research paper on manual handling

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What constitutes effective manual handling training? A systematic review

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Stacy A. Clemes, Cheryl O. Haslam, Roger A. Haslam, What constitutes effective manual handling training? A systematic review, Occupational Medicine , Volume 60, Issue 2, March 2010, Pages 101–107, https://doi.org/10.1093/occmed/kqp127

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Background Injuries caused by manual handling are a major burden to society. Manual handling training programmes have been designed to reduce the likelihood of injury among the workforce; however, concerns have been raised over the efficacy of current manual handling training methods.

Aims To undertake a systematic review of the literature examining the effectiveness of different approaches to training in manual handling.

Methods Peer-reviewed publications along with published conference proceedings published in English, between 1980 and 2009, on the topic of manual handling training comprised the search criteria. A published checklist for reviewing papers was selected, which formed the basis for assessing the quality of the papers reviewed.

Results A total of 1827 papers were located. Following elimination of duplicates, 221 papers were collected and reviewed. Of these, 53 papers were intervention studies with the primary aim of investigating the effectiveness of manual handling training. The review identified little evidence supporting the effectiveness of both technique- and educational-based manual handling training. In addition, there was considerable evidence supporting the idea that the principles learnt during training are not applied in the working environment. Strength and flexibility training shows promise; however, further research is needed to ascertain whether such an intervention is sustainable over the long term.

Conclusions The evidence collected indicates that manual handling training is largely ineffective in reducing back pain and back injury. High priority should be given to developing and evaluating multidimensional interventions, incorporating exercise training to promote strength and flexibility, which are tailored to the industrial sector.

Musculoskeletal disorders (MSDs) have consistently remained the most commonly reported type of work-related ill-health in Great Britain according to national surveys of work-related illness [ 1 ]. Of the estimated number of individuals suffering from a work-related MSD, just over two-fifths suffer from a disorder mainly affecting their back. Back pain can arise in many work situations but is more common in tasks that involve heavy manual labour.

Manual handling has been defined as any activity requiring the use of force exerted by a person to lift, lower, push, pull, carry, move, hold or restrain a person, animal or object [ 2 ]. If these tasks are not carried out safely, there is a risk of injury and research shows a significant linkage between musculoskeletal injuries and manual handling [ 3 , 4 ], with the primary area of physiological and biomechanical concern being the lower back, particularly the discs of the lumbar spine [ 5 ]. Manual handling injuries are estimated to cost the UK £2 billion a year [ 6 ].

The Manual Handling Operations Regulations [ 7 ] set out a hierarchy of control measures to reduce risk of injury, starting with the requirement to avoid hazardous manual handling wherever practicable. Where this is not possible, attention should be given to the provision of lifting aids and task/workplace design. Employers are required to provide their employees with health and safety information and training, and where relevant this should be supplemented with more specific training on manual handling injury risks and prevention [ 8 ]. Training then has a role to play in supplementing these approaches [ 9 ]. The type of training offered and its effectiveness often depends on a multitude of factors such as method of teaching, organization setting and type of training technique that is used [ 10 ]. However, concerns have been raised over the efficacy of current manual handling training methods [ 11–14 ]. The aim of the current study therefore was to systematically review the literature to determine the effectiveness of manual handling training interventions. While previous reviews have considered interventions to reduce back pain in health care workers [ 11 , 13 ], this study examined the effectiveness of manual handling training interventions across all occupations.

The procedures applied for this review followed the recommendations of the Editorial Board of the Cochrane Collaboration Back Review Group [ 15 ]. A comprehensive literature search strategy was devised, selection criteria were applied to identify eligible trials, the methodological qualities of the included articles were assessed and the strength of the evidence from related studies was amalgamated. Unlike other reviews, we included studies conducted both in the workplace and in a laboratory environment, providing the primary goal of the research was to determine the effectiveness of a manual handling training intervention. We also included studies with and without control groups; however, the absence of a control group was reflected in the methodological quality assessment.

The following electronic databases were searched: ANTE (CSA Illumina), ArticleFirst (OCLC), ASSIA (CSA Illumina), Biological Sciences (CSA Illumina), Biotechnology and Bioengineering Abstracts (CSA Illumina), Computer and Information Systems (CSA Illumina), Health and Safety Science Abstracts (CSA Illumina), HSELINE, HSE website, Intute: Social Sciences, IOSH website, NIOSH website, NIOSHTIC-2, PsycINFO (CSA Illumina), PubMed, Science Direct, SPORTDiscuss, TOXLINE (CSA Illumina) and Zetoc.

The databases were searched for the following key text words in the title or the abstract: ‘manual handling’ with the Boolean ‘AND’ to the terms ‘training’, ‘manual handling training’, ‘effectiveness’, ‘efficacy’, ‘reduction in injuries’, ‘lifting’, ‘literature review’ and ‘patient handling’. The electronic databases were searched for articles published between 1980 and 2009. The search strategy also involved examining the reference lists of the relevant articles found to check for further studies.

The literature reviewed encompassed published articles, available in English in the databases listed above. The review was confined to articles in peer-reviewed journals, reports from health and safety agencies and published conference proceedings. Articles were included if they described empirical research in the laboratory or workplace interventions, providing that the focus of the study was the evaluation of manual handling training. Studies employing a broader approach to improving manual handling in the laboratory and workplace were also incorporated; in particular, studies that evaluated the impact of exercise in improving manual handling performance were also included. Two reviewers participated in study selection. For those studies where their eligibility for the current review was unclear from their abstract and title, the full text article was obtained and assessed.

To evaluate the quality of the papers reviewed, the 27-item checklist developed by Downs and Black [ 16 ] (as used by Hignett [ 11 ]) to assess the methodological quality of both randomized and non-randomized studies of health care interventions was applied. Three reviewers independently scored the papers, and inter-rater reliability was assessed using intraclass correlation. This checklist comprised four sections, each assessing specific aspects of the quality of the paper.

Section 1 consisted of 10 questions and evaluates the general structure of the paper, including the clarity of the study’s aims, description of the interventions applied, participant characteristics, identification of confounding factors and presentation of the main findings. Section 2 comprised three questions assessing the external validity of the study, and these questions covered the representativeness of the sample used and the context in which the study was conducted. Section 3 contained seven questions assessing the internal validity (bias) of the research. Questions in this section included the blinding of participants and experimenters to the interventions/study groups, compliance with the intervention, choice of outcome measures and statistical tests. Section 4 incorporated six questions assessing the internal validity (confounding and selection bias), and questions in this section included the sampling strategy, with respect to the diversity within the population recruited and the allocation of participants to intervention/control groups, the time period over which the study was conducted and consideration of participants lost to follow-up. A final question assessing whether the study had sufficient power was also included in the checklist.

For the purpose of the current review, two additional questions were added to Section 3 of the checklist. These questions were the following: (i) ‘was a control group used?’ and (ii) ‘was there a follow-up period?’ A full copy of the modified checklist is shown in Appendix 1 (available as Supplementary data at Occupational Medicine Online). When scoring each paper, if a question was answered ‘yes’, 1 mark was entered alongside that question, and if a question was answered as either ‘no’ or ‘unable to determine’, a mark of 0 was given. For each paper, therefore, Questions 1–28 were either awarded a mark of 1 or a mark of 0. The marks for Question 29 (which assessed statistical power) were given on a scale ranging from 0 to 4, with 0 being ‘insufficient power to detect meaningful differences at P < 0.05’, 1 being ‘just sufficient power to detect differences at P < 0.05’ and 4 being a very large sample size ( n > 1000) capable of detecting meaningful differences at P < 0.001’. The maximum marks available were 32; following the scoring of each paper, its percentage mark was calculated (see Results).

A total of 1827 papers were located. These were checked to eliminate duplications (arising from the different search strategies), and papers that were inappropriate to the research topic, based on their title and details contained within their abstract, were eliminated. A total of 221 papers were collected and reviewed. Of these, 53 papers were intervention studies with the primary aim of investigating the effectiveness of manual handling training, and these papers are included in this review. For the purpose of this review, the 53 intervention papers were grouped according to the type of intervention, or the population targeted, as follows: intervention studies conducted on health care workers, workplace- and laboratory-based intervention studies conducted in all non-health care organizations and workplace- and laboratory-based studies assessing the effectiveness of an exercise intervention for improving manual handling capabilities.

The quality rating (QR) of all intervention studies reviewed ranged from 31 to 84%. For papers to be published in peer-reviewed journals, it is expected that they all have certain key elements included, such as a statement of their aims/hypotheses. Therefore, the minimum QR expected would be ∼20% (based on certain criteria being fulfilled to be published in a peer-reviewed journal, which automatically satisfies some questions on the checklist). With this in mind, the papers included in the current review with a QR between 0 and 49% are described as ‘poor’. These papers typically had a small sample size, no control group and no follow-up. Papers with a QR between 50 and 59% are described as medium quality, those with a QR of 60–69% are described as good quality and those with a QR above 70% are described as of high quality. These papers typically contained large samples, randomization of participants into an intervention or control group, a sufficient intervention period and a follow-up assessment. Assessment of inter-rater reliability revealed an overall intraclass correlation between the three reviewers of 0.97.

Table 1 (available as Supplementary data at Occupational Medicine Online) summarizes interventions conducted on health care personnel, with the goal of reducing injuries associated with manual handling. Health care personnel, particularly nurses, are exposed to high levels of patient handling, and according to Hellsing et al. [ 25 ], the biggest risk facing nurses is work-related back pain. Nurses are estimated to have the highest rate of back pain (in comparison with other health services personnel), with an annual prevalence of 40–50% and a lifetime prevalence of 35–80% [ 32 ]. From the studies reviewed in Table 1 (available as Supplementary data at Occupational Medicine Online), there is very little evidence of the effectiveness of educational-based training for safe patient handling, whether it be nursing school based [ 19 , 21 , 25 ] or applied to qualified staff in the workplace [ 20 , 23 , 28 ]. Strength and flexibility training as reported by Gundewall et al. [ 24 ] shows promise as a measure to reduce patient handling injuries, although further research is needed to ascertain whether such an intervention is sustainable over the long term and whether it has long-term benefits in terms of injury reduction. Ergonomic training interventions, particularly those that include risk assessments and the redesign of equipment and patient handling tasks, have been shown to successfully reduce the risk of manual handling injuries [ 27 , 33 ].

Table 2 (available as Supplementary data at Occupational Medicine Online) summarizes workplace- and laboratory-based intervention studies conducted in non-health care personnel with the goal of improving manual handling training. A characteristic of the studies reviewed in Table 2 (available as Supplementary data at Occupational Medicine Online) is a lack of control groups and/or no follow-up, and according to the QR criteria applied, the majority of studies reviewed in this section have relatively low QRs. From the research reviewed in Table 2 (available as Supplementary data at Occupational Medicine Online), there is little evidence of the effectiveness of manual handling training in industries outside health care. As widely reported in the health care setting [ 47–49 ], the research reported by Carlton [ 36 ] demonstrated that principles taught during training are not carried over into the work environment.

According to Garg and Moore [ 50 ], most manual handling injuries are caused by a mismatch between a worker’s strength and the job requirements. One approach to reduce injuries has been to improve the physical capabilities of the worker, i.e. fitting the worker to the task. A number of studies have investigated the effectiveness of physical training in improving the capabilities for manual handling, and these studies are reviewed in Table 3 (available as Supplementary data at Occupational Medicine Online).

Fourteen studies investigating the effectiveness of exercise training are reviewed in Table 3 (available as Supplementary data at Occupational Medicine Online) with sample sizes ranging from 7 to 60, and a QR ranging from 38 to 69%. The research has examined the effects of exercise programmes on human capacity for manual handling tasks over the short term since the majority of studies had a training intervention lasting for ≤6 weeks (with the exception of one high-quality study [ 24 ]). The research highlights beneficial effects resulting from exercise training, in terms of improved physical capacity for manual handling tasks, over the short term. However, the majority of studies have used small numbers of university students, and little research has been conducted on workers involved with manual handling in the industrial setting. None of the research incorporated a follow-up period of a sufficient length; thus, it is unclear whether the beneficial effects seen with exercise training are maintained or how soon the effects wane following the discontinuation of training. Exercise training in the health care setting shows promise [ 24 , 30 ] [Table 1 (available as Supplementary data at Occupational Medicine Online)]; however, further research, in the form of high-quality longitudinal studies with follow-up, is required before firm conclusions can be made.

Following a review of exercise-based training, Genaidy et al. [ 64 ] highlighted that no longitudinal study had been conducted to determine the best method to maintain the improved work capacity associated with exercise-based training and that no study has correlated improved physical fitness with injury statistics.

This systematic review found that manual handling training is largely ineffective in reducing back pain and back injury. Furthermore, there was considerable evidence supporting the idea that the principles learnt during training are not applied in the working environment. A strength of the current review is the fact that it was not restrictive to a particular occupational group, enabling a comprehensive review of the effectiveness of manual handling training interventions across a range of employment sectors. The principal findings of the review are limited, however, by the high proportion of low-quality studies included in the review.

In the health care setting, there is very little evidence of the effectiveness of educational-based training for safe patient handling, whether it be nursing school based [ 19 , 21 , 25 ] or applied to qualified staff in the workplace [ 20 , 23 , 28 ]. There is also similar evidence that technique- and educational-based training are ineffective in industries outside health care [ 35 , 36 , 38 ]. In health care, there is evidence supporting the idea that the principles taught during training are not applied in the working environment [ 47–49 ], and this has also been reported in other industrial settings [ 36 , 65 ]. In general, evidence for the lack of effectiveness of manual handling training in the health care setting is provided from a number of studies reporting high injury rates occurring in workers who have undergone training [ 66–69 ].

The lack of effectiveness of technique- or educational-based training is widely acknowledged [ 11–14 ]. Kroemer [ 5 ] has suggested possible reasons: (i) people tend to revert to previous habits if training is not reinforced; (ii) emergency situations, the unusual case, a sudden quick movement, increased body weight or reduced physical well-being may overly strain the body and (iii) if job requirements are stressful, behaviour modification will not eliminate risk. Kroemer [ 5 ] argues that money and effort put into training would be better spent on research and implementation of techniques for ergonomic job design.

Strength and flexibility training as reported by Gundewall et al. [ 24 ] and Genaidy et al. [ 54–61 , 64 ] shows promise, although further research is needed to ascertain whether such an intervention is sustainable over the long term and whether it has long-term benefits in terms of injury reduction. High-quality longitudinal randomized control trials with follow-up assessment are needed to further establish the benefits of exercise-based training interventions. It is suggested that a more general approach to improving whole body physical fitness and strength, as applied by Knapik [ 62 ], would have greater benefits in terms of reducing manual handling injuries than task-specific training alone, as used in many studies [see Table 3 (available as Supplementary data at Occupational Medicine Online)]. The major disadvantage of task-specific training is that performance improvements are largely restricted to the task for which the individuals are trained [ 62 ] , and the benefits gained are not transferable to different tasks.

There is support in the literature for a more multidimensional and ergonomic approach to reducing the risks associated with manual handling, in terms of redesigning the workplace, as opposed to relying on the more traditional approaches of fitting the worker to the task. Castro et al. [ 70 ] note that health care is beginning to embrace the concept of patient care ergonomics through the implementation of safe patient handling programmes. Essential elements of such programmes include a ‘no manual lift’ policy. While such a policy requires substantial investment, Castro et al. [ 70 ] have reported that such programmes result in dramatic reductions in injuries. Furthermore, high-quality longitudinal randomized control trials are required to develop multidimensional intervention packages involving ergonomic training, risk assessments, physical training and job redesign, which can be applied to all industries.

In further research, the inclusion of a sufficient follow-up period is essential since a general theme observed in the current review is a lack of follow-up assessments. According to Westgaard and Winkel [ 71 ] when planning a work-based intervention study, outcome assessment requires adequate observation time to allow for the latency for the development of MSDs. They note that an observation time shorter than 6 months is problematic. When assessing outcomes, it is also important to consider psychosocial factors as Gundewall et al. [ 24 ] note that factors such as low job satisfaction can be a strong predictor of injury reporting. Hayne [ 72 ] states that training should start with management and work down since it is pointless training the workforce if managers/supervisors do not have the same level of knowledge. Recent research has demonstrated that MSD interventions can be made considerably more effective by tailoring interventions to managers’ and workers’ level of awareness and readiness to change [ 73 ].

In conclusion, there is little evidence for the effectiveness of educational- and technique-based manual handling training in all industries. The conclusions however are limited by the high proportion of low-quality studies, with small samples and lack of scientific rigour. There is a pressing need for high-quality randomized control trials, involving sufficiently large samples and incorporating long-term follow-up periods. Interventions to promote physical strength and flexibility show potential; however, further research is needed to ascertain whether such an approach is sustainable and whether it has long-term benefits in terms of reducing MSDs.

Musculoskeletal disorders remain the most commonly reported type of work-related ill-health in the UK, and they represent a major burden to society, organizations and the workforce.

Evidence from intervention studies conducted over the past three decades indicates that manual handling training is largely ineffective in reducing back pain and back injury.

High priority should be given to developing and evaluating multidimensional interventions, incorporating exercise training to promote strength and flexibility, which are tailored to the industrial sector.

Health and Safety Executive. Its contents, including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily reflect Health and Safety Executive policy.

None declared.

We would like to thank Dr Fehmidah Munir and Kate Shaw for their assistance with the quality scoring of papers.

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What constitutes effective manual handling training? A systematic review

Affiliation.

• 1 Work and Health Research Centre, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK. [email protected]
• PMID: 19734238
• DOI: 10.1093/occmed/kqp127

Background: Injuries caused by manual handling are a major burden to society. Manual handling training programmes have been designed to reduce the likelihood of injury among the workforce; however, concerns have been raised over the efficacy of current manual handling training methods.

Aims: To undertake a systematic review of the literature examining the effectiveness of different approaches to training in manual handling.

Methods: Peer-reviewed publications along with published conference proceedings published in English, between 1980 and 2009, on the topic of manual handling training comprised the search criteria. A published checklist for reviewing papers was selected, which formed the basis for assessing the quality of the papers reviewed.

Results: A total of 1827 papers were located. Following elimination of duplicates, 221 papers were collected and reviewed. Of these, 53 papers were intervention studies with the primary aim of investigating the effectiveness of manual handling training. The review identified little evidence supporting the effectiveness of both technique- and educational-based manual handling training. In addition, there was considerable evidence supporting the idea that the principles learnt during training are not applied in the working environment. Strength and flexibility training shows promise; however, further research is needed to ascertain whether such an intervention is sustainable over the long term.

Conclusions: The evidence collected indicates that manual handling training is largely ineffective in reducing back pain and back injury. High priority should be given to developing and evaluating multidimensional interventions, incorporating exercise training to promote strength and flexibility, which are tailored to the industrial sector.

Publication types

• Research Support, Non-U.S. Gov't
• Systematic Review
• Back Injuries / physiopathology
• Back Injuries / prevention & control*
• Databases, Bibliographic
• Ergonomics / methods*
• Inservice Training / methods*
• Low Back Pain / physiopathology
• Low Back Pain / prevention & control*
• Moving and Lifting Patients / adverse effects
• Moving and Lifting Patients / nursing
• Nursing Staff
• Occupational Diseases / etiology
• Occupational Diseases / physiopathology
• Occupational Diseases / prevention & control*
• Research Design
• Safety Management / organization & administration
• Workplace / organization & administration

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What constitutes effective manual handling training? A systematic review

2010, Occupational Medicine

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• Published: 15 November 2021

Manual handling of heavy loads and low back pain among different occupational groups: results of the 2018 BIBB/BAuA employment survey

• Martha Sauter 1 , 2 ,
• Julia Barthelme 1 , 2 ,
• Charlotte Müller 1 , 2 &
• Falk Liebers   ORCID: orcid.org/0000-0002-8412-0055 2  

BMC Musculoskeletal Disorders volume  22 , Article number:  956 ( 2021 ) Cite this article

4677 Accesses

4 Citations

Metrics details

In Germany and other European countries, many occupations still involve manual handling of loads (MHL), an activity that puts the musculoskeletal system at risk of low back pain (LBP). This study aims to describe the current prevalence of MHL in different occupational groups stratified by gender in Germany, the association between MHL and LBP and the adjusted prevalence of LBP in different respond-categories of MHL.

Data was collected in telephone interviews conducted as part of the 2018 BIBB/BAuA Employment Survey, which covers work-related topics like working conditions, education, health status and job satisfaction. The analyses were limited to full-time workers (> 35 h/week) aged between 15 and 67. The frequency of MHL was analysed descriptively. BLOSSFELD classification was used to group the participants in occupational categories. The analysis of the association between MHL and the prevalence of LBP over the last 12 months was based on robust log-linear Poisson regression that results in prevalence ratios (PR). The main regression model was adjusted for gender, age, working hours, and working conditions. Adjusted estimates for the prevalence of LBP were calculated based on regression analysis.

The sample consists of n  = 14,331 participants (men: n  = 8828, 61.6%; women: n  = 5503, 38.4%; median age 49 years). Of these, 52.8% say they were exposed to MHL at work. MHL is most common in agricultural occupations, skilled and unskilled occupations. In the regression model, participants who said they were “often” exposed to MHL reported more frequently LBP than those participants who said they were “never” exposed to MHL. The PR as estimate for the association is 1.41 (95%CI [1.32; 1.49]). Postestimation of the prevalence of LBP began with 47.3% (95%CI [43.8%; 51.1%]) for participants who said they were “never” exposed to MHL and rose to 66.5% (95%CI [62.4%; 71.0%]) for participants who indicated they were “often” exposed to MHL.

Conclusions

The 2018 BIBB/BAuA Employment Survey emphasizes that MHL is still common in the German workforce and shows a significant association to LBP. Prevention policies for avoiding MHL remain vital.

Peer Review reports

Manual handling of loads (MHL) is still a common physical workload at workplaces in Germany. According to the 2012 BIBB/BAuA Employment Survey, one fourth of employees said they “often” manually handled loads. Half of these respondents also said they suffered under this working condition [ 1 ]. Strain occurs during the packing and unloading of containers as well as when transporting furniture or during patient handling [ 2 ]. The European Agency of Safety and Health at Work (EU-OSHA) reported a proportion of 32 to 35% of workers who carried or moved heavy loads for at least a quarter of their working time across the EU28 states between 2005 and 2015 [ 3 ]. To protect employees from its adverse health consequences, MHL should be avoided as far as possible [ 4 ].

MHL is well known to be a risk factor for back pain [ 5 , 6 ], which causes a major share of health costs in Germany and is one of the main reasons for incapacity for work [ 7 , 8 ]; it also negatively affects the quality of life and everyday activities [ 9 , 10 , 11 ]. According to the German Federal Statistical Office, 3.2% of total health-care-costs in 2015 were caused by dorsopathies (ICD-10: M45 –M54) [ 7 ]. An annual data report of one of the German health insurances showed that, in 2017 back pain (ICD-10: M54) was the cause of 5.8% of sick days [ 8 ]. There is evidence that further work-related, physical and climatic factors such as heavy physical work, awkward postures, whole-body-vibrations, slipping and falling or working in cold environments contribute to the multifactorial causes of back pain [ 6 , 9 , 12 , 13 ]. Furthermore, sitting and standing a have also been shown to be associated with low back pain (LBP) [ 14 , 15 , 16 ]. Apart from these physical working exposures, psychosocial factors and working hours also affect the genesis of musculoskeletal disorders [ 6 , 17 , 18 ]. Gender, age, anthropometric characteristics, socioeconomic status, and smoking are other factors that influence back pain [ 5 , 6 , 9 , 19 ].

Conducting risk assessments at the workplace is considered a basic step to derive and implement effective measures of primary prevention to reduce physical workload as a work-related risk factor of low back pain [ 20 ]. In a work-specific context, this strategy has also been embedded in German and European legislation [ 21 , 22 ]. Even though digitalization and technological progress are changing working environments, resulting in a decrease in physical workload, there are still professions in which physical strains are high [ 23 ].

It is important to use existing data to keep MHL under surveillance in Germany and to contribute to European surveillance. According to Hulshof et al. (2021) [ 24 ], only few studies present current data. Furthermore, the results of our analysis support the preparation and justification of preventive measures in the third period of the Joint German Occupational Safety and Health Strategy (“GDA”, www.gda-portal.de ) regarding the prevention of musculoskeletal workloads at workplaces. By determining the current prevalence of MHL in different professions, target-oriented primary prevention programs can be implemented. Reducing the prevalence of MHL – as a risk factor for low back pain – can help to reduce the prevalence of low back pain as one of the most expensive disorders in workers with high physical demands [ 7 , 8 , 13 ].

This study aims to investigate the current prevalence of manual handling of heavy loads in different occupational groups stratified by gender in Germany, the association between MHL and self-reported LBP, and adjusted prevalence of low back pain in the different respond categories of MHL, using the 2018 BIBB/BAuA Employment Survey conducted by the Federal Institute of Occupational Training (BIBB) and the Federal Institute for Occupational Safety and Health (BAuA) [ 25 ]. The STROBE checklist was used to secure transparent reporting in this paper [ 26 ].

Study design and setting

The 2018 BIBB/BAuA Employment Survey [ 25 ] is an interview-based, cross-sectional study. The survey is conducted periodically every 6 years and aims at gathering information about the working conditions of the German workforce. All participants gave their verbal consent during the telephone interview. The BAuA ethics committee approved the study and its procedure (EK007_2017 January 9, 2017). Interviews of 20,012 employees were conducted by the social research company Kantar Public from August 2017 to April 2018 using a computer-assisted telephone questionnaire. For the sampling a random-digital-dialing approach was used. For the landline numbers, a two-stage process, so called Kish-Selection-Grid, was implemented to secure equal chances to get interviewed. For mobile numbers it was assumed that the devices are used only by one person. To minimize selection bias, a dual frame approach was implemented to enable interviewers to also contact persons who are only available via cell phone. Furthermore, participants were interviewed in the afternoon, in the evening and on weekends. This led to a sample that consists of 70% landline and 30% mobile network users. Interviewers needed 40 min on average to complete the questionnaire in full. The questionnaire was developed based on the previous 2012 BIBB/BAuA Employment Survey. The main parts are identical to this survey, but some questions were supplemented by new questions. The main topics of the survey, which were assessed are information on the respondent’s current occupation, working conditions, education, health status and job satisfaction [ 27 ]. Further information about the methods of the 2018 BIBB/BAuA Employment Survey are available online ( www.bibb.de ) [ 25 ].

Participants and study size

Participants were included in the 2018 BIBB/BAuA Employment Survey if they were 15 years of age and over, were employed for 10 h per week or more and had an adequate command of the German language. It was conditional to be paid for their work to meet the selection criteria “employed”. This definition was specified for some special cases. This specification has been described in detail earlier [ 25 ]. A total sample of 20,012 employees were included in the survey. This study was conducted as part of project no. F2456, Footnote 1 conducted by the Federal Institute for Occupational Safety and Health (BAuA). For the current study, the sample was restricted to full-time workers (> 35 h/week) in the ages between 15 and under 67 years, resulting in a sample size of 14,414 participants. The resulting sample did not include minors under the age of 16 years. We employed a complete case analysis; therefore, a total of 14,331 persons with complete data were included in the study to examine the prevalence of MHL and its association to LBP (see Additional Table  1 ). As this is a secondary analysis of a sample with high number of participants, we did not perform a formal calculation of the sample size. Due to the large sample size, the power to detect even small difference between the categories of the exposure variable is high.

Operationalization of the variables

All variables were based on self-reports of the participants and collected during the telephone interview of the 2018 BIBB/BAuA Employment Survey.

Outcome variable

During the telephone interview, participants were asked in German if they had experienced pain in their lower back in the last 12 months (“ Please tell me if you have had any of the following health problems during work or on working days in the past 12 months. We are interested in complaints that occurred frequently: Low back pain ” / author’s translation from German). Possible answers were “yes” or “no”. The question had been designed specifically for and applied similarly in all previous BIBB/BAuA employment surveys.

Exposure variable

To assess manual handling of heavy loads, participants were asked how often they had to lift heavy loads (> 20 kg for men and > 10 kg for women). Participants could answer “often”, “sometimes”, “rarely” or “never” to categorize how often they manually handled heavy loads.

Selected confounders

During the telephone interview, respondents were asked to answer questions on their gender (“men”, “women”), age (in years), actual weekly working hours, how often they stood, sat or worked in awkward postures (bending, kneeling, working overhead), climatic factors (“work in cold, heat, wet, damp or draught conditions”) and psychosocial workload (e.g. deadlines and performance pressure). The psychosocial index was operationalized as index (WL PSY ) from 0 to 100 index points. The selection of items used in the index is comparable to the selection made by Kroll (2011) [ 28 , 29 ]. Three subcategories (psychological stress, social burden, temporal involvement) were calculated by adding up points assigned to the items according to the answers. The achieved score was divided by the maximum possible points for valid answers. For WL PSY the sum of these scores was standardized based on the total amount of validly answered subcategories. The higher the score of the index, the greater the psychosocial workload is assumed.

With the exception of awkward postures, working conditions were assessed in the same way as the manual handling of loads, using the categories “often”, “sometimes”, “rarely” and “never”. In the regression model, dummy variables were used to adjust for awkward postures. These were based on the questions regarding how often respondents worked in awkward postures (“often”, “sometimes”, “rarely” and “never”). Interviewers only asked for details on the specific type of posture (kneeling, working overhead, and working in bended postures) if participants responded “often”. Further information about the construction of the dummy variables is provided in the additional material (Additional Fig.  1 ). A German system for classifying occupations, published by B lossfeld , was used to assess occupational groups. This system divides occupations into 12 groups (agricultural occupations, unskilled manual occupations, skilled manual occupations, technicians, engineers, unskilled services, skilled services, semiprofessions, professions, unskilled commercial and administratorial occupations, skilled commercial and administratorial occupations, managers) [ 29 ].

Missing data

The dataset of the 2018 BIBB/BAuA Employment Survey is only missing a small proportion of data. For the relevant exposure variable, only 0.1% of information is missing, and only 0.4% of information on outcome variable LBP. A complete case analysis was therefore performed, on the assumption that the data was missing completely at random.

Statistical methods

The statistical analysis was performed fully syntax based using SPSS 25® statistical software. The description for all variables used are shown stratified by gender (“men”, “women”). For categorical variables, the absolute number (n) and relative frequencies have been presented and for numeric variables arithmetic mean, standard deviation (SD) and median have been provided. Unadjusted prevalences of MHL were estimated based on the descriptive statistics of the data of 14,331 participants. For gender-specific prevalences of MHL in different occupational groups, data was stratified separately for men and women based on the B lossfeld occupation code.

Associations between MHL and LBP were estimated using blockwise adjusted multivariate Poisson regression with robust variance estimates. This approach was used to obtain prevalence ratios (PR) directly from effect estimates of the model. 95% confidence intervals (95%CI) were calculated based on the robust variance estimates. PR with 95% confidence intervals were rounded to two decimal places and used as effect estimates of the association between MHL and LBP. We included sets of confounders step by step to receive information about their influence on the effect estimates resulting in five models. The models were built as follows:

Unadjusted Model #0: only MHL as exposure, no other covariates

Adjusted Model #1: unadjusted Model #0 + gender and age

Adjusted Model #2: adjusted Model #1 + working hours

Adjusted Model #3: adjusted Model #2 + further physical and climatic working conditions

Main Model #4: adjusted Model #3 + psychosocial workload

In detail the main regression model was adjusted for gender, age, working hours, standing, sitting, awkward postures (bending, kneeling, working overhead), climatic factors and psychosocial workload. Confounders considered in the regression models were selected based on an a priori review of the available evidence of relevant cause-effect relationships. The resulting list was included in an underlying causal diagram and considered in the regression model [ 30 ]. The dependent variable was LBP. Postestimations were done on the basis of the main regression Model #4 to derive adjusted estimates of the prevalence of LBP, assuming that the cofactors are equally distributed. This leads to the assumption that the population exhibits an equally distributed proportion of men and women. To simplify the interpretation of the estimated prevalence of LBP age was centered to 45 years, working hours to 40 h/week (median of the subsample) and the index for WL PSY to 38.9 points (arithmetic mean of the subsample). In the postestimation we controlled for these metric variables by choosing the value zero. Subsequently the results of the estimated prevalence refer to a person aged 45, who works 40 h/week, with a mean psychosocial workload of 38.9 index points. The resulting prevalence was rounded to one decimal place.

Participants

In our analysis, 14,331 participants were included from the total dataset of the 2018 BIBB/BAuA Employment Survey ( n  = 20,012), of which 61.6% were men ( n  = 8828) and 38.4% women ( n  = 5503), with a median age of 49 (min = 16 years; max = 66 years). Participants ( n  = 5598) were not included if they did not meet the selection criteria of the study project F2456 of the BAuA. Of those n  = 83 were not included in this specific analysis because they had missing data. For further information about missing data please see the additional material (Additional Table 1 ). On average respondents worked 43.81 h a week and indicated a psychosocial workload of 38.9 index points. Of this population, 52.8% of participants ( n  = 7570) said they were exposed to manual handling of heavy loads at work and 17.5% ( n  = 2505) said that they “often” manually handled loads during working hours. As to low back pain, 43.9% ( n  = 6294) stated that they had experienced pain in their lower back in the last 12 months. Further characteristics are provided in Table 1 .

Prevalence of manual handling of heavy loads among different occupational groups

Regarding the prevalence of manual handling of heavy loads in different occupational groups (as defined by B lossfeld (1985)), the analysis shows that 56.1% ( n  = 105) of men and 54.8% ( n  = 34) of women in the agricultural sector answered “often”. For men, this is followed by persons working in skilled manual occupations (44.6%, n  = 540), unskilled manual occupations (37.4%, n  = 253) and unskilled services (31.2%, n  = 271).

For women, the ranking continues with skilled manual occupations (39.3%, n  = 64), unskilled manual occupations (34.4%, n  = 53), semiprofessions (30.5%, n  = 435) and unskilled services (30.2%, n  = 67).

Women in semiprofessions answered “often” more frequently than men, with a total of 17.1 percentage points compared to 13.1% ( n  = 75) for men. Figures  1 and 2 show the prevalences of exposure to manual handling of heavy loads in the categories “never”, “rarely” and “sometimes” stratified by gender. The corresponding data is provided as Additional Table  2 .

Self-reported frequency of MHL in women among different occupational groups

Self-reported frequency of MHL in men among different occupational groups

Association between manual handling of heavy loads and low back pain

Table 2 shows the crude prevalence of low back pain as the outcome of interest, stratified by the self-reported frequency of manual handling of loads. The prevalence of low back pain increases from 36.0% ( n  = 2435) in participants who answered “never” to 65.9% ( n  = 1651) in participants who answered “often”. Furthermore, Table 2 shows the distribution of all considered confounders in the main Model #4, such as age, gender, working hours, and current weekly working time, physical and psychosocial workloads, stratified by the MHL categories.

Association between MHL and LBP – results of the unadjusted model #0

In the unadjusted model, the prevalence ratio for LBP is estimated at 1.83 (95%CI [1.75; 1.91]) for participants who frequently handle heavy loads manually compared to participants who never handle heavy loads (“never”). In the categories “rare” (1.12 95%CI [1.06; 1.18]) and “sometimes” (1.38 95%CI [1.30; 1.46]) also reveal an association to manual handling of heavy loads compared to participants indicating no manual handling of heavy loads (“never”).

Association between MHL and LBP – result of the main model #4 (adjusted)

After adjusting for gender, age, actual weekly working hours, and further working conditions, including psychosocial workload, this relationship decreases, as can be seen in Table  3 . This decline was mainly due to the adjustment for further physical workloads (e.g. awkward postures) as can be seen in Fig.  3 with the decrease of the prevalence ratio from adjusted Model #2 to adjusted Model #3. Full results of the blockwise regression have been provided as additional material (Additional Table 3 ). Nevertheless, the positive association between the manual handling of heavy loads and LBP is revealed after adjusting for all selected confounders. The model-based, estimated prevalence of LBP increased with the frequency at which heavy loads were handled manually. Participants who said that they “often” handled heavy loads manually reported 40.7% more disorders in the lower back (PR 1.41 95%CI [1.32; 1.49]) compared to participants who said that they never handled loads manually (“never” MHL). Participants who said they “sometimes” (PR 1.19 95%CI [1.12; 1.27]) or “rarely” (1.07 95%CI [1.01; 1.13]) handled loads manually also showed an increased prevalence of LBP compared to the reference group (“never” exposed to MHL). The frequency of working in awkward postures (bending (PR 1.19 95%CI [1.11; 1.27]), kneeling (PR 1.11 95%CI [1.04; 1.19]), sometimes working in awkward postures (PR 1.10 95%CI [1.03; 1.16]), being exposed to hard climatic factors (PR: 1.22 95%CI [1.15; 1.28]), and increased psychosocial workload (PR: 1.11 95%CI [1.08; 1.13]; concerning a change of 10 index point) are also positively associated with LBP in the main Model #4. Furthermore, the results indicate that women (PR 1.21 95%CI [1.16; 1.25]) are at higher risk of low back pain. Sitting (PR 0.90 95%CI [0.85; 0.95]) during working hours and actual weekly working hours (PR 0.92 95%CI [0.90; 0.95], concerning a change of 10 h per week.) show a negative association with LBP. Table 3 shows the adjusted prevalence ratios of the main model.

Relative risk of low back pain in the respond-categories of manual handling of heavy loads. Considered covariates in Model #4: age and gender, working hours, further physical and climatic working conditions and the psychosocial workload

Estimated prevalences of low back pain in the main model #4

The estimates of the prevalence of LBP based on the adjusted model (main Model #4) increase with the frequency at which heavy loads are handled manually. 47.3% (95%CI [43.8%; 51.1%]) of participants who said they never handle heavy loads manually (“never”) indicated complaints in the low back. In the “rarely” category, this value increases to 50.4% (95%CI [46.8%; 54.3%]), and for participants who answered that they “sometimes” handle loads manually it is estimated to be 56.4% (95%CI [52.4%; 60.6%]). For those who answered that they “often” lift heavy loads manually, the estimated percentage of persons who reported pain in their lower back rises to 66.5% (95%CI [62.4%; 71.0%]).

The aim of the study was to determine the current prevalence of MHL in different occupational groups stratified by gender in Germany, the association between this physical strain and low back pain and to estimate adjusted prevalence of LPB in the respond categories of MHL.

The analysis of the German Employment Survey of the Working Population on Qualification and Working Conditions reveals that employees in the agricultural sector frequently handle loads manually (“often”), with a prevalence of over 50% for both men and women. Persons employed in skilled and unskilled manual occupations or unskilled services also indicate a high prevalence of manual handling of heavy loads. Women who work in semiprofessions are also often exposed to the manual handling of heavy loads at work, with 30.5% responding that they “often” manually handle heavy loads. Only 13.1% of men working in these professions said they were “often” exposed to these activities at work. These results correspond to other studies on Germany’s working population, like the so called “DGB Report” (grey literature) provided by German Trade Union, which reports that 55% of employees in Germany perform heavy physical work (including manual handling of heavy loads) [ 1 , 31 ]. A comparison of these results is however difficult, because of the different settings of the studies. Although data about manual handling of heavy loads were assessed in previous BIBB/BAuA Employment Surveys an evaluation of a change of exposure prevalence is difficult to interpret because participants differ in the surveys, there might be a change in the occupational structure and the overall settings of the surveys.

Furthermore, it is a well-known fact that manual handling of loads is a risk factor for musculoskeletal diseases in persons who work in the agricultural sector [ 32 , 33 ].

The analysis of this survey underlines the well-known relationship between manual lifting or carrying of heavy loads and LBP [ 5 , 6 ]. After adjusting for gender, age, actual weekly working hours and physical, climatic and psychosocial working conditions, the prevalence of LBP in employees who frequently handle heavy loads manually is 1.41 times higher than in employees who are not exposed to such activities. According to other studies, effect estimates vary between 1.5 and 3.1, depending on selected confounders [ 6 ]. Due to the subjective measurement of the exposition in this study, it is possible that the estimated effect is too low [ 6 ]. This may be a reason for the lower effect found in this analysis.

When the adjusted prevalence of LBP for workers who frequently handle heavy loads manually is compared to workers who don’t handle heavy loads, it is shown that 19.2 percentage points of LBP can be avoided by reducing manual handling of heavy loads. This underlines the huge potential for primary prevention of MHL to reduce the prevalence of LBP in workers.

Compared to the unadjusted model the effect decreases with the adjustment for the selected covariables. According to the results of the blockwise regression, the main reason for the reduction seems to be the adjustment for physical and climatic working conditions (sitting, standing, awkward postures and climatic factors). The difference between the results of the unadjusted and adjusted model emphasizes the importance of adjustment, when analysing physical strains.

With the increasing frequency of MHL, the estimated prevalences of LBP rise from 47.3% for employees who responded that they do not handle heavy loads manually to 66.5% for those who answered that they “often” handle heavy loads manually. It is already known that the frequency of MHL has an impact on the mechanical strain of the spine [ 6 ]. The results support this knowledge.

The results of this analysis of the 2018 BIBB/BAuA Employment Survey contribute to the third period of the Joint German Occupational Safety and Health Strategy (“GDA”, www.gda-portal.de ), in which specific workplace preventions programs are put into practice to minimise the impact of physical workloads. This supports also the need for prevention of work-related musculoskeletal disorders aimed in the current EU-OSHA campaign “Lighten the Load” 2020-22 ( https://healthy-workplaces.eu/en ).

Some limitations of the study should be considered. The data originated from a cross-sectional study and was collected via telephone. For this reason, there may be selection bias due to the respondents’ availability by phone and their willingness to participate (“self-selection bias”). Efforts were made to obtain the basic data of the non-responders by means of a short questionnaire. However, response rates were too low to allow a comparison of the groups. Interviews were conducted in German; this is why persons without an adequate command of the language have been excluded. Therefore, important data of a potentially vulnerable group of employees is missing.

All variables are based on self-reports of the participants, which leads to an information bias due to memory failure and recall bias. With regard to the latter, it is known that persons with complaints tend to overestimate exposure; in other words, persons without complaints underreport exposure [ 34 ]. The resulting differential misclassification of the exposure status can lead to an overestimation of the effect [ 34 ]. Recall bias may also result in respondents underestimating the effect [ 34 ]. However, objective measurements cannot be obtained for the high number of participants ( n  = 20,012) analysed in this study.

It should be kept in mind, that the major part of the questions of the BIBB/BAuA Employment Survey are self-developed items, which cannot be linked to validated questionnaires [ 27 ]. For instance, LBP was only assessed by asking if it occurred; how often the pain occurred and how intense it was remains unclear. If the question regarding LBP was affirmed, the case definition in this study was fulfilled. This case definition is not in line with a consensus- and synthesised-based case definition for non-specific LBP by van der Molen et al. (2021) [ 35 ], who summarized previous case definition applied in the literature.

The assessment of MHL in the categories “often”, “sometimes”, “rarely” and “never” based on a pre-set specification of heavy loads as weights greater or equal than 20 kg for men and 10 kg for women could have caused an underestimation of the effect size regarding manual handling of loads. It should be mentioned that according to Kuijer et al. (2014) [ 36 ] a risk assessment for loads between 3 and 25 kg is advised. Therefore, it is possible, that persons who reported no manual handling of heavy loads could have pain in their lower back due to manual handling of loads with less weight than indicated in the question in the survey. As this might have affected our reference group, we cannot exclude a possible underestimation of the effect size.

It should be kept in mind, that physical work exposures do not occur isolated in real life. For example, results of the analysis of the 2018 BIBB/BAuA Employment Survey show, that 61.5% of persons, who frequently work in awkward postures and 41.1% of persons, who perform manual handling operations also reported frequent manual handling of heavy loads [ 37 , 38 ]. Andersen et al. (2021) [ 39 ] underline the importance of combined physical workload in the development of MSD. The results of their prospective cohort study, which compared clusters with different exposure combinations, showed that workers exposed to a combination of lifting/carrying, pushing/pulling, working in awkward postures for most of their working time and performing manual handling operations had the largest increase in pain in their lower back [ 39 ].

In addition, the question on the assessment of climatic factors in particular is imprecise (see Operationalization). The index used for the operationalization of psychosocial workload is based on the calculation of a validated index. Secondary data was used to investigate the research questions. The 2018 German Employment Survey of the Working Population on Qualification and Working Conditions does not provide all confounders that are considered important for the investigated research question. For instance, smoking status, anthropometric data and occupational exposure to whole-body-vibrations were not available in the dataset and could not be included in the analysis. However, there may be over-adjustment bias, as a high number of cofactors that were included as models were built based on knowledge obtained from the literature [ 40 , 41 ].

When interpreting the results, it should be kept in mind that the data exclusively originated from employed persons, who tend to be healthier in comparison to the total population. This can lead to bias due to the healthy worker effect. Therefore, the results cannot be applied in full to the general situation in Germany. The weighted sample of the 2018 BiBB/BAuA Survey with n  = 20,012 participants is representative for the German labour force. The weighting factor included age, gender, household size, marital status, job position, nationality and state of residence. However, in this analysis we used a subsample, which was restricted to age, and weekly working hours. Therefore, we could not apply the weighting factor to our subsample. Consequently, the representativeness of our subsample is limited.

Although this cross-sectional study cannot reveal a causal relationship, the dataset represents the largest survey that considers the working conditions of the German working population with an absolute number of 20,012. Furthermore, the aim of the study was to derive prevalence of MHL in the work force in Germany. By using a dataset with such a high number of participants, it is possible to detect even small effects between the exposure categories regarding the outcome. Statistical significance of small differences alone may not be relevant, and do not implicate a need for a practical intervention or prevention approach.

The 2018 BIBB/BAuA Employment Survey could be used to generate a Job Exposure Matrix [ 42 ], because it provides a huge dataset with information about wide range of work-related exposures and occupational groups.

It is still a common occurrence for the German work force to be exposed to the manual handling of heavy loads at work, even though this is already known to be a risk factor, particularly for the lower back. Furthermore, we could confirm an association between manual handling of heavy loads and lower back pain in this secondary analysis. The surveillance of physical strains remains important. According to the results of this study, avoiding this physical workload has huge potential to prevent pain in the lower back – especially in professions in the agricultural sector (i.e. farmers), unskilled manual occupations (i.e. construction helpers), skilled manual occupations (i.e. locksmiths) and in unskilled services (i.e. waiters) –and should furthermore be sustained.

Availability of data and materials

The dataset (number ZA7574) supporting the conclusions of this article is available as scientific-Use-File. The access to the dataset is closed. Administrative permission to access and use can be requested externally at „BIBB – Bundesinstitut für Berufsbildung - Forschungsdatenzentrum “(Postfach 201264; 53142 Bonn; Germany; fax number: + 49 – (0)228 – 107 – 2020)). The dataset will be available as ftp-download after approved application.

www.baua.de/DE/Aufgaben/Forschung/Forschungsprojekte/f2456.html

Abbreviations

European Agency of Safety and Health at Work

Low back pain

Manual handling of heavy loads

Prevalence ratio

Index for psychosocial workload

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Acknowledgements

We would like to thank Prof. Dr. Ute Latza for her support during the process of writing the manuscript and for being one of the supervisors of the corresponding master thesis, which was part of the research project. We thank Prof. Lena Hünefeld and colleagues for providing the dataset of the 2018 BiBB/BAuA Employment Survey. We also would like to thank Eurolingua.de (Dortmund) for proofreading and checking the language of the draft. Furthermore, we like to thank the reviewers for their feedback and their constructive criticism.

Open Access funding enabled and organized by Projekt DEAL. The study is part of the F2456 project conducted by the Federal Institute for Occupational Safety and Health (BAuA) and focuses on physical occupational exposures and complaints of the musculoskeletal system. Further information can be found online ( www.baua.de/DE/Aufgaben/Forschung/Forschungsprojekte/f2456.html ). The funding body (BAuA) played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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FL and MS did the conception of the work, FL and MS prepared the data for analysis, MS analysed the data, all authors worked on the interpretation of data, MS prepared the manuscript; JB, CM, FL reviewed the manuscript. All authors read and approved the final manuscript.

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All participants gave their verbal informed consent during the telephone interview. The verbal informed consent were used due to the sampling procedure. Minors gave consent themselves. There were no data protection concerns about this procedure. Furthermore, the BAuA ethics committee approved the study and its procedure (EK007_2017 January 9, 2017). Administrative permission to access and use the dataset of the 2018 BIBB/BAuA Employment Survey within the scientific project F2457 was granted internally for every author of the draft by Prof. Lena Hünefeld (BAuA Unit 1.2 ‘Monitoring Working Conditions’ / Division 1 ‘Changing World of Work’) at the Federal Institute for Occupational Safety and Health (BAuA) by signing user agreements.

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Supplementary Information

Additional file 1: additional table 1..

Number of missing values per item after applying of selection criteria considering participants aged < 67 and at least 35 h weekly working time. Number of missing values per item used in the main Model #4 after applying of selection criteria considering participants aged < 67 and at least 35 h weekly working time.

Additional file 2: Additional Table 2.

Manual handling of heavy loads in occupational groups ( n  = 14,331; missings n  = 62). The table present the data of manual handling of heavy loads in different occupational groups in men and women. Data was presented as figure in the manuscript.

Additional file 3: Additional Table 3.

Prevalence ratios of further models. Models used in the blockwise regression analyses and main results of the models regarding the relative risk of low back pain in the last 12 months stratified by the self-reported frequency of manual handling of heavy loads.

Additional file 4: Additional Figure 1.

Construction of the dummy-variables. Flowchart of the construction of the dummy-variables for working in awkward postures used in the regression analyses.

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Sauter, M., Barthelme, J., Müller, C. et al. Manual handling of heavy loads and low back pain among different occupational groups: results of the 2018 BIBB/BAuA employment survey. BMC Musculoskelet Disord 22 , 956 (2021). https://doi.org/10.1186/s12891-021-04819-z

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DOI : https://doi.org/10.1186/s12891-021-04819-z

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• J Educ Health Promot

Effectiveness of training program in manual material handling: A health promotion approach

Ameneh jari.

1 Department of Occupational Health and Safety, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Nazi Niazmand-Aghdam

Sadegh ahmadi mazhin.

2 Department of public Health, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Mohsen Poursadeghiyan

3 Social Determinants of Health Research Center, Ardabil University of Medical Sciences, Ardabil, Iran

4 Department of Occupational Health Engineering, School of Health, Ardabil University of Medical Sciences, Ardabil, Iran

Ali Salehi Sahlabadi

Background:.

Even in an era of automation and digitalization, Manual Material Handling (MMH) can be called the most common industrial task. The aim of this study was to evaluate the prevalence of musculoskeletal disorders (MSDs) induced by manual handling tasks on the workers of a printing factory in Tehran in 2017 and then to evaluate the effectiveness of a training intervention based on health promotion.

MATERIALS AND METHODS:

This study had quasi experimental design and was conducted on 40 men. First, demographic data were collected and the Nordic questionnaire was used to determine the prevalence of MSDs in workers. Then, MMH tasks were assessed using Manual Handling Assessment Chart (MAC). A short training course was designed to promote health. Finally, the same MMH tasks were re-evaluated 3 months after the training intervention.

Among the various tasks, the highest prevalence of work-related MSDs (WMSDs) was observed in the lower back (77.5%) and shoulder (62.5%). Based on the final scores of the MAC method, the jobs that received the highest scores were cutting (individual lifting), with 22 scores and action level “immediately necessary,” cutting (individual load carrying), with 15 scores with action level “urgently needed.” Arranging the forms (individual lifting) received a similar score. After the training intervention, the estimated risk level reduced by 12, 9, and 6 points, respectively, reaching a safe action level, i.e., “necessary in the future.”

CONCLUSION:

The results demonstrated that educational interventions might be equally effective in low-technology work environments. More in general, the MAC method can be used to make informed planning of educational interventions against WMSDs risk in MSDs. This health promotion approach is critical for care of human recourse.

Introduction

Printing industry is among the main industries in the country of Iran. Factories in Tehran, which is the capital of Iran, are significantly active in this industry. Workers in this industry are exposed to chemicals and solvents.[ 1 ] Furthermore, due to the type of process and their tasks, they are widely involved in inappropriate postures and manual material handling (MMH).[ 1 ] Manual handling is defined as any activity that requires a person to use force to push, pull, lift, lower, carries, or holds an object.[ 2 ] Occupational tasks in the printing industry that are considered ergonomically, include Manually carrying newspaper packages, repetitive movements of upper limb associated with paper cutting machines, cleaning and preparing the printing machine, embedding the papers and maintaining the machines, which usually puts a person in a difficult situation causing musculoskeletal damages.[ 1 , 3 ]

In general, musculoskeletal disorders (MSDs) have a multifactorial origin with physical, psychological, and social causes. The physical causes may include incorrect physical postures, repetitive movements, excessive force throughout the working day, as well as an unsuitable environment while MMH.[ 4 ] Studies have shown that mismatch between people and the workplace can lead to pain in the lower leg, foot sole, knee, neck, shoulders, and waist.[ 5 ] Work fatigue is defined as a difficulty in concentrating on continuous activities,[ 6 ] which is an effective factor in increasing the incidence of human error.[ 7 ] The possible consequences of fatigue are decreased ability in information processing, decreased level of safety, and level of physical and mental health and increased reaction time.[ 8 ] Work fatigue is recognized as a risk factor for MSDs. A work environment designed based on ergonomic principles can prevent MSDs among workers and also reduce fatigue among them.[ 9 ]

Work-related MSDs (WMSDS) can cause productivity reduction, decrease work quality,[ 10 ] and increase in absenteeism.[ 11 ] Evidence has shown that reducing and preventing musculoskeletal problems is an important global priority.[ 12 ] In assessing MSDs, self-report questionnaires[ 13 ] are used as a tool to collect data, with The Nordic Musculoskeletal Questionnaire (NMQ) as the most known.[ 14 ] In this questionnaire, a body map is provided which divides body into nine separate areas (neck, shoulders, elbows, wrists/hands, upper back, lower back, hips/thighs, and ankles/feet) and the presence or absence of pain and severity of pain in these areas has been monitored for the past 12 months.[ 15 ]

Khandan et al. ,[ 16 ] showed that MSDs in the lower back with 35.1% had the highest prevalence among workers in the printing industry. Frequent and heavy weight MMH has been cited as a risk factor for occupational back pain.[ 17 ] Therefore, due to the importance of this ergonomic risk factor, the main purpose of ergonomic programs is to prevent MSDs related to lifting and repetitive tasks.[ 18 ] One of the preventive measures undertaken by various organizations is conducting methods for determining the permitted weight in manual handling tasks. These include Snook tables, manual handling assessment chart (MAC), National Institute for Occupational Safety and Health equations, and others. There are advantages and disadvantages to using any of the methods above.[ 17 ]

One method of assessing the risk of MSDs is the MAC. This method has been developed by the ergonomic laboratory of Health and Safety Executive (HSE) organization to facilitate the inspection of companies that perform MMH operations and it is superior compared to other methods of assessing physical condition in MMH in terms of ease of use and validity (accuracy). With this method, three types of activities can be evaluated, namely individual load lifting, individual load carrying, and team handling.[ 17 ] In the study by Hashemi Habibabadi et al. ,[ 19 ] which were performed to assess MSDs in Bandar-Abbas charging berth workers using MAC method, the results showed high risk levels, namely risk levels 3 and 4 in all three activities of individual load lifting, individual load carrying, and team handling.

Ergonomic training is useful as a low-cost intervention to reduce the risk factors in WMSDs.[ 20 ] Medical evidence suggests that effective ergonomic interventions have reduced the number and severity of related injuries.[ 21 ] Ergonomic interventions include engineering controls and management controls. Engineering intervention strategies include job design and designing proper tools for the job. Management control strategies include employee training and job rotation. The training methods along with engineering strategies are one of the most important intervention approaches to reduce injuries to individuals. Training is more affordable and accessible than other types of interventions, but it is more difficult to achieve effective results compared to technical interventions.[ 21 , 22 ] In a study by Morken et al. ,[ 23 ] showed that a training program for workers to acquire the knowledge on the prevention of MSDs in the workplace would prevent health disabilities, including MSDs. Education is one of the most important factors affecting safety and health and thus health promotion, which has been widely studied by other researchers.[ 24 ] The health education approach actually starts from the ground up and advises people to change their behaviour and move in a specific direction that is beneficial to their health.[ 25 ] Health education for workers is in the field of work fatigue, proportion of work environment components with workers, ergonomic risk factors and the correct way of MMH with the aim of preventing MSDs and safe load carrying, which ultimately leads to improved health among workers. The study by Feuerstein et al. ,[ 26 ] showed that ergonomic training along with evaluation and correction of workstations significantly reduced pain and work-related symptoms in upper limbs.

In the printing factory examined in the current study, magazines were classified in large numbers and the worker carried the magazines in several batches. In this case, the worker was faced with a significant load weight and due to the low number of workers in the factory each person had to carry that load rapidly. Furthermore, due to the repetitive nature of the work, the workers of this factory were exposed to risk factors for MSDs. Accordingly, the importance of training on MSDs and the correct principles of MMH, also to increase productivity and eliminate economic losses caused by MSDs, evaluation of MMH tasks, training intervention and in fact health education based on health promotion seemed necessary.

Therefore, this study was conducted with the following objectives on the workers of a printing factory in Tehran:

• Evaluation of the prevalence of MSDs using the Nordic questionnaire
• Evaluation of MMH using MAC method
• Training intervention and health education based on health promotion
• Re-evaluation of MMH using MAC method after training intervention.

Materials and Methods

Study design and setting.

This study had quasi experimental design. The production line of the factory was visited and it was coordinated with the management of the printing factory. The various tasks of the printing production line were examined, and the workers with MMH tasks were selected. The MMH tasks were analysed and a description of each task was prepared. Then, each task classified into three categories of, individual load lifting, individual load carrying, and team handling.

The production process of the factory was as follows: In the rolling section, the rolls were opened and placed inside the machine. Then these rolls were moved by two workers and were placed inside the printing machine using a jack. In the printing section, two workers lifted the ink barrel and placed it on top of the other barrel, and the ink barrel was carried to the printing machine by a jack. In the cutting section, the worker lifted the papers from the pallet and placed them on the machine. After cutting the paper with a Hindu machine, the worker carried the paper out of the machine and placed it on a pallet. In the folding section, the worker lifted the covers of the magazine off the table and placed it on the conveyor, then lifted the sorted magazines off the machine and placed them on the pallet. In the forms arranging section, the worker carried the forms from the surface of the pallets and placed them on the conveyor. After passing the forms through the printing machine, the worker lifted the forms from the conveyor, put them on top of each other, then placed them on a table surface and strapped around them. Two people carried the forms from the table surface and put them on pallets. In the waste collection section, the worker collected the waste paper from the ground and placed them in a paper pressure chamber to be used for other purposes. In the waste disposal section, a worker picked up the wastes and transported it to a pickup truck.

Study participants and sampling

The study population consisted of 45 men, 5 of whom were excluded due to a history of MSDs. In the study by Panjali et al. ,[ 27 ] was performed on 44 workers in one of the metal casting industries with MMH tasks. In the study by Dehnavi et al. ,[ 28 ] the subject number was calculated using the following formula: N= ([2 σ 2 ][z1-α/2 + z1-β] 2 )/d 2 . According to the previous studies, the standard deviation and absolute error are 30. The reliability of this test is 95% and the test power is considered equal to 0.80. By substituting the values in the above formula, a minimum subject size of at least 17 was obtained per group. Finally, 40 men who were eligible for the study were evaluated before the intervention and re-evaluated after the training intervention. The inclusion criteria were no history of severe MSDs or accidents affecting the musculoskeletal system.

Data collection tool and technique

The demographic data got collected including age, sex, height, weight, level of education, marital status, smoking, work experience, and average working hours per day. Then, the NMQ was used by self-report method. For this questionnaire, reliability tests were performed using a test–retest method which the results showed that 0%–23% of the answers was non-identical. Furthermore, the validity of the NMQ against clinical history showed a range of 0%–20% disagreement. In this questionnaire, the body is divided into nine areas.[ 15 ] The first question for each area of the body was whether the worker had experienced any musculoskeletal discomfort in that area in the last 12 months. If the worker did not have any symptoms, he should have selected the “no symptoms” option. If he did report symptoms, an additional question was asked about the severity of the symptoms: (mild, moderate, or severe)[ 29 ] .

Manual handling assessment chart before training intervention

In order to evaluate the MMH and the working and environmental conditions, the worker was filmed during the work cycle (each task is usually <15 min, which is repeated regularly and makes the cycle). Filming was done on the days and hours when the worker had the most inappropriate posture (the day and time of which were determined after starting the study and observing the workers in all hours of the week). Then, the weight of the load carried by subjects was measured using SG100 industrial scale. The MAC evaluation chart was used to review and score manual handling tasks. The validity and reliability of this method has been approved by the HSE and has been mentioned in many existing studies.[ 27 , 30 ] Three MAC evaluation charts were used to examine the three tasks of individual load lifting, individual load carrying and team handling. Each chart contains parameters assigning a colour code per task and a numerical score that these codes and scores were extracted from the relevant tables and graphs.[ 31 ] Risk levels are categorized as follows:

G: Green-low risk level

The vulnerability of individuals should be considered in expiry cases.

A: Amber-medium risk level

Works closely examined.

R: Red-high risk level

Immediate measures are needed. This risk can put a large number of workers in danger.

P: Purple-very high risk level

Such an operation expresses a serious risk of injury and should be carefully monitored, especially when the total weight load is on a person.

Finally, to determine the total score of the MAC, the scores dedicated to each variable were summed up, and for each task a total score was obtained. The control action is based on the total MAC score:

• Level 1: If 4 ≤ MAC ≤ 0 action is not required
• Level 2: If 12 ≤ MAC ≤ 5 action is needed in the near future
• Level 3: If 20 ≤ MAC ≤ 13, the action is urgently needed
• Level 4: If 31 ≤ MAC ≤ 21 the action is immediately necessary.

Tasks with control action other than “action is not necessary” should be corrected.[ 30 ]

Training intervention

Having obtained permission from the factory management, the workers gathered in a conference room on the office site and were taught the principles of MMH by lecturing by 2 experts with a master's degree in occupational health and safety at work and presenting a training PowerPoint. Workers were trained in five sessions, each lasting 45 min. Training session was included information on ergonomic risk factors and MMH, MSDs, the importance of preventing MSDs, warm-up exercises at the beginning and during work to reduce excessive work-related stress, correcting workstation settings, the correct way of using equipment as well as the correct way of performing MMH during each task, charging fire extinguisher capsules at proper periods, considering sufficient space to carry the load, proper lighting, proper hygiene, adequate first aid facilities, proper disposal of waste and sewage, minimizing the risk of fire and electrocution, improving the safety of the building according to the latest standards.[ 5 , 32 ] Furthermore, posters in the form of messages and images related to MMH were installed at the workstations. Finally, based on the results of the MAC evaluation and according to the type of control action, tasks were prioritized and suggestions were made to improve the tasks, work environment, and reduce the level of risk, including:

• Train the worker to put the arm and forearm vertically when lifting the load, lifting the load above the knee height or under the height of the elbow while body is straight. Load symmetrically and hold the load and hands in front of the body. The lower back should be without rotation or bending, or the bending and rotation should be low
• Cut the number of journals and formats half that each time they carry, which will reduce the weight of the load
• Increase co-operation while team handling the load, carrying it in coordination and at the same time
• Lay the pallets closer to the outlet of the machine to reduce the carrying distance of the load
• Keep the ground surface permanently dry and clean and keep it in good condition, and the waste papers should be collected quickly from the floor of the factory to prevent them from getting stuck in worker's hands and feet during loading.

Manual handling assessment chart evaluation after training intervention

Eventually, 3 months later,[ 28 ] the tasks were re-evaluated and scored by MAC method to evaluate the effect of training intervention and ensure safe MMH by workers.

Ethical consideration

In order to observe the research ethics, all participants were informed of the working method and objectives of the study, and the information was kept confidential and written consent was obtained from the individuals. The present study was conducted with the full approval of the ethics committee of the Shahid Beheshti University of Medical Science (Approval ID: IR. SBMU. PHNS. REC.1396.28)

Statistical analysis

Statistical analysis of the obtained data was performed using the SPSS software (SPSS V.22 Inc., Chicago, IL, USA). Kolmogorov–Smirnov test was used to check the normal distribution of the data. Descriptive statistical indices, including mean, standard deviation, and frequency, were used in accordance with quantitative and qualitative data. Mann–Whitney U nonparametric test was used to investigate the relationship between demographic variables and MSDs. Furthermore, a significant difference in MAC score before and after the training intervention was determined using the nonparametric Wilcoxon signed-rank test. Significance level in the tests was considered 0.05.

The study population was 40 male participants ranging in age from 26 to 45 years. The mean and standard deviation of age is 36.4 ± 5.7. The minimum work experience among the workers was 5 years and the maximum was 13 years, the mean and standard deviation of work experience was 8.45 ± 2.49 years. The height of the workers was in the range of 170–188 cm with the average height and standard deviation of 179.1 ± 4.5 cm. The weight range was 71–89 kg with the mean and standard deviation of 79 ± 4.5 kg. Workers’ body mass index (BMI) was in the range of 22.6–26.4 kg/m 2 , BMI mean and standard deviation was 24.6 ± 0.8 kg. Furthermore, 27 (67.5%) of subjects were in the healthy weight range and 13 (32.5%) were in the overweight range (obesity limit).

The level of education of all participants was below high-school diploma. Thirty-one participants (75.5%) were married with 9 single (22.5%) participants. Furthermore, 13 participants (32.5%) were smokers and 27 participants (67.5%) were non-smokers. The distribution of tasks with MMH among workers is as follows: 26 participants (65%) had the task of arranging the forms, 4 participants (10%) had the task of rolling, 2 participants (5%) had the task of cutting, 2 participants (5%) had the task of waste disposing, 2 participants (5%) had the task of printing, 2 participants (5%) had the task of folding, and 2 participants (5%) had the task of waste collecting.

Findings from the Nordic questionnaire showed that 90% of workers had WMSDs. The highest prevalence of 72.5% was related to the lower back and prevalence in other areas were 62.5% (shoulders), 55% (knees), 52.5% (elbows), 35% (neck), 17.5% (wrists/hands), 15% (upper back), 10% (ankles/feet), and 5% (hips/thighs), respectively [ Figure 1 ].

The prevalence of musculoskeletal disorders and their percentage among print workers

Based on the Kolmogorov–Smirnov test, the data were not normally distributed. According to nonparametric Mann–Whitney U test, it was found that there was no significant difference between demographic variables including Work experience, height, weight, BMI, age, type of task, smoking, and marital status with MSDs ( P > 0.05) [ Table 1 ]. The evaluation of four MMH tasks with the highest MAC score is shown in Tables ​ Tables2 2 and ​ and3 3 .

Results of studying a significant difference of demographic variables between two groups

*Difference between two groups

Results of MAC method for individual load lifting situation in tasks 1 & 2

Results of MAC method for individual load carrying and team handling situation in tasks 3 & 4

Task 1 was cutting, whose job description was that the worker lifted the papers from the pallet and placed them on the work surface of the machine. Then, the papers were cut by the machine. For this task, the individual load lifting worksheet of MAC evaluation chart was used. The MAC score was 22 (5R3A) before the training intervention and decreased to 12 (2G4A2R) after the training intervention [ Table 2 ].

Task 2 was arranging the forms, whose job description was that the worker lifted the forms from the pallet surface and placed them on the conveyor. For this task, the individual load lifting worksheet of MAC evaluation chart was used. The MAC score was 15 (4R3A1G) before the training intervention and decreased to 6 (4G1R3A) after the training intervention [ Table 2 ].

Task 3 was cutting, whose job description was that the worker picked up the papers that have been cut from the output of the machine and after handling the load for a while, placed them on the pallet. For this task, the individual load carrying worksheet of MAC evaluation chart was used. The MAC score was 15 (1R7A1G) before the training intervention and decreased to 9 (3G6A) after the training intervention [ Table 3 ].

Task 4 was also arranging the forms, whose job description was that the worker lifted the categorized magazines from the conveyor and put them on top of each other, then placed them on a table surface and strapped around them. Two people carried the forms from the table surface and put them on pallets. For this task, the team handling worksheet of MAC evaluation chart was used. The MAC score was 14 (2R4A3G) before the training intervention and decreased to 4 (2A1R) after the training intervention [ Table 3 ].

The results of the MAC evaluation before the training intervention showed that 65% (26 cases) of the tasks are at risk level 3, which is “urgently needed.” 15% (6 cases) of tasks are at risk level 4 which is “immediately necessary.” 15% (6 cases) of tasks are at risk level 2 which is “needed in the near future” and 5% (2 cases) of tasks are at risk level 1 which is “not required.”

After the training intervention, 60% (24 cases) of the tasks were at risk level 2 which is “needed in the near future” and 40% (16 cases) of the tasks were at risk level 1 which is “not required”. Furthermore, according to the analysis of Wilcoxon signed-rank test, there was a significant difference between MAC score before and after the training intervention ( P = 0.0001). In order to reduce the risks of MSDs associated to the four MMH tasks with highest MAC score, the following technical measures were proposed:

• Using mechanical lifting equipment to transfer stacks of magazines and forms from the conveyor to the pallet and vice versa, which in the type of glossy paper has more than 70 kg
• Using a trolley that has a higher surface than the pallet; in this way, the distance between the load to the body and the height of the load lifting position decreases
• Improving the layouts of workstations, by slightly moving the workbench and the machine, so that the person does not take limited posture due to the limited space
• Installing additional lamps and opening windows to use natural light for improving brightness in the workstations; opening doors to use the outside air flow to make the indoor temperature and ventilation suitable.

The mean of the participants’ age showed that the participants were young to middle-aged. The mean of the participants’ body mass also confirms the fact that the subjects were neither obese nor very thin. The small standard deviation of the variables indicates that the participants are close to each other in terms of the desired variables and the exact matching of the participants is observed to some extent. The points above indicate that the participants selected for the study were within the defined framework of the study.

The findings of the study showed that the prevalence of MSDs in 3 areas of the lower back (72.5%), shoulders (62.5%), and knees (55%) was higher than other parts of the body. The main causes of these disorders can be as carrying large and heavy batches of paper and magazines, improper load lifting and unsuitable environmental and work conditions, which puts a lot of pressure on the mentioned areas. Khandan et al. ,[ 16 ] concluded that the highest prevalence of MSDs among printing industry workers is in the lower back, shoulders, and ankles. The results of this study are consistent with the present study. One of the main reasons for the increase in MAC score was the weight of the load, which can cause damages to the lower back and other parts of the body. The high percentage (90%) of the prevalence of MSDs among the subjects and the allocation of the highest percentage of prevalence to the lower back (72.5%) indicated the need to evaluate the manual handling tasks and proper training of MMH to workers. After the training intervention, the weight of the load was reduced and the posture of the workers during the load handling as well as the working environment conditions improved. Hashemi Habibabadi et al. [ 19 ] also considered excess load weight as an important risk factor and one of the reasons for the increase in MAC score.

The results showed that there was no significant relationship between demographic variables such as work experience, age, height, weight, BMI, type of task, smoking, and marital status with MSDs. The study of Hashemi Habibabadi et al. [ 19 ] is consistent with this finding.

The MAC risk level for task 1 (cutting/individual load lifting) was level 4, which was reduced to risk level 2 after the training intervention. In this task, the heavy weight of the load, the large distance between the load and the body, the height of the load lifting place, the improper position of the lower back increased the MAC score and created an unsuitable condition for lifting the load. After the training intervention, the score of the mentioned parameters decreased and therefore task 1 changed to a safe and appropriate task [ Table 2 ].

The MAC risk level for task 2 (arranging the forms/individual load lifting) was level 3, which was reduced to risk level 2 after the training intervention. The reason for improving the load lifting situation was that, after the training intervention, the worker raised the height of the pallet surface, so the score of “the height of the load lifting place” decreased. The worker corrected his posture and moved the load close to the body without rotating or bending the lower back to the sides. Furthermore, the temperature of the factory was adjusted as the ventilation condition improved. Therefore, task 3 was changed to a safe and appropriate task [ Table 2 ].

The MAC risk level for task 3 (cutting/individual load carrying) was level 3, which was reduced to risk level 2 after the training intervention. The reason for the improvement in the load carrying situation was that, after the training intervention, the amount of papers the worker carried was cut to half, thus the weight of the load was reduced, a number of lamps were installed in the factory and the factory temperature was adjusted by improving the ventilation condition. In results the “other environmental factors” parameter score was reduced, and by moving the pallets closer to the machine output, the distance at which the load was carried was reduced to a minimum, so task 2 was changed to a safe and convenient task [ Table 3 ].

The MAC risk level for task 4 (arranging the forms/team handling) was level 3, which was reduced to risk level 1 after the training intervention. The reason for improving the load lifting situation was that, after the training intervention, the weight of the load was reduced. The workers corrected their posture and lifted the load close to the body, the cooperation between people while lifting the load increased and the body's limits of movement while lifting the load was deleted. Therefore, task 4 was changed to a safe and appropriate task [ Table 3 ]. In the study by Dormohammadi et al. ,[ 30 ] the risk level for the task of team handling was in level 3 in moulding unit, which is consistent with MAC action level before intervention for tasks 2, 3, and 4 in the current study.

The results of MAC evaluation before and after the training intervention showed that the risk level of all tasks was reduced to levels 1 and 2 (acceptable risk level), which this reduction was significant ( P = 0.0001) according to the analysis of Wilcoxon signed-rank test between MAC Score, before and after the intervention. Both results confirm the effect of the training intervention on the correct load handling and reduction of the MAC score.

Dehnavi et al. [ 28 ] results are consistent with the current study stating that the positive effect of training-engineering interventions can reduce the severity of pain in the different parts of the body and reduce the risk factors for cumulative injuries in the workplace of printing industry workers. In a review study, Faisting and de Oliveira Sato[ 33 ] stated that ergonomic training alone or in combination with other types of interventions is effective in reducing WMSDs. In addition, other studies[ 20 ] are consistent with the present study. Proportion between workers and work environment components was one of the important factors that were considered during the training intervention and health education. In the long run, disproportion causes fatigue among workers. In addition, high workload, shift work, stress, and lack of workforce can be the causes of work fatigue. Due to the role of fatigue in reducing the quality of work and human error and the subsequent occurrence of MSDs, effective training in this field can eventually improve the health of workers.[ 5 , 24 ]

Limitations and recommendations

The current paper had limitations, including time and space constraints in accurate filming of the worker's physical condition due to high work load, small workstation, and lack of sufficient space, with the possibility of damages to experts in such a small space. Therefore, to conduct similar research in future, it is suggested that factories with a large number of workers (larger sample size) and a larger work environment be selected to remove the restrictions and ensure safety in the workplace. The results of the study can also be used to properly design the workstations.

Assessing the prevalence of MSDs using the Nordic questionnaire provided an overview of the state of the industry before assessing MMH. The high prevalence of MSDs in the lower back indicated the presence of pressure on this area due to excessive load weight and improper load handling. Assessing MMH using MAC method also identified the risk factors for MSDs. Therefore, it provided proper planning for the implementation of the training program. Eventually, this training intervention improved the workers posture during MMH and the effectiveness of which was determined by MAC evaluation after the intervention. Implementing health education is important in the sense that people can improve their health by changing their practical and work style. Moreover, the goal is for the specialist to develop the knowledge and skills for individuals to make an informed choice about their health that ultimately leads to improved health.[ 25 ]

Financial support and sponsorship

This article is a part of the research project, which was supported by Shahid Beheshti University of Medical Sciences (Grant Number 11551).

Conflicts of interest

There are no conflicts of interest.

Acknowledgment

The authors would like to thank subjects for their generous participation and sharing to make this project possible.