Elective and Non-elective Cesarean Section and the Risk for Obesity Among Young Male Conscripts: a Population-based Cohort and Matched-sibling Analysis.
Conditions: Caesarean Section, Obesity, Cesarean Section Complications
Sponsor: Karolinska Institutet

 
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Title  
Elective and non-elective cesarean section and the risk for obesity among young adult males: a population-
based cohort.   
Protocol information 
Version of protocol 
2 (2019/04/24) 
Revision history 
Version 1 (2019/04/17) 
 
Revision  
Version 2: Title update. 
Author of protocol 
Viktor H. Ahlqvist 
Viktor.ahlqvist@ki.se 
Principal investigator 
Dr. Daniel Berglind 
Daniel.berglind@ki.se 
 
Summary 
Previous research has suggested that cesarean section may be associated with an increased risk of 
developing obesity in childhood, adolescence and adulthood. Yet, previous studies have been small or 
unable to differentiate between elective and non-elective cesarean section. Therefore, using a population-
based cohort the purpose is to examine the associations between vaginal delivery, elective and non-elective 
cesarean section on the risk of developing obesity in young adulthood among Swedish young singleton 
males. Using the Swedish medical birth registry, the recorded mode of delivery and indication of delivery 
which will be matched to those males who perform military conscription, where their body mass index is 
recorded. The investigators hypothesize that there will be an elevated risk of obesity in those born with non-
elective cesarean section, as a function of confounding, while those born with elective cesarean section will 
not have a higher risk of obesity than those born with vaginal delivery. 
Introduction 
Background/rationale 
A recent systematic review has suggested that there may be long-term risks for obesity in offspring’s 
following cesarean delivery (1). However, as noted by Rifas-Shiman et al. (2), there is a possibility that the 
association observed is driven mainly by unmeasured confounding. Yuan et al. (3) conducted an extensive 
investigation into various confounders that could explain this association, but still observed an association 
between cesarean section and offspring obesity. Unfortunately, only a few studies (4, 5) and none of the 
aforementioned (2, 3) have been able to distinguish between elective and non-elective (acute) cesarean 
section. One of the likely candidates for unmeasured confounding is confounding by indication, which could 
inflate the risk for obesity in the non-elective cesarean section, as described by Masukume et al. (4). Despite 
this, at 12-months (5), and at 3 and 5 years (4), there have been reported elevated risks of obesity in elective 
deliveries with cesarean section. Which, if true, may rule out the potential of confounding by indication. 
However, large-scale longitudinal studies are warranted and there is a necessity to examine if this indicated 
association persist into young adulthood. 
Objectives 
The objective of the study is to examine if there is an association between being born with an elective 
cesarean section or non-elective cesarean section and developing obesity in young adulthood.  

 
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Hypothesis 
The hypothesis is that there will be an elevated risk of obesity in those born with non-elective cesarean 
section, as a function of confounding, while those born with elective cesarean section will not have a higher 
risk of obesity than those born with vaginal delivery. The hypothesis is rooted in the assumption that the 
association between non-elective cesarean section and obesity may be subject to greater confounding by 
indication, while the association between elective cesarean section and obesity may be less confounded. 
Thus, in the presence of a higher risk of obesity associated with non-elective cesarean section it will 
interpreted as confounded, while a higher risk of obesity associated with elective cesarean section will be 
interpreted as a less confounded and a possible causal association.  
Methods 
Study type 
Population-based cohort. 
Study design 
We will construct a whole population-based cohort using the following Swedish population registries: (i) the 
Swedish Military Service Conscription Registry, (ii) the Swedish Medical Birth Register, (iii) the 
Multigenerational Register and (iv) the Population and Housing Censuses from 1970 and 1990. Additionally, 
we will match full brothers to create a within-families cohort that will be used to identify discordant full 
brothers which will contribute to the matched-sibling analysis (See Analytic Methods & Appendix Figure 1). 
 
For the purpose of this study, we have defined the following inclusion and exclusion criteria’s: 
Inclusion Criteria: 
• 
Singleton birth 
• 
Retrievable from the medical birth registry 
Exclusion Criteria: 
• 
No available information on mode of delivery 
• 
Not conscripteda 
• 
Extreme values at conscriptionb 
 
a During the period of study period, conscription was mandatory by law in Sweden for all male citizens up to 
the age of 47 (6). Males could be exempt from conscriptions (requiring state approval) if any of the following 
conditions applied: i) Physical or mental impairment limiting the possibility to complete military training, ii) at 
risk of developing physical or mental impairment if conscripted, iii) became Swedish citizen after the age of 
28, iv) has performed equivalent military training in foreign country, v) residing abroad for a longer period and 
returning after the age of 28 and vi) able to demonstrate extensive reasons to be exempt (6). As a previous 
study has described (7), only 2-3% of all Swedish men were exempt from conscription. 
b We will exclude conscripts with extreme values of height (≤150 or ≥210 cm), weight (≤40 or ≥150 kg) or 
BMI (≤15 or ≥60 kg/m2), in accordance with previous studies on the Swedish Military conscription register (8). 
In the sensitivity analysis we will examine the impact of this exclusion (see Analytic Methods). 
Variables 
The exposure is the mode of delivery trichotomized as: 1) vaginal birth, 2) birth by elective cesarean section 
and 3) birth by non-elective cesarean section. To facilitate comparison with previous studies, we will report 
the association between any form of cesarean section and obesity. However, this will not be the focus on the 
study nor be included in results and conclusions. 
 
The primary outcome is body mass index (BMI) categorized according to the World Health Organization’s (9) 
standard: underweight BMI<18.5, normal weight BMI 18.5-24.9, overweight BMI 25-29.9 and obese BMI>30. 
As a secondary outcome, we will model the difference between mode of deliveries in continuous BMI. BMI is 
derived by weight in kilograms/height in meters squared. Height and weight are measured using a 
standardized protocol with stadiometer and scale respectively. The reason for choosing to categorize BMI 
according to the World Health Organization’s standard is because they are clinically relevant and because 
they facilitate comparison with previous and future studies.  
 

 
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The following confounders will be adjusted for in multivariate analysis: Pre-pregnancy maternal BMI, 
maternal diabetes at delivery, maternal hypertension at delivery, maternal smoking, parity, maternal and 
paternal education, maternal age at delivery, birth weight standardized according to gestational age, pre-
eclampsia and gestational age. For a more detailed description on each included confounder see Appendix 
Table 1. 
Data sources 
Using the Medical Birth Registry, which contains validated data on approximately 99% of the Swedish 
population (10), we will sample all singleton born individuals born between 1982 and 1987 that are available 
in the Medical Birth Registry. Using the Swedish Military Service Conscription Registry we will retrieve 
outcome data for all of the singletons participating in conscription (which was mandatory by law). The 
Multigenerational register will facilitate linkage of parents and offspring’s and be used to retrieve information 
on maternal age. Finally, the Population and Housing Censuses of 1970 and 1990 were used to retrieve 
information on the highest parental education. Linking of data sources was enabled through the use of a 
personal identification number, a unique id-code assigned to each Swedish resident at birth. For a more 
detailed description on each included variable see Appendix Table 1. 
Study size 
We intend to sample all eligible participants. 
Analytic methods 
First, we will present descriptive characteristics of our cohort and the within-families cohort with appropriate 
measures of dispersion and central tendency for each given variable. We do not intend to present any p-
values for descriptive characteristics, hence no statistical tests will be performed. Second, we will model the 
association between mode of delivery (trichotomized variable) and BMI categories using multinomial logistic 
regression, using the vaginal delivery and normal weight BMI (BMI 18.5-24.9) as reference 
exposure/outcome. For all multinomial logistic regression, we will present crude and multivariate adjusted 
estimates for the exposure and their corresponding 95% confidence interval. All confounders will be adjusted 
for in their modified way (see Appendix Table 1), except for parity which will be treated as a categorical 
variable to account for non-linearity with the outcome. All analysis will be estimated using robust (sandwich) 
standard errors to account for correlation between brothers.  
 
A series of sensitivity analysis will be conducted. First, we will employ multinomial logistic regression with 
fixed effects, to account for factors shared between full-brothers (genetic and environmental). All discordant 
full brothers with available measures will be able to contribute to fixed-effects analysis. Second, we will 
present the original adjusted models but allow for nonlinearity of maternal BMI and maternal age using a 
cubic transformation. Third, we will present a model further adjusted for weight gain during pregnancy, 
standardized by gestational age and BMI category using Sweden specific growth curves (11), and a model 
adjusted for previous cesarean delivery. However, we expect the power in this analysis to be compromised 
by missing data, as validation reviews have indicated that recording of this information varies in the Medical 
Birth Registry (12). Third, we will include those excluded because of extreme values at conscription to 
assess the impact of this exclusion on our findings. Finally, to quantify the required magnitude of a residual 
confounder to fully explain away any observed association, condition on the observed confounders, we will 
compute the E-value (13). All analysis will be conducted using Stata 14.1 (Stata Corp, College Station, TX, 
USA).   
Missing data 
We expect there to be a proportion of missing data. The primary source of data will likely be those individuals 
participating in conscription but not having measures of BMI. Further, governmental validation reports have 
noted that 20% of the cesarean deliveries were not coded by indication (15), which makes these individuals 
ineligible in our main analysis. However, we will in accordance with best practice attempt to describe the 
characteristics of the participants with specific missing data and describe the implications of missing data for 
our findings. All analysis will be conducted as complete cases analysis, as we hypothesize there to be 
missing completely at random and potentially missing not at random in a few cases. 

 
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Other information 
Preferred reporting 
The study will be reported in coherence with the Strengthening the Reporting of Observational Studies in 
Epidemiology (STROBE) Statement. 
Funding 
This work was supported by the Stockholm County Council [ALF 20180266 to DB]. The funders had no role 
in study design, data collection and analysis. 
Ethical considerations 
The study was approved by the Regional Ethical Review Board, Stockholm (Dnr: 2016/1445-31/1). The 
authors declare no conflicts of interest. 
Existing data 
At the time of protocol submission, VHA and DB had not yet received the required data. Yet, they have 
previously conducted studies in the registries and had access to other aspects of the data sources. However, 
this access could not facilitate any analysis relevant to this project. 
 
References 
1. 
Keag OE, Norman JE, Stock SJ. Long-term risks and benefits associated with cesarean delivery for 
mother, baby, and subsequent pregnancies: Systematic review and meta-analysis. PLoS medicine. 
2018;15(1):e1002494. 
2. 
Rifas-Shiman SL, Gillman MW, Hawkins SS, Oken E, Taveras EM, Kleinman KP. Association of 
Cesarean Delivery With Body Mass Index z Score at Age 5 Years. JAMA Pediatr. 2018;172(8):777-9. 
3. 
Yuan C, Gaskins AJ, Blaine AI, Zhang C, Gillman MW, Missmer SA, et al. Association Between 
Cesarean Birth and Risk of Obesity in Offspring in Childhood, Adolescence, and Early Adulthood. JAMA 
Pediatr. 2016;170(11):e162385. 
4. 
Masukume G, O'Neill SM, Baker PN, Kenny LC, Morton SMB, Khashan AS. The Impact of 
Caesarean Section on the Risk of Childhood Overweight and Obesity: New Evidence from a Contemporary 
Cohort Study. Sci Rep. 2018;8(1):15113. 
5. 
Cai M, Loy SL, Tan KH, Godfrey KM, Gluckman PD, Chong YS, et al. Association of Elective and 
Emergency Cesarean Delivery With Early Childhood Overweight at 12 Months of Age. JAMA Netw Open. 
2018;1(7):e185025. 
6. 
Värnpliktslag, 1941:967 (1941). 
7. 
Andersen K, Rasmussen F, Held C, Neovius M, Tynelius P, Sundstrom J. Exercise capacity and 
muscle strength and risk of vascular disease and arrhythmia in 1.1 million young Swedish men: cohort study. 
BMJ. 2015;351:h4543. 
8. 
Neovius M, Kark M, Rasmussen F. Association between obesity status in young adulthood and 
disability pension. Int J Obes (Lond). 2008;32(8):1319-26. 
9. 
World Health Organization. Obesity: preventing and managing the global epidemic. Report of a 
WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i-xii, 1-253. 
10. 
The Swedish Medical Birth Register: a summary of content and quality. 
www.sos.se/fulltext/112/2003-112-3/2003-112-3.pdf. : Stockholm SNBoHaW; 2005. 
11. 
Johansson K, Hutcheon JA, Stephansson O, Cnattingius S. Pregnancy weight gain by gestational 
age and BMI in Sweden: a population-based cohort study. Am J Clin Nutr. 2016;103(5):1278-84. 
12. 
Health NBo, Welfare. The Swedish Medical Birth Register–A summary of content and quality. 
National Board of Health and Welfare Stockholm, Sweden; 2003. 
13. 
VanderWeele TJ, Ding P. Sensitivity Analysis in Observational Research: Introducing the E-Value. 
Ann Intern Med. 2017;167(4):268-74. 
14. 
StataCorp. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015. 
15. 
Källén B, Källén K. Utvärdering av det svenska Medicinska födelseregistret (Evaluation of the 
Swedish Medical Birth Register): Socialstyrelsen. Epidemiologiskt Centrum (Swedish National Board of 
Health and Welfare, Centre of Epidemiology). 2002. 

 
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Appendix: 
Table 1. Source, description, original value and the applied manipulation of each included variable. 
Source 
Variable 
Description 
Original value 
Manipulation 
Swedish Medical birth 
registry 
Vaginal birth 
Recorded delivery by vaginal birth. 
Yes/no 
Trichotomized as: 1) vaginal 
birth, 2) birth by elective 
cesarean section and 3) birth by 
non-elective cesarean section 
Swedish Medical birth 
registry 
Cesarean birth 
Recorded delivery by cesarean section. 
Yes/no 
Swedish Medical birth 
registry 
Indication for Cesarean 
delivery 
Recorded reason for cesarean section. 
Categorical: 1) Elective or 2) Non-
elective 
Swedish Medical birth 
registry 
Pre-pregnancy maternal 
BMI 
BMI at first visit of maternal health clinic 
(kg/m2), using a standardized scale and 
self-reported height. 
Continuous 
No manipulation (see sensitivity 
analysis) 
Swedish Medical birth 
registry 
Maternal diabetes at 
delivery 
Self-reported maternal diabetes mellitus 
status. 
Yes/no 
No manipulation 
Swedish Medical birth 
registry 
Maternal hypertension at 
delivery 
Self-reported maternal hypertension 
status. 
Yes/no 
No manipulation 
Swedish Medical birth 
registry 
Maternal smoking 
Self-reported smoking habits of the 
mother at the first visit of the maternal 
health clinic. 
Categorical: 1) Does not smoke 2) 1-9 
cigarettes per day & 3) ≥10 cigarettes 
per day 
No manipulation 
Swedish Medical birth 
registry 
Parity 
Number of children born, after 28 weeks 
of gestation.  
Continuous 
No manipulation  
Swedish Medical birth 
registry 
Gestational weight gain 
Difference in measured weight between 
first visit and visit at delivery. 
Continuous 
Standardized according to the 
week of gestation and pre-
pregnancy BMI category 
Swedish Medical birth 
registry 
Birth weight 
Birth weight in grams (increments of 10). Continuous 
Standardized according to the 
week of gestation 
Swedish Medical birth 
registry 
Pre-eclampsia 
As recorded by ICD-8 code: 63703-
63710 and with ICD-9 code: 642E-642G 
in the medical birth registry. 
Yes/no 
No manipulation 
Swedish Medical birth 
registry 
Previous cesarean 
delivery 
Maternal history of cesarean delivery. 
Yes/no 
No manipulation 
Swedish Medical birth 
registry 
Gestational age 
Gestational age in completed weeks. 
Continuous 
No manipulation 
Swedish Military Service 
Conscription Registry 
Offspring BMI at 
conscription 
Measured BMI at conscription (kg/m2), 
measured using a standardized scale 
and stadiometer. 
Continuous 
Categorized into: underweight 
BMI<18.5, normal weight BMI 
18.5-24.9, overweight BMI 25-
29.9 or obese BMI>30 

 
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Source 
Variable 
Description 
Original value 
Manipulation 
Population and Housing 
Censuses 
Maternal education 
Highest attainted education. 
Categorical: 1) Primary education (<9 
years), 2) Primary education (9-10 
years), 3) Secondary education (<=2-
years), 4) Secondary education (>2 
years), 5) University (< 3-years), 6)  
University (> 3-years) or 7) Research 
degree 
Highest educational attainment 
by any of the parents 
Population and Housing 
Censuses 
Paternal education 
Highest attainted education. 
Same as above  
Multigenerational Register  
Maternal age at delivery 
Maternal age at the date of delivery. 
Continuous 
No manipulation  (see sensitivity 
analysis) 

 
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Figure 1. Flowchart of derivation of analytic sample and matched-sibling sample.