# Dietary exposure to mixtures of chemicals in the first year of life and allergic and respiratory diseases up to 8 years in the French EDEN mother-child cohort

Manel Ghozal, Rosalie Delvert, Karine Adel-Patient, Muriel Tafflet, Isabella

Annesi-maesano, Amélie Crépet, Véronique Sirot, Marie-Aline Charles, B.

Heude, Manik Kadawathagedara, et al.

► To cite this version:

Manel Ghozal, Rosalie Delvert, Karine Adel-Patient, Muriel Tafflet, Isabella Annesi-maesano, et al. Dietary exposure to mixtures of chemicals in the first year of life and allergic and respiratory diseases up to 8 years in the French EDEN mother-child cohort. Food and Chemical Toxicology, 2025, 196, pp.115167. 10.1016/j.fct.2024.115167. anses-04964046

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# Dietary exposure to mixtures of chemicals in the first year of life and allergic and respiratory diseases up to 8 years in the French EDEN mother-child cohort

Manel Ghozal<sup>a, *, *</sup>, Rosalie Delvert<sup>b</sup>, Karine Adel-Patient<sup>c</sup>, Muriel Tafflet<sup>a</sup>, Isabella Annesi-Maesano<sup>d</sup>, Amélie Crépet<sup>e</sup>, Véronique Sirot<sup>e</sup>, Marie Aline Charles<sup>a</sup>, Barbara Heude<sup>a</sup>, Manik Kadawathagedara<sup>a</sup>, Blandine de Lauzon-Guillain<sup>a, **</sup>

## ARTICLE INFO

Handling Editor: Dr. Bryan Delaney

Keywords:

Diet

Chemicals

Postnatal

Allergy

Multimorbidity

## ABSTRACT

Exposure to environmental chemicals has been associated with higher risk of childhood allergies. This study aimed to examine the association between infant's dietary exposure to mixtures of chemicals and allergic and respiratory multimorbidity in childhood.

Dietary exposures were assessed at 8 and 12 months in 724 and 745 children of the EDEN cohort. Allergic and respiratory multimorbidity clusters were identified using latent class analyses. Associations between dietary exposure to mixtures of chemicals and allergic clusters were assessed by adjusted multinomial logistic regressions.

At 8 months, higher exposure to a mixture of furans, trace elements, dioxins and PAHs was positively associated with the "asthma only" cluster, while moderate exposure to a mixture of PAHs, pesticides, PCBs and acrylamide was negatively associated with this cluster. A mixture of PCBs and BFRs was positively associated with the "multi-morbidity" cluster. Exposure to a mixture of pesticides and trace elements was positively associated with the "allergy without asthma" cluster. At 12-months, higher exposure to a mixture of trace elements and pesticides was positively associated with "multi-morbidity" cluster.

The differences in findings between the two ages suggest the need for further studies to explore this critical window of chemical exposure and its impact on children's health.

## 1. Introduction

Genetic and hereditary factors play a significant role in allergic susceptibility. However, they cannot account alone for the recent surge in allergic prevalence observed worldwide (Campbell et al., 2015). Environmental factors such as dietary changes, exposure to chemicals and air pollution, might play a determinant role in the initiation and development of allergic and respiratory symptoms in humans (Anto et al., 2017).

Early life exposure to environmental chemicals is a factor of primary interest considering the potency of chemicals to alter the development and maturation of the immune system and of the epithelial barrier, which may favor the development of immune-related disorders such as allergic diseases later in life (García-Serna et al., 2021). However, most of epidemiological studies focused on exposure to chemicals during the intrauterine life and limited number of studies focused on childhood exposure to some chemicals in association with asthma or allergy (Gascon et al., 2014; Robinson and Miller, 2015; Luo et al., 2020;

<footnote><sup>a</sup> Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Centre for Research in Epidemiology and StatisticS (CRESS), Paris, France</footnote>

<footnote><sup>b</sup> Université Paris-Saclay, UVSQ, Université Paris-Sud, Inserm, Equipe d'Épidémiologie Respiratoire Intégrative, CESP, 94805, Villejuif, France</footnote>

<footnote><sup>c</sup> Université Paris-Saclay, CEA, INRAE, MTS, Gif-sur-Yvette, France</footnote>

<footnote><sup>d</sup> Institute Desbrest of Epidemiology and Public Health (IDESP), Montpellier University and INSERM, Montpellier, France</footnote>

<footnote><sup>e</sup> Anses, French Agency for Food, Environmental and Occupational Health and Safety, Risk Assessment Department, Methodology and Studies Unit, Maisons-Alfort, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>** Corresponding author. Inserm CRESS Equipe EAROH Batiment Leriche, 16 avenue Paul Vaillant Couturier, 94807, Villejuif Cedex. France.
E-mail addresses: manel.ghozal@inserm.fr (M. Ghozal), blandine.delauzon@inserm.fr (B. de Lauzon-Guillain).</footnote>
Rodrigues et al., 2022; Wang et al., 2022). Only few studies emphasized the early postnatal period of exposure to chemicals (Raanan et al., 2015; Canbaz et al., 2016; Jerzynska et al., 2017; Navaranjan et al., 2021; Mendy et al., 2023).

The existing literature on associations between postnatal exposure to chemicals and allergy is composed mainly of studies on single exposure to chemicals. They did not consider multiple exposure to several substances and the subsequent mixture effects. Moreover, diet is an important source of exposure to a large panel of environmental chemicals in childhood (Papadopoulou et al., 2019), but studies exploring specifically dietary exposure to chemicals in infancy on later children health are still missing or insufficient (LaKind Judy et al., 2018).

Finally, according to the atopic march and atopic multimorbidity concepts, infants with atopic dermatitis are at higher risk of developing allergic rhinitis and asthma in childhood and these despises may persist during several years, leading to allergic and respiratory multimorbidity (Paller et al., 2019).

In this context, the aim of the present study was to explore the association between dietary exposure to mixtures of chemicals in infancy and allergic and respiratory multimorbidity clusters in childhood.

# 2. Materials and methods

## 2.1. Study design

The EDEN mother–child cohort (Heude et al., 2016) enrolled 2002 pregnant women between February 2003 and January 2006, at the end of their first trimester of pregnancy. It involved two university maternity centers in Nancy and Poitiers (France). Pregnant women presenting before 24 weeks of amenorrhea, without multiple pregnancies and able to read and speak French were invited to participate. Children were followed up to age of 8 years by questionnaires completed by parents at the following ages of the child: 4, 8 and 12 months, and 2, 3, 4, 5–6 and 8 years. The study was approved by the ethics committee of the university hospital of Kremlin-Bicêtre (ID 0270, December 12, 2002) and data files were declared to the National Committee for Processed Data and Freedom (CNIL, ID 902267, December 12, 2002). Written consent was obtained from both parents.

## 2.2. Dietary exposure to chemicals in infancy

In the infant French Total Diet Study (iTDS) (Hulin et al., 2014), 670 chemicals were measured in food stuffs. To deal with undetected or unquantified values, a lower bound scenario was applied: non-detected values were replaced by 0, whereas detected values unable to be quantified were replaced by the limit of detection. In the EDEN mother-child cohort, infant diet was assessed at 8 and 12 months using three 24-h dietary records (non-consecutive days). Then, these daily intakes were combined with data from the iTDS to calculate infant dietary exposure to chemicals. 235 individual chemicals were considered as they have been detected in at least one food item consumed at 8 months or 12 months: 86 pesticides, 24 trace elements, 18 PAHs (polycyclic aromatic hydrocarbons), 10 per- and polyfluoroalkyl substances (PFASs), 17 dioxins and furans, 18 polychlorobiphenyls (PCBs), 18 mycotoxins, 15 brominated flame retardants (BFRs), 10 phytoestrogens, 8 phthalates, 3 food additives and compounds, 3 bisphenol A diglycidyl ether (BADGE) derivates, two alkylphenols, plasticizer dibutyl sebacate, acrylamide and bisphenol A (Supplementary Table 1).

Then, mixtures of chemicals were identified solely based on combined dietary exposure of EDEN infants, without considering relative potency factors (RPFs), using the sparse non-negative matrix underapproximation (SNMU) method as proposed by Traoré et al. (Traore et al., 2018). This method of dimension reduction is specific to non-negative matrices and thus suitable for nutritional exposure data consisting of positive values with many zero values (Béchaux et al., 2013).

Applying this method, the chemical exposures of the studied population can be expressed as a matrix E of dimension (PxN) where P is the number of substances and N the number of individuals. E is factorized by two low ranked non-negative matrices (PxK) and (KxN), where K is a factorial dimension designating the number of exposure systems (Zetlaoui et al., 2011; Traore et al., 2018). To choose the optimal K value, SNMU is run for different values of K and the residual sum of squares were minimized as explained in Traoré. Since units of chemicals concentration are not the same between all chemicals, concentrations were reduced to avoid scaling effect. Eight mixtures were identified at each age of exposure (Supplementary Tables 2 and 3), which names were defined according to the substances contributing the most to their composition. A coefficient is given for each infant and each mixture that reflects the contribution of each mixture to the overall exposure for this infant, a higher coefficient reflecting a higher exposure to the mixture. Scores of exposures were divided by the standard deviation (SD) to allow estimation of odds ratio (OR) for a variation of one SD increase in the mixture pattern and facilitate comparison of effect size across mixtures.

## 2.3. Allergic and respiratory variables

Allergic and respiratory events were collected using the International Study on Asthma and Allergies in Childhood (ISAAC) questionnaire (Asher et al., 1995), completed by parents at each follow-up between birth and 8 years of the child. Children were considered as having the allergic or respiratory event if parents reported this event at least once from 1 to 8 years. The MeDALL definition (Anto et al., 2017) was used for eczema and allergic rhinitis and the ISAAC definition was used for current asthma. Parental report of medical diagnosis was used for food allergy.

Children were defined as having current asthma if they fulfilled at least one of the following two criteria: doctor-diagnosed asthma combined with wheezing in the last 12 months, or doctor-diagnosed asthma combined with use of asthma medication in the last 12 months in accordance with the ISAAC definition. Eczema was defined according to the MeDALL definition (Anto et al., 2017) as a positive answer to three items ("Has your child ever been diagnosed with eczema?"; "[Since last follow-up], has your child had an itchy rash (red patches, pimples etc.) on the skin that appears and disappears intermittently?"; "Has this itchy rash affected any of the following areas: the folds of the elbows, behind the knees, in front of the ankles, under the buttocks, around the neck, around the eyes or ears?"). The MeDALL definition was also used for allergic rhinitis and based on a positive answer to two items: "[Since last follow-up] has your child had sneezing, a runny nose or a stuffy nose without respiratory infection (no cold, no rhinopharyngitis, no flu etc.)? Were these nose problems accompanied by watering (crying) or itching (scratching) of the eyes?".

## 2.4. Other variables

Demographic and socioeconomic covariates were collected at delivery: maternal age, maternal education level (up to lower secondary, upper secondary, intermediate, 2-year university degree, ≥3-year university degree), household monthly income (<€800, €801–1500, €1501–2300, €2301–3000, >€3000). Maternal and child characteristics were also collected: primiparity, maternal smoking during pregnancy (yes/no), maternal diet quality (PANDiet score) (Bianchi et al., 2016), family history of allergy (at least one child's parent or sibling with food allergy, asthma, allergic rhinitis or eczema), child's sex, gestational age, and birth weight. Infant feeding practices such as breast-feeding duration and age at complementary feeding introduction were reported by mother using self-reported questionnaires at 4, 8 and 12 months.

## 2.5. Study sample

From the 2002 women included in the EDEN mother-child cohort, 95
left the study before delivery. Children with declared allergic and respiratory events at the 8 months follow up (n = 605) and those with missing data on allergic and respiratory multimorbidity clusters (n = 278) were excluded. Children still breastfed at the 24-h dietary record completion (n = 148 and n = 65 at 8 months and 12 months, respectively) were also excluded, as daily breast milk intake could not be determined. Children with missing food records (n = 152 at 8 months, n = 214 at 12 months) were also excluded. Finally, 724 and 745 children were included in the analyses, for the 8-month and 12-month exposure, respectively (Supplementary Fig. 1).

## 2.6. Statistical analysis

Exposure to mixtures “F-TE-D-PAH”, “TE-F-D-PCB”, “Pest”, “BFR-PAH-TE”, “Pest-TE” and “PAH-Pest-PCB-Acry” was considered as 3-category variables (low/medium/high exposure according to the tertiles). For the remaining mixtures for which the number of children exposed is very low, the variables were considered as binary (exposed/non-exposed).

Associations were tested between mixtures identified at 8- vs 12-month for mixtures showing close or similar compositions using Chi square tests on a subsample of children with available mixture data at both 8 and 12 months (n = 614).

Latent Class Analysis (LCA) was applied to identify allergic multimorbidity clusters in children between 1 and 8 years. 1024 children with available data on all allergy and respiratory outcomes (food allergy, eczema, wheezing, medication for asthma, medical diagnosis of asthma, and allergic rhinitis) and no events declared at the 8 months follow up were included in the LCA model. Solutions of 2-6 clusters were tested using 100 replications and 100,000 iterations. Bayesian Information Criterion (BIC) minimization and interpretability were used to select the optimal number of clusters.

Multinomial logistic regressions were used to examine associations between dietary exposure to mixtures of chemicals in infancy and allergy/respiratory multimorbidity clusters. Potential confounding factors were first identified based on literature findings, then selected with the directed acyclic graph method (Shrier and Platt, 2008) (Supplementary Fig. 2). Our main models were adjusted for the minimal sufficient adjustment set identified by the DAG: maternal age, education level, household income, primiparity, region (recruitment center), maternal diet quality (PANDiet score), family history of allergy, breastfeeding duration and age of complementary feeding introduction.

Interaction with child sex was tested at both ages. A significant interaction was found between exposure to mixture Pest-TE at 8 months and sex, but no significant interaction was reported for the exposure to mixtures at 12 months. Thus, as the child sex is associated with allergies, and is not in the causal pathway from dietary exposure to chemicals to allergic multimorbidity, we decided to adjust for it in the main model. Additionally, for exposure at 8 months to the mixture Pest-TE, we conducted a sensitivity analysis stratified on the child sex.

We also performed some sensitivity analysis. First, to consider the potential role of the prenatal period of exposure (Ghozal et al., 2023), a model was run with additional adjustment on maternal dietary exposure to eight mixtures of chemicals identified during pregnancy. Second, considering the reported associations between perinatal tobacco smoke and children allergy (Feleszko et al., 2014; Silvestri et al., 2015; Li et al., 2022), a second model with additional adjustment on maternal smoking during pregnancy was performed. Also, as exposure variables were not normalized by body weight this model was also adjusted on infant's energy intake. Third, to allow a better comparison of our findings at 8- vs 12-months, a model was run on a subsample of children with available data on exposure at both 8- and 12- months.

To deal with missing values on confounding factors, we performed multiple imputations. Data were assumed to be missing at random, and 5 independent datasets were generated with the fully conditional specification method (MI procedure, FCS statement, NIMPUTE option), then

pooled effect estimates were calculated (SAS MIANALYZE procedure). Continuous variables were imputed with predictive mean matching, and logistic regressions were used for categorical variables (Supplementary Table 4).

# 3. Results

## 3.1. Population description

Children and mothers' characteristics are presented in Table 1. Compared to excluded children, included children with available data on exposure to chemicals at 8 months were more likely to be born to mothers with higher education level, higher income and lower maternal smoking during pregnancy (Supplementary Table 5). Lower family history of allergy (47.6% vs. 54.3%) were also reported among included children. Children with available exposure data at 12 months showed similar characteristics. Description of the study population exposure to mixtures of chemicals is presented in Table 2.

## 3.2. Exposure to mixtures of chemicals

Mixtures were named according to substances' families contributing the most to their composition. Mixtures composition is presented in Supplementary Figs. 3 and 4.

* A mixture composed mainly of furans, trace elements, dioxins and PAHs was identified at 8 and 12 months. At 8 months, this mixture included 30% furans, 24% trace elements, 15% dioxins and 10% PAHs and was named “F-TE-D-PAH”. At 12 months, the mixture included 24% trace elements, 22% furans, 14% dioxins, 14% PCBs and was named “TE-F-D-PCB”. 18 out of the 20 first contributing chemicals are common between the 8- and 12-month mixtures.

* A mixture composed mainly of PCBs and BFRs was identified at 8 and 12 months and was named “PCB-BFR”. At 8 months, this mixture included 65% PCBs and 19% BFRs. At 12 months, the mixture included 55% PCBs and 25% BFRs. 18 out of the 20 first contributing chemicals are common between the 8- and 12-month mixtures.

<table><caption>**Table 1**

Characteristic of the main sample.</caption><thead><tr><th></th><th>8 months<br>(N = 724)</th><th>12 months<br>(N = 745)</th></tr></thead><tbody><tr><td><strong>Maternal characteristics</strong></td><td></td><td></td></tr><tr><td>Age at delivery, mean (SD)</td><td>29.7 (4.66)</td><td>30 (4.69)</td></tr><tr><td>Education level, % (n)</td><td></td><td></td></tr><tr><td>Lower then high school diploma</td><td>20.7% (149)</td><td>19.1% (142)</td></tr><tr><td>High school diploma</td><td>18.3% (132)</td><td>18.2% (135)</td></tr><tr><td>At least 2 years university degree</td><td>24% (173)</td><td>23.5% (174)</td></tr><tr><td>At least 5 years university degree</td><td>37% (267)</td><td>39.2% (291)</td></tr><tr><td>Family income (€/month)</td><td></td><td></td></tr><tr><td>&lt; 1500</td><td>11% (79)</td><td>8.6% (64)</td></tr><tr><td>1501-2300</td><td>27.6% (199)</td><td>28.7% (213)</td></tr><tr><td>2301-3000</td><td>28.3% (204)</td><td>28.3% (210)</td></tr><tr><td>&gt; 3000</td><td>33.1% (239)</td><td>34.4% (255)</td></tr><tr><td>Smoking during pregnancy, % (n)</td><td>20.8% (148)</td><td>20.8% (152)</td></tr><tr><td>Primiparity, % (n)</td><td>50% (361)</td><td>49.5% (368)</td></tr><tr><td>Maternal diet quality (PANDiet-G, 0-100 score), mean (SD)</td><td>64 (6.87)</td><td>64.3 (6.91)</td></tr><tr><td><strong>Child and family characteristics</strong></td><td></td><td></td></tr><tr><td>Boys, % (n)</td><td>47.8% (346)</td><td>49% (365)</td></tr><tr><td>Age of complementary feeding introduction (month), mean (SD)</td><td>4.3 (1.5)</td><td>4.4 (1.53)</td></tr><tr><td>Breastfeeding duration (month), mean (SD)</td><td>2.3 (2.32)</td><td>2.8 (2.97)</td></tr><tr><td>Family history of allergy, % (n)</td><td>47.6% (340)</td><td>47.4% (349)</td></tr><tr><td><strong>Allergic and respiratory clusters, % (n)</strong></td><td></td><td></td></tr><tr><td>Asymptomatic</td><td>84.3% (610)</td><td>84% (626)</td></tr><tr><td>Asthma only</td><td>7.3% (53)</td><td>7.4% (55)</td></tr><tr><td>Multi-morbidity</td><td>4.3% (31)</td><td>4.8% (36)</td></tr><tr><td>Allergy without asthma</td><td>4.1% (30)</td><td>3.8% (28)</td></tr></tbody></table>
<table><caption>**Table 2**
Dietary exposure to mixture of chemicals in study samples.</caption><thead><tr><th></th><th></th><th></th></tr></thead><tbody><tr><td colspan="3">Dietary exposure to mixtures identified at 8 months (N = 724), % (n)</td></tr><tr><td rowspan="3">F-TE-D-PAH</td><td>Low exposure</td><td>25.8% (187)</td></tr><tr><td>Medium exposure</td><td>38.4% (278)</td></tr><tr><td>High exposure</td><td>35.8% (259)</td></tr><tr><td rowspan="2">PCB-BFR</td><td>No exposure</td><td>46.7% (338)</td></tr><tr><td>Exposure</td><td>53.3% (386)</td></tr><tr><td rowspan="2">Pest-TE</td><td>No exposure</td><td>71.3% (516)</td></tr><tr><td>Exposure</td><td>28.7% (208)</td></tr><tr><td rowspan="3">PAH-Ptha</td><td>Low exposure</td><td>33.3% (241)</td></tr><tr><td>Medium exposure</td><td>33.4% (242)</td></tr><tr><td>High exposure</td><td>33.3% (241)</td></tr><tr><td rowspan="2">BFR-PCB-F-Diox</td><td>No exposure</td><td>44.9% (325)</td></tr><tr><td>Exposure</td><td>55.1% (399)</td></tr><tr><td rowspan="2">TE-PAH-Pest</td><td>No exposure</td><td>50.8% (368)</td></tr><tr><td>Exposure</td><td>49.2% (356)</td></tr><tr><td rowspan="3">PAH-Pest-PCB-Acry</td><td>Low exposure</td><td>35.2% (255)</td></tr><tr><td>Medium exposure</td><td>33% (239)</td></tr><tr><td>High exposure</td><td>31.8% (230)</td></tr><tr><td colspan="3">Dietary exposure to mixtures identified at 12 months (N = 745), % (n)</td></tr><tr><td rowspan="3">TE-F-D-PCB</td><td>Low exposure</td><td>30.5% (227)</td></tr><tr><td>Medium exposure</td><td>34.9% (260)</td></tr><tr><td>High exposure</td><td>34.6% (258)</td></tr><tr><td rowspan="2">PCB-BFR</td><td>No exposure</td><td>50.6% (377)</td></tr><tr><td>Exposure</td><td>49.4% (368)</td></tr><tr><td rowspan="2">Pest-TE</td><td>No exposure</td><td>69.5% (518)</td></tr><tr><td>Exposure</td><td>30.5% (227)</td></tr><tr><td rowspan="3">PAH</td><td>Low exposure</td><td>33.2% (247)</td></tr><tr><td>Medium exposure</td><td>35% (261)</td></tr><tr><td>High exposure</td><td>31.8% (237)</td></tr><tr><td rowspan="2">BFR-PAH-TE</td><td>No exposure</td><td>51.8% (386)</td></tr><tr><td>Exposure</td><td>48.2% (359)</td></tr><tr><td rowspan="3">TE-Pest</td><td>Low exposure</td><td>45.2% (337)</td></tr><tr><td>Medium exposure</td><td>21.3% (159)</td></tr><tr><td>High exposure</td><td>33.4% (249)</td></tr><tr><td rowspan="2">Bisph-TE</td><td>No exposure</td><td>75% (559)</td></tr><tr><td>Exposure</td><td>25% (186)</td></tr></tbody></table>

* A mixture composed mainly of pesticides and trace elements was identified at 8 and 12 months and was named "Pest-TE". At 8 months, this mixture included 73% pesticides and 22% trace elements. At 12 months, it included 78% pesticides and 18% trace elements. 18 out of the 20 first contributing chemicals are common between the 8- and 12-months mixtures.

* A mixture composed mainly of pesticides, different from that of the previous mixture (mainly Thiacloprid, Acetamiprid, Captan) was identified at 8 and 12 months and was named "Pest". At 8 months, this mixture included 61% pesticides, 9% PCBs, and 7% phthalates. At 12 months, it included 64% pesticides, 8% phthalates and 8% phytoestrogens. 14 out of the 20 first contributing chemicals are common between the 8- and 12-months mixtures.

* A mixture composed mainly of PAHs, globally different to that of the F-TE-D-PAH mixture, was identified at 8 and 12 months. At 8 months,

this mixture included 79% PAHs and 11% phthalates and was named "PAH-Ptha". At 12 months, it included 83% PAHs and 8% trace elements and was named "PAH". 9 out of the 20 first contributing chemicals are common between the 8- and 12-months mixtures.

* A mixture composed mainly of BFRs (mainly Hexabromocyclododecane compounds) was identified at 8 and 12 months. At 8 months, this mixture included 51% BFRs, 20% PCBs, 12% furans and 10% dioxins and was named "BFR-PCB-F-D". At 12 months, it included 58% BFRs, 14% PAHs and 10% trace elements and was named "BFR-PAH-TE".

* A mixture composed of trace elements and pesticides was identified at 8 and 12 months. At 8 months, this mixture included 39% trace elements, 22% PAHs, and 21% pesticides and was named "TE-PAH-Pest". At 12 months, it included 43% trace elements and 32% pesticides and was named "TE-Pest". 15 out of the 20 first contributing chemicals are common between the 8- and 12-month mixtures.

* A mixture composed of 34% PAHs, 15% pesticides, 12% PCBs and 6% acrylamide, was identified only from data at 8 months, and was named "PAH-Pest-PCB-Acry".

* A mixture composed of 55% BADGE derivates, 11% trace elements and 9% BPA was identified only from data at 12 months and was named "Bisph-TE".

For the 7 first mixtures that showed close or similar compositions between exposures at 8 and 12 months, significant differences were though found between exposures at the two ages (Supplementary Fig. 5).

### 3.3. Allergic and respiratory multimorbidity clusters between 1 and 8 years

Among the 1024 children with allergic and respiratory data available, four clusters of allergic and respiratory diseases were identified (Supplementary Table 6).

i. An "asymptomatic" cluster, (84%): This group of children was characterized by low prevalence of all allergic and respiratory events.

ii. An "asthma only" cluster, (7.2%): a group characterized by a high prevalence of wheezing (89%), asthma medication (100%), and medical diagnosis of asthma (66%), a low prevalence of food allergy (6%), and allergic rhinitis (14%) and no eczema.

iii. A "multi-morbidity" cluster, (5.2%): a group with a high prevalence of all allergic and respiratory outcomes.

iv. A "allergy without asthma" cluster, (3.6%): a group with a high prevalence of food allergy (16%), eczema (44%), and rhinitis (100%), but no medical diagnosis of asthma.

### 3.4. Dietary exposure to mixture of chemicals at 8 months and allergic and respiratory multimorbidity clusters

Compared to low exposure (1st tertile), high dietary exposure (3rd tertile) to the "F-TE-D-PAH" mixture at 8 months was associated with higher risk of belonging to the "asthma only" cluster (OR [95 %CI] = 1.82 [1.13; 2.92]), but not with other clusters (Table 3). This association was unchanged after adjustment for maternal dietary exposure to mixtures of chemicals during pregnancy (Supplementary Table 7).

Compared to no exposure, dietary exposure to the mixture "PCB-BFR" at 8 months was associated with higher risk of belonging to the "multi-morbidity" cluster (1.66 [1.02; 2.73]), but not with other clusters (Table 3). This association was unchanged after adjustment for maternal dietary exposure to mixtures of chemicals during pregnancy (Supplementary Table 7)

Compared to no exposure, dietary exposure to the "Pest-TE" mixture at 8 months was associated with higher risk of belonging to the "allergy without asthma" cluster (OR [95 %CI] 1.58 [1.01; 2.35]), but not with
<caption>**Table 3**</caption>

Association between dietary exposure to mixture of chemicals at 8 months and allergic and respiratory multimorbidity clusters between 1 and 8 years (n = 724).

<table><thead><tr><th rowspan="2">Mixtures</th><th colspan="3">OR[95%CI], reference group: asymptomatic</th></tr><tr><th>Allergy without asthma</th><th>Multimorbidity</th><th>Asthma only</th></tr></thead><tbody><tr><td><strong>F-TE-D-PAH</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>1.28 [0.75; 2.20]</td><td>1.11 [0.65; 1.92]</td><td>1.15 [0.73; 1.82]</td></tr><tr><td>High exposure</td><td>0.57 [0.28; 1.19]</td><td>0.81 [0.45; 1.44]</td><td>1.82 [1.13; 2.92]</td></tr><tr><td><strong>PCB-BFR</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>0.91 [0.57; 1.45]</td><td>1.66 [1.02; 2.73]</td><td>0.97 [0.68; 1.39]</td></tr><tr><td><strong>Pest-TE</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>1.54 [1.01; 2.35]</td><td>0.75 [0.46; 1.22]</td><td>0.90 [0.63; 1.30]</td></tr><tr><td><strong>Pest</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>0.91 [0.5; 1.63]</td><td>1.19 [0.69; 2.07]</td><td>1.12 [0.74; 1.68]</td></tr><tr><td>High exposure</td><td>0.97 [0.55; 1.69]</td><td>0.75 [0.41; 1.37]</td><td>0.92 [0.60; 1.40]</td></tr><tr><td><strong>PAH-Phta</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>0.92 [0.61; 1.4]</td><td>1.06 [0.71; 1.57]</td><td>1.11 [0.81; 1.51]</td></tr><tr><td><strong>BFR-PCB-F-D</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>1.29 [0.83; 1.99]</td><td>0.98 [0.64; 1.48]</td><td>1.11 [0.81; 1.53]</td></tr><tr><td><strong>TE-PAH-Pest</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>0.81 [0.51; 1.29]</td><td>1.35 [0.85; 2.13]</td><td>0.75 [0.53; 1.07]</td></tr><tr><td><strong>PAH-Pest-PCB-Acry</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>1.40 [0.80; 2.44]</td><td>0.74 [0.41; 1.33]</td><td>0.60 [0.37; 0.96]</td></tr><tr><td>High exposure</td><td>0.59 [0.28; 1.26]</td><td>1.80 [0.99; 3.27]</td><td>1.04 [0.66; 1.64]</td></tr></tbody></table>

Values are odds ratios [95% CI] from a multinomial logistic regression model including the eight mixtures simultaneously. The “asymptomatic” cluster was used as a reference group and adjustment were made for maternal characteristics (age, education level, household income, primiparity, diet quality), child and birth characteristics (sex, family history of allergy, breastfeeding duration and age at complementary feeding introduction) and study center. Abbreviations: F-TE-PAH-D, furans-trace elements-polycyclic aromatic hydrocarbons-dioxins; PCB-BFR, polychlorobiphenyls-brominated flame retardants; Pest-TE, pesticides-trace elements; TE-PAH-Pest, trace elements-polycyclic aromatic hydrocarbons-pesticides; Pest, pesticides; PAH-Pest-PCB-Acry, polycyclic aromatic hydrocarbons-pesticides-polychlorobiphenyls-acrylamide; PAH-Phta, polycyclic aromatic hydrocarbons-phtalates; BFR-PCB-F-D, brominated flame retardants-polychlorobiphenyls-furans-dioxins.

other clusters. This association was marginal after adjustment for maternal dietary exposure to mixtures of chemicals during pregnancy (Supplementary Table 7). After stratification on child sex, this association was significant in girls (OR [95%CI] = 2.03 [1.07; 3.83]) but not in boys (OR [95%CI] = 1.35 [0.65; 2.77]), interaction p-value = 0.01.

Compared to low exposure, high dietary exposure to the mixture “PAH-Pest-PCB-Acry” at 8 months showed a marginal association with higher risk of belonging to the “multi-morbidity” cluster (1.8 [0.99; 3.27]). Medium exposure to the same mixture was associated with a lower risk of belonging to the cluster “Asthma only” (Table 3). Only the positive association between this mixture and the cluster “multi-morbidity” was significant after adjustment for maternal dietary exposure to mixtures of chemicals during pregnancy (Supplementary Table 7).

The 8-month exposures to the mixtures “TE-PAH-Pest”, “Pest”, “BFR-PCB-F-D” and “PAH-Phta” were not associated with allergic and respiratory clusters between 1 and 8 years (Table 3).

In the model additionally adjusted for infant’s energy intake and maternal smoking during pregnancy, the association with the mixture “F-TE-D-PAH” was no more significant. All other previous observed associations remained significant (Supplementary Table 8).

In the model run on a subsample of children with available data for both 8- and 12-month exposure, the associations observed with the mixtures “F-TE-D-PAH” and “PCB-BFR” were still significant (Supplementary Table 9).

### 3.5. Dietary exposure to mixture of chemicals at 12 months and allergic and respiratory multimorbidity clusters

Compared to low exposure, high dietary exposure to the mixture “TE-Pest” at 12 months was associated with higher risk of belonging to the “multi-morbidity” cluster (OR[95%CI] 2.31 [1.34; 3.98]) (Table 4). This association was unchanged after adjustment for maternal dietary exposure to mixtures of chemicals during pregnancy (Supplementary Table 10).

The exposures to mixtures “TE-F-D-PCB”, “PCB-BFR”, “Pest-TE”, “Pest”, “Bisph-TE”, “PAH” and “BFR-PAH-TE” at 12 months were not associated with allergic or respiratory clusters between 1 and 8 years (Table 4).

These findings remained similar after additional adjustment for infant’s energy intake and maternal smoking during pregnancy (Supplementary Table 11), and in the subsample of children with available data on both 8- and 12-month exposure (Supplementary Table 12).

## 4. Discussion

This study is the first to examine the association between dietary exposure to mixtures of chemicals during infancy with allergic and respiratory multimorbidity clusters in childhood. Dietary exposure to mixtures of chemicals estimated from food consumption during the complementary feeding period was mainly positively associated with allergic and respiratory multimorbidity. In fact, dietary exposure at 8 months to the mixture “F-TE-D-PAH” was associated with respiratory diseases in childhood, while dietary exposure to the mixture “Pest-TE” was associated with allergy without asthma. Dietary exposure to mixtures “PCBs-BFRs” or “PAH-Pest-PCB-Acry” at 8 months, or to the mixture “TE-Pest” at 12 months was associated with allergic and respiratory multimorbidity. Inversely, medium exposure to the mixture “PAH-Pest-PCB-Acry” at 8 months was associated with a lower risk of belonging to the cluster “Asthma only”.

Comparison of these findings with previous literature is challenging on multiple fronts. First, we considered chemicals as mixtures, while most studies considered chemicals individually or as part of the same family. We consider that overall mixtures better reflect the actual exposure than individual exposures or family-based mixtures. Moreover, the present study was based on dietary exposure to chemicals, while most studies used biomarkers of exposure, reflecting aggregation of different sources of exposure (i.e. including indoor and outdoor air pollution, water, contact materials, medication ...). Food chemical content could be subject to regulation rules, that’s why we decided to focus on this way of exposure. Then, we based the comparison with previous literature on main contributing families to the mixtures, whatever the way of exposure. Finally, the majority of the existing literature on childhood exposure to chemicals and allergies focused on school aged children and are mainly cross-sectional studies.

Childhood exposure to PAHs was associated to the onset and the exacerbation of asthma in several studies (Karimi et al., 2015; Wang et al., 2017; Hu et al., 2022). In a cross-sectional study from the
<caption>**Table 4**</caption>

Association between dietary exposure to mixture of chemicals at 12 months and allergic and respiratory multimorbidity clusters between 1 and 8 years (n = 745).

<table><thead><tr><th rowspan="2">Mixtures</th><th colspan="3">OR[95%CI], reference group: asymptomatic</th></tr><tr><th>Allergy without asthma</th><th>Multimorbidity</th><th>Asthma only</th></tr></thead><tbody><tr><td><strong>TE-F-D-PCB</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>0,95 [0,54; 1,64]</td><td>1,01 [0,60; 1,68]</td><td>0,76 [0,49; 1,18]</td></tr><tr><td>High exposure</td><td>1,09 [0,58; 2,05]</td><td>1,15 [0,63; 2,10]</td><td>1,48 [0,93; 2,34]</td></tr><tr><td><strong>PCB-BFR</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>1,35 [0,84; 2,18]</td><td>0,78 [0,49; 1,22]</td><td>0,74 [0,52; 1,06]</td></tr><tr><td><strong>Pest-TE</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>1,22 [0,78; 1,90]</td><td>0,85 [0,55; 1,30]</td><td>0,77 [0,54; 1,11]</td></tr><tr><td><strong>Pest</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>1,42 [0,82; 2,46]</td><td>1,14 [0,68; 1,91]</td><td>0,87 [0,57; 1,33]</td></tr><tr><td>High exposure</td><td>0,86 [0,47; 1,57]</td><td>1,10 [0,65; 1,86]</td><td>1,12 [0,73; 1,70]</td></tr><tr><td><strong>PAH</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>0,71 [0,47; 1,07]</td><td>0,74 [0,51; 1,08]</td><td>0,86 [0,63; 1,16]</td></tr><tr><td><strong>BFR-PAH-TE</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>0,73 [0,39; 1,36]</td><td>1,04 [0,61; 1,78]</td><td>1,19 [0,78; 1,83]</td></tr><tr><td>High exposure</td><td>1,17 [0,65; 2,09]</td><td>1,00 [0,59; 1,69]</td><td>0,95 [0,62; 1,45]</td></tr><tr><td><strong>TE-Pest</strong></td><td></td><td></td><td></td></tr><tr><td>Low exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Medium exposure</td><td>0,86 [0,42; 1,76]</td><td>0,57 [0,27; 1,21]</td><td>1,26 [0,81; 1,97]</td></tr><tr><td>High exposure</td><td>1,09 [0,57; 2,06]</td><td>2,31 [1,34; 3,98]</td><td>0,85 [0,54; 1,33]</td></tr><tr><td><strong>Bisph-TE</strong></td><td></td><td></td><td></td></tr><tr><td>No exposure</td><td>Ref</td><td>Ref</td><td>Ref</td></tr><tr><td>Exposure</td><td>0,89 [0,53; 1,49]</td><td>0,82 [0,52; 1,30]</td><td>1,21 [0,86; 1,71]</td></tr></tbody></table>

Values are odds ratios [95% CI] from a multinomial logistic regression model including the eight mixtures simultaneously. The “asymptomatic” cluster was used as a reference group and adjustment were made for maternal characteristics (age, education level, household income, primiparity, diet quality), child and birth characteristics (sex, family history of allergy, breastfeeding duration and age at complementary feeding introduction) and study center. Abbreviations: TE-F-D-PCB, trace elements-furans-dioxins- polychlorobiphenyls; PCB-BFR, polychlorobiphenyls-brominated flame retardants; Pest-TE, pesticides-trace elements; Pest, pesticides; Bisph-TE, bisphenols-trace elements; PAH, polycyclic aromatic hydrocarbons; BFR-PAH-TE, brominated flame retardants-polycyclic aromatic hydrocarbons-trace elements; TE-Pest, trace elements-pesticides.

Columbia Center for Children's Environmental Health cohort, home exposure to a semivolatile PAH (pyrene), measured by 2 weeks residential monitoring at 5-6 years was positively associated with asthma, but no association was found with the sum of 8 nonvolatile PAHs (Jung et al., 2012). In a second cross sectional study from same cohort, no association was found between urine PAH biomarker and asthma (Miller et al., 2010). In adults, exposure to PAHs was associated with reduced lung function (Alhamdow et al., 2021). In our study, dietary exposure at 8 months to two mixtures including PAHs in their composition showed positive associations with asthma or allergic and respiratory multimorbidity. However, exposure to the mixture composed mainly by PAHs (PAH-Phta and PAH-Pest-PCB-Acry at 8 months and PAHs at 12 months) was not related to allergic and respiratory multimorbidity clusters.

Few studies explored the association between exposure to BFRs or PCBs and respiratory diseases or allergies in children. Most of studies on BFRs focused on exposure through dust, which is the primary source of exposure to BFRs. In a USA birth cohort, including 234 children, home-dust exposure to BFRs in the first year of life was associated with reduced lung function at 5 years (Mendy et al., 2023). In a case control study, including 110 asthmatic children and 110 matched controls, exposure to 21 PBDEs, measure in mothers' mattresses dust 2 months after delivery, was not associated with asthma between 4 and 8 years (Canbaz et al., 2016). In an Irish birth cohort, at 7 years, serum PCBs concentrations were positively associated with IgE concentration (Grandjean et al., 2010). In our study, higher dietary exposure to the mixture composed of BFRs and PCBs at 8 months was associated with higher risk of allergic and respiratory multimorbidity.

In a recent meta-analysis including 24 studies (Rodrigues et al., 2022), exposure to pesticides was associated with higher risk of asthma but not with allergic rhinitis nor with atopic dermatitis in children and adolescents. However, the studies included used different approaches to assess exposure to pesticides such as biomarkers, proximity to agricultural area or air monitoring data. Conversely, in the present study, two mixtures composed mainly of pesticides, were identified from infant diet but were not associated with the “asthma only” nor with asthma and allergic comorbidity clusters. However, we report a positive association between exposure to the mixture composed of pesticides and some trace elements and the risk of allergy without asthma. Contrary to asthma, only few studies focused on the association of pesticides exposure in childhood with allergies (Rodrigues et al., 2022). Moreover, most of previous studies considered only one or few pesticides. Also, most of previous studies examined the cross-sectional associations in preschool and school age children, while we examined the impact of exposure during the first 8 years of life. Overall, associations between environmental exposure to pesticides and asthma or allergies are still unclear and new studies with harmonized protocols are required to allow comparison of the results (Mamane et al., 2015; Buralli et al., 2020).

Several studies explored the association between exposure to trace elements and allergic or respiratory diseases (Wang et al., 2022). In a cross-sectional study in Korea, positive associations were reported between serum concentrations of lead, mercury and cadmium and asthma and allergic multimorbidity defined as the coexistence of at least two allergic diseases (asthma, allergic rhinitis and/or atopic dermatitis) in adults (≥19 years old) (Koh et al., 2019). In the present study, dietary exposure to the mixture composed mainly of trace elements and several pesticides at 12 months was also associated with increased risk of allergic and respiratory multimorbidity.

Some studies reported a positive association between exposure to selected metals such as lead (Wang et al., 2017; Wu et al., 2019), or nickel and copper (Madrigal et al., 2021), and asthma in childhood. Elements chromium, barium, nickel and aluminum represent 18% of the mixture of furans, trace elements, dioxins and PAHs, which was also associated with asthma without allergies in the present study.

In the EDEN mother-child cohort and the ELFE cohort, using similar methods to assess dietary exposure to chemicals during pregnancy, some mixtures were close to those identified in the present study, such as the one composed mainly by furans, trace elements and PAHs (Traore et al., 2018). Prenatal dietary exposure to this mixture was positively associated with the risk of allergic rhinitis up to eight years in the EDEN mother-child cohort (Ghozal et al., 2023), to the risk of eczema in the ELFE cohort (Ghozal et al., 2024) and postnatal dietary exposure to this mixture was positively related to the risk of belonging to the asthma only cluster in the present study. Even if the allergic or respiratory events are different across studies and exposure period, these results highlight the need to further explore the potential influence of early life exposure to this mixture on allergic and respiratory health.

The underlying mechanisms involved in the association between children exposure to environmental chemicals and allergic diseases are still not well known. Alteration of the immune system development and
maturation during the early life period has been reported with exposure to environmental chemicals (García-Serna et al., 2021). Epigenetic regulation mechanisms such as activation of the aryl hydrocarbon receptor (AhR) transcription factor by chemicals such as PAHs or PCBs was associated with a proinflammatory reaction involved in asthma exacerbation (Hansen et al., 2016; Poulain-Godefroy et al., 2020). Oxidative stress induction is another mechanistic pathway possibly involved in the association between exposure to environmental chemicals, such as metals, and the pathogenesis of asthma or allergy (Huang et al., 2015). Environmental chemicals are also associated with disruption of the microbiome and the epithelial barriers, that are implicated in the development of multiple allergic conditions (Celebi Sozener et al., 2022).

In the present study, we have to acknowledge that findings were quite different for 8-month dietary exposure than for 12-month dietary exposure. Diet strongly evolved from 8 to 12 months and these changes may impact the infant's dietary exposure to chemicals. In fact, compared to 8-month diet, 12-month diet is characterized by decreased intake of infant formula and commercial baby foods intake but increased intake of foods not specially designed for infants. Even if some mixture could appear similar at 8 and 12 months, significant differences were observed between these mixtures.

This is the first study to explore the links between infant dietary exposure to chemical mixtures and allergic and respiratory health in childhood. The large set of variables collected and the prospective design enable to account for the main potential confusion factors, even if residual confounding may not be excluded. While the existing literature focused on biomarkers of exposure to chemicals, we focused here on dietary exposure to chemicals, as diet is an important source of exposure to the majority of environmental chemicals in childhood (Papadopoulou et al., 2019). However, it would be of interest to conduct studies focusing on other sources of exposure to chemicals. Moreover, whereas the majority of previous studies focused on exposure in preschool and school aged children, the present study focused on infancy. Considering the immaturity of the infant's immune system during the early postnatal period, this period is potentially part of a critical window of the immune system vulnerability to environmental chemicals (Cao et al., 2016).

Dietary exposure to chemicals was evaluated by combining infant's dietary intake based on three 24-h dietary records with chemicals concentrations in food stuff. This approach offers the unique opportunity to examine this particular way of exposure and potentially to improve certain guidelines, if relevant. However, it might suffer some uncertainties (ANSES, 2016). NMF methods suffers from some limitations such as instability (Benlamine et al., 2022) or selection of the optimal k rank value (Cai et al., 2023). Nonetheless, SNMU is particularly adapted to dietary exposure data composed of positive values with excess zeros values (Béchaux et al., 2013). Moreover, dietary records have the advantage of not relying on individual memory and thus to limit this bias (Gurinović et al., 2017). Unfortunately, infants' dietary exposure to chemicals through breast milk was not assessed in this study as breast milk quantity was not estimated in the 3-day food records. Future studies should consider the part of breastfeeding in dietary exposure to chemicals at this age.

Allergic and respiratory outcomes were reported by parents, but to limit classification bias, the internationally validated ISAAC questionnaire was used (Asher et al., 1995). Moreover, in this study, allergic and respiratory multimorbidity clusters were identified and analyzed, to consider the cooccurrence of allergic and respiratory diseases in childhood.

## 5. Conclusion

In this study on early postnatal dietary exposure to mixtures of chemicals and allergic multimorbidity in childhood, two mixtures, mainly composed of PCBs and BFRs or of trace elements, and pesticides, were associated with the increased risk of allergic and respiratory

multimorbidity. Two other mixtures composed of furans, trace elements, dioxins and PAHs or pesticides and trace elements were positively associated with only asthma or only allergies, respectively. Inversely, exposure at 8 months to a mixture composed of PAHs, pesticides, PCBs and acrylamide was associated with a lower risk of asthma without allergy. These associations were transient and other studies are needed to better understand the impacts of early dietary exposure to chemicals on children health.

## CRediT authorship contribution statement

**Manel Ghozal:** Writing – original draft, Software, Methodology, Formal analysis, Conceptualization. **Rosalie Delvert:** Writing – review & editing, Methodology. **Karine Adel-Patient:** Writing – review & editing, Conceptualization. **Muriel Tafflet:** Writing – review & editing, Software. **Isabella Annesi-Maesano:** Writing – review & editing, Investigation. **Amélie Crépet:** Writing – review & editing, Resources. **Véronique Sirot:** Writing – review & editing, Resources. **Marie Aline Charles:** Writing – review & editing, Investigation. **Barbara Heude:** Writing – review & editing, Investigation. **Manik Kadawathagedara:** Writing – review & editing. **Blandine de Lauzon-Guillain:** Writing – review & editing, Supervision, Methodology, Conceptualization.

## Funding

This study was supported by the Fondation pour la Recherche Médicale (FRM, grant no.: ENV202109013943) and French National Research Institute for Agriculture, Food and Environment (INRAE) including the metaprogram METABIO. The prenatal exposure to food chemicals was estimated within the COCTELL project, supported by the French Agence Nationale de la Recherche (ANR) (grant no.: ANR-14-CE21-0002-02).

The EDEN study is supported by the FRM, French Ministry of Research: Federative Research Institutes and Cohort Program, INSERM Human Nutrition National Research Program, and Diabetes National Research Program (by a collaboration with the French Association of Diabetic Patients [AFD]), French Ministry of Health, French Agency for Environment Security (AFSSET), French National Institute for Population Health Surveillance (InVS), Paris-Sud University, French National Institute for Health Education (INPES), Nestlé, Mutuelle Générale de l'Education Nationale (MGEN), French-speaking Association for the Study of Diabetes and Metabolism (ALFEDIAM), National Agency for Research (ANR non-thematic programme), and National Institute for Research in Public Health (IRESP: TGIR, 2008 cohort in health programme).

## Declaration of competing interest

The authors 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

The authors thank the EDEN mother-child cohort study group, whose members are I. Annesi-Maesano, J.Y. Bernard, M.A. Charles, P. Dargent-Molina, B. de Lauzon-Guillain, P. Ducimetière, M. de Agostini, B. Foliguet, A. Forhan, X. Fritel, A. Germa, V. Goua, R. Hankard, B. Heude, M. Kaminski, B. Larroque, N. Lelong, J. Lepeule, G. Magnin, L. Marchand, C. Nabet, F. Pierre, R. Slama, M.J. Saurel-Cubizolles, M. Schweitzer, and O. Thiebaugeorges.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fct.2024.115167.
# Data availability

The authors do not have permission to share data.

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