# Prenatal and prepubertal exposures to organochlorine compounds and perfluoroalkyl substances and pubertal development at age 12: The PELAGIE cohort study

Lola Menant, Florence Rouget, Hélène Tillaut, Charline Warembourg, Elke Rouxel, Fabrice Lainé, Éric Gaudreau, Sylvaine Cordier, Ronan Garlantézec, Christine Monfort, et al.

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Lola Menant, Florence Rouget, Hélène Tillaut, Charline Warembourg, Elke Rouxel, et al. Prenatal and prepubertal exposures to organochlorine compounds and perfluoroalkyl substances and pubertal development at age 12: The PELAGIE cohort study. Environment International, 2025, 205, pp.109845. 10.1016/j.envint.2025.109845. hal-05399017

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# Prenatal and prepubertal exposures to organochlorine compounds and perfluoroalkyl substances and pubertal development at age 12: The PELAGIE cohort study

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Lola Menant<sup>a, *, ID</sup>, Florence Rouget<sup>b ID</sup>, Hélène Tillaut<sup>a</sup>, Charline Warembourg<sup>a ID</sup>, Elke Rouxel<sup>a ID</sup>, Fabrice Lainé<sup>c</sup>, Éric Gaudreau<sup>d ID</sup>, Sylvaine Cordier<sup>a</sup>, Ronan Garlantézec<sup>b ID</sup>, Christine Monfort<sup>a ID</sup>, Cécile Chevrier<sup>a ID</sup>

ARTICLE INFO

Keywords:

Pubertal development

POPs

Organochlorine pesticides

PCBs

PFASs

Prenatal exposure

Prepubertal exposure

A B S T R A C T

**Background:** Emerging evidence suggests that prenatal and prepubertal exposure to organochlorine compounds (OCs) and perfluoroalkyl substances (PFASs) is associated with children's reproductive health. This study examines the potential impact of these exposures on pubertal development in 12-year-old children.

**Methods:** Based on the French PELAGIE mother-child cohort, concentrations of OCs and PFASs were measured in cord blood (from 2003 to 2006) and in blood at age 12 (from 2016 to 2018). Medical staff assessed pubertal development (Tanner stages) at age 12, and girls self-reported age at menarche annually (ages 9–16). Associations between exposures and delayed or earlier pubertal development were analyzed using multinomial logistic and Cox regression models, adjusting for confounders, and using quantile g-computation for compound mixtures.

**Results:** Among 502 children (250 girls, 252 boys; median age: 12.8 years), prenatal PFUdA exposure in girls was associated with delayed breast development [OR (95 %CI): 2.05 (1.03,4.06)]. In boys, prenatal PFHxS exposure was associated with reduced risk of earlier gonadal development [0.47 (0.26,0.83)], and β-HCH with reduced risks of both delayed [0.66 (0.43,0.99)] and earlier [0.69 (0.48,0.97)] pubic hair development.

Prepubertal exposure in girls to HCB, PCBs, and PFASs was associated with increased risk of delayed breast development [e.g., PFOA: 2.53 (1.04,6.12)] and later age at menarche [e.g., ΣPCBs: HR 0.77 (0.61,0.97)]. In boys, prepubertal p,p'-DDE was associated with increased risk of earlier puberty [gonadal development: 1.77 (1.09,2.88); pubic hair growth: 1.56 (1.01,2.44)], while PCB-118 was associated with delayed development.

Prepubertal PFASs were associated with reduced risk of earlier puberty [e.g., PFHxS-gonadal stages: 0.39 (0.20,0.75)].

In mixture analyses, no associations were observed with regards to prenatal exposure, but prepubertal exposure was associated with delayed pubertal development in girls.

**Conclusion:** Prenatal and prepubertal exposure to OCs and PFASs may alter pubertal development at age 12 in girls and boys, underscoring the need for further research.

# 1. Introduction

Pubertal development – a major temporal window during adolescence – involves a series of physiological, hormonal, and psychological changes marking the transition to sexual and reproductive maturity. (Sirven, 2009) While the age at onset of puberty is primarily determined

by genetic factors (which account for 50–80 % of individual differences), (Wehkalampi et al., 2008) temporal changes in the age at onset have been detected throughout the 19th and 20th centuries, with a gradual decline observed in the mean or median age at menarche until the 1960 s. (Amselem et al., 2007; Lee and Styne, 2013; Parent et al., 2015) From the 1960 s-1970 s, the secular trend slowed in some countries. However,

<footnote><sup>a</sup> Université de Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) – UMR_S 1085, France</footnote>

<footnote><sup>b</sup> Université de Rennes, CHU Rennes, Inserm UMR S 1085, Irset, France</footnote>

<footnote><sup>c</sup> Inserm CIC 1414, CHU Rennes, France</footnote>

<footnote><sup>d</sup> Centre de Toxicologie du Québec (CTQ), Institut national de santé publique du Québec (INSPQ), Québec, Canada</footnote>

<footnote>* Corresponding author at: Inserm UM1085, 9 avenue du Professeur Leon Bernard, 35000 Rennes, France.</footnote>

<footnote>E-mail address: lola.menant@univ-rennes.fr (L. Menant).</footnote>
certain populations, such as Europeans, continued to experience a decline at a moderate pace. (Amselem et al., 2007; Euling et al., 2008; Lee and Styne, 2013; Parent et al., 2015) It has been suggested that several factors may be responsible for this decline, including the diet, obesity, socio-economic conditions, and exposure to environmental pollutants, including endocrine-disrupting chemicals. (Amselem et al., 2007; Biro et al., 2006; Dunger et al., 2006; Lee and Styne, 2013; Parent et al., 2015; Rosenfield et al., 2009) Alteration of gonadal steroid levels has been considered the primary mechanism involved in these changes. The timing of puberty is also regulated by a complex neuroendocrine system and influenced by genetic, epigenetic, and other hormonal factors. The mechanisms described above can exert effects as early as fetal development and extend into postnatal life. (Lopez-Rodriguez et al., 2021a, 2021b; Parent et al., 2015).

Numerous chemical contaminants are present in our environments, continually exposing the general population, including vulnerable groups such as pregnant women and children, to their possible endocrine disrupting actions. These include persistent organic pollutants (POPs), notably organochlorine compounds (OCs) such as organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). Although their use has been restricted by the UN Stockholm Convention since 2004, (Lallas, 2001) exposure still occurs, mainly through the diet due to their lipophilic and bioaccumulation properties. Among these, several PCBs, dichlorodiphenyltrichloroethane (DDT) and its metabolite p,p'-DDE, are widely recognized for their role as hormone receptor agonists or antagonists. They disrupt neuroendocrine signaling and cause damage, including genetic damage, at various biological levels, including impairment to the hypothalamic-pituitary axis and to the organs directly. (Amir et al., 2021; Lopez-Rodriguez et al., 2021a; Mouritsen et al., 2010; Roy et al., 2009) Perfluoroalkyl substances (PFASs) are also ubiquitous environmental contaminants. Their hydrophobic and lipophobic properties explain their widespread presence in the composition of everyday consumer products, such as food packaging, nonstick cookware, firefighting foam, and clothing. While PFASs are also very persistent in the environment, very few PFASs have thus far been added to the UN Stockholm Convention POP list. However, the available evidence underscores wide ranging effects of PFASs, which, by disrupting various key hormonal (steroidal and thyroid) and genetic pathways, interfere with endocrine and reproductive function. (Mokra, 2021; Rickard et al., 2022).

For the past three decades, epidemiological studies have investigated whether early-life exposure to OCs or PFASs influence the timing and progression of human puberty. Systematic reviews and meta-analyses have concluded that evidence is still limited, particularly due to the heterogeneity in the methods used. (Buck Louis et al., 2008; Lee et al., 2021; Uldbjerg et al., 2022) Nineteen of twenty-five observational studies focused on female populations, primarily using the age at menarche, which is the easiest to collect. (Attfield et al., 2019; Averina et al., 2024; Berghuis et al., 2022; Burns et al., 2016; Carwile et al., 2021; Christensen et al., 2011; Cox et al., 2023; Den Hond et al., 2011; Denham et al., 2005; Ernst et al., 2019; Gladen et al., 2000; Grandjean et al., 2012; Humblet et al., 2011; Korrick et al., 2011; Kristensen et al., 2013; Lam et al., 2014, 2015; Liu et al., 2023; Lopez-Espinosa et al., 2011; Marks et al., 2021; Namulanda et al., 2016; Pinney et al., 2023; Vasiliu et al., 2004; Windham et al., 2015; Wolff et al., 2008) The most-studied OC chemicals were PCBs and p,p'-DDE, and the most studied PFASs were PFOS and PFOA. In most cases, prenatal exposure to these compounds was not associated with pubertal development, but was associated with earlier puberty in girls (for OC: Berghuis et al., 2022; Vasiliu et al., 2004; for PFAS: Ernst et al., 2019) and in boys (for OC: Berghuis et al., 2022; Humblet et al., 2011; for PFAS: Ernst et al., 2019) or later age at menarche or delayed breast development in girls (Kristensen et al., 2013; Liu et al., 2023 for PFAS). With regards to postnatal exposure, findings have been mixed in boys and girls; as studies have reported trends of both delayed and earlier pubertal development in girls, as well as null findings. (for OC: Attfield et al., 2019; Den Hond et al., 2011;

Windham et al., 2015; for PFAS: Carwile et al., 2021; Kristensen et al., 2013; Liu et al., 2023; Lopez-Espinosa et al., 2011; Pinney et al., 2023).

Finally, only a few recent studies have simultaneously addressed both the pre- and postnatal windows of exposure, (Liu et al., 2023) and the potential impact of mixtures of compounds. (Carwile et al., 2021; Liu et al., 2023; Marks et al., 2021).

Based on the French PELAGIE mother-child cohort, our aim was to investigate the association between both pre- and postnatal exposure to numerous OCs and PFASs, individually and as a mixture, and the pubertal status of girls and boys aged 12-13.

# 2. Materials and methods

## 2.1. Population and data collection

The PELAGIE mother-child cohort includes 3,421 women from Brittany, France, who were enrolled during pregnancy between 2002 and 2006. Recruitment was carried out by gynecologist-obstetricians and sonographers during initial prenatal appointments before the 19th week of gestation. At delivery, midwives and pediatricians collected umbilical cord-serum samples, as well as medical data on the pregnancy, delivery, and newborn's health. At enrollment and when the child was 12 years old, families were asked to complete a self-administered questionnaire on their socio-economic characteristics, lifestyle, and health conditions. Between ages 9-16 years, mother-child pairs were followed-up annually via short questionnaires, either by post or online, to repeatedly gather information on the children's lifestyle, health, and development. (Warembourg et al., 2024).

Children with available cord blood samples were eligible for clinical examination at age 12. Of the 1,191 families with available cord blood samples, 933 were invited to participate, and 559 consented to the 12-year examination. Examinations were carried out in the hospital between 2016 and 2018 and included anthropometric, cardiovascular, dental, visual, and reproductive parameters, in addition to blood sample collection. Children born in 2002 (12% of the cohort) were excluded as they were already over the age of 12 in January 2016.

Written informed consent was obtained from parents, and written assent was obtained from children. The study was approved by the Advisory Committee on Information Processing in Health Research (CCTIRS; 2015; no. 15.326bis), the Committee for the Protection of Persons (CPP; 2015; no. 15/23-985), and the French National Commission for Information Technology and Civil Liberties (CNIL; 2002, 2015; no. 915420/2015-456).

## 2.2. Measurement of exposure

Cord blood samples were used to estimate prenatal exposure levels, while serum samples collected at age 12 estimated prepubertal exposure levels. All samples were immediately centrifuged and stored at -80 °C in our laboratory. The *Centre de Toxicologie de Québec* (CTQ), *Institut national de santé publique du Québec* (INSPQ) measured the concentrations of twenty-two OCs (α-Endosulfan, β-Hexachlorocyclohexane (β-HCH), γ-Hexachlorocyclohexane (γ-HCH), Hexachlorobenzene (HCB), Heptachlor epoxide (HCE), Dieldrin, p,p'-DDE, and p,p'-DDT, and PCBs congeners -28, -52, -74, -99, -101, -118, -138, -153, -170, -180, -183, -187, -194, and -203) and nine PFASs (perfluorobutyric acid [PFBA], perfluorohexanoic acid [PFHxA], perfluorooctanoic acid [PFOA], perfluorononanoic acid [PFNA], perfluorodecanoic acid [PFDA], perfluoroundecanoic acid [PFUdA], perfluorobutane sulfonate [PFBS], perfluorohexane sulfonate [PFHxS], as well as perfluorooctane sulfonate [PFOS]). This list of compounds was defined according to the exposure potential of the general population in the Brittany coastal region over recent decades (past usages, one-off environmental contamination data), national French studies on food contamination and biomonitoring, and CTQ capacity.

With regards to the measurements carried out in the 12-year-olds'
serum samples, a primary set of samples (boys samples) allowed us to restrict the list for reasons of cost to the compounds detected in > 30 % of samples. Consequently, the following compounds were not analyzed in the second set of samples (girls samples): α-Endosulfan, γ-Hexachlorocyclohexane (γ-HCH), Heptachlor epoxide (HCE), p,p'-DDT, PCBs congeners -28, -52, -74, -99, -101, -183 et -203, PFBA, PFHxA and PFBS.

Two mL of serum or cord serum were enriched with labeled internal standards. OCs were extracted by a solid phase extraction (SPE) (before 2013) or by a liquid-liquid extraction with hexane in the presence of a saturated ammonium sulfate solution (from 2013). The change in extraction methods showed no impact on the quality of the results provided or on the distribution of measurements, as the methods were comparable. The chemical analysis of OCs was carried out using gas chromatography coupled with mass spectrometry (GC-MS; Agilent Technologies Inc.; Mississauga, Ontario, Canada with an Agilent 60 m DB-XLB column (0.25 mm i.d., 0.25 µm film thickness). Both methods used have been previously described in Chevrier et al., (2013) and Tillaut et al., (2022).

The PFAS analysis was performed as follows: 100 µL of serum or cord serum were enriched with labeled internal standards and PFAS compounds were extracted using a SPE technique with a weak anion exchange resin. The extracts were analyzed by Ultra Performance Liquid Chromatography (UPLC Waters Acquity) with tandem mass spectrometry (MS/MS Waters Xevo TQ-S) (Waters; Milford, MA, USA). The columns used were the ACE EXCEL C₁₈-PFP 50 or 100 mm x 2.1 mm, 2.0 µm (ACE; Aberdeen, Scotland). The methods used over the years for PFAS have been described in Tillaut et al., (2022).

The limit of detection (LODs) varied from 0.005 to 0.3 µg/L for the OCs. The internal reference materials used to control the quality of analyses for the PCBs and OCPs included both certified reference material SRM-1958 from the National Institute of Standards and Technology (NIST; Gaithersburg, MD) and non-certified reference materials W-16-04 and W-19-09 from the AMAP External Quality Assessment Scheme (CTQ/(INSPQ; Québec, Québec, Canada). Each batch of samples contained 2 SRM-1958 and the deviation of the majority of measured concentrations across batches from SRM-1958 (and from all other QCs) was less than 15 % from the certified/reference concentration.

The LODs varied from 0.01 to 0.2 µg/L for PFASs depending on the analytes and year of analysis. The internal reference materials used to control the quality of the PFAS analyses were certified reference material SRM-1958 from the NIST, plus three in-house reference materials (Low, Medium, High QC) prepared by the CTQ. Each batch of samples contained only 1 SRM-1958 and the deviation of the majority of measured concentrations across batches from SRM-1958 (and from all other QCs) was less than 15 % from the certified/reference concentration.

Overall quality and accuracy of the analytical methods (OCs, PFAS) was monitored by participation in the interlaboratory programs such as the AMAP External Quality Assessment Scheme (CTQ/INSPQ; Québec, Québec, Canada) and the German External Quality Assessment Scheme (G-EQUAS; Erlangen, Germany).

Due to variability in the available remaining volumes of cord-blood samples, OC measurements in cord-blood were completed for 465 (n = 235 girls; n = 230 boys) children from the analysis population families, and PFAS measurements for 404 (n = 200 girls; n = 204 boys) children. Both OC and PFAS measurements were available for 382 children (n = 192 girls; n = 190 boys). For child blood sample measurements at age 12, the full set of OCs and PFAS measurements were obtained for 452 children (n = 226 girls; n = 226 boys).

## 2.3. Pubertal assessment at 12 years

During the child's clinical examination, pubertal development was assessed using Tanner clinical staging, a recognized and validated method, by qualified health professionals trained in standard practices.

(Marshall and Tanner, 1970, 1969) For girls, breast development was assessed visually for Tanner stages B1-B5, and by palpation when necessary to distinguish the absence of breast development (B1) from the presence of a breast bud (B2). Both girls and boys were assessed visually for Tanner stages of pubic hair development (PH1-PH5). In boys, gonadal development (Tanner stages G1-G5) was assessed using a Prader orchidometer with palpation of the testis, for those who agreed to it (n = 98.4 %). Of the 559 children who participated in the examination, one child was diagnosed with precocious puberty, and was therefore excluded from the present study population. A total of 502 participants who agreed to the assessment of at least one of the secondary sexual characteristics, comprised the analysis population (n = 250 girls; n = 252 boys).

Pubertal developmental stages were then categorized into three groups for girls and boys for analyses. Breast (B) and gonadal (G) development were broken down as follows: Tanner Stage 3 (the expected stage at age 12), Tanner Stages 1 and 2 (representing somewhat delayed puberty), and Tanner Stages 4 and 5, (representing early puberty). (Amselem et al., 2007; Marshall and Tanner, 1970, 1969) The development of pubic hair (PH) was broken down differently for girls and boys. For girls, Tanner Stages 1-3 represented delayed puberty, Tanner Stage 4 represented expected puberty, and Tanner Stage 5 represented early puberty. For boys, Tanner Stage 1 characterized delayed puberty, Tanner Stage 2 was expected puberty, and Tanner Stages 3-5 represented early puberty. (Amselem et al., 2007; Marshall and Tanner, 1970, 1969).

For girls, menarche status was self-reported in each annual questionnaire, allowing age at menarche to be defined as the first age at which menarche was reported (n = 216). For the remaining participants (n = 34) who did not report having menarche in the latest completed annual questionnaire, right censoring was applied, using the age at the last follow-up point.

## 2.4. Statistical analysis

The study population characteristics were described either in terms of median and interquartile range, or frequency and percentage.

### 2.4.1. Imputation strategies

Compounds detected in < 70 % of blood samples were excluded from the present analyses. For OC and PFAS measurements with detection rates ≥ 70 %, values below the LOD were randomly imputed from a lognormal probability distribution, whose parameters were estimated using a maximum likelihood method. (Jin et al., 2011) Correlations between OC concentrations were computed using Spearman's coefficient. The sum of the most frequently observed PCBs (PCB-118, -138, -153, -170, -180 and -187 for cord-blood measurements; PCB-118, -138—153 and -180 for blood measurements at age 12) was calculated after conversion to their respective molar mass; individual PCBs were also taken into account in the present study. Concentrations were log-transformed to approximate a normal distribution.

Missing data on covariates (up to 14.5 % for breastfeeding) and exposures (up to 9.4 % for cord-blood PFDA), due to analytical interferences in certain samples, were imputed using the chained equations method. (White et al., 2011) A minimum of five and a maximum of twenty-five variables were retained to predict incomplete variables, as recommended. (Austin et al., 2021) Socio-economic and lifestyle variables (e.g. family situation, diet, alcohol and tobacco consumption during pregnancy, breastfeeding) were selected. Outcome data were not included in this list of variables. In total, five datasets were imputed for the prenatal exposure analyses, and another five were imputed for the prepubertal exposure analyses. The estimated associations in each of these datasets were then grouped according to Rubin's rule. (Austin et al., 2021) Missing outcome data were not imputed.
### 2.4.2. Models for estimating the associations

For each OC and PFAS, multinomial logistic regression and Cox proportional hazards models were used to estimate the association between the serum concentration (log₂) and pubertal developmental stage; and in girls, age at menarche, for both the prenatal and the prepubertal measurements. Results from the multinomial models are presented as odds ratios (OR) with their corresponding 95 % confidence intervals (CI). For Cox models, hazard ratios (HR) with 95 % CI were calculated. All models were adjusted for potential confounding factors, as listed below. The proportional hazards hypothesis was tested for each of the Cox models, using the Schoenfeld residuals method. For models not meeting this assumption, certain covariates were categorized.

The linearity assumption was investigated using generalized additive models (GAM), separately for dichotomous outcomes (delayed stage vs. reference; advanced stage vs. reference) of each Tanner outcome. Non-linearity was quantified using the effective degree of freedom (edf) in all datasets generated by multiple imputation. (Hunsicker et al., 2016) An edf > 1.5 defined a non-linear relationship. In the case of a non-linear relationship, the curves of these relationships were produced. In the results, we present only the non-linear curves for compounds significantly associated with pubertal development. However, the full set of curves is available in the Supplemental Material (Supplemental Figs. S5-S14).

Chemical mixture analyses were also conducted considering the joint effects of OCs and PFASs. The quantile G-computation method (Keil et al., 2020) was used to estimate the overall effect of a simultaneous increase of a quartile across all chemical concentrations on the outcome. The method was applied separately for prenatal and prepubertal measurements. Similar to the single-chemical analyses, multinomial models were used to model pubertal developmental stages and Cox models were used to model the age at menarche. The same covariate adjustment strategy was used for the mixture analyses. The average relative contribution of each chemical to the mixture was computed using all five imputed datasets.

R software (version 4.3.0) was used for all analyses. The threshold for statistically significant results was 5 %.

### 2.4.3. Covariate adjustment strategy

Based on a set of risk factors affecting pubertal development, directed acyclic graphs (DAGs) were created to determine a priori the minimum sufficient set of potential confounders that should be taken into account in analyses (Supplemental Figs. S1 and S2). (Schisterman et al., 2009; Shrier and Platt, 2008).

The variables selected for the prenatal models: maternal level of education (less than high school, graduated high school, higher education), maternal age at delivery, maternal pre-pregnancy Body Mass Index (BMI) (underweight, normal, overweight), parity (primiparous, multiparous) and maternal smoking status during pregnancy (non-smoker or ex-smoker, quit during pregnancy, smoker at inclusion).

The variables selected for the prepubertal models: maternal level of education at the child's 12-year follow-up, passive exposure to tobacco smoke (Yes (if at least one parent smokes regularly), No), breastfeeding (never, ≤ 3 months, > 3 months), and child's BMI Z-Score (according to the World Health Organization 2007 scale) at the point of clinical examination.

### 2.4.4. Sensitivity analyses

Sensitivity analyses were carried out by: (1) removing overweight children from the analysis to prevent a potential confounding role of significant adiposity (possibly related to lipophilic POP serum dilution, pubertal development, and Tanner Stage measurement); (2) removing the BMI Z-score adjustment in our analyses of prepubertal exposure period, since child BMI could act as a confounder, mediator or collider in the studied associations; (3) restricting the associations between prepubertal PFAS exposure and girls' pubertal development to girls not yet menstruating at the time of the clinical examination at age 12 to

consider the hypothesis that PFASs might be excreted through menstruation, (Wu et al., 2015) as discussed by Koponen et al., 2018. No such assumption has been mentioned for OCs.

## 3. Results

### 3.1. Population characteristics

At delivery, the median maternal age was 30.9 years for girls and 31.2 years for boys, with a median gestational age of 40.0 weeks for both (Table 1). Mothers were highly educated, with almost three quarters having education beyond high school at inclusion and the child's 12-year follow-up. Almost 87 % of the mothers were living with a partner at 12 years. Eighty percent of the mothers of girls and 73 % of the mothers of boys were non-smokers or ex-smokers at inclusion, and almost 77 % had a normal pre-pregnancy BMI. More than half of the mothers (60 %) had already had at least one child. At the 12-year follow-up, less than 30 % of the children were currently exposed to passive smoking.

<caption>Table 1</caption>

Children's socio-demographic characteristics (N = 502), PELAGIE mother-child cohort, France.

<table><thead><tr><th></th><th>Girls<br>(n = 250, 49.8 %)</th><th>Boys<br>(n = 252, 50.2 %)</th></tr><tr><th></th><th colspan="2">N (%) or Median (Q1-Q3)</th></tr></thead><tbody><tr><td><strong>At inclusion</strong></td><td></td><td></td></tr><tr><td><strong>Maternal education level</strong></td><td></td><td></td></tr><tr><td>Less than high school</td><td>22 (8.8)</td><td>32 (12.7)</td></tr><tr><td>Graduated high school</td><td>49 (19.6)</td><td>33 (13.1)</td></tr><tr><td>Higher education</td><td>179 (71.6)</td><td>187 (74.2)</td></tr><tr><td><strong>Maternal smoking status during pregnancy<sup>c</sup></strong></td><td></td><td></td></tr><tr><td>Non-smoker or ex-smoker</td><td>202 (80.8)</td><td>185 (73.4)</td></tr><tr><td>Quit during pregnancy</td><td>29 (11.6)</td><td>32 (12.7)</td></tr><tr><td>Smoker at inclusion</td><td>18 (7.2)</td><td>33 (13.1)</td></tr><tr><td><strong>Maternal pre-pregnancy BMI (kg/m<sup>2</sup>)<sup>b</sup></strong></td><td></td><td></td></tr><tr><td>Underweight</td><td>18 (7.2)</td><td>22 (8.7)</td></tr><tr><td>Normal</td><td>192 (76.8)</td><td>196 (77.8)</td></tr><tr><td>Overweight</td><td>39 (15.6)</td><td>32 (12.7)</td></tr><tr><td><strong>Family situation</strong></td><td></td><td></td></tr><tr><td>Married or cohabitating</td><td>245 (98.0)</td><td>252 (100)</td></tr><tr><td>Living alone</td><td>5 (2.0)</td><td>0 (0)</td></tr><tr><td><strong>Pregnancy / Birth data</strong></td><td></td><td></td></tr><tr><td><strong>Maternal age at delivery (years)<sup>c</sup></strong></td><td>30.9 (28.6-33.7)</td><td>31.2 (28.3-34.0)</td></tr><tr><td><strong>Parity at inclusion<sup>d</sup>, Multiparous</strong></td><td>150 (60.0)</td><td>151 (59.9)</td></tr><tr><td><strong>Term (Weeks of amenorrhea)<sup>e</sup></strong></td><td>40.0 (39.0-40.0)</td><td>40.0 (39.0-40.0)</td></tr><tr><td><strong>Breastfeeding<sup>f</sup></strong></td><td></td><td></td></tr><tr><td>Never</td><td>57 (22.8)</td><td>58 (23.0)</td></tr><tr><td>1-3 months</td><td>59 (23.6)</td><td>62 (24.6)</td></tr><tr><td>> 3 months</td><td>98 (39.2)</td><td>95 (37.7)</td></tr><tr><td>12-year follow-up</td><td></td><td></td></tr><tr><td><strong>Maternal Family situation</strong></td><td></td><td></td></tr><tr><td>Couple (married, cohabiting, civil union)</td><td>215 (86.0)</td><td>219 (86.9)</td></tr><tr><td>Living alone</td><td>35 (14.0)</td><td>33 (13.1)</td></tr><tr><td><strong>Maternal education level</strong></td><td></td><td></td></tr><tr><td>Less than high school</td><td>21 (8.4)</td><td>23 (9.1)</td></tr><tr><td>Graduated high school</td><td>44 (17.6)</td><td>31 (12.3)</td></tr><tr><td>Higher education</td><td>185 (74.0)</td><td>198 (78.6)</td></tr><tr><td><strong>Passive exposure to tobacco smoke<sup>g</sup>, Yes</strong></td><td>73 (29.2)</td><td>68 (27.0)</td></tr><tr><td><strong>Maternal age at menarche<sup>h</sup></strong></td><td>13.0 (12.0-14.0)</td><td></td></tr><tr><td><strong>Paternal age at voice change<sup>i</sup></strong></td><td></td><td>14.0 (13.0-15.0)</td></tr></tbody></table>

Note: BMI, body mass index.

<footnote>a Missing data: n = 1 for girls; n = 2 for boys; b Missing data: n = 1 for girls; n = 2 for boys; c Missing data: n = 3 for girls; n = 1 for boys; d Missing data: n = 1 for boys; e Missing data: n = 2 for boys; f Missing data: n = 36 for girls; n = 37 for boys; g Missing data: n = 7 for girls; n = 2 for boys; h Missing data: n = 9; i Missing data: n = 110.</footnote>
Of the 502 children, 250 (49.8 %) were girls. The median age of the children at the 12-year clinical examination was 12.8 years with an interquartile range of (12.7–12.9). The majority (87.2 % and 92.1 %, for girls and boys, respectively) had normal BMIs (Table 2). Less than half of the girls (42.4 %) had menstruated by the time of the 12-year questionnaires. Among the girls who provided information on the age of menarche between their 9th and 16th years (n = 216), the median age of onset was 12.8 years. At the 12-year follow-up, approximately half of the girls (54.4 %) were at stage 3 of breast development, and more than one in three (38.8 %) were at stage 4 of pubic hair development, both of which are as expected at this age. Among boys, 40.5 % were in stage 3 of gonadal development and 42.1 % were at stage 2 of pubic hair development, as expected at this age.

Compared with the original cohort, differences were observed in maternal characteristics such as the level of education (62 % with higher education in the initial cohort vs. 73 % in our population), self-reported smoking during pregnancy (85 % non-smokers or ex-smokers vs. 89 %), or normal pre-pregnancy BMI (74 % vs. 77 %) (Supplemental Table S1).

## 3.2. Cord-blood OC and PFAS concentrations

Detection rates for the nine OCs and six PFASs selected for the present analysis (i.e., >70 %) tended to vary between 90.4–100 %, with the exception of PCB-187 and PFUdA, for which around a quarter of subjects had values below the LOD (Table 3). The substances with the highest median concentrations in cord-blood samples were PFOS (4.52 µg/L), PFOA (2.23 µg/L), PFHxS (0.55 µg/L), PFNA (0.35 µg/L), p,p'-DDE (0.19 µg/L), and PCB-153 (0.12 µg/L). The lowest median cord-blood

<caption>**Table 2**</caption>

Children's clinical characteristics and puberty markers at the 12-year follow-up, PELAGIE mother–child cohort, France.

<table><thead><tr><th></th><th>Girls<br>(n = 250)</th><th>Boys<br>(n = 252)</th></tr></thead><tbody><tr><td>Age at exam (years)</td><td>N (%) or Median (Q1-Q3)</td><td>N (%) or Median (Q1-Q3)</td></tr><tr><td>Child's BMI at 12Y (WHO reference)</td><td>12.8 (12.7-12.9)</td><td>12.8 (12.8-12.9)</td></tr><tr><td>Underweight</td><td>13 (5.2)</td><td>8 (3.2)</td></tr><tr><td>Normal build</td><td>218 (87.2)</td><td>232 (92.1)</td></tr><tr><td>Overweight</td><td>19 (7.6)</td><td>12 (4.8)</td></tr><tr><td>Pubertal data at 12 years</td><td></td><td></td></tr><tr><td>Menarche status at 12y, Yes</td><td>106 (42.4)</td><td></td></tr><tr><td>Age at menarche (n = 216)</td><td>12.8 (12.1-13.7)</td><td></td></tr><tr><td>Breast Development</td><td></td><td></td></tr><tr><td>Stage 1 or 2 - No bud or mammary bud</td><td>58 (23.2)</td><td></td></tr><tr><td>Stage 3 - Mammary gland exceeds areola surface</td><td>136 (54.4)</td><td></td></tr><tr><td>Stage 4 or 5 - Submammary fold or adult appearance</td><td>56 (22.4)</td><td></td></tr><tr><td>Pubic hair in girls<sup>a</sup></td><td></td><td></td></tr><tr><td>Stage 1 to 3 - Absence to exceeds pubic symphysis</td><td>124 (49.6)</td><td></td></tr><tr><td>Stage 4 - Pubic triangle</td><td>97 (38.8)</td><td></td></tr><tr><td>Stage 5 - Adult appearance</td><td>20 (8.0)</td><td></td></tr><tr><td>Palpation consent, Yes</td><td></td><td>248 (98.4)</td></tr><tr><td>Left testis (mL)<sup>b</sup></td><td></td><td>10.0 (6.0-12.0)</td></tr><tr><td>Right testis (mL)<sup>c</sup></td><td></td><td>10.0 (6.0-12.0)</td></tr><tr><td>Gonadal Development<sup>d</sup></td><td></td><td></td></tr><tr><td>Stage 1 or 2 - Infantile appearance or testicular volume < 6 mL</td><td></td><td>79 (31.3)</td></tr><tr><td>Stage 3 - Testicular volume [6-12] mL</td><td></td><td>102 (40.5)</td></tr><tr><td>Stage 4 or 5 - Testicular volume ≥ 16 mL or adult size and shape</td><td></td><td>67 (26.6)</td></tr><tr><td>Pubic hair in boys<sup>e</sup></td><td></td><td></td></tr><tr><td>Stage 1 - Absence</td><td></td><td>50 (19.8)</td></tr><tr><td>Stage 2 - A few fine hairs</td><td></td><td>106 (42.1)</td></tr><tr><td>Stage 3 to 5 - Exceeds pubic symphysis to adult appearance</td><td></td><td>84 (33.3)</td></tr></tbody></table>

Note: BMI, body mass index.

concentrations were observed for PCB-187 (0.014 µg/L), -118 (0.028 µg/L), HCB (0.044 µg/L), and PFUdA (0.068 µg/L). The highest correlation coefficients were observed within PCBs (0.66 < r < 0.99), and to a lesser extent, within PFASs. However, high correlation coefficients (r ≈ 0.6) were observed between most OCs, but not PFASs (Supplemental Fig. S3).

## 3.3. OC and PFAS concentrations in 12-year blood samples

Six OCs and 6 PFASs were detected at rates between 72 % to 100 % (Table 4). For both girls and boys, the highest median concentrations were observed in the six PFASs, followed by p,p'-DDE and PCB-153. Similar correlation patterns among OCs and PFASs were observed in both girls and boys, and were consistent with those observed in cord-blood samples (Supplemental Fig. S4). Boys had slightly higher median serum concentrations than girls. Median serum concentrations of OCs and PFASs were lower in the 12-year-old children's blood samples than those measured in cord-blood samples.

## 3.4. Associations between prenatal exposures and 12-year pubertal stages

In single exposure models among girls, higher prenatal concentrations of PFUdA (log2) were associated with an increased risk of delayed breast development (stages B1-B2 vs. B3) [OR (95 % CI) = 2.05 (1.03, 4.06)] (Fig. 1 and Supplemental Table S2). More precisely, this association was both positive and non-linear, with risk increasing more rapidly at higher concentrations (Supplemental Fig. S5). No other associations were observed for prenatal exposure to OCs and PFASs with breast development, pubic hair development, or age at menarche (Fig. 1).

In boys, prenatal concentrations of β-HCH were associated with a decreased risk of delayed pubic hair development (stage PH1 vs PH2) [OR (95 % CI) = 0.66 (0.43, 0.99)] and earlier pubic hair development (stages PH3-PH5 vs. PH2) [OR (95 % CI) = 0.69 (0.48, 0.97)] (Fig. 2 and Supplemental Table S3). Higher prenatal concentrations of PFOS and PFHxS were associated with a decreased risk of earlier gonadal development (stages G4-G5 vs G3) [OR (95 % CI) = 0.56 (0.31, 0.99) and 0.47 (0.26, 0.83), respectively] (Fig. 2), except for the highest levels of PFOS, where the risk increased in a non-linear fashion (Supplemental Fig. S8).

No statistically significant effect of a mixture of OCs and PFASs was reported for the prenatal concentrations and any pubertal outcomes in girls or boys (Table 5).

## 3.5. Associations between prepubertal exposures and 12-year pubertal stages

In girls, an association was observed between higher prepubertal concentrations of HCB and later onset of menarche [HR (95 % CI) = 0.48 (0.30, 0.77)] (Fig. 3 and Supplemental Table S4). Higher prepubertal exposures to PCB-118, -138, -153, -180, and ΣPCB were associated with a decreased risk of earlier breast development (stages B4-B5 vs. B3). A later age at menarche was observed in association with higher levels of PCBs, in particular PCB-153, -180 and ΣPCB (Fig. 3). Higher prepubertal concentrations of PFOA were associated with an increased risk of delayed breast and pubic hair development [OR (95 % CI) = 2.53 (1.04, 6.12) and 2.29 (1.07, 4.90), respectively] (Fig. 3). Higher concentrations of PFOA [HR (95 % CI) = 0.65 (0.45, 0.94)] and PFDA [HR (95 % CI) = 0.68 (0.51, 0.91)] were associated with a later age at menarche (Fig. 3). These associations were non-linear, with no influence on the age at menarche at the lowest concentrations, and a later age at menarche with the highest concentrations once the median values (Supplemental Fig. S12).

In boys, higher prepubertal p,p'-DDE concentrations were associated with increased risk of both earlier gonadal development (stages G4-G5 vs. G3) [OR (95 % CI) = 1.77 (1.09, 2.88)], and pubic hair development (stages PH3-PH5 vs. PH2) [OR (95 % CI) = 1.56 (1.01, 2.44)] (Fig. 4 and Supplemental Table S5). An increased risk of delayed pubic

<footnote><sup>a</sup> Missing data: n = 9; <sup>b</sup> Missing data: n = 6; <sup>c</sup> Missing data: n = 7; <sup>d</sup> Missing data: n = 4; <sup>e</sup> Missing data: n = 12.</footnote>
<table><caption>**Table 3**
Distribution of cord-blood concentrations (µg/L) of OCs (n = 465) and PFASs (n = 404), PELAGIE mother–child cohort, France.</caption><thead><tr><th>Compound</th><th>LOD</th><th>NA</th><th>Detected (%)</th><th>P25</th><th>Median</th><th>P75</th><th>P95</th><th>Max</th></tr></thead><tbody><tr><td colspan="9">Organochlorine compounds (OCs)</td></tr><tr><td>p,p'-DDE</td><td>0.02</td><td>0</td><td>437 (94.0)</td><td>0.12</td><td>0.19</td><td>0.33</td><td>0.59</td><td>3.30</td></tr><tr><td>β-HCH</td><td>0.01</td><td>0</td><td>460 (98.9)</td><td>0.04</td><td>0.05</td><td>0.07</td><td>0.15</td><td>1.30</td></tr><tr><td>HCB</td><td>0.02</td><td>0</td><td>422 (90.8)</td><td>0.03</td><td>0.04</td><td>0.06</td><td>0.09</td><td>0.25</td></tr><tr><td>PCB-118</td><td>0.01</td><td>0</td><td>460 (98.9)</td><td>0.02</td><td>0.03</td><td>0.04</td><td>0.07</td><td>0.14</td></tr><tr><td>PCB-138</td><td>0.01</td><td>13</td><td>452 (100)</td><td>0.05</td><td>0.07</td><td>0.09</td><td>0.16</td><td>0.29</td></tr><tr><td>PCB-153</td><td>0.01</td><td>0</td><td>465 (100)</td><td>0.09</td><td>0.12</td><td>0.17</td><td>0.29</td><td>0.49</td></tr><tr><td>PCB-170</td><td>0.01</td><td>0</td><td>458 (98.5)</td><td>0.02</td><td>0.03</td><td>0.04</td><td>0.08</td><td>0.14</td></tr><tr><td>PCB-180</td><td>0.01</td><td>0</td><td>465 (100)</td><td>0.06</td><td>0.08</td><td>0.11</td><td>0.20</td><td>0.33</td></tr><tr><td>PCB-187</td><td>0.01</td><td>0</td><td>347 (74.6)</td><td>&lt;LOD</td><td>0.01</td><td>0.02</td><td>0.04</td><td>0.08</td></tr><tr><td colspan="9">Perfluoroalkyl substances (PFASs)</td></tr><tr><td>PFOS</td><td>0.16</td><td>0</td><td>404 (100)</td><td>3.49</td><td>4.52</td><td>5.79</td><td>8.52</td><td>27.17</td></tr><tr><td>PFOA</td><td>0.066</td><td>0</td><td>404 (100)</td><td>1.71</td><td>2.23</td><td>2.86</td><td>4.18</td><td>7.36</td></tr><tr><td>PFHxS</td><td>0.063</td><td>0</td><td>404 (100)</td><td>0.42</td><td>0.55</td><td>0.70</td><td>1.10</td><td>3.17</td></tr><tr><td>PFNA</td><td>0.085</td><td>10</td><td>393 (99.7)</td><td>0.26</td><td>0.35</td><td>0.46</td><td>0.68</td><td>1.55</td></tr><tr><td>PFDA</td><td>0.058</td><td>38</td><td>331 (90.4)</td><td>0.08</td><td>0.10</td><td>0.13</td><td>0.18</td><td>0.51</td></tr><tr><td>PFUdA</td><td>0.048</td><td>19</td><td>283 (73.5)</td><td>&lt;LOD</td><td>0.07</td><td>0.09</td><td>0.14</td><td>0.30</td></tr></tbody></table>

Note: β-HCH, β-hexachlorocyclohexane; HCB, hexachlorobenzene; LOD, limit of detection; NA, not available; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluoronanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.

hair development (stage PH1 vs PH2) was associated with prepubertal PCB-118 concentrations [OR (95 % CI) = 1.80 (1.03, 3.14)], in a non-linear but positive relationship with an increased risk that increases with higher PCB levels (Fig. 4 and Supplemental Fig. S14). Similar results were observed for the other PCBs. Higher prepubertal concentrations of PFOA were associated with an increased risk of delayed gonadal development (stages G1-G2 vs. G3) [OR (95 % CI) = 2.73 (1.34, 5.54)] in a non-linear relationship, with a risk that plateaued at the highest PFOA levels (Supplemental Fig. S13). Higher PFOA concentrations were also associated with decreased risk of earlier pubic hair development [OR (95 % CI) = 0.30 (0.14, 0.64)] (Fig. 4). Higher prepubertal concentrations of PFHxS were associated with decreased risk of earlier gonadal and pubic hair development [OR (95 % CI) = 0.39 (0.20, 0.75) and 0.56 (0.32, 0.98), respectively]. The association with gonadal development was non-linear, but showed a clear negative relationship (Supplemental Fig. S13). Higher PFDA concentrations were associated with a decreased risk of earlier pubic hair development [OR (95 % CI) = 0.28 (0.14, 0.55)] (Fig. 4), though this was a non-linear relationship

suggesting that the decrease in risk slowed at the highest concentrations (Supplemental Fig. S14).

Concerning the mixture approach, a one-quartile increase in exposure to the overall mixture was associated with a reduced risk of earlier breast development (stages B4-B5 vs B3) [OR (95 % CI) = 0.50 (0.26, 0.93)] (Table 5), with the ΣPCBs and PFNA acting as the main contributors to the mixture (mean contributions 67 % and 27 %, respectively) (Supplemental Fig. S20). In addition, a one-quartile increase in the mixture was also associated with an increased risk of delayed pubic hair growth (PH1-PH3 vs PH4) [OR (95 % CI) = 1.73 (1.04, 2.86)] (Table 5), with several compounds contributing to the mixture: PFOA (mean = 29 %), HCB (28 %), PFNA (20 %) and p,p'-DDE (17 %) (Supplemental Fig. S21). A later age at menarche was also statistically significantly associated with a one-quartile increase in the mixture [HR (95 % CI) = 0.73 (0.56, 0.95)] (Table 5), with contributions made by PFDA with 31 %, PFNA with 24 %] and HCB with 20 % (Supplemental Fig. S22). No statistically significant associations were observed in boys.

## 3.6. Sensitivity analysis

Analyses excluding overweight children revealed results of the same magnitude as those of the main analysis, though there were some changes in statistical significance (Supplemental Tables S6-S9). Removing the adjustment for BMI Z-score revealed amplified associations, particularly in girls (Supplemental Table S10), as the association between exposure to HCB and delayed breast development [OR (CI 95 %) = 5.38 (2.17–13.30)] and pubic hair growth [4.11 (1.88–9.00)] were amplified. Higher concentrations of PCBs were also associated with delayed pubertal development, while p,p'-DDE and HCB were associated with early breast development, with amplified ORs [0.57 (0.34, 0.96); 0.33 (0.12, 0.84), respectively]. Statistical significance also appears for the age at menarche. In boys, no substantial changes were observed (Supplemental Table S11). Lastly, analyses excluding menstruating girls continued to suggest that prepubertal exposure levels to PFOA were associated with an increased risk of delayed breast development [OR (95 % CI) = 3.14 (1.00, 9.78)], though the same was not true of delayed pubic hair development [OR (95 % CI) = 0.85 (0.28, 2.53)] (Supplemental Table S12).

## 4. Discussion

Our findings suggest that prenatal exposure to specific PFASs (PFUdA in relation to breast development in girls, and PFOS and PFHxS in relation to gonadal development in boys) was associated with delayed

<table><caption>**Table 4**
Distribution of concentrations (µg/L) of OCs and PFASs (n = 452) measured in the 12-year child blood samples of girls (n = 226) and boys (n = 226), PELAGIE mother–child cohort, France.</caption><thead><tr><th rowspan="2">Compound</th><th colspan="5">Girls (n = 226)</th><th colspan="5">Boys (n = 226)</th></tr><tr><th>LOD</th><th>NA</th><th>Detected (%)</th><th>P25</th><th>Median</th><th>P75</th><th>P95</th><th>Max</th><th>LOD</th><th>NA</th><th>Detected (%)</th><th>P25</th><th>Median</th><th>P75</th><th>P95</th><th>Max</th></tr></thead><tbody><tr><td colspan="16">Organochlorine compounds (OCs)</td></tr><tr><td>p,p'-DDE</td><td>0.02</td><td>0</td><td>226 (100)</td><td>0.06</td><td>0.09</td><td>0.13</td><td>0.28</td><td>1.10</td><td>0.02</td><td>0</td><td>226 (100)</td><td>0.07</td><td>0.09</td><td>0.14</td><td>0.27</td><td>1.20</td></tr><tr><td>HCB</td><td>0.02</td><td>0</td><td>225 (99.6)</td><td>0.04</td><td>0.05</td><td>0.06</td><td>0.08</td><td>0.11</td><td>0.02</td><td>0</td><td>226 (100)</td><td>0.04</td><td>0.05</td><td>0.06</td><td>0.08</td><td>0.10</td></tr><tr><td>PCB-118</td><td>0.01</td><td>0</td><td>163 (72.1)</td><td>&lt;LOD</td><td>0.01</td><td>0.02</td><td>0.04</td><td>0.24</td><td>0.01</td><td>0</td><td>174 (77)</td><td>0.01</td><td>0.01</td><td>0.02</td><td>0.04</td><td>0.09</td></tr><tr><td>PCB-138</td><td>0.01</td><td>0</td><td>218 (96.5)</td><td>0.02</td><td>0.03</td><td>0.04</td><td>0.09</td><td>0.22</td><td>0.01</td><td>0</td><td>225 (99.6)</td><td>0.02</td><td>0.03</td><td>0.05</td><td>0.07</td><td>0.16</td></tr><tr><td>PCB-153</td><td>0.01</td><td>0</td><td>226 (100)</td><td>0.03</td><td>0.05</td><td>0.08</td><td>0.18</td><td>0.52</td><td>0.01</td><td>0</td><td>226 (100)</td><td>0.04</td><td>0.07</td><td>0.10</td><td>0.17</td><td>0.52</td></tr><tr><td>PCB-180</td><td>0.01</td><td>0</td><td>204 (90.3)</td><td>0.02</td><td>0.03</td><td>0.05</td><td>0.13</td><td>0.31</td><td>0.01</td><td>0</td><td>222 (98.2)</td><td>0.02</td><td>0.04</td><td>0.07</td><td>0.13</td><td>0.36</td></tr><tr><td colspan="16">Perfluoroalkyl substances (PFASs)</td></tr><tr><td>PFOS</td><td>0.07</td><td>0</td><td>226 (100)</td><td>1.98</td><td>2.47</td><td>3.14</td><td>5.58</td><td>10.36</td><td>0.16</td><td>0</td><td>226 (100)</td><td>2.10</td><td>2.78</td><td>3.80</td><td>7.35</td><td>51.68</td></tr><tr><td>PFOA</td><td>0.019</td><td>0</td><td>226 (100)</td><td>0.97</td><td>1.16</td><td>1.39</td><td>1.85</td><td>3.44</td><td>0.066</td><td>0</td><td>226 (100)</td><td>1.08</td><td>1.37</td><td>1.64</td><td>2.29</td><td>6.07</td></tr><tr><td>PFHxS</td><td>0.031</td><td>0</td><td>226 (100)</td><td>0.48</td><td>0.58</td><td>0.78</td><td>1.50</td><td>7.15</td><td>0.063</td><td>0</td><td>226 (100)</td><td>0.55</td><td>0.70</td><td>0.91</td><td>1.48</td><td>3.96</td></tr><tr><td>PFNA</td><td>0.011</td><td>0</td><td>226 (100)</td><td>0.36</td><td>0.44</td><td>0.56</td><td>1.03</td><td>2.96</td><td>0.085</td><td>15</td><td>211 (100)</td><td>0.39</td><td>0.48</td><td>0.61</td><td>0.83</td><td>4.78</td></tr><tr><td>PFDA</td><td>0.013</td><td>0</td><td>226 (100)</td><td>0.15</td><td>0.18</td><td>0.22</td><td>0.36</td><td>0.55</td><td>0.058</td><td>11</td><td>215 (100)</td><td>0.16</td><td>0.20</td><td>0.26</td><td>0.44</td><td>0.81</td></tr><tr><td>PFUdA</td><td>0.012</td><td>0</td><td>226 (100)</td><td>0.08</td><td>0.11</td><td>0.14</td><td>0.22</td><td>0.39</td><td>0.048</td><td>14</td><td>188 (88.7)</td><td>0.07</td><td>0.10</td><td>0.14</td><td>0.21</td><td>0.44</td></tr></tbody></table>

Note: HCB, hexachlorobenzene; LOD, limit of detection; NA, not available; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluoronanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Associations between prenatal exposure to OCs and PFASs (log2, µg/L) and the development of breasts, pubic hair, and age at menarche in 12-year old girls, PELAGIE mother–child cohort, France. Note: Multinomial logistic regression and standard Cox proportional hazards models adjusted for maternal education level, maternal age at delivery, parity, maternal pre-pregnancy BMI, and maternal smoking status. For OCs: n = 235 for breast development and age at menarche, and n = 227 for pubic hair development; for PFASs: n = 200 for breast development and age at menarche, and n = 192 for pubic hair development. β-HCH, β-hexachlorocyclohexane; BMI, body mass index; HCB, hexachlorobenzene; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.</figcaption></figure>

or slowed pubertal development in both sexes. No associations were observed for organochlorine compounds, with the exception of β-HCH, which was associated with both accelerated and slowed pubic hair development in boys.

In girls, prepubertal exposure to both organochlorine compounds

(PCBs, HCB) and PFAS (PFOA, PFDA) was associated with delayed or slowed pubertal development (breast and pubic hair) and later age at menarche. Using a mixture approach, similar chemicals (PCBs, HCB, PFOA, PFDA), along with PFNA, were also linked to delayed pubertal development. In boys, prepubertal exposure to PCBs and PFAS (PFOA,
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Associations between prenatal exposure to OCs and PFASs (log2, µg/L) and the development of gonads and pubic hair in 12-year old boys, PELAGIE mother-child cohort, France. Note: Multinomial logistic regression models adjusted for maternal education level, maternal age at delivery, parity, maternal pre-pregnancy BMI, and maternal smoking status. For OCs: n = 226 for gonadal development, and n = 219 for pubic hair development; for PFASs: n = 201 for gonadal development, and n = 194 for pubic hair development. β-HCH, β-hexachlorocyclohexane; BMI, body mass index; HCB, hexachlorobenzene; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.</figcaption></figure>

PFHxS and PFDA) was associated with delayed or slowed gonadal and pubic hair development. During the prepubertal period, only p,p'-DDE was associated with earlier pubertal development in boys (for both gonadal and pubic hair).

Longitudinal puberty data are particularly suited to analyzing the role of risk factors affecting pubertal development, as demonstrated by several previous studies using self-reported assessments or clinical ex-aminations (Attfield et al., 2019; Ernst et al., 2019; Korrick et al., 2011; Windham et al., 2015). In the PELAGIE cohort, a clinical examination with a professional assessment of the Tanner Stage at age 12 was chosen to measure pubertal development, ensuring that our data accurately reflect the situation of children aged 12. This choice did not allow us to detect a change in the age at onset of puberty in association with exposure levels, but it did allow us to assess whether the exposure levels varied according to the expected pubertal stage at 12 years. In this study,

a reduced risk of being at an earlier Tanner stage (as well as an increased risk of being at a delayed stage) could be interpreted as a slowdown in pubertal development. Conversely, an increased risk of being at an earlier stage (or a reduced risk of being at a delayed stage) could reflect an acceleration of pubertal development. Interestingly, our results do not show continuity between delayed and earlier stages – suggesting, for example, that exposure to these compounds could slow pubertal devel-opment in the first stages without necessarily affecting the later stages, as observed with prepubertal exposure to PFOA in girls.

To date, sixteen studies have investigated the relationship between early-life exposure to organochlorine compounds (during pregnancy and childhood) and pubertal development in children. The pollutants most often studied are PCBs (n = 13 studies), p,p'-DDE (n = 11 studies) and HCB (n = 7 studies) (Supplemental Table S13).

For OCPs, all the studies (Gladen et al., 2000; Grandjean et al., 2012;
<caption>**Table 5**</caption>

Mixture effects of OCs and PFASs (log2, µg/L) on pubertal development in 12-year old girls and boys, PELAGIE mother–child cohort, France.

<table><thead><tr><th></th><th>Prenatal exposure</th><th>Prepubertal exposure</th></tr></thead><tbody><tr><td><strong>Girls</strong></td><td></td><td></td></tr><tr><td>Breast development (ref. B3)</td><td>OR (95 % CI)<sup>a</sup><br>(n = 192)</td><td>OR (95 % CI)<sup>b</sup><br>(n = 226)</td></tr><tr><td>≤B2</td><td>1.25 (0.65, 2.39)</td><td>1.26 (0.68, 2.30)</td></tr><tr><td>≥B4</td><td>0.98 (0.52, 1.86)</td><td>0.50 (0.26, 0.93)</td></tr><tr><td>Pubic hair development (ref. PH4)</td><td>OR (95 % CI)<sup>a</sup><br>(n = 184)</td><td>OR (95 % CI)<sup>b</sup><br>(n = 219)</td></tr><tr><td>≤PH3</td><td>1.19 (0.69, 2.02)</td><td>1.73 (1.04, 2.86)</td></tr><tr><td>PH5</td><td>1.88 (0.57, 6.13)</td><td>0.87 (0.35, 2.19)</td></tr><tr><td>Age at menarche (years)</td><td>HR (95 % CI)<sup>a</sup><br>(n = 192)</td><td>HR (95 % CI)<sup>b</sup><br>(n = 226)</td></tr><tr><td></td><td>0.95 (0.73, 1.24)</td><td>0.73 (0.56, 0.95)</td></tr><tr><td><strong>Boys</strong></td><td></td><td></td></tr><tr><td>Gonadal development (ref. G3)</td><td>OR (95 % CI)<sup>a</sup><br>(n = 187)</td><td>OR (95 % CI)<sup>b</sup><br>(n = 222)</td></tr><tr><td>≤G2</td><td>0.74 (0.41, 1.35)</td><td>1.67 (0.96, 2.91)</td></tr><tr><td>≥G4</td><td>0.58 (0.30, 1.08)</td><td>0.79 (0.44, 1.44)</td></tr><tr><td>Pubic Hair development (ref. PH2)</td><td>OR (95 % CI)<sup>a</sup><br>(n = 181)</td><td>OR (95 % CI)<sup>b</sup><br>(n = 215)</td></tr><tr><td>PH1</td><td>0.58 (0.27, 1.22)</td><td>1.45 (0.79, 2.64)</td></tr><tr><td>≥PH3</td><td>0.62 (0.34, 1.13)</td><td>0.73 (0.41, 1.29)</td></tr></tbody></table>

Note: BMI, body mass index; CI: 95% confidence interval; OCs, Organochlorine Compounds; PFASs, Perfluoroalkyl substances.

<sup>a</sup> G-computation quantile models adjusted for maternal education level, maternal age at delivery, parity, maternal pre-pregnancy BMI, maternal smoking status.

<sup>b</sup> G-computation quantile models adjusted for maternal education level, passive exposure to tobacco smoke, breastfeeding, child's z-score BMI at 12y.

Marks et al., 2021; Namulanda et al., 2016) except one (Vasiliu et al., 2004) found that prenatal exposure to DDE, HCB, or beta-HCH was not associated with pubertal development, in either boys or girls, as we observed in the present study for girls. For boys, we observed an association between beta-HCH and pubic hair development. Concerning exposure during childhood or adolescence, no consistent pattern across the literature seems to exist. For DDE, two studies did not report any association in girls, similar to our findings, (Denham et al., 2005; Wolff et al., 2008) while two others reported delayed onset of breast development, delayed pubic hair development, (Windham et al., 2015) or later age at menarche. (Attfield et al., 2019) In boys, one European study identified an association between DDE exposure in adolescents and advanced stages of gonadal and pubic hair development, (Den Hond et al., 2011) similar to our study, while a Russian study observed a later age for pubic hair development in boys, (Lam et al., 2015) and an another did not show an association. (Lam et al., 2014) With regards to HCB, two American studies found associations between childhood exposure and delayed onset of breast development and pubic hair in girls, (Windham et al., 2015) or a later age at menarche, (Attfield et al., 2019) similar to our study, however, this was not corroborated in another American study. (Denham et al., 2005) For boys, the present study showed no association between prepubertal exposure to HCB and gonadal development in boys, similar to the two previous Russian studies (Lam et al., 2014, 2015), but contradicting a Belgian study that observed advanced stages of gonadal development. (Den Hond et al., 2011) With regards to pubic hair development in boys, findings were conflicting between a Belgian study and Russian studies, while the present study observed no association. For β-HCH, most of the results reported by the few previous studies reported no association, except for a Russian study that found a later age for pubic hair development in boys. (Lam et al., 2015).

With regards to PCBs, our study observed no association between prenatal exposure and pubertal development in either girls or boys, consistent with the majority of the results reported in the six previous studies. (Gladen et al., 2000; Vasiliu et al., 2004; Grandjean et al., 2012;

Marks et al., 2021; Berghuis et al., 2022; Humblet et al., 2011) With regards to childhood or adolescence, three studies observed an association between PCB exposure and delayed menarche or breast development in girls, (Attfield et al., 2019; Den Hond et al., 2011; Windham et al., 2015) consistent with our results. On the other hand, one study found no association (Wolff et al., 2008), while another observed an earlier age of menarche in girls with PCB exposure. (Denham et al., 2005) In boys, one Belgian study observed an association between prepubertal PCB exposure and advanced stages of gonadal development, (Den Hond et al., 2011) though two Russian studies did not show any association, consistently with our results. (Burns et al., 2016; Korrick et al., 2011) Concerning the link between PCBs and pubic hair development in boys, our findings suggest a delay, adding further heterogeneity to the already mixed results. (Burns et al., 2016; Den Hond et al., 2011).

Ten studies recently investigated the relationship between early-life exposure to PFASs and pubertal development in children and adolescents (Supplemental Table S14). Consistent with the majority of the literature, (Christensen et al., 2011; Ernst et al., 2019; Kristensen et al., 2013; Liu et al., 2023; Marks et al., 2021) the present study did not report any association between prenatal exposure to PFOA, PFOS, PFHxS, PFNA, or PFDA and pubertal development in girls. In boys, only two studies have investigated the association between prenatal exposure to PFAS and gonadal or pubic hair development. (Ernst et al., 2019; Liu et al., 2023) No associations were observed with PFOA, PFNA, and PFOS. Our findings were similar, except that PFOS was linked to delayed gonadal development. In contrast, higher PFHxS levels were associated with advanced pubertal development in a European study (Ernst et al., 2019) but showed no association with pubic hair development in a North American study. (Liu et al., 2023) In our analysis, PFHxS was associated with delayed gonadal development and no association with pubic hair development. The present study was the first to examine the possible role of prenatal PFUdA exposure on pubertal development. Our findings suggest that prenatal PFUdA exposure was associated with delayed breast development in girls, but not with other pubertal development indicators in girls and boys.

Concerning prepubertal exposure to PFOA, four studies (Carwile et al., 2021; Liu et al., 2023; Lopez-Espinosa et al., 2011; Pinney et al., 2023) among six (Averina et al., 2024; Carwile et al., 2021; Cox et al., 2023; Liu et al., 2023; Lopez-Espinosa et al., 2011; Pinney et al., 2023) reported delayed pubertal development in girls with higher exposure, including later age at menarche, consistent with our findings. In boys, three studies (Carwile et al., 2021; Liu et al., 2023; Lopez-Espinosa et al., 2011) reported no association with pubertal development, and one study (Averina et al., 2024) observed advanced pubertal development, but the present study was the first to report possible delayed pubertal development. Regarding PFOS, four studies (Carwile et al., 2021; Liu et al., 2023; Lopez-Espinosa et al., 2011; Pinney et al., 2023) reported delayed pubertal development in girls, particularly for breast development, while we did not observe an association. In boys, three studies (Averina et al., 2024; Carwile et al., 2021; Liu et al., 2023) reported no association, as in our study. For PFHxS and PFNA, our findings of no association with pubertal development in girls are consistent with three previous studies, (Averina et al., 2024; Carwile et al., 2021; B Cox et al., 2023) although two others (Liu et al., 2023; Pinney et al., 2023) reported delayed puberty. For PFDA and PFUdA, an American study (Carwile et al., 2021) observed delayed puberty, in line with our observations, but contrasting with a European study (Averina et al., 2024) reporting advanced development. In boys, three previous studies (Averina et al., 2024; Carwile et al., 2021; Liu et al., 2023) did not observe any association with PFNA, PFDA or PFUdA. This was consistent with the present findings for PFNA and PFUdA, but contradicts with the delayed gonadal or pubic hair development that we reported for PFHxS and PFDA.

The effects of exposures to mixtures of compounds have only been assessed in three previous studies (in the U.S. and Great Britain). (Carwile et al., 2021; Liu et al., 2023; Marks et al., 2021) The British
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Associations between prepubertal exposure to OCs and PFASs (log2, µg/L) and the development of breasts, pubic hair, and age at menarche in 12-year old girls, PELAGIE mother–child cohort, France. Note: Multinomial logistic regression and standard Cox proportional hazards models adjusted for maternal education level, passive exposure to tobacco smoke, breastfeeding, and child's z-score BMI at 12y. For OCs and PFASs n = 226 for breast development and age at menarche, and n = 219 for pubic hair development. BMI, body mass index; HCB, hexachlorobenzene; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.</figcaption></figure>

study, which separately and jointly assessed prenatal exposure to mix-
tures of OCs and PFAS, found no association with the age of menarche.
(Marks et al., 2021) One of the American studies, using Quantile G-
computation, did not identify any association between prenatal expo-
sure to the compound mixture and pubertal development, but did

observe associations between PFAS exposure (PFOA, PFOS, PFNA, PFHxS) at age 12 and delayed breast and pubic hair development in girls, with the main contributors to the mixture being PFNA and PFHxS. No associations were observed in boys. (Liu et al., 2023) Using the Bayesian Kernel Machine Regression (BKMR) method, the second
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Associations between prepubertal exposure to OCs and PFASs (log2, µg/L) and the development of gonads and pubic hair in 12-year old boys, PELAGIE mother-child cohort, France. Note: Multinomial logistic regression models adjusted for maternal education level, passive exposure to tobacco smoke, breastfeeding, and child's z-score BMI at 12y. For OCs and PFASs n = 222 for gonadal development, and n = 215 for pubic hair development. BMI, body mass index; HCB, hexachlorobenzene; OCs, Organochlorine Compounds; PCBs, polychlorinated biphenyls; PFASs, Perfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFUdA, perfluoroundecanoic acid.</figcaption></figure>

American study observed that higher exposure to PFAS mixtures (PFOA, PFOS, PFDA, PFHxS, MeFOSAA, PFNA) during childhood was associated with delayed pubertal development in girls, but not boys. (Carwile et al., 2021) Although the exact list of compounds considered in the mixtures and the statistical models differ, our results also suggested that prepubertal exposure to a mixture of compounds including several PFAS (PFOA and PFDA) was associated with delayed breast and pubic hair development in girls, while no association was observed in boys or for prenatal exposure.

The discrepancies in the findings across the literature should not be necessarily viewed as contradictory and could be attributed to a variety of factors, including: differences in compound exposure levels observed in the study populations, variations in study periods that may imply different co-exposures to other risk factors, wide ranges of ages at assessment for pubertal development (from 6 to 17 years old), and methodological differences in the outcome definition. Moreover, we

cannot exclude the possibility that some compounds might influence the age at onset of puberty, but not the pace of pubertal development, or vice versa. Other methodological differences concerning exposure and outcome assessment (i.e. self-report or clinical exam, Tanner scale or other) could also introduce various forms of bias affecting our ability to directly compare previous findings with our own.

Some organochlorine and perfluoroalkyl substances can disrupt the normal development of puberty by interfering with the hypothalamic-pituitary-gonadal (HPG) axis, via several mechanisms crucial in sexual maturation. (Lee et al., 2019; Mouritsen et al., 2010; Schoeters et al., 2008) Intervening at various levels of the HPG axis, whether by mimicking or blocking the action of natural hormones, binding to receptors, or altering their synthesis and/or metabolism, their influence can be felt as early as the prenatal and neonatal phase, or just before puberty. These critical periods of development are particularly sensitive, as such mechanisms can potentially modify gene expression through
epigenetic processes. (Lee et al., 2019) Assessing the effects of OCs and PFASs on human puberty is complex, due to the long interval between the exposure and the appearance of pubertal markers, making it difficult to understand the exact mechanisms involved. (Lee et al., 2019; Schoeters et al., 2008) To our knowledge, only a few studies have used animal experiments to examine the possible role of exposure to OCs and PFASs in sexual maturation. (Du et al., 2019; Lau et al., 2006; Rasier et al., 2007) In rodents, some of these studies have identified effects on this maturation – sometimes with trends contrary to those observed here. However, these studies used maturation outcomes (such as vaginal opening or first estrus) that make them difficult to compare with those obtained in the present observational study.

The long half-lives of the pollutants examined in this study support the idea that prenatal and child measurements at age 12 reflect chronic exposure to organochlorine compounds and PFASs. A study showed half-lives between 11 and 17 years for PCBs (–118, –138, –153, –170, –180, –187), 6.4 years for HCB, and 17 years for p,p'-DDE (Bu et al., 2015). These values are consistent with those found in other studies, which are within the same orders of magnitude. (Gallo et al., 2015; Ritter et al., 2011) Two studies (Olsen et al., 2007; Lee and Choi, 2017) have estimated the biological half-lives of PFASs, which vary according to chemical structure and chain length. Modeling shows human half-lives ranging from 3 to 4 years for PFOA, 4 to 5 years for PFOS, and 7 to 10 years for PFHxS.

In our study, prenatal exposure was assessed via umbilical cord-blood samples – a method frequently used in the literature. This approach is based on the widely established and recognized hypothesis that measurements of OCs and PFASs in cord-blood samples reflect a continuous exposure during fetal life, while recognizing that it may also represent exposure during the first months of life. (Barr et al., 2005).

We assumed that the measurements taken during the child's 12-year clinical examination might adequately reflect exposure over the course of several years leading up to age 12. This phase can also correspond to a so-called "peripubertal phase" for children who have already started puberty. Grandjean's et al., 2008 study revealed that though these contaminants may have slightly shorter half-lives in children, they remain long enough to reflect chronic exposure. Moreover, a longitudinal study carried out on serum samples taken at 1, 6, and 10.5 years of age (between 2005-2015), showed that children's body burden of serum PFAS remained stable, or increased with age, confirming a correlation between the exposure data across different periods. (Koponen et al., 2018) These results suggest that the body burden observed at 10.5 years of age reflects previous exposure to the four PFASs studied (PFOS, PFOA, PFNA and PFHxS), reinforcing the relevance and confidence of the measurements taken at 12 years of age in our study to assess exposure during the prepubertal period.

It is hypothesized that associations observed between prepubertal contaminant exposure and pubertal development in girls may be influenced by reverse causality. Menstrual blood loss may be a potential means of PFASs excretion, which could influence variations in PFAS serum concentrations – thus partly explaining the association with delayed pubertal development. (Cox et al., 2023; Wu et al., 2015) However, our sensitivity analyses showed similar results when restricted to the non-menstruating girls with regards to breast development.

To our knowledge, this is the first French study, and one of the first in Europe, to examine the association between exposure to POPs and PFAS and pubertal development. Our sensitivity analyses showed that, despite some variation in the magnitude of the results, the initial trends remained constant, attesting to the robustness of our observations. The mixture approach considered in the present study also allowed us to better simulate human exposure to multiple chemical compounds simultaneously. The use of the Quantile g-computation method strengthened the associations observed in the single-pollutant analyses, confirming both the robustness and the consistency of our results. However, we cannot exclude the possibility that our results may have been influenced by exposure to one or more other chemical substances

that were neither measured nor taken into account by our study. The fact that we limited our analyses to exposure with a detection rate > 70 % meant that we were able to treat all these exposures continuously, strengthening our findings. On the other hand, non-linear associations may be subject to the risk of chance associations, particularly in areas of the exposure range where data are sparse. Such areas can unduly influence the shape of the exposure-response function and reduce the reliability of the estimates with wider confidence intervals. Despite this limitation, when non-linear approaches proved necessary, the curves presented in the Supplementary Material reinforced confidence in our results.

Due to the numerous models tested in this study, there is a risk of false positive findings, thus we remain cautious in interpreting our results. However, our findings remain consistent between the main analyses and the sensitivity analyses, reinforcing their robustness. Furthermore, all the statistical tests reported in the study were specified in advance (rather than *a posteriori*) and all the results are reported in the article.

Finally, the PELAGIE cohort, initially recruited from the general population of Brittany, was not intended to be representative. (Warenbourg et al., 2024) In general, once included, and for each follow-up conducted in the cohort, voluntary participation probably favored a population that is better educated than the source population as a whole.

## 5. Conclusion

Conducted in France, this study highlighted associations between prenatal and prepubertal exposure to several organochlorine compounds and perfluoroalkyl substances and pubertal development at age 12, with sex-specific effects. In girls, prenatal exposure to PFUdA (but not OCs), as well as prepubertal exposure to OCs and PFASs, was associated with delayed puberty. In boys, both prenatal and prepubertal exposure to PFASs was associated with slowed puberty, whereas prenatral and prepubertal exposure to OCs exhibited compound- and period-specific associations with pubertal timing (delayed or earlier puberty). Although our study investigated two critical periods of exposure, it did not consider early childhood exposure, which may play a key role in pubertal development and remains understudied. Additional studies incorporating repeated exposure measurements are required to identify sensitive ages and assess the impact of exposures on overall pubertal timing. Finally, a better understanding of the determinants of exposure is essential to explain inter-study differences and to inform effective public policies for exposure reduction.

## Data sharing

The PELAGIE cohort data comply with the European regulation on the protection of personal data (25/05/2018). This regulation is based on a logic of compliance and increased responsibility of the actors who access to the data. In addition, the cohort study complies with the French "informatique et liberté" law (law n°78-17, January 1978, 2018). Access to data is thus possible following the agreement of the cohort principal investigators (Cécile Chevrier, Charline Warenbourg) and on condition that the actors demonstrate respect for these European and French principles of personal data protection, to strengthen the rights of individuals. The code may also be made available to the scientific community. Further enquiries can be directed to the corresponding author.

## CRediT authorship contribution statement

**Lola Menant:** Writing – review & editing, Writing – original draft, Validation, Methodology, Formal analysis, Data curation, Conceptualization. **Florence Rouget:** Writing – review & editing, Writing – original draft, Supervision, Methodology, Conceptualization. **Hélène Tillaut:** Writing – review & editing, Methodology, Data curation. **Charline**
**Warembourg:** Writing – review & editing, Methodology, Data curation.
**Elke Rouxel:** Writing – review & editing, Methodology, Data curation.
**Fabrice Lainé:** Writing – review & editing, Supervision, Methodology, Investigation, Funding acquisition. **Éric Gaudreau:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Sylvaine Cordier:** Writing – review & editing, Methodology, Conceptualization.
**Ronan Garlantézeç:** Writing – review & editing, Methodology, Investigation, Funding acquisition, Conceptualization. **Christine Monfort:** Writing – review & editing, Validation, Supervision, Methodology, Investigation, Data curation. **Cécile Chevrier:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization.

## Funding

The PELAGIE cohort has been funded (since its inception) by Inserm, the French Ministries of Health (2003–2004), Labor (2002–2003), and Research (ATC 2003–2004), the French National Institute for Public Health Surveillance (InVS, 2002–2006), the National Agency for Research (ANR, 2005–2008, 2010–2012, 2015–2019), the French Agency for Environmental Health Safety (Afsset/ANSES, 2007–2009, 2009–2012, 2019–2023), the French Agency for Drug Safety (2013–2017), the Fondation de France (2014–2017, 2015–2018, 2017–2020, 2019–2021, 2021–2024), the French Ministry of Ecology (PNRPE 2014–2016), the Research Institute of Public Health (IReSP 2011–2014), and the following European programs: Hi-WATE (2007–2009), ENRIECO (2008–2010), OBERON (2019–2023), REMEDIA (2020–2024), and ENDOMIX (No 101136566, 2024–2028). This research is part of a PhD project funded by the Fondation de France (2023–2026).

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cecile Chevrier reports financial support was provided by French National Research Agency (ANR-14-CE21-0005). Cecile Chevrier reports financial support was provided by Foundation of France. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

We are grateful to the physicians, nurses, and all the families who participated in the study (and continue to do so). We especially thank the UIC health personnel, Stéphanie Métayé and Cécile Réminiac for their rigorous work in examining the children, and Nathalie Costet, Véronique Villalon, and Isabelle Coiffec who contributed to the PELAGIE cohort in general. We also thank Nolwenn Le Meur, Teacher-Researcher at Ecole des hautes études en santé publique (EHESP) (Rennes, France) and German Cano Sancho, Researcher at Institut national de la recherche pour l'agriculture, l'alimentation et l'environnement (INRAE) (Nantes, France), for their help and advice. We particularly thank Jane Roffe and Courtney Dow for the English editing.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.envint.2025.109845.

## Data availability

Data will be made available on request, subject to compliance with European data protection rules and with the consent of the cohort's PIs.

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