Literature DB >> 32810184

Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: An individual participant data meta-analysis of 229,000 singleton births.

Elise M Philips1,2, Susana Santos1,2, Leonardo Trasande3,4,5,6,7, Juan J Aurrekoetxea8,9,10, Henrique Barros11,12, Andrea von Berg13, Anna Bergström14,15, Philippa K Bird16, Sonia Brescianini17, Carol Ní Chaoimh18,19, Marie-Aline Charles20, Leda Chatzi21, Cécile Chevrier22, George P Chrousos23, Nathalie Costet22, Rachel Criswell24,25, Sarah Crozier26, Merete Eggesbø27, Maria Pia Fantini28, Sara Farchi29, Francesco Forastiere29, Marleen M H J van Gelder30,31, Vagelis Georgiu32, Keith M Godfrey26,33, Davide Gori28, Wojciech Hanke34, Barbara Heude20, Daniel Hryhorczuk35, Carmen Iñiguez10,36, Hazel Inskip26,33, Anne M Karvonen37, Louise C Kenny19,38, Inger Kull39,40, Debbie A Lawlor41,42, Irina Lehmann43, Per Magnus44, Yannis Manios45, Erik Melén14,39,40, Monique Mommers46, Camilla S Morgen47,48, George Moschonis49, Deirdre Murray19,50, Ellen A Nohr51, Anne-Marie Nybo Andersen48, Emily Oken52, Adriëtte J J M Oostvogels53, Eleni Papadopoulou54, Juha Pekkanen37,55, Costanza Pizzi56, Kinga Polanska34, Daniela Porta29, Lorenzo Richiardi56, Sheryl L Rifas-Shiman52, Nel Roeleveld30, Franca Rusconi57, Ana C Santos11,12, Thorkild I A Sørensen48,58, Marie Standl59, Camilla Stoltenberg60,61, Jordi Sunyer10,62,63, Elisabeth Thiering59,64, Carel Thijs46, Maties Torrent65, Tanja G M Vrijkotte53, John Wright66, Oleksandr Zvinchuk67, Romy Gaillard1,2, Vincent W V Jaddoe1,2.   

Abstract

BACKGROUND: Fetal smoke exposure is a common and key avoidable risk factor for birth complications and seems to influence later risk of overweight. It is unclear whether this increased risk is also present if mothers smoke during the first trimester only or reduce the number of cigarettes during pregnancy, or when only fathers smoke. We aimed to assess the associations of parental smoking during pregnancy, specifically of quitting or reducing smoking and maternal and paternal smoking combined, with preterm birth, small size for gestational age, and childhood overweight. METHODS AND
FINDINGS: We performed an individual participant data meta-analysis among 229,158 families from 28 pregnancy/birth cohorts from Europe and North America. All 28 cohorts had information on maternal smoking, and 16 also had information on paternal smoking. In total, 22 cohorts were population-based, with birth years ranging from 1991 to 2015. The mothers' median age was 30.0 years, and most mothers were medium or highly educated. We used multilevel binary logistic regression models adjusted for maternal and paternal sociodemographic and lifestyle-related characteristics. Compared with nonsmoking mothers, maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with a higher risk of childhood overweight (odds ratio [OR] 1.17 [95% CI 1.02-1.35], P value = 0.030). Children from mothers who continued smoking during pregnancy had higher risks of preterm birth (OR 1.08 [95% CI 1.02-1.15], P value = 0.012), small size for gestational age (OR 2.15 [95% CI 2.07-2.23], P value < 0.001), and childhood overweight (OR 1.42 [95% CI 1.35-1.48], P value < 0.001). Mothers who reduced the number of cigarettes between the first and third trimester, without quitting, still had a higher risk of small size for gestational age. However, the corresponding risk estimates were smaller than for women who continued the same amount of cigarettes throughout pregnancy (OR 1.89 [95% CI 1.52-2.34] instead of OR 2.20 [95% CI 2.02-2.42] when reducing from 5-9 to ≤4 cigarettes/day; OR 2.79 [95% CI 2.39-3.25] and OR 1.93 [95% CI 1.46-2.57] instead of OR 2.95 [95% CI 2.75-3.15] when reducing from ≥10 to 5-9 and ≤4 cigarettes/day, respectively [P values < 0.001]). Reducing the number of cigarettes during pregnancy did not affect the risks of preterm birth and childhood overweight. Among nonsmoking mothers, paternal smoking was associated with childhood overweight (OR 1.21 [95% CI 1.16-1.27], P value < 0.001) but not with adverse birth outcomes. Limitations of this study include the self-report of parental smoking information and the possibility of residual confounding. As this study only included participants from Europe and North America, results need to be carefully interpreted regarding other populations.
CONCLUSIONS: We observed that as compared to nonsmoking during pregnancy, quitting smoking in the first trimester is associated with the same risk of preterm birth and small size for gestational age, but with a higher risk of childhood overweight. Reducing the number of cigarettes, without quitting, has limited beneficial effects. Paternal smoking seems to be associated, independently of maternal smoking, with the risk of childhood overweight. Population strategies should focus on parental smoking prevention before or at the start, rather than during, pregnancy.

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Mesh：

Year:  2020        PMID： 32810184      PMCID： PMC7433860          DOI： 10.1371/journal.pmed.1003182

Source DB:  PubMed          Journal:  PLoS Med        ISSN： 1549-1277            Impact factor:   11.069


Introduction

One in five women of reproductive age are expected to be tobacco users by 2025 [1]. Although strategies to prevent smoking are globally implemented, up to 25% of women in Western countries smoke during pregnancy [2]. This is a major public health concern, particularly since smoking during pregnancy not only affects women’s own health but is also associated with adverse birth and offspring outcomes, such as preterm birth, low birth weight, and childhood overweight [3-13]. Preterm birth and low birth weight are major causes of perinatal morbidity and mortality, and childhood overweight is related to a higher risk of cardiovascular disease, premature death, and disability in adulthood [14-16]. A vast number of studies observed consistent associations of continued maternal smoking during pregnancy with increased risks of preterm birth, low birth weight, and childhood overweight [7,10,11]. However, evidence on critical windows of vulnerability to maternal smoking and changes in smoking behavior during pregnancy remain inconclusive, potentially reflecting between-study heterogeneity of outcome measures and small study sample sizes. Previous studies focusing on maternal smoking in first trimester of pregnancy only consistently showed no associations with preterm birth but showed conflicting results for the risks of low birth weight and childhood overweight [8,9,17-21]. Also, the associations of paternal smoking during pregnancy with preterm birth, low birth weight, and childhood overweight have been scarcely studied and remain unclear [20,22,23]. Paternal smoking might affect offspring outcomes through direct gamete or passive smoking intrauterine effects. However, comparisons of maternal and paternal smoking associations can also be used to disentangle direct uterine programming effects and confounding by shared or family-based lifestyle or socioeconomic variables. To our knowledge, no large sample size studies assessed the associations of maternal smoking during first trimester only, of reducing the number of cigarettes during pregnancy, or of paternal smoking only with birth and childhood outcomes. We conducted an individual participant data meta-analysis among 229,158 singleton births from 28 pregnancy and birth cohort studies in Europe and North America to assess the associations of parental smoking during pregnancy with preterm birth, small size for gestational age (SGA), and childhood overweight. We were specifically interested in the associations of quitting or reducing smoking during pregnancy and of combined maternal and paternal smoking patterns with birth and offspring outcomes.

Methods

Inclusion criteria and participating cohorts

This study was part of an international LifeCycle Project (https://lifecycle-project.eu) collaboration on maternal obesity and childhood outcomes [24-28]. Pregnancy and birth cohort studies were eligible for inclusion if they included mothers with singleton live-born children who were born from 1989 onwards, had information available on maternal prepregnancy/early-pregnancy body mass index (BMI), and had at least one offspring measurement (birth weight or childhood BMI). We identified eligible cohorts from existing collaborations on childhood health (EarlyNutrition Project, CHICOS Project, www.birthcohorts.net assessed until July 2014). Fifty cohorts from Europe, North America, and Oceania were identified and invited, of which 39 cohorts agreed to participate. The cohorts were approved by their local institutional review boards, and written informed consent from all participants or parents was obtained. Eleven cohorts were excluded from the current analysis because there was no information on maternal smoking patterns or only nonsmoking mothers in their cohort. In total, 28 cohorts comprising data on 229,158 singleton births were included (). Twenty-two of the 28 cohorts defined themselves as regionally or nationally based studies, four as hospital-based (Co.N.ER, EDEN, GASPII, LUKAS), one as internet users–based (NINFEA), and one as studying selected populations (FCOU). The plan for analyses given to the cohorts when inviting them to participate in this paper from the LifeCycle Project collaboration is provided in . Based on data availability and additional research questions, it was decided among the collaborators to refine the existing questions and to extend the project with additional questions to be addressed. Analyses that were not in the original plan are marked in . Associations of smoking with early- and late-childhood BMI were excluded because of low numbers. All cohorts provided written informed consent for using their data. Anonymized datasets were stored on a single central secured data server with access for the main analysts (EP, SS) only. This study is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline ().

Flowchart of the cohorts and participants.

BMI, body mass index.

Parental tobacco smoking

Parental smoking information was obtained by questionnaires (cohort-specific information in ). We used trimester-specific maternal smoking information to categorize smoking during pregnancy in three groups (nonsmoking; first-trimester-only smoking; continued smoking [as being any second or third trimester smoking]). Trimester-specific maternal smoking information was categorized into nonsmoking, ≤4 cigarettes/day, 5–9 cigarettes/day, and ≥10 cigarettes/day. We combined the information about maternal smoking in first and third trimester to examine the change in smoking behavior. Information on paternal nonsmoking/smoking was used. To explore the combined effects of maternal and paternal smoking, we combined the maternal and paternal smoking information into six categories: maternal and paternal nonsmoking (used as reference category); maternal nonsmoking and paternal smoking; maternal first-trimester-only smoking and paternal nonsmoking; maternal first-trimester-only smoking and paternal smoking; maternal continued smoking and paternal nonsmoking; and maternal continued smoking and paternal smoking.

Birth complications and childhood overweight

Information on gestational age at birth, birth weight, and childhood weight and height was measured, derived from clinical records, or reported (cohort-specific information in ). Preterm birth was defined as <37 weeks of gestation, and full-term birth (≥37 weeks) was used as the reference group in the analyses [29]. We created sex- and gestational age–adjusted birth weight standard deviation scores (SDSs) based on a North European reference chart [30]. SGA at birth was defined per cohort as sex- and gestational age–adjusted birth weight below the 10th percentile. The reference group used in the analyses comprises children born at appropriate and large size for gestational age (i.e., cohort-specific sex- and gestational age–adjusted birth weight above the 10th percentile). BMI measurements in mid-childhood (≥5 to <10 years) were used. If there were multiple measurements of a child available within the age interval, we used the measurement at the highest age. We created sex- and age-adjusted SDSs of childhood BMI using World Health Organization (WHO) reference growth charts (Growth Analyzer 4.0, Dutch Growth Research Foundation) [31,32]. Childhood normal weight, overweight, and obesity were defined using WHO cutoffs [31,32]. For the analyses, we combined the overweight and obesity group, hereafter referred to as the overweight group. Normal weight was used as the reference group in childhood overweight analyses.

Covariates

Information on covariates was mostly assessed using questionnaires. Most covariates were provided by cohorts as categorical variables: child’s sex, maternal educational level (low, medium, high), parity (nulliparous, multiparous), and alcohol consumption during pregnancy (yes, no). To allow handling of missing data, continuous covariates were categorized: maternal age (defined on the basis of data availability: <25.0 years, 25.0–29.9 years, 30.0–34.9 years, and ≥35.0 years) and prepregnancy or early-pregnancy maternal and paternal BMI (underweight [<18.5 kg/m2], normal weight [18.5–24.9 kg/m2], overweight [25.0–29.9 kg/m2], and obesity [≥30.0 kg/m2]). Maternal ethnicity was not included, since most cohorts were largely of European descent and there was a high percentage of missing data. Covariates per cohort are described in .

Statistical analysis

We conducted 1-stage meta-analyses, in which we analyzed individual participant data from all cohorts simultaneously in binary logistic multilevel mixed-effects models, accounting for clustering of participants within cohorts [33]. First, we examined the associations of maternal smoking (across different trimesters; dose-response) with the risks of preterm birth, SGA, and childhood overweight. When examining the dose-response effects of first trimester maternal smoking, mothers who continued smoking were excluded from the analysis. Second, we used similar models to investigate the associations of change in maternal smoking behavior from first to third trimester with the risks of preterm birth, SGA, and childhood overweight. Finally, we used similar models to investigate the combined associations of both maternal and paternal smoking with the risks of these outcomes. We assessed whether the risk estimates between categories statistically differed using the formula [34]. We adjusted all analyses focused on maternal smoking for maternal age, educational level, parity, prepregnancy or early-pregnancy BMI, alcohol consumption during pregnancy, and paternal smoking. We adjusted all analyses focused on combined maternal and paternal smoking for the same covariates and paternal BMI. As sensitivity analyses, we repeated all models for gestational age at birth, sex- and gestational age–adjusted birth weight SDSs, and childhood sex- and age-adjusted BMI SDSs. Also, we conducted two-stage random-effects meta-analyses for the core associations and tested for heterogeneity between the cohorts estimates with the I2 test [33,35]. To express the uncertainty associated with I2 estimates, we calculated the corresponding 95% confidence intervals (CIs) [36]. All covariates were categorized and missing values were added as an additional group to prevent exclusion of noncomplete cases. If information on a covariate was available for less than 50% of the cohort sample used for each analysis, available information was not used and the corresponding data for that full cohort sample were assigned to the missing category. We conducted a sensitivity analysis with complete cases only. Also, to explore the influence on our results of using maternal age and BMI as categorical covariates, we repeated the complete cases’ analysis using these covariates continuously. The statistical analyses were performed using the Statistical Package of Social Sciences version 24.0 for Windows (SPSS, Chicago, IL, United States of America) and Review Manager (RevMan) version 5.3 of the Cochrane Collaboration (The Nordic Cochrane Centre, Copenhagen, Denmark).

Results

Participants’ characteristics

Information about the main characteristics per cohort is given in . Overall, 14.4% (range 5.5–26.8) of mothers and 27.5% (range 16.9–83.8) of fathers smoked during pregnancy. Children were born at a median gestational age of 40.0 weeks (95% range 35.7–42.3) and a median birth weight of 3,530 grams (95% range 2,390–4,580). In total, 4.7% of children were born preterm, 10.0% were SGA at birth, and 20% were in the overweight group. Additional information about maternal smoking is given in . Values are expressed as number of participants (valid %) or medians (95% range). “First trimester only” refers to mothers who smoked during first trimester only. Childhood overweight also includes obesity and includes information at child age ≥5 to <10 years. Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight SDS per cohort. a Subset of participants with follow-up completed at 4 years of child’s age by the time of data transfer (March 2015). Abbreviations: BMI, body mass index; NA, not available (not collected or not provided) or not applicable (gestational age at birth [FCOU, GINIplus, LISAplus, LUKAS] and birth weight [GINIplus, LISAplus] due to study samples restricted to specific ranges of gestational age and weight at birth); SDS, standard deviation score

Changes in maternal smoking habits during pregnancy and the risks of preterm birth, SGA, and childhood overweight

shows that maternal first trimester smoking only was not associated with adverse birth outcomes but was associated with higher risks of childhood overweight (odds ratio [OR] 1.17 (95% CI 1.02–1.35), P value = 0.030). Compared with children from mothers who did not smoke during pregnancy, those from mothers who continued smoking had higher risks of preterm birth (OR 1.08 [1.02–1.15], P value = 0.012), SGA (OR 2.15 [2.07–2.33], P value < 0.001), and childhood overweight (OR 1.42 [1.35–1.48], P value < 0.001). We observed dose-response relationships for third trimester smoking starting at ≤4 cigarettes/day. We observed similar results when we used the continuous outcomes, except for the association of first-trimester-only smoking with childhood BMI SDS, which was in the same direction but no longer significant (S4 Table). We observed similar results when using two-stage random-effects models (Figs ). We observed low to moderate heterogeneity between the cohorts’ estimates (I2 estimates range from 0% to 47%; corresponding CIs are presented in the footnotes of Figs 2, 3 and 4). Only the cohort-specific results for the associations of maternal continued smoking with SGA showed high heterogeneity between estimates (I2 75% [95% CI 56%–86%]). Almost all cohorts were included in the analyses for continued smoking, whereas only roughly half had information on first-trimester-only smoking. When restricting the two-stage continued smoking models to the cohorts also with information on first-trimester-only smoking, we observed a lower heterogeneity between estimates (I2 23% [95% CI 0%–65%]), but the pooled risk estimate remained similar (S1 Fig).
Fig 2

Maternal smoking with risks of preterm birth assessed by 2-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of preterm birth per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 0% (95% CI 0%–57%) and 4% (95% CI 0%–47%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable.

Fig 3

Maternal smoking with risks of small size for gestational age assessed by two-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of small size for gestational age per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 21% (95% CI 0%–65%) and 75% (95% CI 56%–86%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable.

Fig 4

Maternal smoking with risks of childhood overweight assessed by two-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of childhood overweight per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 0% (95% CI 0%–60%) and 47% (95% CI 1%–72%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable.

Maternal smoking with risks of preterm birth assessed by 2-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of preterm birth per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 0% (95% CI 0%–57%) and 4% (95% CI 0%–47%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable.

Maternal smoking with risks of small size for gestational age assessed by two-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of small size for gestational age per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 21% (95% CI 0%–65%) and 75% (95% CI 56%–86%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable.

Maternal smoking with risks of childhood overweight assessed by two-stage random-effects models.

(A) First trimester smoking versus nonsmoking, (B) continued smoking versus nonsmoking. Values are odds ratios (95% CIs) per cohort and pooled from binary logistic regression models that reflect the risk of childhood overweight per smoking pattern (first-trimester-only smoking or continued smoking) compared to that of nonsmoking. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. The cohorts for which no estimate was provided had no data available for that particular analysis. The heterogeneity between the estimates of each cohort was 0% (95% CI 0%–60%) and 47% (95% CI 1%–72%) for first-trimester-only smoking and continued smoking, respectively. CI, confidence interval, IV, instrumental variable. Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per smoking group compared with the reference group (no maternal smoking). Number of cigarettes used as continued smoking dosage was based on third trimester information. Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. *P value < 0.05. **P value < 0.001. shows that, compared with mothers who did not smoke during pregnancy, mothers who quit smoking from first to third trimester had similar risks of delivering SGA infants. Reducing the number of cigarettes, without quitting, from first to third trimester lowered the risks of delivering SGA infants, but risks were still higher compared with those of nonsmoking mothers (OR 1.89 [1.52–2.34] when reducing from 5–9 to ≤4 cigarettes/day; 2.79 [2.39–3.25] and 1.93 [1.46–2.57] when reducing from ≥10 to 5–9 and ≤ 4 cigarettes/day, respectively [all P values < 0.001]). Mothers who increased the number of cigarettes from first to third trimester increased their risks of delivering SGA infants (OR 2.43 [2.05–2.89] and 2.47 [1.71–3.58] when increasing from ≤4 to 5–9 and ≥10 cigarettes/day, respectively; and 2.70 [2.35–3.10] when increasing from 5–9 to ≥10 cigarettes/day [all P value < 0.001]). Changes in maternal smoking from first to third trimester did not influence the risks of preterm birth and childhood overweight. Similar results were observed when assessing the associations of the changes in maternal smoking during pregnancy with the continuous outcomes (S5 Table). Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per change in smoking group compared with that of the reference group (nonsmoking in first and third trimester). Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, educational level, parity, prepregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking. *P value < 0.05. **P value < 0.001.

Parental smoking during pregnancy and the risks of preterm birth, SGA, and childhood overweight

Among mothers who did not smoke during pregnancy, paternal smoking tended to be associated with higher risks of preterm birth (OR 1.06 [1.00–1.12], P value = 0.05), SGA (OR 1.04 [1.00–1.09], P value = 0.05), and childhood overweight (OR 1.21 [1.16–1.27], P value < 0.001) (). Among mothers who smoked during first trimester only, paternal smoking was not associated with preterm birth or SGA but was associated with a higher risk of childhood overweight (OR 1.36 [1.02–1.80], P value = 0.036). Among mothers who continued smoking during pregnancy, paternal smoking further increased the risks of SGA and childhood overweight (both Z-score P value for differences in effect sizes between categories <0.0001) but not the risk of preterm birth. Children whose mothers continued smoking during pregnancy and whose fathers also smoked had the highest risks of being born preterm (OR 1.10 [1.02–1.19], P value = 0.016) and SGA (OR 2.37 [2.26–2.49], P value < 0.001) and of childhood overweight (OR 1.76 [1.65–1.87], P value < 0.001). Similar results were observed for the combined maternal and paternal smoking with the continuous outcomes (S6 Table). Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per smoking group compared with the reference group (no parental smoking). Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, maternal body mass index, paternal body mass index, maternal education, parity, and maternal alcohol consumption during pregnancy. *P value < 0.05. **P value < 0.001.

Discussion

In this study, maternal continued smoking during pregnancy was associated, in a dose-response manner, to higher risks of preterm birth, being SGA at birth, and childhood overweight. Maternal smoking during the first trimester of pregnancy only was not associated with risks of preterm birth and SGA but was associated with a higher risk of childhood overweight. Reducing the number of cigarettes during pregnancy without quitting may be beneficial for the risk of SGA but seems not to influence the risks of preterm birth and childhood overweight. Paternal smoking seems to be associated, independently of maternal smoking, with the risks of childhood overweight. Maternal smoking is a major public health concern [1]. The associations of maternal continued smoking during pregnancy and increased risks of preterm birth and SGA are well established [7,10,18]. Also, several studies have suggested associations of fetal smoke exposure with childhood overweight and obesity [11,22]. In line with these previous studies, we observed that children whose mothers continued smoking during pregnancy have higher risks of preterm birth, being SGA at birth, and overweight in childhood. The risks of preterm birth were somewhat weaker than reported previously [7,9,18], potentially because no information was available about induced or spontaneous preterm birth. Results from previous studies focused on the associations of maternal early smoking cessation and of reducing the number of cigarettes during pregnancy with child health outcomes are inconsistent [8,17,19,21,22]. Results from prospective studies in the Netherlands and Australia previously suggested that quitting smoking after the first trimester was not associated with risks of adverse birth outcomes [18,19]. A large US study with more than 21,000 first trimester smokers reported that smoking of any duration during pregnancy was associated with an increased risk of fetal growth restriction with decreasing risk the earlier that cessation occurred [17]. Similarly, a recent study from the UK Millennium Cohort Study suggested that two-thirds of the total adverse smoking impact on birth weight occurs in the second trimester and that cutting smoking intensity by the third month in pregnancy leads to infants of the same weight as those infants born to persistent light smokers [37]. A recent study investigating associations of parental smoking with fetal growth using additional methods of mendelian randomization and parental negative control showed consistent linear dose-dependent associations of maternal smoking with fetal growth from early second trimester onward [38]. These studies suggest that smoking cessation programs should focus on the benefit of quitting as early in pregnancy as possible. A previous analysis using data from the Nurses’ Health Study showed that first-trimester-only maternal smoking was not, or was only to a limited extent, associated with obesity in later life [20]. However, in the same cohort, first-trimester-only maternal smoking was associated with type 2 diabetes in the offspring [39]. In the current study, maternal first-trimester-only smoking was not associated with the risks of preterm birth or SGA but was associated with an increased risk of childhood overweight. A biological explanation might be that maternal first-trimester-only smoking already leads to specific adaptations, which might have lifelong consequences for body composition and metabolic health in later life, but the fetal smoke exposure is not long enough to affect birth outcomes. Reducing the number of cigarettes from first to third trimester lowered the risks of SGA, but risks were still elevated compared with those in infants born to nonsmoking mothers. This association was not observed for preterm birth and childhood overweight. Thus, our findings suggest that quitting smoking in the first trimester of pregnancy might optimize birth outcomes but might not reduce the risk of adverse metabolic effects in the offspring to the level of nonsmoking. Also, reducing the number of cigarettes from first trimester onward may reduce risks of fetal growth restriction. The role of paternal smoking during pregnancy on child health outcomes remains unclear [23,40,41]. Paternal smoking has been associated with reduced semen quality and fertility and higher risks of spontaneous abortion, birth defects, and, in the long-term, attention-deficit/hyperactivity disorder and several cancers [42-45]. A recent meta-analysis showed that paternal smoking was associated with increased risks of preterm birth and SGA [44]. In a previous Dutch study, paternal smoking during pregnancy among nonsmoking mothers was associated with higher childhood BMI [12]. A small study from the US using self-reported smoking and serum cotinine measurements found a higher BMI at 2 and 3 years of age in children whose mothers were exposed to passive smoking during pregnancy [40]. In the current study, paternal smoking among nonsmoking mothers was associated with a higher risk of childhood overweight and tended to be associated with higher risks of preterm birth and SGA. This suggests that paternal smoking may be, independently of maternal smoking, associated with childhood overweight. However, we cannot exclude the possibility of residual confounding by factors not or insufficiently measured in the studies. Previous studies used comparisons of maternal and paternal smoking associations to explore potential mechanisms [12,46]. In the current study, if only one parent smoked, the risks of SGA were much higher among maternal smokers than among paternal smokers, whereas the risks of preterm birth for maternal and paternal smoking were similar. The similar associations of maternal and paternal smoking and preterm birth may suggest that the underlying mechanisms include shared family-based characteristics, such as environmental exposures and lifestyle. The stronger associations of maternal smoking, compared with paternal smoking, with SGA may suggest that these associations are mainly explained by intrauterine mechanisms. Since paternal smoking among nonsmoking mothers was not associated with SGA, the risk increase when both parents smoked may represent an additional mechanistic pathway through shared family-based characteristics. The risk of overweight was slightly higher among children whose mothers smoked than whose fathers smoked. However, the risks increased significantly if both parents smoked. These findings suggest that, although intrauterine programming mechanisms might play a role, shared family-based lifestyle and genetic characteristics are potential underlying mechanisms. Whether these findings also reflect transgenerational epigenetic inheritance through the gametes needs to be further studied. Various components of tobacco smoke might be involved in the mechanistic pathway toward adverse birth outcomes and childhood overweight. Both nicotine and carbon monoxide are reported to reduce placental blood flow [47]. Nicotine stimulates acetylcholine receptors, which release a multitude of vasoactive catecholamines and peptides, which in turn reduce blood flow through vasoconstriction [47]. Carbon monoxide competes with oxygen for binding sites on the transport protein hemoglobin, causing hypoxia [48]. Chronic hypoxia interferes with the maternal circulatory adjustments to pregnancy which can be another cause of reduced placental blood flow [49]. Uterine blood flow is essential for uterine, placental, and fetal growth. Several mechanisms for nicotine-induced alterations in overweight risks have been proposed, including stimulation of the fetal hypothalamic-pituitary axis [50]. It has been suggested that cadmium, present in tobacco smoke, modulates oxytocin receptor function, proposing a role in the pathophysiology of preterm birth [48]. Recent studies have found an association between maternal smoking during pregnancy and birth weight with a mediating role of DNA methylation [51-53]. Further research is needed to assess such possible mechanisms. During the last few years, e-cigarettes have been widely used as substitutes for smoking. Evidence from recently started cohorts is needed to clarify whether e-cigarettes are any safer during pregnancy. We performed an individual participant data meta-analysis of prospective cohort studies to investigate the associations of parental smoking during pregnancy with preterm birth, SGA, and childhood overweight. We included data from cohort studies in Europe and North America, so our findings are mainly applicable to populations in developed countries. Inclusion of data from other regions could have led to differences in prevalence of maternal and paternal smoking, birth complications, childhood overweight, and ethnic and sociodemographic characteristics, complicating or limiting the possibility of doing a meta-analysis. Among study limitations, our outcomes might not be generalizable to populations from low-income and middle-income countries, which need to be further studied. The large sample size enabled us to investigate the effects of changing smoking habits and paternal smoking. However, our study might have been underpowered to detect associations in the analyses looking at maternal-only first trimester smoking and the change in smoking habits from first to third trimester, due to small sample sizes. Since we used original, individual participant data, we did not formally assess the quality of the individual studies included. We are aware that our study cannot overcome potential limitations of individual studies in terms of their design and conduct, differences in the definitions of exposure and outcome data, and variation in missing data. Parental smoking information during pregnancy was self-reported. For active smoking, correlations between cotinine measurements and self-reported smoking habits are high [54]. We have no information on the specific question asked or the timing in which it was asked, which might have differed across cohorts and influenced our results. It has been suggested that using maternal nonsmokers as a reference group without considering the impact of passive smoke exposure may contribute to an underestimation of the estimated effects [40]. To limit this misclassification, all analyses on maternal smoking were adjusted for paternal smoking. Although smoking in the preconception period has been reported not to be associated with fetal growth restriction, studies considering its effect on childhood overweight are lacking [17]. In the current study, information on smoking in the preconception period was missing. Further research is needed to assess the associations of smoking in the preconception period with offspring outcomes. It has been suggested that exposure to smoking during childhood amplifies the association between prenatal smoke exposure and childhood BMI outcomes [55]. Many women resume smoking shortly after birth. Six weeks after birth, approximately 25% of women resumed smoking, and 1 year after birth these numbers are up to 80% [56]. In our study, information on exposure to smoking during childhood was not available for most cohorts. Further research is needed to assess whether childhood BMI outcomes are additionally influenced by exposure to smoking during childhood. Overall, we observed low to moderate heterogeneity in the 2-stage random-effects models, which might be due to the inclusion of cohorts that were mostly high-income and of European descent. However, we observed high heterogeneity between the cohorts for the associations of maternal continued smoking with SGA. This might be in part explained by differences in pattern and dosage of maternal and paternal smoking between cohorts. When we restricted the 2-stage continued smoking models to the cohorts that also had information on first-trimester-only smoking, we observed a substantially lower heterogeneity between estimates. Missing values of covariates were used as an additional group. This approach has been commonly used in large meta-analyses of individual participant data because of the constraints in applying more advanced imputation strategies. Although we cannot disregard the possibility of bias, we consider it unlikely considering the relatively small percentage of missing data [57]. We observed similar results when we conducted a complete case analysis (S7 Table). Also, similar associations were observed when adjusting for maternal age and BMI as categorical or continuous covariates (S7 and S8 Tables). Although we adjusted for multiple lifestyle-related factors, we cannot exclude residual confounding by other environmental lifestyle-related factors. From the current observational data, no conclusions can be drawn on the causality of the observed associations. Our results suggest that as compared to mothers who continued smoking throughout pregnancy, mothers who quit smoking during the first trimester have a reduced risk of birth complications. Reducing the number of cigarettes without quitting during pregnancy is still associated with an increased risk of birth complications. The observed risk estimates were small to moderate but are important from a public health perspective, since smoking is a common adverse exposure and preterm birth and SGA are among the most frequent birth complications. Also, preterm birth, SGA, and childhood obesity are related with adverse health consequences later in life. Our findings suggest that it is of great importance to invest in prevention of smoking in women of reproductive age before or at the start of pregnancy. Pregnant women should still be motivated to reduce smoking, even later in pregnancy. The current guidelines focus only on quitting smoking and not reducing, which can be discouraging for women who find it difficult to quit smoking. These women should be provided with sufficient information about the risks of continued smoking but also about the benefits of reducing their number of cigarettes. Future research should investigate whether quitting smoking in the first trimester or reducing the number of cigarettes during pregnancy is also beneficial for other adverse birth and offspring outcomes. Although we cannot exclude a role of residual confounding and shared family-based characteristics in the associations of paternal smoking with childhood overweight, we recommend that fathers are more closely involved in preconception and pregnancy consultations focused on smoking reduction. Our results suggest that maternal smoking during the first trimester only is not associated with the risks of SGA and preterm birth but is associated with a higher risk of childhood overweight. Reducing the number of cigarettes during pregnancy without quitting may be beneficial for the risk of SGA but does not influence the risks of preterm birth and childhood overweight. Paternal smoking seems to be associated, independently of maternal smoking, with the risks of childhood overweight. Population strategies should focus on parental smoking prevention before or at the start of, rather than during, pregnancy. (PDF) Click here for additional data file. (PDF) Click here for additional data file. (PDF) Click here for additional data file.

Maternal continued smoking with risks of small size for gestational age assessed by two-stage random-effects models.

(PDF) Click here for additional data file.

Cohort-specific methods of data collection for parental smoking, birth outcomes, and childhood BMI. BMI, body mass index.

(PDF) Click here for additional data file.

Cohort-specific description of available covariates.

(PDF) Click here for additional data file.

Cohort-specific description of maternal smoking variables.

(PDF) Click here for additional data file.

Associations of maternal smoking with gestational age at birth, birth weight, and childhood BMI.

BMI, body mass index. (PDF) Click here for additional data file.

Change in maternal smoking habits during pregnancy, gestational age at birth, birth weight, and childhood BMI.

BMI, body mass index. (PDF) Click here for additional data file.

Associations of maternal and paternal smoking with gestational age at birth, birth weight, and childhood BMI.

BMI, body mass index. (PDF) Click here for additional data file.

Complete cases analysis of maternal smoking with risks of birth complications and childhood overweight (with maternal age and BMI in categories).

BMI, body mass index. (PDF) Click here for additional data file.

Complete cases analysis of maternal smoking with risks of birth complications and childhood overweight (with maternal age and BMI continuously).

BMI, body mass index. (PDF) Click here for additional data file.

Contact information for data requests per cohort.

(PDF) Click here for additional data file. 2 Jan 2020 Dear Dr Jaddoe, Thank you for submitting your manuscript entitled "Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight: an individual participant data meta-analysis of 230,000 families" for consideration by PLOS Medicine. Your manuscript has now been evaluated by the PLOS Medicine editorial staff and I am writing to let you know that we would like to send your submission out for external peer review. However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire. 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Sincerely, Louise Gaynor-Brook, MBBS PhD Associate Editor PLOS Medicine plosmedicine.org ----------------------------------------------------------- Requests from the editors: General comment: Please remove all language that implies causality, throughout your manuscript. Reference should be made to associations instead. General comment: Please cite reference numbers in square brackets, leaving a space before the reference bracket, and removing spaces between reference numbers where more than one reference is cited. General comment: Please rename supplementary figures/tables as Supplementary Figure / Table, etc rather than eFigure and eTable Please revise your title according to PLOS Medicine's style, placing the study design in the subtitle (ie, after a colon). We suggest “Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: an individual participant data meta-analysis of 229,000 singleton births” or similar. Data Availability Statement: PLOS Medicine requires that the de-identified data underlying the specific results in a published article be made available, without restrictions on access, in a public repository or as Supporting Information at the time of article publication, provided it is legal and ethical to do so. Please see the policy at http://journals.plos.org/plosmedicine/s/data-availability and FAQs at http://journals.plos.org/plosmedicine/s/data-availability#loc-faqs-for-data-policy Please provide appropriate contact(s) (web or email address) to whom requests for access to de-identified data can be made. Please note that this cannot be a study author. Please remove the ‘Research in context’ section, replacing instead with a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should use non-identical language, that is distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary Please report your abstract according to PRISMA for abstracts, following the PLOS Medicine abstract structure (Background, Methods and Findings, Conclusions) http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001419 Abstract Background: Please expand upon the context of why the study is important. The final sentence should clearly state the study question. Please combine the Methods and Findings components of your Abstract under one subheading of ‘Methods and Findings’. Please include brief demographic details of the populations included in the meta-analysis (e.g. age ranges, nationalities, parity of women, etc.), years during which the studies took place, and further details of the study settings (i.e. which countries in Europe and North America; from where were women recruited e.g. hospitals, community settings, etc.) It is not clear how many studies include parental smoking and how many are just maternal or paternal - please mention this in the abstract Please include the important dependent variables that are adjusted for in the analyses. There is no need to define OR and CI in the abstract as these are standard abbreviations. In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology. Lines 41-44 - Please quantify the results presented with OR and 95% CI Please replace ‘Interpretation’ with the ‘Conclusions’ Please begin this section with "In this study, we observed ..." or similar. Please address the study implications, emphasizing what is new without overstating your conclusions. Introduction Please expand your Introduction to outline past research and explain the need for and potential importance of your study. Indicate whether your study is novel and how you determined that. If there has been a systematic review of the evidence related to your study (or you have conducted one), please refer to and reference that review and indicate whether it supports the need for your study. Line 59 - please provide the range for % women who smoke during pregnancy, or revise the term ‘range’ Line 61 - Please revise or remove sentence "Also, since paternal and maternal smoking often cluster within families, insight into the effects of combined parental smoking may help to improve family-focused prevention strategies", as prevention strategies are not included in the scope of this study. Methods Please incorporate eFigure 1 into the main text of your manuscript. Please add the following statement, or similar, to the Methods: "This study is reported as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline (S1 Checklist)." When completing the PRISMA checklist, please use section and paragraph numbers, rather than page numbers. Please complete your PRISMA checklist - several boxes not ticked. We note that some form of search strategy was used (even if not like a conventional meta-analysis) - please elaborate on how cohorts were identified (line 75 - "cohort studies were invited") and how eligibility for inclusion in the meta-analysis was decided? Please expand upon the methods used to check quality and heterogeneity, which are paramount for meta-analyses. We note that all covariates are categorised. Please ensure that certain variables such as age not categorised (please refer to report from Reviewer 1) Please confirm that written or oral informed consent was obtained in all cohort studies included. Results Lines 161-7 - Please quantify the results presented with OR and 95% CI All tables - please define all abbreviations used in the table legend (except cohort names). Please incorporate supplementary figures into the main text. Discussion Please remove all subheadings throughout your discussion. Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion. Requests from the academic editor: The authors imply causation in several places - eg "Quitting smoking in the first trimester place mothers at the same risk of preterm birth and small size for gestational age as non-smoking mothers." I think the language should be tempered throughout to make it clear that the findings are based on observational data and associations can be seen, but causation cannot be assessed. The authors do discuss, that "shared family-based lifestyle and genetic characteristics are potential underlying mechanisms" for childhood overweight; and this makes sense. However, the abstract implies that maternal and paternal smoking are directly linked to childhood overweight. Comments from the reviewers: Reviewer #1: See attachment Michael Dewey Reviewer #2: This study stems from the knowledge that prenatal exposure to maternal smoking carries risks for the baby and it investigates the important question of whether quitting smoking during early pregnancy reduces the risks of birth complications and childhood obesity, compared to continued smoking. The authors have conducted a powerful study by meta-analysing data from 28 European cohorts reaching an impressive N=229158 families. They conclude that quitting early in pregnancy is beneficial in reducing the risk of low birth weight. This study is commendable since it is powerful and addresses an important and needed question with immediate clinical relevance. However, before its publication I would like the authors to carry out revisions according to the following points: Main considerations: 1) The authors mention in the Introduction that smoking leads to, amongst other outcomes, congenital abnormalities, still birth and sudden infant death syndrome, which are major complications, but the study focuses on pre-term birth, low birth weight and childhood overweight, potentially less life-threatening. What was the reason to leave out the most detrimental outcomes from this study? If this study is to be translated to a clinical application it would need to be relevant to families in reducing risks of major complications. Perhaps the authors could emphasised how detrimental pre-term births, low birth weight and being overweight in childhood are for long-term health to add context to this research. 2) The Methods (either main text or supplemental) section needs an explanation per cohort on how smoking and the covariates were measured and derived. It is very unlikely that the type of information is the same across all these numerous studies. For instance, was the question asked to the mothers whether they smoked in the first trimester and similarly for the later time-points or was the question whether they smoked in the last two weeks or currently relative to a questionnaire? Some studies contain many variables related to smoking, so it is important to know what was used to create the smoking variables used here. Even if questionnaires are aimed at first trimester, depending on the study they might have been returned at various times during pregnancy. Some women might have been enrolled late in the study etc. so the accuracy of the time of this self-reported information in relation to the time in pregnancy can vary and it is important to specify all this information to understand the results and to be able to reproduce the study. Particularly as some cohorts are much bigger in size than others and they might have affected the results more. 3) At lines 136-137: What was the reason for categorising the missing participants as an additional group rather than conducting multiple imputation? This approach could add bias in the estimates as shown for instance by Groenfeld et al (CMAJ. 2012 Aug 7; 184(11): 1265-1269)? 4) The authors have not commented on the limitation that for some of the analyses the sample size was very small (for instance in the dose-stratified analyses in Table 3) and when they compare the effect of a change in habit between first-trimester-only smoking to continued or the effect of a dose change they are effectively comparing the different associations (odds ratios). However, differences in samples sizes lead to differences in power and therefore the associations are not always comparable. They should make conclusions only regarding the associations for which there is enough evidence to conclude that there is a risk, for instance the effect of continued smoking (based on N~5000) on small for gestational age. They cannot rule out an effect of smoking only in the first trimester (based on N~200). 5) Some of the effects considered have confidence interval very close to 1, so the authors should be more cautious in concluding a risk since even if there was an effect it might be small and not necessarily meaningful. 6) Could the effect of paternal smoking on 'childhood overweight' suggest that there is some residual confounding? 7) The authors should state clearly in the abstract, discussion and conclusions that this is an observational study, rather than causal, and the difference in associations between different smoking behaviours might be due to familial characteristics rather than different exposure to smoke, which could be measured by cotinine levels for instance, at different timepoints in pregnancy in relation to birth outcomes. 8) Could the authors investigate more the issue of high heterogeneity in the small for gestational age analysis by conducting some sensitivity analysis? For instance they could conduct the analysis only including the cohorts that have both data (first trimester and continued) and compare the associations found across these to check that they remain similar to what they have found. The authors should consider the effect that excluding large cohorts from the first trimester data could have on the continued smoking analyses. Other points: 9) At lines 104-105: what category was used as reference for gestational age? The authors mentioned the definition used for SGA and that "appropriate and large size for gestational age were used as the reference group". Do they mean that everyone else not in the category for SGA was the reference group? 10) At lines 159-160: Could the authors add info on heterogeneity in the other models too? Could they also add in the Discussion what could have contributed to the high heterogeneity for the small for gestational age outcome? Reviewer #3: This is an individual participant data meta-analysis of prospective cohort studies to examine the associations of prenatal parental smoking with adverse birth outcomes and childhood overweight. It is a well-described manuscript, with large study sample. It would be much better if the authors more discuss the biological mechanisms in the discussion session. For example, the authors referred to cadmium and DNA methylation, which is very interesting, but do they explain the different results in the associations of the outcomes? Any attachments provided with reviews can be seen via the following link: [LINK] Submitted filename: philips.pdf Click here for additional data file. 14 Apr 2020 Submitted filename: response letter.docx Click here for additional data file. 21 May 2020 Dear Dr. Jaddoe, Thank you very much for re-submitting your manuscript "Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: an individual participant data meta-analysis of 229,000 singleton births" (PMEDICINE-D-19-04667R2) for consideration at PLOS Medicine. I have discussed the paper with our academic editor and it was also seen again by three reviewers. I am pleased to tell you that, provided the remaining editorial and production issues are fully dealt with, we expect to be able to accept the paper for publication in the journal. The remaining issues that need to be addressed are listed at the end of this email. 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If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it. Please let me know if you have any questions. Otherwise, we look forward to receiving the revised manuscript shortly. Sincerely, Richard Turner, PhD Senior Editor, PLOS Medicine rturner@plos.org ------------------------------------------------------------ Requests from Editors: Please confirm whether or not all authors have agreed to the removal of Michelle Taylor as an author. At line 20, for example, please avoid "effect" (estimate) given the research design, in favour of "risk estimate", say. In your abstract and throughout the paper, please quote p values alongside 95% CI, where available. Early in the methods section of the main text, please state whether or not the study had a protocol or prespecified analysis plan (and if so attach the document as a supplementary file, referred to in the text). Please highlight analyses that were not prespecified. At line 143, would that be written informed consent? Please add "In this study ..." or similar to begin the sentence at line 380. Please adapt your text around line 470 to signpost the discussion of study limitations, e.g., by adding "among study limitations ...". At line 472, please adapt the text to "our study might have been underpowered" or similar. Please read through the text and adapt punctuation where necessary; for example, at line 33 "...at the start, rather than during, pregnancy." would seem more readable. Competing interest information - currently at the end of the ms - should appear only in the metadata (via the submission form). Please move the "details of ethics approval" statement at the end of the ms to the methods section of the main text, and state whether consent was informed. Please move the lengthy acknowledgements and funding information at the end of the main text to a supplementary file. As for the rest of the article, please adapt the figures so that p values are quoted as "p<0.001" where appropriate. Comments from Reviewers: *** Reviewer #1: The authors have addressed all my points. Michael Dewey *** Reviewer #2: The authors have done a good job in addressing the comments. Please consider these corrections too: Abstract, line 20: what effect sizes are smaller than what? As it reads it does not look like 1.89, 1.93 and 2.79 are that much smaller compared to 2.15, with overlapping confidence intervals. The authors should rephrase these results in a more easily interpretable way. Line 121: usually maternal smoking is assumed to affect the foetus because of in-utero effects. What was the reason for choosing also paternal smoking? Initially I thought it was a negative control, i.e. if effects of paternal are similar to maternal ones there is less causal evidence as these could be attributable to shared confounding such as low socioeconomic status. Could the authors state more clearly the rationale for choosing to investigate paternal smoking too and discussing the results in the discussion in view of their initial hypothesis. *** Reviewer #3: [no further comments] *** Any attachments provided with reviews can be seen via the following link: [LINK] 18 Jun 2020 Submitted filename: Responses to production issues.docx Click here for additional data file. 9 Jul 2020 Dear Dr. Jaddoe, On behalf of my colleagues and the academic editor, Dr. Sarah J Stock, I am delighted to inform you that your manuscript entitled "Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: an individual participant data meta-analysis of 229,000 singleton births" (PMEDICINE-D-19-04667R3) has been accepted for publication in PLOS Medicine. 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Table 1

Characteristics of the participating pregnancy and birth cohorts (n = 229,158).

Maternal smokingPaternal smokingBirth outcomesChildhood BMI
Cohort name, number of participants, birth years (country)NoFirst trimester onlyContinuedNoYesGestational age at birth (weeks)Preterm birthBirth weight (g)Small size for gestational age at birthAge (months)BMI (SDS)Overweight
ABCD, n = 7,324, 2003–2004 (the Netherlands)6,571 (89.7)NA753 (10.3)NANA40.0 (35.0–42.0)385 (5.3)3,460 (2,270–4,500)732 (10.1)68.1 (61.6–82.1)0.09 (−1.69 to 2.29)706 (16.6)
ALSPAC, n = 12,148, 1991–1992 (United Kingdom)9,581 (78.9)NA2,567 (21.1)7,397 (63.2)4,301 (36.8)40.0 (35.0–42.0)650 (5.4)3,440 (2,240–4,420)1,190 (10.0)115.0 (88.0–119.0)0.24 (−1.61 to 2.66)1,960 (26.3)
BAMSE, n = 4,057, 1994–1996 (Sweden)3,533 (87.1)72 (1.8)452 (11.1)2,756 (83.1)560 (16.9)40.0 (35.0–42.0)212 (5.3)3,545 (2,334–4,550)396 (9.9)101.0 (89.0–109.0)0.52 (−1.20 to 2.63)814 (31.2)
BIB, n = 1,641, 2007–2010 (UK)1,398 (85.2)NA243 (14.8)NANA39.7 (35.3–41.9)83 (5.1)3,200 (2,180–4,280)163 (10.0)NANANA
Co.N.ER, n = 641, 2004–2005 (Italy)549 (85.6)30 (4.7)62 (9.7)441 (68.9)199 (31.1)39.0 (36.0–41.0)29 (4.5)3,340 (2,420–4,230)63 (9.9)95.0 (86.6–111.1)0.69 (−1.29 to 2.92)102 (35.5)
DNBC, n = 71,710, 1996–2002 (Denmark)59,030 (82.3)NA12,680 (17.7)49,534 (70.5)20,756 (29.5)40.1 (35.9–42.4)3,168 (4.4)3,600 (2,420–4,640)7,124 (10.0)85.0 (75.1–89.5)0.01 (−1.95 to 2.07)5,644 (15.5)
EDEN, n = 1,880, 2003–2005 (France)1,376 (73.2)148 (7.9)356 (18.9)999 (59.5)679 (40.5)39.0 (35.0–41.0)106 (5.6)3,300 (2,158–4,200)187 (10.0)67.6 (65.0–72.4)−0.01 (−1.52 to 2.02)145 (12.9)
FCOU, n = 4,003, 1993–1996 (Ukraine)3,647 (91.1)NA356 (8.9)461 (16.2)2,382 (83.8)NANA3,400 (2,100–4,300)393 (10.2)84.0 (75.0–93.0)−0.02 (−2.02 to 2.06)119 (12.7)
GASPII, n = 680, 2003–2004 (Italy)599 (88.1)23 (3.4)58 (8.5)510 (75.2)168 (24.8)40.0 (36.0–42.0)28 (4.1)3,350 (2,401–4,320)67 (9.9)104.0 (98.0–113.0)0.70 (−1.37 to 2.66)172 (37.1)
GENERATION R, n = 7,934, 2002–2006 (The Netherlands)6,190 (78.0)461 (5.8)1,283 (16.2)2,833 (56.5)2,183 (43.5)40.1 (35.4–42.3)474 (6.0)3,420 (2,190–4,480)788 (10.0)115.3 (69.4–119.4)0.35 (−1.52 to 2.67)1,578 (27.1)
GENERATION XXI, n = 7,541, 2005–2006 (Portugal)5,766 (76.5)540 (7.2)1,235 (16.4)NANA39.0 (35.0–41.0)557 (7.4)3,200 (2,130–4,095)747 (10.0)85.0 (70.2–95.0)0.63 (−1.38 to 3.23)1,991 (37.9)
GENESIS, n = 2,261, 2003–2004 (Greece)1,842 (81.5)30 (1.3)389 (17.2)NANA40.0 (34.0–40.0)224 (10.0)3,250 (2,100–4,200)213 (10.0)61.9 (60.1–71.9)0.93 (−1.43 to 4.11)39 (43.3)
GINIplus, n = 2,086, 1995–1998 (Germany)1,903 (91.2)NA193 (8.8)NANANANANANA62.9 (60.2–74.4)0.01 (−1.77 to 1.93)215 (10.3)
HUMIS, n = 986, 2002–2009 (Norway)932 (94.5)NA54 (5.5)NANA40.1 (33.2–42.9)86 (8.7)3,580 (1,822–4,703)98 (10.0)84.0 (60.0–92.0)0.02 (−2.03 to 2.14)58 (17.5)
INMA, n = 2,406, 1997–2008 (Spain)1,988 (82.6)NA418 (17.4)1,395 (58.0)1,009 (42.0)39.9 (36.0–42.0)98 (4.1)3,250 (2,300–4,200)238 (10.0)83.6 (75.1–94.5)0.55 (−1.37 to 3.31)489 (37.7)
KOALA, n = 2,800, 2000–2002 (the Netherlands)2,594 (92.6)NA206 (7.4)NANA40.0 (36.0–42.0)89 (3.2)3,500 (2,478–4,510)277 (10.0)106.2 (61.5–119.3)−0.17 (−2.16 to 1.77)199 (11.4)
LISAplus, n = 1,965, 1997–1999 (Germany)1,697 (86.4)87 (4.4)181 (9.2)1,557 (82.0)342 (18.0)NANANANA62.7 (60.2–74.0)−0.09 (−1.92 to 1.88)201 (10.2)
LUKAS, n = 441, 2002–2005 (Finland)371 (84.1)35 (7.9)35 (7.9)NANANANA3,630 (2,790–4,689)44 (10.0)73.2 (68.6–76.0)0.52 (−1.08 to 3.33)114 (31.4)
MoBa, n = 80,116, 1999–2009 (Norway)72,466 (90.5)NA7,650 (9.5)63,071 (79.2)16,523 (20.8)40.1 (36.1–42.4)3,312 (4.1)3,620 (2,521–4,640)7,967 (10.0)85.9 (61.0–100.9)0.15 (−2.05 to 2.30)6,002 (19.5)
NINFEA, n = 2,259, 2005–2010 (Italy)a2,085 (92.3)29 (1.3)145 (6.4)NANA39.7 (35.9–41.9)91 (4.0)3,240 (2,271–4,189)220 (10.0)86.1 (84.8–93.1)−0.02 (−2.16 to 2.43)95 (21.5)
PÉLAGIE, n = 1,353, 2002–2005 (France)1,022 (75.2)172 (12.7)159 (11.8)597 (61.8)369 (38.2)40.0 (36.0–41.0)44 (3.3)3,400 (2,460–4,315)135 (10.0)NANANA
Piccolipiù, n = 3,292, 2011–2015 (Italy)2,572 (78.1)374 (11.4)346 (10.5)1,496 (71.4)598 (28.6)39.0 (36.0–41.0)93 (2.9)3,340 (2,470–4,229)323 (10.0)NANANA
PRIDE Study, n = 1,616, 2011–2015 (the Netherlands)1,519 (94.0)39 (2.4)58 (3.6)NANA39.0 (35.6–41.0)77 (4.9)3,484 (2,280–4,500)154 (9.9)NANANA
Project Viva, n = 2,001, 1999–2002 (USA)1,784 (89.2)124 (6.2)93 (4.6)NANA39.7 (34.7–41.9)142 (7.1)3,487 (2,155–4,536)199 (10.0)92.2 (82.5–116.5)0.42 (−1.38 to 3.04)315 (30.6)
REPRO_PL, n = 1,434, 2007–2011 (Poland)1,215 (84.7)83 (5.8)136 (9.5)866 (63.0)509 (37.0)39.0 (36.0–41.0)64 (4.5)3,350 (2,376–4,290)142 (10.0)88.0 (84.3–94.0)0.64 (−1.55 to 3.64)19 (38.8)
RHEA, n = 651, 2007–2008 (Greece)544 (83.6)NA107 (16.4)287 (48.6)303 (51.4)38.0 (35.0–40.0)73 (11.3)3,190 (2,312–4,059)63 (9.9)NANANA
SCOPE BASELINE, n = 1,216, 2009–2011 (Ireland)1,078 (88.7)NA138 (11.3)739 (78.5)203 (21.5)40.3 (35.2–41.7)60 (4.9)3,460 (2,353–4,485)121 (10.0)NANANA
SWS, n = 2,716, 1998–2007 (UK)2,316 (85.3)NA400 (14.7)NANA40.1 (35.1–42.1)154 (5.7)3,450 (2,330–4,475)268 (10.0)80.3 (74.7–87.2)0.21 (−1.51 to 2.47)368 (22.0)
Total group196,168 (85.6)2,247 (1.0)30,743 (13.4)134,939 (72.5)51,084 (27.5)40.0 (35.7–42.3)10,299 (4.7)3,530 (2,390–4,580)22,312 (10.0)85.2 (61.0–117.7)0.13 (−1.86 to 2.43)21,345 (20.0)

Values are expressed as number of participants (valid %) or medians (95% range). “First trimester only” refers to mothers who smoked during first trimester only. Childhood overweight also includes obesity and includes information at child age ≥5 to <10 years. Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight SDS per cohort.

a Subset of participants with follow-up completed at 4 years of child’s age by the time of data transfer (March 2015).

Abbreviations: BMI, body mass index; NA, not available (not collected or not provided) or not applicable (gestational age at birth [FCOU, GINIplus, LISAplus, LUKAS] and birth weight [GINIplus, LISAplus] due to study samples restricted to specific ranges of gestational age and weight at birth); SDS, standard deviation score

Table 2

Maternal smoking with risks of birth complications and childhood overweight.

Maternal smokingPreterm birthSmall size for gestational age at birthChildhood overweight
Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)
No maternal smokingReferenceReferenceReference
ncases/total = 8,586/188,357ncases/total = 16,879/190,873ncases/total = 17,530/92,434
Only first trimester smoking1.03 (0.85–1.25)0.99 (0.85–1.15)1.17 (1.02–1.35)*
ncases/total = 120/2,116ncases/total = 200/2,144ncases/total = 329/1,084
First trimester dosage
    ≤4 cigarettes/day0.99 (0.70–1.39)0.96 (0.75–1.22)1.02 (0.78–1.33)
ncases/total = 36/828ncases/total = 77/826ncases/total = 78/340
    5–9 cigarettes/day1.00 (0.58–1.72)0.90 (0.59–1.36)1.37 (0.92–2.06)
ncases/total = 14/288ncases/total = 25/288ncases/total = 35/136
    ≥10 cigarettes/day0.81 (0.45–1.46)0.88 (0.57–1.35)1.31 (0.89–1.93)
ncases/total = 12/273ncases/total = 23/271ncases/total = 40/152
Continued smoking1.08 (1.02–1.15)*2.15 (2.07–2.23)**1.42 (1.35–1.48)**
ncases/total = 1,593/29,951ncases/total = 5,233/30,125ncases/total = 3,486/13,083
Continued smoking dosage
    ≤4 cigarettes/day1.01 (0.89–1.14)1.57 (1.45–1.70)**1.30 (1.18–1.42)**
ncases/total = 288/5,866ncases/total = 836/6,034ncases/total = 688/2,792
    5–9 cigarettes/day1.07 (0.95–1.19)2.40 (2.25–2.56)**1.42 (1.30–1.55)**
ncases/total = 367/7,115ncases/total = 1,341/7,162ncases/total = 813/3,284
    ≥10 cigarettes/day1.11 (1.01–1.22)*2.93 (2.76–3.10)**1.55 (1.43–1.67)**
ncases/total = 524/9,771ncases/total = 2,001/9,743ncases/total = 1,137/4,139

Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per smoking group compared with the reference group (no maternal smoking).

Number of cigarettes used as continued smoking dosage was based on third trimester information. Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, educational level, parity, prepregnancy or early-pregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking.

*P value < 0.05.

**P value < 0.001.

Table 3

Change in maternal smoking habits during pregnancy and risks of birth complications and childhood overweight.

Maternal smokingPreterm birthSmall size for gestational age at birthChildhood overweight
Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)
No maternal smoking in first trimester
    Third trimester no smokingReferenceReferenceReference
ncases/total = 4,527/100,634ncases/total = 8,698/103,740ncases/total = 11,177/59,070
    Third trimester ≤4 cigarettes/day0.73 (0.40–1.34)1.20 (0.81–1.78)1.31 (0.90–1.92)
ncases/total = 11/278ncases/total = 28/274ncases/total = 41/147
    Third trimester 5–9 cigarettes/day1.07 (0.48–2.48)2.02 (1.18–3.46)*1.27 (0.64–2.37)
ncases/total = 6/104ncases/total = 16/103ncases/total = 13/51
    Third trimester ≥10 cigarettes/day1.51 (0.65–3.49)1.74 (0.91–3.32)1.60 (0.72–3.55)
ncases/total = 6/80ncases/total = 11/79ncases/total = 10/31
Maternal smoking in first trimester ≤4 cigarettes/day
    Third trimester quit0.96 (0.69–1.35)1.04 (0.82–1.31)1.20 (0.94–1.53)
ncases/total = 38/862ncases/total = 84/859ncases/total = 98/388
    Third trimester ≤4 cigarettes/day1.05 (0.86–1.27)1.54 (1.37–1.74)**1.32 (1.14–1.52)**
ncases/total = 114/2,261ncases/total = 328/2,457ncases/total = 289/1,169
    Third trimester 5–9 cigarettes/day1.15 (0.85–1.55)2.43 (2.05–2.89)**1.81 (1.45–2.25)**
ncases/total = 47/885ncases/total = 170/880ncases/total = 121/440
    Third trimester ≥10 cigarettes/day1.37 (0.76–2.47)2.47 (1.71–3.58)**1.31 (0.79–2.19)
ncases/total = 12/186ncases/total = 36/185ncases/total = 21/86
Maternal smoking in first trimester 5–9 cigarettes/day
    Third trimester quit1.04 (0.62–1.73)0.95 (0.64–1.42)1.32 (0.91–1.92)
ncases/total = 16/304ncases/total = 27/304ncases/total = 41/165
    Third trimester ≤4 cigarettes/day0.86 (0.58–1.28)1.89 (1.52–2.34)**1.53 (1.17–2.00)*
ncases/total = 27/657ncases/total = 102/654ncases/total = 80/307
    Third trimester 5–9 cigarettes/day1.00 (0.85–1.18)2.21 (2.02–2.42)**1.43 (1.26–1.61)**
ncases/total = 163/3,551ncases/total = 630/3,617ncases/total = 403/1,704
    Third trimester ≥10 cigarettes/day0.99 (0.76–1.30)2.70 (2.35–3.10)**1.40 (1.15–1.69)*
ncases/total = 59/1,330ncases/total = 265/1,319ncases/total = 149/632
Maternal smoking in first trimester ≥10 cigarettes/day
    Third trimester quit0.82 (0.46–1.43)1.06 (0.71–1.57)1.34 (0.96–1.88)
ncases/total = 13/285ncases/total = 28/283ncases/total = 52/194
    Third trimester ≤4 cigarettes/day1.26 (0.82–1.95)1.93 (1.46–2.57)**1.14 (0.81–1.61)
ncases/total = 22/358ncases/total = 59/354ncases/total = 48/192
    Third trimester 5–9 cigarettes/day1.26 (0.97–1.63)2.79 (2.39–3.25)**1.46 (1.18–1.80)**
ncases/total = 62/1,078ncases/total = 224/1,072ncases/total = 128/503
    Third trimester ≥10 cigarettes/day1.16 (1.04–1.31)*2.95 (2.75–3.15)**1.67 (1.53–1.83)**
ncases/total = 364/6,949ncases/total = 1,434/6,940ncases/total = 849/2,976

Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per change in smoking group compared with that of the reference group (nonsmoking in first and third trimester). Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, educational level, parity, prepregnancy body mass index, alcohol consumption during pregnancy, and paternal smoking.

*P value < 0.05.

**P value < 0.001.

Table 4

Associations of maternal and paternal smoking with risks of birth complications and childhood overweight.

Maternal and paternal smokingPreterm birthSmall size for gestational age at birthChildhood overweight
Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)Odds ratio (95% confidence interval)
Maternal nonsmoking
    Paternal nonsmokingReferenceReferenceReference
ncases/total = 5,232/123,666ncases/total = 10,746/123,328ncases/total = 10,298/59,395
    Paternal smoking1.06 (1.00–1.12)1.04 (1.00–1.09)1.21 (1.16–1.27)**
ncases/total = 1,505/31,890ncases/total = 3,030/33,691ncases/total = 3,199/15,474
Maternal first trimester smoking
    Paternal nonsmoking0.64 (0.36–1.15)0.78 (0.53–1.13)1.36 (0.98–1.87)
ncases/total = 12/412ncases/total = 30/412ncases/total = 54/233
    Paternal smoking1.03 (0.70–1.51)1.05 (0.80–1.39)1.36 (1.02–1.80)*
ncases/total = 29/626ncases/total = 59/625ncases/total = 70/305
Maternal continued smoking
    Paternal nonsmoking1.04 (0.93–1.15)2.06 (1.94–2.20)**1.33 (1.23–1.44)**
ncases/total = 405/8,768ncases/total = 1,366/8,723ncases/total = 877/3,872
    Paternal smoking1.10 (1.02–1.19)*2.37 (2.26–2.49)**1.76 (1.65–1.87)**
ncases/total = 810/15,806ncases/total = 2,896/15,967ncases/total = 1,785/6,661

Values are odds ratios (95% confidence intervals) from multilevel binary logistic mixed-effects models that reflect the risk of preterm birth, small size for gestational age, and childhood overweight per smoking group compared with the reference group (no parental smoking).

Preterm birth is defined as birth before the gestational age of 37 weeks. Small size for gestational age is defined as the lowest 10% of sex- and gestational age–adjusted birth weight standard deviation score per cohort. Childhood overweight is overweight and obesity together according to the World Health Organization criteria. Models are adjusted for maternal age, maternal body mass index, paternal body mass index, maternal education, parity, and maternal alcohol consumption during pregnancy.

*P value < 0.05.

**P value < 0.001.

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3.  Epidemiology of Obesity.

Authors:  Thorkild I A Sørensen; Andrea Rodriguez Martinez; Terese Sara Høj Jørgensen
Journal:  Handb Exp Pharmacol       Date:  2022

Review 4.  Obesity II: Establishing causal links between chemical exposures and obesity.

Authors:  Jerrold J Heindel; Sarah Howard; Keren Agay-Shay; Juan P Arrebola; Karine Audouze; Patrick J Babin; Robert Barouki; Amita Bansal; Etienne Blanc; Matthew C Cave; Saurabh Chatterjee; Nicolas Chevalier; Mahua Choudhury; David Collier; Lisa Connolly; Xavier Coumoul; Gabriella Garruti; Michael Gilbertson; Lori A Hoepner; Alison C Holloway; George Howell; Christopher D Kassotis; Mathew K Kay; Min Ji Kim; Dominique Lagadic-Gossmann; Sophie Langouet; Antoine Legrand; Zhuorui Li; Helene Le Mentec; Lars Lind; P Monica Lind; Robert H Lustig; Corinne Martin-Chouly; Vesna Munic Kos; Normand Podechard; Troy A Roepke; Robert M Sargis; Anne Starling; Craig R Tomlinson; Charbel Touma; Jan Vondracek; Frederick Vom Saal; Bruce Blumberg
Journal:  Biochem Pharmacol       Date:  2022-04-05       Impact factor: 6.100

5.  Prenatal smoking and drinking are associated with altered newborn autonomic functions.

Authors:  Ayesha Sania; Michael M Myers; Nicolò Pini; Maristella Lucchini; J David Nugent; Lauren C Shuffrey; Shreya Rao; Jennifer Barbosa; Jyoti Angal; Amy J Elliott; Hein J Odendaal; William P Fifer
Journal:  Pediatr Res       Date:  2022-04-19       Impact factor: 3.953

Review 6.  Brown Adipose Tissue: New Challenges for Prevention of Childhood Obesity. A Narrative Review.

Authors:  Elvira Verduci; Valeria Calcaterra; Elisabetta Di Profio; Giulia Fiore; Federica Rey; Vittoria Carlotta Magenes; Carolina Federica Todisco; Stephana Carelli; Gian Vincenzo Zuccotti
Journal:  Nutrients       Date:  2021-04-24       Impact factor: 5.717

7.  Foetal tobacco and cannabis exposure, body fat and cardio-metabolic health in childhood.

Authors:  Kim N Cajachagua-Torres; Hanan El Marroun; Irwin K M Reiss; Susana Santos; Vincent W V Jaddoe
Journal:  Pediatr Obes       Date:  2021-10-21       Impact factor: 3.910

Review 8.  Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review.

Authors:  Aurélie Nakamura; Olivier François; Johanna Lepeule
Journal:  Int J Environ Res Public Health       Date:  2021-05-11       Impact factor: 3.390

9.  The Effects of Different Smoking Patterns in Pregnancy on Perinatal Outcomes in the Southampton Women's Survey.

Authors:  Martin M O'Donnell; Janis Baird; Cyrus Cooper; Sarah R Crozier; Keith M Godfrey; Michael Geary; Hazel M Inskip; Catherine B Hayes
Journal:  Int J Environ Res Public Health       Date:  2020-10-30       Impact factor: 3.390

10.  Maternal smoking and preterm birth: An unresolved health challenge.

Authors:  Sarah J Stock; Linda Bauld
Journal:  PLoS Med       Date:  2020-09-14       Impact factor: 11.069
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