smoking during pregnancy research

Tobacco, Nicotine, and E-Cigarettes Research Report What are the risks of smoking during pregnancy?

Smoking during pregnancy is linked with a range of poor birth outcomes—including:

• Low birth weight and preterm birth 58,59
• Restricted head growth 60
• Placental problems 61
• Increased risk of still birth 62
• Increased risk of miscarriage 62,63

Health and developmental consequences among children have also been linked to prenatal smoke exposure, including:

• Poorer lung function, persistent wheezing, and asthma, possibly through DNA methylation 64
• Visual difficulties, such as strabismus, refractive errors, and retinopathy 65

Unfortunately, smoking by pregnant women is common. In 2014, 8.4 percent of women smoked at any time during pregnancy, with those aged 20 to 24 who were American Indian or Alaska Natives having higher rates, at 13 percent and 18 percent, respectively. 66 One fifth of women who smoked during the first 6 months of pregnancy quit by their third trimester. Overall cessation rates were highest for those with the highest educational attainment and private insurance. 66   Therefore, there is a clear need to expand smoking cessation treatment to younger women and to those of lower socioeconomic status (see Box: " Smoking Cessation for Pregnant Women ").

• Open access
• Published: 21 December 2022

Cigarette smoking during pregnancy and adverse perinatal outcomes: a cross-sectional study over 10 years

• Baptiste Tarasi 1 ,
• Jacques Cornuz 2 ,
• Carole Clair 3 &
• David Baud 1  

BMC Public Health volume  22 , Article number:  2403 ( 2022 ) Cite this article

9718 Accesses

11 Citations

2 Altmetric

Metrics details

It has been shown that active exposure to tobacco is associated with adverse pregnancy outcomes including, but not limited to, intrauterine fetal death, reduced fetal weight, and higher risk of preterm birth. We want to investigate these effects in a high-income country.

This cross-sectional study examined 20,843 pregnant women who delivered over 10 years at the Maternity Hospital of the Centre Hospitalier Universitaire Vaudois (CHUV) in Lausanne, Switzerland. The objective was to evaluate a dose–response relationship between daily cigarette use during pregnancy and possible adverse perinatal outcomes. The social and clinical characteristics as well as obstetric and neonatal outcomes were compared between the smoking and the non-smoking groups. Adjusted odds ratios (aOR) and trend analyses (p trend ) were calculated.

Nineteen thousand five hundred fifty-four pregnant women met the inclusion criteria and 2,714 (13.9%) of them were smokers. Even after adjusting for confounding factors, smoking during pregnancy was associated with preterm birth, birthweight < 2500 g, intrauterine growth restriction, neonatal respiratory and gastrointestinal diseases, transfer to the neonatal intensive care unit, and neonatal intensive care unit admissions > 7 days. Intrauterine death and neonatal infection were associated with heavy smoking (≥ 20 cigarettes/day). Smoking appeared to be a protective factor for pre-eclampsia and umbilical cord arterial pH below 7.1. A significant trend (p trend  < 0.05) was identified for preterm birth, intrauterine growth restriction, birthweight < 2500 g, umbilical cord arterial pH below 7.1, transfers to our neonatal intensive care unit, and neonatal intensive care unit admissions more than 7 days.

Cigarette smoking is associated with several adverse perinatal outcomes of pregnancy with a dose-dependent effect.

Peer Review reports

Among adults, the consequences of cigarette use are well known and can lead to cardiovascular, pulmonary, and oncological diseases as well as other chronic illnesses [ 1 ]. These negative health consequences are remote in time and therefore do not always cause sufficient immediate concern to motivate smoking cessation, especially in younger individuals [ 2 ]. The number of smokers worldwide in 2019 was estimated to be 1.14 billion, corresponding to 7.69 million deaths and 200 million DALYs (Disability Adjusted Life Years). Globally, the proportion of smokers is much lower among women with 6.62% of female individuals identified as smokers compared to 32.7% of male individuals. However, this proportion is considerably higher among women in high-income countries with 17.6% of women compared to 26.9% of men identifying as smokers [ 3 ].

There is evidence that women are more likely to discontinue cigarette use during their pregnancy [ 4 ]. The global prevalence of smoking during pregnancy is estimated to be 1.7% [ 5 ]. This proportion, also evaluated in 2018, is significantly higher in high-income countries, reaching 7.2% in the USA [ 6 ] and 8.1% in Europe [ 5 ]. These numbers should be interpreted cautiously as up to 25% of pregnant women with cigarette use prior to pregnancy incorrectly indicated that they ceased smoking during pregnancy [ 7 ]. Pregnant women with a lower level of education and those who experience an unplanned pregnancy have a higher prevalence of smoking and a lower probability of quitting [ 8 , 9 ].

The effects of smoking during pregnancy have been the subject of numerous studies and have been associated with many adverse perinatal outcomes. Specifically active exposure to tobacco has been shown to be associated with a dose–response relationship to adverse outcomes such as preterm birth (birth before 37 weeks of pregnancy) [ 10 , 11 , 12 ], reduced birth weight [ 13 , 14 ], with the reduction in fetal measurements occurring after the first trimester [ 15 ], and transfer to a neonatal intensive care unit [ 16 ]. Smoking has also been associated in a dose-dependent manner with an increased risk of intrauterine fetal death [ 17 , 18 , 19 , 20 ]. In contrast to adverse outcomes cited, smoking has been identified to be a protective factor against pre-eclampsia [ 21 , 22 ]. Regarding the neonatal impact, smoking during pregnancy can alter fetal lung development and lead to respiratory problems [ 23 , 24 ]. Long term, fetal exposure to smoking during pregnancy can result in more frequent development of gastrointestinal pathologies [ 25 ].

In summary, many studies have already investigated adverse obstetric and neonatal outcomes [ 26 , 27 ]. However, not all of them included a large sample from a single center or adjusted their results to account for potential confounding factors. In addition, many studies have focused only on a single adverse outcome. For example, Soneji et al. focused their study on prematurity [ 12 ], and Larsen et al. focused mainly on birth weight [ 13 ]. If we take the main studies found in the literature that focused on several outcomes, Ratnasiri et al. did not focus on neonatal outcomes and did not evaluate a potential dose–response [ 28 ]. Finally, the well conducted research of Li et al. did not focus on several key outcomes including the risk of pre-eclampsia or neonatal infections, pulmonary pathologies, or gastrointestinal pathologies and did not evaluate a potential dose–response as well [ 29 ].

For all these reasons, we firstly aimed to assess multiple obstetric and neonatal outcomes associated with cigarette smoking during pregnancy within a single and large Swiss obstetric cohort with prospectively collected data. Some have already been studied, others not. Secondly, we want to evaluate a potential dose–response relationship between the quantity of cigarette use and adverse outcomes.

This cross-sectional study utilized our obstetrical database at the Maternity Hospital of the Centre Hospitalier Universitaire Vaudois (CHUV) in Lausanne, Switzerland, where 20,843 pregnant women gave birth between 1997 and 2006. Data available in this database include demographic, labor, and delivery information, as well as maternal and neonatal outcomes.

All information regarding patient health and pregnancy was collected at the time of admission to the hospital, with the majority occurring at the time of admission for delivery or, for some, at the time of admission to the antepartum unit in the case of complicated pregnancies. A medical history was taken for each patient presenting to the hospital by the obstetrical care provider. If urgent care was required, the history was postponed to an appropriate time during the hospitalization. Our computer system did not permit closure of a patient file that did not include all the mandatory information, including smoking habits. This information was collected verbally with the following question: "Do you smoke cigarettes daily?" with a dichotomous “yes/no” answer. If the answer was “yes”, the number corresponding to the current consumption was then requested by the computer system. The number of cigarettes consumed thus represents usage in the late third trimester, and does not take into account variation of smoking during pregnancy.

Regarding neonatal data, all information was added to our database at the end of the stay by the neonatologists and/or the obstetricians. All women whose records contained all the data needed for our study were included regardless of mode of delivery. The exclusion criteria were as follows: women under 18 years of age or women with multiple pregnancies. The quality of this database of prospectively collected data has already been described elsewhere (cross-check congruent data in 98.2–99.8% of cases) [ 30 ].

The following social and clinical characteristics were extracted from the database: daily cigarette use, maternal age, country of birth, marital status, parity, previous pregnancy loss, education, professional status, health insurance, and the presence of significant psychosocial difficulties. The latter was defined as pregnant women referred for a dedicated indication for consultation associated with challenging psychosocial circumstances (psychiatric pathologies, alcohol or drug abuse, etc.…). We assessed the following obstetric and neonatal outcomes: delivery mode, pre-eclampsia, intrauterine death, neonatal death, preterm birth, intrauterine growth restriction, birthweight, umbilical cord arterial pH, APGAR score at 5 min, neonatal infection, hypoglycemia, cerebral hemorrhage or convulsion, jaundice, neonatal anemia, respiratory diseases (including pulmonary infection, pneumothorax, apnea, and hyaline membrane disease), gastrointestinal diseases (including feeding difficulties, occlusive syndrome, digestive hemorrhage, necrotizing enterocolitis, diarrhea, and vomiting), transfers to our neonatal intensive care unit, and neonatal intensive care unit admissions longer than 7 days.

The social and clinical characteristics, as well as the obstetric and neonatal outcomes, were compared between the smoking and non-smoking pregnant women. For the same comparisons, the group of smoking pregnant women was also divided into 3 subgroups according to their daily cigarette usage (< 10/day, ≥ 10/day, and ≥ 20/day). The p-value for each clinical and social characteristic, comparing smokers and non-smokers, was calculated using a Chi-squared test. Logistic regression models to assess the association between smoking and obstetric and neonatal outcomes were built and odds ratios were calculated (aOR), adjusted for maternal age, country of birth, marital status, parity, previous pregnancy loss, education, professional status, psychosocial difficulties and insurance. For some outcomes, such as birth weight, intrauterine growth restriction, umbilical cord arterial pH, APGAR score at 5 min, respiratory diseases, gastrointestinal diseases, neonatal infection, hypoglycemia, cerebral hemorrhage or convulsion, jaundice, neonatal anemia, and transfers to or stay in our neonatal intensive care unit, the odds ratios were also adjusted for the gestational age as these outcomes can occur more frequently in preterm neonates. For the calculation of adjusted estimators in multivariate logistic regression models, the baseline variables that significantly differed between both the groups (confounders) or those that are known risk factors for adverse outcomes were included in the models.

Finally, trend analyses (p trend ) were also calculated, using the Cochran-Armittage test, for all the outcomes examined to evaluate a potential dose–response relationship according to the number of daily cigarettes consumed.

Statistical analyses were performed using STATA 16 (Stata Corporation, College Station, USA).

The study was carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki). This study was approved by the local IRB (Ethical Commission of the Canton of Vaud, Switzerland, protocol no. 101/08).

Over a period of 10 years, 19.554 pregnant women met the inclusion criteria. Among them, 16,840 (86.1%) identified as non-smokers and 2,714 (13.9%) identified as smokers (Fig.  1 ).

Classification of pregnant women according to the number of cigarettes consumed per day

The prevalence of pregnant women who reported cigarette use was higher among pregnant women of Swiss origin, single, divorced, or widowed, those who have had a previous spontaneous abortion, those with significant psychosocial difficulties, and nulliparous pregnant women (Table 1 ).

After adjustment for confounding factors, smoking during pregnancy was associated with preterm birth (aOR 1.16 [95%CI 1.03–1.31]), birthweight < 2500 g (aOR 1.78 [95%CI 1.53–2.08]), small for gestational age (aOR 1.83 [95%CI 1.64–2.05]), respiratory diseases (aOR 1.32 [95%CI 1.13–1.56]), gastrointestinal diseases (aOR 1.63 [95%CI 1.11–2.42]), transfers to the neonatal intensive care unit (aOR 1.44 [95%CI 1.26–1.63]), and neonatal intensive care unit admission > 7 days (aOR 1.64 [95%CI 1.42–1.90]). These associations were stronger in the groups of women with higher number of cigarettes consumed per day. Intrauterine death (aOR 1.98 [95%CI 1.01–3.89]) and neonatal infection (aOR 1.53 [95%CI 1.05–2.22]) were only associated with heavy smoking (≥ 20 cigarettes/day) but not with lower smoking exposure. In contrast, smoking appeared to be a protective factor for pre-eclampsia (aOR 0.62 [95%CI 0.44–0.88]) and umbilical cord arterial pH below 7.1 (aOR 0.65 [95%CI 0.50–0.86]). Rate of cesarean section, neonatal deaths and other neonatal outcomes such as an APGAR score below 7 at 5 min, hypoglycemia, cerebral hemorrhage or convulsion, jaundice, and neonatal anemia showed no significant differences between the smoking and the non-smoking groups (Table 2 ).

A significant dose–response relationship trend was identified between the number of daily cigarettes consumed and preterm birth (p trend  < 0.001), intrauterine growth restriction (p trend  < 0.001), birthweight < 2500 g (p trend  < 0.001), umbilical cord arterial pH below 7.1 (p trend  = 0.001), transfers to our neonatal intensive care unit (p trend  < 0.001), and neonatal intensive care unit admissions more than 7 days (p trend  < 0.001).

No trend was found for the other outcomes investigated: pre-eclampsia, increased rate of cesarean section, neonatal death, intrauterine death, APGAR score < 7 at 5 min, hypoglycemia, jaundice, neonatal anemia, neonatal infection, cerebral hemorrhage or convulsion, respiratory diseases, and gastrointestinal diseases.

As our database includes a sample of pregnant women from the 1997 to 2006, this likely explains why the rate of pregnant individuals who identify as smokers, 13.9%, is higher than the rate described in statistics from 2018, which are estimated to be 8.1% in Europe [ 5 ] and 7.2% in the USA [ 6 ].

Cigarette smoking has an impact on pregnancy with several adverse perinatal outcomes. In our study, cigarette use was strongly associated with preterm birth, lower birthweight, intrauterine growth restriction, transfers to the neonatal intensive care unit, and neonatal intensive care unit admissions > 7 days. All of the above associations have a dose–response relationship, with significant trend values. Our results align with those found in the literature [ 10 , 11 , 12 , 13 , 14 , 16 ]. Intrauterine death was associated with heavy cigarette consumption (≥ 20/day), while other studies attributed intrauterine death with lower tobacco consumption [ 17 , 18 , 19 ]. Finally, smoking during pregnancy can induce neonatal pulmonary and gastrointestinal pathologies. Heavy cigarette consumption (≥ 20/day) also increases the risk of neonatal infections.

The mechanisms by which tobacco smoking result in adverse perinatal outcomes are complex. They may occur as a result of disruption of fundamental processes such as proliferation, apoptosis, and invasion of the trophoblasts during placental development. Alteration of the vascularization and the metabolism of the placenta may also be a cause [ 31 ].

The association between neonatal gastrointestinal pathology and smoking during pregnancy, as well as the association with neonatal infections, has been little studied until now. As a comparison, it has been shown that adult smokers are themselves more susceptible to bacterial or viral infections than non-smokers which may be due to alteration of the structural, functional, and immunological functions of the host defenses [ 32 , 33 ].

Smoking during pregnancy may, however, also still be a protective factor. Cigarette use during pregnancy has been shown to reduce the risk of pre-eclampsia [ 21 , 22 ] as was also identified in our study. The protective role of smoking can be partially explained by the effects of carbon monoxide, one of the products of tobacco combustion. Carbon monoxide inhibits the placental production of anti-angiogenic proteins such as sFlt1 or sEng, which play a role in the pathogenesis of preeclampsia. However, the pathogenesis of pre-eclampsia remains complex and is still not fully understood [ 34 ]. It may be worth mentioning that Luque-Fernandez et al. have partially explained the paradoxical phenomenon of this protective effect by studying prevalent cases at birth rather than all incident cases in a pregnancy cohort, which results in selection bias [ 35 ]. In our study, tobacco smoking was also a protective factor against the risk of umbilical cord arterial pH below 7.1. This phenomenon has been little studied. However, we will qualify our results by comparing them with those of Zaigham et al. whose prospective-observational cohort study of 308 patients showed no significant differences in pH values between smokers and non-smokers [ 36 ].

Our results do not suggest a significant association for some outcomes such as an APGAR score below 7 at 5 min, hypoglycemia, cerebral hemorrhage or convulsion, jaundice, and neonatal anemia.

With the proportion of pregnant smokers estimated to be 8.1% in Europe [ 5 ] and 7.2% in the USA [ 6 ] in 2018, it is clear that there is still much to be done in terms of prevention. Although low tobacco consumption is associated with less severe outcomes than heavy consumption, it is important to inform pregnant women that even at low doses, smoking has consequences for the fetus, in addition to the consequences on their own health. Effective interventions for smoking cessation during pregnancy include regular interval counseling and the provision of nicotine replacement therapy to patients who do not respond to counseling only [ 37 ]. The use of incentives to motivate smoking cessation also showed encouraging results [ 38 ].

The strength of our study is the analysis of multiple prospectively collected outcomes within a single, large cohort. It confirms the different outcomes studied separately in the literature but also demonstrated a dose–response effect, which has not been systematically evaluated [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ].

Our research also contains some weaknesses. First, we did not assess a possible change in smoking during pregnancy and we also did not include the occasional smokers. This constitutes an information bias. By using a large available database, which was not designed specifically for this research, we were also unable to utilize a standardized questionnaire to assess cigarette consumption. Second, we did not assess passive smoking or secondhand exposure, which may also affect the fetus [ 39 ]. Furthermore, we did not take into account certain factors that could be confounding, such as alcohol or cannabis use [ 40 , 41 ]. Information regarding other factors, such as comorbidities or concomitant medication use were not available and therefore were also not taken into account.

In addition, it is important to mention that some odds ratio confidence intervals are wide, especially for the subgroup of “ ≥ 20 cig/day”. This may be explained by the fact that this subgroup only includes 499 patients out of 19,554 patients. We thus acknowledge that some of the comparisons are underpowered, and therefore the lack of statistically significant relationships for some of the comparisons may not necessarily indicate that there is no relationship. Since the associations found in our study might be underestimated due to patients underreporting their consumption, this “ > 20 cig/day” group might represent the true impact of smoking during pregnancy. Indeed, about 24% of pregnant smokers stop smoking during pregnancy and up to 25% of pregnant smokers also misreport their actual tobacco consumption. This represents a possible classification bias.

We can also mention the lack of generalizability due to a localized sample. Finally, during the time period of our study (1997–2006), obstetrical management may have altered. This potential change was not taken into account as a covariate. Also, the rate of smoking in pregnancy has been declining [ 5 ]. Within the Swiss population, the latest existing data to our knowledge includes the years 2011–2016. The proportion of pregnant smokers during this time was estimated to be 6.8%, showing a decrease in consumption since the data collected for our research [ 42 ]. Although the estimate of association may hold, many characteristics of women in the study may not hold.

Cigarette smoking during pregnancy is associated with several adverse perinatal outcomes. This relationship is often dose-dependent, as with preterm birth, birthweight < 2500 g, intrauterine growth restriction, transfers to neonatal intensive care unit, and neonatal intensive care unit admissions more than 7 days. Prevention among women must be further emphasized, as some adverse outcomes could be avoided by a smoke-free pregnancy.

Availability of data and materials

The datasets analysed during the current study are available from the corresponding author on reasonable request.

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2014. (Reports of the Surgeon General). Available from: http://www.ncbi.nlm.nih.gov/books/NBK179276/ . [Cited 22 Dec 2021].

West R. Tobacco smoking: Health impact, prevalence, correlates and interventions. Psychol Health. 2017;32(8):1018–36.

Article   Google Scholar  

Reitsma MB, Flor LS, Mullany EC, Gupta V, Hay SI, Gakidou E. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and initiation among young people in 204 countries and territories, 1990–2019. Lancet Public Health. 2021;6(7):e472–81.

Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Menacker F, Munson ML. Births: final data for 2003. Natl Vital Stat Rep Cent Dis Control Prev Natl Cent Health Stat Natl Vital Stat Syst. 2005;54(2):1–116.

Google Scholar  

Lange S, Probst C, Rehm J, Popova S. National, regional, and global prevalence of smoking during pregnancy in the general population: a systematic review and meta-analysis. Lancet Glob Health. 2018;6(7):e769–76.

Drake P, Driscoll AK, Mathews TJ. Cigarette smoking during pregnancy: United States, 2016. NCHS Data Brief. 2018;305:1–8.

George L, Granath F, Johansson ALV, Cnattingius S. Self-reported nicotine exposure and plasma levels of cotinine in early and late pregnancy. Acta Obstet Gynecol Scand. 2006;85(11):1331–7.

Article   CAS   Google Scholar  

Madureira J, Camelo A, Silva AI, Reis AT, Esteves F, Ribeiro AI, et al. The importance of socioeconomic position in smoking, cessation and environmental tobacco smoke exposure during pregnancy. Sci Rep. 2020;10(1):15584.

Flower A, Shawe J, Stephenson J, Doyle P. Pregnancy planning, smoking behaviour during pregnancy, and neonatal outcome: UK millennium cohort study. BMC Pregnancy Childbirth. 2013;13:238.

Diguisto C, Dochez V. Consequences of active cigarette smoking in pregnancy - CNGOF-SFT expert report and Guidelines on the management of smoking during pregnancy. Gynecol Obstet Fertil Senol. 2020;48(7–8):559–66.

CAS   Google Scholar  

Moore E, Blatt K, Chen A, Van Hook J, DeFranco EA. Relationship of trimester-specific smoking patterns and risk of preterm birth. Am J Obstet Gynecol. 2016;215(1):109.e1-6.

Soneji S, Beltrán-Sánchez H. Association of maternal cigarette smoking and smoking cessation with preterm Birth. JAMA Netw Open. 2019;2(4): e192514.

Larsen S, Haavaldsen C, Bjelland EK, Dypvik J, Jukic AM, Eskild A. Placental weight and birthweight: the relations with number of daily cigarettes and smoking cessation in pregnancy. A population study. Int J Epidemiol. 2018;47(4):1141–50.

Kataoka MC, Carvalheira APP, Ferrari AP, Malta MB, de Barros Leite Carvalhaes MA, de Lima Parada CMG. Smoking during pregnancy and harm reduction in birth weight: a cross-sectional study. BMC Pregnancy Childbirth. 2018;18(1):67.

Abraham M, Alramadhan S, Iniguez C, Duijts L, Jaddoe VWV, Den Dekker HT, et al. A systematic review of maternal smoking during pregnancy and fetal measurements with meta-analysis. PLoS ONE. 2017;12(2): e0170946.

Kondracki AJ. Low birthweight in term singletons mediates the association between maternal smoking intensity exposure status and immediate neonatal intensive care unit admission: the E-value assessment. BMC Pregnancy Childbirth. 2020;20(1):341.

Anderson TM, Lavista Ferres JM, Ren SY, Moon RY, Goldstein RD, Ramirez JM, et al. Maternal smoking before and during pregnancy and the risk of sudden unexpected infant death. Pediatrics. 2019;143(4): e20183325.

Pineles BL, Hsu S, Park E, Samet JM. Systematic review and meta-analyses of perinatal death and maternal exposure to tobacco smoke during pregnancy. Am J Epidemiol. 2016;184(2):87–97.

Marufu TC, Ahankari A, Coleman T, Lewis S. Maternal smoking and the risk of still birth: systematic review and meta-analysis. BMC Public Health. 2015;15:239.

Flenady V, Koopmans L, Middleton P, Frøen JF, Smith GC, Gibbons K, et al. Major risk factors for stillbirth in high-income countries: a systematic review and meta-analysis. Lancet Lond Engl. 2011;377(9774):1331–40.

England L, Zhang J. Smoking and risk of preeclampsia: a systematic review. Front Biosci J Virtual Libr. 2007;12:2471–83.

Lisonkova S, Joseph KS. Incidence of preeclampsia: risk factors and outcomes associated with early- versus late-onset disease. Am J Obstet Gynecol. 2013;209(6):544.e1-544.e12.

McEvoy CT, Spindel ER. Pulmonary effects of maternal smoking on the fetus and child: effects on lung development, respiratory morbidities, and life long lung health. Paediatr Respir Rev. 2017;21:27–33.

Gibbs K, Collaco JM, McGrath-Morrow SA. Impact of tobacco smoke and nicotine exposure on lung development. Chest. 2016;149(2):552–61.

Karur O, Gutvirtz G, Wainstock T, Sheiner E. Maternal prenatal smoking and long-term gastrointestinal morbidity of the offspring: a population-based cohort analysis. Reprod Toxicol Elmsford N. 2021;103:133–8.

Tran DT, Roberts CL, Havard A, Jorm LR. Linking birth records to hospital admission records enhances the identification of women who smoke during pregnancy. Aust N Z J Public Health. 2014;38(3):258–64.

Avşar TS, McLeod H, Jackson L. Health outcomes of smoking during pregnancy and the postpartum period: an umbrella review. BMC Pregnancy Childbirth. 2021;21(1):254.

Ratnasiri AWG, Gordon L, Dieckmann RA, Lee HC, Parry SS, Arief VN, et al. Smoking during pregnancy and adverse birth and maternal outcomes in California, 2007 to 2016. Am J Perinatol. 2020;37(13):1364–76.

Li R, Lodge J, Flatley C, Kumar S. The burden of adverse obstetric and perinatal outcomes from maternal smoking in an Australian cohort. Aust N Z J Obstet Gynaecol. 2019;59(3):356–61.

Baud D, Meyer S, Vial Y, Hohlfeld P, Achtari C. Pelvic floor dysfunction 6 years post-anal sphincter tear at the time of vaginal delivery. Int Urogynecology J. 2011;22(9):1127–34.

Morales-Prieto DM, Fuentes-Zacarías P, Murrieta-Coxca JM, Gutierrez-Samudio RN, Favaro RR, Fitzgerald JS, et al. Smoking for two- effects of tobacco consumption on placenta. Mol Aspects Med. 2021;87:101023.

Jiang C, Chen Q, Xie M. Smoking increases the risk of infectious diseases: a narrative review. Tob Induc Dis. 2020;18:60.

Bagaitkar J, Demuth DR, Scott DA. Tobacco use increases susceptibility to bacterial infection. Tob Induc Dis. 2008;4:12.

Karumanchi SA, Levine RJ. How does smoking reduce the risk of preeclampsia? Hypertension. 2010;55(5):1100–1.

Luque-Fernandez MA, Zoega H, Valdimarsdottir U, Williams MA. Deconstructing the smoking-preeclampsia paradox through a counterfactual framework. Eur J Epidemiol. 2016;31(6):613–23.

Zaigham M, Helfer S, Kristensen KH, Isberg PE, Wiberg N. Maternal arterial blood gas values during delivery: Effect of mode of delivery, maternal characteristics, obstetric interventions and correlation to fetal umbilical cord blood. Acta Obstet Gynecol Scand. 2020;99(12):1674–81.

Diamanti A, Papadakis S, Schoretsaniti S, Rovina N, Vivilaki V, Gratziou C, et al. Smoking cessation in pregnancy: An update for maternity care practitioners. Tob Induc Dis. 2019;17:57.

Leung LWS, Davies GA. Smoking Cessation Strategies in Pregnancy. J Obstet Gynaecol Can JOGC J Obstet Gynecol Can JOGC. 2015;37(9):791–7.

Crane JMG, Keough M, Murphy P, Burrage L, Hutchens D. Effects of environmental tobacco smoke on perinatal outcomes: a retrospective cohort study. BJOG Int J Obstet Gynaecol. 2011;118(7):865–71.

Popova S, Dozet D, O’Hanlon G, Temple V, Rehm J. Maternal alcohol use, adverse neonatal outcomes and pregnancy complications in British Columbia, Canada: a population-based study. BMC Pregnancy Childbirth. 2021;21(1):74.

Gunn JKL, Rosales CB, Center KE, Nuñez A, Gibson SJ, Christ C, et al. Prenatal exposure to cannabis and maternal and child health outcomes: a systematic review and meta-analysis. BMJ Open. 2016;6(4): e009986.

Gmel G, Notari L. Consommation d’alcool et de tabac pendant la grossesse en Suisse : évaluation de l’enquête du monitorage suisse des addictions 2011–2016. Addiction Suisse; 2018. Available from: https://www.bag.admin.ch/bag/fr/home/das-bag/publikationen/forschungsberichte/forschungsberichte-sucht/forschungsberichte-tabak.html#-497648074 . [Cited 11 Nov 2022] .

Download references

Acknowledgements

We thank all midwives and doctors who computerized obstetrical data used in this study. Their involvement was essential to allow this study.

This work was supported by the research fund in obstetrics and gynecology of the University Hospital of Lausanne, Switzerland. The funding sources had no role in the study design, data collection, data analysis or the interpretation thereof, or in writing the report.

Author information

Authors and affiliations.

Materno-Fetal and Obstetric Research Unit, Woman-Mother-Child Department, University Hospital of Lausanne, CHUV, 1011, Lausanne, Switzerland

Baptiste Tarasi & David Baud

Department of Ambulatory Care, Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1011, Lausanne, Switzerland

Jacques Cornuz

Department of Training, Research and Innovation, Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1011, Lausanne, Switzerland

Carole Clair

You can also search for this author in PubMed   Google Scholar

Contributions

BT handled the literature review as well as the writing of the manuscript. DB took care of the project development, the data collection, and the data analysis. JC also participated in the project development. Finally, CC was responsible for the manuscript's critical reviewing. The authors read and approved the final manuscript.

Corresponding author

Correspondence to David Baud .

Ethics declarations

Ethics approval and consent to participate.

The study was carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki). This study was approved by the local IRB (Ethical Commission of the Canton of Vaud, Switzerland, protocol no. 101/08). Informed consent was obtained from all subjects and/or their legal guardian.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

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

Rights and permissions

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

Reprints and permissions

About this article

Cite this article.

Tarasi, B., Cornuz, J., Clair, C. et al. Cigarette smoking during pregnancy and adverse perinatal outcomes: a cross-sectional study over 10 years. BMC Public Health 22 , 2403 (2022). https://doi.org/10.1186/s12889-022-14881-4

Download citation

Received : 20 September 2022

Accepted : 16 December 2022

Published : 21 December 2022

DOI : https://doi.org/10.1186/s12889-022-14881-4

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Smoking during pregnancy
• Perinatal outcomes
• Preterm birth
• Birthweight
• Intrauterine growth restriction

BMC Public Health

ISSN: 1471-2458

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

• Search Menu
• Supplements
• Advance articles
• Editor's Choice
• Special Issues
• Author Guidelines
• Submission Site
• Why Publish With Us?
• Open Access
• About Nicotine & Tobacco Research
• About Society for Nicotine & Tobacco Research
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Smoking in pregnancy: an ongoing challenge.

Corresponding Author: Linda Bauld, PhD, UK Centre for Tobacco and Alcohol Studies, University of Stirling, Stirling, UK. Telephone: +44-(0)7714-213-372; E-mail: [email protected]

• Article contents
• Figures & tables
• Supplementary Data

Linda Bauld, Cheryl Oncken, Smoking in Pregnancy: An Ongoing Challenge, Nicotine & Tobacco Research , Volume 19, Issue 5, 1 May 2017, Pages 495–496, https://doi.org/10.1093/ntr/ntx034

• Permissions Icon Permissions

Maternal smoking during pregnancy carries significant risks to mother infant and child. Smoking during pregnancy is associated with an increased risk of ectopic pregnancy, placental previa and abruption, preterm premature rupture of membranes, fetal growth restriction, preterm delivery, oral facial clefts, and sudden infant death syndrome. 1 , 2 One of the most measurable effects of smoking is approximately doubling the risk of delivering a low birth weight infant. 2 This special issue of the journal highlights the continued risks of smoking in pregnancy and the importance of policies and interventions to address this issue, despite the progress that has been made in reducing smoking in pregnancy in some countries. New data on risks, incidence, interventions and women’s own perspectives are highlighted. Together the included papers provide new data examining key issues in the field, from a wide range of countries.

On risks, two papers are included. Although most of the research examining the effects of smoking on birth weight has been conducted in high income countries, a meta-analysis in this review confirms the association between smoking during pregnancy and low birth weight in the Americas. 3 Additionally, although studies suggest a causal inference between maternal smoking and disruptive behavioral disorders and attention deficit disorder in children, 2 this edition provides new data on the potential risk of maternal smoking and a broad range of psychiatric morbidity in the offspring using sibling pairs that controls for genetic and familial factors. 4

Despite the health risks, the majority of women who smoke prior to pregnancy continue to smoke cigarettes during pregnancy. This special issue includes a number of papers that explore some of the determinants of maternal smoking during pregnancy. Although smoking during pregnancy rates are declining in many high income countries, indigenous women in these countries continue to have high smoking rates, as outlined in a narrative review this special edition. 5 Although women who quit smoking during pregnancy tend to be of a higher socioeconomic status, and have lower levels of nicotine dependence, articles in this edition indicate that psychological distress and depressive symptoms, 6 , 7 substance use disorders, 8 adverse childhood experiences 9 may also play a significant role in smoking during pregnancy. Analyses of data of Norwegian women also indicates that differences in educational status of smokers versus nonsmokers that exist during pregnancy are increasing over time and contributing to health disparities. 10 A study in Tasmania highlights that post-natal depression and whether the women are in a relationship may affect whether women continue to smoke when pregnant. 11 A further study included here also examined the factors that may influence whether spontaneous smoking cessation occurs in pregnant women, in this case from a sample in rural Poland. 12 They found the main predictors of early cessation were higher educational attainment amongst women and partners and not having children, while barriers were being single, living with a current smoker and having both parents who smoke. These and other barriers reflect those identified in earlier research and illustrate that individual and community factors continue to influence smoking status in pregnancy.

What can be offered to pregnant women who smoke to aid cessation? First, biochemical validation of smoking status can assist in reliably identifying smoking and providing an opportunity to offer support. 13 , 14 Behavioral strategies are effective, but unfortunately treatment is underutilized as indicated by an article examining Medicaid data in the United States. 15 Underutilization may be due to provider knowledge and confidence in assistance to pregnant smokers as suggested by two surveys of Australian providers 16 , 17 or lack of attention to smoking cessation in clinical curricula in the United Kingdom, for example. 18 Consequently, additional efforts may be needed to train our health care providers to deliver smoking cessation.

Additionally, because of the low success rates of many behavioral interventions, innovative strategies are needed to help women stop smoking. An article by Emery and colleagues highlights additional cognitive and behavioral indicators of quit attempts that may inform future treatment studies 19 and Joseph and colleagues describe how interventions to increase breastfeeding may decrease postpartum relapse to smoking. 20 An article by Acquvita and colleagues provides insight into facilitators and barriers for smoking cessation in women with substance use disorders. 8 Although the use of text messaging for smoking cessation during pregnancy is limited, a further article included here indicates that delivering treatment by this method is feasible and well-liked by pregnant smokers. 21 Another article included here suggests that emotion regulation interventions 22 may have promise for smoking treatment as evidenced by preliminary quit rates. In addition, electronic cigarettes 23 or complementary and alternative medicine 24 are being used by some pregnant smokers, indicating a need for further research in these areas.

In summary, smoking during pregnancy continues to be a world-wide public health problem. The risks of smoking during pregnancy are substantial, and the benefits to cessation are great. This special edition provides further insight into the epidemiology and treatment of smoking during pregnancy, which holds promise to inform better treatment for smoking during pregnancy.

RCP . Passive smoking and children, Royal College of Physicians, London . 2010 . http://shop.rcplondon.ac.uk/products/passive-smoking-and- children?variant=6634905477 . Accessed January 10, 2017.

USDHHS . The Health Consequences of Smoking - 50 Years of Progress: A report of the Surgeon General . Washington, DC : U.S Department of Health and Human Services . 2014 . www.cdc.gov/tobacco/data_statistics/sgr/50th-anniversary/ . Accessed January 10, 2017.

Google Scholar

Google Preview

Pereira P Mata F Figueiredo A Andrade K Pereira M . Maternal active smoking during pregnancy and low birth weight in the Americas: a systematic review and meta-analysis . Nicotine Tob Res . 2017 ; 19 ( 5 ): 497 – 505 .

Ekblad M Lehtonen L Korkeila J Gissler M . Maternal smoking during pregnancy and the risk for psychiatric morbidity in singleton sibling pairs . Nicotine Tob Res . 2017 ; 19 ( 5 ): 597 – 604 .

Gould G Patten C Glover M Kira A Jayasinghe H . Smoking in pregnancy among indigenous women in high income countries: a narrative review . Nicotine Tob Res . 2017 ; 19 ( 5 ): 506 – 517 .

Goodwin R Cheslack Postava K Nelson D et al.  . Serious psychological distress and smoking during pregnancy in the United States: 2008–2014 . Nicotine Tob Res . 2017 ; 19 ( 5 ): 605 – 614 .

Kolko R Emery R Cheng Y Levine M . Do psychiatric disorders or measures of distress moderate response to postpartum relapse prevention interventions? Nicotine Tob Res . 2017 ; 19 ( 4 ): 615 – 622 .

Acquavita S Talks A Fiser K . Facilitators and barriers to smoking while pregnant for women with substance use disorders . Nicotine Tob Res . 2017 ; 19 ( 5 ): 555 – 561 .

Pear V Petito L Abrams B . The role of maternal adverse childhood experiences and race in intergenerational high-risk smoking behaviors . Nicotine Tob Res . 2017 ; 19 ( 5 ): 572 – 577 .

Grøtvedt L Kvalvik L Grøholt EK Akerkar R Egeland G . Development of social and demographic differences in maternal smoking between 1999 and 2014 in Norway . Nicotine Tob Res . 2017 ; 19 ( 5 ): 539 – 546 .

Frandsen M Thow M Ferguson S . Profile of maternal smokers who quit during pregnancy: a population-based cohort study of tasmanian women 2011–2013 . Nicotine Tob Res . 2017 ; 19 ( 5 ): 532 – 538 .

Goniewicz M Balwicki L Smith D et al.  . Factors associated with spontaneous quitting among smoking pregnant women from rural areas in Poland . Nicotine Tob Res . 2017 ; 19 ( 5 ): 647 – 651 .

Ashford K Wiggins A Rayens E Rayens MK Assef S Fallin A . Perinatal biochemical confirmation of smoking status by trimester . Nicotine Tob Res . 2017 ; 19 ( 5 ): 631 – 635 .

Shisler S Eiden R Molnar D Schuetze P Huestis M Homish G . Smoking in pregnancy and fetal growth: the case for more intensive assessment . Nicotine Tob Res . 2017 ; 19 ( 5 ): 525 – 531 .

Scheuermann T Richter K Jacobson L Shireman T . Medicaid coverage of smoking cessation counseling and medication is underutilized for pregnant and postpartum women . Nicotine Tob Res . 2017 ; 19 ( 5 ): 656 – 659 .

Tzelepis F Daly J Dowe S Bourke A Gillham K Freund M . Supporting Aboriginal women to quit smoking: antenatal and postnatal care providers’ confidence, attitudes and practices . Nicotine Tob Res . 2017 ; 19 ( 5 ): 642 – 646 .

Bar Zeev Yael Bonevski B Twyman L et al.  . Opportunities missed: a cross-sectional survey of the provision of smoking cessation care to pregnant women by Australian General Practitioners and Obstetricians . Nicotine Tob Res . 2017 ; 19 ( 5 ): 636 – 641 .

Duaso MJ Forman J Harris J Lorencatto F McEwen A . National survey of smoking and smoking cessation education within UK midwifery school curricula . Nicotine Tob Res . 2017 ; 19 ( 5 ): 591 – 596 .

Emery J Sutton S Naughton F . Cognitive and behavioural predictors of quit attempts and biochemically-validated abstinence during pregnancy . Nicotine Tob Res . 2017 ; 19 ( 5 ): 547 – 554 .

Joseph H Emery R Bogen D Levine M . The influence of smoking on breastfeeding among women who quit smoking during pregnancy . Nicotine Tob Res . 2017 ; 19 ( 5 ): 652 – 655 .

Sloan M Hopewell S Coleman T Cooper S Naughton F . Smoking cessation support by text message during pregnancy: a qualitative study of views and experiences of the MiQuit intervention . Nicotine Tob Res . 2017 ; 19 ( 5 ): 572 – 577 .

Bradizza C Stasiewicz P Zhuo Y et al.  . Smoking cessation for pregnant smokers: development and pilot test of an Emotion Regulation Treatment (ERT) for negative affect smokers . Nicotine Tob Res . 2017 ; 19 ( 5 ): 578 – 584 .

Oncken C Ricci K Kuo CL Dornelas E Kranzler H Sankey H . Correlates of electronic cigarettes use before and during pregnancy . Nicotine Tob Res . 2017 ; 19 ( 5 ): 595 – 590 .

Loree A Ondersma S Grekin E . Toward enhancing treatment for pregnant smokers: Laying the groundwork for the use of complementary and alternative medicine approaches . Nicotine Tob Res . 2017 ; 19 ( 5 ): 562 – 571 .

Author notes

Email alerts, citing articles via.

• About Nicotine & Tobacco Research
• Recommend to your Library

Affiliations

• Online ISSN 1469-994X
• Copyright © 2024 Society for Research on Nicotine and Tobacco
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

A systematic review of maternal smoking during pregnancy and fetal measurements with meta-analysis

Affiliation Child Health, University of Aberdeen, Aberdeen, United Kingdom

Affiliation FISABIO – Universitat Jaume I – Universitat de València Epidemiology and Environmental Health Joint Research Unit and Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Valencia, Spain

Affiliation The Generation R Study, Department of Paediatrics, Department of Epidemiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands

Affiliation MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom

Affiliation University College London, London, United Kingdom

Affiliation Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway

Affiliation Department of Environmental Epidemiology, Nofer Institute of Occupational Medicine, Lodz, Poland

* E-mail: [email protected]

• Miriam Abraham, 
• Salem Alramadhan, 
• Carmen Iniguez, 
• Liesbeth Duijts, 
• Vincent W. V. Jaddoe, 
• Herman T. Den Dekker, 
• Sarah Crozier, 
• Keith M. Godfrey, 
• Peter Hindmarsh, 

• Published: February 23, 2017
• https://doi.org/10.1371/journal.pone.0170946
• Reader Comments

Maternal smoking during pregnancy is linked to reduced birth weight but the gestation at onset of this relationship is not certain. We present a systematic review of the literature describing associations between maternal smoking during pregnancy and ultrasound measurements of fetal size, together with an accompanying meta-analysis.

Studies were selected from electronic databases (OVID, EMBASE and Google Scholar) that examined associations between maternal smoking or smoke exposure and antenatal fetal ultrasound measurements. Outcome measures were first, second or third trimester fetal measurements.

There were 284 abstracts identified, 16 papers were included in the review and the meta-analysis included data from eight populations. Maternal smoking was associated with reduced second trimester head size (mean reduction 0.09 standard deviation (SD) [95% CI 0.01, 0.16]) and femur length (0.06 [0.01, 0.10]) and reduced third trimester head size (0.18 SD [0.13, 0.23]), femur length (0.27 SD [0.21, 0.32]) and estimated fetal weight (0.18 SD [0.11, 0.24]). Higher maternal cigarette consumption was associated with a lower z score for head size in the second (mean difference 0.09 SD [0, 0.19]) and third (0.15 SD [0.03, 0.26]) trimesters compared to lower consumption. Fetal measurements were not reduced for those whose mothers quit before or after becoming pregnant compared to mothers who had never smoked.

Conclusions

Maternal smoking during pregnancy is associated with reduced fetal measurements after the first trimester, particularly reduced head size and femur length. These effects may be attenuated if mothers quit or reduce cigarette consumption during pregnancy.

Citation: Abraham M, Alramadhan S, Iniguez C, Duijts L, Jaddoe VWV, Den Dekker HT, et al. (2017) A systematic review of maternal smoking during pregnancy and fetal measurements with meta-analysis. PLoS ONE 12(2): e0170946. https://doi.org/10.1371/journal.pone.0170946

Editor: Raymond Niaura, Legacy, Schroeder Institute for Tobacco Research and Policy Studies, UNITED STATES

Received: October 28, 2016; Accepted: January 12, 2017; Published: February 23, 2017

Copyright: © 2017 Abraham et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The study was supported by the European Cooperation in Science and Technology, who provided funds for publication. KMG is supported by the National Institute for Health Research through the NIHR Southampton Biomedical Research Centre and by the European Union's Seventh Framework Programme (FP7/2007-2013), projects Early Nutrition and ODIN under grant agreement numbers 289346 and 613977.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Maternal smoking during pregnancy is associated with a reduction in birth weight of approximately 250g and is known to adversely affect the health of both fetus and mother.[ 1 ] Knowledge of the age at onset of faltering fetal growth in association with maternal smoking would be useful evidence to underpin public health advice for mothers not to smoke during pregnancy. The advent of ultrasound in the mid-1980s provided an opportunity to study antenatal fetal size and growth as indices of fetal wellbeing, and there is now a rapidly expanding literature of “fetal epidemiology”.

The literature describing associations between maternal smoking and reduced fetal measurements is inconsistent. For example, maternal smoking is associated with reduced second trimester growth in some studies[ 2 , 3 ] but not all[ 4 ] and abdominal and proximal muscle growth restriction has been linked to maternal smoking in one population[ 5 ] but to peripheral fetal growth (i.e. femur length) in others.[ 2 , 3 ] One study reported an association between exposure to maternal smoking and increased fetal head and arm growth.[ 6 ] Here we report a systematic review of the literature with meta-analysis to answer the question “at which gestational ages are the associations between exposure to maternal smoking apparent?” In secondary analyses we sought to relate fetal size to high or low cigarette consumption and the cessation of smoking before or during pregnancy.

Materials and methods

Rationale, inclusion criteria and search strategy.

We have previously completed a systematic review linking antenatal size and growth to risk for postnatal outcomes linked to non-communicable diseases[ 7 ] and then sought to identify which potentially modifiable environmental exposures were linked to reduced fetal size. A database search was carried out in August 2014 and updated in May 2016 using OVID MEDLINE, EMBASE and CINAHL databases. Studies where fetal ultrasound anthropometric measurements related to maternal environmental exposures were included. Papers which related maternal exposures to congenital malformations (e.g. renal cysts) were excluded. The number and diversity of papers identified persuaded us to present the maternal smoking literature separately from other exposures. Search terms were identified after reviewing relevant publications already known to the authors from our earlier work[ 7 ] and are displayed in S1 Fig . Papers were also identified from the following cohorts known to have fetal measurement data: the Raine cohort; ( http://www.rainestudy.org.au/ ); the EDEN cohort ( https://eden.vjf.inserm.fr ); Southampton Women Survey (SWS, http://www.leu.soton.ac.uk/sws/ ); the Generation R study ( http://www.erasmusmc.nl/epi/research/Generation-R/ ); and INMA Mother and Child Cohort Study[ 8 ]. References of identified papers were also searched to identify additional studies. Abstracts were independently reviewed by two authors and studies which fell within our predefined inclusion criteria were identified and full papers obtained. Ethics approval was not required for this systematic review and meta-analysis since no patient contact took place.

Fetal measurements

The measurements considered in the first trimester (i.e. ≤13 weeks gestation) were: crown rump length (CRL), biparietal diameter (BPD), head circumference (HC) abdominal circumference (AC) and mean abdominal diameter (MAD). For the second trimester (i.e. 14 to <28 weeks gestation) and third trimester (i.e. ≥28 weeks) femur length (FL), HC, BPD, MAD, AC and estimated fetal weight (EFW) were considered.

Data synthesis for meta-analysis

Standardised fetal measurements were derived for each fetal measurement for every population. No interaction terms were sought since our focus was on the relationship between maternal smoking and fetal size. Original data were provided by the custodians of three datasets (Scand_SGA[ 4 , 9 , 10 ], Prabhu et al [ 3 ] and Pringle et al [ 11 ]) where EFW was derived[ 12 ] and Z scores for fetal measurements calculated using linear regression which considered sex, gestation and maternal height. Previously unpublished data were also provided in a format for meta-analysis by four other cohorts ([ 2 , 13 , 14 ] and SWS). Results from one published study[ 15 ] were also included. Mean absolute and standardised fetal measurements were reported since this paper[ 15 ] reported only absolute measurements. Where more than one publication arose from a single cohort (e.g. Scand-SGA[ 4 , 9 , 10 ]), a single dataset was used to derive results for meta-analysis. Z scores (but not absolute values) of MAD and HC were considered as interchangeable measurements for AC and BPD respectively in the meta-analysis. Review Manager (version 5.3.5) was used for meta-analysis. The following secondary analyses were carried out: (i) comparison of fetal measurements between individuals exposed to lower or higher maternal cigarette consumption (ii) comparison of fetal measurements for individuals whose mothers quit before becoming pregnant and never smokers and (iii) comparison of fetal measurements for individuals whose mothers quit during pregnancy and never smokers. The secondary analyses were restricted to those fetal measurement where maternal smoking (yes/no) was associated with altered z scores of fetal measurements. The risk of bias and heterogeneity were explored using funnel plots and I 2 (for the latter, a value of >50% was considered indicative of substantial heterogeneity[ 16 ]). The Effective Public Health Practice Project tool was used to assess the quality of the studies included in the final review ( http://www.ephpp.ca/PDF/Quality%20Assessment%20Tool_2010_2.pdf ).

Study selection

The search identified 284 abstracts and 16 papers were included in this review,[ 2 – 6 , 9 – 11 , 13 – 15 , 17 – 21 ] Fig 1 . Studies were excluded that related maternal smoking to fetal organ volumes including total lung and renal volumes[ 22 , 23 ], brain[ 24 ] or kidney[ 25 ]) and abdominal fat.[ 26 ] One paper were identified from reading reference lists[ 9 ]. One publication[ 27 ] was considered but excluded since the proportion of maternal smoking was very low (2.2%).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0170946.g001

Study characteristics

There was one small randomised controlled study,[ 20 ] two case-control studies,[ 5 , 28 ] one case only study[ 18 ] and the remainder were prospective cohorts. One paper compared maternal cotinine to fetal measurements[ 14 ] and the remainder relied upon maternal reported smoking. There were three studies with strong study design,[ 9 , 14 , 17 ] nine with moderate and four with weak study design;[ 4 , 15 , 18 , 21 ]. For each study included, Table 1 describes the quality of study design, the direction of any association and in which trimester any association was present. See S1 Table for full results of the quality control.

https://doi.org/10.1371/journal.pone.0170946.t001

Systematic review

Fetal size and maternal smoking..

Three publications were based on one cohort[ 4 , 9 , 10 ] and two publications on a second cohort[ 13 , 19 ] and results are summarised for each paper. Maternal smoking was not associated with altered first trimester size in the two studies identified.[ 3 , 13 ] The relationship between maternal smoking and second trimester fetal measurements differed between studies: BPD was reduced in association with maternal smoking in two papers,[ 14 , 15 ] was increased in a third[ 21 ] and not changed in eight [ 2 – 4 , 9 – 11 , 13 , 19 ]; FL was reduced in association with maternal smoking in two papers[ 2 , 3 ] but not in nine [ 4 , 6 , 9 – 11 , 13 – 15 , 19 ]; and AC or MAD was reduced in association with maternal smoking in two studies,[ 10 , 15 ] increased in one[ 6 ] and not changed in seven.[ 2 , 9 , 11 , 13 , 14 , 19 ] In the third trimester, maternal smoking was associated with reduced EFW and AC (or MAD) in all studies reporting these measurements. Third trimester BPD or HC was reduced in fetuses whose mothers smoked in five studies,[ 2 , 10 , 13 , 15 , 19 ] BPD was increased in one study[ 6 ] and not associated with maternal smoking in three.[ 9 , 11 , 21 ] Third trimester femur length was reduced in six studies [ 2 , 6 , 11 , 13 , 19 ] and not associated with maternal smoking in four studies.[ 10 , 15 , 18 , 21 ] Fuller details are presented in S2 Table .

Fetal growth and maternal smoking.

Maternal smoking was associated with reduced growth in the second or third trimester in all six studies identified.[ 2 , 5 , 6 , 13 , 17 , 20 ] The studies reported different growth outcomes making meta-analysis impractical, but the magnitude of association between maternal smoking and fetal size differed between studies: maternal smoking was associated with (i) a reduction of 8–10% of standard deviation score for growth in EFW, FL and BPD between 20 and 34 weeks gestation; [ 13 ] (ii) a mean reduction in EFW between 33 weeks and term of 0.13 z score;[ 17 ] (iii) a reduction in HC and AC growth equivalent to 0.5mm/week between 13 and 30 weeks gestation[ 2 ] or reduced AC growth by ~1mm/week between 27 and 37 weeks gestation[ 5 ]. Abstinence from smoking was associated with increased growth in EFW, FL and AC (approximately 50g/week, 0.3 and 2 mm/week respectively) between 30 and 34 weeks gestation compared to ongoing smoking.[ 20 ]

Fetal size and passive smoke exposure.

Among non-smoking mothers, exposure to second hand smoke exposure in restaurants (but not home or workplace) was associated with reduced BPD between 20 and 32 weeks but not 32–38 weeks.[ 19 ] When passive maternal exposure to tobacco smoke was defined as <10ng/mL plasma cotinine, there was a negative association which approached significance between plasma cotinine and second trimester BPD.[ 14 ]

Meta-analysis

The details available from the eight populations included in the meta-analysis are presented in Table 2 .

https://doi.org/10.1371/journal.pone.0170946.t002

First trimester size.

Among two cohorts, there was increased AC z score (mean increased 0.09 z score [95% CI 0.00, 0.18], p = 0.04) for fetuses exposed to maternal smoking compared to unexposed fetuses, Table 3 and Fig 2 . No other fetal measurement was associated with maternal smoking, Table 3 .

https://doi.org/10.1371/journal.pone.0170946.t003

The vertical lines correspond to 95% confidence intervals.

https://doi.org/10.1371/journal.pone.0170946.g002

Second trimester size.

Maternal smoking was associated with reduced absolute (p = 0.001) and z score (p = 0.04) FL, Table 3 and Fig 2 . Maternal smoking was associated with reduced BPD/HC z score (p = 0.03), Figs 2 and 3 , but not with EFW or AC, Table 3 . The I 2 values for heterogeneity between studies exceeded 50% for all absolute fetal measurements except FL and also for standardised measurements for BPD and AC. S2 Fig present forest plots for comparisons of standardised measurement and S3 Fig presents the differences in absolute measurements between fetuses whose mothers did and did not smoke. S4 Fig shows funnel plots for estimates of second trimester standardised scores.

https://doi.org/10.1371/journal.pone.0170946.g003

Third trimester size.

Maternal smoking was associated with reduced absolute and z score values for all fetal measurements, Table 3 , Figs 2 and 3 . The results were unchanged when z scores for MAD (from the Scand_SGA cohort) were removed from the AC analysis and when z scores for HC results were removed from the BPD analysis (SWS data and Generation R 2 ), data not presented. The heterogeneity test across studies was significant for all absolute measurements but for none of the standardised measurements. S5 Fig presents forest plots and I 2 values comparisons of z scores and between fetuses whose mothers did and not smoke and S6 Fig present differences in the absolute fetal measurements.

Secondary analyses.

Comparisons between individuals with high relative to low maternal cigarette consumption demonstrated a borderline significant reduction in second trimester BPD z score for the high compared to the low consumption group (four populations, mean reduction 0.09 [0, 0.19] p = 0.05) ( S3 Table ) and also for third trimester BPD z score (three populations, mean reduction 0.15 [0.03, 0.26] p = 0.01) and FL z score (three populations, mean reduction 0.17 [0.06, 0.28] p = 0.003), S4 Table . There was no reduction in second or third trimester fetal measurements for individuals whose mothers quit during pregnancy compared to non-smokers, S3 and S4 Tables. There was no difference between second trimester measurements for those whose mothers had quit before becoming pregnant and whose mothers had never smoked.

This systematic review of the literature and meta-analysis were designed to describe the gestation at which exposure to maternal smoking became associated with reduced antenatal fetal size and growth. Biparietal diameter and femur length were reduced by at least 0.06 standard deviations (SD) by the second trimester, and all fetal measurements were reduced in the third trimester, typically by 0.2 SD. The reductions in fetal size associated with maternal smoking are statistically significant but small. In the studies where data were available, we also observed an exposure-response relationship for maternal cigarette consumption and reduced second and third trimester fetal head size, and we saw no evidence of reduced measurements among fetuses whose mothers quit before or after becoming pregnant compared to non-smokers. Collectively our findings support current public health advice that mothers should quit whilst pregnant[ 29 ] and also suggest that harm reduction might be achieved by reduced cigarette consumption and this now needs exploring in longitudinal studies.

Heterogeneity between studies is not unexpected given the different methodologies used, and in particular some different covariates were included when z scores were derived, but the direction of effect of maternal smoking was consistent although the magnitude did vary. The I 2 values for standardised fetal measurements indicated little/moderate heterogeneity was likely,[ 16 ] whereas those for absolute measurements indicated the presence of considerable/substantial heterogeneity.[ 16 ] Heterogeneity for the differences in absolute fetal measurements associated with maternal smoking between studies was most likely explained by not considering covariates, especially gestational age. Funnel plots for second trimester standardised measurements demonstrated heterogeneity for BPD and AC but, acknowledging that there were fewer than the ideal number of ten studies included in the analysis,[ 30 ] the plots appeared symmetrical and suggested no obvious bias.

Strength of this work are its novelty and the use of unpublished data from many cohorts for meta-analysis. Among the cohorts included, the fewest number of confounders were included when adjusting fetal measurements from the Generation R study and the greatest for SWS and the reduction in second trimester femur length SD score was greater for the Generation R study compared to SWS (see S2 Fig ) and it is possible that consideration of more variables would yield a less obvious association between maternal smoking and fetal femur length in the Generation R study participants. However, it is notable that the absolute femur length measurements were considerably shorter for the Generation R study participants compared to SWS so a corresponding discrepancy in standardised measurements is not unexpected. Furthermore, two cohorts included in the meta-analysis have already described differences in absolute femur length between exposed and unexposed fetuses after adjustment for a comprehensive list of variables.[ 2 , 3 ]

The fetus has traditionally been thought to have a privileged position where it was protected from the adverse effects of environmental exposures by the maternal-placental “unit”, but it is clear that maternal smoking affects fetal wellbeing and growth. Whilst a study such as ours cannot prove causation (although the trial of Heil et al [ 20 ] points to causation), our results fulfil many of the Bradford Hill[ 31 ] criteria including strength, consistency, temporality and biological gradient. Our secondary analyses showed that cessation before and shortly after becoming pregnant was not associated with reduced fetal size and this suggests that the mechanisms affecting fetal growth are predominantly acting in the second half of pregnancy and not before or during early pregnancy. Although maternal smoking may be causally related to small fetal size, other factors such as maternal diet, alcohol and physical activity might be linked to both fetal growth and smoking and partly explain the associations we have observed.

This systematic review has some limitations. First maternal smoking during pregnancy is known to be underreported by mothers[ 32 ], and among the studies we considered maternal smoking was only objectively measured in one study[ 14 ], thus the magnitude of the association between maternal smoking and small fetal size is likely to be underestimated. Second, the results were restricted to observations made in Western populations and thus may not be generalisable to all populations. Third, secondary analyses were restricted to a subset of populations and it is possible that some of the comparisons would have achieved significance with a larger sample size. Fourth, first trimester dimensions are technically difficult to measure and the absence of association with maternal smoking may at least partly reflect reduced accuracy of measurements, and additionally first trimester data were only available from two cohorts, in one of whom reduced first trimester crown rump length has been reported for fetuses whose mothers who both smoke and do not take folic acid.[ 33 ] Finally, data were not available to link maternal smoking in specific trimesters to fetal size in each trimester.

In summary, maternal smoking during pregnancy is associated with reduced fetal size and growth from the second trimester. The relationship between maternal exposure to second hand smoke should be further explored since this exposure is associated with reduced birth weight.[ 34 ]

A PRISMA checklist is available as a supporting information ( S1 Checklist ). The page numbers described in this checklist correspond to page number on the manuscript as submitted and not the manuscript as published.

Supporting information

S1 table. quality control analysis for the studies included in this review..

https://doi.org/10.1371/journal.pone.0170946.s001

S2 Table. A summary of data in each of the studies included in this systematic review.

https://doi.org/10.1371/journal.pone.0170946.s002

S3 Table. Results of the sensitivity analysis for second trimester measurements.

https://doi.org/10.1371/journal.pone.0170946.s003

S4 Table. Results of the sensitivity analyses for the third trimester.

*Data only available in one study.

https://doi.org/10.1371/journal.pone.0170946.s004

S1 Fig. A “print screen” showing details of the OVID literature search used in May 2016.

https://doi.org/10.1371/journal.pone.0170946.s005

S2 Fig. Forest plots showing differences in standardised second trimester measurements between individuals whose mothers smoked and did not smoke.

https://doi.org/10.1371/journal.pone.0170946.s006

S3 Fig. Forest plots showing differences in absolute second trimester measurements between individuals whose mothers smoked and did not smoke.

https://doi.org/10.1371/journal.pone.0170946.s007

S4 Fig. Funnel plots for standardised second trimester measurements between individuals whose mothers smoked and did not smoke.

https://doi.org/10.1371/journal.pone.0170946.s008

S5 Fig. Forest plots showing differences in standardised third trimester measurements between individuals whose mothers smoked and did not smoke.

https://doi.org/10.1371/journal.pone.0170946.s009

S6 Fig. Forest plots showing differences in absolute third trimester measurements between individuals whose mothers smoked and did not smoke.

https://doi.org/10.1371/journal.pone.0170946.s010

S1 PRISMA Checklist.

https://doi.org/10.1371/journal.pone.0170946.s011

Author Contributions

• Conceptualization: ST.
• Data curation: ST CI HDD SC WS.
• Formal analysis: ST.
• Funding acquisition: ST.
• Methodology: ST.
• Project administration: ST.
• Resources: ST.
• Writing – original draft: ST.
• Writing – review & editing: MA SA CI LD VWJ HDD SC KMG PH TV GWJ WH WS GD ST.
• 1. Tobacco Advisory Group of the Royal College of Physicians. Passive smoking and children. 2010(ISBN 978-1-86016-376-0).
• View Article
• PubMed/NCBI
• Google Scholar
• 16. Cochrane Library. Cochrane handbook for systematic reviews of interventions http://handbook.cochrane.org/chapter_9/9_5_2_identifying_and_measuring_heterogeneity.htm . Updated 2011. Accessed 02/16, 2016.
• 29. National Institute for Health and Care Excellence. How to stop smoking in pregnancy and following childbirth. https://www.nice.org.uk/guidance/ph26 . Updated 2010. Accessed 01/06, 2016.

• Open access
• Published: 04 April 2024

Smoking during pregnancy and its effect on placental weight: a Mendelian randomization study

• Annika Jaitner 1 ,
• Marc Vaudel 2 , 3 , 4 ,
• Krasimira Tsaneva-Atanasova 5 , 6 ,
• Pål R. Njølstad 2 , 7 ,
• Bo Jacobsson 3 , 8 , 9 ,
• Jack Bowden 1 , 10 ,
• Stefan Johansson 11 , 2 &
• Rachel M. Freathy 1  

BMC Pregnancy and Childbirth volume  24 , Article number:  238 ( 2024 ) Cite this article

543 Accesses

7 Altmetric

Metrics details

The causal relationship between maternal smoking in pregnancy and reduced offspring birth weight is well established and is likely due to impaired placental function. However, observational studies have given conflicting results on the association between smoking and placental weight. We aimed to estimate the causal effect of newly pregnant mothers quitting smoking on their placental weight at the time of delivery.

We used one-sample Mendelian randomization, drawing data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( N  = 690 to 804) and the Norwegian Mother, Father and Child Cohort Study (MoBa) ( N  = 4267 to 4606). The sample size depends on the smoking definition used for different analyses. The analysis was performed in pre-pregnancy smokers only, due to the specific role of the single-nucleotide polymorphism (SNP) rs1051730 ( CHRNA5 – CHRNA3 – CHRNB4 ) in affecting smoking cessation but not initiation.

Fixed effect meta-analysis showed a 182 g [95%CI: 29,335] higher placental weight for pre-pregnancy smoking mothers who continued smoking at the beginning of pregnancy, compared with those who stopped smoking. Using the number of cigarettes smoked per day in the first trimester as the exposure, the causal effect on placental weight was 11 g [95%CI: 1,21] per cigarette per day. Similarly, smoking at the end of pregnancy was causally associated with higher placental weight. Using the residuals of birth weight regressed on placental weight as the outcome, we showed evidence of lower offspring birth weight relative to the placental weight, both for continuing smoking at the start of pregnancy as well as continuing smoking throughout pregnancy (change in z-score birth weight adjusted for z-score placental weight: -0.8 [95%CI: -1.6,-0.1]).

Our results suggest that continued smoking during pregnancy causes higher placental weights .

Peer Review reports

Maternal smoking during pregnancy is often described as one of the most modifiable risk factors for adverse pregnancy outcomes [ 1 ]. Despite a strong public health message, many women continue to smoke in pregnancy. In the UK, the NHS digital service provides statistics indicating that approximately 8.6% of mothers were known smokers at the time of delivery in the first half of 2023 [ 2 ]. Mendelian randomization (MR) studies between smoking during pregnancy and offspring birth weight suggest a causal relationship between smoking during pregnancy and lower birth weight [ 3 , 4 , 5 , 6 ]. However, the underlying mechanisms remain unclear.

A potential mediator for the effect of smoking on fetal growth is the placenta, which provides oxygen and nutrient transport between mother and fetus [ 7 ]. The maternal environment is experienced through the placenta [ 8 ]. Additionally, studies have shown that maternal smoking is associated with altered histological morphology and structure, which, for example, can lead to a reduction in vascularization [ 9 , 10 ]. Such abnormalities and the direct effect of nicotine on the placenta can reduce the maternal and fetal exchange, potentially leading to placental insufficiency [ 11 , 12 ]. Several observational studies have reported a reduction in placental weight in mothers who smoked in pregnancy or continued to smoke compared to non-smoking mothers [ 7 , 13 ]. Furthermore, a linear decrease in placental weight with the number of cigarettes smoked per day was observed [ 13 ]. In contrast to these findings, Mitsuda et al. observed the highest placental weights for women who continued to smoke in pregnancy compared with those who never smoked or who quit smoking before pregnancy [ 14 ]. The apparently conflicting results from observational epidemiological studies linking smoking to placental weight may be due to unmeasured confounding and bias, and were conducted in different populations and with different study designs, making them difficult to compare. Hence, additional approaches are necessary to investigate a potential causal relationship.

One method enabling the inference of causal effects in the presence of confounding is one-sample MR. It is a method, which utilises the natural randomization of inheritance of germline genetic variation from parents to their offspring at conception [ 15 ]. We used a genetic variant, single-nucleotide polymorphism (SNP) rs1051730, as the instrumental variable to genetically proxy maternal smoking. Previous studies have shown that each additional copy of the risk allele rs1051730 is associated with higher odds of continuing smoking during pregnancy as well as an increase of about one cigarette per day [ 16 , 17 , 18 ]. The SNP is located within the nicotine acetylcholine receptor gene cluster CHRNA5 – CHRNA3 – CHRNB4 on chromosome 15. The biological relationship to smoking and nicotine dependence supports the association between the SNP and smoking. However, it is important to note that rs1051730 is not associated with smoking initiation [ 16 , 18 ]. Due to the specific association of rs1051730 with smoking behaviour, we only used data from mothers who smoked before pregnancy to capture continuing smoking compared to stopping smoking in pregnancy. To investigate any causal relationship between maternal smoking during pregnancy and placental weight we used two cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC) [ 19 , 20 ] and the Norwegian Mother, Father and Child Cohort Study (MoBa) [ 21 , 22 ]. Figure  1 shows the directed acyclic graph describing the causal assumptions for our study analysis. Our aim was to improve the understanding of the effect of continuing smoking in pregnancy by investigating the causal relationship between maternal smoking and placental weight.

Directed acyclic graph (DAG) to highlight the MR framework. The MR assumptions for the instrumental variable (in this case maternal rs1051730) are shown in red: 1 The instrumental variable needs to be associated with the exposure. 2 The instrumental variable is independent of confounding factors that confound the association of the exposure and the outcome. 3 The instrumental variable is independent of the outcome given the exposure and the confounding factors. The MR analysis estimates the effect between the exposure and the outcome shown in blue. The MR analysis is adjusted for offspring sex and ancestry principal components (and genetic batch variables in MoBa). These are summarised in the measured confounder variable Z. U stands for unmeasured confounders, which we are unable to include in the analysis

Study populations

We performed our analysis in two different study populations. ALSPAC is a prospective longitudinal cohort study [ 19 , 20 ]. More information on the cohort is given in the supplementary material. Our analysis was performed in unrelated mothers with genetic information for rs1051730 available. Placental weight measures were available for 37% of the records. We excluded multiple births and preterm births (pregnancy duration < 37 weeks). Full details including sample sizes are shown in Fig.  2 . After all exclusions, the analysis in pre-pregnancy smokers with available placental weight measures as an outcome was therefore performed in up to 804 individuals in ALSPAC. MoBa is a population-based pregnancy cohort study conducted by the Norwegian Institute of Public Health [ 21 , 22 ]. The study is linked with the Medical Birth Registry of Norway (MBRN) , a national health registry containing information about all births in Norway. More detailed information on the cohort and the version used is given in the supplementary material. We restricted the MoBa data to unrelated individuals with genetic information for the mother available. Additionally, we excluded multiple births and preterm births (pregnancy duration < 37 *7 days). Full details including sample sizes are shown in Fig.  2 . After all exclusions, there were 4667 pre-pregnancy smokers with available placental weight measures in MoBa, and up to 4606 of these individuals had smoking information relevant for our analyses. 

Flowchart to display the exclusion criteria of both the ALSPAC and the MoBa study including sample sizes

Genetic instrument

We instrumented the smoking behaviour using rs1051730, which has shown to be associated with smoking quantity and the inability to quit smoking but not smoking initiation [ 16 , 17 , 18 ]. We used the genotype dosage of the genetic variant, rs1051730 as a continuous variable, which for each individual was a number close to 0, 1, or 2, reflecting the number of smoking risk alleles, combined with the probability of having 0, 1, or 2 risk alleles from the genotype imputation. More information on genotyping in both cohorts is described in detail in previously published articles [ 22 , 23 ].

Outcome variable

The main outcome of interest is placental weight measured in grams. In ALSPAC, placental weight measures were obtained directly from obstetric records by research midwives who went back to the handwritten medical records of most patients and abstracted data including all weight measures. In MoBa, data related to pregnancy and birth were standardised and stem from the MBRN. Reporting placenta weight to the MBRN is mandatory and is carried out by the midwife attending the birth. All midwives share curriculum and training regarding the reporting of data, including examination of the afterbirth to the MBRN. The placenta is examined and characteristics of the placenta and umbilical cord, including measurements of the placental weight (untrimmed with the cord and membranes attached) are reported. The method has been unchanged since the inception of the MBRN in 1967. The reporting of these data to the MBRN has been validated, with good inter- and intra-observer agreement, making the data suitable for large scale epidemiological research [ 24 ].

Exposure variable

The exposures of interest were (i) continuing smoking during pregnancy vs. quitting and (ii) number of cigarettes smoked per day during pregnancy. We used different measures of self-reported smoking variables. Study specific differences are outlined below.

Smoking variables of interest in ALSPAC

In ALSPAC, mothers were asked if they smoked before pregnancy. No specific time frame was given in the questionnaire to the mothers. We included everyone in the study who said they consumed tobacco before pregnancy even if this consumption was through other sources than cigarettes, such as pipes and cigars. The frequency of tobacco consumption via cigarettes was by far the highest (97.8% of the mothers who smoked pre-pregnancy said they smoked cigarettes). The following smoking variables were used as exposures in the analysis performed in ALSPAC:

Smoking in the first three months of pregnancy

At 18 weeks of gestation the mother was asked whether she smoked in the first three months of pregnancy. This variable is self-reported and retrospective.

Smoking in the last two weeks of pregnancy

This information was gained from a questionnaire sent out 8 weeks after the child was born. As for the previous variables smoking refers to any type of tobacco consumption.

Number of cigarettes smoked per day

Besides classifying whether a mother smoked or not as a binary variable, the participants were also asked about the number of cigarettes smoked per day in the first three months and the last two weeks of pregnancy. The following categories were given: 0 cigarettes, 1–4, 5–9, 10–14, 15–19, 20–24, 25–29, 30 or more cigarettes. For the analysis the categories were coded with the number of the lower bound of each category.

Smoking variables of interest in MoBa

In MoBa, the mothers were asked whether they smoked during the last three months before becoming pregnant. The information for all smoking variables is taken from the MBRN [ 25 ]. The following smoking variables were used as exposures in the analysis performed in MoBa:

Mother smoking at the beginning of pregnancy

The antenatal health card containing this information is filled out at the first antenatal visit between 6 and 12 weeks of gestation.

Mother smoking at the end of pregnancy

The end of pregnancy corresponds to the last trimester (approximately 36 weeks of gestation).

This information was recorded for the beginning and the end of pregnancy. In contrast to ALSPAC, the number of cigarettes in MoBa is given in integer values, instead of being grouped into categories. Mothers who stopped smoking in pregnancy and therefore reported that they were not smoking at the beginning and/or the end of pregnancy were coded with 0 cigarettes.

• Mendelian randomization

We performed one-sample MR using individual level data. MR requires three assumptions to hold for rs1051730 to be a valid instrumental variable [ 15 ]. The assumptions are graphically highlighted in Fig.  1 . Due to the genetic variants being defined at conception we assumed that it is independent of factors confounding the association between smoking during pregnancy and placental weight. We cannot formally test that the genetic instrument is only associated with the outcome through the exposure. However, based on the position of rs1051730 in the genome and therefore likely biological role, we assumed that the third assumption holds as well. We test the association between the SNP and placental weight in mothers who have never smoked to further support that there are no pleiotropic pathways. Additionally, we studied the association between the SNP and various variables in the MoBa study.

For all analyses, we aimed to estimate the causal effect of smoking on placental weight (PW) in mothers who smoked pre-pregnancy ( \({S}_{pre}\) =1). For continuous smoking definitions, our causal estimand was the population average effect of intervening to lower individuals observed smoking level \(s\) by 1 cigarette per day.

For binary smoking definitions, our causal estimand reflects the population average effect if all mothers continued to smoke versus if all mothers subsequently quit.

In each case, we impose a fourth identifying assumption of homogeneity, meaning that the causal effect does not vary across levels of a single instrument, nor across instruments. For all analysis a two-stage regression approach was used. In the continuous smoking exposure case, the smoking variable (S) was firstly regressed on rs1051730 (G) and adjusted for known confounders or competing exposures (Z) via a linear model:

to furnish a genetically predicted smoking variable ( \(\widehat{S})\) . Note that this first stage regression does not require any placental weight measurements. We therefore performed the regression in all pre-pregnancy smoking mothers with available smoking information during pregnancy. The sample sizes used for this stage are given in Table  2 . Secondly, PW was regressed on \(\widehat{S}\) :

We adjusted all our analyses for offspring sex and ancestry principal components, which is reflected by Z in the equations above. We performed sensitivity analyses adjusting for additional potential confounders (Supplementary SFigure 2 and SFigure  3 ). For binary smoking exposure variables, we performed a logistic regression in the first stage. The estimation of the standard error of the causal estimate ( \({\beta }_{1}\) ) accounts for first stage uncertainties.

Residuals of z-score birth weight on z-score placental weight

We performed a final analysis by incorporating both birth and placental weight into a single outcome variable, thereby taking into account their relationship. Using the residuals from the regression of birth weight on placental weight can be used as a measure of placental efficiency [ 26 ].

We firstly generated z-scores using generalised additive models for location, scale and shape from the gamlss R-package [ 27 , 28 ]:

of placental weight adjusting for gestational duration in female offspring ( \(P{W}_{Zf}\) );

of placental weight adjusting for gestational duration in male offspring ( \(P{W}_{Zm}\) );

of birth weight adjusting for gestational duration in female offspring ( \(B{W}_{Zf}\) );

of birth weight adjusting for gestational duration in male offspring ( \(B{W}_{Zm}\) ).

This resulted in adjusted z-scores of birth weight \(B{W}_{Z}=(B{W}_{Zm}, B{W}_{Zf})\) and placental weight \(P{W}_{Z}=(P{W}_{Zm}, P{W}_{Zf})\) . The scores were derived from the individual level data within the ALSPAC and the MoBa study separately.

2) We then regressed \(B{W}_{Z}\) on \(P{W}_{Z}\) :

• $$B{W}_{Z}={\gamma }_{0}+{\gamma }_{1}P{W}_{Z}+{\epsilon }_{B{W}_{Z}.}$$ (3)

3) Next, we took the estimated residuals ( \(\widehat{R}\) ) from the equation in step 2: \(\widehat{R}=B{W}_{Z}-\widehat{B{W}_{Z}.}\)

4) Finally, we used the residuals from step 3 as the outcome in an MR analysis with a binary smoking exposure S, applying the two stage approach below:

• $$logit(Pr(S=1|({S}_{Pre}=1),G,Z))={\alpha }_{0}+{\alpha }_{1}G+{\alpha }_{2}Z+{\epsilon }_{S}$$ (4)
• $$\widehat{R}|{(S}_{Pre}=1),\widehat{S},Z={\beta }_{0}+{\beta }_{1}Z+{\epsilon }_{\widehat{R}}.$$ (5)

This enabled us to estimate the causal effect of maternal smoking on birth weight relative to placental weight.

Adjustment variables and meta-analysis

We adjusted all analysis for offspring sex and principal components to account for population stratification (first 5 in ALSPAC and first 10 in MoBa). All analysis in MoBa were additionally adjusted for genetic batch variables. After performing the MR study in ALSPAC and in MoBa, we meta-analysed the results from smoking at the beginning of pregnancy and smoking at the end of pregnancy. The Q statistics (on 1df) (STable 1 ) provided no evidence to refute the null hypothesis that causal estimates derived from ALSPAC and MoBa pertained to different underlying quantities. We therefore combined them using an inverse variance weighted fixed effect model to produce an overall estimate.

Study population characteristics

Table 1 shows clinical characteristics in the datasets used for the analysis from both the ALSPAC and the MoBa study.

SNP-exposure association in ALSPAC and MoBa

The results for the association between the different smoking exposures and the genetic instrument rs1051730 are shown in Table  2 . This corresponds to the first stage of the MR. For all the different smoking variables the SNP is a strong instrument showing that each additional risk allele increases the likelihood of continuing smoking in pregnancy as well as the quantity.

Binary smoking exposure

In the fixed effect meta-analysis, we observed that mothers who continued smoking in pregnancy had, on average, a 182 g (95% CI: [29,335]) higher placental weight compared with those who stopped smoking at the beginning of pregnancy. The F-statistic as a measure of the strength of the instrument was 11.1 in ALSPAC and 9.9 in MoBa for the analysis at the beginning of pregnancy, which is very close to the minimum F-Statistic of 10 suggested in the literature [ 15 , 29 ]. In MoBa, the F-Statistic, 17.1, was higher for the analysis with the smoking at the end of pregnancy exposure. In ALSPAC, the F-Statistic did not change much for the different time points of smoking in pregnancy as the exposure. For both ALSPAC and MoBa, and the meta-analysis similar effect sizes were evident for the analysis at the end of pregnancy (meta-analysis: 202 g, 95% CI: [53,351]) compared to the analysis with the smoking exposure being measured at the beginning of pregnancy. Results for the MR study in pre-pregnancy smokers in ALSPAC and in MoBa as well as the fixed effect meta-analysis for a binary smoking exposure are displayed in Fig.  3 .

Forest plot with binary smoking variables on the y-axis and the causal estimate from the MR with placental weight as the outcome on the x-axis. The colours indicate the results for the different studies and the fixed effect meta-analysis. The bars indicate the 95% confidence intervals. The F-statistics from the first stage of the MR analysis are displayed alongside with the sample size N for each analysis. The size of the dot of the point estimate for each analysis is proportional to 1/SE

Cigarettes smoked per day exposure

The meta-analysis results indicated an increase of 11 g (95% CI: [1,21]) in placental weight for each additional cigarette smoked at the beginning of pregnancy amongst the mothers who smoked before pregnancy. Each additional cigarette at the end of pregnancy caused an increase in placental weight of 16 g (95% CI: [4,28]). Figure  4 shows the results of this MR study. The effects in ALSPAC and MoBa were consistent with the meta-analysis. For these analyses the F-statistics were slightly higher than for the binary analysis.

Forest plot with smoking quantity variables on the y-axis and the causal estimate from the MR with placental weight as the outcome on the x-axis. The colours indicate the results for the different studies and the fixed effect meta-analysis. The bars indicate the 95% confidence intervals. The F-statistics from the first stage of the MR analysis are displayed alongside with the sample size N for each analysis. The size of the dot of the point estimate for each analysis is proportional to 1/SE

Residual z score analysis

For both ALSPAC and MoBa, negative point estimates were obtained for the MR with the residuals of the regression of adjusted birth weight on adjusted placental weight as outcome (see Fig.  5 ). This indicated that for mothers who continue to smoke, their offspring birth weights tend to be lower relative to the placental weight. Christians et al. [ 26 ] suggest using the residuals from a regression of birth weight on placental weight as a measure of placenta efficiency. In this context, our results suggest that continuing smoking during pregnancy is causally associated with a lower placenta efficiency.

Forest plot with binary smoking variables on the y-axis and the causal estimate from the MR with the residuals of the regression of adjusted z-score birth weight on adjusted z-score on placental weight as the outcome on the x-axis. The effect sizes reflect the change in z-score birth weight adjusted for z-score placental weight for continuing smoking vs quitting in pregnancy. The colours indicate the results for the different studies and the fixed effect meta-analysis. The bars indicate the 95% confidence intervals. The F-statistics from the first stage of the MR analysis are displayed alongside with the sample size N for each analysis. The size of the dot of the point estimate for each analysis is proportional to 1/SE

Sensitivity analyses

We performed sensitivity analyses to check the assumptions of the MR analysis. In the ALSPAC data, there was no evidence of association between the SNP and placental weight in mothers who have never smoked. The linear regression of placental weight on rs1051730 in never smokers ( N  = 1465) yielded an effect estimate of 3 g per smoking risk allele (95% CI: [-7,13]). We also saw no association between the SNP and various variables that could affect placental weight and therefore are a potential for pleiotropic pathways (supplementary SFigure  1 ).

All our analysis presented in this paper were adjusted for offspring sex and ancestry principal components. We believe offspring sex is a competing exposure and therefore the adjustment will increase the precision of our analysis. Nevertheless, we performed sensitivity analyses adjusting for different sets of potential confounders and showed consistently an increased placental weight for mothers who continue to smoke in pregnancy (Supplementary SFigure  2 and SFigure 3 ).

Using an MR approach, we have provided evidence that continuing smoking during pregnancy causes higher placental weights for term born babies. The results were consistent for both the binary exposure of continuing vs quitting smoking and number of cigarettes smoked per day in two independent cohorts.

Given the well-established relationship between maternal smoking in pregnancy and lower birth weight, it is plausible that smoking would lead to lower placental weights due to an impairment of the placental function. Zdravkovic et al. [ 30 ] stated the likelihood of tobacco exposure reducing the blood flow between mother and child thereby causing a hypoxic environment for the fetus and this could be manifested in decreased placental and fetal growth as oxygen binding is essential for the development of these organs. However, our findings are more in line with a compensatory effect. The placenta might grow larger relative to birth weight to meet the oxygen demands of the fetus and to restore oxygen binding sites. This hypothesis is supported by our findings of the residual analysis, which showed lower birth weights relative to the placental weight for mothers who continue to smoke vs those who quit smoking in pregnancy. The impact of a hypoxic environment on the placenta has been studied in animal models with conflicting results [ 31 ]. For example, increased placental weights with a reduced fetal weight were seen in guinea pigs when exposed to chronic mid gestation 10.5% hypoxia [ 32 ] and observed in mice for a chronic early 13% hypoxia [ 33 ]. Studies in rats have reported that under chronic 13–14% hypoxia in early gestation, an increased placental weight was detected, but without any change in fetal weight [ 34 , 35 ]. This suggests that in some conditions the placenta might be able to adapt and compensate for the hypoxic environment, but in other situations, the enhanced placental growth (and therefore placental weight increase) limits other factors of the fetal development process. Placental weight is often used to proxy placental function [ 36 ], but as discussed above this is not a straightforward relationship and needs to be carefully interpreted. Additionally, placental weight is a combination of several components including size, surface area and thickness. Both abnormally higher and lower placental weights are associated with increased risk of pregnancy complications [ 31 ]. Further explorations of the placenta, placenta functioning and efficacy and how to quantify these are necessary. However, sample sizes of such studies are currently limited and a MR study to investigate causality was not feasible.

Due to the properties of the MR method, adjusting for covariates is not strictly necessary but can increase precision. However, it is important to only adjust for variables that, one is confident about, act as a confounder to the exposure and the outcome variable or a competing exposure. Therefore, we adjusted all our analysis for offspring sex and the population stratification via principal components. There are various other covariates that we could have adjusted for, like, for example, gestational duration. However, it is possible that gestational duration acts as a mediator for smoking in pregnancy and placental weight rather than a confounder. Adjusting for gestational duration could then induce collider bias. In the supplementary material (SFigure 3 ) we showed in a sensitivity analysis that additionally adjusting the MR analysis for different sets of covariates, which are potential confounders of the relationship between the smoking exposure and placental weight, were consistent with the results in the main paper.

One of the limitations of our study is that the available sample size of mothers who smoke before pregnancy was limited. Hence, this leads to large uncertainties surrounding the magnitude of the effect on placental weight. However, this study comprises two of the biggest mother child birth cohorts available. A second limitation was the inevitable differences in variable measurements between the cohorts. For example, information about the number of cigarettes smoked per day was recorded differently in ALSPAC (categories) and in MoBa (integer values). However, in MoBa, mothers tended to report 5 or 10 cigarettes per day instead of integer values in between, which reduces the differences in this variable between the two cohorts. Additionally, instrumental variable analyses are robust to measurement errors as the expected number of cigarettes smoked is based on the genetic information used for the analysis. There was little heterogeneity between the cohorts, and there was good agreement across various analysis models, which strengthens our results despite measurement differences between the cohorts. Another limitation is that all smoking information from the mothers was self-reported data. The strong public health message on smoking might potentially lead to underreporting of smoking in pregnancy. However, a validation of self-reported smoking was performed in a subset of the MoBa participants and revealed that daily smoking prevalence increased only slightly, from 9 to 11%, when investigating cotinine concentrations, suggesting that self-reported smoking is a valid marker for tobacco exposure in MoBa [ 37 ]. It is also important to recognize that the smoking variables at the end of pregnancy only capture whether the mother smoked at this timepoint but for non-smokers it does not give insight into when in pregnancy the mother stopped smoking.

One of the strengths of our study is the use of rs1051730 which has very robust statistical evidence for association with smoking cessation and smoking quantity. There is also strong biological evidence for this association as rs1051730 is in the nicotine acetylcholine receptor gene cluster CHRNA5-CHRNA3-CHRNB4. Rare variant burden associations have implicated all three of these genes as important in influencing smoking quantity [ 38 ].

Conclusions

In conclusion, we have provided evidence to support a causal effect of continued maternal smoking in pregnancy on increased placental weight. Using the MR approach, our study adds to existing evidence on the relationship between placental weight and maternal smoking, which until now included inconsistent results from observational studies that are more susceptible to bias and confounding by unmeasured variables. Our work supports a mechanism whereby maternal smoking leads to a compensatory increase in placenta weight, but further investigations on maternal smoking, birth weight and placental properties are necessary to better understand mediation effects or other forms of interactions between these three components.

Availability of data and materials

The data in ALSPAC is fully available, via managed systems, to any researchers. The managed system is a requirement of the study funders, but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science.

The ALSPAC data management plan describes in detail the policy regarding data sharing, which is through a system of managed open access. The following steps highlight how to apply for access to the data included in this paper and all other ALSPAC data. (1) Please read the ALSPAC access policy, which describes the process of accessing the data and samples in detail and outlines the costs associated with doing so. (2) You may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011. (3) Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please email [email protected].

Data from the Norwegian Mother, Father and Child Cohort Study and the Medical Birth Registry of Norway used in this study are managed by the national health register holders in Norway (Norwegian Institute of public health) and can be made available to researchers, provided approval from the Regional Committees for Medical and Health Research Ethics (REC), compliance with the EU General Data Protection Regulation (GDPR) and approval from the data owners. The consent given by the participants does not open for storage of data on an individual level in repositories or journals. Researchers who want access to data sets for replication should apply through helsedata.no. Access to data sets requires approval from The Regional Committee for Medical and Health Research Ethics in Norway and an agreement with MoBa.

Abbreviations

Avon Longitudinal Study of Parents and Children

• Birth weight

Confidence interval

Medical Birth Registry of Norway

Norwegian Mother, Father and Child Cohort Study

• Placental weight

Standard deviation

Single nucleotide polymorphism

Cnattingius S. The epidemiology of smoking during pregnancy: Smoking prevalence, maternal characteristics, and pregnancy outcomes. Nicotine Tob Res. 2004;6(SUPPL. 2):S125–40.

Population Health CA and SCTeam, Lead Analyst: Walt Treloar. Statistics on Women’s Smoking Status at Time of Delivery: England, Quarter 3, 2022–23. NHS England, part of the Government Statistical Service. 2023. Available from: https://digital.nhs.uk/data-and-information/publications/statistical/statistics-on-women-s-smoking-status-at-time-of-delivery-england/statistics-on-womens-smoking-status-at-time-of-delivery-england-quarter-3-2022-23 .

Tyrrell J, Huikari V, Christie JT, Cavadino A, Bakker R, Brion MJA, et al. Genetic variation in the 15q25 nicotinic acetylcholine receptor gene cluster (CHRNA5- CHRNA3-CHRNB4) interacts with maternal selfreported smoking status during pregnancy to influence birth weight. Hum Mol Genet. 2012;21(24):5344–58.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Pereira RD, Rietveld CA, van Kippersluis H. The Interplay between Maternal Smoking and Genes in Offspring Birth Weight. J Hum Resour. 2022;1020–11266R2.

Wang X, Zuckerman B, Pearson C, Kaufman G, Chen C, Wang G, et al. Maternal cigarette smoking, metabolic gene polymorphism, and infant birth weight. JAMA. 2002;287(2):195–202.

Article   CAS   PubMed   Google Scholar  

Yang Q, Millard LAC, Davey Smith G. Proxy gene-by-environment Mendelian randomization study confirms a causal effect of maternal smoking on offspring birthweight, but little evidence of long-term influences on offspring health. Int J Epidemiol. 2020;49(4):1207–18.

Article   PubMed   Google Scholar  

Wang N, Tikellis G, Sun C, Pezic A, Wang L, Wells JCK, et al. The effect of maternal prenatal smoking and alcohol consumption on the placenta-to-birth weight ratio. Placenta. 2014;35(7):437–41.

Article   PubMed   PubMed Central   Google Scholar  

Salafia CM, Zhang J, Charles AK, Bresnahan M, Shrout P, Sun W, et al. Placental characteristics and birthweight. Paediatr Perinat Epidemiol. 2008;22(3):229–39.

Heidari Z, Mahmoudzadeh-Sagheb H, Sheibak N. Placenta structural changes in heavy smoking mothers: a stereological aspect. Curr Med Res Opin. 2018;34(11):1893–7.

Jauniaux E, Burton GJ. Morphological and biological effects of maternal exposure to tobacco smoke on the feto-placental unit. Early Hum Dev. 2007;83(11):699–706.

Pintican D, Andreea Poienar A, Strilciuc S, Mihu D. Effects of maternal smoking on human placental vascularization: A systematic review. 2019;58(4):454–9.

Google Scholar  

Holloway AC, Salomon A, Soares MJ, Garnier V, Raha S, Sergent F, et al. Characterization of the adverse effects of nicotine on placental development: in vivo and in vitro studies. Am J Physiol Endocrinol Metab. 2014;306(4):E443–56.

Larsen S, Haavaldsen C, Bjelland EK, Dypvik J, Jukic AM, Eskild A. Placental weight and birthweight: The relations with number of daily cigarettes and smoking cessation in pregnancy. A population study Int J Epidemiol. 2018;47(4):1141–50.

Mitsuda N, N Awn JP, Eitoku M, Maeda N, Fujieda M, Suganuma N, et al. Association between maternal active smoking during pregnancy and placental weight: The Japan environment and Children’s study. Placenta. 2020;94:48–53.

Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Smith GD. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27(8):1133–63.

Freathy RM, Ring SM, Shields B, Galobardes B, Knight B, Weedon MN, et al. A common genetic variant in the 15q24 nicotinic acetylcholine receptor gene cluster (CHRNA5-CHRNA3-CHRNB4) is associated with a reduced ability of women to quit smoking in pregnancy. Hum Mol Genet. 2009;18(15):2922–7.

Furberg H, Kim Y, Dackor J, Boerwinkle E, Franceschini N, Ardissino D, et al. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat Genet. 2010;42(5):441–7.

Article   CAS   Google Scholar  

Liu M, Jiang Y, Wedow R, Li Y, Brazel DM, Chen F, et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet. 2019;51(2):237–44.

Boyd A, Golding J, Macleod J, Lawlor DA, Fraser A, Henderson J, et al. Cohort Profile: The ‘Children of the 90s’—the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol. 2013;42(1):111–27.

Fraser A, Macdonald-wallis C, Tilling K, Boyd A, Golding J, Davey smith G, et al. Cohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int J Epidemiol. 2013;42(1):97–110.

Magnus P, Birke C, Vejrup K, Haugan A, Alsaker E, Daltveit AK, et al. Cohort Profile Update: The Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2016;45(2):382–8.

Helgeland Ø, Vaudel M, Sole-Navais P, Flatley C, Juodakis J, Bacelis J, et al. Characterization of the genetic architecture of infant and early childhood body mass index. Nat Metab. 2022;4(3):344–58.

Solé-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J, et al. Genetic effects on the timing of parturition and links to fetal birth weight. Nat Genet. 2023;55(4):559–67.

Sunde ID, Vekseth C, Rasmussen S, Mahjoob E, Collett K, Ebbing C. Placenta, cord and membranes: a dual center validation study of midwives’ classifications and notifications to the Medical Birth Registry of Norway. Acta Obstet Gynecol Scand. 2017;96(9):1120–7.

Norwegian Institute of Public Health. Medical Birth Registry of Norway. 2024. Available from: https://www.fhi.no/en/ch/medical-birth-registry-of-norway/ . Accessed 18 Jan 2024.

Christians JK, Grynspan D, Greenwood SL, Dilworth MR. The problem with using the birthweight:placental weight ratio as a measure of placental efficiency. Placenta. 2018;1(68):52–8.

Article   Google Scholar  

Stasinopoulos DM, Rigby RA. Generalized additive models for location scale and shape (GAMLSS) in R. J Stat Softw. 2007;23(7):1–46.

Stasinopoulos MD, Rigby RA, Heller GZ, Voudouris V, De Bastiani F. Flexible regression and smoothing: Using GAMLSS in R. Flexible Regression and Smoothing: Using GAMLSS in R; 2017.

Book   Google Scholar  

Staiger D, Stock JH. Instrumental Variables Regression with Weak Instruments. Econometrica. 1997;65(3):557–86.

Zdravkovic T, Genbacev O, McMaster MT, Fisher SJ. The adverse effects of maternal smoking on the human placenta: A review. Placenta. 2005;26(SUPPL.):S81–6.

Siragher E, Sferruzzi-Perri AN. Placental hypoxia: What have we learnt from small animal models? Placenta. 2021;15(113):29–47.

Thompson LP, Pence L, Pinkas G, Song H, Telugu BP. Placental Hypoxia During Early Pregnancy Causes Maternal Hypertension and Placental Insufficiency in the Hypoxic Guinea Pig Model. Biol Reprod. 2016;95(6):1–10.

Matheson H, Veerbeek JHW, Charnock-Jones DS, Burton GJ, Yung HW. Morphological and molecular changes in the murine placenta exposed to normobaric hypoxia throughout pregnancy. J Physiol. 2016;594(5):1371–88.

Nuzzo AM, Camm EJ, Sferruzzi-Perri AN, Ashmore TJ, Yung H wa, Cindrova-Davies T, et al. Placental Adaptation to Early-Onset Hypoxic Pregnancy and Mitochondria-Targeted Antioxidant Therapy in a Rodent Model. Am J Pathol. 2018;188(12):2704–16.

Ganguly E, Aljunaidy MM, Kirschenman R, Spaans F, Morton JS, Phillips TEJ, et al. Sex-Specific Effects of Nanoparticle-Encapsulated MitoQ (nMitoQ) Delivery to the Placenta in a Rat Model of Fetal Hypoxia. Front Physiol. 2019;10:458308.

McNamara H, Hutcheon JA, Platt RW, Benjamin A, Kramer MS. Risk factors for high and low placental weight. Paediatr Perinat Epidemiol. 2014;28(2):97–105.

Kvalvik LG, Nilsen RM, Skjærven R, Vollset SE, Midttun Ø, Ueland PM, et al. Self-reported smoking status and plasma cotinine concentrations among pregnant women in the Norwegian Mother and Child Cohort Study. Pediatr Res. 2012;72(1):101–7.

Rajagopal VM, Watanabe K, Mbatchou J, Ayer A, Quon P, Sharma D, et al. Rare coding variants in CHRNB2 reduce the likelihood of smoking. Nat Genet. 2023;55(7):1138–48.

Download references

Acknowledgements

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses.

The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study.

We thank the Norwegian Institute of Public Health (NIPH) for generating high-quality genomic data. This research is part of the HARVEST collaboration, supported by the Research Council of Norway (#229624). We also thank the NORMENT Centre for providing genotype data, funded by the Research Council of Norway (#223273), South East Norway Health Authorities and Stiftelsen Kristian Gerhard Jebsen. We further thank the Center for Diabetes Research, the University of Bergen for providing genotype data and performing quality control and imputation of the data funded by the ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, the Research Council of Norway, the Novo Nordisk Foundation, the University of Bergen, and the Western Norway Health Authorities.

Supported by grants from the European Research Council (AdG #293574), the Bergen Research Foundation (“Utilizing the Mother and Child Cohort and the Medical Birth Registry for Better Health”), Stiftelsen Kristian Gerhard Jebsen (Translational Medical Center), the University of Bergen, the Research Council of Norway (FRIPRO grant #240413), the Western Norway Regional Health Authority (Strategic Fund “Personalized Medicine for Children and Adults”), the Novo Nordisk Foundation (grant #54741), and the Norwegian Diabetes Association; and (to S.J.) Helse Vest’s Open Research Grant (grant #912250), the Research Council of Norway (FRIPRO grant #315599), and Novo Nordisk Foundation (grant #NNF21OC0070349). This work was partly supported by the Research Council of Norway through its Centres of Excellence funding scheme (#262700), Better Health by Harvesting Biobanks (#229624) and The Swedish Research Council, Stockholm, Sweden (2015-02559), The Research Council of Norway, Oslo, Norway (FRIMEDBIO #547711), March of Dimes (#21-FY16-121). The Norwegian Mother, Father, and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, NIH/NIEHS (contract no N01-ES-75558), NIH/NINDS (grant no.1 UO1 NS 047537-01 and grant no.2 UO1 NS 047537-06A1).

Analyses were performed using digital laboratories in HUNT Cloud at the Norwegian University of Science and Technology, Trondheim, Norway. We are grateful for outstanding support from the HUNT Cloud community.

The authors would like to acknowledge the use of the University of Exeter High-Performance Computing (HPC) facility in carrying out this work.

The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and A.J. and R.M.F. will serve as guarantors for the contents of this paper.

Genotyping of the ALSPAC maternal samples were funded by the Wellcome Trust (WT088806). Specific funds for recent detailed data collection on the mothers were obtained from the US National Institutes of Health (R01 DK077659) and Wellcome Trust (WT087997MA) for completion of selected items of obstetric data extraction, including placental weights. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ).

A.J. received funding for her PhD studentship from the Faculty of Health and Life Sciences at the University of Exeter.

P.R.N. was supported by grants from the European Research Council (AdG #293,574), Trond Mohn Foundation (Mohn Center for Diabetes Precision Medicine), the Research Council of Norway (#240,413), the Western Norway Regional Health Authority (Strategic Fund), the Novo Nordisk Foundation (#NNF54741).

K.T.A. gratefully acknowledges the financial support of the EPSRC via grant EP/T017856/1.

S.J. was supported by Helse Vest’s Open Research Grant (grants #912,250 and F-12144), the Novo Nordisk Foundation (NNF20OC0063872) and the Research Council of Norway (grant #315,599).

M.V. acknowledges the support of the Research Council of Norway (project #301,178).

R.M.F. is supported by a Wellcome Senior Research Fellowship (WT220390)and is also supported by a grant from the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Number R01HD101669.

This project utilised high-performance computing funded by the UK Medical Research Council (MRC) Clinical Research Infrastructure Initiative (award number MR/M008924/1).

This study was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

This research was funded in part, by the Wellcome Trust (Grant number: WT220390). For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

Author information

Authors and affiliations.

Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK

Annika Jaitner, Jack Bowden & Rachel M. Freathy

Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway

Marc Vaudel, Pål R. Njølstad & Stefan Johansson

Department of Genetics and Bioinformatics, Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway

Marc Vaudel & Bo Jacobsson

Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway

Marc Vaudel

Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK

Krasimira Tsaneva-Atanasova

EPSRC Hub for Quantitative Modelling in Healthcare University of Exeter, Exeter, UK

Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway

Pål R. Njølstad

Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Bo Jacobsson

Department of Obstetrics and Gynecology, Sahlgrenska University Hospital, Gothenburg, Gothenburg, Sweden

Novo Nordisk Genetics Centre of Excellence, Oxford, UK

Jack Bowden

Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway

Stefan Johansson

You can also search for this author in PubMed   Google Scholar

Contributions

A.J., R.M.F., J.B. and K.T.A, contributed to the study design. A.J. performed the analyses in this study and drafted the manuscript. Data interpretation and statistical analysis were aided by J.B. and K.T.A.. Biological and clinical interpretation were supported by R.M.F., S.J. and B.J.. P.R.N., S.J. and M.V. contributed to the collection of and management of the MoBa cohort data. For the analysis in the MoBa dataset A.J. was supported by M.V. and S.J. All authors reviewed and edited previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Rachel M. Freathy .

Ethics declarations

Ethics approval and consent to participate.

The establishment of MoBa and initial data collection was based on a licence from the Norwegian Data Protection Agency and approval from The Regional Committees for Medical and Health Research Ethics. The MoBa cohort is currently regulated by the Norwegian Health Registry Act. The current study was approved by the Regional Committees for Medical and Health Research Ethics (no. 2012/67).

Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

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

Supplementary Information

Supplementary material 1., rights and permissions.

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

Reprints and permissions

About this article

Cite this article.

Jaitner, A., Vaudel, M., Tsaneva-Atanasova, K. et al. Smoking during pregnancy and its effect on placental weight: a Mendelian randomization study. BMC Pregnancy Childbirth 24 , 238 (2024). https://doi.org/10.1186/s12884-024-06431-0

Download citation

Received : 27 October 2023

Accepted : 17 March 2024

Published : 04 April 2024

DOI : https://doi.org/10.1186/s12884-024-06431-0

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

BMC Pregnancy and Childbirth

ISSN: 1471-2393

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

Nicotine Research Program

Tobacco and pregnancy.

Women who smoke or are around smokers while pregnant expose their unborn children to a number of diseases and health risks.

According to the Centers for Disease Control and Prevention , SmokefreeWomen , American Cancer Society , and American Lung Association:

• Low birth weight and premature delivery. It is estimated that smoking in women during pregnancy causes low birth weight in at least 1 in 5 infants and increases the risk of having a baby too early. Approximately 14 percent of premature deliveries and 1 in 10 infant deaths are attributed to mothers who smoke.
• Secondhand smoke consequences. Secondhand smoke can cause seemingly healthy, full-term babies to have narrowed airways and reduced lung function. Secondhand smoke can also lead to an increased risk of diseases, including severe asthma, ear infections, colds, pneumonia and bronchitis.
• Higher mortality rates. Smoking during pregnancy increases an infant's risk of sudden infant death syndrome.

More about research at Mayo Clinic

• Research Faculty
• Laboratories
• Core Facilities
• Centers & Programs
• Departments & Divisions
• Clinical Trials
• Institutional Review Board
• Postdoctoral Fellowships
• Training Grant Programs
• Publications

Mayo Clinic Footer

• Request Appointment
• About Mayo Clinic
• About This Site

Legal Conditions and Terms

• Terms and Conditions
• Privacy Policy
• Notice of Privacy Practices
• Notice of Nondiscrimination
• Manage Cookies

Advertising

Mayo Clinic is a nonprofit organization and proceeds from Web advertising help support our mission. Mayo Clinic does not endorse any of the third party products and services advertised.

• Advertising and sponsorship policy
• Advertising and sponsorship opportunities

Reprint Permissions

A single copy of these materials may be reprinted for noncommercial personal use only. "Mayo," "Mayo Clinic," "MayoClinic.org," "Mayo Clinic Healthy Living," and the triple-shield Mayo Clinic logo are trademarks of Mayo Foundation for Medical Education and Research.

Smoking, Pregnancy, and Babies

Most people know that smoking causes cancer and other major health problems. And smoking while you’re pregnant can cause serious problems, too. Your baby could be born too early, have a birth defect, or die from sudden infant death syndrome (SIDS). Even being around cigarette smoke can cause health problems for you and your baby. 1

It’s best to quit smoking before you get pregnant. But if you’re already pregnant, quitting can still help protect you and your baby from health problems. It’s never too late to quit smoking. 2

If you smoked and had a healthy pregnancy in the past, there’s no guarantee that your next pregnancy will be healthy. When you smoke during pregnancy, you put your health and your baby’s health at risk. 3

Smoking can cause fertility problems for you or your partner. Women who smoke have more trouble getting pregnant than women who don’t smoke. In men, smoking can damage sperm and contribute to impotence (erectile dysfunction, or ED). Both problems can make it harder for a man to father a baby when he and his partner are ready. 3 ,  4

• Your baby may be born too small, even after a full-term pregnancy. Smoking slows your baby’s growth before birth.
• Your baby may be born too early (premature birth). Premature babies often have health problems. 5
• Smoking can damage your baby’s developing lungs and brain. The damage can last through childhood and into the teen years. 4
• Smoking doubles your risk of abnormal bleeding during pregnancy and delivery. This can put both you and your baby in danger. 5
• Smoking raises your baby’s risk for birth defects, including cleft lip, cleft palate, or both. A cleft is an opening in your baby’s lip or in the roof of her mouth (palate). He or she can have trouble eating properly and is likely to need surgery. 1 , 4
• Babies of moms who smoke during pregnancy—and babies exposed to cigarette smoke after birth—have a higher risk for SIDS. 1

If you smoke during pregnancy, you are more likely to give birth too early . A baby born 3 weeks or more before your due date is premature. 5  Babies born too early miss important growth that happens in the womb during the final weeks and months of pregnancy. 6

The earlier a baby is born, the greater the chances for serious health problems or death. Premature babies can have: 6 , 7 , 8

• Low birth weight
• Feeding difficulties
• Breathing problems right away
• Breathing problems that last into childhood
• Cerebral palsy (brain damage that causes trouble with movement and muscle tone)
• Developmental delays (when a baby or child is behind in language, thinking, or movement skills)
• Problems with hearing or eyesight

Premature babies may need to stay at the hospital for days, weeks, or even months. 5

• Outlook for Mother and Baby
• How Does Smoking Affect Fertility?
• How Can Smoking Harm You and Your Baby?
• How Can a Premature Birth Harm Your Baby?
• How Can Quitting Help You and Your Baby?
• Support for Quitting During Pregnancy
• Stay Smokefree for a Healthy Child
• 1-800-QUIT-NOW
• 1-855-DÉJELO-YA (Español)
• 1-800-838-8917 (中文)
• 1-800-556-5564 (한국어)
• 1-800-778-8440 (Tiếng Việt)
• Text QUITNOW to 333888 —Message and data rates may apply
• quitSTART app external icon
• Quit Smoking ( En Español )
• Smokefree.gov external icon ( En Español )
• Asian Smokers’ Quitline external icon

Amanda B. smoked while she was pregnant. Her baby was born 2 months early and was kept in an incubator.

“I’ll never forget her tiny, little cry. It wasn’t like the cries you hear; you know—a loud, screaming, typical baby cry. It was just this soft, little cry.”

The best time to quit smoking is before you get pregnant, but quitting at any time during pregnancy can help your baby get a better start on life. Talk to your doctor about the best ways to quit while you’re pregnant or trying to get pregnant.

When you stop smoking: 1

• Your baby gets more oxygen, even after just 1 day.
• Your baby will grow better.
• Your baby is less likely to be born too early.
• You’ll have more energy and breathe more easily.
• You will be less likely to develop heart disease, stroke, lung cancer, lung disease, and other smoking-related diseases.

Most pregnant women who smoke want to quit, but quitting isn’t always easy during pregnancy. What’s more, if you’re pregnant and still smoking, you may feel ashamed and alone.

The right kind of support can help a pregnant woman get through the unique challenges of quitting during this phase of life. Special guidance is available for you and the people around you. These resources include:

• Help Her Quit Smoking
• Pregnancy, Motherhood, and Smoking
• Smokefree Women

Quitting Smoking Protects Your Health and the Health of Your Baby

Quitting smoking to protect the health of you and your baby is one of the most important things you can do. If you are pregnant or planning to get pregnant, talk to your doctor or call 1-800-QUIT-NOW to get started.

Staying smokefree is important. Tobacco smoke contains a deadly mix of more than 7,000 chemicals. 9 When your child is not exposed to smoke, you can expect him or her to have: 10

• Fewer coughs and chest colds
• A lower risk for bronchitis or pneumonia (lung problems)
• Fewer ear infections
• Fewer asthma attacks and wheezing problems
• Centers for Disease Control and Prevention. Substance Use During Pregnancy [last updated 2022 May 23; accessed 2023 Mar 6].
• Centers for Disease Control and Prevention. Pregnant? Don’t Smoke!  [last updated 2017 Nov 13; accessed 2018 Mar 22].
• National Cancer Institute. Smoking & Your Baby  [accessed 2023 Mar 6].
• U.S. Department of Health and Human Services. Let’s Make the Next Generation Tobacco-Free: Your Guide to the 50th Anniversary Surgeon General’s Report on Smoking and Health. [PDF – 795KB] Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2014 [accessed 2018 Mar 22].
• National Cancer Institute. Quit While Pregnant [accessed 2023 Mar 6].
• Centers for Disease Control and Prevention. Preterm Birth [last updated 2017 Nov 27; accessed 2018 Mar 22].
• Been JV, Lugtenberg MJ, Smets E, van Schayck CP, Kramer BW, Mommers M, Sheikh A. Preterm Birth and Childhood Wheezing Disorders: A Systematic Review and Meta-Analysis. PLOS Medicine 2014 Jan 28.  DOI: 10.1371/journal.pmed.1001596 [accessed 2018 Mar 22].
• Harju M, Keski-Nisula L, Georgiadis L, Räisänen S, Gissler M, Heinonen S. The Burden of Childhood Asthma and Late Preterm and Early Term Births. The Journal of Pediatrics 2014;164(2):295–9 [accessed 2018 Mar 22].
• U.S. Department of Health and Human Services. A Report of the Surgeon General. How Tobacco Smoke Causes Disease: What It Means to You.  Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2010 [accessed 2018 Mar 22].
• National Cancer Institute. Smoking & Your Baby [last updated 2019 Jan 28; accessed 2019 Jan 25].

To receive email updates about this page, enter your email address:

• Smoking & Tobacco Use
• Smokefree.gov external icon
• National Cancer Institute external icon

Exit Notification / Disclaimer Policy

• The Centers for Disease Control and Prevention (CDC) cannot attest to the accuracy of a non-federal website.
• Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website.
• You will be subject to the destination website's privacy policy when you follow the link.
• CDC is not responsible for Section 508 compliance (accessibility) on other federal or private website.

• Download PDF
• Share X Facebook Email LinkedIn
• Permissions

Vitamin C Supplementation Among Pregnant Smokers and Airway Function Trajectory in Offspring : A Secondary Analysis of a Randomized Clinical Trial

• 1 Department of Pediatrics and Pape Pediatric Research Institute, Oregon Health & Science University, Portland
• 2 Division of Neuroscience, Oregon National Primate Research Center, Beaverton
• 3 Oregon Health & Science University–Portland State University School of Public Health and Knight Cancer Institute, Portland
• 4 Oregon Clinical & Translational Research Institute, Oregon Health & Science University, Portland
• 5 Department of Pediatrics, Well Center for Research, Indiana University School of Medicine, Indianapolis

In a randomized clinical trial (RCT), McEvoy et al 1 , 2 demonstrated that vitamin C supplementation among women who smoked during pregnancy significantly increased their offspring’s forced expiratory flows (FEFs) at 3 and 12 months of age (the VCSIP [Vitamin C to Decrease Effects of Smoking in Pregnancy on Infant Lung Function] trial). A longitudinal follow-up study 3 demonstrated that, at 60 months of age, the offspring continued to have significantly higher FEFs between 25% and 75% expired volume (FEF 25%-75% ) and a significantly lower wheeze occurrence.

Read More About

McEvoy CT , Shorey-Kendrick LE , MacDonald KD, et al. Vitamin C Supplementation Among Pregnant Smokers and Airway Function Trajectory in Offspring : A Secondary Analysis of a Randomized Clinical Trial . JAMA Pediatr. Published online April 08, 2024. doi:10.1001/jamapediatrics.2024.0430

Manage citations:

© 2024

Artificial Intelligence Resource Center

Pediatrics in JAMA : Read the Latest

Browse and subscribe to JAMA Network podcasts!

Others Also Liked

Select your interests.

Customize your JAMA Network experience by selecting one or more topics from the list below.

• Academic Medicine
• Acid Base, Electrolytes, Fluids
• Allergy and Clinical Immunology
• American Indian or Alaska Natives
• Anesthesiology
• Anticoagulation
• Art and Images in Psychiatry
• Artificial Intelligence
• Assisted Reproduction
• Bleeding and Transfusion
• Caring for the Critically Ill Patient
• Challenges in Clinical Electrocardiography
• Climate and Health
• Climate Change
• Clinical Challenge
• Clinical Decision Support
• Clinical Implications of Basic Neuroscience
• Clinical Pharmacy and Pharmacology
• Complementary and Alternative Medicine
• Consensus Statements
• Coronavirus (COVID-19)
• Critical Care Medicine
• Cultural Competency
• Dental Medicine
• Dermatology
• Diabetes and Endocrinology
• Diagnostic Test Interpretation
• Drug Development
• Electronic Health Records
• Emergency Medicine
• End of Life, Hospice, Palliative Care
• Environmental Health
• Equity, Diversity, and Inclusion
• Facial Plastic Surgery
• Gastroenterology and Hepatology
• Genetics and Genomics
• Genomics and Precision Health
• Global Health
• Guide to Statistics and Methods
• Hair Disorders
• Health Care Delivery Models
• Health Care Economics, Insurance, Payment
• Health Care Quality
• Health Care Reform
• Health Care Safety
• Health Care Workforce
• Health Disparities
• Health Inequities
• Health Policy
• Health Systems Science
• History of Medicine
• Hypertension
• Images in Neurology
• Implementation Science
• Infectious Diseases
• Innovations in Health Care Delivery
• JAMA Infographic
• Law and Medicine
• Leading Change
• Less is More
• LGBTQIA Medicine
• Lifestyle Behaviors
• Medical Coding
• Medical Devices and Equipment
• Medical Education
• Medical Education and Training
• Medical Journals and Publishing
• Mobile Health and Telemedicine
• Narrative Medicine
• Neuroscience and Psychiatry
• Notable Notes
• Nutrition, Obesity, Exercise
• Obstetrics and Gynecology
• Occupational Health
• Ophthalmology
• Orthopedics
• Otolaryngology
• Pain Medicine
• Palliative Care
• Pathology and Laboratory Medicine
• Patient Care
• Patient Information
• Performance Improvement
• Performance Measures
• Perioperative Care and Consultation
• Pharmacoeconomics
• Pharmacoepidemiology
• Pharmacogenetics
• Pharmacy and Clinical Pharmacology
• Physical Medicine and Rehabilitation
• Physical Therapy
• Physician Leadership
• Population Health
• Primary Care
• Professional Well-being
• Professionalism
• Psychiatry and Behavioral Health
• Public Health
• Pulmonary Medicine
• Regulatory Agencies
• Reproductive Health
• Research, Methods, Statistics
• Resuscitation
• Rheumatology
• Risk Management
• Scientific Discovery and the Future of Medicine
• Shared Decision Making and Communication
• Sleep Medicine
• Sports Medicine
• Stem Cell Transplantation
• Substance Use and Addiction Medicine
• Surgical Innovation
• Surgical Pearls
• Teachable Moment
• Technology and Finance
• The Art of JAMA
• The Arts and Medicine
• The Rational Clinical Examination
• Tobacco and e-Cigarettes
• Translational Medicine
• Trauma and Injury
• Treatment Adherence
• Ultrasonography
• Users' Guide to the Medical Literature
• Vaccination
• Venous Thromboembolism
• Veterans Health
• Women's Health
• Workflow and Process
• Wound Care, Infection, Healing
• Register for email alerts with links to free full-text articles
• Access PDFs of free articles
• Manage your interests
• Save searches and receive search alerts

• Alzheimer's disease & dementia
• Arthritis & Rheumatism
• Attention deficit disorders
• Autism spectrum disorders
• Biomedical technology
• Diseases, Conditions, Syndromes
• Endocrinology & Metabolism
• Gastroenterology
• Gerontology & Geriatrics
• Health informatics
• Inflammatory disorders
• Medical economics
• Medical research
• Medications
• Neuroscience
• Obstetrics & gynaecology
• Oncology & Cancer
• Ophthalmology
• Overweight & Obesity
• Parkinson's & Movement disorders
• Psychology & Psychiatry
• Radiology & Imaging
• Sleep disorders
• Sports medicine & Kinesiology
• Vaccination
• Breast cancer
• Cardiovascular disease
• Chronic obstructive pulmonary disease
• Colon cancer
• Coronary artery disease
• Heart attack
• Heart disease
• High blood pressure
• Kidney disease
• Lung cancer
• Multiple sclerosis
• Myocardial infarction
• Ovarian cancer
• Post traumatic stress disorder
• Rheumatoid arthritis
• Schizophrenia
• Skin cancer
• Type 2 diabetes
• Full List »

share this!

April 22, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

trusted source

Active military service may heighten women's risk of having low birthweight babies

by British Medical Journal

Active military service may heighten a woman's risk of having a low birthweight baby, suggests a review of the available scientific evidence published online in the journal BMJ Military Health .

The findings highlight the need for more research specifically focused on women in the armed forces, and their reproductive health in particular, conclude the study authors.

Worldwide, increasing numbers of women are on active service in their country's armed forces. The UK Armed Forces, for example, has set a target of 30% female representation by 2030. And more and more countries are deploying women in combat units, and in other challenging environments, such as submarines, note the study authors.

Mounting evidence suggests that stress experienced during pregnancy is associated with birth complications, such as preterm delivery and low birthweight. And a military career and lifestyle expose service personnel to a wide range of physical, mental, and environmental stressors that could potentially influence pregnancy outcomes.

The study authors therefore wanted to explore the potential impact of active military service on the risks of preterm labor and birth, low birthweight, and stillbirth.

They scoured research databases for relevant studies, and included 21 that met all the eligibility criteria in their analysis. The studies, which involved 650,628 women serving in the US military, were all published between 1979 and 2023.

Ten of the studies included a comparison group—usually the wives of active service personnel. By way of a proxy for those that didn't include a comparator, the study authors drew on national data from the US National Vital Statistics for any given year.

Analysis of the study results indicated no heightened risk of preterm birth among pregnant active service women. But there were significant methodological differences; most studies had a moderate to high risk of bias; and several included only small sample sizes, caution the study authors.

There was no observed association between branch of military service and increased risk of preterm birth, although again this should be interpreted cautiously as 5 studies included mixed service samples and the study design varied considerably, say the study authors.

There was no clear evidence for an increased risk of stillbirth among women on active military service, either.

But nearly two thirds (62.5%) of the studies concluded that women on active service may be at heightened risk of having a low birthweight baby, including one study with the lowest risk of bias. And 4 of the 5 studies that included a comparison group also indicated an increased risk of low birthweight.

Seven of the 8 studies reporting on low birthweight were carried out in single-service settings. Both of those from the US Air Force suggested a higher prevalence of low birthweight babies born to active duty military personnel.

But some 53% and 38% of the studies reporting on preterm birth and low birthweight , respectively, didn't have a matched comparison group and relied on a proxy drawn from national statistical data.

This introduces a risk of systematic error as the baseline characteristics of the two groups are inherently different, caution the study authors.

Women on active military service will also be medically screened before any tours of duty and will have fewer co-existing conditions, while national data will include high risk and multiple pregnancies, they explain.

Only observational studies were included in the review, and the data collection methods and/or adjustment for influential factors varied, acknowledge the study authors. Only 8 studies reported on smoking status despite a high prevalence of smoking in the military and the fact that smoking is associated with several health issues before and during pregnancy.

The data also focused exclusively on the US military, which, although unsurprising given that it is one of the largest in the world, does limit the generalizability of the findings to armed forces personnel elsewhere, say the study authors.

Nevertheless, they conclude, "This review highlights a need for more female-specific research in armed forces, beyond the US military setting, to inform military maternity pathways and policies in ways that safeguard mothers and their babies while enhancing military readiness."

Explore further

Feedback to editors

Gene linked to epilepsy and autism decoded in new study

7 hours ago

Blood test finds knee osteoarthritis up to eight years before it appears on X-rays

Researchers find pregnancy cytokine levels impact fetal brain development and offspring behavior

Study finds biomarkers for psychiatric symptoms in patients with rare genetic condition 22q

8 hours ago

Clinical trial evaluates azithromycin for preventing chronic lung disease in premature babies

9 hours ago

Scientists report that new gene therapy slows down amyotrophic lateral sclerosis disease progression

Using stem cell-derived heart muscle cells to advance heart regenerative therapy

Analysis identifies 50 new genomic regions associated with kidney cancer risk

10 hours ago

Illusion demystifies the way vision works: Experiments imply brightness perception occurs deeper in brain than thought

How buildings influence the microbiome and human health

Related stories.

Skin cancer risk higher in military personnel

Jul 8, 2018

Fewer births on weekends and holidays than weekdays, data analysis of births from 1979–2018 in Japan shows

Feb 14, 2024

Living in a 'war zone' linked to delivery of low birthweight babies

Nov 28, 2017

PTSD and harmful drinking in the UK Armed Forces and UK Police Service

Mar 31, 2021

Birthweight and early pregnancy body mass index may risk pregnancy complications

Dec 19, 2018

Cannabis use during pregnancy associated with adverse birth outcomes

Nov 16, 2023

Recommended for you

Opioids during pregnancy not linked to substantially increased risk of psychiatric disorders in children

Apr 24, 2024

Follow-up finds landmark steroid study remains safe 50 years on

Apr 23, 2024

Accelerated aging biology in the placenta found to contribute to a rare form of pregnancy-related heart failure

Apr 17, 2024

Women who experience major complications during pregnancy found to have increased risk of early death years later

Apr 16, 2024

New study focuses on the placenta for clues to the development of gestational diabetes

Let us know if there is a problem with our content.

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Medical Xpress in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

Pregnant and postnatal women's experiences of interacting with health care providers about their tobacco smoking: a qualitative systematic review

Affiliations.

• 1 Faculty of Nursing, Memorial University, St. John's, NL, Canada.
• 2 Memorial University Faculty of Nursing Collaboration for Evidence-Based Nursing and Primary Health Care: A JBI Affiliated Group, St. John's, NL, Canada.
• 3 Health Sciences Library, Memorial University, St. John's, NL, Canada.
• PMID: 36477572
• DOI: 10.11124/JBIES-22-00052

Objective: The objective of this review was twofold: i) to comprehensively identify the best available evidence about the experiences of women who smoked tobacco during pregnancy or postnatally (or both) concerning health care providers' interactions with them about their smoking, when such interactions occurred during contact for prenatal or postnatal health care in any health care setting; and ii) to synthesize the research findings for recommendations to strengthen health care providers' interventions regarding smoking during pregnancy and smoking during the postnatal period.

Introduction: Maternal tobacco smoking during pregnancy and maternal tobacco smoking postnatally pose serious health risks for the woman, fetus, and offspring, whereas maternal smoking cessation has beneficial health effects. Given the importance of health care providers' interactions with pregnant and postnatal women for smoking cessation care, it is essential to understand women's experiences of such interactions.

Inclusion criteria: Studies considered for this review had qualitative research findings about the experiences of women who smoked tobacco during pregnancy or postnatally (or both) in relation to health care providers' interactions with them about their smoking.

Methods: The review was conducted using the JBI approach to qualitative systematic reviews. Published studies were sought through 6 academic databases (eg, CINAHL, MEDLINE). Unpublished studies were searched in 6 gray literature sources (eg, ProQuest Dissertations and Theses, Google Scholar). Reference lists of retrieved records were also searched. The searches occurred in October and November 2020; no country, language, or date limits were applied. Study selection involved title and abstract screening, full-text examination, and critical appraisal of all studies that met the inclusion criteria for the review. Study characteristics and research findings were extracted from the included studies. Study selection and extraction of findings were conducted by 2 reviewers independently; differences between reviewers were resolved through consensus. The research findings were categorized, and the categories were aggregated into a set of synthesized findings. The synthesized findings were assigned confidence scores. The categories and finalized synthesized findings were agreed upon by all reviewers.

Results: The 57 included studies varied in qualitative research designs and in methodological quality (from mostly low to high). There were approximately 1092 eligible participants, and 250 credible and unequivocal research findings. The research findings yielded 14 categories and 6 synthesized findings with low to very low confidence scores. Some women who smoked tobacco during pregnancy and some women who smoked tobacco postnatally lacked supportive interactions by health care providers regarding their smoking; other women experienced supportive interactions by health care providers. Women were adversely impacted when health care providers' interactions lacked supportiveness, and were beneficially impacted when interactions were supportive. Women varied in openness to health care providers' interactions regarding their smoking, from not being receptive to being accepting, and some women wanted meaningful health care provider interactions.

Conclusions: Although confidence in the synthesized findings is low to very low, the evidence indicates that supportive health care provider interactions may facilitate positive smoking behavior change in pregnancy and postnatally. It is recommended that health care providers implement accepted clinical practice guidelines with women who smoke prenatally or postnatally, using an approach that is person-centered, emotionally supportive, engaging (eg, understanding), and non-authoritarian.

Systematic review registration number: PROSPERO CRD42020178866.

Copyright © 2022 JBI.

Publication types

• Systematic Review
• Research Support, Non-U.S. Gov't
• Delivery of Health Care*
• Health Personnel*
• Qualitative Research
• Tobacco Smoking

An official website of the United States government

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

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

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Elsevier Sponsored Documents

Smoking and vaping patterns during pregnancy and the postpartum: A longitudinal UK cohort survey

Katharine bowker.

a Division of Primary Care Research and UK Centre for Tobacco and Alcohol Studies, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK

Sarah Lewis

b Division of Epidemiology and Public Health and UK Centre for Tobacco and Alcohol Studies, University of Nottingham, Clinical Sciences Building 2, Nottingham City Hospital Hucknall Road, Nottingham NG5 1PB, UK

Michael Ussher

c Population Health Research Institute, St George's, University of London, London SW17 0RE, UK

d Institute for Social Marketing and Health, University of Stirling, Stirling FK9 4LA, UK

Felix Naughton

e University of East Anglia, Faculty of Medicine and Health Sciences, Edith Cavell Building, Norwich NR4 7TJ, UK

Lucy Phillips

Tim coleman, sophie orton, hayden mcrobbie.

f National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW 2031, Australia

Linda Bauld

g Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, EH16 4UX, UK

Associated Data

• • Between 16% and 23% of pregnant smokers and ex-smokers vape during pregnancy.
• • Most pregnant vapers also continue to smoke (dual use).
• • Vaping habits of exclusive vapers is stable during pregnancy and the postpartum.
• • A third of dual users in early pregnancy are exclusively smoking in the postpartum.

Introduction

There is limited information about longitudinal patterns of vaping during pregnancy and the postpartum. We describe the prevalence, frequency, and reasons for vaping throughout pregnancy and postpartum. We also describe temporal patterns in pregnant women’s vaping.

A longitudinal cohort study across England and Scotland, with questionnaires in early pregnancy (8–24 weeks gestation), late pregnancy (34–38 weeks) and 3 months postpartum. A total of 750 women, aged 16 years or over, who were either current smokers, vapers or had smoked in the 3 months before pregnancy, were recruited between June and November 2017.

Vaping prevalence was 15.9% (n = 119/750) in early pregnancy: 12.4% (n = 93/750) were dual users and 3.5% (n = 26/750) exclusive vapers. Late pregnancy vaping prevalence was 17.8% (n = 68/383): 12.5% (n = 48/383) were dual users and 5.2% (n = 20/383) exclusive vapers. Postpartum vaping prevalence was 23.1% (n = 95/411): 14.6% (n = 60/411) were dual users and 8.5% (n = 35/411) exclusive vapers. The most frequently reported reason to vape among all vapers was to quit smoking. A total of 316 women completed all three surveys: 2.6% (n = 8/316) were exclusive vapers in early pregnancy with most remaining exclusive vapers postpartum (n = 6/8, 75%). Of the 11.5% (n = 35/316) dual users in early pregnancy, 31.4% (n = 11/35) were exclusive smokers by the postpartum.

Vaping prevalence was between 15.9% and 23.1% during pregnancy and the postpartum period, and the majority were dual users. Vaping habits of exclusive vapers remains stable throughout pregnancy and the postpartum. However, the vaping habits of dual users varies, with a third exclusively smoking in the postpartum.

1. Background

Smoking in pregnancy has adverse health consequences for the woman and baby ( Clifford et al., 2012 , Cnattingius, 2004 , Delpisheh et al., 2007 , Gluckman et al., 2008 ); efforts to eliminate smoking is a public health priority. In England, 10.4% of women self-report smoking at delivery (NHS Digital, 2019 ) and rates are higher among younger and more deprived women ( Health and Social Care Information Centre, 2015 , McAndrew et al., 2012 ). Up to half of women report quitting smoking either just before or around the time of finding out they are pregnant ( Orton et al., 2014 , Pickett et al., 2003 ); however, up to 60% of these may relapse in the postpartum( Colman and Joyce, 2003 , Cooper et al., 2017 , Jones et al., 2016 ). Exposure to second-hand smoke from postpartum smoking will increase the infant’s risk of sudden infant death, respiratory and ear infections, and asthma ( Pugmire, Sweeting, & Moore, 2017 ). In addition, children of women who smoke cigarettes are more likely to initiate smoking themselves ( Leonardi-Bee, Jere, & Britton, 2011 ).

Electronic cigarette (e-cigarette/vaping) prevalence in England in 2019 was between 5 and 7% for non-pregnant adults (Ann McNeill, Brose, Calder, Bauld, & Robson, 2020 ). Vaping appears to be an effective aid to assist non-pregnant smokers to quit smoking ( Hajek et al., 2019 , Hartmann-Boyce et al., 2020 ). Although not risk free, e-cigarettes, unlike cigarettes, do not release products of combustion (A McNeill et al., 2015 ). Compared to smoking, vaping exposes non-pregnant adults to lower levels of carcinogens and toxins ( Caponnetto et al., 2018 , Shahab et al., 2017 ). Vapers who quit smoking (exclusive vapers) have lower toxicant exposure compared to dual users (those who smoke and vape) ( Goniewicz et al., 2018 ). Exposure to second-hand e-cigarette vapour may also pose less risk than exposure to second-hand cigarette smoke ( Hess, Lachireddy, & Capon, 2016 ). The Royal College of Physicians concluded vaping is unlikely to exceed 5% of the harm from smoking ( Royal College of Physicians, 2016 ). There are limited data on the safety of vaping during pregnancy on the woman or baby ( Cardenas et al., 2019 , Froggatt et al., 2020 , Gillen and Saltzman, 2014 , McDonnell et al., 2020 ). However, it is unlikely that findings regarding vaping safety among non-pregnant populations would be different from pregnant women. There is currently no evidence about the effectiveness of vaping for helping women to stop smoking during pregnancy. Current advice for clinicians caring for pregnant women in the UK supports vaping in order to avoid smoking ( Smoking in Pregnancy Challenge Group, 2019 ).

Cross sectional data on vaping during pregnancy show that prevalence is between 0.6 and 15% ( Bowker et al., 2021 , Kapaya et al., 2019 , Kurti et al., 2017 , Liu et al., 2019 , Mark et al., 2015 , Obisesan et al., 2020 , Rollins et al., 2020 ), and that most pregnant vapers also smoke (dual use) ( Bowker et al., 2021 , Kapaya et al., 2019 , Liu et al., 2019 ). Such variation in prevalence figures may be influenced by different methods of data collection, recall periods, whether women were asked about use before or at differing timepoints during pregnancy, and variation between countries. There is limited understanding about longitudinal patterns of vaping throughout pregnancy. If e-cigarettes are shown to be less harmful in pregnancy than smoking, they could be a useful tool to help women who cannot quit smoking completely using traditional methods. Finding out why and when pregnant women vape and how this relates to smoking status would help us to understand the context around vaping during pregnancy.

In this longitudinal cohort study, we describe the prevalence, frequency and reasons for vaping throughout pregnancy and the postpartum. We also describe temporal patterns in individuals’ smoking and vaping during pregnancy and postpartum. We describe whether exposure remains stable or varies and how this relates to smoking status. Understanding why women are vaping could help us understand women’s perceptions about the role of e-cigarettes for smoking cessation and whether views vary throughout pregnancy and the postpartum.

2.1. Study design

A longitudinal cohort study was undertaken; eligible women were 16 years old or over (no upper age limit), 8–24 weeks pregnant and either recent ex-smokers (smoked during the 3 months immediately prior to finding out they were pregnant), current smokers (every day or occasionally) and/or vapers (every day or occasionally). Surveys were conducted in early pregnancy (8–24 weeks gestation) (baseline), late pregnancy (34–38 weeks gestation) and postpartum (3 months postpartum). Women who were unable to read or understand the questionnaires in English or were enrolled in other smoking cessation studies were excluded. A detailed description of the methods and characteristics of the participants recruited is published elsewhere ( Bowker et al., 2021 ). Ethical approval was given by the South West Frenchay Research Ethics Committee. We used “Strengthening the Reporting of Observational Studies in Epidemiology” (STROBE) ( von Elm et al., 2007 ) and “Transparent Reporting of Evaluations with Nonrandomized Designs” (TREND) guidance ( Des Jarlais, Lyles, Crepaz, & Group, 2004 ) to aid the reporting of this study.

2.2. Study setting and regimen

Women were recruited between June and November 2017 while attending National Health Service (NHS) hospital antenatal clinics at a range of locations in England and Scotland. Posters were visible in the antenatal clinics and research midwives/nurses promoted the study by handing a questionnaire to women attending clinics. Women completed a screening survey asking about their vaping and smoking status; those eligible and willing then completed a full baseline survey at the same time point (consent was implied through their completion of the questionnaire). They were then asked to give consent to join the longitudinal cohort and be sent follow-up surveys by post or email web-link. Written consent for longitudinal follow-up was taken face-to-face after completing the baseline (early pregnancy) survey; however, if women required more time, they were followed up by telephone, and verbal consent was taken. At each follow-up, participants were sent a prompt by Short Message Service (SMS) texts to enhance response rates, plus one reminder by post, text and/or email. If women failed to respond they were called to complete questions by telephone. Women were offered a £10 high street shopping voucher for completing each survey.

2.3. Description of the surveys

The early pregnancy survey included questions on age, gestation, educational attainment, age left education, ethnicity, previous pregnancies and whether pregnancy was planned. All three surveys contained a section about the participant’s experience of using e-cigarettes, smoking behaviour and beliefs. Responses included yes/no answers, Likert scales and multiple-choice options. The two follow-up surveys asked questions about infant feeding methods and the postpartum survey asked about birthweight.

All three surveys asked current vapers about their main reason for vaping, offering eight options. Due to low use of some of the response options, we report the top three responses: to quit smoking, to cut down smoking, to avoid returning to smoking. This latter option could imply women perceived themselves as established ex-smokers or may have been ex-smokers when they started vaping. Our ‘other’ category amalgamates the remaining responses: curiosity, enjoyment, to use when I am not allowed to smoke, don’t know and other (unknown). Women in the postpartum were also given the option ‘to use around my baby’.

Cigarette dependence was assessed using the Heaviness of Smoking Index (HSI) ( Heatherton et al., 1991 , Heatherton et al., 1989 , Riaz et al., 2016 ) (time to first smoking in the morning and number of cigarettes per day). Cigarettes smoked per day (CPD) were categorised as either “0–10” or “≥11” to distinguish between heavy and light smokers ( Husten, 2009 ); we included zero as some women smoked occasionally but not every day.

The surveys are available online as supplementary information .

2.4. Measurements

2.4.1. smoking and vaping status at baseline.

In early pregnancy, vaping status was determined on responses to the following statement: ‘ what best describes your use of e-cigarettes right now?’ . Participants could select one of the following: 1) I have never heard of e-cigarettes and have never tried them; 2) I have heard of e-cigarettes but have never tried them; 3) I have tried e-cigarettes, but do not use them now; 4) I have tried e-cigarettes and still use them, but not every day; 5) I have tried e-cigarettes and still use them every day.

Smoking status was based on responses to the following statement: ‘ what best describes your smoking right now?’ . Participants could select one of the following: 1) I have never smoked; 2) I completely stopped smoking more than 3 months before finding out I was pregnant; 3) I completely stopped smoking at some time in the 3 months before finding out I was pregnant; 4) I completely stopped smoking after I found out I was pregnant ; 5)I smoke occasionally, but not every day now I am pregnant; 6) I smoke every day, but have cut down during my pregnancy; 7) I smoke every day, about the same as before my pregnancy; 8) I smoke every day, and tend to smoke more than before my pregnancy.

Ex-smokers were those who reported they were not smoking currently but had done so during the 3 months before finding out they were pregnant. Women who reported vaping daily or occasionally (vape, but not every day) were defined as ‘vapers’. Women who reported that they smoked either daily or occasionally and did not vape (in any capacity), were defined as a ‘smoker’. Smokers who reported that they also vaped (in any capacity) were defined as ‘dual users’. Women who reported that they did not smoke but vaped (in any capacity) were defined as ‘exclusive vapers’.

2.4.2. Smoking and vaping status at follow up

On the follow-up surveys, women were asked ‘ How often do you use an e-cigarette or vaping device now? ’ and could select the following options: 1) Not used at all; 2) only used once or twice; 3) used occasionally, but less than weekly; 4) used less than daily, but at least once a week; 5) used every day.

Smoking status was determined on responses to the following statement: ‘ what best describes your smoking right now?’. Participants could select the following: 1) I don’t smoke at all; 2) I smoke occasionally, but not every day; 3) I smoke every day, but have cut down during my pregnancy; 4) I smoke every day, about the same as before my pregnancy; 5) I smoke every day, and tend to smoke more than before my pregnancy.

W omen who reported quitting smoking since completing the previous survey were defined as ‘ex-smokers’. Women were defined as ‘vapers’ if they reported they were currently vaping either daily, using less than daily but at least once a week, using occasionally but less than weekly, or vaping once or twice. If women reported that they smoked either daily or occasionally and did not vape (in any capacity), then they were defined as a ‘smoker’. Smokers who reported that they also vaped (in any capacity) were defined as ‘dual users’. Women who reported that they did not smoke but vaped (in any capacity) were defined as ‘exclusive vapers’.

Where follow-up surveys were missing responses to the vaping question used to define current vaping status ‘How often do you use an e-cigarette or vaping device now?’, two researchers independently reviewed the participant’s other responses to questions surrounding vaping habits (follow up survey questions; A9-A17) in order to determine vaping status.

2.5. Statistical analysis

To observe the pattern of vaping throughout pregnancy, we aimed to recruit at least 600 women into the cohort ( Bowker et al., 2021 ). Analysis was conducted using Stata-SE version 15 (StataCorp LLC, College Station, TX, USA).

We described the characteristics and smoking/vaping behaviour of the women who completed a survey in early pregnancy, those who entered the cohort study and those who completed all three surveys. Using chi-squared tests for categorical variables and t-tests for continuous variables, we looked to see if there were differences between women who only completed an early pregnancy survey and women who completed a survey at each of the three time points. P values of <0.05 were deemed significant.

We then described cross sectional prevalence of vaping and smoking in early and late pregnancy and the postpartum. For women who were classified as vapers at any of the time points, we described the frequency of vaping and main reason for vaping at each time point. We presented prevalence of vaping at each time point after excluding vapers who report vaping only once or twice, to highlight the prevalence of women who regularly vape during pregnancy. We also described the frequency of vaping specifically in vapers who completed all three surveys.

We described the temporal changes in vaping status within women who completed all three surveys to explore the patterns in individuals’ smoking and vaping habits during pregnancy and postpartum. To investigate the impact of missing outcome data for smoking and vaping status in late pregnancy or the postpartum we used multiple imputation, using Stata’s mi command, based on the characteristics that were associated with non-completion of all surveys. We included the outcome variable in the model. Since some of the smoking/vaping categories had zero or very few observations, and in multiple imputation proportions could be calculated for some but not all imputed datasets due to zero observations, these rare categories were excluded from our tree diagram.

3.1. Summary of the survey responses

Fig. 1 summarises the survey response rates. Of 1024 eligible women, 84.6% (n = 867) completed a survey in early pregnancy (baseline) and of these 86.5% (n = 750/867) joined the cohort. Surveys were returned by 52.3% (n = 392/750) of the cohort in late pregnancy (34–38 weeks gestation) and 56.0% (n = 415/750) in postpartum (3 months after having a baby). A total of 42.1% (n = 316/750) of women completed all three surveys and had complete data on their smoking and vaping status. The characteristics of the women who completed the early pregnancy survey have been described elsewhere ( Bowker et al., 2021 ). Supplementary Table 1 shows that compared to those who only completed the early pregnancy survey, women who completed all three surveys were significantly more likely to be ex-smokers in early pregnancy (p = 0.003), to hold higher educational qualification (p < 0.001), to have left education at a higher age (p < 0.001), to have a planned pregnancy (p < 0.001) and to report they were seriously planning on quitting smoking (p = 0.012). Women from the North and Midlands areas of England were more likely to have completed all three surveys compared with other regions (p = 0.008).

Recruitment and flow of participants through the study.

3.2. Cross sectional prevalence and frequency of vaping in early and late pregnancy and postpartum

Table 1 shows that in early pregnancy 15.9% (n = 119/750) of pregnant smokers or recent ex-smokers reported vaping; 12.4% (n = 93/750) were dual users and 3.5% (n = 26/750) were exclusive vapers. Reported vaping prevalence in late pregnancy was 17.8% (n = 68/383) (of which 12.5% (n = 48/383) were dual users and 5.2% (n = 20/383) exclusive vapers. In the postpartum, prevalence was 23.1% (n = 95/411) of which 14.6% (n = 60/411) were dual users and 8.5% (n = 35/411) were exclusive vapers. When vapers who reported only vaping once or twice were excluded from each time point (data not shown in table) the vaping prevalence in early pregnancy was 12.2% (n = 92/750), 13.6% (n = 52/383) in late pregnancy and 18.7% (n = 77/411) in the postpartum.

Smoking and vaping status, frequency, and main reason for vaping in early and late pregnancy and the postpartum.

*5 women did not provide information on smoking/vaping in late pregnancy and 4 women did not provide information on smoking/vaping in the postpartum.

**‘Other’ includes: Curiosity, enjoyment, to use when I am not allowed to smoke, don’t know and other (unknown).

^ The early pregnancy survey responses contained women who stated that they vaped, but then reported having ‘not used at all’ in their response to a question about frequency of vaping.

In early pregnancy, 65.4% (n = 17/26) of exclusive vapers reported vaping daily. A total of 31.2% (n = 29/93) of dual users reported vaping daily and 25.8% (n = 24/93) vaped less than daily but at least once a week. In late pregnancy (75.0%, n = 15/20) and the postpartum (77.1%, n = 27/35) a greater proportion of exclusive vapers reported vaping daily compared with early pregnancy. Among dual users a decreased proportion reported daily vaping in late pregnancy (25.0%, n = 12/48) and postpartum (23.3%, n = 14/60) compared with early pregnancy.

When observing only women who reported vaping at all three time points, in early pregnancy most exclusive vapers reported vaping every day (66.7%, n = 4/6). By late pregnancy and the postpartum all (100%) exclusive vapers reported daily use. Dual users varied in their daily reported vaping during pregnancy, but by the postpartum only one dual user reported vaping daily (6.3%, n = 1/16).

3.3. Longitudinal patterns of vaping during pregnancy and the postpartum

Fig. 2 shows the patterns of vaping and smoking behaviour within the 316 women who completed all three surveys and provided information on their smoking and vaping status. Fig. S1 shows the patterns of vaping and smoking at the three time points with missing data at follow-up imputed using multiple imputation; the patterns were similar to the non-adjusted figures.

Patterns of vaping and smoking throughout pregnancy.

3.3.1. Patterns of women that vape in early pregnancy

In total 2.6% (n = 8/316) of women who completed all three surveys were classified as exclusive vapers in early pregnancy; most remained exclusive vapers in late pregnancy (87.5%, n = 7/8) and the postpartum (75%, n = 6/8). Exclusive vapers in early pregnancy who were no longer exclusive vapers at later time points all became dual users.

In total 11.5% (n = 35/316) of women were classified as dual users in early pregnancy; over half remained dual users (60.0%, n = 21/35) in late pregnancy, of which 76.2% (n = 16/21) were dual users in the postpartum. Some temporal changes are evident in these dual users. For example, by the postpartum around a third (31.4%, n = 11/35) of dual users in early pregnancy were exclusive smokers. Around a quarter (n = 25.7%, n = 9/35) of dual users in early pregnancy, were exclusive smokers by late pregnancy, over half of whom remained exclusive smokers in the postpartum (66.7%, n = 6/9). Nearly a quarter (23.8%, n = 5/21) of women who dual used throughout pregnancy became exclusive smokers in the postpartum. A minority of early pregnancy dual users (11.4%, n = 4/35), became exclusive vapers by late pregnancy and remained exclusive vapers in the postpartum. Only one dual user (2.9%, n = 1/35) in early pregnancy become an ex-smoker in late pregnancy and remained so in the postpartum.

3.3.2. Patterns of women that do not vape in early pregnancy

There were 142 women classified as smokers in early pregnancy and 68.3% (n = 97/140), remain smokers throughout. A minority of exclusive smokers in early pregnancy were vaping in late pregnancy, either as dual users (9.9%, n = 14/142), or exclusive vapers (1.4%, n = 2/142). Those who became dual users in late pregnancy often returned to exclusive smoking in the postpartum (78.6%, n = 11/14). A minority of women who were exclusive smokers throughout pregnancy became dual users in the postpartum (10.8%, n = 12/112). Around 10% of women who were classified as ex-smokers during early and late pregnancy started vaping postpartum; 4.6% (n = 5/108) were duals users and 4.6% (n = 5/108) were exclusive vapers. A third (33.3%, n = 36/108) of ex-smokers were smoking in the postpartum.

3.4. Main reasons for vaping in early and late pregnancy and postpartum

The most frequently reported main reason to vape among exclusive vapers at each time point was to quit smoking: in early pregnancy 65.4% (n = 17/26), late pregnancy 55.0% (n = 11/20) and postpartum 57.1% (n = 20/35). A minority of exclusive vapers in early pregnancy reported that their main reason to vape was to avoid returning to smoking (11.5%, n = 3/26); this became a more frequent response in late pregnancy (25.0%, n = 5/20) and the postpartum (28.6%, n = 10/35). The most frequently reported main reason to vape among dual users was to quit smoking: early pregnancy 50.5% (n = 47/93), late pregnancy 37.5% (n = 18/48) and postpartum 38.3% (n = 23/60). The second most frequently reported main reason among dual users was to cut down their smoking: early pregnancy 30.1% (n = 28/93), late pregnancy 31.3% (n = 15/48) and postpartum 28.3% (n = 17/60).

4. Discussion

This is the first study to prospectively collect longitudinal data to describe pregnant women’s vaping throughout pregnancy and the postpartum. Our findings show that nearly 16% of pregnant smokers or ex-smokers are vaping in early pregnancy, 18% in late pregnancy and 23% in the postpartum. Most vapers during pregnancy and the postpartum report being dual users. We have also been able to report temporal changes in vaping. Vaping status among exclusive vapers in early pregnancy remained stable throughout pregnancy and the postpartum. Dual users appear less stable with around a quarter of dual users in early pregnancy becoming exclusive smokers by late pregnancy and a third exclusively smoking by the postpartum. A minority of women who were ex-smokers or smokers throughout pregnancy became vapers in the postpartum.

A limitation of this study is that we relied on self-reported data. Previous studies have shown stigma associated with both smoking and vaping during pregnancy (Katharine Bowker et al., 2018 ; Laura Schilling et al., 2019 ) and this could potentially lead to underreporting. However, there is some evidence that using self-reported smoking data during pregnancy is valid ( Pickett, Rathouz, Kasza, Wakschlag, & Wright, 2005 ) and as there was no intervention, there was no expectation that women should stop vaping or smoking. The surveys were completed discreetly during antenatal appointments in early pregnancy ( Bowker et al., 2021 ) and at the woman’s own discretion at follow up, enabling women to give honest responses. The participants were predominantly white British, similar to other UK cohorts of pregnant smokers ( Orton et al., 2014 ), but we recognise that our findings may not be generalisable to other ethnicities. Our follow up rates were relatively low at 52.3% in late pregnancy and 55.3% postpartum, and only 42.1% completed all three surveys, although our multiple imputation analysis that accounted for nonresponse bias showed similar smoking and vaping patterns to the main analysis.

We have data on longitudinal patterns for a relatively small number of exclusive and dual use vapers; these low numbers are possibly a reflection of low and variable levels of vaping in pregnant populations ( Whittington et al., 2018 ). Following a larger number of vapers over time would likely ensure a more representative understanding of vaping patterns. We defined vapers as anyone who reported vaping at any of the time points, including those who reported vaping only once or twice; we did not want to exclude infrequent vapers as we wanted to capture those experimenting with e-cigarettes. However, the prevalence of vaping after we excluded infrequent vapers showed that most vapers in our study used an e-cigarette more than once or twice. E-cigarette use may change over time and could explain the increase in proportions of those vaping in late pregnancy and the postpartum. However, when interpreting the temporal changes of vaping, consideration should be given to the highlighted differences in characteristics, such as education, between those that completed all three surveys and those that only completed the early pregnancy survey.

Exclusive vapers in early pregnancy appear less likely to return to smoking in the postpartum when compared with ex-smokers. Although we recognise the numbers of exclusive vapers were low, this pattern is similar to studies outside of pregnancy, which have shown rates of relapse to smoking in exclusive vapers is low over time ( Farsalinos et al., 2014 , Pasquereau et al., 2017 ). Exclusive vapers appear committed to vaping; the majority reported daily vaping throughout pregnancy and the postpartum. Little is known about why some pregnant women can quit smoking while vaping while others struggle; finding out more about the devices vapers use, the strengths of nicotine and adherence to e-cigarettes could aid our understanding.

Dual users commonly returned to smoking; nearly a quarter of women who reported being a dual user in early pregnancy were smoking exclusively by late pregnancy and around a third of pregnant dual users in early pregnancy were smoking exclusively in the postpartum. Dual users were less likely to report daily vaping compared to exclusive users, so it could be that their vaping habits were insufficient to assist with smoking cessation, or they were vaping as an alternative to smoking in some situations. Nevertheless, like previous studies we found dual users often reported that their primary reason for vaping was to quit smoking ( Chiang et al., 2019 , Fallin et al., 2016 , Wagner et al., 2017 ). One survey, which explored vaping use before and during pregnancy, found only one pregnant woman switched from dual use before pregnancy to vaping exclusively during pregnancy ( L. Schilling, Spallek, Maul, Tallarek, & Schneider, 2021 ). It is vital that more support is given to pregnant dual users to help them use e-cigarettes exclusively and thereby achieve their goal of smoking cessation. Although e-cigarettes are not risk free (American Lung American Lung Association, 2020 , Britton et al., 2016 , Froggatt et al., 2020 ), evidence outside of pregnancy observes health benefits among vapers who stop smoking combustible cigarettes completely ( McDonnell et al., 2020 , Shahab et al., 2017 ).

We found that nearly 11% of women who had smoked exclusively throughout pregnancy became dual users in the postpartum, and a similar proportion of women who were ex-smokers throughout pregnancy took up vaping (either exclusive or dual) in the postpartum. This could reflect women choosing to experiment with e-cigarettes as a novel product but may also be indicative of women trying to protect their new-born from second-hand smoke exposure by using e-cigarettes instead of continuing or returning to smoking in the postpartum period. Currently clinicians support pregnant smokers to stop smoking; they may also need to support dual users to stop smoking and avoid returning to smoking, and these women may have differing needs to exclusive smokers.

5. Conclusion

Between 16% and 23% of pregnant smokers and ex-smokers reported vaping at some point during pregnancy and the postpartum period; the majority dual use but vape with the intention to quit smoking. Temporal patterns show that the vaping habits of exclusive vapers remains stable throughout pregnancy and the postpartum. However, the vaping habits of dual users varies with a third becoming exclusive smokers by the postpartum period. Exclusive vapers appear more committed to vaping and vape daily, whereas dual users are less frequent users.

This work was funded by Cancer Research UK (CRUK), Tobacco Advisory Group Project (Grant number C53479/A22733). CRUK had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Author contribution

The study was conceptualized and designed by SC, SL, TC, LB, HM, MU, FN, SO, KB. KB, LP and SC were involved in planning and managing the data collection. SL, SC, KB, were involved in in the statistical analysis. KB wrote the first draft of the manuscript and all authors contributed to and have approved the final manuscript.

Declaration of Competing Interest

Dr Hayden McRobbie has in the past 3 years received honoraria for speaking at smoking cessation meetings and attending advisory board meetings that have been organised by Pfizer. He has no relationships with the manufacturers of vaping products. All other authors declare that they have no conflicts of interest.

Acknowledgements

The authors would like to thank all participants and staff at the NHS hospitals who were involved in this study. Lesley Sinclair from the University of Edinburgh for her involvement in the conceptualization and design of the study. James Brimicombe, from the University of Cambridge, for developing the study database and the following administrative staff at the University of Nottingham: Rebekah Howell, Katarzyna Kowalewska, Tom Coleman-Haynes, Karen Daykin, Rachel Whitemore, Miranda Clark, Anne Dickinson and Darren Kinahan-Goodwin. Tim Coleman is a National Institute for Health Research (NIHR) Senior Investigator. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.addbeh.2021.107050 .

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Will I get seasick on a cruise? Here's what travelers should know.

Mackenzie Pollock had a feeling she’d get seasick on her first cruise .

The 29-year-old Oregon resident tends to get carsick, so when she felt nausea on a Caribbean sailing with Princess Cruises in February, it wasn’t a surprise. And she came prepared. 

Pollock talked to her doctor before the trip, who prescribed Scopolamine patches. She also stocked up on Bonine tablets after seeing videos about it online. “I’m a librarian,” she said. “I do copious amounts of research on everything.”

There were “days here and there” during the 20-day trip when she felt sick, like when they went in and out of Florida and sailed through a thunderstorm. But between the two medications and other coping strategies like sitting on her suite’s balcony, she was able to manage it and enjoy her time with family.

Getting seasick can put a damper on a cruise, but there are ways to keep it from ruining your trip.

Why do people get seasick?

Seasickness is a form of motion sickness. That happens when there is a difference between the information you get from your visual system, your inner ear and receptors in your muscles, according to Dr. Kathleen Cullen, a professor of biomedical engineering at Johns Hopkins University. In a cruise ship cabin, for instance, the surroundings might appear stable even while the vessel is moving.

“And this mismatch between what your visual system is experiencing and what your balance organs are telling your brain about how you're moving is sort of an alert signal to your brain that something is wrong,” said Cullen. “So, it's a sensory conflict that actually is the big problem.”

Motion sickness symptoms can include nausea, dizziness and vomiting. 

Some travelers are more vulnerable than others, according to the Centers for Disease Control and Prevention. Those include kids between 2 and 12, and people who have a history of migraines, vertigo and vestibular disorders. “Pregnancy, menstruation, and taking hormone replacement therapy or oral contraceptives have also been identified as potential risk factors,” the health agency said on its website .

On the other hand, people older than 50 are less likely to develop it, and toddlers and infants are usually immune.

What is the worst cruise for seasickness?

While modern cruise ships have stabilizers that reduce their roll, some itineraries are more prone to choppy waters.

“If you're doing a transatlantic over to England , the North Atlantic can be pretty gnarly, especially in the winter,” said Rusty Pickett, a travel adviser and owner of Shellback Cruises. The Drake Passage, a feature of many Antarctica expedition sailings , is also notoriously treacherous.

Travelers can seek out calmer seas, though. ( Click here for USA TODAY’s guide to the best times to cruise by region.)

Where is the best cabin to avoid seasickness?

The bow of the ship tends to bounce up and down, said Pickett. “Lower in the ship, middle (and just aft of middle) minimizes the movement,” he added.

Booking a stateroom with a window so you can keep an eye on the horizon or getting fresh air – like Pollock did on her balcony – could also be helpful, Cullen said.

Short vs. long cruises: Which one is right for you? Here's how they compare.

How do I stop being seasick on a cruise?

Travelers can bring medications and other remedies with them. Prescription Scopolamine patches can help get passengers “over the hump,” Cullen said. There are also other over-the-counter medications like Dramamine.

Those can make users drowsy. Travelers should talk to their doctor about their options ahead of their cruise.

Ginger candies or ginger ale – made with real ginger – and acupressure wristbands may also be helpful.

After you board, Cullen recommends watching the horizon on the ship’s outer decks. “That's a pretty good way to keep yourself, initially, from getting motion sick if you're prone to it,” she said.

The CDC offers other suggestions , including lying down, closing your eyes and sleeping; limiting caffeinated and alcoholic drinks; eating small portions of food often; and not smoking.

What other options do passengers have?

Cruise ships generally have onboard medical staff that can treat a range of ailments, and Pickett said the vessels keep a supply of seasickness medication on hand.

During an Antarctica expedition I took with Aurora Expeditions in December, crew members also placed barf bags around the ship that passengers could grab if they felt sick while outside their rooms.

Pollock said feeling seasick didn’t put her off cruising, and she and her family plan to take another. “It was frustrating when it happened, but it didn't overshadow the trip at all.”

Nathan Diller is a consumer travel reporter for USA TODAY based in Nashville. You can reach him at [email protected].