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Early Life Course Risk Factors for Childhood Obesity: The IDEFICS Case-Control Study Karin Bammann1,2*, Jenny Peplies2, Stefaan De Henauw3, Monica Hunsberger4, Denes Molnar5,
Luis A. Moreno6, Michael Tornaritis7, Toomas Veidebaum8, Wolfgang Ahrens2, Alfonso Siani9, on behalf
of the IDEFICS consortium
1 Institute for Public Health and Nursing Research (IPP), University of Bremen, Bremen, Germany, 2 BIPS Institute for Prevention Research and Epidemiology, Bremen,
Germany, 3 Department of Public Health, Ghent University, Ghent, Belgium, 4 Department of Public Health and Community Medicine, University of Gothenburg,
Gothenburg, Sweden, 5 Department of Pediatrics, University of Pécs, Pécs, Hungary, 6 Growth, Exercise, Nutrition and Development (GENUD) Research Group, University
of Zaragoza, Zaragoza, Spain, 7 Research and Education Foundation of Child Health, Strovolos, Cyprus, 8 Department of Chronic Diseases, National Institute for Health
Development, Tallinn, Estonia, 9 Unit of Epidemiology and Population Genetics, Institute of Food Sciences, National Research Council, Avellino, Italy
Abstract
Background: The early life course is assumed to be a critical phase for childhood obesity; however the significance of single factors and their interplay is not well studied in childhood populations.
Objectives: The investigation of pre-, peri- and postpartum risk factors on the risk of obesity at age 2 to 9.
Methods: A case-control study with 1,024 1:1-matched case-control pairs was nested in the baseline survey (09/2007–05/ 2008) of the IDEFICS study, a population-based intervention study on childhood obesity carried out in 8 European countries in pre- and primary school settings. Conditional logistic regression was used for identification of risk factors.
Results: For many of the investigated risk factors, we found a raw effect in our study. In multivariate models, we could establish an effect for gestational weight gain (adjusted OR = 1.02; 95%CI 1.00–1.04), smoking during pregnancy (adjusted OR = 1.48; 95%CI 1.08–2.01), Caesarian section (adjusted OR = 1.38; 95%CI 1.10–1.74), and breastfeeding 4 to 11 months (adjusted OR = 0.77; 95%CI 0.62–0.96). Birth weight was related to lean mass rather than to fat mass, the effect of smoking was found only in boys, but not in girls. After additional adjustment for parental BMI and parental educational status, only gestational weight gain remained statistically significant. Both, maternal as well as paternal BMI were the strongest risk factors in our study, and they confounded several of the investigated associations.
Conclusions: Key risk factors of childhood obesity in our study are parental BMI and gestational weight gain; consequently prevention approaches should target not only children but also adults. The monitoring of gestational weight seems to be of particular importance for early prevention of childhood obesity.
Citation: Bammann K, Peplies J, De Henauw S, Hunsberger M, Molnar D, et al. (2014) Early Life Course Risk Factors for Childhood Obesity: The IDEFICS Case- Control Study. PLoS ONE 9(2): e86914. doi:10.1371/journal.pone.0086914
Editor: Amanda Bruce, University of Missouri-Kansas City, United States of America
Received August 12, 2013; Accepted December 16, 2013; Published February 13, 2014
Copyright: � 2014 Bammann et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was done as part of the IDEFICS Study (www.idefics.eu). We gratefully acknowledge the financial support of the European Community within the Sixth RTD Framework Programme Contract No. 016181 (FOOD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: [email protected]
Introduction
Excess body fat is one of the major health concerns in childhood
populations [1,2]. Although the energy imbalance resulting from
high energy intake and low energy expenditure can contribute to
the development of overweight and obesity in children, there is no
general consensus about its importance as the main driver of
weight gain [3]. In recent years, factors early in the life course
emerged as possible determinants of early overweight and obesity
[4,5]. These can lead to epigenetic changes which are associated
with the programming of metabolic outcomes in the offspring.
Different pre-, peri- and postnatal risk factors for childhood obesity
have been investigated and there is an increasing need to
disentangle the contribution of factors like maternal weight,
gestational weight gain, glycemic control, smoking and alcohol use
during pregnancy, birth weight, breast feeding on the adiposity of
the offspring, for which partly inconsistent results have been
obtained [5]. While high birth weight was consistently shown to be
a risk factor for obesity, the situation is less clear with low birth
weight that might or might not play a role in the development of
subsequent overweight and obesity [6]. Likewise, the impact of
breastfeeding on childhood obesity is still a matter of research [7].
Although a protective effect of breastfeeding for subsequent
obesity of the offspring has been demonstrated in several studies,
this result might at least partly be due to confounding: Amir and
Donath show in their studies that maternal smoking and obesity
lead to a lesser probability of breastfeeding [8,9], both, maternal
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smoking and maternal obesity, being themselves strong risk factors
for childhood overweight [5]. Correspondingly, it is suspected by
some authors that the association of breastfeeding and childhood
overweight is a statistical artifact rather than a true causal
association [10].
In summary, there is still a considerable lack of research
regarding the effect of early life course factors on the risk of
childhood obesity.
The IDEFICS study is a large European multi-center interven-
tion study on childhood obesity. Prior to the intervention phase, a
baseline survey was conducted in the control and intervention
regions to assess a wealth of factors related to diet- and lifestyle-
related diseases in childhood. We used this data to set up a
matched case-control study on obesity. The aim of the paper is to
investigate the impact of pre-, peri- and postnatal risk factors on
the subsequent risk of obesity within this case-control study.
Materials and Methods
Ethics Statement We certify that all applicable institutional and governmental
regulations concerning the ethical use of human volunteers were
followed during this research, and that the IDEFICS project
passed the Ethics Review process of the Sixth Framework
Programme (FP6) of the European Commission. Ethical approval
was obtained from the relevant local or national ethics committees
by each of the eight study centers, namely from the Ethics
Committee of the University Hospital Ghent (Belgium), the
National Bioethics Committee of Cyprus (Cyprus), the Tallinn
Medical Research Ethics Committee of the National Institutes for
Health Development (Estonia), the Ethics Committee of the
University Bremen (Germany), the Scientific and Research Ethics
Committee of the Medical Research Council Budapest (Hungary),
the Ethics Committee of the Health Office Avellino (Italy), the
Ethics Committee for Clinical Research of Aragon (Spain), and
the Regional Ethical Review Board of Gothenburg (Sweden). All
parents or legal guardians of the participating children gave
written informed consent to data collection, examinations,
collection of samples, subsequent analysis and storage of personal
data and collected samples. Additionally, each child gave oral
consent after being orally informed about the modules by a study
nurse immediately before every examination using a simplified
text. This procedure was chosen due to the young age of the
children. The oral consenting process was not further document-
ed, but it was subject to central and local training and quality
control procedures of the study. Study participants and their
parents/legal guardians could consent to single components of the
study while abstaining from others. All procedures were approved
by the above-mentioned Ethics Committees.
Study Sample IDEFICS is a multi-center population-based intervention study
on childhood obesity that is carried out in selected regions of 8
European countries comprising Belgium, Cyprus, Estonia, Ger-
many, Hungary, Italy, Spain and Sweden. The study was set up in
pre- and primary school settings in a control and an intervention
region in each of these countries. Two major surveys (baseline and
follow-up) were conducted in pre-schools and primary school
classes (1 st
and 2 nd
grades at baseline). The baseline survey
(September 2007–May 2008) reached a response proportion of
51% and included 16 220 children aged 2 to 9 years. The general
design of the IDEFICS study has been described elsewhere [11]. A
brief description of the study regions can be found in Bammann
et al. [12].
Anthropometric measurements were done during a physical
examination. Weight to the nearest 0.1 kg and foot-to-foot
bioelectrical resistance in Ohm was measured using an electronic
scale TANITA BC 420 SMA (TANITA Europe GmbH,
Sindelfingen, Germany) with the children being in a fasting status
and wearing only underwear. Standing height was measured with
the children’s head in a Frankfort plane using a stadiometer SECA
225 (seca GmbH & Co. KG., Hamburg, Germany) to the nearest
0.1 cm. As in the weight measurement, the children were wearing
only underwear, all hair ornaments were removed and all braids
undone. Body mass index (BMI) was calculated as weight (kg)
divided by height squared (m). For obtaining the International
Task Force of Obesity (IOTF) category, BMI categories were
interpolated for continuous age as proposed [13,14]. Cubic splines
were used for this interpolation. The resistance index (RI) was
calculated as squared height (cm 2 ) divided by resistance (Ohm).
The RI was shown to be a good predictor for fat free mass in
children [15].
Within the baseline survey, a self-administered questionnaire
was filled in by the parents to gather information on the children’s
behavior, parental attitudes and on the social microenvironment of
the children (IDEFICS parental questionnaire). A further ques-
tionnaire on health-related and medical information was given to
the parents in the course of the physical examination of the child
(IDEFICS medical questionnaire). Questionnaires were developed
in English, translated to the respective languages and back
translated to English to minimize any heterogeneity due to
translation problems. Different language versions were available in
the centers, and help was offered to those parents who felt they
were not able to fill in the questionnaire by themselves. For filling
in the IDEFICS medical questionnaire, the help of medical
personnel was offered directly at the survey sites.
Eligible for the IDEFICS case-control study on obesity were all
children from the baseline survey for whom a basic set of
anthropometric indicators and pregnancy information was present
(N = 16,113). From these children, all children aged 4 to 8 years
that met the IOTF criteria for childhood obesity were identified as
cases (N = 1,024). Controls were selected from the group of IOTF
normal weighted children (N = 11,193) and matched 1:1 by study
center, sex and age (sliding window +/20.5 years) to the cases. For all cases, controls with identical sex and study center and a
minimal distance with respect to age were selected. The decision
for a 1:1 matched design was based on a sample size calculation.
In our study, risk factors with prevalences among controls of at
least 10% leading to odds ratios of 1.6 and more can be detected
with a power of more than 90% (two-sided, p = 0.05).
Investigated Risk Factors The investigated risk factors directly related to the child can be
grouped into prepartum, peripartum, and postpartum factors (see
Table 1). Further family-related risk factors included in the present
analysis are familial clustering and parental social background. All
information was assessed by the IDEFICS parental questionnaire,
except for the occurrence of gestational diabetes that was taken
from the IDEFICS medical questionnaire. All investigated risk
factors are based on self-report.
Included prepartum factors were smoking during pregnancy,
gestational weight gain and gestational diabetes. The questions
relating to smoking during pregnancy and to gestational weight
gain were posed to biological mothers, only. Regarding smoking
during pregnancy, possible answer categories were ‘‘Never’’,
‘‘Rarely, at maximum once a month’’, ‘‘Several occasions a
week’’ or ‘‘Daily’’. We categorized ‘‘Rarely, at maximum once a
month’’ or more often as smoking during pregnancy. Validity of
Early Life Course Factors for Childhood Obesity
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maternal recall of smoking during pregnancy and of gestational
weight gain is high even after several decades [16,17].
Included peripartum factors were birth weight and information
whether the child was delivered by Caesarian section. The validity
of parental long-term recall of birth weight and of Caesarian
sections is good to excellent [16–18], and is not related to time of
recall since birth [19].
Included postpartum factors were duration of breastfeeding and
introduction of solid foods. The early infant feeding of the child
was assessed by a table indicating different types of feeding where
starting and ending age could be given by the parents. The exact
wording of the question was ‘‘What type of feeding with your child
was used prior to being fully integrated into the usual household
diet?’’. Length of breastfeeding was calculated by subtracting
starting age from ending age of breastfeeding, either exclusive or in
combination with other types of feeding. The introduction of solid
foods was assessed using the question ‘‘At what age did you first
introduce …?’’ followed by a table with 5 different foods and the
possibility of giving the time of introduction as age of the child in
month. Early introduction of solid food was defined as introducing
cereals, meat, vegetables or fruits at a child’s age before 4 months.
Previous research has shown that the validity of maternal recall for
duration of breastfeeding is very high, even after 10 years and
more [16,17,20,21]. Repeatability and validity for maternal recall
of introduction of solid foods is shown to be higher than for
introduction of fluids other than breast milk, but considerably
lower than for breastfeeding with no clear direction of bias towards
wrong recall of earlier or later dates [20,22].
The familial clustering of overweight and obesity was assessed
using self-reported parental BMI. The parental BMI was
calculated as weight (kg)/squared height (m 2 ).
The parental social background was described using the
parental education and the age of mother at birth. For the
analyses, these were transferred country-by-country to Interna-
tional Standard Classification of Education (ISCED) levels [12,23]
and the maximum ISCED level of both parents was calculated.
Statistical Analyses To evaluate the impact of a putative risk factor, conditional
logistic regression models were fitted to the data. This allows an
unbiased estimation of effects in matched case-control studies with
regard to the matching variables. Within this approach, each
matched set forms a stratum. In the case of 1:1-matched pairs, the
likelihood of being a case for N strata is then given by:
LC (b)~ XN
i~1
1
(1ze b(xi(Case){xi(Control) ))
The estimation of the bs was done using Cox’ proportional hazard model with maximum likelihood estimation [24]. 95%
confidence intervals (95% CI) were computed.
For all variables, the influence of the child’s sex and age group
(, = 6 years, .6 years) on the raw odds ratio (OR) was tested
using the Breslow-Day test for homogeneity of the odds ratios [25].
We found all OR to be homogenous regarding age group. OR
Table 1. Risk factors investigated in the study.
Risk factor Hypotheses
Prepartum
Smoking during pregnancy Own causal effect (risk factor) e.g. through fetal growth retardation and subsequent developmental adaptations [46,47].
Possible confounder: Parental energy intake [47], parental socioeconomic status [46].
Gestational weight gain Own causal effect (risk factor) e.g. through shared genetic factors (on weight gain), shared environment (e.g. diet), fetal programming [48,49].
Possible confounder: Maternal BMI [49].
Gestational diabetes Own causal effect (risk factor) e.g. through shared genetic factors, shared environment, fetal programming [50].
Possible confounder: Maternal BMI.
Peripartum
Birth weight Own causal effect (risk factor) reflecting fetal growth, programming for lean mass and fat distribution [32].
Possible artifact due to high correlation of BMI and lean body mass [32].
Caesarian section Own causal effect (risk factor) e.g. through differences in colonizing bacteria species [34].
Possible confounder: Maternal BMI, maternal smoking during pregnancy, breastfeeding [34].
Postpartum
Breastfeeding (initiation and duration) Own causal effect (protective factor) e.g. through nutritional programming [51,52], moderation of genetic effects [53], reduced risk of overfeeding [54].
Known confounder: parental obesity, maternal smoking during pregnancy, parental socioeconomic status; might completely remove the effect [55].
Association possibly artificial due to lower breastfeeding success in obese and/or smoking mothers [10,26].
Early introduction of solid foods Own causal effect (risk factor) e.g. through nutritional programming [56].
Possible confounder: Parental socioeconomic status [57], breastfeeding [58,59].
doi:10.1371/journal.pone.0086914.t001
Early Life Course Factors for Childhood Obesity
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that were found to be heterogeneous over sexes are reported in the
text.
For each of the investigated factors, we built multivariate
models adjusting for known or suspected confounders from the
literature (cf. Table 1). Since many of the investigated risk factors
are correlated, we finally built a multivariate model containing all
factors that were shown to be influential in the analyses. We
reported the Wald statistics to judge the relative importance of the
single factors.
All statistical analyses were done with SAS 9.2 (SAS Institute,
Cary (NC), USA).
Raw ORs for parental BMI and parental ISCED level can be
found in the Appendix (Table S1).
Results
A basic description of the study sample is displayed in Table 2.
Roughly 50% of the case-control-pairs are male, 48% are 4–6
years, and 52% are 7–8 years old. The case-control pairs show
large differences with respect to country of origin, ranging from
39.7% from Italy to 3.9 from Belgium and 2.7% from Sweden.
The investigated early life course risk factors are shown in
Table 3. Maternal smoking during pregnancy carried a 50%
higher risk of the child being a case. Stratification by sex revealed
that this elevated risk was present only in boys (OR = 2.15; 95%
CI 1.43–3.23), but not in girls (OR = 1.13; 95% CI 0.78–1.62).
The elevated obesity risk of maternal smoking during pregnancy
remained practically unchanged when adjusting for parental BMI
and parental educational level. Gestational weight gain showed a
linear dose-response relationship mounting in a twofold risk of
obesity if the mother gained 25 kg and more during pregnancy,
which was not explained by maternal BMI. Also, gestational
diabetes was associated with an excess risk of 32%. After
adjustment for maternal BMI the elevated risk disappeared almost
completely (OR = 1.05; 95%CI 0.57–1.94).
The matched raw odds ratios for birth weight show a clear
linear dose-response relationship with childhood obesity
(OR = 0.58; 95%CI 0.39–0.86 for a birth weight ,2.5 kg up to
OR = 1.83; 95%CI 1.26–2.65 for a birth weight of .4 kg).
However, when we adjusted for the RI as an indicator of fat free
mass of the child, the effect of birth weight on the subsequent
obesity risk disappeared completely. Being born via Caesarian
section carried a higher obesity risk in our study (OR = 1.43;
95%CI 1.17–1.75). After adjustment for maternal BMI, maternal
weight gain during pregnancy and initiation of breastfeeding, this
risk was reduced and no longer statistically significant (OR = 1.27;
95%CI 0.99–1.64). The initiation of any breastfeeding carries an
unadjusted OR of 0.75 (95%CI 0.61–0.91), and is thus protective
against subsequent obesity in childhood. However, parental
educational level, maternal BMI and maternal smoking during
pregnancy almost completely explained this effect; the adjusted
OR is near to unity (OR = 0.91; 95%CI 0.70–1.18). Likewise, the
duration of breastfeeding shows unadjusted a u-shaped relation-
ship to obesity with a protective effect only for the two middle
categories (4–6 months, 7–11 months of non-exclusive breastfeed-
ing). After adjustment for the afore-mentioned confounders, only
7–11 moths of non-exclusive breast-feeding remained statistically
significant protective (OR = 0.70; 95%CI 0.49–0.99). Early
introduction of solid foods shows an unadjusted OR of 1.43
(95% CI 1.02–2.01) that is reduced to a non-significant 1.33 (95%
CI 0.93–1.90) after adjustment for parental educational level and
initiation of breast-feeding.
To assess the combined effect of all investigated factors, we built
two multivariate models (Table 4). The first model included
gestational weight gain in kg, and design variables for smoking
during pregnancy, Caesarian section, early introduction of solid
foods and breastfeeding 4 to 11 months. The second model
additionally included the confounding factors parental BMI in kg/
m 2
and parental educational level (unadjusted matched OR of
these confounders can be found in Table A of the appendix).
In the overall group, statistically significant risk factors for
obesity were Caesarian section (adjusted OR = 1.38; 95%CI 1.10–
1.74), gestational weight gain in kg (adjusted OR = 1.02; 95%CI
1.00–1.04), maternal smoking during pregnancy (adjusted
OR = 1.48; 95%CI 1.08–2.01) and breastfeeding 4 to 11 months
(adjusted OR = 0.77; 95%CI 0.62–0.96). After additional adjust-
ment for parental BMI and parental educational level, statistically
significant factors were maternal BMI in kg/m 2
(adjusted
OR = 1.16; 95%CI 1.11–1.20), paternal BMI in kg/m 2
(adjusted
OR = 1.11; 95%CI 1.07–1.16), and gestational weight gain in kg
(adjusted OR = 1.04; 95%CI 1.01–1.07).
Discussion
This paper investigated the impact of early life course risk
factors on the risk of subsequent childhood obesity. For many of
the investigated risk factors, we found a raw effect in our study.
Our results regarding maternal smoking are confirmed by
literature. In studies where maternal smoking was assessed, this
factor is quite consistently reported to be a marked risk factor [26–
28]. Similarly, high gestational weight gain was previously shown
to be a risk factor not only for overweight and obesity of the child
[29], but also of the mother [30]. Sometimes this effect is
attributed to the influence of maternal adiposity [5], however in
our study, gestational weight gain showed an independent effect,
also after control for parental BMI. We were well in accordance
with the literature, regarding high birth weight which was also a
risk factor in our study [6,26,31]. However, when we adjusted for
fat-free mass, this effect was completely removed, corroborating
Table 2. Description of the study sample.
Case-control pairs
N %
Sex
Girls 515 50.3
Boys 509 49.7
Age
4–6 years 494 48.2
7–8 years 530 51.8
Center
Italy 407 39.7
Cyprus 193 18.8
Hungary 135 13.2
Germany 81 7.9
Spain 77 7.5
Estonia 63 6.2
Belgium 40 3.9
Sweden 28 2.7
Total 1,024 100
doi:10.1371/journal.pone.0086914.t002
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the hypothesis that birth weight is mainly influencing lean body
mass and not fat mass [32]. Since the BMI is correlated with fat
mass and with fat-free mass, one could argue that adjusting for fat-
free mass leads generally to over-adjustment. Since the difference
of fat-free mass between normal-weight and obese children is
much lower than that of fat mass [33], we argue that adjustment
for fat-free mass should not be able to mask any true effect on fat
mass. Moreover, we checked for each of the other investigated
factors whether adjustment for fat-free mass influences the OR.
This was, apart from the effect for birth weight, not the case.
Caesarian section is another putative risk factor for childhood
obesity that came into focus rather recently [34]. We also did find
an elevated risk for obesity in the offspring, also after controlling
for gestational gain, maternal BMI and breastfeeding initiation.
However, in the final multivariate model Caesarian section was
not of particular importance, when judged by the Wald statistic,
and no longer statistically significant. The impact breastfeeding
exerts on overweight is controversial since it is influenced by
several other risk factors, as e.g. socioeconomic status, maternal
BMI and maternal smoking [35]. One of the rare RCTs showed
no effects of feeding breast milk on the prevalence of obesity until
Table 3. IOTF obesity risk of early life course factors.
Raw OR OR adjusted for confounding factors
Controls Cases OR a
95% CI OR ab
95% CI Adjustment factors
Maternal smoking during pregnancy N % N % Maternal BMI, parental educational level
No 857 88.0 809 83.1 1.00 – 1.00 –
Yes 117 12.0 165 16.9 1.52 1.16–1.98 1.50 1.09–2.06
Gestational weight gain in kg N % N % Maternal BMI
,10 179 20.7 160 18.5 0.85 0.65–1.13 0.81 0.59–1.11
10–,15 434 50.1 414 47.8 1.00 – 1.00 –
15–,25 225 26.0 245 28.3 1.07 0.84–1.36 1.03 0.79–1.35
. = 25 28 3.2 47 5.4 2.00 1.16–3.45 2.11 1.14–3.89
Gestational diabetes N % N % Maternal BMI
No 999 97.6 991 96.8 1.00 – 1.00 –
Yes 25 2.4 33 3.2 1.32 0.79–2.22 1.05 0.57–1.94
Birth weight in kg N % N % Resistance index of the child
,2.5 73 7.6 44 4.5 0.58 0.39–0.86 1.00 0.55–1.82
2.5–4 836 86.8 830 85.3 1.00 – 1.00 –
.4 54 5.6 99 10.2 1.83 1.26–2.65 0.99 0.57–1.71
Caesarian section N % N % Maternal BMI, gestational weight gain, initiation of breastfeeding
No 662 70.4 596 62.7 1.00 – 1.00 –
Yes 279 29.6 355 37.3 1.43 1.17–1.75 1.27 0.99–1.64
Breastfeeding N % N % Maternal BMI, parental educational level, maternal smoking during pregnancy
No 252 24.6 310 30.3 1.00 – 1.00 –
Yes 772 75.4 714 69.7 0.75 0.61–0.91 0.91 0.70–1.18
Breastfeeding duration in months N % N % Maternal BMI, parental educational level, maternal smoking during pregnancy
0 252 24.6 310 30.3 1.00 – 1.00 –
.0–3 171 16.7 181 17.7 0.86 0.66–1.12 1.03 0.73–1.44
4–6 311 30.4 276 27.0 0.71 0.56–0.90 0.89 0.66–1.21
7–11 218 21.3 170 16.6 0.62 0.47–0.81 0.70 0.49–0.99
. = 12 72 7.0 87 8.5 0.93 0.65–1.35 1.25 0.80–1.94
Early introduction of solid foods N % N % Parental educational level, duration of breastfeeding
No 955 93.3 931 90.9 1.00 – 1.00 –
Yes 69 6.7 93 9.1 1.43 1.02–2.01 1.33 0.93–1.90
a Analyses were matched on sex, age and country.
b Analyses were additionally adjusted for putative confounders (see last column).
Matched odds ratios (OR) and 95% confidence intervals (95% CI): OR with p,0.05 are printed in bold. doi:10.1371/journal.pone.0086914.t003
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the age of 15 [36], suggesting that the protective effects found in
other studies were due to statistical artifacts. Similarly, the RCT of
Kramer et al. on breastfeeding promotion in preterm babies in
Belarus showed no difference regarding obesity prevalence later in
life in the two arms of the study [37]. Many previous studies have
investigated either ever versus never-breastfeeding, while fewer
have studied the duration of breastfeeding. Moreover, duration of
breast-feeding is frequently modeled as months of breastfeeding
assuming thus a strictly linear effect without any upper limit. In
our study, we categorized the duration of breastfeeding and found
a u-shaped effect. Interestingly, a similar pattern was found in a
cohort study in Brazil [38] and in a secondary analyses of several
cohorts examining the risk of duration of breastfeeding on
cardiovascular risk factors [39]. However in our study, the effects
were no longer statistically significant when controlling for
confounding factors. As many other studies [5,40–42], we also
found a strong impact of parental weight status on the risk of
childhood obesity. In a full model that included all investigated
early life course risk factors for which we could establish an effect,
gestational weight gain, smoking during pregnancy, Caesarian
section were found to be risk factors for later childhood obesity,
and breastfeeding 4 to 11 months was found to be protective.
However, after additional adjustment for parental BMI and
parental educational status, only gestational weight gain remained
statistically significant. Both, maternal as well as paternal BMI
were the strongest risk factors in our study, and they confounded
several of the investigated associations. The current study has
several limitations. It has to be kept in mind that the IDEFICS
regions are not representative of the respective countries of
Europe, let alone of the European population as a whole.
Moreover, due to the high number of Italian obese children in
the IDEFICS baseline survey (and the low number in Sweden and
Belgium), the case-control sample was highly unbalanced with
regard to country. As country was a matching variable this should
not bias the results. We did not test for different effects by country,
as we did for sex and age group, since the sample size was too
small for most countries. For most of the associations that are
hypothesized to be of a physiologic nature, like e.g. the association
between Caesarian section and obesity, generalizability should not
be compromised by the choice of regions. However, the
association of social factors, like parental education, with
childhood obesity is strongly dependent on context and therefore
of limited external validity [12].
The investigated risk factors all rely on parental self-report. The
validity of parental recall of most of the investigated factors is quite
high, and we did not find much evidence for differential
misclassification, which means that recall bias leads to risk
attenuation rather than to distorted results. Recall bias might
play a role in the lacking effect for introduction of solid food, as
this factors has probably lowest validity among all investigated
factors. Parental BMI is calculated using self-reported height and
weight. Self-reported BMI is known to underestimate the true
BMI, especially in the obese [43]. Assuming a familial clustering of
obesity this produces a likely differential misclassification for
parental BMI in our cases and controls. This misclassification also
leads to attenuated Odds Ratios for paternal and maternal BMI,
since especially among cases the proportion of overweight and
obese parents is underestimated as opposed to the control group.
Our results show that parental BMI is of particular importance
for childhood obesity. The parental BMI is a factor or an indicator
for very different causal pathways, belonging to categories of
shared genetics, a shared obesogenic environment or the process
known as early programming. Currently many obesity interven-
tion programs target children. However, reducing the prevalence
of parental overweight and obesity would not only help preventing
childhood obesity, but would in general lead to an improved
health not only of the children, but also of their parents. Beyond
this, our results indicate that especially maternal weight gain
should be monitored closely during pregnancy. The mechanisms
and possible prevention targets of maternal diet [44,45] and other
social and behavioral factors before and during pregnancy as risk
factors for parental BMI and high gestational weight gain as well
as for obesity in the offspring should be the subject of further
studies.
Supporting Information
Table S1 Distribution of continuous variables in the study
population.
(DOCX)
Author Contributions
Analyzed the data: KB JP. Contributed reagents/materials/analysis tools:
KB JP SDH MH DM LAM MT TV WA AS. Wrote the paper: KB JP
MH AS. Conceived and designed the study: KB DM LAM WA AS.
References
1. Fiese BH, Bost KK, McBride BA, Donovan SM (2013) Childhood obesity
prevention from cell to society. Trends Endocrinol Metab 24: 375–377.
2. Fruhbeck G, Toplak H, Woodward E, Yumuk V, Maislos M, et al. (2013)
Obesity: the gateway to ill health - an EASO position statement on a rising
public health, clinical and scientific challenge in Europe. Obes Facts 6: 117–120.
3. Bleich SN, Ku R, Wang YC (2011) Relative contribution of energy intake and
energy expenditure to childhood obesity: a review of the literature and directions
for future research. Int J Obes (Lond) 35: 1–15.
4. Heerwagen MJ, Miller MR, Barbour LA, Friedman JE (2010) Maternal obesity
and fetal metabolic programming: a fertile epigenetic soil. Am J Physiol Regul
Integr Comp Physiol 299: R711–722.
Table 4. Multivariate models for pre-, peri- and postpartum risk factors on IOTF obesity risk.
Model I Model II
ORab 95% CI Wald ORab 95% CI Wald
Gestational weight gain in kg
1.02 1.00–1.04 3. 827 1.04 1.01–1.07 8.717
Smoking during pregnancy
1.48 1.08–2.01 6.102 1.43 0.94–2.16 2.771
Caesarian section 1.38 1.10–1.74 7.558 1.17 0.87–1.57 1.015
Breastfeeding 4 to 11 months
0.77 0.62–0.96 5.415 0.83 0.62–1.11 1.552
Early introduction of solid foods
1.12 0.75–1.68 0.315 1.23 0.71–2.12 0.528
Maternal BMI 1.16 1.11–1.20 56.858
Paternal BMI 1.11 1.07–1.16 27.017
Parental educational level
0.92 0.81–1.04 1.686
a Analyses were matched on sex, age and country.
bAnalyses were additionally adjusted for all parameters in the respective column. Matched odds ratios (OR), 95% confidence intervals (95% CI) and Wald-statistics (Wald): OR with p,0.05 are printed in bold. doi:10.1371/journal.pone.0086914.t004
Early Life Course Factors for Childhood Obesity
PLOS ONE | www.plosone.org 6 February 2014 | Volume 9 | Issue 2 | e86914
5. Tounian P (2011) Programming towards childhood obesity. Ann Nutr Metab 58
Suppl 2: 30–41. 6. Yu ZB, Han SP, Zhu GZ, Zhu C, Wang XJ, et al. (2011) Birth weight and
subsequent risk of obesity: a systematic review and meta-analysis. Obes Rev 12:
525–542. 7. Beyerlein A, von Kries R (2011) Breastfeeding and body composition in
children: will there ever be conclusive empirical evidence for a protective effect against overweight? Am J Clin Nutr 94: 1772S–1775S.
8. Amir LH, Donath SM (2003) Does maternal smoking have a negative
physiological effect on breastfeeding? The epidemiological evidence. Breastfeed Rev 11: 19–29.
9. Amir LH, Donath S (2007) A systematic review of maternal obesity and breastfeeding intention, initiation and duration. BMC Pregnancy Childbirth 7:
9. 10. Bartok CJ, Ventura AK (2009) Mechanisms underlying the association between
breastfeeding and obesity. Int J Pediatr Obes 4: 196–204.
11. Ahrens W, Bammann K, Siani A, Buchecker K, De Henauw S, et al. (2011) The IDEFICS cohort: design, characteristics and participation in the baseline survey.
Int J Obes (Lond) 35 Suppl 1: S3–15. 12. Bammann K, Gwozdz W, Lanfer A, Barba G, De Henauw S, et al. (2013)
Socioeconomic factors and childhood overweight in Europe: results from the
multi-centre IDEFICS study. Pediatr Obes 8: 1–12. 13. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH (2000) Establishing a standard
definition for child overweight and obesity worldwide: international survey. BMJ 320: 1240–1243.
14. Cole TJ, Flegal KM, Nicholls D, Jackson AA (2007) Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ 335: 194.
15. Houtkooper LB, Lohman TG, Going SB, Hall MC (1989) Validity of bioelectric
impedance for body composition assessment in children. J Appl Physiol 66: 814– 821.
16. Tomeo CA, Rich-Edwards JW, Michels KB, Berkey CS, Hunter DJ, et al. (1999) Reproducibility and validity of maternal recall of pregnancy-related events.
Epidemiology 10: 774–777.
17. Jaspers M, de Meer G, Verhulst FC, Ormel J, Reijneveld SA (2010) Limited validity of parental recall on pregnancy, birth, and early childhood at child age
10 years. J Clin Epidemiol 63: 185–191. 18. Walton KA, Murray LJ, Gallagher AM, Cran GW, Savage MJ, et al. (2000)
Parental recall of birthweight: a good proxy for recorded birthweight? Eur J Epidemiol 16: 793–796.
19. Olson JE, Shu XO, Ross JA, Pendergrass T, Robison LL (1997) Medical record
validation of maternally reported birth characteristics and pregnancy-related events: a report from the Children’s Cancer Group. Am J Epidemiol 145: 58–67.
20. Li R, Scanlon KS, Serdula MK (2005) The validity and reliability of maternal recall of breastfeeding practice. Nutr Rev 63: 103–110.
21. Promislow JH, Gladen BC, Sandler DP (2005) Maternal recall of breastfeeding
duration by elderly women. Am J Epidemiol 161: 289–296. 22. Launer LJ, Forman MR, Hundt GL, Sarov B, Chang D, et al. (1992) Maternal
recall of infant feeding events is accurate. J Epidemiol Community Health 46: 203–206.
23. UNESCO United Nations Educational SaCOIfS (2006) ISCED 1997. International Standard Classification of Education. Montreal.
24. Chen K, Lo SH (1999) Case-cohort and case-control analysis with Cox’s model.
Biometrika 86: 755–764. 25. Breslow NE, Day NE (1980) Statistical methods in cancer research Vol. 1 The
analysis of case-control studies. Lyon: International Agency for Research on Cancer. 338 S. p.
26. Dubois L, Girard M (2006) Early determinants of overweight at 4.5 years in a
population-based longitudinal study. Int J Obes (Lond) 30: 610–617. 27. Chen A, Pennell ML, Klebanoff MA, Rogan WJ, Longnecker MP (2006)
Maternal smoking during pregnancy in relation to child overweight: follow-up to age 8 years. Int J Epidemiol 35: 121–130.
28. Howe LD, Matijasevich A, Tilling K, Brion MJ, Leary SD, et al. (2012)
Maternal smoking during pregnancy and offspring trajectories of height and adiposity: comparing maternal and paternal associations. Int J Epidemiol 41:
722–732. 29. Poston L (2012) Gestational weight gain: influences on the long-term health of
the child. Curr Opin Clin Nutr Metab Care 15: 252–257. 30. Herring SJ, Rose MZ, Skouteris H, Oken E (2012) Optimizing weight gain in
pregnancy to prevent obesity in women and children. Diabetes Obes Metab 14:
195–203. 31. Brophy S, Cooksey R, Gravenor MB, Mistry R, Thomas N, et al. (2009) Risk
factors for childhood obesity at age 5: analysis of the millennium cohort study. BMC Public Health 9: 467.
32. Labayen I, Moreno LA, Blay MG, Blay VA, Mesana MI, et al. (2006) Early
programming of body composition and fat distribution in adolescents. J Nutr 136: 147–152.
33. Wells JC, Fewtrell MS, Williams JE, Haroun D, Lawson MS, et al. (2006) Body composition in normal weight, overweight and obese children: matched case-
control analyses of total and regional tissue masses, and body composition trends in relation to relative weight. Int J Obes (Lond) 30: 1506–1513.
34. Blustein J, Attina T, Liu M, Ryan AM, Cox LM, et al. (2013) Association of
caesarean delivery with child adiposity from age 6 weeks to 15 years. Int J Obes (Lond) 37: 900–906.
35. Brion MJ, Lawlor DA, Matijasevich A, Horta B, Anselmi L, et al. (2011) What
are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts.
Int J Epidemiol 40: 670–680. 36. Singhal A, Cole TJ, Fewtrell M, Lucas A (2004) Breastmilk feeding and
lipoprotein profile in adolescents born preterm: follow-up of a prospective
randomised study. Lancet 363: 1571–1578. 37. Kramer MS, Matush L, Vanilovich I, Platt RW, Bogdanovich N, et al. (2009) A
randomized breast-feeding promotion intervention did not reduce child obesity in Belarus. J Nutr 139: 417S–421S.
38. Neutzling MB, Hallal PR, Araujo CL, Horta BL, Vieira Mde F, et al. (2009) Infant feeding and obesity at 11 years: prospective birth cohort study. Int J Pediatr
Obes 4: 143–149.
39. Fall CH, Borja JB, Osmond C, Richter L, Bhargava SK, et al. (2011) Infant- feeding patterns and cardiovascular risk factors in young adulthood: data from
five cohorts in low- and middle-income countries. Int J Epidemiol 40: 47–62. 40. Fleten C, Nystad W, Stigum H, Skjaerven R, Lawlor DA, et al. (2012) Parent-
Offspring Body Mass Index Associations in the Norwegian Mother and Child
Cohort Study: A Family-based Approach to Studying the Role of the Intrauterine Environment in Childhood Adiposity. Am J Epidemiol 176: 83–92.
41. Dieu HT, Dibley MJ, Sibbritt D, Hanh TT (2007) Prevalence of overweight and obesity in preschool children and associated socio-demographic factors in Ho
Chi Minh City, Vietnam. Int J Pediatr Obes 2: 40–50. 42. Durmus B, Arends LR, Ay L, Hokken-Koelega AC, Raat H, et al. (2012)
Parental anthropometrics, early growth and the risk of overweight in pre-school
children: the Generation R Study. Pediatr Obes 8: 339–350. 43. Connor Gorber S, Tremblay M, Moher D, Gorber B (2007) A comparison of
direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev 8: 307–326.
44. Moore VM, Davies MJ, Willson KJ, Worsley A, Robinson JS (2004) Dietary
composition of pregnant women is related to size of the baby at birth. J Nutr 134: 1820–1826.
45. Phelan S, Hart C, Phipps M, Abrams B, Schaffner A, et al. (2011) Maternal behaviors during pregnancy impact offspring obesity risk. Exp Diabetes Res
2011: 985139. 46. Oken E, Levitan EB, Gillman MW (2008) Maternal smoking during pregnancy
and child overweight: systematic review and meta-analysis. Int J Obes (Lond) 32:
201–210. 47. Durmus B, Mook-Kanamori DO, Holzhauer S, Hofman A, van der Beek EM,
et al. (2010) Growth in foetal life and infancy is associated with abdominal adiposity at the age of 2 years: the generation R study. Clin Endocrinol (Oxf) 72:
633–640.
48. Oken E, Rifas-Shiman SL, Field AE, Frazier AL, Gillman MW (2008) Maternal gestational weight gain and offspring weight in adolescence. Obstet Gynecol
112: 999–1006. 49. Oken E, Taveras EM, Kleinman KP, Rich-Edwards JW, Gillman MW (2007)
Gestational weight gain and child adiposity at age 3 years. Am J Obstet Gynecol 196: 322 e321–328.
50. Kim SY, Sharma AJ, Callaghan WM (2012) Gestational diabetes and childhood
obesity: what is the link? Curr Opin Obstet Gynecol 24: 376–381. 51. Barker DJ (1995) The fetal and infant origins of disease. Eur J Clin Invest 25:
457–463. 52. Singhal A, Lucas A (2004) Early origins of cardiovascular disease: is there a
unifying hypothesis? Lancet 363: 1642–1645.
53. Verier C, Meirhaeghe A, Bokor S, Breidenassel C, Manios Y, et al. (2010) Breast-feeding modulates the influence of the peroxisome proliferator-activated
receptor-gamma (PPARG2) Pro12Ala polymorphism on adiposity in adoles- cents: The Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA)
cross-sectional study. Diabetes Care 33: 190–196.
54. Poskitt EM, Breda J (2012) Complementary feeding and non communicable diseases: current knowledge and future research needs. Nutr Metab Cardiovasc
Dis 22: 819–822. 55. Monasta L, Batty GD, Cattaneo A, Lutje V, Ronfani L, et al. (2010) Early-life
determinants of overweight and obesity: a review of systematic reviews. Obes Rev 11: 695–708.
56. Thompson AL (2012) Developmental origins of obesity: early feeding
environments, infant growth, and the intestinal microbiome. Am J Hum Biol 24: 350–360.
57. Gibbs BG, Forste R (2013) Socioeconomic status, infant feeding practices and early childhood obesity. Pediatr Obes Apr 2. doi: 10.1111/j.2047–
6310.2013.00155.x. [Epub ahead of print].
58. Huh SY, Rifas-Shiman SL, Taveras EM, Oken E, Gillman MW (2011) Timing of solid food introduction and risk of obesity in preschool-aged children.
Pediatrics 127: e544–551. 59. Wasser H, Bentley M, Borja J, Davis Goldman B, Thompson A, et al. (2011)
Infants perceived as ‘‘fussy’’ are more likely to receive complementary foods before 4 months. Pediatrics 127: 229–237.
Early Life Course Factors for Childhood Obesity
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