5 Exposure Suppresses Dendritic Maturation in Subgranular Zone in Aged Rats. Neurotox Res. 2017;32(1):50–7.

Ku T, Li B, Gao R, Zhang Y, Yan W, Ji X, et al. NF-κB-regulated microRNA-574-5p underlies synaptic and cognitive impairment in response to atmospheric PM 2.5 aspiration. Part Fibre Toxicol. 2017;14(1):34.

Liu X, Qian X, Xing J, Wang J, Sun Y, Wang Qg, et al. Particulate Matter Triggers Depressive-Like Response Associated With Modulation of Inflammatory Cytokine Homeostasis and Brain-Derived Neurotrophic Factor Signaling Pathway in Mice. Toxicol Sci. 2018;164(1):278–88.

Weuve J, Puett RC, Schwartz J, Yanosky JD, Laden F, Grodstein F. Exposure to Particulate Air Pollution and Cognitive Decline in Older Women. Arch Intern Med. 2012;172(3):219–27.

Tonne C, Elbaz A, Beevers S, Singh-Manoux A. Traffic-related air pollution in relation to cognitive function in older adults. Epidemiology. 2014;25(5):674–81.

Wurth R, Kioumourtzoglou MA, Tucker KL, Griffith J, Manjourides J, Suh H. Fine Particle Sources and Cognitive Function in An Older Puerto Rican Cohort in Greater Boston. Environ Epidemiol. 2018;2(3): e022.

Gallagher M, Koh MT. Episodic memory on the path to Alzheimer’s disease. Curr Opin Neurobiol. 2011;21(6):929–34.

Aisen PS, Cummings J, Jack CR, Morris JC, Sperling R, Frölich L, et al. On the path to 2025: understanding the Alzheimer’s disease continuum. Alzheimers Res Ther. 2017;9(1):60.

Dickerson BC, Eichenbaum H. The Episodic Memory System: Neurocircuitry and Disorders. Neuropsychopharmacology. 2010;35(1):86–104.

Zhao W, W, Wang X, X, Yin C, He M, Li S, Han Y. Trajectories of the Hippocampal Subfields Atrophy in the Alzheimer’s Disease: A Structural Imaging Study. Front Neuroinform. 2019;13:13.

Fonken LK, Xu X, Weil ZM, Chen G, Sun Q, Rajagopalan S, et al. Air pollution impairs cognition, provokes depressive-like behaviors and alters hippocampal cytokine expression and morphology. Mol Psychiatry. 2011;16(10):987–95.

Davis DA, Akopian G, Walsh JP, Sioutas C, Morgan TE, Finch CE. Urban air pollutants reduce synaptic function of CA1 neurons via an NMDA/NȮ pathway in vitro. J Neurochem. 2013;127(4):509–19.

Woodward NC, Pakbin P, Saffari A, Shirmohammadi F, Haghani A, Sioutas C, et al. Traffic-related air pollution impact on mouse brain accelerates myelin and neuritic aging changes with specificity for CA1 neurons. Neurobiol Aging. 2017;53:48–58.

Zammit AR, Ezzati A, Zimmerman ME, Lipton RB, Lipton ML, Katz MJ. Roles of hippocampal subfields in verbal and visual episodic memory. Behav Brain Res. 2017;317:157–62.

Casanova R, Wang X, Reyes J, Akita Y, Serre ML, Vizuete W, et al. A Voxel-Based Morphometry Study Reveals Local Brain Structural Alterations Associated with Ambient Fine Particles in Older Women. Front Hum Neurosci. 2016;10:495.

Chen J-C, Wang X, Wellenius GA, Serre ML, Driscoll I, Casanova R, et al. Ambient air pollution and neurotoxicity on brain structure: Evidence from women’s health initiative memory study. Ann Neurol. 2015;78(3):466–76.

Cho J, Noh Y, Kim SY, Sohn J, Noh J, Kim W, et al. Long-term ambient air pollution exposures and brain imaging markers in Korean adults: the Environmental Pollution-Induced Neurological EFfects (EPINEF) study. Environ Health Perspect. 2020;128(11).

Power MC, Lamichhane AP, Liao D, Xu X, Jack CR, Gottesman RF, et al. The association of long-term exposure to particulate matter air pollution with brain MRI findings: the ARIC study. Environ Health Perspect. 2018;126(2): 027009.

Wilker EH, Preis SR, Beiser AS, Wolf PA, Au R, Kloog I, et al. Long-term exposure to fine particulate matter, residential proximity to major roads and measures of brain structure. Stroke. 2015;46(5):1161–6.

Bejanin A, Schonhaut DR, La Joie R, Kramer JH, Baker SL, Sosa N, et al. Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease. Brain. 2017;140(12):3286–300.

Jagust W. Imaging the evolution and pathophysiology of Alzheimer disease. Nat Rev Neurosci. 2018;19(11):687–700.

Harrison TM, La Joie R, Maass A, Baker SL, Swinnerton K, Fenton L, et al. Longitudinal tau accumulation and atrophy in aging and alzheimer disease. Ann Neurol. 2019;85(2):229–40.

Power MC, Adar SD, Yanosky JD, Weuve J. Exposure to air pollution as a potential contributor to cognitive function, cognitive decline, brain imaging, and dementia: A systematic review of epidemiologic research. Neurotoxicology. 2016;56:235–53.

Schwartz M, Deczkowska A. Neurological Disease as a Failure of Brain-Immune Crosstalk: The Multiple Faces of Neuroinflammation. Trends Immunol. 2016;37(10):668–79.

Zhu X, Raina AK, Lee H-g, Casadesus G, Smith MA, Perry G. Oxidative stress signalling in Alzheimer’s disease. Brain Res. 2004;1000(1–2):32–9.

Gruzieva O, Merid SK, Gref A, Gajulapuri A, Lemonnier N, Ballereau S, et al. Exposure to traffic-related air pollution and serum inflammatory cytokines in children. Environ Health Perspect. 2017;125(6).

Alemany S, Crous-Bou M, Vilor-Tejedor N, Milà-Alomà M, Suárez-Calvet M, Salvadó G, et al. Associations between air pollution and biomarkers of Alzheimer’s disease in cognitively unimpaired individuals. Environ Int. 2021;157.

Ma Y-H, Chen H-S, Liu C, Feng Q-S, Feng L, Zhang Y-R, et al. Association of Long-term Exposure to Ambient Air Pollution With Cognitive Decline and Alzheimer’s Disease-Related Amyloidosis. Biol Psychiatry. 2023;93(9):780–9.

Jack CR, Holtzman DM. Biomarker modeling of Alzheimer’s disease. Neuron. 2013;80(6):1347–58.

Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, et al. Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12(3):292–323.

Buchhave P, Minthon L, Zetterberg H, Wallin ÅK, Blennow K, Hansson O. Cerebrospinal Fluid Levels ofβ-Amyloid 1–42, but Not of Tau, Are Fully Changed Already 5 to 10 Years Before the Onset of Alzheimer Dementia. Arch Gen Psychiatry. 2012;69(1):98–106.

Calderón-Garcidueñas L, Solt AC, Henríquez-Roldán C, Torres-Jardón R, Nuse B, Herritt L, et al. Long-term air pollution exposure is associated with neuroinflammation, an altered innate immune response, disruption of the blood-brain barrier, ultrafine particulate deposition, and accumulation of amyloid β-42 and α-synuclein in children and young adults. Toxicol Pathol. 2008;36(2):289–310.

Fu M, Wang H, Bai Q, Du J, Niu Q, Nie J. Urinary polycyclic aromatic hydrocarbon metabolites, plasma p-tau231 and mild cognitive impairment in coke oven workers. Chemosphere. 2022;307.

Cleveland DW, Hwo S-Y, Kirschner MW. Physical and chemical properties of purified tau factor and the role of tau in microtubule assembly. J Mol Biol. 1977;116(2):227–47.

Medeiros R, Baglietto-Vargas D, LaFerla FM. The Role of Tau in Alzheimer’s Disease and Related Disorders. CNS Neurosci Ther. 2011;17(5):514–24.

Suárez-Calvet M, Karikari TK, Ashton NJ, Lantero Rodriguez J, Milà-Alomà M, Gispert JD, et al. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer’s continuum when only subtle changes in Aβ pathology are detected. EMBO Mol Med. 2020;12(12).

Baek MS, Lee MJ, Kim H-K, Lyoo CH. Temporal trajectory of biofluid markers in Parkinson’s disease. Sci Rep. 2021;11(1):14820.

Nie J, Duan L, Yan Z, Niu Q. Tau Hyperphosphorylation is Associated with Spatial Learning and Memory After Exposure to Benzo[a]pyrene in SD Rats. Neurotox Res. 2013;24(4):461–71.

Isaksen JL, Ghouse J, Skov MW, Olesen MS, Holst AG, Pietersen A, et al. Associations between primary care electrocardiography and non-Alzheimer dementia. Journal of Stroke and Cerebrovasc Dis. 2022;31(9).

Kuang H, Zhou ZF, Zhu YG, Wan ZK, Yang MW, Hong FF, et al. Pharmacological Treatment of Vascular Dementia: A Molecular Mechanism Perspective. Aging Dis. 2021;12(1):308–26.

O’Brien JT, Thomas A. Vascular dementia. Lancet. 2015;386(10004):1698–706.

Aarsland D, Creese B, Politis M, Chaudhuri KR, ffytche DH, Weintraub D, et al. Cognitive decline in Parkinson disease. Nat Rev Neurol. 2AD;13(4):217–31.

Bang J, Spina S, Miller BL. Frontotemporal dementia. Lancet. 2015;386(10004):1672–82.

Ashton NJ, Hye A, Rajkumar AP, Leuzy A, Snowden S, Suárez-Calvet M, et al. An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders. Nat Rev Neurol. 2020;16(5):265–84.

Künzli N, Jerrett M, Mack Wendy J, Beckerman B, LaBree L, Gilliland F, et al. Ambient Air Pollution and Atherosclerosis in Los Angeles. Environ Health Perspect. 2005;113(2):201–6.

Sweeney MD, Ayyadurai S, Zlokovic BV. Pericytes of the neurovascular unit: key functions and signaling pathways. Nat Neurosci. 2016;19(6):771–83.

Pandey T, Abubacker S. Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy: An Imaging Mimic of Multiple Sclerosis. Med Princ Pract. 2006;15(5):391–5.

Romay MC, Toro C, Iruela-Arispe ML. Emerging molecular mechanisms of vascular dementia. Curr Opin Hematol. 2019;26(3):199–206.

Wardlaw JM, Smith C, Dichgans M. Small vessel disease: mechanisms and clinical implications. Lancet Neurol. 2019;18(7):684–96.

Kalaria RN. Neuropathological diagnosis of vascular cognitive impairment and vascular dementia with implications for Alzheimer’s disease. Acta Neuropathol. 2016;131(5):659–85.

Iadecola C. The Pathobiology of Vascular Dementia. Neuron. 2013;80(4):844–66.

Kalaria RN. The pathology and pathophysiology of vascular dementia. Neuropharmacology. 2018;134:226–39.

Du S-Q, Wang X-R, Xiao L-Y, Tu J-F, Zhu W, He T, et al. Molecular Mechanisms of Vascular Dementia: What Can Be Learned from Animal Models of Chronic Cerebral Hypoperfusion? Mol Neurobiol. 2017;54(5):3670–82.

Wolters FJ, Zonneveld HI, Hofman A, Van Der Lugt A, Koudstaal PJ, Vernooij MW, et al. Cerebral perfusion and the risk of dementia: a population-based study. Circulation. 2017;136(8):719–28.

Benedictus MR, Binnewijzend MAA, Kuijer JPA, Steenwijk MD, Versteeg A, Vrenken H, et al. Brain volume and white matter hyperintensities as determinants of cerebral blood flow in Alzheimer’s disease. Neurobiol Aging. 2014;35(12):2665–70.

Babadjouni R, Patel A, Liu Q, Shkirkova K, Lamorie-Foote K, Connor M, et al. Nanoparticulate matter exposure results in neuroinflammatory changes in the corpus callosum. PLoS ONE. 2018;13(11).

Liu Q, Radwanski R, Babadjouni R, Patel A, Hodis DM, Baumbacher P, et al. Experimental chronic cerebral hypoperfusion results in decreased pericyte coverage and increased blood–brain barrier permeability in the corpus callosum. J Cereb Blood Flow Metab. 2019;39(2):240–50.

Erickson LD, L D, Gale S D, Anderson J E, Brown B L, Hedges D W. Association between Exposure to Air Pollution and Total Gray Matter and Total White Matter Volumes in Adults: A Cross-Sectional Study. Brain Sci [Internet]. 2020;10(3):164.

Woodward NC, Levine MC, Haghani A, Shirmohammadi F, Saffari A, Sioutas C, et al. Toll-like receptor 4 in glial inflammatory responses to air pollution in vitro and in vivo. J Neuroinflammation. 2017;14(1):84.

Emre M, Aarsland D, Brown R, Burn DJ, Duyckaerts C, Mizuno Y, et al. Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov Disord. 2007;22(12):1689–707.

Aarsland D, Zaccai J, Brayne C. A systematic review of prevalence studies of dementia in Parkinson’s disease. Mov Disord. 2005;20(10):1255–63.

Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30(12):1591–601.

Goetz CG, Emre M, Dubois B. Parkinson’s disease dementia: Definitions, guidelines, and research perspectives in diagnosis. Ann Neurol. 2008;64(S2):S81–92.

Elobeid A, Libard S, Leino M, Popova SN, Alafuzoff I. Altered Proteins in the Aging Brain. J Neuropathol Exp Neurol. 2016;75(4):316–25.

Kovacs G G. Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine. Int J Mol Sci [Internet]. 2016;17(2):189.

Calderón-Garcidueñas L, Ayala A. Air Pollution, Ultrafine Particles, and Your Brain: Are Combustion Nanoparticle Emissions and Engineered Nanoparticles Causing Preventable Fatal Neurodegenerative Diseases and Common Neuropsychiatric Outcomes? Environ Sci Technol. 2022;56(11):6847–56.

Calderón-Garcidueñas L, Gónzalez-Maciel A, Reynoso-Robles R, Delgado-Chávez R, Mukherjee PS, Kulesza RJ, et al. Calderón-Garcidueñas L, Gónzalez-Maciel A, Reynoso-Robles R, Delgado-Chávez R, Mukherjee PS, Kulesza RJ, et al. Hallmarks of Alzheimer disease are evolving relentlessly in Metropolitan Mexico City infants, children and young adults. APOE4 carriers have higher suicide risk and higher odds of reaching NFT stage V at ≤ 40 years of age. Environ Res. 2018;164:475–87. Environ Res. 2018;164:475–87.

Calderón-Garcidueñas L, González-Maciel A, Reynoso-Robles R, Hammond J, Kulesza R, Lachmann I, et al. Quadruple abnormal protein aggregates in brainstem pathology and exogenous metal-rich magnetic nanoparticles (and engineered Ti-rich nanorods). The substantia nigrae is a very early target in young urbanites and the gastrointestinal tract a key brainstem portal. Environ Res. 2020;191:110139.

Fiondella L, Mattioli I, Salemme S, Carbone C, Vinceti G, Tondelli M, et al. The brain correlates of behavioral disturbances in frontotemporal dementia. Alzheimers Dement. 2021;17(S6).

Rosen HJ, Gorno-Tempini ML, Goldman WP, Perry RJ, Schuff N, Weiner M, et al. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology. 2002;58(2):198.

Woollacott IOC, Rohrer JD. The clinical spectrum of sporadic and familial forms of frontotemporal dementia. J Neurochem. 2016;138(S1):6–31.

Ber IL, Guedj E, Gabelle A, Verpillat P, Volteau M, Thomas-Anterion C, et al. Demographic, neurological and behavioural characteristics and brain perfusion SPECT in frontal variant of frontotemporal dementia. Brain. 2006;129(11):3051–65.

Tang J, Chen A, He F, Shipley M, Nevill A, Coe H, et al. Association of air pollution with dementia: a systematic review with meta-analysis including new cohort data from China. Environ Res. 2023;223.

Abolhasani E, Hachinski V, Ghazaleh N, Azarpazhooh MR, Mokhber N, Martin J. Air Pollution and Incidence of Dementia. Neurology. 2023;100(2):e242–54.

Peters R, Ee N, Peters J, Booth A, Mudway I, Anstey KJ. Air pollution and dementia: a systematic review. J Alzheimer’s Dis. 2019;70(s1):S145–63.

Delgado-Saborit JM, Guercio V, Gowers AM, Shaddick G, Fox NC, Love S. A critical review of the epidemiological evidence of effects of air pollution on dementia, cognitive function and cognitive decline in adult population. Sci Total Environ. 2021;757.

Xu X, Ha SU, Basnet R. Basnet R. A Review of Epidemiological Research on Adverse Neurological Effects of Exposure to Ambient Air Pollution. Front Public Health. 2016;4:157.

Stern Y. Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurol. 2012;11(11):1006–12.

Xu H, Dupre ME, Gu D, Wu B. The impact of residential status on cognitive decline among older adults in China: Results from a longitudinal study. BMC Geriatr. 2017;17(1):107.

Download references

Acknowledgements

No funding was secured for this study.

Author information

Authors and affiliations.

Department of Health in Emergencies and Disasters, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Mahdiyeh Mohammadzadeh

Climate Change and Health Research Center (CCHRC), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran

Department of Occupational Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran

Amir Hossein Khoshakhlagh

Department of Physical Medicine & Rehabilitation, Neurology, Cognitive Neurology and Alzheimer’s Center, Department of Psychiatry, Feinberg School of Medicine & Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Chicago, IL, USA

Jordan Grafman

You can also search for this author in PubMed Google Scholar

Contributions

M.M and A.H. Kh conceptualized the study and were involved in screening and data extraction. All authors were involved in the interpretation of the findings. M.M wrote the first draft. All authors were involved in the scientific processes leading up to the writing of the manuscript and contributed to the interpretation of the findings and the critical evaluation of the final version of the manuscript.

Corresponding author

Correspondence to Amir Hossein Khoshakhlagh .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: appendix a1. supplementary material online: search queries., additional file 2: appendix a2. air pollution and alzheimer’s dementia., additional file 3: appendix a3. air pollution and non-alzheimer’s dementia., rights and permissions.

Reprints and permissions

About this article

Cite this article.

Mohammadzadeh, M., Khoshakhlagh, A.H. & Grafman, J. Air pollution: a latent key driving force of dementia. BMC Public Health 24 , 2370 (2024). https://doi.org/10.1186/s12889-024-19918-4

Download citation

Received : 05 June 2024

Accepted : 28 August 2024

Published : 02 September 2024

DOI : https://doi.org/10.1186/s12889-024-19918-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Vascular dementia
Non-Alzheimer dementia
Air pollution

BMC Public Health

ISSN: 1471-2458

General enquiries: [email protected]

Open access
Published: 30 August 2024

Research landscape analysis on dual diagnosis of substance use and mental health disorders: key contributors, research hotspots, and emerging research topics

Waleed M. Sweileh 1

Annals of General Psychiatry volume 23 , Article number: 32 ( 2024 ) Cite this article

Metrics details

Substance use disorders (SUDs) and mental health disorders (MHDs) are significant public health challenges with far-reaching consequences on individuals and society. Dual diagnosis, the coexistence of SUDs and MHDs, poses unique complexities and impacts treatment outcomes. A research landscape analysis was conducted to explore the growth, active countries, and active journals in this field, identify research hotspots, and emerging research topics.

A systematic research landscape analysis was conducted using Scopus to retrieve articles on dual diagnosis of SUDs and MHDs. Inclusion and exclusion criteria were applied to focus on research articles published in English up to December 2022. Data were processed and mapped using VOSviewer to visualize research trends.

A total of 935 research articles were found. The number of research articles on has been increasing steadily since the mid-1990s, with a peak of publications between 2003 and 2012, followed by a fluctuating steady state from 2013 to 2022. The United States contributed the most articles (62.5%), followed by Canada (9.4%). The Journal of Dual Diagnosis , Journal of Substance Abuse Treatment , and Mental Health and Substance Use Dual Diagnosis were the top active journals in the field. Key research hotspots include the comorbidity of SUDs and MHDs, treatment interventions, quality of life and functioning, epidemiology, and the implications of comorbidity. Emerging research topics include neurobiological and psychosocial aspects, environmental and sociocultural factors, innovative interventions, special populations, and public health implications.

Conclusions

The research landscape analysis provides valuable insights into dual diagnosis research trends, active countries, journals, and emerging topics. Integrated approaches, evidence-based interventions, and targeted policies are crucial for addressing the complex interplay between substance use and mental health disorders and improving patient outcomes.

Introduction

Substance use disorders (SUDs) refer to a range of conditions characterized by problematic use of psychoactive substances, leading to significant impairment in physical, psychological, and social functioning [ 1 ]. These substances may include alcohol, tobacco, illicit drugs (e.g., cocaine, opioids, cannabis), and prescription medications. The global burden of SUDs is substantial, with far-reaching consequences on public health, socio-economic development, and overall well-being. For instance, alcohol abuse accounts for 3 million deaths worldwide annually, while the opioid crisis has escalated to unprecedented levels in certain regions, such as North America, resulting in tens of thousands of overdose deaths per year [ 2 , 3 , 4 ]. Mental health disorders (MHDs) encompass a wide range of conditions that affect mood, thinking, behavior, and emotional well-being [ 5 ]. Examples of MHDs include depression, anxiety disorders, post-traumatic stress disorder (PTSD), bipolar disorder, schizophrenia, and eating disorders. These conditions can significantly impair an individual's ability to function, negatively impacting their quality of life, relationships, and overall productivity [ 6 , 7 , 8 ]. Furthermore, certain MHD such as major depressive disorder and anxiety are often associated with specific affective temperaments, hopelessness, and suicidal behavior and grasping such connections can help in crafting customized interventions to reduce suicide risk [ 9 ]. In addition, a systematic review of 18 studies found that demoralization with somatic or psychiatric disorders is a significant independent risk factor for suicide and negative clinical outcomes across various populations [ 10 ]. The coexistence of SUDs and MHDs, often referred to as dual diagnosis or comorbidity, represents a complex and prevalent phenomenon that significantly impacts affected individuals and healthcare systems [ 11 , 12 , 13 , 14 , 15 ]. For instance, individuals with depression may be more likely to self-medicate with alcohol or drugs to cope with emotional distress [ 16 ]. Similarly, PTSD has been linked to increased rates of substance abuse, as individuals attempt to alleviate the symptoms of trauma [ 17 , 18 ]. Moreover, chronic substance use can lead to changes in brain chemistry, increasing the risk of developing MHDs or exacerbating existing conditions [ 17 , 19 , 20 , 21 ]. The coexistence of SUDs and MHDs presents unique challenges from a medical and clinical standpoint. Dual diagnosis often leads to more severe symptoms, poorer treatment outcomes, increased risk of relapse, and higher rates of hospitalization compared to either disorder alone [ 22 ]. Additionally, diagnosing and treating dual diagnosis cases can be complex due to overlapping symptoms and interactions between substances and psychiatric medications. Integrated treatment approaches that address both conditions simultaneously are essential for successful recovery and improved patient outcomes [ 20 ]. Patients grappling with dual diagnosis encounter a multifaceted web of barriers when attempting to access essential mental health services. These barriers significantly compound the complexity of their clinical presentation. The first barrier pertains to stigma, where societal prejudices surrounding mental health and substance use disorders deter individuals from seeking help, fearing discrimination or social repercussions [ 23 ]. A lack of integrated care, stemming from fragmented healthcare systems, poses another significant hurdle as patients often struggle to navigate separate mental health and addiction treatment systems [ 24 ]. Insurance disparities contribute by limiting coverage for mental health services and imposing strict criteria for reimbursement [ 25 ]. Moreover, there is a shortage of adequately trained professionals equipped to address both substance use and mental health issues, creating a workforce barrier [ 26 ]. Geographical disparities in access further hinder care, particularly in rural areas with limited resources [ 27 ]. These barriers collectively serve to exacerbate the clinical complexity of patients with dual diagnosis, and ultimately contributing to poorer outcomes.

A research landscape analysis involves a systematic review and synthesis of existing literature on a specific topic to identify key trends, knowledge gaps, and research priorities [ 28 , 29 ]. Scientific research landscape analysis, is motivated by various factors. First, the rapid growth of scientific literature poses a challenge for researchers to stay up-to-date with the latest developments in their respective fields. Research landscape analysis provides a structured approach to comprehend the vast body of literature, identifying crucial insights and emerging trends. Additionally, it plays a vital role in identifying knowledge gaps, areas with limited research, or inadequate understanding. This pinpointing allows researchers to focus on critical areas that demand further investigation, fostering more targeted and impactful research efforts [ 30 ]. Furthermore, in the realm of policymaking and resource allocation, evidence-based decision-making is crucial. Policymakers and funding agencies seek reliable information to make informed decisions about research priorities. Research landscape analysis offers a comprehensive view of existing evidence, facilitating evidence-based decision-making processes [ 28 ]. When it comes to the research landscape analysis of dual diagnosis of SUDs and MHDs, there are several compelling justifications to explore this complex comorbidity and gain a comprehensive understanding of its interplay and impact on patient outcomes. Firstly, the complexity of the interplay between SUDs and MHDs demands a comprehensive examination of current research to unravel the intricacies of this comorbidity [ 31 ]. Secondly, dual diagnosis presents unique challenges for treatment and intervention strategies due to the overlapping symptoms and interactions between substances and psychiatric medications. A research landscape analysis can shed light on effective integrated treatment approaches and identify areas for improvement [ 18 ]. Moreover, the public health impact of co-occurring SUDs and MHDs is substantial, resulting in more severe symptoms, poorer treatment outcomes, increased risk of relapse, and higher rates of hospitalization. Understanding the research landscape can inform public health policies and interventions to address this issue more effectively [ 32 ]. Lastly, the holistic approach of research landscape analysis enables a comprehensive understanding of current knowledge, encompassing epidemiological data, risk factors, treatment modalities, and emerging interventions. This integrative approach can lead to more coordinated and effective care for individuals with dual diagnosis [ 22 ]. Based on the above argument, the current study aims to conduct a research landscape analysis of dual diagnosis of SUDs and MHDs. The research landscape analysis bears a lot of significance for individuals and society. First and foremost, it’s a beacon of hope for individuals seeking help. Research isn’t just about dry statistics; it's about finding better ways to treat and support those facing dual diagnosis. By being informed about the latest breakthroughs, healthcare professionals can offer more effective, evidence-backed care, opening the door to improved treatment outcomes and a brighter future for those they serve. Beyond the individual level, this understanding has profound societal implications. It has the power to chip away at the walls of stigma that often surround mental health and substance use issues. Greater awareness and knowledge about the complexities of dual diagnosis can challenge stereotypes and biases, fostering a more compassionate and inclusive society. Additionally, society allocates resources based on research findings. When we understand the prevalence and evolving nature of dual diagnosis, policymakers and healthcare leaders can make informed decisions about where to channel resources most effectively. This ensures that the needs of individuals struggling with co-occurring disorders are not overlooked or under-prioritized. Moreover, research helps identify risk factors and early warning signs related to dual diagnosis. Armed with this information, we can develop prevention strategies and early intervention programs, potentially reducing the incidence of co-occurring disorders and mitigating their impact. Legal and criminal justice systems also stand to benefit. Understanding dual diagnosis trends can inform policies related to diversion programs, treatment alternatives to incarceration, and the rehabilitation of individuals with co-occurring disorders, potentially reducing rates of reoffending. Moreover, dual diagnosis research contributes to public health planning by highlighting the need for integrated mental health and addiction services. This knowledge can guide the development of comprehensive healthcare systems that offer holistic care to individuals with co-occurring disorders. Families and communities, too, are vital players in this narrative. With a grasp of research findings, they can provide informed, empathetic, and effective support to their loved ones, contributing to better outcomes.

The present research landscape analysis of dual diagnosis of SUDs and MHDs was conducted using a systematic approach to retrieve, process, and analyze relevant articles. The following methodology outlines the key steps taken to address the research questions:

Research Design The present study constitutes a thorough and robust analysis of the research landscape concerning the dual diagnosis of SUD and MHD. It's important to note that the research landscape analysis differs from traditional systematic or scoping reviews. In conducting research landscape analysis, we made deliberate methodological choices aimed at achieving both timely completion and unwavering research quality. These choices included a strategic decision to focus our search exclusively on a single comprehensive database, a departure from the customary practice of utilizing multiple databases. Furthermore, we streamlined the quality control process by assigning specific quality checks to a single author, rather than following the conventional dual-reviewer approach. This approach prioritized efficiency and expediency without compromising the rigor of our analysis. To expedite the research process further, we opted for a narrative synthesis instead of a quantitative one, ensuring that we provide a succinct yet highly informative summary of the available evidence. We place a premium on research transparency and, as such, are committed to sharing the detailed search string employed for data retrieval. This commitment underscores our dedication to fostering reproducibility and transparency in research practices.

Ethical considerations Since the research landscape analysis involved the use of existing and publicly available literature, and no human subjects were directly involved, no formal ethical approval was required.

Article retrieval Scopus, a comprehensive bibliographic database, was utilized to retrieve articles related to the dual diagnosis of SUDs and MHDs. Scopus is a multidisciplinary abstract and citation database that covers a wide range of scientific disciplines, including life sciences, physical sciences, social sciences, and health sciences. It includes content from thousands of scholarly journals.

Keywords used To optimize the search process and ensure the inclusion of pertinent articles, a set of relevant keywords and equivalent terms were employed. Keywords for “dual diagnosis” included dual diagnosis, co-occurring disorders, comorbid substance use, comorbid addiction, coexisting substance use, combined substance use, simultaneous substance use, substance use and psychiatric, co-occurring substance use and psychiatric, concurrent substance use and mental, coexisting addiction and mental, combined addiction and mental, simultaneous addiction and mental, substance-related and psychiatric, comorbid mental health and substance use, co-occurring substance use and psychiatric, concurrent mental health and substance use, coexisting mental health and substance use, combined mental health and substance use, simultaneous mental health and substance use, substance-related and coexisting psychiatric, comorbid psychiatric and substance abuse, co-occurring mental health and substance-related, concurrent psychiatric and substance use, coexisting psychiatric and substance abuse, combined psychiatric and substance use, simultaneous psychiatric and substance use, substance-related and concurrent mental, substance abuse comorbidity. Keywords for “Substance use disorders” included substance abuse, substance dependence, drug use disorders, addiction, substance-related disorders, drug abuse, opioid use disorder, cocaine use disorder, alcohol use disorder, substance misuse, substance use disorder, substance-related, substance addiction. Keywords for “Mental health disorders” included psychiatric disorders, mental illnesses, mental disorders, emotional disorders, psychological disorders, schizophrenia, depression, PTSD, ADHD, anxiety, bipolar disorder, eating disorders, personality disorders, mood disorders, psychotic disorders, mood and anxiety disorders, mental health conditions. To narrow down the search to focus specifically on dual diagnosis, we adopted a strategy that involved the simultaneous presence of SUDs and MHDs in the presence of specific keywords in the titles and abstracts such as “dual,” “co-occurring,” “concurrent,” “co-occurring disorders,” “dual disorders,” “dual diagnosis,” “comorbid psychiatric,” “cooccurring psychiatric,” “comorbid*,” and “coexisting”.

Inclusion and exclusion criteria To maintain the study’s focus and relevance, specific inclusion and exclusion criteria were applied. Included articles were required to be research article, written in English, and published in peer-reviewed journals up to December 31, 2022, Articles focusing on animal studies, internet addiction, obesity, pain, and validity of instruments and tools were excluded.

Flow chart of the search strategy Supplement 1 shows the overall search strategy and the number of articles retrieved in each step. The total number of research articles that met the inclusion and exclusion criteria were 935.

Validation of search strategy The effectiveness of our search strategy was rigorously assessed through three distinct methods, collectively demonstrating its ability to retrieve pertinent articles while minimizing false positives. First, to gauge precision, we meticulously examined a sample of 30 retrieved articles, scrutinizing their alignment with our research question and their contributions to the topic of dual diagnosis. This manual review revealed that the majority of the assessed articles were highly relevant to our research focus. Second, for a comprehensive evaluation, we compared the articles obtained through our search strategy with a set of randomly selected articles from another source. This set comprised 10 references sourced from Google Scholar [ 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ], and the aim was to determine if our strategy successfully identified articles selected at random from an alternative database. Impressively, our analysis showed that the search strategy had a notably high success rate in capturing these randomly selected articles. Lastly, to further corroborate the relevance of our retrieved articles, we investigated the research interests of the top 10 active authors and the subject scope of the top 10 active journals. This exploration confirmed that their areas of expertise and the journal scopes were in alignment with the field of mental health and/or substance use disorders. These three validation methods collectively reinforce the reliability of our search strategy, affirming that the vast majority of the retrieved articles are indeed pertinent to our research inquiry.

Data processing and mapping Data extracted from the selected articles were processed and organized using Microsoft Excel. Information on the titles/abstracts/author keywords, year of publication, journal name, authors, institution and country affiliation, and number of citations received by the article were extracted. To visualize and analyze the research landscape, VOSviewer, a bibliometric analysis tool, was employed [ 43 ]. This software enables mapping and clustering of co-occurring terms, authors, and countries, providing a comprehensive overview of the dual diagnosis research domain.

Interpreting VOSviewer maps and generating research topics

We conducted a rigorous analysis and generated a comprehensive research landscape using VOSviewer, a widely acclaimed software tool renowned for its expertise in mapping research domains. We seamlessly integrated pertinent data extracted from the Scopus database, including publication metadata, into VOSviewer to delve into the frequency of author keywords and terminologies. The resulting visualizations provided us with profound insights into the intricate web of interconnected research topics and their relationships within the field. Interpreting VOSviewer maps is akin to navigating a vibrant and interconnected tapestry of knowledge. Each term or keyword in the dataset is depicted as a point on the map, represented by a circle or node. These nodes come in varying sizes and colors and are interconnected by lines of differing thicknesses. The size of a node serves as an indicator of the term’s significance or prevalence within the dataset. Larger nodes denote that a specific term is frequently discussed or plays a pivotal role in the body of research, while smaller nodes signify less commonly mentioned concepts. The colors assigned to these nodes serve a dual purpose. Firstly, they facilitate the categorization of terms into thematic groups, with terms of the same color typically belonging to the same cluster or sharing a common thematic thread. Secondly, they aid in the identification of distinct research clusters or thematic groups within the dataset. For instance, a cluster of blue nodes might indicate that these terms are all associated with a particular area of research. The spatial proximity of nodes on the map reflects their closeness in meaning or concept. Nodes positioned closely together share a robust semantic or contextual connection and are likely to be co-mentioned in research articles or share a similar thematic focus. Conversely, nodes situated farther apart indicate less commonality in terms of their usage in the literature. The lines that link these nodes represent the relationships between terms. The thickness of these lines provides insights into the strength and frequency of these connections. Thick lines indicate that the linked terms are frequently discussed together or exhibit a robust thematic association, while thinner lines imply weaker or less frequent connections. In essence, VOSviewer maps offer a visual narrative of the underlying structure and relationships within your dataset. By examining node size and color, you can pinpoint pivotal terms and thematic clusters. Simultaneously, analyzing the distance between nodes and line thickness unveils the semantic closeness and strength of associations between terms. These visual insights are invaluable for researchers seeking to unearth key concepts, identify research clusters, and track emerging trends within their field of study.

Growth pattern, active countries, and active journals

The growth pattern of the 935 research articles on dual diagnosis of substance use disorders and mental health disorders shows an increasing trend in the number of published articles over the years. Starting from the late 1980s and early 1990s with only a few publications, the research interest gradually picked up momentum, and the number of articles has been consistently rising since the mid-1990s. Table 1 shows the number of articles published in three different periods. The majority of publications (52.2%) were produced between 2003 and 2012, indicating a significant surge in research during that decade. The subsequent period from 2013 to 2022 saw a continued interest in the subject, accounting for 35.5% of the total publications. The number of articles published per year during the period from 2013 to 2022 showed a fluctuating steady state with an average of approximately 33 articles per year. The earliest period from 1983 to 2002 comprised 12.3% of the total publications, reflecting the initial stages of research and the gradual development of interest in the field.

Out of the total 935 publications, the United States contributed the most with 585 publications, accounting for approximately 62.5% of the total research output. Canada follows with 88 publications, making up around 9.4% of the total. The United Kingdom and Australia also made substantial contributions with 70 and 53 publications, accounting for 7.5 and 5.7%, respectively. Table 2 shows the top 10 active countries.

Based on the list of top active journals in the field of dual diagnosis of substance use and mental health disorders, it is evident that there are several reputable and specialized journals that focus on this important area of research (Table 3 ). These journals cover a wide range of topics related to dual diagnosis, including comorbidity, treatment approaches, intervention strategies, and epidemiological studies. The Journal of Dual Diagnosis appears to be a leading and comprehensive platform for research on dual diagnosis. It covers a broad spectrum of studies related to substance use disorders and mental health conditions. The Journal of Substance Abuse Treatment ranked second while the Mental Health and Substance Use Dual Diagnosis journal ranked third and seems to be dedicated specifically to the intersection of substance use disorder and mental health disorders, providing valuable insights and research findings related to comorbidities and integrated treatment approaches.

Most frequent author keywords

Mapping author keywords with a minimum occurrence of five (n = 96) provides insights in research related to dual diagnosis. Figure 1 shows the 96 author keywords and their links with other keywords. The number of occurrences represent the number of times each author keyword appears in the dataset, while the total link strength (TLS) indicates the combined strength of connections between keywords based on their co-occurrence patterns. The most frequent author keywords with high occurrences and TLS represent the key areas of focus in research on the dual diagnosis of substance use and mental health disorders.

“Comorbidity” is the most frequent keyword, with 144 occurrences and a high TLS of 356. This reflects the central theme of exploring the co-occurrence of substance use disorders and mental health conditions and their complex relationship. “Substance use disorder” and “dual diagnosis” are also highly prevalent keywords with 122 and 101 occurrences, respectively. These terms highlight the primary focus on studying individuals with both substance use disorders and mental health disorders, underscoring the significance of dual diagnosis in research. “Co-occurring disorders” and “substance use disorders” are frequently used, indicating a focus on understanding the relationship between different types of disorders and the impact of substance use on mental health. Several specific mental health disorders such as “schizophrenia,” “depression,” “bipolar disorder,” and “PTSD” are prominent keywords, indicating a strong emphasis on exploring the comorbidity of these disorders with substance use. “Mental health” and “mental illness” are relevant keywords, reflecting the broader context of research on mental health conditions and their interaction with substance use. “Treatment” is a significant keyword with 34 occurrences, indicating a focus on investigating effective interventions and treatment approaches for individuals with dual diagnosis. “Addiction” and “recovery” are important keywords, highlighting the interest in understanding the addictive nature of substance use and the potential for recovery in this population. The mention of “veterans” as a keyword suggests a specific focus on the dual diagnosis of substance use and mental health disorders in the veteran population. “Integrated treatment” is an important keyword, indicating an interest in studying treatment approaches that address both substance use and mental health disorders together in an integrated manner.

Network visualization map of author keywords with a minimum occurrence of five in the retrieved articles on dual diagnosis of substance use and mental health disorders

Most impactful research topics

To have an insight into the most impactful research topics on dual diagnosis, the top 100 research articles were visualized and the terms with the largest node size and TLS were used to. To come up with the five most common investigated research topics:

Dual diagnosis and comorbidity of SUDs and MHDs: This topic focuses on the co-occurrence of substance use disorders and various mental health conditions, such as schizophrenia, bipolar disorder, PTSD, anxiety disorders, and major depressive disorder. This research topic explored the prevalence, characteristics, and consequences of comorbidity in different populations, including veterans, adolescents, and individuals experiencing homelessness [ 13 , 19 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ].

Treatment and interventions for co-occurring disorders: This topic involves studies on different treatment approaches and interventions for individuals with dual diagnosis. These interventions may include motivational interviewing, cognitive-behavioral therapy, family intervention, integrated treatment models, assertive community treatment, and prolonged exposure therapy. The goal is to improve treatment outcomes and recovery for individuals with co-occurring substance use and mental health disorders [ 48 , 53 , 54 , 55 , 56 , 57 , 58 , 59 ].

Quality of life and functioning in individuals with dual diagnosis: This research topic explores the impact of dual diagnosis on the quality of life and functioning of affected individuals. It assesses the relationship between dual diagnosis and various aspects of well-being, including social functioning, physical health, and overall quality of life [ 60 , 61 , 62 , 63 , 64 ].

Epidemiology and prevalence of co-occurring disorders: This topic involves population-based studies that investigate the prevalence of comorbid substance use and mental health disorders. It examines the demographic and clinical correlates of dual diagnosis, as well as risk factors associated with the development of co-occurring conditions [ 50 , 52 , 60 , 65 , 66 , 67 ].

Implications and consequences of comorbidity: This research topic explores the consequences of comorbidity between substance use and mental health disorders, such as treatment utilization, service access barriers, criminal recidivism, and the impact on suicidality. It also investigates the implications of comorbidity for treatment outcomes and the potential risks associated with specific comorbidities [ 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 ].

Emerging research topics

Upon scrutinizing the titles, abstracts, author keywords, and a visualization map of the 100 recently published articles, the research themes listed below came to the forefront. It’s worth noting that some of the research themes in the 100 recently published articles were not groundbreaking; rather, they represented a natural progression of ongoing research endeavors, and that is why they were not listed as emerging research themes. For instance, there was a continuation of research into the prevalence and epidemiology of co-occurring mental illnesses and substance use disorders and characteristics of various cases of co-morbid cases of SUDs and MHDs. The list below included such emergent themes. It might seem that certain aspects within these research themes duplicate the initial research topics, but it’s crucial to emphasize that this is not the case. For example, both themes delve into investigations concerning treatment, yet the differentiation lies in the treatment approach adopted.

Neurobiological and psychosocial aspects of dual diagnosis: This research topic focuses on exploring the neurobiological etiology and underlying mechanisms of comorbid substance use and mental health disorders. It investigates brain regions, neurotransmitter systems, hormonal pathways, and other neurobiological factors contributing to the development and maintenance of dual diagnosis. Additionally, this topic may examine psychosocial aspects, such as trauma exposure, adverse childhood experiences, and social support, that interact with neurobiological factors in the context of comorbidity [ 76 ].

Impact of environmental and sociocultural factors on dual diagnosis: This research topic delves into the influence of environmental and sociocultural factors on the occurrence and course of comorbid substance use and mental health disorders. It may explore how cultural norms, socioeconomic status, access to healthcare, and societal attitudes toward mental health and substance use affect the prevalence, treatment outcomes, and quality of life of individuals with dual diagnosis [ 77 , 78 ].

New interventions and treatment approaches for dual diagnosis: This topic involves studies that propose and evaluate innovative interventions and treatment approaches for individuals with dual diagnosis. These interventions may include novel psychotherapeutic techniques, pharmacological treatments, digital health interventions, and integrated care models. The research aims to improve treatment effectiveness, adherence, and long-term recovery outcomes in individuals with comorbid substance use and mental health disorders [ 79 , 80 , 81 , 82 , 83 , 84 ].

Mental health and substance use in special populations with dual diagnosis: This research topic focuses on exploring the prevalence and unique characteristics of comorbid substance use and mental health disorders in specific populations, such as individuals with eating disorders, incarcerated individuals, and people with autism spectrum disorder. It aims to identify the specific needs and challenges faced by these populations and develop tailored interventions to address their dual diagnosis [ 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 ].

Public health implications and policy interventions for dual diagnosis: This topic involves research that addresses the public health implications of dual diagnosis and the need for policy interventions to address this complex issue. It may include studies on the economic burden of comorbidity, the impact on healthcare systems, and the evaluation of policy initiatives aimed at improving prevention, early intervention, and access to integrated care for individuals with dual diagnosis [ 81 , 96 , 97 , 98 , 99 , 100 , 101 ].

Comparison in research topics

The comparison between the most impactful research topics and emerging research topics in the field of dual diagnosis reveals intriguing insights into the evolving landscape of this critical area of study (Table 4 ). In the most impactful research topics, there is a strong emphasis on the epidemiology of dual diagnosis, indicating a well-established foundation in understanding the prevalence, characteristics, and consequences of comorbid SUDs and MHDs. Treatment and interventions also receive considerable attention, highlighting the ongoing efforts to improve outcomes and recovery for individuals with dual diagnosis. Quality of life and medical consequences are additional focal points, reflecting the concern for the holistic well-being of affected individuals and the health-related implications of comorbidity.

On the other hand, emerging research topics signify a shift towards newer methods and interventions. The exploration of neurobiology in the context of dual diagnosis reflects a growing interest in unraveling the underlying neurobiological mechanisms contributing to comorbidity. This shift suggests a deeper understanding of the neural pathways and potential targets for intervention. The consideration of dual diagnosis in special groups underscores a recognition of the unique needs and challenges faced by specific populations, such as individuals with autism spectrum disorder. This tailored approach acknowledges that one size does not fit all in addressing dual diagnosis. Finally, the exploration of environmental and psychosocial contexts highlights the importance of socio-cultural factors, policy interventions, and societal attitudes in shaping the experience of individuals with dual diagnosis, signaling a broader perspective that extends beyond clinical interventions. In summary, while the most impactful research topics have laid a strong foundation in epidemiology, treatment, quality of life, and medical consequences, the emerging research topics point to a promising future with a deeper dive into the neurobiology of dual diagnosis, a focus on special populations, and a broader consideration of the environmental and psychosocial context. This evolution reflects the dynamic nature of dual diagnosis research as it strives to advance our understanding and improve the lives of those affected by comorbid substance use and mental health disorders.

The main hypothesis underlying the study was that dual diagnosis, or the comorbidity of SUDs and MHDs, was historically underrecognized and under-researched. Over time, however, there has been a significant increase in understanding, appreciation, and research into this complex interplay in clinical settings. This was expected to manifest through a growing number of publications, increased attention to integrated treatment approaches, and a heightened recognition of the complexities and public health implications associated with dual diagnosis. The study aims to analyze this progression and its implications through a research landscape analysis, identifying key trends, knowledge gaps, and research priorities. The research landscape analysis of the dual diagnosis of SUDs and MHDs has unveiled a substantial and evolving body of knowledge, with a notable rise in publications since the mid-1990s and a significant surge between 2003 and 2012. This growing research interest underscores the increasing recognition of the importance and complexity of dual diagnosis in clinical and public health contexts. The United States has emerged as the most active contributor, followed by Canada, the United Kingdom, and Australia, with specialized journals such as the Journal of Dual Diagnosis playing a pivotal role in disseminating research findings. Common keywords such as “comorbidity,” “substance use disorder,” “dual diagnosis,” and specific mental health disorders highlight the primary focus areas, with impactful research topics identified as the comorbidity of SUDs and MHDs, treatment and interventions, quality of life, epidemiology, and the implications of comorbidity. Emerging research themes emphasize neurobiological and psychosocial aspects, the impact of environmental and sociocultural factors, innovative treatment approaches, and the needs of special populations with dual diagnosis, reflecting a shift towards a more holistic and nuanced understanding. The study highlights a shift from traditional epidemiological studies towards understanding the underlying mechanisms and broader social determinants of dual diagnosis, with a need for continued research into integrated treatment models, specific needs of diverse populations, and the development of tailored interventions.

The findings of this research landscape analysis have significant implications for clinical practice, public health initiatives, policy development, and future research endeavors. Clinicians and healthcare providers working with individuals with dual diagnosis can benefit from the identified research hotspots, as they highlight crucial aspects that require attention in diagnosis, treatment, and support. The prominence of treatment and intervention topics indicates the need for evidence-based integrated approaches that address both substance use and mental health disorders concurrently [ 102 , 103 , 104 ]. The research on the impact of dual diagnosis on quality of life and functioning underscores the importance of holistic care that addresses psychosocial and functional well-being [ 63 ]. For public health initiatives, understanding the prevalence and epidemiological aspects of dual diagnosis is vital for resource allocation and the development of effective prevention and early intervention programs. Policymakers can use the research landscape analysis to inform policies that promote integrated care, reduce barriers to treatment, and improve access to mental health and substance abuse services [ 15 , 105 ]. Furthermore, the identification of emerging topics offers opportunities for investment in research areas that are gaining momentum and importance.

The present study lays a robust groundwork, serving as a catalyst for the advancement of research initiatives and the formulation of comprehensive policies and programs aimed at elevating the quality of life for individuals grappling with the intricate confluence of SUDs and MHDs. Within the realm of significance, it underscores a critical imperative—the urgent necessity to revolutionize the landscape of tailored mental health services offered to patients harboring this challenging comorbidity. The paper distinctly illuminates the exigency for a heightened quantity of research endeavors that delve deeper into unraveling the temporal intricacies underpinning the relationship between SUDs and MHDs. In so doing, it not only unveils potential risk factors but also delves into the far-reaching consequences of treatment modalities over the extended course of time. This illumination, therefore, not only beckons but virtually ushers in a promising trajectory for prospective research endeavors, a path designed to uncover the intricate and evolving journey of dual diagnosis. A profound implication of this study is the direct applicability of its findings in the corridors of policymaking. By leveraging the insights encapsulated within the paper, policymakers stand uniquely equipped to sculpt policies that unequivocally champion the cause of integrated care. The remarkable emphasis on themes of treatment and intervention, permeating the research's core, emphatically underscores the urgent demand for dismantling barriers obstructing access to mental health and substance abuse services. It is incumbent upon policymakers to heed this call, for policies fostering the integration of care can inexorably elevate the outcomes experienced by patients grappling with dual diagnosis. Furthermore, this study artfully directs policymakers to allocate their resources judiciously by identifying burgeoning areas of research that are surging in prominence and pertinence. These emergent topics, discerned within the study, are not just topics; they are emblematic of windows of opportunity. By investing in these areas, policymakers can tangibly bolster research initiatives that are primed to tackle the multifaceted challenges inherent in the realm of dual diagnosis, addressing both current exigencies and future prospects. Additionally, the paper furnishes the foundational blueprint essential for the development of screening guidelines and clinical practice protocols that truly grasp the complexity of dual diagnosis. Clinical practitioners and healthcare establishments would be remiss not to harness this invaluable information to augment their own practices, thereby delivering more effective and empathetic care to individuals contending with dual diagnosis. In essence, this study serves as the compass guiding the way toward a more compassionate, comprehensive, and efficacious approach to mental health and substance abuse care for those in need.

The current landscape analysis of reveals significant implications and highlights the growing research interest in this field since the late 1980s. This increasing trend underscores the complexities and prevalence of comorbid conditions, which necessitate focused research and intervention strategies. The results can be generalized to guide future research priorities, inform clinical guidelines, shape healthcare policies, and provide a framework for other countries to adapt and build upon in their context.

The key take-home message emphasizes the importance of recognizing the high prevalence and intricate relationship between SUDs and MHDs, necessitating integrated and tailored treatment approaches. Additionally, the study advocates for employing efficient research methodologies to synthesize vast amounts of literature and identify emerging trends, focusing on quality of life, treatment outcomes, and the broader socio-cultural and policy contexts to improve care and support for individuals with dual diagnosis. Finally, the research underscores the critical need for continued focus on dual diagnosis, advocating for comprehensive, integrated, and innovative approaches to research, clinical practice, and policymaking to improve outcomes for affected individuals.

Despite the comprehensive approach adopted in this research landscape analysis, several limitations must be acknowledged. The exclusive reliance on Scopus, while extensive, inherently limits the scope of the analysis, potentially omitting relevant articles indexed in other databases such as the Chinese scientific database, thus not fully representing the entire research landscape on dual diagnosis of SUDs and MHDs. Assigning quality control responsibilities to a single author, rather than employing a dual-reviewer system, may introduce bias and affect the reliability of the quality assessment. Although this approach was chosen to expedite the process, it might have compromised the thoroughness of quality checks. The use of narrative synthesis instead of a quantitative synthesis limits the ability to perform meta-analytical calculations that could provide more robust statistical insights. This choice was made for efficiency, but it may affect the depth of the analysis and the generalizability of the conclusions. The reliance on specific keywords to retrieve articles means that any relevant studies not containing these exact terms in their titles or abstracts may have been overlooked, potentially leading to an incomplete representation of the research domain. The restriction to English-language articles and peer-reviewed journals may exclude significant research published in other languages or in non-peer-reviewed formats, introducing linguistic and publication type bias that could skew the results towards predominantly English-speaking regions and established academic journals. The inclusion of articles up to December 31, 2022, means that any significant research published after this date is not considered, potentially missing the latest developments in the field. The validation of the search strategy using a small sample of 30 articles and a comparison with 10 randomly selected articles from Google Scholar may not be sufficient to comprehensively assess the effectiveness of the search strategy; a larger sample size might provide a more accurate validation. Some of the research topics and findings may be specific to particular populations (e.g., veterans) and might not be generalizable to other groups, highlighting the need for caution when extrapolating the results to broader contexts. Although no formal ethical approval was required due to the use of existing literature, ethical considerations related to the interpretation and application of findings must still be acknowledged, particularly in terms of representing vulnerable populations accurately and sensitively. Acknowledging these limitations is crucial for interpreting the findings of this research landscape analysis and for guiding future research efforts to address these gaps and enhance the robustness and comprehensiveness of studies on the dual diagnosis of SUDs and MHDs.

In conclusion, the research landscape analysis of dual diagnosis of substance abuse and mental health disorders provides valuable insights into the growth, active countries, and active journals in this field. The identification of research hotspots and emerging topics informs the scientific community about prevailing interests and potential areas for future investigation. Addressing research gaps can lead to a more comprehensive understanding of dual diagnosis, while the implications of the findings extend to clinical practice, public health initiatives, policy development, and future research priorities. This comprehensive understanding is crucial in advancing knowledge, improving care, and addressing the multifaceted challenges posed by dual diagnosis to individuals and society.

Availability of data and materials

All data presented in this manuscript are available on the Scopus database using the search query listed in the methodology section.

Hasin DS, O’Brien CP, Auriacombe M, Borges G, Bucholz K, Budney A, et al. DSM-5 criteria for substance use disorders: recommendations and rationale. Am J Psychiatry. 2013;170(8):834–51. https://doi.org/10.1176/appi.ajp.2013.12060782 .

Article PubMed PubMed Central Google Scholar

Collaborators GA. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet. 2018;392(10152):1015–35. https://doi.org/10.1016/s0140-6736(18)31310-2 .

Article Google Scholar

Ayalew M, Tafere M, Asmare Y. Prevalence, trends, and consequences of substance use among university students: implication for intervention. Int Q Community Health Educ. 2018;38(3):169–73. https://doi.org/10.1177/0272684x17749570 .

Article PubMed Google Scholar

Raftery D, Kelly PJ, Deane FP, Baker AL, Ingram I, Goh MCW, et al. Insight in substance use disorder: a systematic review of the literature. Addict Behav. 2020;111:106549. https://doi.org/10.1016/j.addbeh.2020.106549 .

Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry. 2005;62(6):593–602. https://doi.org/10.1001/archpsyc.62.6.593 .

Hossain MM, Nesa F, Das J, Aggad R, Tasnim S, Bairwa M, et al. Global burden of mental health problems among children and adolescents during COVID-19 pandemic: an umbrella review. Psychiatry Res. 2022;317:114814. https://doi.org/10.1016/j.psychres.2022.114814 .

Article CAS PubMed PubMed Central Google Scholar

Kurdyak P, Patten S. The burden of mental illness and evidence-informed mental health policy development. Can J Psychiatry. 2022;67(2):104–6. https://doi.org/10.1177/07067437211021299 .

Stumbrys D, Jasilionis D, Pūras D. The burden of mental health-related mortality in the Baltic States in 2007–2018. BMC Public Health. 2022;22(1):1776. https://doi.org/10.1186/s12889-022-14175-9 .

Pompili M, Innamorati M, Gonda X, Serafini G, Sarno S, Erbuto D, et al. Affective temperaments and hopelessness as predictors of health and social functioning in mood disorder patients: a prospective follow-up study. J Affect Disord. 2013;150(2):216–22. https://doi.org/10.1016/j.jad.2013.03.026 .

Costanza A, Vasileios C, Ambrosetti J, Shah S, Amerio A, Aguglia A, et al. Demoralization in suicide: a systematic review. J Psychosom Res. 2022;157:110788. https://doi.org/10.1016/j.jpsychores.2022.110788 .

Arias F, Szerman N, Vega P, Mesías B, Basurte I, Rentero D. Bipolar disorder and substance use disorders. Madrid study on the prevalence of dual disorders/pathology. Adicciones. 2017;29(3):186–94. https://doi.org/10.2088/adicciones.782 .

Brewer S, Godley MD, Hulvershorn LA. Treating mental health and substance use disorders in adolescents: what is on the menu? Curr Psychiatry Rep. 2017;19(1):5. https://doi.org/10.1007/s11920-017-0755-0 .

Jones CM, McCance-Katz EF. Co-occurring substance use and mental disorders among adults with opioid use disorder. Drug Alcohol Depend. 2019;197:78–82. https://doi.org/10.1016/j.drugalcdep.2018.12.030 .

Murthy P, Mahadevan J, Chand PK. Treatment of substance use disorders with co-occurring severe mental health disorders. Curr Opin Psychiatry. 2019;32(4):293–9. https://doi.org/10.1097/yco.0000000000000510 .

Saddichha S, Schütz CG, Sinha BN, Manjunatha N. Substance use and dual diagnosis disorders: future epidemiology, determinants, and policies. Biomed Res Int. 2015;2015:145905. https://doi.org/10.1155/2015/145905 .

Hammen C. Adolescent depression: stressful interpersonal contexts and risk for recurrence. Curr Dir Psychol Sci. 2009;18(4):200–4. https://doi.org/10.1111/j.1467-8721.2009.01636.x .

Wolitzky-Taylor K, Bobova L, Zinbarg RE, Mineka S, Craske MG. Longitudinal investigation of the impact of anxiety and mood disorders in adolescence on subsequent substance use disorder onset and vice versa. Addict Behav. 2012;37(8):982–5. https://doi.org/10.1016/j.addbeh.2012.03.026 .

Mueser KT, Drake RE, Wallach MA. Dual diagnosis: a review of etiological theories. Addict Behav. 1998;23(6):717–34.

Article CAS PubMed Google Scholar

Hartz SM, Pato CN, Medeiros H, Cavazos-Rehg P, Sobell JL, Knowles JA, et al. Comorbidity of severe psychotic disorders with measures of substance use. JAMA Psychiat. 2014;71(3):248–54. https://doi.org/10.1001/jamapsychiatry.2013.3726 .

Carroll KM, Kiluk BD, Nich C, Babuscio TA, Brewer JA, Potenza MN, et al. Cognitive function and treatment response in a randomized clinical trial of computer-based training in cognitive-behavioral therapy. Subst Use Misuse. 2011;46(1):23–34. https://doi.org/10.3109/10826084.2011.521069 .

Drake RE, Mueser KT. Psychosocial approaches to dual diagnosis. Schizophr Bull. 2000;26(1):105–18. https://doi.org/10.1093/oxfordjournals.schbul.a033429 .

Ruggeri M, Leese M, Thornicroft G, Bisoffi G, Tansella M. Definition and prevalence of severe and persistent mental illness. Br J Psychiatry. 2000;177:149–55. https://doi.org/10.1192/bjp.177.2.149 .

Reavley NJ, Jorm AF. Stigmatizing attitudes towards people with mental disorders: findings from an Australian national survey of mental health literacy and stigma. Aust N Z J Psychiatry. 2011;45(12):1086–93. https://doi.org/10.3109/00048674.2011.621061 .

Torrey WC, Tepper M, Greenwold J. Implementing integrated services for adults with co-occurring substance use disorders and psychiatric illnesses: a research review. J Dual Diagn. 2011;7(3):150–61. https://doi.org/10.1080/15504263.2011.592769 .

Bouchery EE, Harwood HJ, Dilonardo J, Vandivort-Warren R. Type of health insurance and the substance abuse treatment gap. J Subst Abuse Treat. 2012;42(3):289–300. https://doi.org/10.1016/j.jsat.2011.09.002 .

Abuse S, Administration MHS. National Mental Health Services Survey (N-MHSS): 2014. Data on mental health treatment facilities. Department of Health and Human Services, Substance Abuse and Mental Health …; 2014.

Shiner B, Gottlieb D, Rice K, Forehand JA, Snitkin M, Watts BV. Evaluating policies to improve access to mental health services in rural areas. J Rural Health. 2022;38(4):805–16. https://doi.org/10.1111/jrh.12674 .

Ioannidis JP, Greenland S, Hlatky MA, Khoury MJ, Macleod MR, Moher D, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet. 2014;383(9912):166–75. https://doi.org/10.1016/s0140-6736(13)62227-8 .

Bornmann L, Bowman BF, Bauer J, Marx W, Schier H, Palzenberger MJBbHmiosi. (2014): 11 Bibliometric standards for evaluating research institutes in the natural sciences.201.

Hicks D, Wouters P, Waltman L, de Rijcke S, Rafols I. Bibliometrics: the Leiden manifesto for research metrics. Nature. 2015;520(7548):429–31. https://doi.org/10.1038/520429a .

Ziedonis D, Brady K. Dual diagnosis in primary care. Detecting and treating both the addiction and mental illness. Med Clin North Am. 1997;81(4):1017–36. https://doi.org/10.1016/s0025-7125(05)70561-7 .

Kim JI, Kim B, Kim BN, Hong SB, Lee DW, Chung JY, et al. Prevalence of psychiatric disorders, comorbidity patterns, and repeat offending among male juvenile detainees in South Korea: a cross-sectional study. Child Adolesc Psychiatry Ment Health. 2017;11:6. https://doi.org/10.1186/s13034-017-0143-x .

Astals M, Domingo-Salvany A, Buenaventura CC, Tato J, Vazquez JM, Martín-Santos R, et al. Impact of substance dependence and dual diagnosis on the quality of life of heroin users seeking treatment. Subst Use Misuse. 2008;43(5):612–32. https://doi.org/10.1080/10826080701204813 .

Buckley PF. Prevalence and consequences of the dual diagnosis of substance abuse and severe mental illness. J Clin Psychiatry. 2006;67(Suppl 7):5–9.

PubMed Google Scholar

Buckley PF, Brown ES. Prevalence and consequences of dual diagnosis. J Clin Psychiatry. 2006;67(7):e01. https://doi.org/10.4088/jcp.0706e01 .

Canaway R, Merkes M. Barriers to comorbidity service delivery: the complexities of dual diagnosis and the need to agree on terminology and conceptual frameworks. Aust Health Rev. 2010;34(3):262–8. https://doi.org/10.1071/ah08723 .

Edward KL, Munro I. Nursing considerations for dual diagnosis in mental health. Int J Nurs Pract. 2009;15(2):74–9. https://doi.org/10.1111/j.1440-172X.2009.01731.x .

Healey C, Peters S, Kinderman P, McCracken C, Morriss R. Reasons for substance use in dual diagnosis bipolar disorder and substance use disorders: a qualitative study. J Affect Disord. 2009;113(1–2):118–26. https://doi.org/10.1016/j.jad.2008.05.010 .

Horsfall J, Cleary M, Hunt GE, Walter G. Psychosocial treatments for people with co-occurring severe mental illnesses and substance use disorders (dual diagnosis): a review of empirical evidence. Harv Rev Psychiatry. 2009;17(1):24–34. https://doi.org/10.1080/10673220902724599 .

Kerfoot KE, Petrakis IL, Rosenheck RA. Dual diagnosis in an aging population: prevalence of psychiatric disorders, comorbid substance abuse, and mental health service utilization in the department of veterans affairs. J Dual Diagn. 2011;7(1–2):4–13. https://doi.org/10.1080/15504263.2011.568306 .

Morojele NK, Saban A, Seedat S. Clinical presentations and diagnostic issues in dual diagnosis disorders. Curr Opin Psychiatry. 2012;25(3):181–6. https://doi.org/10.1097/YCO.0b013e328351a429 .

Thylstrup B, Johansen KS. Dual diagnosis and psychosocial interventions–introduction and commentary. Nord J Psychiatry. 2009;63(3):202–8. https://doi.org/10.1080/08039480802571069 .

van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523–38. https://doi.org/10.1007/s11192-009-0146-3 .

Arndt S, Tyrrell G, Flaum M, Andreasen NC. Comorbidity of substance abuse and schizophrenia: the role of pre-morbid adjustment. Psychol Med. 1992;22(2):379–88. https://doi.org/10.1017/S0033291700030324 .

Barnes TRE, Mutsatsa SH, Hutton SB, Watt HC, Joyce EM. Comorbid substance use and age at onset of schizophrenia. Br J Psychiatry. 2006;188:237–42. https://doi.org/10.1192/bjp.bp.104.007237 .

Brady KT, Killeen T, Saladin ME, Dansky B, Becker S. Comorbid substance abuse and posttraumatic stress disorder: characteristics of women in treatment. Am J Addict. 1994;3(2):160–4. https://doi.org/10.1111/j.1521-0391.1994.tb00383.x .

Brière FN, Rohde P, Seeley JR, Klein D, Lewinsohn PM. Comorbidity between major depression and alcohol use disorder from adolescence to adulthood. Compr Psychiatry. 2014;55(3):526–33. https://doi.org/10.1016/j.comppsych.2013.10.007 .

Brown PJ, Stout RL, Mueller T. Substance use disorder and posttraumatic stress disorder comorbidity: addiction and psychiatric treatment rates. Psychol Addict Behav. 1999;13(2):115–22. https://doi.org/10.1037/0893-164X.13.2.115 .

Bulik CM, Klump KL, Thornton L, Kaplan AS, Devlin B, Fichter MM, et al. Alcohol use disorder comorbidity in eating disorders: a multicenter study. J Clin Psychiatry. 2004;65(7):1000–6. https://doi.org/10.4088/JCP.v65n0718 .

Compton WM, Conway KP, Stinson FS, Grant BF. Changes in the prevalence of major depression and comorbid substance use disorders in the United States between 1991–1992 and 2001–2002. Am J Psychiatry. 2006;163(12):2141–7. https://doi.org/10.1176/ajp.2006.163.12.2141 .

Green AI, Drake RE, Brunette MF, Noordsy DL. Schizophrenia and co-occurring substance use disorder. Am J Psychiatry. 2007;164(3):402–8. https://doi.org/10.1176/ajp.2007.164.3.402 .

Morgenstern J, Langenbucher J, Labouvie E, Miller KJ. The comorbidity of alcoholism and personality disorders in a clinical population: prevalence rates and relation to alcohol typology variables. J Abnorm Psychol. 1997;106(1):74–84. https://doi.org/10.1037/0021-843X.106.1.74 .

Back SE, Waldrop AE, Brady KT. Treatment challenges associated with comorbid substance use and posttraumatic stress disorder: clinicians’ perspectives. Am J Addict. 2009;18(1):15–20. https://doi.org/10.1080/10550490802545141 .

Brown PJ, Recupero PR, Stout R. PTSD substance abuse comorbidity and treatment utilization. Addict Behav. 1995;20(2):251–4. https://doi.org/10.1016/0306-4603(94)00060-3 .

Harris KM, Edlund MJ. Use of mental health care and substance abuse treatment among adults with co-occurring disorders. Psychiatr Serv. 2005;56(8):954–9. https://doi.org/10.1176/appi.ps.56.8.954 .

Hien DA, Cohen LR, Miele GM, Litt LC, Capstick C. Promising treatments for women with comorbid PTSD and substance use disorders. Am J Psychiatry. 2004;161(8):1426–32. https://doi.org/10.1176/appi.ajp.161.8.1426 .

Manwani SG, Szilagyi KA, Zablotsky B, Hennen J, Griffin ML, Weiss RD. Adherence to pharmacotherapy in bipolar disorder patients with and without co-occurring substance use disorders. J Clin Psychiatry. 2007;68(8):1172–6. https://doi.org/10.4088/JCP.v68n0802 .

Minkoff K. An integrated treatment model for dual diagnosis of psychosis and addiction. Hosp Community Psychiatry. 1989;40(10):1031–6. https://doi.org/10.1176/ps.40.10.1031 .

Smith JP, Book SW. Comorbidity of generalized anxiety disorder and alcohol use disorders among individuals seeking outpatient substance abuse treatment. Addict Behav. 2010;35(1):42–5. https://doi.org/10.1016/j.addbeh.2009.07.002 .

Kamali M, Kelly L, Gervin M, Browne S, Larkin C, O’Callaghan E. The prevalence of comorbid substance misuse and its influence on suicidal ideation among in-patients with schizophrenia. Acta Psychiatr Scand. 2000;101(6):452–6. https://doi.org/10.1034/j.1600-0447.2000.101006452.x .

Padgett DK, Gulcur L, Tsemberis S. Housing first services for people who are homeless with co-occurring serious mental illness and substance abuse. Res Soc Work Pract. 2006;16(1):74–83. https://doi.org/10.1177/1049731505282593 .

Schmidt LM, Hesse M, Lykke J. The impact of substance use disorders on the course of schizophrenia-A 15-year follow-up study. Dual diagnosis over 15 years. Schizophr Res. 2011;130(1–3):228–33. https://doi.org/10.1016/j.schres.2011.04.011 .

Singh J, Mattoo SK, Sharan P, Basu D. Quality of life and its correlates in patients with dual diagnosis of bipolar affective disorder and substance dependence. Bipolar Disord. 2005;7(2):187–91. https://doi.org/10.1111/j.1399-5618.2004.00173.x .

Urboanoski KA, Cairney J, Bassani DG, Rush BR. Perceived unmet need for mental health care for Canadians with co-occurring mental and substance use disorders. Psychiatr Serv. 2008;59(3):283–9. https://doi.org/10.1176/appi.ps.59.3.283 .

Kingston REF, Marel C, Mills KL. A systematic review of the prevalence of comorbid mental health disorders in people presenting for substance use treatment in Australia. Drug Alcohol Rev. 2017;36(4):527–39. https://doi.org/10.1111/dar.12448 .

Klinkenberg WD, Caslyn RJ, Morse GA, Yonker RD, McCudden S, Ketema F, et al. Prevalence of human immunodeficiency virus, hepatitis B, and hepatitis C among homeless persons with co-occurring severe mental illness and substance use disorders. Compr Psychiatry. 2003;44(4):293–302. https://doi.org/10.1016/S0010-440X(03)00094-4 .

Wallace C, Mullen PE, Burgess P. Criminal offending in schizophrenia over a 25-year period marked by deinstitutionalization and increasing prevalence of comorbid substance use disorders. Am J Psychiatry. 2004;161(4):716–27. https://doi.org/10.1176/appi.ajp.161.4.716 .

Bronisch T, Wittchen HU. Suicidal ideation and suicide attempts: comorbidity with depression, anxiety disorders, and substance abuse disorder. Eur Arch Psychiatry Clin Neurosci. 1994;244(2):93–8. https://doi.org/10.1007/BF02193525 .

Hatzenbuehler ML, Keyes KM, Narrow WE, Grant BF, Hasin DS. Racial/ethnic disparities in service utilization for individuals with co-occurring mental health and substance use disorders in the general population: Results from the national epidemiologic survey on alcohol and related conditions. J Clin Psychiatry. 2008;69(7):1112–21. https://doi.org/10.4088/JCP.v69n0711 .

Hodgins S, Tiihonen J, Ross D. The consequences of conduct disorder for males who develop schizophrenia: associations with criminality, aggressive behavior, substance use, and psychiatric services. Schizophr Res. 2005;78(2–3):323–35. https://doi.org/10.1016/j.schres.2005.05.021 .

Hunt GE, Bergen J, Bashir M. Medication compliance and comorbid substance abuse in schizophrenia: impact on community survival 4 years after a relapse. Schizophr Res. 2002;54(3):253–64. https://doi.org/10.1016/S0920-9964(01)00261-4 .

Link BG, Struening EL, Rahav M, Phelan JC, Nuttbrock L. On stigma and its consequences: evidence from a longitudinal study of men with dual diagnoses of mental illness and substance abuse. J Health Soc Behav. 1997;38(2):177–90. https://doi.org/10.2307/2955424 .

Priester MA, Browne T, Iachini A, Clone S, DeHart D, Seay KD. Treatment access barriers and disparities among individuals with co-occurring mental health and substance use disorders: an integrative literature review. J Subst Abuse Treat. 2016;61:47–59. https://doi.org/10.1016/j.jsat.2015.09.006 .

Talamo A, Centorrino F, Tondo L, Dimitri A, Hennen J, Baldessarini RJ. Comorbid substance-use in schizophrenia: relation to positive and negative symptoms. Schizophr Res. 2006;86(1–3):251–5. https://doi.org/10.1016/j.schres.2006.04.004 .

Teplin LA, Elkington KS, McClelland GM, Abram KM, Mericle AA, Washburn JJ. Major mental disorders, substance use disorders, comorbidity, and HIV-AIDS risk behaviors in juvenile detainees. Psychiatr Serv. 2005;56(7):823–8. https://doi.org/10.1176/appi.ps.56.7.823 .

Hinckley JD, Danielson CK. Elucidating the neurobiologic etiology of comorbid PTSD and substance use disorders. Brain Sci. 2022. https://doi.org/10.3390/brainsci12091166 .

Jarnecke AM, Saraiya TC, Brown DG, Richardson J, Killeen T, Back SE. Examining the role of social support in treatment for co-occurring substance use disorder and posttraumatic stress disorder. Addict Behav Rep. 2022. https://doi.org/10.1016/j.abrep.2022.100427 .

Kyster NB, Tranberg K, Osler M, Hjorthøj C, Mårtensson S. The influence of childhood aspirations on the risk of developing psychotic disorders, substance use disorders, and dual diagnosis in adulthood based on the Metropolit 1953 Danish male birth cohort. Eur Child Adolesc Psychiatry. 2022. https://doi.org/10.1007/s00787-022-02091-7 .

Cunill R, Castells X, González-Pinto A, Arrojo M, Bernardo M, Sáiz PA, et al. Clinical practice guideline on pharmacological and psychological management of adult patients with attention deficit and hyperactivity disorder and comorbid substance use. Adicciones. 2022;34(2):168–78. https://doi.org/10.2088/adicciones.1569 .

Margolese HC, Boucher M, Therrien F, Clerzius G. Treatment with aripiprazole once-monthly injectable formulation is effective in improving symptoms and global functioning in schizophrenia with and without comorbid substance use—a post hoc analysis of the ReLiAM study. BMC Psychiatry. 2022. https://doi.org/10.1186/s12888-022-04397-x .

Minkoff K, Covell NH. Recommendations for integrated systems and services for people with co-occurring mental health and substance use conditions. Psychiatric Serv. 2022;73(6):686–9. https://doi.org/10.1176/appi.ps.202000839 .

Oliva V, De Prisco M, Pons-Cabrera MT, Guzmán P, Anmella G, Hidalgo-Mazzei D, et al. Machine learning prediction of comorbid substance use disorders among people with bipolar disorder. J Clin Med. 2022. https://doi.org/10.3390/jcm11143935 .

Somohano VC, Kaplan J, Newman AG, O’Neil M, Lovejoy T. Formal mindfulness practice predicts reductions in PTSD symptom severity following a mindfulness-based intervention for women with co-occurring PTSD and substance use disorder. Addict Sci Clin Pract. 2022. https://doi.org/10.1186/s13722-022-00333-2 .

Watkins LE, Patton SC, Drexler K, Rauch SAM, Rothbaum BO. Clinical effectiveness of an intensive outpatient program for integrated treatment of comorbid substance abuse and mental health disorders. Cogn Behav Pract. 2022. https://doi.org/10.1016/j.cbpra.2022.05.005 .

Bertulies-Esposito B, Ouellet-Plamondon C, Jutras-Aswad D, Gagnon J, Abdel-Baki A. The impact of treatment orders for residential treatment of comorbid severe substance use disorders for youth suffering from early psychosis: a case series. Int J Ment Heal Addict. 2021;19(6):2233–44. https://doi.org/10.1007/s11469-020-00317-w .

Butler A, Nicholls T, Samji H, Fabian S, Lavergne MR. Prevalence of mental health needs, substance use, and co-occurring disorders among people admitted to prison. Psychiatric Serv. 2022;73(7):737–44. https://doi.org/10.1176/appi.ps.202000927 .

Henderson JL, Wilkins LK, Hawke LD, Wang W, Sanches M, Brownlie EB, et al. Longitudinal emergence of concurrent mental health and substance use concerns in an ontario school-based sample: the research and action for teens study. J Can Acad Child Adolesc Psychiatry. 2021;30(4):249–63.

PubMed PubMed Central Google Scholar

Huang JS, Yang FC, Chien WC, Yeh TC, Chung CH, Tsai CK, et al. Risk of substance use disorder and its associations with comorbidities and psychotropic agents in patients with autism. JAMA Pediatr. 2021. https://doi.org/10.1001/jamapediatrics.2020.5371 .

Lu W, Muñoz-Laboy M, Sohler N, Goodwin RD. Trends and disparities in treatment for co-occurring major depression and substance use disorders among US adolescents from 2011 to 2019. JAMA Netw Open. 2021. https://doi.org/10.1001/jamanetworkopen.2021.30280 .

Melkonian AJ, Flanagan JC, Calhoun CD, Hogan JN, Back SE. Craving moderates the effects of intranasal oxytocin on anger in response to social stress among veterans with co-occurring posttraumatic stress disorder and alcohol use disorder. J Clin Psychopharmacol. 2021;41(4):465–9. https://doi.org/10.1097/JCP.0000000000001434 .

Otasowie J. Co-occurring mental disorder and substance use disorder in young people: aetiology, assessment and treatment. BJPsych Adv. 2021;27(4):272–81. https://doi.org/10.1192/bja.2020.64 .

Saraiya TC, Badour CL, Jones AC, Jarnecke AM, Brown DG, Flanagan JC, et al. The role of posttraumatic guilt and anger in integrated treatment for PTSD and co-occurring substance use disorders among primarily male veterans. Psychol Trauma: Theory Res Pract Policy. 2022. https://doi.org/10.1037/tra0001204 .

Walhout SJN, Zanten JV, DeFuentes-Merillas L, Sonneborn CKME, Bosma M. Patients with autism spectrum disorder and co-occurring substance use disorder: a clinical intervention study. Subst Abuse: Res Treat. 2022. https://doi.org/10.1177/11782218221085599 .

Walker D, Infante AA, Knight D. Examining the impact of mental health, substance use, and co-occurring disorders on juvenile court outcomes. J Res Crime Delinq. 2022;59(6):820–53. https://doi.org/10.1177/00224278221084981 .

Warfield SC, Pack RP, Degenhardt L, Larney S, Bharat C, Ashrafioun L, et al. The next wave? Mental health comorbidities and patients with substance use disorders in under-resourced and rural areas. J Subst Abuse Treat. 2021. https://doi.org/10.1016/j.jsat.2020.108189 .

Hien DA, Fitzpatrick S, Saavedra LM, Ebrahimi CT, Norman SB, Tripp J, et al. What’s in a name? A data-driven method to identify optimal psychotherapy classifications to advance treatment research on co-occurring PTSD and substance use disorders. Eur J Psychotraumatol. 2022. https://doi.org/10.1080/20008198.2021.2001191 .

Leonhardt M, Brodahl M, Cogan N, Lien L. How did the first COVID-19 lockdown affect persons with concurrent mental health and substance use disorders in Norway? A qualitative study. BMC Psychiatry. 2022. https://doi.org/10.1186/s12888-022-03812-7 .

Leonhardt M, Kyrdalen E, Holstad A, Hurlen-Solbakken H, Chiu MYL, Lien L. Norwegian cross-cultural adaptation of the social and communities opportunities profile-mini for persons with concurrent mental health and substance use disorders. J Psychosoc Rehabil Mental Health. 2022. https://doi.org/10.1007/s40737-022-00309-0 .

Sell L, Lund HL, Johansen KS. Past, present, and future labor market participation among patients admitted to hospital with concurrent substance use and mental health disorder, and what we can learn from it. J Occup Environ Med. 2022;64(12):1041–5. https://doi.org/10.1097/JOM.0000000000002633 .

Sverdlichenko I, Hawke LD, Henderson J. Understanding the service needs of youth with opioid use: a descriptive study of demographics and co-occurring substance use and mental health concerns. J Subst Abuse Treat. 2022. https://doi.org/10.1016/j.jsat.2021.108592 .

Yerriah J, Tomita A, Paruk S. Surviving but not thriving: Burden of care and quality of life for caregivers of patients with schizophrenia spectrum disorders and comorbid substance use in South Africa. Early Interv Psychiatry. 2022;16(2):153–61. https://doi.org/10.1111/eip.13141 .

Murthy P, Chand P. Treatment of dual diagnosis disorders. Curr Opin Psychiatry. 2012;25(3):194–200. https://doi.org/10.1097/YCO.0b013e328351a3e0 .

Schneier M. Better treatment for dual diagnosis patients. Psychiatr Serv. 2000;51(9):1079. https://doi.org/10.1176/appi.ps.51.9.1079 .

Tirado Muñoz J, Farré A, Mestre-Pintó J, Szerman N, Torrens M. Dual diagnosis in depression: treatment recommendations. Adicciones. 2018;30(1):66–76. https://doi.org/10.2088/adicciones.868 .

Carrà G, Clerici M. Dual diagnosis–policy and practice in Italy. Am J Addict. 2006;15(2):125–30. https://doi.org/10.1080/10550490500528340 .

Download references

Acknowledgements

Author information, authors and affiliations.

Department of Physiology and Pharmacology/Toxicology, Division of Biomedical Sciences, College of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine

Waleed M. Sweileh

You can also search for this author in PubMed Google Scholar

Contributions

W.S started the idea, designed the methodology; did the data analysis, graphics, and data interpretation; wrote and submitted the manuscript. This was a single-authored manuscript. W.S wrote and submitted the manuscript.

Corresponding author

Correspondence to Waleed M. Sweileh .

Ethics declarations

Ethics approval and consent to participate.

IRB at An-Najah National University (Palestine) requires no approval for bibliometric studies.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1., rights and permissions.

Reprints and permissions

About this article

Cite this article.

Sweileh, W.M. Research landscape analysis on dual diagnosis of substance use and mental health disorders: key contributors, research hotspots, and emerging research topics. Ann Gen Psychiatry 23 , 32 (2024). https://doi.org/10.1186/s12991-024-00517-x

Download citation

Received : 28 July 2023

Accepted : 21 August 2024

Published : 30 August 2024

DOI : https://doi.org/10.1186/s12991-024-00517-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Substance use disorders
Mental health disorders
Dual diagnosis
Research landscape analysis
Treatment interventions
Comorbidity

Annals of General Psychiatry

ISSN: 1744-859X

Submission enquiries: [email protected]

Corpus ID: 6312985

BMC Health Services Research BioMed Central Study protocol The German MultiCare-study: Patterns of multimorbidity in primary health care – protocol of a prospective cohort study

Tables from this paper.

70 Citations

Improving the health of people with multimorbidity: the need for prospective cohort studies, health behaviour, social support, socio-economic status and the 5-year progression of multimorbidity: results from the multicare cohort study, analysis of health care costs in elderly patients with multiple chronic conditions using a finite mixture of generalized linear models, which chronic diseases and disease combinations are specific to multimorbidity in the elderly results of a claims data based cross-sectional study in germany, impact of depression on health care utilization and costs among multimorbid patients – results from the multicare cohort study, social inequalities in patient-reported outcomes among older multimorbid patients – results of the multicare cohort study.

Highly Influenced

Implementation of chronic illness care in German primary care practices – how do multimorbid older patients view routine care? A cross-sectional study using multilevel hierarchical modeling

Self-rated health in multimorbid older general practice patients: a cross-sectional study in germany, experiences of patients with multimorbidity with primary care and the association with patient activation: a cross-sectional study in germany, patterns of multimorbidity in primary care patients at high risk of future hospitalization., related papers.

Showing 1 through 3 of 0 Related Papers

Open access
Published: 30 August 2024

The effect of single versus multiple piezocisions on the rate of canine retraction: a randomized controlled trial

Farah Y. Eid 1 &
Ahmed R. El-Kalza 1

BMC Oral Health volume 24 , Article number: 1024 ( 2024 ) Cite this article

Metrics details

Piezocision is a minimally invasive surgical method aiming to accelerate tooth movement. However, its effect was found to be transient, appertaining to the regional acceleratory phenomenon (RAP). Hence, the aim of the study was to evaluate the effect of single and multiple piezocisions on the rate of orthodontic tooth movement (OTM). Moreover, the impact of both protocols on canine tipping and orthodontically induced inflammatory root resorption (OIIRR) has been assessed.

Thirty indicated patients for the therapeutic extraction of maxillary first premolars were enlisted in this split-mouth study, and they were randomly split into two equal groups, each including 15 subjects. In the Single Application Group (SAG), one side of the maxillary arch arbitrarily received a single piezocision before the onset of canine retraction, whereas in the Multiple Application Group (MAG), piezocisions were randomly performed on one side, three times on a monthly basis, over the 12-week study period. The contralateral sides of both groups served as the controls. Canine retraction was carried out bilaterally using nickel-titanium closed-coil springs, delivering 150 g of force, and the rate of tooth movement, as well as canine tipping were evaluated on a monthly basis, over a 3-month period. Cone-bean computed tomography scans were also conducted pre- and post- canine retraction, and OIIRR was assessed using Malmgren Index.

The reported outcomes revealed a significant increase in the amount of canine retraction, canine tipping, as well as root resorption scores on the experimental sides in both groups SAG and MAG post-retraction ( p < 0.001). However, upon comparing the experimental sides in both groups, non-significant differences have been observed between them regarding all the assessed outcomes ( p > 0.05).

Conclusions

Single and multiple piezocisions effectively accelerate OTM in comparison to conventional orthodontic treatment, with relative outcomes reported by both intervention frequencies. Accordingly, single piezocision is recommended as an adjunct to OTM. Furthermore, significant tooth tipping as well as a significantly higher root resorption risk accompanies both single and multiple piezocision applications in conjunction with OTM.

Name of the Registry

Clinicaltrials.gov

Trial Registration Number

NCT05782088

Date of Registration

23/03/2023 “Retrospectively registered”.

https://clinicaltrials.gov/ct2/show/NCT05782088

Peer Review reports

The prolonged orthodontic treatment period is usually a matter of serious concern for the patients, and it also results in several dental and periodontal side effects [ 1 , 2 , 3 ]. Moreover, the prolonged treatment duration has an adverse effect on patient compliance, and his/her willingness to continue treatment. Consequently, several methods aiming to accelerate orthodontic tooth movement (OTM) and lessen the treatment duration have been proposed, including surgical [ 4 , 5 ] and non-surgical adjuncts [ 6 ].

The suggested acceleratory surgical interventions include corticotomy, which is considered a significantly invasive technique, since it involves the elevation of a relatively large flap, followed by cortical bone cuts, all of which might result in post-operative complications [ 4 , 7 , 8 ]. Several other less invasive surgical methods have been proposed for the acceleration of OTM, such as micro-osteoperforations [ 9 , 10 ], corticison [ 5 , 11 ], as well as piezocision [ 12 , 13 ].

Piezocision is known to involve minor piezoelectric cuts without flap elevation [ 14 , 15 ]. The acceleratory effect of piezocision and all the other surgical methods is mainly credited to the regional acceleratory phenomenon (RAP), which involves a transient demineralization, together with a surge in cellular activity in the alveolar bone, in response to the cortical bone injury [ 16 ]. The impact of RAP has been reported to be temporary, and entirely reversible. Moreover, the magnitude of RAP was found to be dependent on the corticotomy depth [ 17 ].

The impact of piezocision on the rate of OTM has been investigated in several trials, and despite its effectiveness in accelerating tooth movement, its effect was found to be transient [ 18 , 19 ], which might be related to the temporary nature of RAP as previously explained. Therefore, it has been suggested that performing multiple piezocisions throughout the treatment might be helpful in prolonging and/or re-inducing the biological effect of RAP, and accordingly, maintain the acceleratory effect for a longer time [ 20 , 21 ].

With orthodontically induced inflammatory root resorption (OIIRR) being a commonly encountered iatrogenic repercussion of orthodontic treatment, the impact of the proposed methods for acceleration of OTM has been assessed regarding this issue, based on the rationale of decreasing treatment time could concurrently decrease the incidence or the severity of OIIRR. Accordingly, piezocision and OIIRR with OTM have been tested in several studies with contradictory findings being reported [ 22 , 23 , 24 ].

In conclusion, by reviewing the literature, no clinical trial has been conducted to investigate the impact of multiple piezocisions on the rate of tooth movement, except for one study employing an initial corticotomy followed by a second flapless corticotomy using piezosurgery after two months, to facilitate the traction of an impacted canine [ 25 ]. Therefore, the aim of our study was to assess and compare the effect of single versus multiple piezocisions on the rate of OTM, judged by the rate of canine retraction. Moreover, maxillary canine tipping, and OIIRR with both single and multiple piezocision techniques were evaluated pre- and post- canine retraction.

The null hypothesis was that there are no significant differences in the rate of canine retraction, the amount of experienced canine tipping during movement, and in the risk of OIIRR with both single and multiple piezocisions.

Materials and methods

Study design.

The study was a compound design randomized controlled trial, comprising two parallel groups, with a split-mouth design in each.

Study subjects

Thirty participants with an age ranging from 15 to 25 years, have been appointed for this study. The sample size was calculated based on 95% confidence level to detect differences in the canine retraction rate with and without piezocision. Alfawal et al [ 15 ] reported that the mean ± SD canine retraction rate at the third month = 1.10 ± 0.29 mm/month on the piezocision side, and 0.98 ± 0.22 mm/month on the control side. The mean ± SD difference = 0.11 ± 0.255, and 95% confidence interval= -0.04, 0.26. Repeated piezocision is assumed to accelerate orthodontic tooth movements [ 20 ]. Based on comparison of paired means, the minimum sample size was calculated to be 14 per group, increased to 15 to make up for cases lost to follow-up. The total required sample size = number of groups × number per group = 2 × 15 = 30 patients [ 26 ]. The sample was calculated using MedCalc Statistical Software version 19.0.5 (MedCalc Software bvba, Ostend, Belgium; https://www.medcalc.org ; 2019).

Ethical approval has been procured from the Institutional Review Board of the Faculty of Dentistry, Alexandria University, Alexandria, Egypt (IRB:00010556–IORG:0008839). Manuscript Ethics Committee number 0582-01/2023. Patients were recruited from the outpatient clinic, Department of Orthodontics, Alexandria University starting January 2023, and the study was terminated in January 2024. Subjects were examined and screened, and the following enrolment criteria have been considered: (1) Class I bimaxillary protrusion, and Class II division 1 patients requiring the extraction of maxillary 1st premolars with consequent canine retraction, (2) Healthy systemic condition with no chronic problems, (3) No previous orthodontic treatment, (4) Acceptable oral hygiene, (5) Healthy periodontium. The study procedures were thoroughly explained to all the enrolled subjects, and signed informed consents were attained accordingly. All research procedures were performed in agreement with the relevant guidelines and regulations, as stated in the Declaration of Helsinki.

Patients requiring the therapeutic extraction of maxillary 1st premolars bilaterally (P), were tested for piezocision along with canine retraction (I), applied only once versus multiple times (C), to evaluate the difference in the rate of tooth movement with both protocols (O).

Randomization and subject allocation

The thirty recruited patients were randomly allocated to either group (15 per group), using a computer-generated randomization code (Sealed Envelope Ltd). As per the split-mouth design within each group, the randomization process was repeated once again for allocation of the “experimental” and “control” sides in the maxillary arch. Randomization was performed by a trial independent person.

Patients’ preparation

Preparation for fixed orthodontic treatment entailed recording the enrolled subjects’ medical and dental history, along with collecting the customary orthodontic records (photographs, x-rays, and study models). Oral hygiene reinforcement was also mandatory prior to the onset of orthodontic treatment. Maxillary and mandibular straight wire fixed Roth appliances (Sprint ® II; Forestadent, Germany) were bonded by the same operator, with 0.022 \(\:\:\times\:\:\) 0.028-inch slots in all participants, after which they were referred for maxillary first premolars’ extraction. Levelling and alignment were then started, and a wire sequence of 0.014-inch, 0.018-inch, followed by 0.016 \(\:\:\times\:\:\) 0.022-inch NiTi wires were used, over an approximate period of 3–4 months. This stage was considered achieved when a 0.016 \(\:\:\times\:\:\) 0.022-inch stainless steel arch wire was positioned passively in all the maxillary teeth, on which canine retraction will be performed.

Anchorage preparation

After levelling and alignment, anchorage reinforcement was ensured through the bilateral inter-radicular placement of mini-screws between the maxillary second premolars and first molars, 8 mm from the apex of the interdental papilla. The placed mini-screws were 1.7 mm in diameter, and 8 mm in length (Orthoeasy; Forestadent, Germany). Mini-screws were installed under local anesthesia, with a screw driver employed for the self-drilling process.

Intervention

In group SAG, piezocision was performed only once prior to the commencement of canine retraction (T0) on one side of the maxillary arch that has been randomly selected. As for the MAG group, piezocision was repeated three times, on a monthly basis (T0, T1, and T2), over the 12-week study period. The contralateral sides in both groups represented the controls.

On the experimental sides in both groups, the surgical procedure was conducted under local infiltrative anaesthesia to the mesial and distal sides of the maxillary canine. Vertical interproximal incisions were made 5 mm apical to the mesial and distal interdental papilla of the experimental canine, on the buccal aspect using surgical blade No. 15. Incisions extended apically 10 mm in length through the periosteum, permitting the blade to reach the alveolar bone. A Piezo surgical knife (Piezomed, tip B1) was subsequently employed to create the cortical bone incision through the gingival opening, to an approximate depth of 3 mm ( Fig. 1 ) . No suturing has been required for the soft tissue incisions after termination of the surgery [ 18 , 27 ]. Moreover, analgesics (paracetamol) were prescribed post-operatively, whereas anti-inflammatory drugs were prohibited to avoid intervening with the RAP [ 18 ].

(A) Vertical interproximal incisions mesial and distal to the maxillary canine using surgical blade No. 15. (B) Vertical cortical cuts using the Piezo surgical knife, with a depth of 3 mm

Canine retraction was accomplished using nickel-titanium (NiTi) closed-coil springs stretched between the canine bracket hook and the mini-screw head, with a force of 150 g applied on each side of the maxillary arch, and the force magnitude was adjusted each visit, as measured by a force gauge (Morelli Ortodontia, Brazil) (Fig. 2 ).

Canine retraction using NiTi closed-coil springs bilaterally stretched between the mini-screw head and the canine bracket hook

Due to the nature of the clinical procedure, neither the patient nor the operator could be blinded during the intervention. However, both the operators during measurements, and the statistician during data analysis were blinded.

Alginate impressions (Ca37; Cavex, Haarlem, The Netherlands) were taken before the start of canine distalization (T0), and then repeated on a monthly basis (T1, T2, T3) over the 12-week research duration. Dental models were then poured, coded, and scanned (inEos X5 CAD/CAM lab scanner; Dentsply Sirona, PA, USA), producing three-dimensional (3D) digital images of the fabricated models. The needed measurements were carried out using AutoCAD version 2020 (AutoCAD; Autodesk, USA). Pre-retraction and post-retraction cone-beam computed tomography (CBCT) scans were also conducted in both groups SAG and MAG (within a 12-week interval). A research design flowchart is represented in Fig. 3 , recapitulating the research methodology.

Research design flowchart summarizing the study procedures

Measurement of canine retraction

Various landmarks were determined on the maxillary arch, including the mid-palatal raphe, the medial points on the third right and left rugae, and the cusp tips of the right and left maxillary canines. From both the medial points of the right and left third rugae, and the cusp tips of the right and left maxillary canines, perpendicular lines were dropped to the mid-palatal raphe. Antero-posterior measurements were subsequently performed between the canine lines and the third rugae lines on each side, for the assessment of the canine retraction rate [ 28 ] (Fig. 4 ).

Measurement of canine retraction using AutoCAD between the canine cusp tips and the medial ends of the third rugae

Measurement of canine tipping

Tipping of the maxillary canine during retraction was evaluated by drawing vertical lines on the palatal surfaces of the lateral incisor and the canine that extend from the middle of the incisal edge of the lateral incisor and the cusp tip of the maxillary canine to the middle of the cervical line of each, thereby dividing each of them into equal halves. The distance between the lateral incisor and the canine was assessed at two points on their clinical crowns: incisal, and cervical, enabling the detection of crown tipping of the canine during distalization, if there was a difference in the measurements between both the assessed levels [ 9 ] (Fig. 5 ).

Evaluation of canine tipping using AutoCAD by measuring the distance between the canine and lateral incisor at the incisal and cervical levels

Measurement of OIIRR

In both groups, maxillary canine root resorption was evaluated on the procured pre-retraction and post-retraction CBCT scans, that were conducted using the J. Morita R100 Cone beam 3D Imaging System machine (MFG Corp., Kyoto, Japan). The scan was executed with a Field of View (FOV) of 100 × 50 mm (Width × Height). Volumes’ reconstruction was carried out with a 0.160 mm isometric voxel size, a tube voltage of 90 kVp and 8 mA, and an exposure time of 20 s.

Malmgren Index [ 29 ] was used for the assessment of OIIRR, and each of the tested canines was given a score ranging from 0 to 4, according to the degree of detected resorption. Using the software OnDemand3D ™ (Cybermed Inc., South Korea), and utilizing the arch section module, the focal trough was adjusted twice to allow the mesiodistal and the labiolingual sectioning of each canine, parallel to the long axis of its root (Fig. 6 ). The chosen slice thickness interval was 0.1 mm. The two perpendicular cross-sections showing the maximum length of the canine root were subsequently selected for evaluation using the designated index [ 30 ] (Fig. 7 ).

Axial views showing the adjusted focal trough permitting the sectioning of the right maxillary canine with an interval of 0.1 mm in two directions: (A) Labiolingual, (B) Mesiodistal

The re-oriented CBCT image of the maxillary canine revealing the maximum root length. (A) Labiolingual cross-section, (B) Mesiodistal cross-section

Intra-rater and inter-rater reliability

Calibration on the study measurements was performed for two assessors (F.E., and A.E.), who repeated the measurements to ensure consistency, within a one-week interval. Both intra- and inter-rater reliability were evaluated, and intraclass correlation coefficient (ICC) ranged from 0.87 to 0.99 indicating excellent reliability between examiners and across time [ 31 ].

Statistical analysis

Normality was tested for the included variables using descriptive statistics, plots (Q-Q plots and histograms), and Shapiro Wilk normality tests. All quantitative data exhibited normal distribution, so means and standard deviation (SD) were calculated, and parametric tests were implemented. Comparisons of canine retraction and tipping between the two groups (single vs. multiple piezocision) were performed using independent samples t-test, while comparisons between the experimental and control sides were performed using paired samples t-test. Mean differences and 95% confidence intervals were calculated. Meanwhile, comparisons between different time points were performed through repeated measures ANOVA, followed by multiple pairwise comparisons with Bonferroni adjusted significance levels. Comparisons of root resorption scores between the two groups (single vs. multiple piezocision) were done using Mann-Whitney U test, whereas comparisons between the experimental and control sides, and between the pre- and post- scores were performed using Wilcoxon Signed Ranks test. The significance level was set at p-value < 0.05. Data analysis was performed using IBM SPSS for Windows (Version 26.0).

Over the study period, no subject dropouts were recorded neither in the pre-intervention period, nor throughout the remainder of the research duration. Non-significant differences have been reported between the enrolled participants in the two study groups regarding their baseline characteristics ( p > 0.05), as displayed in Table 1 . No mini-screw failures have also been reported in any of the study participants over the 12-week observation period. Moreover, all the study models that were obtained every month, as well as the pre- and post-retraction CBCT scans were accounted for.

Canine retraction

The amount of maxillary canine distalization at the studied time points is depicted in Table 2 , regarding both groups SAG and MAG. In group SAG, the mean distance travelled by the canines has been significantly greater on the experimental sides in comparison with the control sides at all the assessed time points ( p < 0.001), in addition to the total moved distance after the 12-week study period, with that being 4.49 mm ± 0.34 on the experimental side, and 2.77 mm ± 0.29 on the control side. Moreover, on the experimental side, the amount of the canine retraction was significantly less at T3 when compared to those recorded at T1 and T2 ( p < 0.01). Opposingly, on the control side, non-significant differences have been observed in the amount of retraction across time ( p = 0.09).

In group MAG, a similar pattern to that observed in the SAG has been documented, with the experimental sides showing statistically greater moved distances by the maxillary canines at T1, T2, and T3 in comparison with the control sides ( p < 0.001). Also, the total amount of canine retraction achieved on the experimental side was statistically higher than that recorded on the control side, with values of 4.68 mm ± 0.27, and 2.79 mm ± 0.29, respectively. The experimental side showed a significant reduction in the moved distances by the canines at T3 in comparison with both T1 and T2 ( p < 0.001), whereas the control side revealed a relatively constant rate of tooth movement across the three time points ( p = 0.12).

When the experimental sides in both groups SAG and MAG were compared as presented in Fig. 8 , non-significant differences between both groups have been documented at T1 ( p = 0.11), T2 ( p = 0.10), T3 ( p = 0.68), as well as in the total moved distance after 12 weeks ( p = 0.11). However, a significantly less amount of canine retraction was recorded at T3 in comparison to T1, and T2 ( p < 0.001).

Comparison of canine retraction on the experimental sides in groups SAG and MAG

Canine tipping

Canine tipping on both the experimental and control sides in groups SAG and MAG is displayed in Table 3 . In the two study groups, a similar trend has been observed on both the experimental and control sides, where a significant increase in the moved distance by the maxillary canine has been documented relative to the lateral incisor at the incisal, and cervical levels, as well as after calculating the difference between both levels at all the assessed time points ( p < 0.001). Furthermore, in both single and multiple application groups, a statistically greater amount of maxillary canine tipping has been noted on the experimental sides relative to the control sides at all the measured levels (incisal, cervical, difference between both), and at all the evaluated time points aside from the baseline (T0) ( p < 0.05).

In Table 4 , comparisons between the amount of resultant canine tipping post-retraction on the experimental sides in groups SAG and MAG are displayed. Statistically non-significant differences have been reported between both groups at all the assessed levels and time points ( p > 0.05). Within group comparisons showed statistically significant differences in the amount of canine tipping at all the time points, and at all the evaluated levels ( p < 0.001).

Malmgren Index scores for OIIRR of the maxillary canines in both groups SAG and MAG, on the experimental and control sides are represented in Table 5 . Within each of the tested sides, a significant score change has been documented denoting an increased incidence and/or severity of OIIRR post-retraction on the experimental sides in the SAG and MAG groups ( p < 0.001), and on the control sides in SAG ( p = 0.08) and in MAG ( P = 0.03).

Upon comparing the root resorption changes between the experimental sides in the two groups as displayed in Fig. 9 , non-significant differences have been observed between them following canine distalization ( p = 0.81).

Comparison of root resorption scores on the experimental sides in groups SAG and MAG

With surgical methods being reported as effective acceleratory adjuncts to OTM, minimally invasive options are always advocated by both clinicians and patients. Hence, the objective of this study was to evaluate and compare the influence of single versus multiple piezocisions on the canine retraction rate. Moreover, canine tipping and root resorption were evaluated with both piezocision protocols. According to the reported results, the null hypothesis has been accepted as non-significant differences have been documented between single and multiple piezocision applications in all the measured outcomes, whether the amount of tooth movement, tipping, or the associated OIIRR.

The employed study design in the present investigation was a compound design randomized controlled trial (RCT), pertaining to RCTs being beheld as the benchmark for evaluation of intervention efficiency [ 32 ]. Furthermore, the split-mouth technique limited the influence of inter-subject variability, with the enrolled participants acting as their own controls, thereby decreasing the required sample size [ 33 ].

Extractions were scheduled at the beginning of orthodontic treatment, just after fixed appliance bonding, thus considerable time has been allowed between the extraction date and the onset of canine retraction. This sequence has been planned because extraction is considered a traumatic surgical procedure, that can induce RAP and alter the tooth movement rate, thereby obscuring the effect of the tested surgical intervention [ 34 ]. A similar precaution has been taken by several investigators [ 9 , 35 ].

NiTi closed-coil springs were used to retract the maxillary canines in both groups, for the purpose of generating continuous forces throughout the 12-week assessment period [ 36 ]. Moreover, the medial ends of the third rugae were used a stable reference points for the measurement of canine retraction [ 37 ], as performed in former studies [ 6 , 15 ].

The CBCT scans performed by the enlisted participants pre- and post-retraction (12-week interval) were imperative for assessing the influence of piezocision on root resorption. It is noteworthy to mention that high intra-observer and inter-observer reliability have been advocated regarding CBCT measurements in several investigations [ 38 , 39 ]. Moreover, higher diagnostic accuracy has been reported with CBCTs when compared to periapical and panoramic radiographs with regards to the identification and diagnosis of root resorption [ 40 , 41 ]. On another note, Malmgren index [ 29 ] has been used in the present study as a reliable scoring system for root resorption evaluation, as well in other studies [ 30 , 42 ].

Results of the present study reported a significant increase in the amount of tooth movement on the piezocision sides in both the single and multiple application groups in comparison to the control sides, at all the assessed time points by approximately 62.5%. This resultant acceleration is mainly attributed to the RAP that has been induced by the surgical injury to cortical bone, and the consequent reduction in the bone resistance to tooth movement [ 16 , 43 ]. Furthermore, in response to the employed selective decortication, an increase in the inflammatory markers together with an elevation in the cytokines’ levels take place, prompting the activity of osteoclasts and enhancing the bone remodeling process, finally resulting in acceleration of OTM [ 44 , 45 ]. Findings reported in the present study are in agreement with those by Aksakalli et al [ 14 ], as well as Abbas et al [ 46 ], where piezocision was reported to significantly accelerate canine distalization into the extraction space by 1.5-2 times during the first three months of fixed appliance therapy.

Moreover, it has been observed that the greatest distances moved by the maxillary canines on the experimental sides in both groups were recorded in the 1st two months of treatment, followed by a significant decrease by the 3rd month, in contrast to the relatively constant rate of tooth movement on the control sides. However, despite the drop reported at T3, the distance travelled on the piezocision side was still significantly higher than that on the control side. A possible explanation has been provided by Wilcko et al [ 47 , 48 ], where they stated that RAP is a unique phenomenon that exhibits a distinct pattern in its emergence and extent, with its onset taking place only a few days post-injury, reaching its peak after 4 to 8 weeks, and lasting for 2 to 4 months. A relatively similar pattern of tooth movement has been reported by Alfawal et al [ 15 ] with both piezocision and laser-assisted flapless corticotomies during canine distalization, and again by Jaber et al [ 49 ] with laser-assisted flapless corticotomy.

The relatively similar distances moved by the maxillary canines on the experimental sides in both groups with single and multiple applications do not support the theory recommending repeating the surgical injury in an attempt to re-induce the RAP, and consequently maintain the acceleratory impact on the teeth during orthodontic treatment. This theory has been tested by Sanjideh et al [ 50 ], where a second corticotomy procedure was performed after 4 weeks after treatment onset, and was found effective in accelerating OTM over a longer duration. With piezocisions, the same hypothesis has been investigated by Charavet et al [ 20 ], where one-stage versus two-stage piezocisions were compared, and repeated injuries were found to effectively re-activate RAP. However, when the same hypothesis was tested clinically in the present study, non-significant differences have been found between single and multiple piezocisions, thereby refuting the theory due to its clinical and statistical non-significance. This level of insignificance between both techniques could be explained by Wilcko et al [ 47 , 48 ] as stated earlier, where they reported that RAP could last for up to 4 months, thus re-induction within 4 weeks is not needed.

Significant tipping of the maxillary canines in both groups has been reported on the experimental as well as on the control sides. This finding may be related to the direction of the force vector in the present study, which was in a distal and a relatively apical direction, since the NiTi coil springs were attached from the mini-screw head (8 mm apical to the apex of the interdental papilla, between the maxillary 2nd premolar and 1st molar), to the hook on the distal wing of the maxillary canine bracket. These findings are in accordance with those reported by Abbas et al [ 46 ] where significant tipping of the maxillary canines was noted after retraction, with both piezocision and corticotomy procedures, in comparison with the controls. However, the non-significant differences between both experimental sides (single and multiple piezocision) in the resultant tipping movement could be related to the non-significant differences between them in the rate of tooth movement that has been reported earlier as well.

Analysis of the root resorption scores in the present study revealed a statistically significant difference between the experimental and control sides in both groups SAG and MAG, with more resorption related to both the single and the multiple surgical interventions. Comparative findings were reported by Elkalza et al [ 24 ] and Patterson et al [ 27 ], where significant root resorption has been recorded with piezocision-assisted orthodontics. Conversely, others reported significantly less root resorption with piezocision in comparison to conventional orthodontic treatment [ 46 ].

Even though the induced RAP following surgical injury is known to increase alveolar bone turnover through stimulating the accompanying cellular activity could possibly reduce the incidence of root resorption due to the remarkable reduction in the pressure areas [ 51 , 52 ], the precise association between alveolar bone density and OIIRR is quite perplexing. Contradictory findings have been reported in the literature regarding this issue, where some have suggested that the osteoporotic environment induced by corticotomy-related procedures favor bone remodeling around the roots [ 53 ], whereas others documented an increase in OIIRR with the increased bone turnover rate [ 54 ]. On a cellular level, three weeks post-corticotomy, an increase in osteoclast number has been noted in conjunction with a surge in the bone turnover rate, which was attributed to the RAP response [ 55 ]. On a biological level, Teng and Liou [ 56 ] found that bone remodeling markers from the gingival crevicular fluid, such as bone-specific alkaline phosphatase showed a constant increase throughout the experimental period following interdental cuts between the teeth in Beagle dogs. Furthermore, the experimental dogs did not encounter a systemic increase in bone turnover, as depicted through serum alkaline phosphatase levels, thus it has been concluded that the RAP response is experienced locally, and that the extent of the osteotomy is possibly directly related to the intensity of bone turnover and the associated osteoporotic changes. Accordingly, it could be argued that the increased clastic cellular activity during the enhanced turnover process, could possibly increase the expected amount of OIIRR.

Moreover, RAP has been reportedly associated with an increase in the local inflammatory response [ 51 ], with a consequent significant increase in inflammatory markers such as cytokines and chemokines at the injury site [ 9 ]. Since OIIRR is considered an inflammatory process, the elevated levels of inflammatory mediators induced by RAP and surgical injuries could be possible risk factors for root resorption [ 57 ].

Study limitations

Limitations of the present study include the lack of assessment over a longer period and repeating the intervention after 2 or 3 months instead of every month, covering the entire orthodontic treatment duration. Therefore, future studies are recommended to extend past the canine retraction stage for a more comprehensive appraisal. Additionally, a larger sample size would have aided in the generalizability of the obtained results. It is also noteworthy to mention that the lack of operator blinding during the intervention could result in potential bias. Nonetheless, specific measures were taken to manage this downside, including the randomized subject allocation, as well as blinding of the operators during both the measurement and the data analysis phases.

Assessment of patient reported outcome measures are also advocated, such as pain, discomfort, functional limitation, periodontal side effects, in addition to patient acceptability to the repeated interventions. Moreover, measurement of maxillary canine tipping has been performed relative to the lateral incisor, hence, its assessment relative to a more stable reference point is recommended for a more accurate evaluation.

Considering the present study’s 12-week interval, single and multiple piezocisions effectively accelerate OTM in comparison to conventional orthodontic treatment, with relative outcomes reported by both intervention frequencies. Accordingly, single piezocision is recommended as an adjunct to OTM.

Given the employed mechanics for canine retraction in the present study, significant tooth tipping accompanies accelerated OTM with both single and multiple surgical interventions, with comparable amounts using both protocols. Therefore, bodily tooth movement is less encountered in conjunction with piezocision-assisted orthodontics.

Incidence of OIIRR is significantly higher with both single and multiple piezocison applications in contrast to OTM solely, which could be related to the enhanced clastic cellular activity at the injury sites. Approximate OIIRR risks have been documented using both protocols.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Orthodontic tooth movement

Regional acceleratory phenomenon

Orthodontically induced inflammatory root resorption

Nickel-titanium

Three-dimensional

Cone-beam computed tomography

Field of view

Intraclass correlation coefficient

Standard deviation

Randomized controlled trial

Kurol J, Owman-Moll P, Lundgren D. Time-related root resorption after application of acontrolled continuous orthodontic force. Am J Orthod Dentofac Orthop. 1996;110:303–10.

Article CAS Google Scholar

Ristic M, Svabic MV, Sasic M, Zelic O. Clinical and microbiological effects of fixed orthodontic appliances on periodontal tissues in adolescents. Orthod Craniofac Res. 2007;10:187–95.

Article CAS PubMed Google Scholar

Ge M, He W, Chen J, Wen C, Yin X, Hu Z, et al. Efficacy of low-level laser therapy for accelerating tooth movement during orthodontic treatment: a systematic review and meta-analysis. Lasers Med Sci. 2015;30:1609–18.

Cassetta M, Di Carlo S, Giansanti M, Pompa V, Pompa G, Barbato E. The impact of osteotomy technique for corticotomy-assisted orthodontic treatment (CAOT) on oral health-related quality of life. Eur Rev Med Pharmacol Sci. 2012;16:35–40.

Google Scholar

Kim SJ, Park YG, Kang SG. Effects of Corticision on paradental remodeling in orthodontic tooth movement. Angle Orthod. 2009;79:284–91.

Article PubMed Google Scholar

Eid FY, El-Kenany WA, Mowafy MI, El-Kalza AR, Guindi MA. A randomized controlled trial evaluating the effect of two low-level laser irradiation protocols on the rate of canine retraction. Sci Rep. 2022;12:1–13.

Article Google Scholar

Mousa MM, Hajeer MY, Burhan AS, Almahdi WH. Evaluation of patient-reported outcome measures (PROMs) during surgically-assisted acceleration of orthodontic treatment: a systematic review and meta-analysis. Eur J Orthod. 2022;44:622–35.

Al-Naoum F, Hajeer MY, Al-Jundi A. Does alveolar corticotomy accelerate orthodontic tooth movement when retracting upper canines? A split-mouth design randomized controlled trial. J Oral Maxillofac Surg. 2014;72:1880–9.

Alikhani M, Raptis M, Zoldan B, Sangsuwon C, Lee YB, Alyami B, et al. Effect of micro-osteoperforations on the rate of tooth movement. Am J Orthod Dentofac Orthop. 2013;144:639–48.

Hajeer MY, Al-Bitar MI, Alsino HI, Jaber ST, Brad B, Darwich K. Effectiveness of flapless cortico-alveolar perforations using mechanical drills versus traditional corticotomy on the retraction of maxillary canines in class II division 1 malocclusion: a three-arm randomized controlled clinical trial. Cureus. 2023;15.

Sirri MR, Burhan AS, Hajeer MY, Nawaya FR. Evaluation of corticision-based acceleration of lower anterior teeth alignment in terms of root resorption and dehiscence formation using cone-beam computed tomography in young adult patients: a randomized controlled trial. Int Orthod. 2021;19:580–90.

Dibart S, Sebaoun JD, Surmenian J. Piezocision: a minimally invasive, periodontally accelerated orthodontic tooth movement procedure. Compend Contin Educ Dent. 2009;30(–4):342.

PubMed Google Scholar

Dibart S, Surmenian J, Sebaoun JD, Montesani L. Rapid treatment of class II malocclusion with piezocision: two case reports. Int J Periodontics Restor Dent. 2010;30:487–93.

Aksakalli S, Calik B, Kara B, Ezirganli S. Accelerated tooth movement with piezocision and its periodontal-transversal effects in patients with class II malocclusion. Angle Orthod. 2016;86:59–65.

Alfawal AM, Hajeer MY, Ajaj MA, Hamadah O, Brad B. Evaluation of piezocision and laser-assisted flapless corticotomy in the acceleration of canine retraction: a randomized controlled trial. Head Face Med. 2018;14:1–12.

Frost HM. The regional acceleratory phenomenon: a review. Henry Ford Hosp Med J. 1983;31:3–9.

CAS PubMed Google Scholar

Alaa M, Alfawal H, Hajeer MY, Ajaj MA, Hamadah O, Brad B. Effectiveness of minimally invasive surgical procedures in the acceleration of tooth movement: a systematic review and meta-analysis. Prog Orthod. 2016;17:1.

Charavet C, Lecloux G, Bruwier A, Rompen E, Maes N, Limme M, et al. Localized piezoelectric alveolar decortication for orthodontic treatment in adults: a randomized controlled trial. J Dent Res. 2016;95:1003–9.

Charavet C, Lecloux G, Jackers N, Albert A, Lambert F. Piezocision-assisted orthodontic treatment using CAD/CAM customized orthodontic appliances: a randomized controlled trial in adults. Eur J Orthod. 2019;41:495–501.

Charavet C, Van Hede D, Anania S, Maes N, Albert A, Lambert F. One-stage versus two-stage piezocision-assisted orthodontic tooth movement: a preclinical study based on Nano-CT and RT-PCR analyses. J Stomatol Oral Maxillofac Surg. 2022.

Hajeer MY, Aljabban O, Mahaini L. The effectiveness of repetition or multiplicity of different surgical and non-surgical procedures compared to a single procedure application in accelerating orthodontic tooth movement: a systematic review and meta-analysis. Cureus. 2022;14.

Strippoli J, Schmittbuhl M, Durand R, Rompré P, Turkewicz J, Voyer R, et al. Impact of piezocision-assisted orthodontics on root resorption and alveolar bone: a prospective observational study. Clin Oral Investig. 2021;25:4341–8.

Arana JG, Rey D, Ríos H, Álvarez MA, Cevidanes L, Ruellas AC, et al. Root resorption in relation to a modified piezocision technique. Angle Orthod. 2022;92:347–52.

Article PubMed PubMed Central Google Scholar

Elkalza AR, Rateb AS. Comparative study of root resorption between two methods for accelerated tooth movement. Egypt Orthod J. 2018;53:23–30.

Mousa MR, Hajeer MY, Burhan AS, Heshmeh O, Alam MK. The effectiveness of minimally-invasive corticotomy-assisted orthodontic treatment of palatally impacted canines compared to the traditional traction method in terms of treatment duration, velocity of traction movement and the associated dentoalveolar changes: a randomized controlled trial. F1000Res. 2023;12.

Petrie A, Sabin C. Medical Statistics at a Glance. 3rd edition. John Wiley & Sons; West Sussex, UK; 2009.

Patterson BM, Dalci O, Papadopoulou AK, Madukuri S, Mahon J, Petocz P, et al. Effect of piezocision on root resorption associated with orthodontic force: a microcomputed tomography study. Am J Orthod Dentofac Orthop. 2017;151:53–62.

Aboul SMBE-D, El-Beialy AR, El-Sayed KMF, Selim EMN, El-Mangoury NH, Mostafa YA. Miniscrew implant-supported maxillary canine retraction with and without corticotomy-facilitated orthodontics. Am J Orthod Dentofac Orthop. 2011;139:252–9.

Malmgren O, Goldson L, Hill C, Orwin A, Petrini L, Lundberg M. Root resorption after orthodontic treatment of traumatized teeth. Am J Orthod. 1982;82:487–91.

Eid FY, El-Kenany WA, Mowafy MI, El-Kalza AR. The influence of two photobiomodulation protocols on orthodontically induced inflammatory root resorption (a randomized controlled clinical trial). BMC Oral Health. 2022;22:1–10.

Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15:155–63.

Stang A. Randomized controlled trials—an indispensible part of clinical research. Dtsch Ärztebl Int. 2011;108:661.

PubMed PubMed Central Google Scholar

Pandis N, Walsh T, Polychronopoulou A, Katsaros C, Eliades T. Split-mouth designs in orthodontics: an overview with applications to orthodontic clinical trials. Eur J Orthod. 2013;35:783–9.

Häsler R, Schmid G, Ingervall B, Gebauer U. A clinical comparison of the rate of maxillary canine retraction into healed and recent extraction sites—a pilot study. Eur J Orthod. 1997;19:711–9.

Üretürk SE, Saraç M, Fıratlı S, Can ŞB, Güven Y, Fıratlı E. The effect of low-level laser therapy on tooth movement during canine distalization. Lasers Med Sci. 2017;32:757–64.

Dixon V, Read MJ, O’Brien KD, Worthington HV, Mandall NA. A randomized clinical trial to compare three methods of orthodontic space closure. J Orthod. 2002;29:31–6.

Almeida MA, Phillips C, Kula K, Tulloch C. Stability of the palatal rugae as landmarks for analysis of dental casts. Angle Orthod. 1995;65:43–8.

El-Beialy AR, Fayed MS, El-Bialy AM, Mostafa YA. Accuracy and reliability of cone-beam computed tomography measurements: influence of head orientation. Am J Orthod Dentofac Orthop. 2011;140:157–65.

Tarazona-Álvarez P, Romero-Millán J, Peñarrocha-Oltra D, Fuster-Torres MÁ, Tarazona B, Peñarrocha-Diago M. Comparative study of mandibular linear measurements obtained by cone beam computed tomography and digital calipers. J Clin Exp Dent. 2014;6:e271.

Yi J, Sun Y, Li Y, Li C, Li X, Zhao Z. Cone-beam computed tomography versus periapical radiograph for diagnosing external root resorption: a systematic review and meta-analysis. Angle Orthod. 2017;87:328–37.

Dudic A, Giannopoulou C, Leuzinger M, Kiliaridis S. Detection of apical root resorption after orthodontic treatment by using panoramic radiography and cone-beam computed tomography of super-high resolution. Am J Orthod Dentofac Orthop. 2009;135:434–7.

Aboalnaga AA, Fayed MMS, El-Ashmawi NA, Soliman SA. Effect of micro-osteoperforation on the rate of canine retraction: a split-mouth randomized controlled trial. Prog Orthod. 2019;20:1–9.

Wilcko WM, Wilcko MT, Bouquot J, Ferguson DJ. Rapid orthodontics with alveolar reshaping: two case reports of decrowding. I J Periodontics Restor Dent. 2001;21:9–20.

CAS Google Scholar

Baloul SS, Gerstenfeld LC, Morgan EF, Carvalho RS, Van Dyke TE, Kantarci A. Mechanism of action and morphologic changes in the alveolar bone in response to selective alveolar decortication-facilitated tooth movement. Am J Orthod Dentofac Orthop. 2011;139:S83–101.

Teixeira C, Khoo E, Tran J, Chartres I, Liu Y, Thant L, et al. Cytokine expression and accelerated tooth movement. J Dent Res. 2010;89:1135–41.

Article CAS PubMed PubMed Central Google Scholar

Abbas NH, Sabet NE, Hassan IT. Evaluation of corticotomy-facilitated orthodontics and piezocision in rapid canine retraction. Am J Orthod Dentofac Orthop. 2016;149:473–80.

Wilcko WM, Ferguson DJ, Bouquot J, Wilcko MT. Rapid orthodontic decrowding with alveolar augmentation: case report. World J Orthod. 2003;4.

Wilcko MT, Wilcko WM, Bissada NF, editors. An evidence-based analysis of periodontally accelerated orthodontic and osteogenic techniques: a synthesis of scientific perspectives. Semin Orthod. 2008.

Jaber ST, Al-Sabbagh R, Hajeer MY. Evaluation of the efficacy of laser-assisted flapless corticotomy in accelerating canine retraction: a split-mouth randomized controlled clinical trial. Oral Maxillofac Surg. 2022;26:81–9.

Sanjideh PA, Rossouw PE, Campbell PM, Opperman LA, Buschang PH. Tooth movements in foxhounds after one or two alveolar corticotomies. Eur J Orthod. 2010;32:106–13.

Mostafa YA, Fayed MMS, Mehanni S, ElBokle NN, Heider AM. Comparison of corticotomy-facilitated vs standard tooth-movement techniques in dogs with miniscrews as anchor units. Am J Orthod Dentofac Orthop. 2009;136:570–7.

Cho KW, Cho SW, Oh CO, Ryu YK, Ohshima H, Jung HS. The effect of cortical activation on orthodontic tooth movement. Oral Dis. 2007;13:314–9.

Goldie RS, King GJ. Root resorption and tooth movement in orthodontically treated, calcium-deficient, and lactating rats. Am J Orthod. 1984;85:424–30.

Engström C, Granström G, Thilander B. Effect of orthodontic force on periodontal tissue metabolism a histologic and biochemical study in normal and hypocalcemic young rats. Am J Orthod Dentofac Orthop. 1988;93:486–95.

Sebaoun JD, Kantarci A, Turner JW, Carvalho RS, Van Dyke TE, Ferguson DJ. Modeling of trabecular bone and lamina dura following selective alveolar decortication in rats. J Periodontol. 2008;79:1679–88.

Teng GY, Liou EJ. Interdental osteotomies induce regional acceleratory phenomenon and accelerate orthodontic tooth movement. J Oral Maxillofac Surg. 2014;72:19–29.

Brezniak N, Wasserstein A. Orthodontically induced inflammatory root resorption. Part II: the clinical aspects. Angle Orthod. 2002;72:180–4.

Download references

Acknowledgements

Not applicable.

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Author information

Authors and affiliations.

Department of Orthodontics, Faculty of Dentistry, Alexandria University, Champolion street, Azarita, Alexandria, Egypt

Farah Y. Eid & Ahmed R. El-Kalza

You can also search for this author in PubMed Google Scholar

Contributions

F.E.: Conceptualization, data curation, analysis and interpretation of the study results, writing and preparing the original manuscript, reviewing and editing. A.E.: Supervision, conceptualization, performing the clinical procedures, revising the written manuscript, and helping in drawing out the final study conclusions. All authors reviewed the manuscript.

Corresponding author

Correspondence to Farah Y. Eid .

Ethics declarations

Ethics approval and consent to participate.

All the research procedures were performed in accordance with the relevant guidelines and regulations, as stated in the Declaration of Helsinki. The study was approved by the Institutional Review Board of the Faculty of Dentistry, Alexandria University, Alexandria, Egypt (IRB:00010556–IORG:0008839). Manuscript Ethics Committee number 0582-01/2023. Oral assents and written informed consents were obtained from the patients and/or their legal guardians, respectively, prior to the onset of treatment.

Consent for publication

Oral and written consents for publication have been obtained from the patients and/or their legal guardians.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Eid, F.Y., El-Kalza, A.R. The effect of single versus multiple piezocisions on the rate of canine retraction: a randomized controlled trial. BMC Oral Health 24 , 1024 (2024). https://doi.org/10.1186/s12903-024-04716-6

Download citation

Received : 15 April 2024

Accepted : 07 August 2024

Published : 30 August 2024

DOI : https://doi.org/10.1186/s12903-024-04716-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Piezocision
Acceleration
Anchorage loss
Root resorption
Tipping movement

BMC Oral Health

ISSN: 1472-6831

General enquiries: [email protected]

Sustainable Development in Omsk, 2002–3 and 2005

Cite this chapter.

Judith Marquand

Part of the book series: St Antony’s Series ((STANTS))

40 Accesses

Chapter 8 described how a three-person team from each of the distance-learning project’s four partner universities came to England early in 2001 for a course on developing distance-learning courses. Two of each team were distance-learning experts; the third was a university teacher with an interest in the content of the degree. I took these four visitors on a three-day visit to Yorkshire and Teesside to see UK environmental policy in action. The representative of Omsk State University was Professor Sergey Kostarev, then vice-chairman of Omsk Oblast Ecological Committee. At the end of the visit, he asked if I would develop a project with him in Omsk.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save.

Get 10 units per month
Download Article/Chapter or eBook
1 Unit = 1 Article or 1 Chapter
Cancel anytime
Available as PDF
Read on any device
Instant download
Own it forever
Durable hardcover edition
Dispatched in 3 to 5 business days
Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Unable to display preview. Download preview PDF.

You can also search for this author in PubMed Google Scholar

Copyright information

About this chapter

Marquand, J. (2009). Sustainable Development in Omsk, 2002–3 and 2005. In: Development Aid in Russia. St Antony’s Series. Palgrave Macmillan, London. https://doi.org/10.1057/9780230233621_10

Download citation

DOI : https://doi.org/10.1057/9780230233621_10

Publisher Name : Palgrave Macmillan, London

Print ISBN : 978-1-349-30350-2

Online ISBN : 978-0-230-23362-1

eBook Packages : Palgrave Social & Cultural Studies Collection Social Sciences (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Publish with us

Policies and ethics

Find a journal
Track your research

Open access
Published: 02 September 2024

Knowledge of antimicrobial stewardship and the Access, Watch and Reserve (AWaRe) classification of antibiotics among frontline healthcare professionals in Akwa Ibom State, Nigeria: a cross-sectional study

Mary R. Akpan ORCID: orcid.org/0000-0001-8036-8136 1 ,
Idongesit L. Jackson ORCID: orcid.org/0000-0003-3460-7233 1 ,
Unyime I. Eshiet ORCID: orcid.org/0000-0003-4388-1517 1 ,
Sediong A. Mfon ORCID: orcid.org/0009-0000-6778-8419 1 &
Ekpema A. Abasiattai ORCID: orcid.org/0009-0007-0480-0266 2

BMC Health Services Research volume 24 , Article number: 1014 ( 2024 ) Cite this article

Metrics details

Antimicrobial stewardship (AMS) aims to improve antibiotic use while reducing resistance and its consequences. There is a paucity of data on the availability of AMS programmes in southern Nigeria. Further, there is no data on Nigerian healthcare professionals’ knowledge of the WHO ‘Access, Watch and Reserve’ (AWaRe) classification of antibiotics. This study sought to assess knowledge of AMS and the AWaRe classification of antibiotics among frontline healthcare professionals in Akwa Ibom State, Nigeria.

This was a cross-sectional survey of 417 healthcare professionals, comprising medical doctors, pharmacists and nurses, across 17 public hospitals in Akwa Ibom State, Nigeria. A paper-based self-completion questionnaire was used to collect data from the participants during working hours between September and November 2023. Statistical analysis was done using SPSS version 25.0, with p < 0.05 indicating statistical significance.

Four hundred and seventeen out of the 500 healthcare professionals approached agreed to participate, giving an 83.4% response rate. Most of the participants were female (62.1%) and nurses (46.3%). Approximately 57% of participants were familiar with the term antibiotic/antimicrobial stewardship, however, only 46.5% selected the correct description of AMS. Majority (53.0%) did not know if AMS programme was available in their hospitals. 79% of participants did not know about AWaRe classification of antibiotics. Among the 87 (20.9%) who knew, 28.7% correctly identified antibiotics into the AWaRe groups from a given list. Only profession significantly predicted knowledge of AMS and awareness of the AWaRe classification of antibiotics ( p < 0.001). Pharmacists were more likely to define AMS correctly than medical doctors (odds ratio [OR] = 2.02, 95% confidence interval [CI] = 1.16–3.52, p = 0.012), whereas nurses were less likely to be aware of the WHO AWaRe classification of antibiotics than medical doctors (OR = 0.36, 95% CI = 0.18–0.72, p = 0.004).

Conclusions

There was a notable knowledge deficit in both AMS and the AWaRe classification of antibiotics among participants in this study. This highlights the need for educational interventions targeted at the different cadres of healthcare professionals on the role of AMS programmes in reducing antimicrobial resistance and its consequences.

Peer Review reports

Introduction

Antimicrobial resistance (AMR) is ranked fifth among the World Health Organisation’s (WHO) top ten global public health threats [ 1 ]. Available reports showed that an estimated 4·95 million deaths in 2019 were associated with AMR, with western sub-Saharan Africa recording highest death rate at 27·3 deaths per 100 000 [ 2 ]. Antimicrobial stewardship (AMS) has been promoted at international and national levels as a set of coordinated interventions required to improve antibiotic use and reduce resistance and associated morbidity and mortality [ 3 , 4 , 5 , 6 , 7 ]. To support AMS effort at local, national and global levels, the Antibiotics Working Group for the 21st WHO Model List of Essential Medicines adopted the ‘Access, Watch and Reserve’ (AWaRe) classification of antibiotics in the Essential Medicines List [ 8 ]. This classification, which was adopted and endorsed by G20 Health Ministers in October 2018, has since been updated and currently contains 258 antibiotics. The WHO 13th General Programme of Work 2019–2023 recommended that at least 60% of total country-level antibiotic consumption should come from Access group antibiotics [ 9 ].

There is a paucity of data on the availability and/or implementation of AMS programmes in African countries. Although a previous systematic review on the implementation of AMS programmes in African countries found no data on established hospital AMS programme in Nigeria, [ 10 ] a recent study of 20 hospitals randomly selected from the six geopolitical zones of the country to assess AMS implementation and practice reported that only six (30%) of the 20 hospitals had AMS committees with no regular AMS-related activities [ 11 ]. Successful implementation of hospital AMS programmes relies on active participation of healthcare professionals, including medical doctors with expertise in infectious diseases, pharmacists, among others [ 12 , 13 ]. To this end, the WHO global action plan on AMR emphasised improved awareness and understanding of the link between antibiotic use and development of resistance among healthcare professionals in order to optimise antibiotic use [ 14 ]. The objectives of this study therefore were to assess knowledge of AMS and the AWaRe classification of antibiotics among frontline healthcare professionals. Additionally, the study sought to assess the availability and/or implementation of AMS programmes in public hospitals in Akwa Ibom State, Nigeria.

Study design, population and setting

This was a cross-sectional survey. Participants were included purposively based on profession, if they were medical doctors, pharmacists or nurses and work in public secondary or tertiary healthcare hospitals in Akwa Ibom State. Participants were drawn from 16 state-run secondary care hospitals and one tertiary care hospital. The Raosoft online sample size calculator formula for unknown population was used to compute sample size of frontline healthcare professionals to recruit for the study. Using a 95% confidence level, 5% margin of error and population size of 20 000 and assuming 50% response distribution, the recommended sample size was 377. To account for non-response and non-completion of questionnaire, the sample size was increased by 10%; therefore a sample size of 415 frontline healthcare professionals was targeted for this study.

Survey instrument and data collection

A 13-item self-administered paper-based questionnaire was used for data collection in this study (Supplementary file). A set of 15 questionnaire items was initially developed from relevant international documents [ 7 , 8 , 9 ]. To assess content validity, the 15-item questionnaire was sent to two clinical pharmacists who are knowledgeable in questionnaire design and AMS. These experts, who were unconnected to the study, were asked to assess the instrument’s relevance and representativeness of the study objectives. Based on their feedback, two items were dropped: one was unrelated to the study objectives, while the other was redundant. In order to assess face validity, the 13-item survey instrument was administered to 10 professionals (three medical doctors, three pharmacists, and four nurses). Non-response to questionnaire items, time required to complete the questionnaire, and feedback received were used to improve the instrument. The final questionnaire comprised three sections: section A collected demographic information of respondents; section B collected data on knowledge of the term antibiotic/antimicrobial stewardship and the definition/description of AMS. For the description of AMS, six answer options, of which one was correct, were included for participants to select from. Section B also collected data on the availability of AMS in the participating hospitals, while section C contained questions on knowledge of the AWaRe classification of antibiotics. Participants were also asked to identify antibiotics belonging to ‘Access’, ‘Watch’, and ‘Reserve’ groups from a given list of antibiotics. The Cronbach’s alpha coefficient for the survey instrument in this study was 0.67. Data were obtained from the participants during working hours between September and November 2023.

Statistical analysis

Analysis was done using SPSS version 25 (IBM Corp., Amonk, NY). Descriptive statistics was used to present the data. For the item on knowledge of AMS definition, response options were stratified into ‘correct’ and ‘incorrect’. All other options apart from the correct option were coded incorrect. Binary logistic regression was performed to identify the predictors of knowledge of AMS definition and awareness of the WHO AWaRe classification of antibiotics Statistical significance was set at p < 0.05.

Ethical considerations

Ethical approval was obtained from the Health Research Ethics Committees of the Akwa Ibom state Ministry of Health (AKHREC/01/08/23/169; 07/09/2023) and the University of Uyo Teaching hospital (UUTH/AD/S/96/VOLXXI/776; 21/08/2023). Consent to participate in the survey was sought in the questionnaire; participants were required to check a box to consent they agreed to take part in the study.

Four hundred and seventeen out of the 500 healthcare professionals approached agreed to participate, giving an 83.4% response rate.

Participants’ characteristics

A total of 417 frontline healthcare professionals from 17 public hospitals participated in the study, of which majority were female (62.1%, n = 259). 46% ( n = 193) of the participants were nurses, while medical doctors and pharmacists made up 25.4% ( n = 106) and 28.3% ( n = 118), respectively. A summary of the demographic characteristics of participants is provided in Table 1 .

Knowledge of antimicrobial stewardship, antimicrobial stewardship availability and AWaRe classification among healthcare professionals in participating hospitals

Over half (56.8%, n = 237) of the healthcare professionals indicated they had heard the term antibiotic/antimicrobial stewardship. Within the professional cohorts, more than half, 57% ( n = 108) of the nurses indicated they have never heard the term. More than half (53.0%, n = 221) of the healthcare professionals indicated they did not know if AMS programme was available in their hospitals. Among those who indicated that the programme was available in their hospitals, more than half (57.4%) did not select which core element(s) applied to their hospitals.

Regarding the definition/description of AMS, less than half (46.5%, n = 194) of the participants selected the correct description of AMS.

Of the 417 participants, majority (79.1%, n = 330) indicated they have not heard the term ‘Access, Watch, Reserve’ classification of antibiotics. Within each professional group, less than half knew about the AWaRe classification of antibiotics. A summary of the knowledge of AMS, AMS availability and the AWaRe classification is shown in Table 2 .

Knowledge of the AWaRe classification of antibiotics among healthcare professionals

Only 87 (20.9%) health professionals indicated they knew about the AWaRe classification, and attempted questions on the AWaRe classification. Among the 87 who responded ‘yes”, only 25 (28.7%) correctly identified all nine antibiotics from a given list into “Access’, ‘Watch’ and ‘Reserve’. A summary of knowledge of AWaRe classification details and identification of antibiotics belonging to Access, Watch and Reserve is as shown in Table 3 .

Effects of participants’ characteristics on knowledge of antimicrobial stewardship

Table 4 presents the results of binary logistic regression to determine the effects of gender, age, profession and length of practice on the likelihood that participants correctly define AMS. Of the variables assessed, only profession significantly ( p < 0.001) predicted the model. Pharmacists were more likely to define AMS correctly than medical doctors (odds ratio [OR] = 2.02, 95% confidence interval [CI] = 1.16–3.52, p = 0.012).

Effects of participants’ characteristics on knowledge of the AWaRe classification of antibiotics

Results of binary logistic regression to assess the impact of gender, age, profession and length of practice on the likelihood that participants were aware of the WHO AWaRe classification of antibiotics revealed that only profession significantly ( p < 0.001) predicted the model. Nurses were less likely to be aware of the WHO AWaRe classification of antibiotics than medical doctors (OR = 0.36, 95% CI = 0.18–0.72, p = 0.004) (Table 5 ).

A number of studies have investigated the knowledge, attitude and perceptions of healthcare professionals (medical doctors, pharmacists and nurses) towards AMR and the effectiveness of AMS programmes in reducing AMR. Majority of the studies reported that healthcare professionals generally agree on the global and national burden of AMR, the association between antibiotic use in humans and agriculture and the development of resistance, and that AMS can reduce resistance [ 15 , 16 , 17 , 18 ]. Our findings show that more than half of the participants were familiar with the term ‘antibiotic/antimicrobial stewardship’, however, a few of the healthcare professionals selected the correct definition/description of AMS. More than half of the participants did not know if AMS programmes were available in their hospitals, especially among nurses, as well as which core components of AMS applied to their practice setting. A study of knowledge and practices of healthcare professionals towards AMS found that the majority of participants had poor knowledge of AMS, with pharmacists having better knowledge of AMS compared to nurses [ 19 ]. Although nurses have vital roles in hospital AMS, [ 20 , 21 , 22 ] and various models of nurses’ engagement in AMS have been described, [ 23 ] majority of the nurses in our study were not aware of AMS nor the correct description of the term. This finding is consistent with a previous study which found that more than half of the nurses who participated in a study to assess knowledge and attitudes were not familiar with AMS, although about 95% of the nurses believed they had a role in AMS interventions [ 24 ]. There is a likelihood that nurses’ knowledge of AMS may be setting- and/or location-specific. A previous study of nurses’ attitudes toward AMS found that approximately half of the nurses reported familiarity and knowledge of the term AMS [ 25 ]. Furthermore, a study of comparative self-assessment of knowledge on antimicrobials, AMR and AMS between medical doctors, pharmacists and nurses reported that a greater percentage of nurses had higher confidence level on knowledge of all three topics compared to pharmacists and doctors who had less confidence level [ 26 ].

Of the variables assessed, only profession significantly predicted knowledge regarding the definition of AMS. Pharmacists were twice as likely to define AMS correctly as medical doctors. In contrast to our finding, profession was not a significant predictor of AMS knowledge in the study of Sefah et al [ 19 ]. This difference in knowledge between these professions observed in our study may be because, as medicine experts, pharmacists are more aware and conscious of the association between antibiotic use and the development of resistance. The differences in knowledge could also be due to differences in undergraduate curriculum and training, as well as professional focus between pharmacists and medical doctors [ 27 , 28 ]. Prior research involving final-year medical and pharmacy students revealed that a greater proportion of pharmacy students than medical students had received formal instruction in antimicrobial stewardship [ 29 ].

The knowledge gap reported in this study and others [ 12 , 19 , 24 , 26 ] highlights the need for educational interventions such as, meetings, academic detailing, distribution of educational materials and educational outreaches [ 30 ] targeted at different cadres of healthcare professionals. Education is one of the enabling interventions of AMS which has been reported to improve compliance with antibiotic policies alone and in combination with restrictive interventions [ 30 ].

The goal of the AWaRe classification of antibiotics is to reduce AMR. The ‘Watch’ and ’Reserve’ groups of antibiotics are to be prioritised as key targets of stewardship programmes and monitoring to preserve their effectiveness [ 8 , 9 ]. In this study, an overwhelming majority of participants had no idea of the AWaRe classification. Amongst the medical doctors who participated in the study, only about a quarter knew about the AWaRe classification. This finding is of concern because of the risk of overprescribing antibiotics from the ‘Watch’ and “Reserve’ groups, which ought to be used for specific infectious syndromes and in highly specific patients and settings, [ 8 ] respectively. The current recommendation is that at least 60% of antibiotic use should come from the ‘Access’ group antibiotics [ 9 ]. Pharmacists play important roles in AMS, including prospective monitoring of antibiotic use and providing feedback and education on rational prescribing [ 31 ].

Our study revealed that only profession significantly predicted awareness of the WHO AWaRe classification of antibiotics. Although there was no significant difference in the level of awareness of the WHO AWaRe classification between pharmacists and medical doctors, nurses were less likely to be aware of this classification than medical doctors. Older guidelines for hospital AMS, [ 31 , 32 ] however, emphasised the roles of medical doctors and pharmacists in successful implementation rather than nurses’ roles. Nevertheless, the majority of the participants had no knowledge of the AWaRe classification and may therefore be unable to provide education and feedback that can promote the prescribing of the ‘Access’ group antibiotics. Among the few frontline healthcare professionals who knew about the AWaRe classification, less than one-third correctly identified nine antibiotics included in the survey instrument into ‘Access’, ‘Watch’ and ‘Reserve’ groups. The authors are unaware of studies that assessed knowledge of the AWaRe classification of antibiotics among healthcare professionals with which to compare this study findings. Nevertheless, the knowledge gap identified echoes the need for improved awareness of AMR and judicious use of antibiotics in the Watch’ and ‘Reserve’ groups through effective communication, education and training of frontline healthcare professionals.

Limitations

While this study recruited a little above the target sample size, a major limitation is that it was a single-state study, thus findings may not be generalised to other states and practice settings. Furthermore, due to the cross-sectional design of the study, causality cannot be ascertained. As is common with survey research, participant bias, which arises when participants’ responses are deliberately or unintentionally different from their intended responses, is another limitation; selection bias due to the use of the non-probability sampling method in the recruitment of study participants and the possibility of social desirability bias among the participants may have affected the findings of the study.

Overall, there was a notable knowledge deficit in both AMS and the AWaRe classification of antibiotics among healthcare professionals who participated in this study. Educational programmes should be developed for different professional groups to enhance competency and proficiency in AMS to ensure judicious use of antibiotics with a high potential for selection of resistance.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Antimicrobial resistance

Antimicrobial stewardship

Access, Watch, and Reserve

Confidence interval

Group of 20

Statistical Product and Service Solutions

World Health Organisation

Ten threats to global health in 2019. World Health Organisation. 2019. https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019 . Accessed January 10, 2024.

Murray C, Ikuta K, Sharara F, Swetschinski L, Aguilar G, Gray A, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;12(10325):629–55.

Article Google Scholar

Dyar OJ, Huttner B, Schouten J, Pulcini C. What is antimicrobial stewardship? Clin Microbiol Infect. 2017;23(11):793–8.

Article CAS PubMed Google Scholar

Policy guidance on integrated antimicrobial stewardship activities. World Health Organisation. 2021. https://iris.who.int/bitstream/handle/10665/341432/9789240025530-eng.pdf?sequence=1 . Accessed January 10, 2024.

Start smart then focus: antimicrobial stewardship toolkit for inpatient care settings. UK Health Security Agency. 2023. https://www.gov.uk/government/publications/antimicrobial-stewardship-start-smart-then-focus/start-smart-then-focus-antimicrobial-stewardship-toolkit-for-inpatient-care-settings . Accessed January 10, 2024.

Barlam TF, Cosgrove SE, Abbo LM, MacDougall C, Schuetz AN, Septimus EJ, et al. Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis. 2016;62:e51.

Article PubMed PubMed Central Google Scholar

Core elements of hospital antibiotic stewardship programs. Centers for Disease Control and Prevention. 2019. https://www.cdc.gov/antibioticuse/healthcare/pdfs/hospitalcore-elements-H.pdf . Accessed January 10, 2024.

Model List of Essential Medicines, 23rd List. World Health Organisation. 2023. https://iris.who.int/bitstream/handle/10665/371090/WHO-MHP-HPS-EML-2023.02-eng.pdf?sequence=1 . Accessed January 10, 2024.

2021 AWaRe classification. World Health Organisation. 2021. https://www.who.int/publications/i/item/2021-aware-classification . Accessed January 10, 2024.

Akpan M, Isemin N, Udoh A, Ashiru-Oredope D. Implementation of antimicrobial stewardship programmes in African countries: a systematic literature review. J Glob Antimicrob Resist. 2020;22:317–24.

Article PubMed Google Scholar

Iregbu K, Nwajiobi-Princewill P, Medugu N, Umeokonkwo C, Uwaezuoke N, Peter Y, et al. Antimicrobial stewardship implementation in Nigerian hospitals: gaps and challenges. Afr J Clin Exper Microbiol. 2021;22:60–6.

Fishman N. Policy statement on amtimicrobial stewardship by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Diseases Society of America (IDSA), and the Pediatric Diseases Society (PIDS). Infect Control Hosp Epidemiol. 2012;33:322–7.

Antimicrobial stewardship: systems and processes for effective antimicrobial medicine use. National Institute of Health and Care Excellence. 2015. https://www.nice.org.uk/guidance/ng15/resources/antimicrobial-stewardship-systems-and-processes-for-effective-antimicrobial-medicine-use-pdf-1837273110469 . Accessed January 17, 2024.

Global action plan on antimicrobial resistance. World Health Organisation. 2015. https://apps.who.int/iris/bitstream/handle/10665/193736/9789241509763_eng.pdf?sequence=1 Accessed January 17, 2024.

Tegagn GT, Yadesa TM, Ahmed Y. Knowledge, attitudes and practices of healthcare professionals towards antimicrobial stewardship and their predictors in Fitche Hospital. J Bioanal Biomed. 2017;9:091–7.

Labi A, Obeng-Nkrumah N, Bjerrum S, Adu Aryee NA, Ofori-Adjei YA, Yawson AE, Newman MJ. Physicians’ knowledge, attitudes, and perceptions concerning antibiotic resistance: a survey in a Ghanaian tertiary care hospital. BMC Health Serv Res. 2018;18:126.

Al-Halawa D, Abu Seir R, Qasrawi R. Antibiotic resistance knowledge, attitudes, and practices among pharmacists: a cross-sectional study in West Bank, Palestine. J Environ Public Health. 2019. https://doi.org/10.1155/2023/2294048 .

Tembo N, Mudenda S, Banda M, Chileshe M, Matafwali S. Knowledge, attitudes and practices on antimicrobial resistance among pharmacy personnel and nurses at a tertiary hospital in Ndola, Zambia: implications for antimicrobial stewardship programmes. JAC Antimicrob Resist. 2022. https://doi.org/10.1093/jacamr/dlac107 .

Sefah I, Chetty S, Yamoah P, Meyer JC, Chigome A, Godman B, Bangalee V. A Multicenter cross-sectional survey of knowledge, attitude, and practices of healthcare professionals towards antimicrobial stewardship in Ghana: findings and implications. Antibiotics. 2023;12:1497.

Carter E, Greendyke WG, Furuya E, Srinivasan A, Shelley A, Bothra A, et al. Exploring the nurses’ role in antibiotic stewardship: a multisite qualitative study of nurses and infection preventionists. Am J Infect Control. 2018;46:492–7.

Huizen P, Kuhn L, Russo PL, Connell CJ. The nurses’ role in antimicrobial stewardship: a scoping review. Int J Nurs Stud. 2021;113:103772.

Davey K, Aveyard H. Nurses’ perceptions of their role in antimicrobial stewardship within the hospital environment. An integrative literature review. J Clin Nurs. 2022;31:3011–20.

Castro-Sánchez E, Gilchrist M, Ahmad R, Courtenay M, Bosanquet J, Holmes AH. Nurse roles in antimicrobial stewardship: lessons from public sectors models of acute care service delivery in the United Kingdom. Antimicrob Resist Infect Control. 2019;8:162.

Merrill K, Hanson SF, Sumner S, Vento T, Veillette J, Webb B. Antimicrobial stewardship: staff nurse knowledge and attitudes. Am J Infect Control. 2019;47:1219–24.

Ju J, Han K, Ryu J, Cho H. Nurses’ attitudes toward antimicrobial stewardship in South Korea. J Hosp Infect. 2022;129:162–70.

Balliram R, Sibanda W, Essack SY. The knowledge, attitudes and practices of doctors, pharmacists and nurses on antimicrobials, antimicrobial resistance and antimicrobial stewardship in South Africa. S Afr J Infect Dis. 202110.4102/ sajid.v36i1.262.

Keijsers CJPW, Brouwers JRBJ, Wildt DJ, Custers EJF, Cate OT, Hazen ACM, et al. A comparison of medical and pharmacy students’ knowledge and skills of pharmacology and pharmacotherapy. Br J Clin Pharmacol. 2014;78(4):781–8.

Harrington AR, Warholak TL, Hines LE, Taylor AM, Sherill D, Malone DC. Healthcare professional students’ knowledge of drug-drug interactions. Am J Pharm Educ. 2011;75:199. https://doi.org/10.5688/ajpe7510199 .

Ubaka CM, Schellack N, Nwomeh B, Goff DA. Antimicrobial resistance and stewardship knowledge and perception among medical and pharmacy students in Nigeria. Open Forum Infect Dis. 2019. https://doi.org/10.1093/ofid/ofz360.1703 .

Davey P, Brown E, Charani E, Fenelon L, Gould IM, Holmes A, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev. 2017. https://doi.org/10.1002/14651858.CD003543.pub4 .

MacDougall C, Polk RE. Antimicrobial stewardship programs in health care systems. Clin Microbiol Rev. 2005;18:638–56.

Dellit T, Owens R, McGowan J, Gerding D, Weinstein R, Burke J, et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis. 2007;44:159–77.

Download references

Acknowledgements

The authors are grateful to all healthcare professionals who participated in the study.

No funds, grants, or other support was received for conducting this study.

Author information

Authors and affiliations.

Department of Clinical Pharmacy and Biopharmacy, Faculty of Pharmacy, University of Uyo, Uyo, 520271, Akwa Ibom State, Nigeria

Mary R. Akpan, Idongesit L. Jackson, Unyime I. Eshiet & Sediong A. Mfon

Pharmacy Department, University of Uyo Teaching Hospital, Uyo, Akwa Ibom State, Nigeria

Ekpema A. Abasiattai

You can also search for this author in PubMed Google Scholar

Contributions

MA conceptualised the study. All authors contributed to methods design and ethics processes. Data collection: SM; Data analysis: MA, IJ & SM; Writing of original draft: MA. All authors reviewed, edited and approved the final manuscript.

Corresponding author

Correspondence to Mary R. Akpan .

Ethics declarations

Ethics approval and consent to participate.

Approval to conduct the study was obtained from the Health Research Ethics Committees of the Akwa Ibom State Ministry of Health (AKHREC/01/08/23/169; 07/09/2023) and the University of Uyo Teaching hospital (UUTH/AD/S/96/VOLXXI/776; 21/08/2023). Informed consent to participate in the survey was sought in the questionnaire; participants were required to check a box to consent they agreed to take part in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Reprints and permissions

About this article

Cite this article.

Akpan, M.R., Jackson, I.L., Eshiet, U.I. et al. Knowledge of antimicrobial stewardship and the Access, Watch and Reserve (AWaRe) classification of antibiotics among frontline healthcare professionals in Akwa Ibom State, Nigeria: a cross-sectional study. BMC Health Serv Res 24 , 1014 (2024). https://doi.org/10.1186/s12913-024-11428-8

Download citation

Received : 10 June 2024

Accepted : 12 August 2024

Published : 02 September 2024

DOI : https://doi.org/10.1186/s12913-024-11428-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Antibiotics
Healthcare professionals