Elective and nonelective cesarean section and obesity among young adult male offspring: A Swedish population-based cohort study.

BACKGROUND: Previous studies have suggested that cesarean section (CS) is associated with offspring overweight and obesity. However, few studies have been able to differentiate between elective and nonelective CS, which may differ in their maternal risk profile and biological pathway. Therefore, we aimed to examine the association between differentiated forms of delivery with CS and risk of obesity in young adulthood. METHODS AND
FINDINGS: Using Swedish population registers, a cohort of 97,291 males born between 1982 and 1987 were followed from birth until conscription (median 18 years of age) if they conscripted before 2006. At conscription, weight and height were measured and transformed to World Health Organization categories of body mass index (BMI). Maternal and infant data were obtained from the Medical Birth Register. Associations were evaluated using multinomial and linear regressions. Furthermore, a series of sensitivity analyses were conducted, including fixed-effects regressions to account for confounders shared between full brothers. The mothers of the conscripts were on average 28.5 (standard deviation 4.9) years old at delivery and had a prepregnancy BMI of 21.9 (standard deviation 3.0), and 41.5% of the conscripts had at least one parent with university-level education. Out of the 97,291 conscripts we observed, 4.9% were obese (BMI ≥ 30) at conscription. The prevalence of obesity varied slightly between vaginal delivery, elective CS, and nonelective CS (4.9%, 5.5%, and 5.6%, respectively), whereas BMI seemed to be consistent across modes of delivery. We found no evidence of an association between nonelective or elective CS and young adulthood obesity (relative risk ratio 0.96, confidence interval 95% 0.83-1.10, p = 0.532 and relative risk ratio 1.02, confidence interval 95% 0.88-1.18, p = 0.826, respectively) as compared with vaginal delivery after accounting for prepregnancy maternal BMI, maternal diabetes at delivery, maternal hypertension at delivery, maternal smoking, parity, parental education, maternal age at delivery, gestational age, birth weight standardized according to gestational age, and preeclampsia. We found no evidence of an association between any form of CS and overweight (BMI ≥ 25) as compared with vaginal delivery. Sibling analysis and several sensitivity analyses did not alter our findings. The main limitations of our study were that not all conscripts had available measures of anthropometry and/or important confounders (42% retained) and that our cohort only included a male population.
CONCLUSIONS: We found no evidence of an association between elective or nonelective CS and young adulthood obesity in young male conscripts when accounting for maternal and prenatal factors. This suggests that there is no clinically relevant association between CS and the development of obesity. Further large-scale studies are warranted to examine the association between differentiated forms of CS and obesity in young adult offspring. TRIAL REGISTRATION: Registered as observational study at ClinicalTrials.gov Identifier: NCT03918044.

Introduction

Globally [1], and in Sweden [2], there has been an unprecedented increase in the prevalence of cesarean deliveries since the early 1990s. Between 1990 and 2014 the world prevalence of cesarean section (CS) increased by 285% (6.7% versus 19.1% of all births) [1], albeit with large regional disparities. The indications for CS are many, and CS is often warranted to avoid fetal and/or maternal morbidity and mortality [3]. However, indications for CS are to some degree subjective [4], and changes in maternal risk profiles do not explain the increased prevalence of CS [5,6]. Maternal preference and/or fear of childbirth has been described to be a contributing factor to the increase in CS rates [7-9]. Notably, the World Health Organization (WHO) states that, on a population level, rates of CS higher than 10%–15% are not associated with additional reductions in maternal, neonatal, and infant mortality rates [3].

The large increases of CS have sparked an interest in its long-term effects on offspring health [3]. Indeed, CS has been associated with various negative outcomes—e.g., asthma [10,11], allergic rhinitis [11], and food allergies [12], as well as overweight and obesity [10,13-16]. Proposed mechanisms explaining the observed association between CS and subsequent morbidity in the offspring include, but are not limited to, hormonal surge [17], lack of stress exposure [17], DNA methylation [18-20], and microflora transmission (hygiene hypothesis) [20,21].

The association between CS and offspring overweight and obesity has recently received further attention [10,15,22-25]. Notably, the unprecedented increase in CS has occurred at the same time as the obesity epidemic [26], which may suggest a connection between the two trends. However, as previous studies have noted [22,23,25], the association between CS and obesity may be mainly driven by unmeasured confounding. Yuan and colleagues [15] conducted a careful investigation aiming to control for such confounding, but they still observed an association between CS and offspring obesity. Yuan and colleagues [15] did not, however, differentiate between elective and nonelective CS. To the best of our knowledge, only a few studies have investigated effects of elective and nonelective CS separately [23-25]. This is unfortunate because the indications for and the obstetric risks of CS may depend on the type of CS, which could make the confounding structure differ importantly between the types of CS. Notably, one of the likely candidates for unmeasured confounding is confounding by indication, which could inflate the risk for obesity in the nonelective CS group [23], given that nonelective CS may be more likely to be conducted on the basis of fetal indication and obstetric complications [27,28]. Additionally, elective and nonelective CS may differ in fetal stress exposure [29] and microflora transmission [30], which could have implications for associations to subsequent obesity. Furthermore, given the rise in CS [1], there could be different implications for public health in the presence of different risks of development of obesity depending on the type of CS delivery. Despite few studies differentiating between elective and nonelective CS, at 12 months [24] but not at 3 and 5 years of age [23], there have been reported elevated risks of obesity in elective CS. However, large-scale longitudinal studies are warranted, and there is a necessity to examine whether this indicated association persists into young adulthood.

Objective

Here, we aim to examine the association between differentiated forms of delivery with CS and risk of obesity in young adulthood in a large, total-population sample of male conscripts based on objectively measured anthropometry. We evaluate the role of confounding by indication by separately studying elective and nonelective CS, carefully controlling for confounding factors including prepregnancy maternal body mass index (BMI), and by sibling comparisons, hence adjusting for shared familial factors.

Methods

Study design

A male total population–based cohort was constructed using the following Swedish population–based registries: (1) the Swedish Military Service Conscription Registry [31], (2) the Swedish Medical Birth Register (MBR) [32], (3) the Multi-Generation Register [33], and (4) the population and housing censuses from 1970 and 1990 [33]. Registers were linked via a personal identification number, a unique ID code assigned to each Swedish resident at birth. Furthermore, all full brothers and parents were identified and matched using a unique family identification number through the Multi-Generation Register. The study was approved by the Regional Ethical Review Board, Stockholm (Dnr: 2016/1445-31/1). The study protocol and statistical analysis plan were registered on April 17, 2019, at clinicaltrials.gov (NCT03918044) to increase transparency and reduce the risk for post hoc analysis.

Study population

Using the MBR, which contains validated birth data on approximately 99% of the Swedish population [32], all male singletons born between 1982 and 1987 available in the MBR were sampled (n = 300,344) (Fig 1). The first exclusion criterion was not having available information on the mode of delivery (n = 16,970). The sampled singletons were then matched to their conscription data if they conscripted before 2006 using the Swedish Military Service Conscription Registry (n = 229,632). During the study period, conscription was mandatory by law in Sweden for all male citizens up to the age of 47 [34]. The study period was selected because of the changes in conscription procedures occurring after the set period. During the study period, males could only be exempt from conscriptions (requiring state approval) if they suffered from chronic disease or severe handicap [35]. Except for in sensitivity analyses, we excluded those with extreme values of weight (≤40 or ≥150 kg), height (≤150 or ≥210 cm), and/or BMI (≤15 or ≥60 kg/m2) at conscription (n = 105) in accordance with previous studies [36]. All analyses were conducted as complete-case analyses because we a priori hypothesized any missing data to be missing completely at random and potentially missing not at random in a few cases; therefore, we excluded all individuals with missing height and/or weight at conscription (n = 76,410) and/or those with missing information on other characteristics of interest (e.g., maternal BMI and maternal smoking) (n = 55,826) (S1 Table). In total, 97,291 male conscripts with a median age of 18 years at follow-up (i.e., conscription) remained eligible for analysis and were included in the final analytical sample. In addition, we identified 9,676 matchable full brothers.

Fig 1

Flowchart of the derivation of the analytical sample.

BMI, body mass index.

Exposure—Mode of delivery

Using the Swedish MBR, we obtained information on recorded mode of delivery (vaginal or cesarean delivery), which was supplemented with information on indication for cesarean delivery (elective or nonelective), which yielded our primary trichotomized exposure coded as (1) vaginal delivery, (2) delivery by elective CS, and (3) delivery by nonelective CS. In accordance with the reporting standard in the MBR, we define elective CS as prelabor CS and nonelective CS as CS after the onset of labor. There was no alteration in the reporting procedure of elective or nonelective CS in the MBR during the period of study. Additionally, to facilitate comparison with previous studies, we report the dichotomized exposure: (1) vaginal delivery and (2) delivery by any form of CS. Finally, in a post hoc sensitivity analysis, the exposures (1) vaginal delivery, (2) instrumental vaginal delivery (forceps or vacuum extraction), (3) delivery by elective CS, and (4) delivery by nonelective CS were used to diminish the assumption of homogeneity in vaginal deliveries.

Outcome—Young adulthood BMI

The primary outcome was obesity defined according to categories of BMI (kg/m2) categorized using WHO’s [37] standards: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), and obese (BMI ≥ 30). Although our aim is to examine obesity, we quantify associations between CS and all categories of BMI as compared with normal weight BMI. Weight in kilograms and height in centimetres were measured at conscription using a standardized scale and a stadiometer [36] under supervision of a nurse or physician [38]. To facilitate comparisons with previous studies, we also examined the odds of obesity (BMI ≥ 30) using all other BMI categories as reference outcome (BMI < 30). Finally, we estimated the association between our primary exposure (vaginal/elective CS/nonelective CS) and BMI at conscription as a continuous variable.

Confounders

We considered a series of confounders that have been previously associated with cesarean delivery and metabolic or adiposity-related factors in offspring. From the MBR data on prepregnancy maternal BMI [39,40] (continuous), maternal diabetes at delivery [41,42] (yes/no), maternal hypertension at delivery [43] (yes/no), self-reported maternal smoking [44,45] at the commencement of pregnancy (nonsmoker, 1–9 cig/day, ≥10 cig/day), parity [46,47] (treated as categorical), birth weight in grams [48,49] standardized according to week of gestational age using the total population as reference (continuous), preeclampsia [50,51] (ICD-8: 63703–63710 and ICD-9 642E-642G) (yes/no), gestational age [49,52] (continuous), and maternal age at delivery [53,54] (continuous) were collected. Using the population and housing censuses, we identified the highest level of paternal and maternal education [55,56] (categorical) to serve as a proxy for household socioeconomic status.

Statistical analyses

We descriptively present the distribution of the outcomes and confounders over the total analytic cohort and over the primary exposures (vaginal, elective CS, and nonelective CS) using appropriate measures of central tendency and dispersion. For our main analysis, we employed multinomial logistic regression to estimate crude and confounder-adjusted relative risk ratios (RRRs) with 95% confidence intervals (CIs). All standard errors were estimated using the robust (sandwich) method to account for the correlation between brothers [57]. All statistical analyses were performed using Stata 15.1 (Stata Corp, College Station, TX, United States).

Sensitivity analyses

We descriptively present the available characteristics of the individuals not participating in conscription and those excluded due to missing data and compare these to the conscripted and analytic sample, respectively, using χ2 test (categorical), t test (continuous), and Wilcoxon rank-sum test (continuous skewed). In the sensitivity analysis, we introduced several multinomial logistic models. First, a model in which we introduced a cubic transformation of maternal age and maternal BMI, in addition to the untransformed factor, to relax the assumption of linearity was used. Second, a model in which we adjusted for gestational weight gain [58] in a subset of individuals with available measures of maternal BMI at delivery (n = 96,050) standardized by categories of BMI and gestational week according to Swedish reference values [59] was used. Third, using information on previous cesarean deliveries recorded after 1973, we adjusted for whether a mother had ever had a CS before (binary). Previous cesarean delivery may impact the association between a subsequent cesarean delivery and obesity [15]. Fourth, we included those with available data previously excluded for extreme values at conscription (n = 62) to ascertain that our exclusion did not alter our primary findings. In our final multinomial model, we examined the association between any form of cesarean delivery and BMI categories. For our secondary outcomes, we employed logistic regression to examine the association between our primary exposure and obesity and linear regression, treating BMI as a continuous outcome. Furthermore, we employed multinomial logistic regression with fixed effects (conditional) [60] and fixed-effects linear regression [22] in a subset of 3,346 and 9,676 discordant full brothers, respectively, to account for unmeasured familial confounding (genetic and environmental) [61]. The fixed-effects regressions were adjusted for the same factors as our main analysis, excluding highest parental education, which did not vary between full brothers. In the post hoc analysis, we examine the influence of CS on ordered BMI categories, employing a generalized ordered logit model that was relaxed of proportionality assumptions [62], and we further relaxed linearity of all continuous factors (maternal prepregnancy BMI, maternal age, birth weight standardized according to gestational age, and gestational age) using restricted cubic splines with five knots at Harrell’s recommended positions [63]: 5th, 27.5th, 50th, 72.5th, and 95th percentiles. Because previous validity reports [32] have noted that there may be some misclassification of the type of CS in the MBR and that this misclassification is primarily present in preterm deliveries that were misclassified as elective while being nonelective, we repeated our main analysis excluding those born preterm (<37 full weeks of gestation) and repeated our main analysis restricted to those born at term (≥37 and <42 weeks of gestation). Finally, as gestational age may act as a collider under certain causal pathways, we repeated our main analysis, excluding adjustment for gestational age.

Compliance with ethical standards

The study was approved by the Regional Ethical Review Board, Stockholm (Dnr: 2016/1445-31/1). The requirement to obtain informed consent was waived by the Regional Ethical Review Board, Stockholm (Dnr: 2016/1445-31/1). All research was performed in accordance with relevant guidelines/regulations.

Results

Descriptive statistics

In our cohort of 97,291 conscripts, we observed that 4.9% were obese at conscription (Table 1). The prevalence of obesity among those born by vaginal delivery was 4.9% (CI 95% 4.7–5.0), which was not statistically significantly different from those born by elective CS (5.5%, CI 95% 4.8–6.2, p = 0.057). The prevalence of obesity among those born by nonelective CS was 5.6% (CI 95% 4.9–6.3), which was statistically significantly higher as compared with those born by vaginal delivery (p = 0.032). The mean BMI was lower among those born by vaginal delivery (22.8, CI 95% 22.8–22.8) as compared with those born by elective CS (23.0, CI 95% 22.9–23.1, p = 0.010) or nonelective CS (23.1, CI 95% 22.9–23.2, p < 0.001). Although statistically different (all p < 0.05), most covariates did not vary substantially with mode of delivery. However, those with vaginal delivery had higher birth weight, lower maternal BMI, and lower occurrence of maternal prepregnancy obesity. The elective CS group had higher occurrence of university-level parental education and of maternal diabetes mellitus. The nonelective CS group had a higher occurrence of preeclampsia and maternal smoking at the commencement of pregnancy.

Table 1

Sample characteristics of the full analytical cohort by mode of delivery.

Sample characteristics	Total (N = 97,291)	Vaginal delivery (N = 89,024)	Elective cesarean section (N = 4,147)	Nonelective cesarean section (N = 4,120)
Offspring characteristics
Age at conscription (years), median (IQR)	18 (18, 18)	18.0 (18, 18)	18 (18, 18)	18 (18, 18)
BMI category at conscription, No. (%)
Underweight	5,945 (6.1)	5,491 (6.2)	224 (5.4)	230 (5.6)
Normal weight	71,511 (73.5)	65,479 (73.6)	3,044 (73.4)	2,988 (72.5)
Overweight	15,041 (15.5)	13,720 (15.4)	650 (15.7)	671 (16.3)
Obese	4,794 (4.9)	4,334 (4.9)	229 (5.5)	231 (5.6)
BMI (kg/m2) at conscription, mean (SD)	22.8 (3.7)	22.8 (3.6)	23.0 (3.8)	23.1 (3.8)
Birth weight (g), mean (SD)	3,615.9 (518.3)	3,633.1 (499.4)	3,444.0 (554.7)	3,416.8 (754.1)
Weeks of gestation, mean (SD)	39.5 (1.6)	39.6 (1.5)	38.2 (1.3)	39.0 (2.6)
Maternal characteristics
Maternal age at birth (years), mean (SD)	28.5 (4.9)	28.4 (4.9)	30.6 (5.3)	28.7 (5.2)
Maternal prepregnancy BMI, mean (SD)	21.9 (3.0)	21.9 (3.0)	22.3 (3.4)	22.4 (3.2)
Maternal BMI category, No. (%)
Underweight	7,450 (7.7)	6,847 (7.7)	313 (7.5)	290 (7.0)
Normal weight	77,080 (79.2)	70,875 (79.6)	3,139 (75.7)	3,066 (74.4)
Overweight	10,933 (11.2)	9,727 (10.9)	562 (13.6)	644 (15.6)
Obese	1,828 (1.9)	1,575 (1.8)	133 (3.2)	120 (2.9)
Parity, median (IQR)	2.0 (1.0, 2.0)	2.0 (1.0, 2.0)	2.0 (1.0, 3.0)	1.0 (1.0, 2.0)
Maternal diabetes mellitus, No. (%)	463 (0.5)	354 (0.4)	77 (1.9)	32 (0.8)
Maternal hypertension, No. (%)	204 (0.2)	164 (0.2)	16 (0.4)	24 (0.6)
Preeclampsia, No. (%)	1,515 (1.6)	1,162 (1.3)	103 (2.5)	250 (6.1)
Maternal smoking at the commencement of pregnancy, No. (%)
Not smoking	70,814 (72.8)	64,915 (72.9)	3,068 (74.0)	2,831 (68.7)
1–9 cig/day	16,677 (17.1)	15,163 (17.0)	683 (16.5)	831 (20.2)
≥10 cig/day	9,800 (10.1)	8,946 (10.0)	396 (9.5)	458 (11.1)
Socioeconomic factor
Highest parental education, No. (%)
Primary education	8,416 (8.7)	7,635 (8.6)	398 (9.6)	383 (9.3)
Secondary education	48,509 (49.9)	44,538 (50.0)	1,938 (46.7)	2,033 (49.3)
University education	40,366 (41.5)	36,851 (41.4)	1,811 (43.7)	1,704 (41.4)

Abbreviations: BMI, body mass index; cig, cigarette; IQR, interquartile range; No., number; SD, standard deviation

Mode of delivery and offspring obesity

In our primary analysis (Table 2), there was no statistically significant association between elective CS and obesity (RRR 1.14, CI 95% 0.99–1.30, p = 0.069), whereas a similar association between nonelective CS and obesity differed from unity (RRR 1.17, CI 95% 1.02–1.34, p = 0.027) as compared with vaginal delivery. We observed no association between elective or nonelective CS and obesity (RRR 1.02, CI 95% 0.88–1.18, p = 0.826 and RRR 0.96, CI 95% 0.83–1.10, p = 0.532, respectively) as compared with vaginal delivery when accounting for prepregnancy maternal BMI, maternal diabetes at delivery, maternal hypertension at delivery, maternal smoking, parity, parental education, maternal age at delivery, gestational age, birth weight standardized according to gestational age, and preeclampsia. Neither elective nor nonelective CS were associated with overweight at conscription as compared with vaginal delivery.

Table 2

Cesarean section deliveries and their associations to obesity, overweight, and underweight in offspring.

	Crude
	Underweight versus normal weight			Overweight versus normal weight			Obese versus normal weight
Mode of delivery	RRR	95% CI	p	RRR	95% CI	p	RRR	95% CI	p
Vaginal	1	-	-	1	-	-	1	-	-
Elective cesarean section	0.88	0.76–1.01	0.064	1.02	0.93–1.11	0.669	1.14	0.99–1.30	0.069
Nonelective cesarean section	0.92	0.80–1.05	0.220	1.07	0.98–1.17	0.113	1.17	1.02–1.34	0.027
	Adjusteda
	Underweight versus normal weight			Overweight versus normal weight			Obese versus normal weight
	RRR	95% CI	p	RRR	95% CI	p	RRR	95% CI	p
Vaginal	1	-	-	1	-	-	1	-	-
Elective cesarean section	0.88	0.76–1.01	0.079	0.99	0.90–1.08	0.818	1.02	0.88–1.18	0.826
Nonelective cesarean section	0.94	0.81–1.08	0.359	0.99	0.90–1.08	0.764	0.96	0.83–1.10	0.532

Empty cells (-) indicate reference group.

aAdjusted for prepregnancy maternal BMI, maternal diabetes at delivery, maternal hypertension at delivery, maternal smoking, parity, parental education, maternal age at delivery, birth weight standardized according to gestational age, preeclampsia, and gestational age.

Abbreviations: BMI, body mass index; CI, confidence interval; RRR, relative risk ratio

Sensitivity analysis

Characteristics in individuals who were and were not conscripted did not differ materially overall, although differences were statistically significant in our large sample (all p < 0.05, S1 Table). Similarly, although every characteristic except mean BMI and maternal preeclampsia were statistically different (p < 0.05), there was no major discrepancy between those with incomplete records and those retained in the analytical cohort. However, we noted that parental university education was more common among the conscripted as compared with the not conscripted (38.4% versus 29.7%, p < 0.05) and more common among the retained analytical cohort as compared with those with incomplete records (41.5% versus 36.1%, p < 0.05).

The stratification of vaginal deliveries into vaginal instrumental deliveries and vaginal deliveries did not alter our main findings; there was no meaningful change in any estimate as compared with our main analysis (S2 Table).

Our further sensitivity analyses (S3 Table), in which we (1) relax linearity assumptions of confounders, (2) account for standardized gestational weight gain, (3) account for a history of cesarean delivery, and (4) include those previously excluded at conscription, did not differ to any meaningful extent from our main analysis. In our last multinomial model (S4 Table), when treating all CSs as one group, we did not observe any association between CS and obesity after accounting for confounders (RRR 0.98, CI 95% 0.89–1.09, p = 0.775) as compared with vaginal delivery. When treating obesity as a binary outcome (S5 Table), there was no association between elective or nonelective CS and obesity in our fully adjusted model (RRR 1.02, CI 95% 0.88–1.18, p = 0.772 and RRR 0.96, CI 95% 0.84–1.11, p = 0.603, respectively) as compared with vaginal delivery. There was no association between elective (mean difference: 0.05, CI 95% −0.06 to 0.16, p = 0.338) or nonelective CS (mean difference: 0.02, CI 95% −0.09 to 0.14, p = 0.675) and continuous BMI when accounting for proposed confounders as compared with vaginal delivery (S6 Table). When employing multinomial fixed-effects regression, in a subset of discordant siblings, we observed a statistically significant association (p = 0.04) between nonelective CS and overweight (RRR 1.99, CI 95% 1.05–3.77) as compared with vaginal delivery (S7 Table). No other fixed-effects regression (linear or multinomial logistic) differed meaningfully from our main analysis (S7 Table and S8 Table).

There was no difference between our main analyses and when excluding those born preterm, restricting to those born at term, not adjusting gestational age (S9 Table), or treating BMI categories as an ordered outcome (S10 Table).

Discussion

Main findings

In this longitudinal cohort of 97,291 male conscripts, we found that there was no association between elective or nonelective CS and young adulthood obesity when accounting for possible confounding factors and conducting several predefined sensitivity analyses as compared with vaginal delivery. To the best of our knowledge, we have presented the largest and most comprehensive differentiation between elective and nonelective CS so far.

Comparison with previous research

In contrast with previous research [10,13,15,16], we did not observe any association between CS and young adulthood obesity. This could be explained by previous studies’ limited ability to adjust for maternal prepregnancy BMI [16], small sample sizes [10,13,15,16], and/or inability to differentiate between elective/prelabor and nonelective/acute CS [10,16]. To the best of our knowledge, the largest previous study on CS and offspring overweight/obesity that differentiated between types of CS was conducted on children (5 years old), with only 145 exposed cases, and described a significant association between CS on maternal request and overweight/obesity (odds ratio [OR] 1.18, CI 95% 1.00–1.41) [64]. In contrast, a meta-analysis [13] suggested that there was no association between prelabor CS and obesity in adulthood. However, this analysis was limited to very few participants (prelabor CS = 252 and vaginal delivery = 17,506).

Although a majority of previous studies have had limitations, studies with less uncertainty have suggested that there may be an attenuation with age in the association between CS and obesity [15,23]. The attenuation by age could potentially explain our findings. However, childhood obesity not persisting into young adulthood or adulthood may be of less relevance for clinical manifestation of obesity-related consequences [65-67].

Contrary to our findings, a recent study [24] on very young children (12 months old) suggested a strong association between elective CS and overweight (OR 2.01, CI 95% 1.13–3.58) but no such association for emergency CS (OR 1.08, CI 95% 0.66–1.76). The authors hypothesize that this may be a function of lack of fetal stress exposure induced by the onset of labor, which may be absent in elective CS, and that emergency CS may be exposed to maternal microbiota to a greater extent than elective CS. However, adjusting for intrapartum antibiotics did not alter their findings, suggesting that microbiota exposure did not explain the low risk in the emergency CS [24]. Contrary to the suggestion that CS supports the hygiene hypothesis, there have been suggestions that CS is a risk factor for childhood obesity that is independent of second- and third-trimester antibiotic use [68], although antibiotic use may also independently influence childhood obesity [68].

In addition to the aforementioned discrepancies between our study and previous studies, it should be noted that our cohort was born between 1982 and 1987, which could have implications for the comparability to more recent birth cohorts [24]. However, several studies conducted on younger children with more recent birth years have suggested null associations similar to those we observed in our cohort [22,23,25].

In our cohort, only accounting for maternal prepregnancy BMI attenuated the association between elective or nonelective CS and obesity by 15% and 16%, respectively (RRR 1.14 versus 0.99 and 1.17 versus 1.01) (S11 Table). Indeed, this was the strongest confounder in the association between either form of CS and obesity in our study. As obesity has a high heritability [69] and/or could be a function of fetal programming [70], it is plausible that taking maternal prepregnancy BMI into account captures both genetic predispositions transferred from mother to offspring and the fetal exposure to an obesogenic state in the mother. Using our fixed-effects linear regression, which accounts for familial confounding shared between brothers (e.g., obesogenic familial environment and obesity-related genetic traits), we did not observe any association between any form of CS and offspring obesity. Notably, we observed an association between nonelective CS and overweight in our multinomial discordant sibling sample. However, this may be explained by the small number of exposed cases and the possibility of residual confounding. Hence, we suspect there to be an association between nonelective CS and overweight as a function of confounding by medical indication for CS [23]. Indeed, if there is a causal effect of CS on overweight/obesity, an association should be present in elective CS as well [23].

Despite unnecessary CS being subject to some criticism [71], it is of interest to further study unnecessary CS and its possible association to offspring morbidity [72]. Although Swedish registers enable us to differentiate between elective and nonelective CS, they do not enable us to perform detailed classifications of CS using such classifications as the Robson classification [73], which may provide further insight into the potential role of CS in offspring health.

Strengths and limitations

The strengths of our study lie in our longitudinal design, large sample size, ability to control for a series of possible confounders, and ability to differentiate between elective and nonelective CS. Furthermore, the usage of MBR and the Swedish Military Service Conscription Registry enabled us to retrieve objective and standardized measures of exposure (birth mode) and outcome (BMI), limiting measurement error and information bias.

Despite the strengths of our study, there are several limitations that should be acknowledged. First, although conscription was mandatory by law under the period of study, there may be selection bias present in our cohort because those offspring with severe health conditions are not eligible for conscription [35]. Despite the potential for selection bias, we did not observe major differences, albeit most factors are statistically significantly different (p < 0.05), between our analytic sample and the excluded populations, with the exception of highest parental education (S1 Table). However, caution is warranted when generalizing and interpreting our findings. Second, there are still potential unmeasured confounders that we failed to account for. Third, we were limited to any record of previous CS in the MBR after 1973, which may fail to capture some previous CSs and fail to fully account for the motives to perform an elective CS. Fourth, the usage of registers limited us to a formal diagnosis of maternal conditions, which may only capture the most severe cases of maternal health. Furthermore, there may be some misclassification of nonelective CS among preterm deliveries [32]. However, our analysis excluding preterm deliveries and restricting to at-term deliveries was consistent with our main analysis, suggesting that this misclassification of nonelective CS does not influence our conclusion. Despite this, a certain proportion of misclassification is expected and could inflate the risk estimate of an offspring developing obesity in the elective CS group, if an offspring of a nonelective CS is at higher risk of developing obesity as compared with those with a true elective CS, given medical indications. Fifth, despite the ability to control for unmeasured confounding, sibling analysis has several limitations, such as increased bias from nonshared confounders and increased attenuation from measurement error, as compared with conventional analysis [57]. However, our collection of CS by medical records and standardized measurement of BMI reduces the impact of measurement error. Furthermore, by accounting for observed nonshared confounders, we limit any additional confounding to nonshared unobserved confounders. Despite this, caution is warranted when directly interpreting the estimates from sibling analysis. Finally, our cohort consisted of a male population, which limits the generalizability to females. However, studies including female populations have suggested no difference between males and females in the association between CS and obesity [14,15,23,25,64]. The generalizability of our study may be limited to countries with rates of CS similar to those in Sweden during the study period.

Conclusions

We observed no association between elective or nonelective CS and young adulthood obesity in young male conscripts when accounting for maternal and prenatal factors. Furthermore, we note that most of the crude association between CS and obesity could be explained by maternal prepregnancy BMI. This suggests that there is no clinically relevant association between CS and the development of obesity. Further large-scale studies are warranted to examine the association between differentiated forms of CS and obesity in young adult offspring.

Descriptive characteristics of the total population, eligible population, and the step-by-step excluded population.

(DOCX)

Click here for additional data file.

Relative risk ratios associated with instrumental vaginal delivery, elective cesarean section, and nonelective cesarean section as compared with vaginal delivery of underweight, overweight, and obesity relative to normal weight.

(DOCX)

Click here for additional data file.

Sensitivity analysis on associations between elective and nonelective cesarean section as compared with vaginal delivery of underweight, overweight, and obesity relative to normal weight.

(DOCX)

Click here for additional data file.

Association between pooled cesarean section and underweight, overweight, and obesity as compared with normal weight.

(DOCX)

Click here for additional data file.

Association between mode of delivery and obesity status (BMI ≥ 30).

(DOCX)

Click here for additional data file.

Linear association between mode of delivery and continuous body mass index.

(DOCX)

Click here for additional data file.

Relative risk ratios associated with elective cesarean section and nonelective cesarean section as compared with vaginal delivery of underweight, overweight, and obesity relative to normal weight in a subset of discordant full brothers.

(DOCX)

Click here for additional data file.

Fixed-effects linear association between mode of delivery and continuous body mass index in a subset of full brothers.

(DOCX)

Click here for additional data file.

Association between mode of delivery and underweight, overweight, and obesity as compared with normal weight, excluding those born before 37 weeks of gestation (preterm), restricting to those born between 37 weeks and 41 weeks and 6 days of gestation (at term), and not adjusting for gestational age.

(DOCX)

Click here for additional data file.

Crude and adjusted association between mode of delivery and underweight, overweight, and obesity as compared with normal weight using generalized ordered logit estimation.

(DOCX)

Click here for additional data file.

Association between mode of delivery and underweight, overweight, and obesity as compared with normal weight, only adjusting for maternal prepregnancy body mass index.

(DOCX)

Click here for additional data file.

30 Sep 2019

Dear Dr. Berglind,

Thank you very much for submitting your manuscript "Elective and non-elective cesarean section and the risk for obesity among young adult males: a population-based cohort study" (PMEDICINE-D-19-03196) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also sent to three independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and the accompanying reviewer attachment from Reviewer 1 can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Oct 14 2019 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. 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. If new competing interests are declared later in the revision process, this may also hold up the submission. 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. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosmedicine/s/submission-guidelines#loc-methods.

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.

We look forward to receiving your revised manuscript.

Sincerely,

Louise Gaynor, MBBS PhD

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

1. 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

Specifically, please provide a URL or email contact information from where data can be requested. Please note that the contact for data access cannot be one of the authors.

2. Title: Please include that the study was based on a Swedish population. Also, we suggest that you please change “risk for” to “association with” in the title.

3. Abstract: Please include the years during which the study took place, and length of follow up. Specifically, please include the relevant information on cohort birth years, and year of conscription.

4. Abstract: Please quantify the main results (with 95% CIs and p values). Specifically, please include p values for tests of association between C-section birth and obesity.

5. Abstract: Please include the specific dependent variables that are adjusted for in the adjusted analyses described.

6. Abstract: Please address the study implications without overreaching what can be concluded from the data; your study is observational and therefore causality cannot be inferred from your results. Please remove language that implies causality, such as “This suggests that there is no clinically relevant causal role of CS in the development of obesity and that an association between CS and offspring obesity may be a function of confounding.”

7. At this stage, we ask that you include 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 be 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

8. Methods: Please clarify the age(s) of the individuals at the time of conscription (when BMI was assessed).

9. Results: Please provide 95% CIs and p values for statistical tests in support of the assertions that the prevalence of obesity varied slightly between delivery modalities (lines 176-178) and that most covariates did not vary substantially with mode of delivery (lines 178-179).

10. Results: Line 186-187: Please revise the statement: “In our primary analysis, there was an insignificant association between elective CS and obesity (RRR 1.14, CI 95%: 0.99-1.30)...” to more accurately state that there was no significant association observed between elective CS and obesity.

11. Results: Line 188: Please describe which factors are adjusted for in the analysis of the association between CS and obesity in the adjusted models.

12. Results: Please provide p values for the sensitivity analyses, and tests for associations between mode of delivery and offspring obesity status.

13. Discussion: Lines 218-220, and at 293-295: Please revise the language to avoid any misleading assertion that the lack of any association identified in the present study serves as supporting evidence for the idea that associations identified in other studies are attributable to confounding of elective vs. non-elective c-sections.

14. Discussion: Lines 251-252: Please clarify where the analyses of association between CS and obesity adjusted only for pre-pregnancy BMI are presented.

15. Discussion: Lines 274-276: Were any statistical tests done to support the assertion that characteristics did or did not differ between the analyzed and excluded populations? If so, please present these in the results, and sTable1.

16. Tables: sTable7: There is a footnote for “a” but no “a” in the table. Please update footnote “b” to reflect the adjusted factors in the model.

17. Thank you for including the STROBE checklist. Please revise the checklist to use section and paragraph numbers, rather than page numbers and line numbers.

Comments from the reviewers:

Reviewer #1: See attachment

Michael Dewey

Reviewer #2: Ahlqvist et al. present a retrospective cohort study on the association between birth by Caesarean section and obesity in young adulthood among 97,000 Swedish males. I have detailed my comments below.

Major comments:

I do believe that replication in science is good and necessary, and research does not have to be novel to be publication-worthy. However, for the association between CS and offspring obesity, there have been around 100 studies (28 studies in Kuhle et al. 2015, 35 studies in Darmasseelane et al. 2014, and about 40 primary studies published since) published to date that looked at the issue from a lot of different angles in a multitude of settings using different kinds of analyses; the majority of studies adjusted for the key confounder maternal pre-pregnancy weight and still found an association. Based on the available evidence, I think it is safe to say that there is a true association. The paper by Ahlqvist et al, while solid, does not offer anything groundbreakingly new that would make me question the presence of that association between CS and obesity.

I have reviewed a number of manuscripts on the subject, and most papers, like the one under review, justify their existence with the claim that confounding has not been sufficiently considered in previous studies (not true), only to go on to either use the same set of confounders as most previous studies, or add one confounder to their models and remove another. Ahlqvist et al perform a sibling-analysis to account for unmeasured familial confounding (as has been done before for this association), but this type of analysis adds confounding by non-shared confounders, as the paper by Frisell et al. 2012 (reference 57 in the manuscript) points out. This bias is not acknowledged or discussed by the authors.

The other claim to (near-)novelty that the authors make is that "only a few studies [3 studies are referenced] have investigated effects of elective and non-elective CS in separate". I cannot verify or refute that claim, but in the presence of approximately 100 studies on the association, the authors need to demonstrate how they arrived at this number - did they do a systematic review of the literature? The authors also should describe clearly what the definition of elective and non-elective CS is, and if that definition is used consistently in the database.

Another issue is the external validity of the study, since the men in the study were born more than 30 years ago (1982 to 1987). As expected, the CS rate in the sample is very low at 8.5% and the obesity prevalence sits at 4.9%. Both prevalences are considerably lower than what we see today. With the CS rate between 20 and 30% in most Western countries, I would question whether the population of women who had an elective CS in the 1980s is in any way comparable to women undergoing elective CS these days. The authors try to claim external validity by stating "In addition to aforementioned discrepancies between our study and previous studies, it should be noted that our cohort was born between 1982 and 1987, which could have implications for the comparability to more recent birth cohorts (24). However, several studies conducted on younger children with more recent birth years have suggested similar null associations as those we observed in our cohort (22, 23, 25)." I disagree with that logic: Because more recent studies also had null findings, the current study has external validity?

Minor comments:

- Use abbreviation CS consistently throughout

- Line 60: "in the offspring" not "in offspring's"

- Line 72: "which could inflate the risk for obesity in the non-elective cesarean section" should read "which could inflate the risk for obesity in the non-elective CS group" or "which could inflate the risk for obesity in children born by non-elective CS"

- Lines 189, 204, 231, 252: Replace "&" with "and"

- I would probably forego the adjustment for gestational age as it may be a collider. See the paper by Wilcox et al. 2011 (https://www.ncbi.nlm.nih.gov/pubmed/21946386)

- Line 158-159: "First, a model where we introduced a cubic transformation of maternal age and maternal BMI, to relax the assumption of linearity." Transforming age and BMI doesn't "relax" the assumption, the assumption is always there and should be met for the analysis. I would suggest examining linearity with LOESS or GAM first and then transform (or not) in the main analysis and skipping that part of the sensitivity analysis.

- Line 186: "In our primary analysis, there was an insignificant association between elective CS and obesity [...]" There is no "insignificant" association. Should read: "The association was not statistically significant."

- Lines 223-226: "In contrast to previous research (10, 13, 15, 16), we did not observe any association between CS and young adulthood obesity. This could be explained by previous studies limited ability to adjust for maternal pre-pregnancy BMI (16), small sample sizes (10, 13, 15, 16), and/or inability to differentiate between elective/pre-labor and non-elective/acute CS (10, 16)." The authors should avoid handpicking a few of the many many studies to give the impression that the existing body of research has serious shortcomings.

Reviewer #3: Ali Khashan (University College Cork)

The present study was performed to examine the association between mode of delivery and the risk of offspring overweight and obesity in early adulthood. The study used data from the Swedish national registers and included males who with data on height and weight measured at conscription. The study results showed no evidence of an association between elective or emergency CS and the risk of overweight or obesity in male offspring with the relative risk ratios very close to one. This is an important study considering the limited evidence on the association between CS and the risk of obesity in young adults. The manuscript is very well written and the fact that the statistical analysis plan was registered before the analysis was performed is a strength in this paper. The lack of an association between CS and risk of overweight or obesity in early adulthood is an important finding for mothers and clinicians. A key limitation is the fact BMI was measured only once while one would have liked more than one measurement over time. The authors may wish to consider the following comments:

1) I am not sure if I missed this, but what was the age of children at the time of weight and height measurement? Considering that conscription was up to age 47, does this mean the outcome was measured at different age points for different persons? If this were the case, then age at the time the outcome was measured should be taken into account in the analysis.

2) Although the sibling analysis is an important analysis in this type of study, it is usually used to assess potential familial confounding when there is an association. In other words, it is used to determine whether an observed association is potentially causal or due to shared familial confounding. In this study there was no evidence of an association between CS and offspring obesity, therefore the sibling analysis has no added value and in fact it could be misleading as readers may misinterpret the significant result in the sibling analysis. I would remove the analysis from the manuscript and clarify that because there was no evidence of an association in the cohort analyses, the sibling analysis was not performed.

3) Although I understand the authors' approach of excluding persons with missing outcome data, excluding persons with missing maternal BMI and missing maternal smoking is not justified. I would include those persons in the analysis and use a missing data indicator for those two variables. Including those persons in the crude analysis would help the authors assess whether their assumption on missing data is accurate or not.

4) The authors highlight the potential misclassification of CS in preterm births, have they considered performing an analysis excluding preterm birth to check whether this potential misclassification is an issue? This is an analysis worth performing.

5) This study adds to a body of evidence from Sweden, that we and others did, showing limited evidence, if any, of an association between CS and asthma, type 1 diabetes, autism, ADHD and psychosis and the authors cited our two recent papers on CS and child obesity (reference 23 and 25) and we have two papers in press showing almost similar results from New Zealand and UK cohorts. The authors may want to have a more detailed discussion of these negative findings in terms of clinical practice and the fact CS does not seem to cause child morbidity, when good quality data and robust statistical analyses are used. Another discussion point is the fact Sweden has a low CS rate compared to other high income countries. Is it possible that elective CS in Sweden is elective due to medical indications and that what causes child morbidity, including obesity, is the unnecessary elective CS? I doubt this is the case, however, it is worth discussing the generalisability of results from a country with low CS rate to countries with high CS rate.

Any attachments provided with reviews can be seen via the following link:

[LINK]

Submitted filename: ahlqvist.pdf

Click here for additional data file.

10 Oct 2019

Submitted filename: Reviwer comments Point-by-point version Final version.docx

Click here for additional data file.

29 Oct 2019

Dear Dr. Berglind,

Thank you very much for re-submitting your manuscript "Elective and non-elective cesarean section and the association with obesity among young adult males: a Swedish population-based cohort study" (PMEDICINE-D-19-03196R1) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning 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. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide 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 be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. 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.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Nov 05 2019 11:59PM.

Sincerely,

Clare Stone, PhD

Managing Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

- I'd suggest removing "the association with" from the title, as there is no association ("... C section and obesity among young adult male offspring ..."). Apologies for making requested changes to the title again.

- Please add some summary demographic details for the conscripts in the abstract?

- I think the Author Summary could benefit from some "what do our findings mean" points and could mention the need to study young female offspring, for example?

-Please use square brackets in the main text for references

Comments from Reviewers:

Reviewer #1: The authors have addressed my points.

Michael Dewey

Reviewer #3: I would like to thank the authors for addressing my comments and making the relevant changes in the text. I have no further comments.

Any attachments provided with reviews can be seen via the following link:

[LINK]

5 Nov 2019

Submitted filename: Acceptence Point-by-point Addressal.docx

Click here for additional data file.

5 Nov 2019

Dear Dr. Berglind,

On behalf of my colleagues and the academic editor, Dr. Ali S Khashan, I am delighted to inform you that your manuscript entitled "Elective and non-elective cesarean section and obesity among young adult male offspring: a Swedish population-based cohort study" (PMEDICINE-D-19-03196R2) has been accepted for publication in PLOS Medicine.

PRODUCTION PROCESS

Before publication you will see the copyedited word document (in around 1-2 weeks from now) and a PDF galley proof shortly after that. The copyeditor will be in touch shortly before sending you the copyedited Word document. We will make some revisions at the copyediting stage to conform to our general style, and for clarification. When you receive this version you should check and revise it very carefully, including figures, tables, references, and supporting information, because corrections at the next stage (proofs) will be strictly limited to (1) errors in author names or affiliations, (2) errors of scientific fact that would cause misunderstandings to readers, and (3) printer's (introduced) errors.

If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.

PRESS

A selection of our articles each week are press released by the journal. You will be contacted nearer the time if we are press releasing your article in order to approve the content and check the contact information for journalists is correct. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact.

PROFILE INFORMATION

Now that your manuscript has been accepted, please log into EM and update your profile. Go to https://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.

Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Clare Stone, PhD

Managing Editor

PLOS Medicine

plosmedicine.org