# Association Between Parental Social Position and Childhood Overweight: Mediation by Lifestyle and BMI Patterns During Pregnancy

Camille Le Gal, Mireille C Schipper, Marion Lecorguillé, Laura Pavicic, Thierry Simeon, Marie-aline Charles, Romy Gaillard, Sandrine Lioret, Barbara Heude

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Camille Le Gal, Mireille C Schipper, Marion Lecorguillé, Laura Pavicic, Thierry Simeon, et al. *Association Between Parental Social Position and Childhood Overweight: Mediation by Lifestyle and BMI Patterns During Pregnancy*. Pediatric Obesity, inPress, 10.1111/ijpo.70047. hal-05240651

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ORIGINAL RESEARCH

OPEN ACCESS

# Association Between Parental Social Position and Childhood Overweight: Mediation by Lifestyle and BMI Patterns During Pregnancy

Camille Le Gal¹

<figure><img src="image_3.png" /></figure>

Mireille C. Schipper²,³ | Marion Lecorguillé¹

<figure><img src="image_4.png" /></figure>

Laura Pavicic¹ | Thierry Simeon⁴

<figure><img src="image_5.png" /></figure>

Marie-Aline Charles⁴ | Romy Gaillard²,³ | Sandrine Lioret¹ | Barbara Heude¹

¹Université Paris Cité and Université Sorbonne Paris Nord, Paris, France | ²Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, the Netherlands | ³Department of Pediatrics, Sophia's Children's Hospital, Erasmus MC, University Medical Center, Rotterdam, the Netherlands | ⁴Ums INED-INSERM-EFS, Paris, France

**Correspondence:** Camille Le Gal (camille.le-gal@inserm.fr)

**Received:** 21 November 2024 | **Revised:** 8 July 2025 | **Accepted:** 23 July 2025

**Funding:** This work was supported by European Union's Horizon 2020 research and innovation program, 733206, Agence Nationale de la Recherche, ANR-11-EQPX-0038, ANR-19-COH0-0001, ANR-19-CE36-0006, Netherlands Organization for Health Research and Development, NWO, ZonMw VIDI 09150172110034, NWO, ZonMw, 05430052110007, Dutch Diabetes Research Foundation, 2024.28.001, European Research Council Starting Grant, ERC-2024-STG-101161004.

**Keywords:** childhood overweight | migration | prenatal lifestyle factors | social inequalities

## ABSTRACT

In high-income countries, children born to parents with low socio-economic position (SEP) or with non-Western ethnicity are disproportionally affected by obesity as early as preschool age. We assessed how much of these associations were mediated by parental lifestyle and BMI patterns during pregnancy. We characterised 5–6 years old children with or without overweight from the French Etude Longitudinale Française depuis l'Enfance (ELFE) (n = 8584) and the Dutch Generation R birth cohorts (n = 6511). We used counterfactual mediation analyses to assess the potential mediating effect of previously identified lifestyle patterns: “high parental smoking, poor-quality maternal diet and sedentary behaviour” and “high parental body mass index and low gestational weight gain”. Both patterns jointly mediated 62.8% of the association between parents' education level and childhood overweight in ELFE and 23.2% in Generation R. In Generation R, they jointly mediated 8.9% of the association between parents' geographic origin and childhood overweight. In ELFE, parents with non-Western backgrounds were less likely to follow the first pattern, resulting in a negative indirect effect. Parental lifestyle and BMI patterns during pregnancy seem key contributors to the early development of socio-economic inequalities in childhood overweight, while other yet unidentified factors may contribute to inequalities related to geographic origin.

## 1 | Introduction

A recent Non-Communicable Disease Risk Factor Collaboration and WHO study, analysing data for 63 million individuals aged 5 to 19 years across 190 countries, revealed an increase in childhood and adolescent obesity from 31 million in 1990

to 160 million in 2022 [1, 2]. For European children aged 2 to 7 years, the prevalence of overweight (obesity included) was estimated at 17.9% in 2016 [3]. Multiple studies [4, 5] have demonstrated a negative link between parent's socio-economic position (SEP) and risk of childhood overweight early in life. Early overweight predisposes children to a multitude of comorbidities [6]

Sandrine Lioret and Barbara Heude shared the last authorship.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Pediatric Obesity* published by John Wiley & Sons Ltd on behalf of World Obesity Federation.
and also substantially increases their risk of adult obesity [7],
thereby reinforcing socio-economic health inequalities through-
out life [8].

Besides SEP, evidence across Europe suggests that children
from parents with an immigrant background may be at in-
creased risk of overweight as compared with their native
counterparts [9–11]. Our previous study [12] of the French
Etude Longitudinale Française depuis l'Enfance (ELFE) birth
cohort confirmed that children of immigrant mothers, and
to a lesser extent those born to descendants of immigrants,
were at an increased risk of overweight from as early as age
3.5 years as compared with their peers born to non-immigrant
mothers. Likewise, work by Van Rossem et al. [13] identified
a higher obesity risk trajectory among children of non-Dutch
ethnic background in the Generation R birth cohort, in The
Netherlands up to age 4 years.

Such an early social patterning of overweight is a major pub-
lic health concern but also a matter of social justice. A better
understanding of the mechanisms involved is needed to facil-
itate more effective efforts to address this injustice, but these
causal pathways remain underexplored. This gap in knowl-
edge becomes particularly critical considering the notable
prevalence of overweight in very young children, which un-
derscores the importance of early life risk factors. The precon-
ception and pregnancy periods are increasingly recognised as
a window of vulnerability for the programming of cardiometa-
bolic health [14]. In the literature, individual risk factors iden-
tified with a robust level of evidence include high maternal
body mass index (BMI), excessive gestational weight gain,
unhealthy diet, smoking, and sedentary behaviours [15, 16].
These lifestyle and BMI-related factors are also socially pat-
terned [17, 18]. However, they are often analysed separately
even though they interact with each other and combine into
patterns, with supposedly synergistic effects on both mother
and child health. Furthermore, these lifestyle behaviours and
BMI status are related between parents. In the context of the
European EndObesity consortium, Lecorguillé et al. [19] used
an integrative approach to synthesise mothers' and fathers'
lifestyle and BMI factors during pregnancy into patterns. Two
of these patterns were common to the ELFE and Generation
R cohorts and were found associated with increased risk of
childhood overweight. The first lifestyle pattern was charac-
terised by high parental smoking, poor-quality maternal diet,
and sedentary behaviour in the French ELFE cohort and high
parental smoking and poor-quality maternal diet in the Dutch
Generation R cohort. The second pattern featured high paren-
tal body mass index and low gestational weight gain.

Building on these novel insights, along with the known social patterning of lifestyle behaviours and BMI in adults [20], the current study investigated to what extent these parental lifestyle and BMI patterns during pregnancy mediate the association between parental social position and their child's risk of overweight. Social position was assessed using multiple dimensions: parents' geographic origin and parents' SEP, defined by education level and household income. We tested this mediation hypothesis in two distinct European populations, the ELFE and Generation R cohorts, to allow for comparing results between different settings.

2 | Materials and Methods

## 2.1 | Study Population

The multidisciplinary and national ELFE birth cohort [21] enrolled 18 329 children from a random sample of 344 maternity units across hexagonal France in 2011. The enrollment took place over 25 days in four waves of 4 to 8 days each, covering all four seasons. Inclusion criteria were single or twin births ≥ 33 weeks of gestation and mothers aged ≥ 18 years and not planning to leave mainland France for the next 3 years. Recognising the language diversity among the population, study materials, including the information letter and consent form, were made available in Arabic, Turkish, and English, the three most commonly spoken languages in France among non-French speakers. Consent for their child's participation was obtained from 51% of eligible mothers, with fathers (if present) given the chance to consent and informed of their right to oppose the study.

The Generation R study is a prospective cohort study from early
pregnancy onward in Rotterdam, The Netherlands [22]. Eligible
mothers had to live in the study area with a delivery date from
April 2002 to January 2006. The study aimed to enrol mothers
in early pregnancy (gestational age < 18 weeks), but enrolment
was allowed until the birth of the child. In total, 9778 mothers
were included in the study (response rate 61%), 91% (n = 8880)
during pregnancy. Fathers were invited to participate, with 71%
(n = 6347) enrolling. Mothers and fathers were asked for their
written informed consent. At the start of each phase, moth-
ers and fathers received written and oral information about
the study.

## 2.2 | Data Collection and Measurements

For analyses, preference was given to using variables that were
harmonised [23] between the two cohorts from previous work
conducted as part of the EU Child cohort Network which op-
erates as a federated analysis infrastructure with harmonised
datasets [24].

## 2.3 | Social Position (Exposure): Geographic Origin and Socio-Economic Position (Education Level and Income)

In the ELFE cohort, maternal and paternal geographic origin
data and SEP factors, including education level and household
income, were collected by computer-assisted telephone inter-
views when the child was 2 months old. In the Generation R
cohort, all three factors were collected with self-reported ques-
tionnaires at study enrollment.

The child's geographic origin was classified as "at least one non-Western parent" versus "no non-Western parent". Parents' education was determined by the highest level achieved by either of the child's parents and classified as "≤ high school degree" versus "≥ undergraduate degree" (corresponding to short-cycle tertiary education or above). Household income was dichotomized according to the first quintile of its distribution in ELFE
and based on 1200 €/monthly in Generation R. These definitions
are further detailed in [Supporting Information](#).

## 2.4 | Parental Lifestyle and BMI Patterns (Candidate Mediators)

The two parental lifestyle and BMI patterns from the previously mentioned work by Lecorguillé et al. [19] were derived by using principal component analyses and thus are independent (orthogonal) by construction. Each cohort mother-father dyad has a score on each lifestyle pattern, with high (low) scores indicating high (low) adherence to a given pattern [19].

## 2.5 | Childhood Anthropometrics (Outcome)

Anthropometric measurements were collected by telephone when the child was about age 5 in ELFE: parents were asked to report their child's weight and height as recorded in the health booklet. In Generation R, weight and height were measured in all children at about 6 years at the research centre. Child BMI was calculated as weight (kg)/[height (m)]². Children were classified as having overweight (including obesity) or thin/normal BMI status based on age- and sex-specific cut-offs from the International Obesity Task Force (IOTF), corresponding to an adult BMI equivalent of ≥ 25 kg/m².

## 2.6 | Covariates

Covariates, including child sex, maternal age at delivery, and parity, were collected by in-person interviews upon delivery at the maternity hospital in ELFE, and details on maternal health history were collected from medical records. In Generation R, covariates were obtained from medical records or by questionnaires at enrollment or during pregnancy, as described in the statistical analysis section.

## 2.7 | Study Sample Selected for Statistical Analysis

In ELFE, we included one randomly selected twin, whereas in Generation R, twins were excluded from the analysis because the proportion of missing data was higher in this group and

imputation was questionable because of the inherent specificities of this population (Figure 1). Anthropometric measurements among children were selected from age ranges of 4.2 to 6.5 years (average 5.0 years) in ELFE and 4.8 to 9.1 years (average 6.2 years) in Generation R. Only children with at least one BMI measure available within these age ranges in both cohorts were eligible for analyses (N=8584 in ELFE and N=6511 in Generation R). When multiple BMI measures were available for the same child, only the last one was used.

## 2.8 | Statistical Analysis

We examined the associations between indicators of social position and the two previously derived parental lifestyle and BMI patterns (derived by Lecorguillé et al. [19]) using multivariable linear regression analyses. We used counterfactual mediation analyses to explore the role of these patterns in the causal pathway between social position indicators and the risk of overweight in children at ages 5 to 6, analysing each cohort separately. Counterfactual mediation analysis was used to break down the total effect of each social position indicator under study on child's overweight risk into the sum of a natural direct effect (NDE, independent of the candidate mediators) and natural indirect effect (NIE, via candidate mediators) (Figure 2). As an example, for parents' education level, the total effect can be considered as the change in overweight risk if the education level changed from "≥ undergraduate degree" to "≤ high school degree". Here, the NDE would be the change in overweight risk from the same shift in education level while keeping mediators at the values they naturally take when the education level is unchanged (e.g., "≥ undergraduate degree"). Also, the NIE would be the change in overweight risk if parents' education level remained unmodified (e.g., "≥ undergraduate degree") but mediators changed to the values they would naturally take if the education level had shifted from "≥ undergraduate degree" to "≤ high school degree". For these analyses, we used the Medflex package in RStudio (2022) (RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA) dedicated to counterfactual mediation analysis. This allowed us to estimate the mediated proportion attributable to each lifestyle and BMI pattern individually as well as the collective mediated effect of the two patterns combined. Of note, the proportion could not be estimated and was therefore not reported when the natural direct and indirect effects were of opposite signs.

ELFE

$n=18329$ children includes within the ELFE cohort

$n=18042$ children

**Study population:**
$n=8584$ children with information on weight status at age 5

**Excluded:**

Twin birth
(only one of the twin is included)
$n=287$

**Excluded:**

Children with no information on weight status at age 5.
Of whom : 7640 were lost to follow-up
$n=9458$

Generation R

$n=9901$ children born to 9778 mothers within Generation R

**Excluded:**

Twin birth
Induced abortion
IUVD
Loss to follow up
$n=246$
$n=29$
$n=75$
$n=45$

$n=9506$ singleton live births

**Excluded:**

Children with no information on weight status at age around 6 or lost to follow up
$n=2995$

**Study population:**

$n=6511$ children with information on weight status at age around 6

<caption>**FIGURE 1** | Flow chart of the study sample in the ELFE (left) and Generation R (right) cohort.</caption>
<figure><img src="image_6.png" /><figcaption>**FIGURE 2** | Conceptual framework for mediation analyses. Baseline assessment during pregnancy.</figcaption></figure>

All association and mediation analyses were adjusted for child sex, maternal age at delivery, and parity. Analyses focusing on parents' education level were further adjusted for parents' geographic origin. The examined income levels were adjusted for both parents' geographic origin and education level. These adjustments were consistent with the previous work by Le Gal et al. [12], which structured analyses following a socio-ecological framework. We assumed that parents' geographic origin and education level were at the most distal levels, with the latter influencing income level, the most proximal variable. This hierarchical approach was designed to ensure that intermediate exposures did not affect the association of the distal exposures with the outcome under study [25, 26].

We used the Multivariate Imputation by Chained Equations [27] package in R to address missing data, including all relevant variables providing information for the imputation process and assuming the data were missing at random. We generated 10 imputed datasets and ensured reproducibility by using a fixed random seed. The results of the imputed datasets were combined using the Mlcombine function in R, which estimates combined effects and their confidence intervals. This method aligns with Rubin's rules [28] by considering both within- and between- imputation variability, ensuring the standard errors reflect the uncertainty due to missing data.

In accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, we adhered to its methodological framework and provided a detailed checklist in the Supporting Information.

## 3 | Results

In the ELFE and Generation R cohorts, 696 of 8594 (8.1%) and 1149 of 6511 (17.6%) children included in the study samples exhibited

overweight at age 5 to 6 years (Table 1). Notably, the proportion of non-Western parents was threefold higher in Generation R than in ELFE (37.9% vs. 12.3%). In addition, the proportion of parents with an education level below a high school degree was twice as high in Generation R than in ELFE (50.3% vs. 23.2%).

In ELFE, parents with non-Western backgrounds were less likely to adhere to the first pattern, characterised by high parental smoking, poor-quality maternal diet, and maternal sedentary behaviour than their Western counterparts; no such association was observed in Generation R (Table 2). SEP factors were inversely associated with this lifestyle pattern in both cohorts. Parents from non-Western backgrounds, with a low education level (in both cohorts), or those with a low income (in ELFE only) were more likely to follow the second pattern, characterised by high parental BMI and low gestational weight gain; of note, parents with a low income had lower scores on this pattern in Generation R than ELFE.

When considering the association between parents' geographic origin and child overweight, the NIE for the combined parental lifestyle and BMI patterns in ELFE was negative ($\beta_{NIE}$ -0.04 [95% CI -0.08; -0.01]) (Figure 3a). When analysed separately, only the first lifestyle pattern had a negative NIE ($\beta_{NIE}$ -0.07 [-0.11; -0.04]). The second pattern positively mediated a small portion of the association ($\beta_{NIE}$ 0.03 [0.01; 0.05]). In Generation R, the NIE for the combined patterns was positive ($\beta_{NIE}$ 0.08 [0.05; 0.11]), corresponding to a mediation of 8.9% of the total effect. The main contributor was the second pattern, accounting for almost the entire mediation effect.

Regarding SEP, the two lifestyle and BMI patterns combined explained 62.8% of the association between parents' education level and childhood overweight ($\beta_{NIE}$ 0.27 [0.22; 0.34]) in ELFE (Figure 3b). The first pattern contributed more than the second one ($\beta_{NIE}$ 0.26 [0.20; 0.32]) versus ($\beta_{NIE}$ 0.03 [0.01; 0.05]). In
<table><caption>TABLE 1 | Characteristics of the ELFE (N=8584) and Generation R (N=6511) samples at age 5 to 6 years.</caption><thead><tr><th></th><th>ELFE<br>(N=8584)</th><th>Generation<br>R (N=6511)</th></tr></thead><tbody><tr><td>Child with overweight</td><td>8.1% (696)</td><td>17.6% (1149)</td></tr><tr><td>Sex of the child</td><td></td><td></td></tr><tr><td>Girl</td><td>48.5% (4162)</td><td>49.8% (3240)</td></tr><tr><td>Maternal age at delivery<br>(years), Mean (SD)</td><td>30.90 (4.59)</td><td>31.0 (5.20)</td></tr><tr><td>Parity</td><td></td><td></td></tr><tr><td>First time mother</td><td>46.9% (3978)</td><td>54.6% (3554)</td></tr><tr><td>Second time mother</td><td>36.5% (3096)</td><td>29.3% (1908)</td></tr><tr><td>≥ Third time mother</td><td>12.3% (1045)</td><td>12.8% (832)</td></tr><tr><td>Missing values</td><td>102</td><td>217</td></tr><tr><td>Parent's geographical origin</td><td></td><td></td></tr><tr><td>At least one Non-<br>Western parent</td><td>12.3% (1054)</td><td>37.9% (2468)</td></tr><tr><td>Missing values</td><td>255</td><td>176</td></tr><tr><td>Parent's education level</td><td></td><td></td></tr><tr><td>≤ High school degree</td><td>23.2% (1992)</td><td>50.3% (3272)</td></tr><tr><td>Missing values</td><td>0</td><td>0</td></tr><tr><td>Household income* (€)</td><td></td><td></td></tr><tr><td>1st Quintile or ≤ 1200 €</td><td>12.4% (1063)</td><td>13.0% (844)</td></tr><tr><td>Missing values</td><td>452</td><td>1601</td></tr></tbody></table>

Note: As total household income in the Generation R cohort.

*Household income is expressed per consumption unit in the ELFE cohort, whereas it is reported.

Generation R, the global mediating effect was 23.2% ($\beta_{NIE}$ 0.13 [0.09; 0.17]), with both parental lifestyle and BMI patterns contributing almost equally.

Although the total effect of household income level on childhood overweight was close to zero in both cohorts after adjusting for parents' geographic origin and education level, the two patterns combined mediated a major proportion of the association in ELFE: 71.8% ($\beta_{NIE}$ 0.10 [0.06; 0.15]) (Figure 3c). We found no mediating effect for this association in the Generation R cohort.

## 4 | Discussion

This study is among the first to explore early mechanisms contributing to social inequalities in childhood overweight, by addressing different dimensions of social position along with the lifestyle and BMI status of both parents during pregnancy. In two birth cohorts from France and The Netherlands, common lifestyle and BMI patterns mediated an important part of the association between SEP and childhood overweight. Yet, these patterns had inconsistent mediating effects across the cohorts for the association between parents' geographic origin and

childhood overweight, showing a negative indirect effect in ELFE but not Generation R.

To the best of our knowledge, no other study has assessed how parental lifestyle and BMI patterns during pregnancy mediate the association of parents' geographic origin and child overweight, so direct comparisons with the literature are challenging. Our prior research in ELFE [12] showed that the increased likelihood of overweight in 3.5-year-old children born to mothers with an immigration background was only slightly mitigated after adjusting for maternal education level, maternal occupational category, and household income level. Likewise, in the Generation R cohort, Van Rossem et al. [13] found that the increased likelihood of overweight in 2-year-old children born to Turkish or Moroccan parents versus those born to native Dutch parents was only slightly mitigated after adjusting for maternal education level, household income, and material hardship. Altogether, the results of these two studies suggest that the influence of parental migration status/ethnicity on childhood overweight is mainly due to factors other than these dimensions of SEP.

The differences in mediation effects we observed between cohorts is likely due to substantial socio-demographic disparities. As compared with the ELFE cohort, the Generation R cohort has a higher proportion of parents born outside the cohort's country. Their non-Western population also differs in nationalities, with immigrants originating mainly from Turkey, Morocco, and Suriname in The Netherlands and from Maghreb and Sub-Saharan Africa in France. Another explanation could also partly derive from the theory of the healthy migrant effect: individuals capable of migrating generally have higher economic resources, better health status, and healthier lifestyle on average than their non-migrating counterparts, both in their country of origin and in the host country [29]. However, this paradigm might vary depending on the specific geographic origin, host country, and reasons for migration, which differ by context [30]. Previous findings from the ELFE study showed that immigrant mothers have healthier dietary habits regardless of their SEP [31] and a lower smoking prevalence as compared with non-immigrant mothers [32]. Also, smoking prevalence was found to be low among non-Western populations in The Netherlands [33].

However, these explanations do not elucidate the mechanisms underlying the total effect of geographic origin on childhood overweight. Beyond SEP dimensions, unmeasured social determinants of health, such as language proficiency, health literacy, social support, healthcare access, and other psychosocial factors may also play a role [34–36]. Especially, factors related to stigma or structural discrimination can lead to chronic psychosocial stress, identified as a contributor to the social origin of obesity [35, 37, 38] Another likely mediation hypothesis involves parenting practices related to the child's diet and movement behaviours early in life, the confirmation of which was beyond the scope of the study: in particular, immigrant parents may face specific barriers to maintaining their traditional lifestyle for their child because of conflicting social norms and expectations in their host country [39, 40].

For mediation analyses involving parental SEP (specifically education level and household income), results across both cohorts are
<table><caption>TABLE 2 | Association between parental social position indicators and parental lifestyle and BMI patterns in ELFE and Generation R cohorts.</caption><thead><tr><th rowspan="3"></th><th colspan="6">High parental smoking, poor-quality maternal diet (and maternal sedentary behaviour in ELFE)</th><th colspan="4">High parental BMI and low gestational weight gain</th></tr><tr><th colspan="3">ELFE</th><th colspan="3">Generation R</th><th colspan="3">ELFE</th><th colspan="2">Generation R</th></tr><tr><th>N</th><th>β</th><th>95% CI</th><th>p</th><th>N</th><th>β</th><th>95% CI</th><th>p</th><th>β</th><th>95% CI</th><th>p</th><th>β</th><th>95% CI</th><th>p</th></tr></thead><tbody><tr><td>Parents' geographic origin</td><td>8229</td><td></td><td></td><td>&lt;0.001</td><td>5917</td><td></td><td>0.5</td><td></td><td></td><td>0.002</td><td></td><td></td><td>&lt;0.001</td><td></td></tr><tr><td>No Non-Western parent</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>At least one Non-Western parent</td><td></td><td>-0.21</td><td>-0.29; -0.13</td><td></td><td>0.03</td><td>-0.05; 0.11</td><td></td><td>-0.11</td><td>-0.04; -0.19</td><td></td><td>-0.28</td><td>-0.34; -0.21</td><td></td></tr><tr><td>Parents' education level</td><td>8229</td><td></td><td></td><td>&lt;0.001</td><td>5917</td><td></td><td>&lt;0.001</td><td></td><td></td><td>0.008</td><td></td><td></td><td>&lt;0.001</td><td></td></tr><tr><td>≥ Undergraduate degree</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>≤ High school degree</td><td></td><td>0.84</td><td>0.78; 0.90</td><td></td><td>0.71</td><td>0.63; 0.79</td><td></td><td>-0.08</td><td>-0.02; -0.14</td><td></td><td>-0.19</td><td>-0.26; -0.13</td><td></td></tr><tr><td>Household income* (€)</td><td>7985</td><td></td><td></td><td>&lt;0.001</td><td>4803</td><td></td><td>&lt;0.001</td><td></td><td></td><td>&lt;0.001</td><td></td><td></td><td>0.012</td><td></td></tr><tr><td>&gt; 1st Quintile or &gt; 1200 €</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>1st Quintile or ≤ 1200 €</td><td></td><td>0.21</td><td>0.13; 0.29</td><td></td><td>0.32</td><td>0.20; 0.45</td><td></td><td>-0.18</td><td>-0.11; -0.26</td><td></td><td>0.13</td><td>0.03; 0.23</td><td></td></tr></tbody></table>

Note: As total household income in the Generation R cohort. All analyses were adjusted for child sex, maternal age at birth, and parity. Additionally, analyses focusing on parents' education level were further adjusted for parents' geographical origin. Those examining income level were adjusted for both parents' geographical origin and parent's educational level.

Abbreviations: BMI, body mass index; CI, Confidence interval.

*Household income is expressed per consumption unit in the ELFE cohort, whereas it is reported.
<figure><img src="image_7.png" /><figcaption>**FIGURE 3** | Legend on next page.</figcaption></figure>

consistent, thereby reinforcing their robustness. Our results show that parental lifestyle and BMI patterns during pregnancy mediate the inverse association between parents' education and child overweight. In ELFE, this relation is largely explained by suboptimal parental lifestyle behaviours during pregnancy (first pattern) beyond parental BMI status (second pattern). In Generation R,

both patterns contributed equally to the mediation effect. Several hypotheses could explain why suboptimal parental lifestyle behaviours during pregnancy largely mediate the inverse association between parents' education and child overweight, one involving a greater health literacy of parents with high education attainment [36]. Such parents may better understand and thus implement
**FIGURE 3** | (a) Mediating effect of parental lifestyle and BMI patterns during pregnancy on the association between parents' geographic origin and risk of overweight in children: Results at age 5 to 6 years from the ELFE cohort and Generation R cohort. Here the total effect can be considered as the change in overweight risk if parents' geographic origin changed from "no Non-Western parent" to "at least one non-Western parent". The NDE would be the change in overweight risk from the same shift in geographic origin while keeping mediators at the values they naturally take when geographical origin is unchanged (e.g., "no Non-Western parent"). Also, the NIE would be the change in overweight risk if geographic origin remained unmodified (e.g., "no Non-Western parent") but mediators changed to the values they would naturally take if geographic origin had shifted from "no Non-Western parent" to "at least one non-Western parent". Analyses performed on imputed data and adjusted for child's sex, maternal age, and parity. (b) Mediating effect of parental lifestyle and BMI patterns during pregnancy on the association between parents' education level and risk of overweight in children: Results at age 5 to 6 years from the ELFE cohort and Generation R cohort. Analyses performed on imputed data and adjusted for child's sex, maternal age, parity, and parents' geographic origin. Counterfactual hypothesis: Here the total effect can be considered as the change in overweight risk if parents' education level changed from "≥ undergraduate degree" to "≤ high school degree". The NDE would be the change in overweight risk from the same shift in education level while keeping mediators at the values they naturally take when education is unchanged (e.g., "≥ undergraduate degree"). Also, the NIE would be the change in overweight risk if parents' education level remained unmodified (e.g., "≥ undergraduate degree") but mediators changed to the values they would naturally take if parents' education level had shifted from "≥ undergraduate degree" to "≤ high school degree". (c) Mediating effect of parental lifestyle and BMI patterns during pregnancy on the association between household income level and risk of overweight in children: Results at age 5 to 6 years from the ELFE cohort and Generation R cohort. Analyses performed on imputed data and adjusted for the child's sex, maternal age, parity, parents' geographic origin, and parents' education level. Counterfactual hypothesis: Here the total effect can be considered as the change in overweight risk if household income level changed from "high and medium" to "low". The NDE would be the change in overweight risk from the same shift in income while keeping mediators at the values they naturally take when income is unchanged (e.g., "high and medium"). Also, the NIE would be the change in overweight risk if household income remained unmodified (e.g., "high and medium") but mediators changed to the values they would naturally take if household income level had shifted from "high and medium" to "low". \*\*High and medium" categories correspond here to "Quintile > 1 (ELFE) or > 1200 euros (Generation R)" and "low" category corresponds to "1st Quintile (ELFE) or ≤1200 € (Generation R)".

public health recommendations. Enhanced comprehension and application could manifest in healthier lifestyle patterns adopted by both parents from pregnancy, potentially benefitting foetal development and metabolic programming. Furthermore, considering that parental lifestyle patterns tend to persist postpartum [41] and that parents serve as primary educators and role models for their child [42], children may likely adopt similar lifestyle habits, which in turn contribute to their energy balance equation related to overweight [43].

A Norwegian study [44] of 27134 children aged 5 years used an inverse odds weighting approach and found a 63.7% mediating effect of prenatal and early postnatal factors on the relation between parents' education level and child overweight. A German study [45] of 4772 children aged 5 to 7 years showed a 77.8% mediation by parental lifestyle factors (BMI, smoking, shared meals, media consumption, physical activity) on this association, although these factors were not collected during pregnancy. These data support earlier findings, including a 2017 literature review [46] of factors influencing the SEP-adiposity association in youth up to age 18, highlighting parents' education level as a common SEP indicator and identifying consistent mediators such as breastfeeding duration, maternal pregnancy smoking, and infant feeding practices.

Although our analyses indicate a mediating effect of parents' lifestyle and BMI patterns on the association between household income level and child overweight in the ELFE but not Generation R children at age 5 years, they do not demonstrate a total effect for this association in either cohort. The absence of a total effect could be attributed to low statistical power as well as selection bias and differential attrition biases. These factors may have resulted in the initial selection of participants with high income levels and a greater loss of participants with low income levels over time, thus inhibiting our ability to include individuals with more precarious living conditions in our analyses. However, this variable should

still be considered because household income during pregnancy reflects the family's financial capacity to access goods and services. All else being equal, increased income might enable access to wealthier neighbourhoods to live in and better products and services, such as more optimal prenatal care, healthier food options, and maternal health resources. These advantages could improve maternal nutrition and lifestyle patterns, positively influencing foetal development and metabolic programming of adipose tissue.

This study has some limitations. First, as already mentioned, as in all cohorts, there is an inherent selection and attrition bias, with individuals with high SEP more likely to participate and remain in the study than those experiencing socio-economic disadvantage. This bias may potentially attenuate our ability to investigate the complete social gradient. The absolute value of the indirect effect may be even stronger with a better representation of underprivileged populations as well as more precise measurements of lifestyle behaviours during pregnancy (e.g., objective measurements instead of questionnaires) [47, 48]. Additionally, conducting the study in two distinct cohorts from different countries presented challenges in harmonisation of variables. Despite rigorous efforts to standardise variables, some differences remained across measures. For example, in the ELFE cohort, income was calculated per consumption unit, while in the Generation R cohort, total net household income was used, without adjustment for household size or composition. These methodological differences, combined with unequal purchasing power between countries, limit the comparability of income-related analyses across cohorts. Another example is sedentary behaviour, which was measured in ELFE but not in Generation R and thus characterises the first lifestyle patterns in ELFE but not in Generation R, potentially affecting the comparability of results.

However, this double analysis, conducted both within ELFE and Generation R cohorts, is also a key strength, providing valuable
insights across diverse settings. On the one hand, consistent find-
ings (e.g., with education level) support their robustness. On the
other, discrepant findings (e.g., with geographic background and
income) highlight the importance of accounting for country-
specific factors when targeting at-risk populations and tailoring
public health interventions. Another strength is in examining
both education level and income to approximate SEP because
they capture a non-interchangeable dimension of socio-economic
vulnerability [34], whereas most studies focus solely on education
level. Furthermore, this study is unique in including the parents'
geographic origin variable along with SEP, thus adding another di-
mension to these analyses by going beyond purely socio-economic
aspects. Finally, the analysis used principal component analysis to
address lifestyle and BMI status as patterns rather than individual
risk factors. This approach enables a more comprehensive and in-
tegrated examination of numerous variables that would otherwise
be correlated and would have challenged the mediation analysis.
It provides a holistic view that more accurately reflects real-life
scenarios and enhances our understanding of the complex inter-
actions influencing health outcomes. It also takes into account
paternal factors, in terms of social and health determinants and
within a broader context of lifestyle patterns. These aspects are
not usually included in similar analyses, which represents a key
strength of this research in that it shifts the focus from the mother
to the parental dyad.

Our study highlights the importance of addressing various dimen-
sions of social vulnerability when developing multi-behavioural
interventions. Enhancing knowledge and health literacy with so-
cial support is crucial for empowering individuals to improve their
health behaviours [34]. A growing body of evidence is emerging,
demonstrating the beneficial impact of interventions targeting
both parents on obesity risk and associated behaviours in chil-
dren during the first 1000 days of life, especially those living with
social disadvantage [49]. The lifestyle patterns identified during
pregnancy are likely part of broader trajectories that begin before
conception and extend into the postnatal period [50]. Our focus
on prenatal exposures was motivated by the fact that parental life-
styles during pregnancy represent upstream determinants in the
causal chain—likely shaping the postnatal family environment
and, ultimately, the child’s own behaviours. Nevertheless, further
research into postnatal influences remains crucial, particularly
to better understand the mechanisms underlying the association
between parents’ geographic origin and the risk of childhood over-
weight, which remains insufficiently explained by the prenatal pe-
riod examined in this study.

5 | Conclusion

A substantial part of the association between parents' education
level and childhood overweight was attributable to suboptimal
parental lifestyle and BMI patterns during pregnancy in both
ELFE and Generation R cohorts, with the strength of this media-
tion varying between the cohorts. Conversely, these patterns did
not explain the association between parents' geographic origin
and childhood overweight. Mechanisms explaining this associ-
ation seem to involve other unidentified factors. Our findings
underscore the need for context-specific public health strategies
tailored to the socio-economic and socio-cultural characteristics

of families as early as pregnancy to mitigate inequalities in
childhood overweight.

Author Contributions

C Le Gal, B Heude, S Lioret, MC Schipper and R Gaillard designed the re-
search, wrote the manuscript and analysed the data. M Lecorguillé has
provided data curation for this project. S Lioret, B Heude, MC Schipper,
R Gaillard, M Lecorguillé, L Pavicic, T Simeon, MA Charles reviewed
drafts and provided critical feedback. All authors approved the final
manuscript and were responsible for the final content of the paper.

Acknowledgements

We thank all investigators working on the EndObesity Project. This proj-
ect received funding from the European Joint Programming Initiative
“A Healthy Diet for a Healthy Life” (JPI HDHL, EndObesity). We used
variables that were harmonised in the framework of the H2020 LifeCycle
project. The LifeCycle project received funding from the European
Union's Horizon 2020 research and innovation program (grant no. 733206
LifeCycle). The ELFE study is a joint project between the French Institute
for Demographic Studies (INED) and the National Institute of Health
and Medical Research (INSERM), in partnership with the French blood
transfusion service (Etablissement français du sang [EFS]), Santé pub-
lique France, the National Institute for Statistics and Economic Studies
(INSEE), the Direction générale de la santé (DGS, part of the Ministry of
Health and Social Affairs), the Direction générale de la prévention des ris-
ques (DGPR, Ministry for the Environment), the Direction de la recherche,
des études, de l’évaluation et des statistiques (DREES, Ministry of Health
and Social Affairs), the Département des études, de la prospective et des
statistiques (DEPS, Ministry of Culture), and the Caisse nationale des al-
locations familiales (CNAF), with the support of the Ministry of Higher
Education and Research and the Institut national de la jeunesse et de
l’éducation populaire (INJEP). Via the RECONAI platform, it receives
government grants managed by the National Research Agency under
the “Investissements d’avenir” program (ANR-11-EQPX-0038, ANR-
19-COH0-0001). This work was funded through the French National
Research Agency (ANR-19-CE36-0006). R.G. received funding from the
Netherlands Organisation for Health Research and Development (NWO,
ZonMw VIDI 09150172110034, and NWO, ZonMW, grant number
05430052110007), from the Dutch Diabetes Research Foundation (Grant
NO. 2024.28.001), and an European Research Council Starting Grant
(ERC-2024-STG-101161004). The authors thank Laura Smales for help in
preparing the manuscript.

Ethics Statement

The ELFE study received approvals from the Advisory Committee for
the Processing of Information for Health Research (Comité Consultatif
sur le Traitement des Informations pour la Recherche en Santé) and
National Data Protection Authority (Commission National Informatique
et Libertés) and the National Council for Statistical Information. All re-
search was performed in accordance with the Declaration of Helsinki.
Generation R study approval was obtained by the Medical Ethical
Committee of the Erasmus Medical Center, University Medical Center,
Rotterdam (MEC 198.782/2001/31).

Consent

In ELFE study, consent for their child's participation was obtained from mothers, with fathers (if present) given the chance to consent and informed of their right to oppose the study. Recognising the language diversity among the population, study materials, including information letter and consent form, were made available in Arabic, Turkish, and English, the three most commonly spoken languages in France among non-French speakers. In the Generation R study, mothers and fathers were asked for their written informed consent for the four consecutive
phases of the study (prenatal, birth to 4 years, 4–16 years, and > 16 years). At the start of each phase, mothers and fathers received written and oral information about the study.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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**Supporting Information**

Additional supporting information can be found online in the
Supporting Information section. Data S1: ijpo70047-sup-0001-Supinfo.
docx.