Associations between food contaminants exposure and pubertal development at 10 and 13 years old

Associations between food contaminants exposure and pubertal development at 10 and 13 years old | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Associations between food contaminants exposure and pubertal development at 10 and 13 years old Sofia Almeida Costa, Milton Severo, Catarina Campos Silva, Carla Lopes, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6311918/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Endocrine-disrupting compounds, such as acrylamide(AA) and bisphenol A(BPA), are external substances usually found food that may influence pubertal development. This study aims to assess the association of food contaminants exposure (AA and BPA), individually and combined, on pubertal development in children and adolescents aged 4-13. Data from four waves of Portuguese population-based birth cohort Generation XXI was used(n=5279). Dietary information was gathered through food diaries. AA exposure was estimated combining food intake with EFSA occurrence data, while BPA exposure was predicted using a random forest model. Linear regression models tested the association food contaminants exposure-pubertal development. A significant negative association was found in girls between individual AA exposure at 7-years(-0.007(95%CI:-0.013,-0.002)), 10-years(-0.006(95%CI:-0.010,-0.003)) and 13-years(-0.005(95%CI:-0.009,-0.001)). In boys, a significant positive association was found between BPA exposure at 10 and 13-years, and AA exposure at 13-years(0.003(95%CI:0.000,0.007)). The combined exposure did not significantly change the results observed for individual exposure to each food contaminant. Health sciences/Endocrinology/Endocrine system and metabolic diseases Health sciences/Risk factors Health sciences/Diseases/Endocrine system and metabolic diseases Health sciences/Diseases/Endocrine system and metabolic diseases/Endocrine reproductive disorders Health sciences/Health care/Nutrition cohort acrylamide bisphenol A children adolescents Tanner Introduction Puberty represents a dynamic transition from childhood to adulthood, with significant physical changes leading to reproductive maturity. However, the timing of pubertal onset and the speed of its progression vary greatly among individuals and may be influenced by external factors 1 . In recent years, the development of different endocrine abnormalities due to exposure to endocrine-disrupting compounds (EDC) from the environment has been well described 2 . EDC are external substances usually found in air, water, food, and other consumer products, and they are one of the factors that may influence puberty timing 3 , 4 . These compounds may directly interfere with estrogenic or androgenic signalling pathways and consequently with the hypothalamic-pituitary-gonadal axis or indirectly with peripheral organs, such as adipose tissue and adrenal glands 5 . Considering that the correct function of the endocrine system is essential for the control, development and maturation of the different tissues and organs, EDC exposure in critical time windows can significantly impair short- and long-term health outcomes 4 . Prenatal period, namely the embryo-fetal time, and postnatal period, childhood and adolescence, are the most susceptible to disruptions 1 , 4 . Acrylamide (AA) is a compound primarily formed via the Maillard reaction when the amino acid asparagine reacts with reducing sugar under low-moisture conditions at temperatures exceeding 120ºC. It is commonly found in baked or fried carbohydrate-rich foods, tobacco smoke, and other industrial applications 4 , 6 , 7 . For the general population, particularly children and adolescents, diet represents the primary source of AA exposure 8 . Major dietary contributors include cereal products (such as bread, toast, breakfast cereals, biscuits, and snacks), potato-based foods (including chips, French fries, and crisps), coffee and coffee substitutes 8 , 9 . AA was classified as “probably carcinogenic” by the International Agency for Research on Cancer in 1994 10 . Moreover, recently, AA was also considered a potential EDC 4 , 11 , corroborated by animal studies which found an association with reproductive toxicity, including ovarian dysfunction, disrupted spermatogenesis and infertility 4 . However, epidemiological studies in humans, particularly testing the association between AA exposure at younger ages and pubertal development, are limited and inconclusive. Bisphenol A (BPA) is a monomer used to produce polycarbonate plastics and epoxy resins. Polycarbonate plastics are commonly applied to food contact materials, such as reusable beverage bottles, tableware, cookware, and food containers. Epoxy resins are often used in protective linings of food and beverage cans 12 , 13 . Additionally, BPA is utilised in different non-food-related products, including toys, medical devices, thermal paper, electronic products, and flame retardants 14 . Diet is considered the main source of BPA exposure in humans, with canned foods and beverages being the most relevant contributors 15 , 16 . This food contaminant was considered EDC, and considering both the estrogenic and anti-androgenic effects after exposure may impair the reproductive system and pubertal regulation 17 , 18 . Despite that, previous studies testing pre- and post-natal BPA exposure and consequences on pubertal development have shown controversial results, leaving the conclusions of this association unclear. Different possible explanations for the inconclusive results found in the previously published studies regarding EDC and pubertal development may be related to the type of EDC, duration of exposure, type of outcomes and age at exposure/ outcome evaluation 19 . Furthermore, most of the studies have been focused on assessing the effect of individual compounds, with a narrow perspective considering the complexity of the diet and the real-world scenario of food contaminants exposure. Thus, this study aims to assess the association of food contaminants exposure, namely acrylamide and bisphenol A, individually and combined, on pubertal development in children and adolescents aged 4 to 13. Results Sociodemographic characteristics between eligible participants and the remaining cohort at baseline were similar (supplemental material, Table S1 ). Of the included participants, 51.3% were male, and 48.7% were female. Statistical differences were only found for maternal characteristics. Regarding the general characteristics of the eligible participants (Table 1 ), no significant differences were found between girls and boys for maternal age and maternal education. However, some significant differences were found in the other variables. As expected, compared to girls, boys presented a higher level of physical activity, higher total energy intake, and higher z-BMI. Regarding the daily dietary exposure to AA and BPA at 4-, 7-, 10- and 13- years old, the median dietary exposure is higher in boys for both AA and BPA, decreasing with age in both sexes. Table 1 General characteristics of the eligible participants, stratified by sex. Girls (n = 2572) Boys (n = 2707) p-value Maternal age (years) , mean (SD) 30.0 (6.3) 29.7 (6.2) 0.108 Maternal education (years) , mean (SD) 11.1 (4.3) 11.2 (4.3) 0.407 Physical Activity a , n (%) 4 years old 1788 (70.7) 1797 (67.9) 0.078 7 years old 1660 (71.6) 1691 (68.8) 0.101 10 years old 1415 (59.2) 1720 (68.1) < 0.001 13 years old 989 (51.2) 1362 (67.1) < 0.001 Total Energy Intake (kcal) , mean (SD) 4 years old 1562 (280.8) 1641 (301.6) < 0.001 7 years old 1711 (293.6) 1812 (313.4) < 0.001 10 years old 1855 (364.3) 1947 (396.1) < 0.001 13 years old 1759 (405.3) 1923 (445.9) < 0.001 z-BMI , mean (SD) 4 years old 0.62 (1.10) 0.56 (1.06) 0.061 7 years old 0.71 (1.14) 0.70 (1.22) 0.728 10 years old 0.63 (1.21) 0.74 (1.25) 0.002 13 years old 0.47 (1.13) 0.41 (1.22) 0.076 Acrylamide, µg/kg bw/day , median (P25-P75) 4 years old 0.76 (0.50, 1.11) 0.83 (0.56, 1,23) < 0.001 7 years old 0.63 (0.42, 0.89) 0.67 (0.45, 0.94) < 0.001 10 years old 0.58 (0.39, 0.85) 0.62 (0.41, 0.90) 0.002 13 years old 0.41 (0.27, 0.60) 0.46 (0.30, 0.66) < 0.001 Bisphenol A, ng/kg bw/day , median (P25-P75) 4 years old 69.3 (60.7, 79.0) 68.5 (61.1, 76.0) 0.03 7 years old 50.2 (42.6, 57.8) 50.1 (43.8, 57.1) 0.81 10 years old 35.7 (29.7, 41.9) 36.8 (30.5, 42.4) 0.006 13 years old 24.4 (20.8, 28.4) 25.1 (21.0, 29.6) 0.002 Abbreviations: n – sample size, % – percentage, SD – standard deviation, kcal – kilocalories, z-BMI – body mass index z-score, µg – microgram, ng – nanogram, kg – kilogram, bw – body weight, P25–25th percentile, P75–75th percentile. Notes: a) Practice of leisure physical activity outside the school setting. p-values from the chi-square test, Student's t-test or Mann–Whitney U test, as appropriate. Significant values are in bold . Table 2 presents the pubertal development of participants according to the Tanner scale at 10 and 13 years. The estimated percentage of participants in stage 1 of breast or genital rating was 26.6% in girls and 73.4% in boys at 10 years, while at 13 years, these percentages reduced, as expected, to 1.6% and 1.2%, respectively. At 13 years of age, 55.6% of the girls and 61.7% of the boys have reached stage 4 or 5 for the breast or genital rating. Despite that, regarding pubic hair, 61.2% of the girls and 31.4% of the boys have reached stage 4 or 5. Table 2 Pubertal development of participants at 10- and 13-years old, stratified by sex. Girls Boys n % n % Pubic hair, 10 years Stage 1 984 45.8 1925 85.3 Stage 2 689 32.0 278 12.3 Stage 3 394 18.3 44 2.0 Stage 4 80 3.7 8 0.4 Stage 5 3 0.1 1 0.0 Breast or genital rating a , 10 years Stage 1 574 26.6 1658 73.4 Stage 2 986 45.8 547 24.2 Stage 3 501 23.3 45 2.0 Stage 4 93 4.3 8 0.4 Stage 5 0 0.0 1 0.0 Axillary hair, 13 years Stage 1 111 22.6 746 39.0 Stage 2 170 34.6 528 27.6 Stage 3 128 26.0 406 21.2 Stage 4 69 14.0 195 10.2 Stage 5 14 2.8 37 1.9 Pubic hair, 13 years Stage 1 9 0.5 261 13.3 Stage 2 99 5.9 489 25.0 Stage 3 543 32.3 592 30.3 Stage 4 857 51.0 513 26.2 Stage 5 172 10.2 102 5.2 Breast or genital rating a , 13 years Stage 1 32 1.6 25 1.2 Stage 2 209 10.7 262 13.1 Stage 3 706 36.2 481 24.0 Stage 4 850 43.6 715 35.7 Stage 5 152 7.8 521 26.0 Abbreviations: n – sample size, % – percentage. Notes: a) Breast rating for girls or genital rating for boys. Table 3 presents the linear regression models to test the association between food contaminants exposure, individually and combined, with the global score of pubertal development. After adjusting for the participant’s exact age, maternal age, maternal education, the practice of leisure physical activity and total energy intake (model 2), a significant negative association was found between individual AA exposure at 7 years (-0.007 (95% CI: -0.013, -0.002)), 10 years (-0.006 (95% CI: -0.010, -0.003)) and 13 years (-0.005 (95% CI: -0.009, -0.001)) and a higher pubertal development global score in girls. On the contrary, there was a significant positive association for individual AA exposure at 13 years (0.003 (95% CI: 0.000, 0.007)) in boys. Regarding individual BPA exposure, a significant positive association with a higher pubertal development global score was found only in boys for exposures at 10 and 13 years of age. Testing the combined exposure in the model did not significantly change the results observed for the individual exposure to each food contaminant, except for the AA association in boys that lost its significance. Table 3 Association between acrylamide (µg/day) and bisphenol A (ng/day) exposure and the global score of pubertal development applying linear regression models, stratified by sex (β and 95% confidence interval (CI)). Girls Boys Model 1 Model 2 Model 1 Model 2 β (95% CI) β (95% CI) β (95% CI) β (95% CI) AA 4 years old 0.001 (-0.005, 0.007) -0.001 (-0.008, 0.005) 0.006 (0.000, 0.012) 0.002 (-0.004, 0.008) 7 years old -0.004 (-0.009, 0.001) -0.007 (-0.013, -0.002) 0.003 (-0.001, 0.008) 0.001 (-0.004, 0.007) 10 years old -0.005 (-0.008, -0.001) -0.006 (-0.010, -0.003) 0.000 (-0.003, 0.004) 0.000 (-0.004, 0.004) 13 years old -0.005 (-0.008, -0.001) -0.005 (-0.009, -0.001) 0.004 (0.001, 0.007) 0.003 (0.000, 0.007) BPA 4 years old 0.02 (-0.48, 0.52) 0.02 (-0.48, 0.52) 0.35 (-0.18, 0.88) 0.33 (-0.19, 0.86) 7 years old -0.16 (-0.59, 0.27) -0.15 (-0.58, 0.28) 0.13 (-0.31, 0.57) 0.17 (-0.26, 0.61) 10 years old -0.07 (-0.45, 0.31) -0.07 (-0.45, 0.31) 0.46 (0.03, 0.88) 0.46 (0.04, 0.88) 13 years old -0.12 (-0.46, 0.22) -0.13 (-0.47, 0.21) 0.47 (0.14, 0.81) 0.49 (0.15, 0.82) AA + BPA 4 years old, AA 0.000 (-0.005, 0.005) -0.001 (-0.007, 0.004) 0.005 (-0.001, 0.010) 0.002 (-0.004, 0.008) 4 years old, BPA 0.02 (-0.48, 0.52) 0.03 (-0.48, 0.53) 0.33 (-0.20, 0.86) 0.33 (-0.20, 0.86) 7 years old, AA -0.004 (-0.009, 0.001) -0.007 (-0.013, -0.002) 0.003 (-0.001, 0.008) 0.001 (-0.004, 0.006) 7 years old, BPA -0.15 (-0.58, 0.28) -0.13 (-0.56, 0.30) 0.11 (-0.33, 0.55) 0.16 (-0.28, 0.60) 10 years old, AA -0.004 (-0.007, -0.001) -0.005 (-0.009, -0.002) 0.000 (-0.004, 0.003) 0.000 (-0.004, 0.003) 10 years old, BPA -0.08 (-0.46, 0.30) -0.07 (-0.45, 0.31) 0.46 (0.03, 0.88) 0.46 (0.04, 0.88) 13 years old, AA -0.004 (-0.008, -0.001) -0.004 (-0.008, 0.000) 0.003 (0.000, 0.006) 0.002 (-0.001, 0.006) 13 years old, BPA -0.13 (-0.47, 0.21) -0.13 (-0.47, 0.21) 0.47 (0.13, 0.81) 0.48 (0.14, 0.82) Abbreviations: β – regression coefficient, 95% CI – 95% confidence interval, AA – acrylamide; BPA – bisphenol A. Model 1: adjusted for participant’s exact age (at 10-year follow-up for girls and at 13-year follow-up for boys), maternal age, maternal education, and cross-sectional practice of leisure physical activity. Model 2: adjusted for model 1 plus cross-sectional total energy intake (kcal). Significant values are in bold . Discussion Considering data from a population-based birth cohort, the present study found an adverse effect of food contaminants exposure, namely acrylamide and bisphenol A, on pubertal development. In girls, higher exposure to AA at 7, 10 and 13 years of age was inversely associated with pubertal development at 10 and 13 years. In boys, higher exposure to AA at 13 years and higher exposure to BPA at 10 and 13 years of age was positively associated with precious pubertal development. The combined effect of these food contaminants was also tested, and the results remained the same, except for the effect of AA among boys, which lost its significance. To the best of our knowledge, this is the first study assessing the association between food contaminants exposure, estimated through collected dietary information, and pubertal development, measured through the Tanner scale. Moreover, this study followed a prospective and cross-sectional epidemiological design to the extent that the exposure was measured before or at the same time as the outcome was assessed. In this work, we only found one significant negative longitudinal association between higher exposure to AA at 7 years and later pubertal development in girls. According to studies performed in animal models, it was plausible that AA and BPA exposure causes later puberty by disrupting the hypothalamic-pituitary-gonadal axis, reducing sex hormone concentrations in both female and male animals 20 , 21 . On the other hand, BPA also has estrogen-mimicking properties, which may trigger early puberty in both sexes 21 . The previous epidemiological evidence on the association between AA and BPA dietary exposure and impaired pubertal development in humans is limited and contradictory. The comparison of the present findings with other studies is also difficult, considering the methodological differences across them. First, most previous studies estimated the exposure in spot urine or blood samples. From what we know, only one study performed in preschool-age Japanese children in 2006 estimated dietary acrylamide exposure using 3-day diet records 22 . Second, the moment of exposure assessment differs, which sometimes reflects the pre-natal exposure and other times reflects the post-natal exposure, especially for BPA-tested associations. Third, different methodologies to assess pubertal development were used across studies, i.e., using other scales rather than the Tanner scale, the interpretation of one single parameter or an overall pubertal development score, and measuring sex hormones in the blood to determine the pubertal stage. Fourth, the cross-sectional design of most studies and the small sample size. Fifth, the variability of the chosen potential confounders also differs, especially concerning BMI and total energy intake. Given the conceptual framework of this study and the potential role of AA and BPA as an endocrine disruptor, our final model was adjusted for sociodemographic characteristics, lifestyle factors, and total energy intake. Since participants' BMI could mediate the observed association, any adjustment or stratification to the model for this variable would be inappropriate. Regarding AA, in line with our results, in a study involving 230 boys and 198 girls aged 3–6 years, a positive association between dietary AA exposure and higher sex hormone levels was found exclusively in boys 22 . A cross-sectional study using data from individuals aged 6–19 years of NHANES 2013–2016 found a negative correlation between blood acrylamide and glycidamide biomarkers and sex hormone levels in girls 20 . However, contrary to our findings, these authors also found a significant negative association among boys 20 . Another recent Japanese study among adolescents aged 13–14 years found that AA measured in urine was associated with lower testosterone levels and a delayed puberty stage in males 23 . Finally, other authors did not find significant associations between blood acrylamide and glycidamide biomarkers and sex hormones using cross-sectional data from NHANES 2003–2004 of participants older than 12 years 24 . Nevertheless, all these studies adjusted their models to BMI, among other potential confounders, which may conditionate the interpretation and the comparison of the results. For BPA cross-sectional 25 – 27 and longitudinal 28 – 30 studies did not find an association between urinary BPA and abnormalities in pubertal development in girls, which is in line with our results. In another cross-sectional study from the United Kingdom, although concentrations of urinary BPA have shown a positive association with the onset of thelarche, the authors failed to find a statistical significance for the hazard ratio 31 . One South Korean study found that prenatal exposure to BPA was associated with early puberty but did not find a significant result considering childhood exposure 19 . Additionally, a systematic review with meta-analysis, including only studies performed with female participants, found no significant association between BPA exposure and pubertal development 17 . Among boys, aligned with the findings of this paper, a cross-sectional study performed among Chinese boys aged 9–18 found a significant positive association between urinary BPA and early pubertal onset 32 . Still, contradictory to our results, some authors found positive associations with statistical significance between BPA exposure and precocious puberty in girls 33 – 35 . In boys, several studies failed to find a significant association 34 , 36 . In one cohort study, including 250 Mexican boys, prenatal BPA exposure was associated with reduced odds of adrenarche and puberty. Still, no clear association was found between childhood BPA exposure and pubertal onset 37 . There are some possible explanations for these differences. As observed for AA studies, most of the previously published results were adjusted for BMI, making direct comparison difficult, as the effect of food contaminants exposure on pubertal development may not be accurately measured in the adjusted model. Furthermore, the dual functionality of BPA, acting as an agonist or antagonist in the causal pathway, may explain the contradictory results of the BPA effect on early or later pubertal development. It is also important to highlight that spot or first-morning urines may not correctly represent exposure to food contaminants, especially for those with relatively short half-lives, such as AA and BPA. In fact, the half-live ranges between 5–8 hours for AA 38 and approximately 6 hours for BPA body 39 . Furthermore, the intra-individual variability and the inconstant concentration of food contaminants in urine throughout the day may not be captured with a single sample collection 36 , 40 . Only two cited studies assessed the effect of childhood combined exposures (phthalates and phenols) 19 , 41 . They failed to find a significant association with impaired pubertal development in girls and boys. Our findings revealed that significant associations of AA and BPA exposure (cross-sectionally and longitudinally) with abnormalities in the timing of puberty onset remained significant when combined exposure to these food contaminants was tested. This represents an important input to fill the gap in knowledge since it provides a more realistic perspective from real-world exposure. Lastly, the interpretation of a single pubertal parameter appears limited, considering the different velocities of pubic hair versus breast/genital rating in girls and boys 42 , 43 . Additionally, we cannot discard some misclassification in our sample, especially in boys. Puberty typically begins in boys about two years later than in girls, and many boys aged 10 to 13 are still prepubescent 43 . However, boys in our cohort appear to experience a relatively rapid pace of pubertal development, progressing in genital stages compared to pubic hair within this age range. This justified the use of GRM to compute a global score of pubertal development, including the most relevant and discriminating parameters. We concluded from the reliability analysis (Table S2) that the high missing rate for axillary hair might indicate issues with this variable, conditioning its relevance to the model. Therefore, axillary hair was not included in the calculated global score of pubertal development. Our analyses have some limitations that must be addressed. First, the sociodemographic characteristics of the eligible participants may suggest a potential presence of participation bias. However, given that statistically significant results were found in our sample for maternal characteristics, we hypothesise that the effects observed in the general population would be even more pronounced. Second, a possible misclassification of the pubertal stage, especially in boys, was detected. We try to overcome this limitation by computing a global score of pubertal development using a graded response model, as explained above. Third, we opted for a linear regression model since our outcome variables did not allow us to apply a mathematical longitudinal model (only two outcome observations). However, since the exposure was measured before the outcome, we were able to interpret the results longitudinally from an epidemiologic perspective. Nonetheless, this study had several strengths. First, the use of a prospective population-based birth cohort with extensive data collection on sociodemographic characteristics, food consumption, and anthropometric and pubertal measurements. Second, the study includes a large sample size of eligible participants, enhancing its statistical power. Third, a large comprehensive database with dietary information was used to estimate exposure to food contaminants. Fourth, the AA exposure assessment accounted for inter-individual and intra-individual variability. Fifth, the availability of 24-hour urine samples for a sub-sample of the GXXI cohort enabled a more accurate estimation of total daily BPA exposure. In fact, when combined with dietary data, this information allowed the construction of a random forest model, an approach rarely employed in previous research. Finally, the development of a global score of pubertal development, which integrated the different Tanner parameters, and enabled a more accurate interpretation of results by reducing errors of classification. In the past years, concerns regarding the potential effect of EDC exposure on adverse health outcomes related to puberty development have been raised 1 , 4 , 44 . There is a plausible causal relation between the dysregulation of the sexual hormone system caused by dietary exposure to EDC, such as acrylamide and BPA, responsible for the increased adverse health outcomes and burden of diseases in future life stages. The findings of the present study highlight the importance of reducing daily exposure to both acrylamide and BPA in children and adolescents, as chronic intake was associated with adverse health effects, namely impaired puberty onset. We hope this knowledge will support public health researchers, food safety authorities, and policymakers to design updated guidelines, recommendations, and food policies to mitigate these risks. In conclusion, childhood and adolescent exposure to acrylamide and bisphenol A was associated with impaired timing of puberty onset. Higher exposure to acrylamide at 7, 10 and 13 years of age was negatively associated with pubertal development at 10 and 13 years in girls. A higher exposure to acrylamide at 13 years and a higher exposure to bisphenol A at 10 and 13 years were positively associated with precious pubertal development in boys. The combined exposure effect of acrylamide and bisphenol A did not significantly change the found associations. Further studies applying longitudinal models are needed to assess the exposure effects of these food contaminants on pubertal development and reduce the uncertainties surrounding these associations. Methods Study design and participants This study utilised data from Generation XXI (GXXI), an ongoing prospective population-based birth cohort established between April 2005-August 2006, across five public healthcare units providing obstetrical and neonatal care in the metropolitan area of Porto, Portugal, as previously described 45 . Recruitment was based on the following eligibility criteria: mothers residing in one of the six municipalities within the metropolitan area of Porto, delivering at the public hospitals serving these municipalities, and giving birth to live infants with a gestational age of at least 24 weeks. Between 24-72 hours post-delivery, mothers were invited to join the GXXI cohort, with a participation rate of 91%, resulting in the enrolment of 8,495 mothers and 8,647 children. Participants were subsequently invited for follow-up assessments at 4, 7, 10, and 13 years of age, with participation rates of 86%, 80%, 76%, and 54%, respectively. The lower participation rate of the last follow-up was attributed to the COVID-19 pandemic, which prematurely interrupted data collection in March 2020. This study analysed data from all follow-up evaluations. The eligibility criteria for inclusion were having at least one completed food diary, i.e. at least two reported days within each follow-up, and having performed a sexual development evaluation at 10 and/or at 13 years old. Our final sample included 5279 participants. Sociodemographic characteristics and lifestyle factors Sociodemographic characteristics were collected from the participants and mothers using standardised questionaries. Maternal age at baseline and maternal educational level (defined as the number of completed schooling years) were the variables considered and collected at baseline. The child’s sex was collected at baseline, and the exact age of the child was calculated based on the date on which the pubertal development assessment was conducted. Regarding lifestyle factors, physical activity was considered a potential confounding variable in the association between exposure to food contaminants and pubertal development impairment. Thus, the practice (yes/no) of leisure physical activity outside the school was used at 4-, 7-, 10-, and 13-year follow-ups. Dietary intake and exposure to food contaminants Before the face-to-face interview, parents (or primary caregivers) at the 4-, 7-, and 10-year follow-ups, as well as adolescents at the 13-year follow-up, were instructed by the research team, both orally and in writing, to complete a 3-day food diary, including two weekdays and one weekend day. Detailed information was collected for each food or beverage consumed, such as the time and place of consumption, brand, preparation method, cooking process, and quantity consumed. During the face-to-face interviews, trained researchers reviewed the food diaries. Trained nutritionists coded data from the 4-, 7-, and 10-year follow-ups using Food Processor SQL software 46 and processed data from the 13-year follow-up with the "eAT24" software. Dietary data from the 4- to 10-year follow-ups were harmonised in the "eAT24" software to ensure consistency. This software, developed for the Portuguese National Food, Nutrition, and Physical Activity Survey 2015-2016, integrates the Portuguese Food Composition Table and uses the FoodEx2 classification system, as previously described 47,48 . Finally, all food items and beverages were converted into energy and nutrients, and the individual mean daily intake was computed. Participants were eligible for inclusion in the present study only if their food diaries included data for at least two complete days in any follow-up evaluation. The daily dietary exposure to AA (µg/kg of body weight/day) was then calculated following previously described methods 9 . Data on AA levels in various food groups were obtained from the EFSA Scientific Opinion on Acrylamide in Food, published in 2015 8 . Ten cycles of random assignments were conducted, producing ten distinct estimated AA values for each consumption occasion. A random forest model was used to estimate the daily exposure to BPA, as described elsewhere 49 . This methodology combined information on food group consumption, food packing material, and the total urinary concentration of BPA measured in 24-h urine of a sub-sample. A 2-times 5-fold cross-validation was applied to handle the possible overfitting of the model. The random forest was then applied to predict the total BPA daily exposure in the remaining sample and the remaining follow-up waves. Anthropometrics measurements Trained observers performed a physical examination and anthropometric measures at the 4-, 7‐, 10‐ and 13‐year‐old follow‐up evaluations. Height and weight were measured objectively during face-to-face interviews following standard procedures. Measurements were taken after a 12-hour fasting period, with participants dressed in light clothing and barefoot 50 . Height was recorded to the nearest centimetre using a wall stadiometer (SECA, Hamburg, Germany), while body weight was measured to the nearest tenth of a kilogram using a digital scale (SECA, Columbia, USA). Body mass index (BMI) was calculated as weight divided by height squared, and participants were classified based on age- and sex-specific BMI z-scores (z-BMI) provided by the World Health Organization 51 . Pubertal development Pubertal development was assessed at ages 10 and 13 using the Tanner scale, a standardized method for evaluating sexual maturation 42,43 . The scale encompasses different parameters, namely breast development in girls, genital development in boys and pubic hair development in both sexes. At 13 years old, axillary hair was evaluated for both sexes. The evaluation was conducted by trained professionals who received training from a single endocrinologist. Breast development in girls was assessed through visual inspection and palpation, while testicular volume was measured to evaluate genital development in boys using the Prader orchidometer. Each parameter was classified into five stages: 1 – prepubertal; 2, 3, and 4 – pubertal; and 5 – postpubertal. When discrepancies arose between breast or testicular development and pubic hair staging, the former was prioritised. Ethics approval and consent to participate All study phases complied with the Ethical Principles for Medical Research Involving Human Subjects expressed in the Declaration of Helsinki 52 . The baseline and follow-up evaluations were approved by the University of Porto Medical School/ S. João Hospital Centre Ethics Committee, except the 13-year follow-up approved by the ISPUP Ethics Committee. At baseline and follow-up evaluations, all procedures were explained to participants, and informed consent was signed by one of the parents or legal guardians (at 13 years, it was also signed by the participants). The Data Protection National Commission additionally approved the baseline evaluation. The study follows the present EU General Data Protection Regulation under close supervision of the Data Protection Office of ISPUP. Statistical analysis Proportions were compared using the chi-square test, mean using the Student’s t-test and median using the Mann-Whitney U test. The analyses were stratified by sex. A global score of pubertal development at 10 and 13 years old was created using graded response models (GRM), which enables handling ordered polytomous variables 53 . This model assumes that item discrimination is not equal across all items and that differences between each response category are not the same across all items. The present study used GRM to compute a global score of pubertal development, including items of pubic hair and breast/genital development, evaluated at 10 and 13 years old (supplemental material, Figure S1 and Table S3). The association between the global score of pubertal development and the participant’s exact age at 10- and 13-year follow-up was evaluated using the linear regression model. According to the strongest coefficient found, the exact age at 10-year follow-up in girls and the exact age at 13-year follow-up in boys were the variables that explained better the differences in the global score of puberty. A linear regression model was used to test the associations between exposure to food contaminants, individually and combined, and pubertal development. Both cross-sectional and longitudinal practice of leisure physical activity and total energy intake were pointed as potential confounding variables and tested. Only the cross-sectional variables remained statistically significant, being those included in the final model. Thus, two models are presented in this paper. Model 1 was adjusted for the exact participants’ age, maternal age, maternal education, and cross-sectional practice of leisure physical activity. Model 2 was adjusted for model 1 plus cross-sectional total energy intake (kcal). Moreover, the analysis was performed separately for each of the 10 different estimated values of AA and then combined using Rubin’s rules 54 . All statistical analyses were performed with a 5% significance level, and missing data were treated at random. The R software version 4.2.1 for Windows was used. Declarations Data availability The data from Generation XXI are not publicly available due to privacy or ethical restrictions. The data can be made available for research proposals to the Generation XXI Executive Committee ( [email protected] ) upon request. Further information about Generation XXI can be obtained via the Generation XXI website [www.geracao21.com] or by emailing [email protected] . Acknowledgements We gratefully acknowledge the families enrolled in Generation XXI for their kindness, the participating hospitals and their staff for their help and support, and all previous and current members of the research and field team for their enthusiasm and perseverance. G21 was funded by Programa Operacional de Saúde – Saúde XXI, Quadro Comunitário de Apoio III and Administração Regional de Saúde Norte (Regional Department of Ministry of Health). This particular study was supported through FEDER from the Operational Programme Factors of Competitiveness – COMPETE and through national funding from the Foundation for Science and Technology – FCT (Portuguese Ministry of Education and Science) under the project “FOCAcCIa: Exposure to food additives and contaminants from food processing and packaging: Defining patterns and their effects on adiposity and cognitive function from childhood to adolescence” (POCI-01-0145-FEDER-031949); and the FCT doctoral grant (DOI 10.54499/UI/BD/150785/2020) (SAC). The funding institutions had no role in this article's design, analysis or writing. Contribute of authors SAC, CL and DT contributed to the design and implementation of the research. MS, CCS and SAC to the analysis of the results. SAC wrote the original draft manuscript. SAC, MS, CCS, CL and DT reviewed the manuscript. Competing interest The authors have no competing interests to declare. References Uldbjerg, C. S. et al. Prenatal and postnatal exposures to endocrine disrupting chemicals and timing of pubertal onset in girls and boys: a systematic review and meta-analysis. Hum Reprod Update 28, 687–716 (2022). Lopez-Rodriguez, D., Franssen, D., Heger, S. & Parent, A.-S. Endocrine-disrupting chemicals and their effects on puberty. Best Pract Res Clin Endocrinol Metab 35, 101579 (2021). Manyori, F. et al. Association between phenols exposure and earlier puberty in children: A systematic review and meta-analysis. Environ Res 190, 1–10 (2020). Matoso, V., Bargi-Souza, P., Ivanski, F., Romano, M. A. & Romano, R. M. Acrylamide: A review about its toxic effects in the light of Developmental Origin of Health and Disease (DOHaD) concept. Food Chem 283, 422–430 (2019). Parent, A.-S., Franssen, D., Fudvoye, J., Gérard, A. & Bourguignon, J.-P. 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L. & Lee, C. C. Dietary intake of 4-nonylphenol and bisphenol A in Taiwanese population: Integrated risk assessment based on probabilistic and sensitive approach. Environmental Pollution 244, 143–152 (2019). Bigambo, F. M. et al. Association between phenols exposure and earlier puberty in children: A systematic review and meta-analysis. Environ Res 190, 110056 (2020). Giulivo, M., Lopez de Alda, M., Capri, E. & Barceló, D. Human exposure to endocrine disrupting compounds: Their role in reproductive systems, metabolic syndrome and breast cancer. A review. Environ Res 151, 251–264 (2016). Choe, Y. et al. Prenatal and childhood exposure to endocrine-disrupting chemicals and early thelarche in 8-year-old girls: A prospective study using Bayesian kernel regression. Environ Res 263, 120056 (2024). Yu, Y. et al. Adolescence is a sensitive period for acrylamide-induced sex hormone disruption: Evidence from NHANES populations and experimental mice. Ecotoxicol Environ Saf 249, 114413 (2023). Calcaterra, V. et al. Evaluating Phthalates and Bisphenol in Foods: Risks for Precocious Puberty and Early-Onset Obesity. Nutrients 16, (2024). Nagata, C. et al. Associations of Acrylamide Intake With Urinary Sex Hormone Levels Among Preschool-Age Japanese Children. Am J Epidemiol 187, 75–81 (2018). Nagata, C. et al. Acrylamide exposure, sex hormones, and pubertal status in Japanese adolescents. Int J Environ Health Res 1–10 (2024) doi: 10.1080/09603123.2024.2401578 . Chu, P.-L., Liu, H.-S., Wang, C. & Lin, C.-Y. Association between acrylamide exposure and sex hormones in males: NHANES, 2003–2004. PLoS One 15, e0234622 (2020). Jung, M. K. et al. The analysis of endocrine disruptors in patients with central precocious puberty. BMC Pediatr 19, 323 (2019). McGuinn, L. A., Ghazarian, A. A., Joseph Su, L. & Ellison, G. L. Urinary bisphenol A and age at menarche among adolescent girls: evidence from NHANES 2003–2010. Environ Res 136, 381–386 (2015). Buluş, A. D. et al. The evaluation of possible role of endocrine disruptors in central and peripheral precocious puberty. Toxicol Mech Methods 26, 493–500 (2016). Wolff, M. S. et al. Associations of urinary phthalate and phenol biomarkers with menarche in a multiethnic cohort of young girls. Reprod Toxicol 67, 56–64 (2017). Wolff, M. S. et al. Environmental phenols and pubertal development in girls. Environ Int 84, 174–180 (2015). Wolff, M. S. et al. Investigation of relationships between urinary biomarkers of phytoestrogens, phthalates, and phenols and pubertal stages in girls. Environ Health Perspect 118, 1039–1046 (2010). Howland, R. E. et al. Assessing Endogenous and Exogenous Hormone Exposures and Breast Development in a Migrant Study of Bangladeshi and British Girls. Int J Environ Res Public Health 17, (2020). Wang, Z. et al. Urine bisphenol A and pubertal development in boys. Int J Hyg Environ Health 220, 43–50 (2017). Durmaz, E. et al. Urinary Bisphenol A Levels in Girls with Idiopathic Central Precocious Puberty. J Clin Res Pediatr Endocrinol 6, 16–21 (2014). Kasper-Sonnenberg, M., Wittsiepe, J., Wald, K., Koch, H. M. & Wilhelm, M. Pre-pubertal exposure with phthalates and bisphenol A and pubertal development. PLoS One 12, e0187922 (2017). Chen, Y. et al. Association between bisphenol a exposure and idiopathic central precocious puberty (ICPP) among school-aged girls in Shanghai, China. Environ Int 115, 410–416 (2018). Frederiksen, H. et al. Bisphenol A and other phenols in urine from Danish children and adolescents analyzed by isotope diluted TurboFlow-LC–MS/MS. Int J Hyg Environ Health 216, 710–720 (2013). Ferguson, K. K. et al. Prenatal and peripubertal phthalates and bisphenol A in relation to sex hormones and puberty in boys. Reproductive Toxicology 47, 70–76 (2014). Miller, M. J., Carter, D. E. & Sipes, I. G. Pharmacokinetics of acrylamide in Fisher-344 rats. Toxicol Appl Pharmacol 63, 36–44 (1982). Thayer, K. A. et al. Pharmacokinetics of Bisphenol A in Humans Following a Single Oral Administration HHS Public Access. Environ Int 83, 107–115 (2015). Pollack, A. Z. et al. Variability and exposure classification of urinary phenol and paraben metabolite concentrations in reproductive-aged women. Environ Res 151, 513–520 (2016). Freire, C. et al. International Journal of Hygiene and Environmental Health Association of prenatal exposure to phthalates and synthetic phenols with pubertal development in three European cohorts. Int J Hyg Environ Health 261, (2024). Marshall, W. A. & Tanner, J. M. Variations in pattern of pubertal changes in girls. Arch Dis Child 44, 291–303 (1969). Marshall, W. A. & Tanner, J. M. Variations in the pattern of pubertal changes in boys. Arch Dis Child 45, 13–23 (1970). European Environment Agency. The Impacts of Endocrine Disrupters on Wildlife, People and Their Environments . (Luxembourg, 2012). doi: 10.2800/41462 . Larsen, P. S. et al. Pregnancy and birth cohort resources in Europe: A large opportunity for aetiological child health research. Paediatric and Perinatal Epidemiology vol. 27 393–414 Preprint at https://doi.org/10.1111/ppe.12060 (2013). US Department of Agriculture Agricultural Research Service. USDA National Nutrient Database for Standard Reference: Nutrient Data Laboratory. www.ars.usda.gov. Preprint at (2004). Lopes, C. et al. National food, nutrition, and physical activity survey of the Portuguese general population (2015–2016): Protocol for design and development. J Med Internet Res 20, 1–11 (2018). Goios, A. C. L. et al. Validation of a new software eAT24 used to assess dietary intake in the adult Portuguese population. Public Health Nutr 1–11 (2020) doi: 10.1017/S1368980020001044 . Costa, S. A. et al. Methodological approaches for the assessment of bisphenol A exposure. Food Research International 173, 113251 (2023). Guerra, R. S., Fonseca, I., Pichel, F., Restivo, M. T. & Amaral, T. F. Hand length as an alternative measurement of height. Eur J Clin Nutr 68, 229–233 (2014). WHO Multicentre Growth Reference Study Group. Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age Methods and Development . (2006). World Medical Association. WMA Declaration of Helsinki: ethical principles for medical research involving human subjects. 353, 1418–1419 (1974). Samejima, F. Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement 34, 100 (1969). Marshall, A., Altman, D. G., Holder, R. L. & Royston, P. Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines. BMC Med Res Methodol 9, 57 (2009). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6311918","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442007639,"identity":"36aad8a3-dcf8-4ef6-b76c-2cd17ce6abf4","order_by":0,"name":"Sofia Almeida Costa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBADOTYSNSQwGCNpYSZOS2ID0Vrk2w8/fPjzh116H//ZY9IFDIfzGKT7D+DVYnAmzdiYJyE5t00iL016BsPhYgaZw/htMWDIYZNmSGAGauExk+ZhOJzYIJFMwGH9b9gkfyTUp7PxnyFSC8ONHDYJnoTDCWwMOURqMbjxDOiXtOOGQL8kW88wSC9mkzlsQMBhyQ8f/rCplpfvP3vwdkGFdR6/dOMDAi6DAx5ghBgwJLBJEKsBogUUqyRoGQWjYBSMgpEBAKtjOnduJHR4AAAAAElFTkSuQmCC","orcid":"","institution":"Universidade do Porto","correspondingAuthor":true,"prefix":"","firstName":"Sofia","middleName":"Almeida","lastName":"Costa","suffix":""},{"id":442007641,"identity":"b8f7c832-e855-40a2-8bed-473a16d02e1b","order_by":1,"name":"Milton Severo","email":"","orcid":"","institution":"Universidade do Porto","correspondingAuthor":false,"prefix":"","firstName":"Milton","middleName":"","lastName":"Severo","suffix":""},{"id":442007642,"identity":"d9697fec-67b8-4ebe-a99a-e4dc53b76729","order_by":2,"name":"Catarina Campos Silva","email":"","orcid":"","institution":"Universidade do Porto","correspondingAuthor":false,"prefix":"","firstName":"Catarina","middleName":"Campos","lastName":"Silva","suffix":""},{"id":442007643,"identity":"477cdad7-0f2d-4458-9d91-e94352e5b6ad","order_by":3,"name":"Carla Lopes","email":"","orcid":"","institution":"Universidade do Porto","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"","lastName":"Lopes","suffix":""},{"id":442007644,"identity":"513c1e37-937b-42c8-a54c-41ac6ed2f5d2","order_by":4,"name":"Duarte Torres","email":"","orcid":"","institution":"Universidade do Porto","correspondingAuthor":false,"prefix":"","firstName":"Duarte","middleName":"","lastName":"Torres","suffix":""}],"badges":[],"createdAt":"2025-03-26 11:38:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6311918/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6311918/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97040277,"identity":"c3921209-2f19-4f53-a9a4-83e885512086","added_by":"auto","created_at":"2025-11-29 08:09:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1184720,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6311918/v1/fbae596b-73be-4b4d-8519-fce48ecaac87.pdf"},{"id":80669691,"identity":"4cf7ff0c-1bd2-4ce7-9f18-e4b6b6de0b20","added_by":"auto","created_at":"2025-04-15 19:06:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":298075,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6311918/v1/63888f1a758beeec208eeea2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations between food contaminants exposure and pubertal development at 10 and 13 years old","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePuberty represents a dynamic transition from childhood to adulthood, with significant physical changes leading to reproductive maturity. However, the timing of pubertal onset and the speed of its progression vary greatly among individuals and may be influenced by external factors\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn recent years, the development of different endocrine abnormalities due to exposure to endocrine-disrupting compounds (EDC) from the environment has been well described\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. EDC are external substances usually found in air, water, food, and other consumer products, and they are one of the factors that may influence puberty timing\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These compounds may directly interfere with estrogenic or androgenic signalling pathways and consequently with the hypothalamic-pituitary-gonadal axis or indirectly with peripheral organs, such as adipose tissue and adrenal glands\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsidering that the correct function of the endocrine system is essential for the control, development and maturation of the different tissues and organs, EDC exposure in critical time windows can significantly impair short- and long-term health outcomes\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Prenatal period, namely the embryo-fetal time, and postnatal period, childhood and adolescence, are the most susceptible to disruptions\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAcrylamide (AA) is a compound primarily formed via the Maillard reaction when the amino acid asparagine reacts with reducing sugar under low-moisture conditions at temperatures exceeding 120\u0026ordm;C. It is commonly found in baked or fried carbohydrate-rich foods, tobacco smoke, and other industrial applications\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. For the general population, particularly children and adolescents, diet represents the primary source of AA exposure\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Major dietary contributors include cereal products (such as bread, toast, breakfast cereals, biscuits, and snacks), potato-based foods (including chips, French fries, and crisps), coffee and coffee substitutes\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. AA was classified as \u0026ldquo;probably carcinogenic\u0026rdquo; by the International Agency for Research on Cancer in 1994\u003csup\u003e10\u003c/sup\u003e. Moreover, recently, AA was also considered a potential EDC\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, corroborated by animal studies which found an association with reproductive toxicity, including ovarian dysfunction, disrupted spermatogenesis and infertility\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, epidemiological studies in humans, particularly testing the association between AA exposure at younger ages and pubertal development, are limited and inconclusive.\u003c/p\u003e \u003cp\u003eBisphenol A (BPA) is a monomer used to produce polycarbonate plastics and epoxy resins. Polycarbonate plastics are commonly applied to food contact materials, such as reusable beverage bottles, tableware, cookware, and food containers. Epoxy resins are often used in protective linings of food and beverage cans\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Additionally, BPA is utilised in different non-food-related products, including toys, medical devices, thermal paper, electronic products, and flame retardants\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Diet is considered the main source of BPA exposure in humans, with canned foods and beverages being the most relevant contributors\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This food contaminant was considered EDC, and considering both the estrogenic and anti-androgenic effects after exposure may impair the reproductive system and pubertal regulation\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Despite that, previous studies testing pre- and post-natal BPA exposure and consequences on pubertal development have shown controversial results, leaving the conclusions of this association unclear.\u003c/p\u003e \u003cp\u003eDifferent possible explanations for the inconclusive results found in the previously published studies regarding EDC and pubertal development may be related to the type of EDC, duration of exposure, type of outcomes and age at exposure/ outcome evaluation\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Furthermore, most of the studies have been focused on assessing the effect of individual compounds, with a narrow perspective considering the complexity of the diet and the real-world scenario of food contaminants exposure.\u003c/p\u003e \u003cp\u003eThus, this study aims to assess the association of food contaminants exposure, namely acrylamide and bisphenol A, individually and combined, on pubertal development in children and adolescents aged 4 to 13.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSociodemographic characteristics between eligible participants and the remaining cohort at baseline were similar (supplemental material, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Of the included participants, 51.3% were male, and 48.7% were female. Statistical differences were only found for maternal characteristics.\u003c/p\u003e \u003cp\u003eRegarding the general characteristics of the eligible participants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), no significant differences were found between girls and boys for maternal age and maternal education. However, some significant differences were found in the other variables. As expected, compared to girls, boys presented a higher level of physical activity, higher total energy intake, and higher z-BMI. Regarding the daily dietary exposure to AA and BPA at 4-, 7-, 10- and 13- years old, the median dietary exposure is higher in boys for both AA and BPA, decreasing with age in both sexes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral characteristics of the eligible participants, stratified by sex.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2572)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2707)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaternal age (years)\u003c/b\u003e, \u003cb\u003emean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.0 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.7 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaternal education (years)\u003c/b\u003e, \u003cb\u003emean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.1 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.2 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1788 (70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1797 (67.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1660 (71.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1691 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1415 (59.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1720 (68.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e989 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1362 (67.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Energy Intake (kcal)\u003c/b\u003e, \u003cb\u003emean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1562 (280.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1641 (301.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1711 (293.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1812 (313.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1855 (364.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1947 (396.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1759 (405.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1923 (445.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ez-BMI\u003c/b\u003e, \u003cb\u003emean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.62 (1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56 (1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.71 (1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70 (1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.63 (1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74 (1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.47 (1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41 (1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcrylamide, \u0026micro;g/kg bw/day\u003c/b\u003e, \u003cb\u003emedian (P25-P75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.76 (0.50, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83 (0.56, 1,23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.63 (0.42, 0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67 (0.45, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58 (0.39, 0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62 (0.41, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.41 (0.27, 0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46 (0.30, 0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBisphenol A, ng/kg bw/day\u003c/b\u003e, \u003cb\u003emedian (P25-P75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.3 (60.7, 79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.5 (61.1, 76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.2 (42.6, 57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.1 (43.8, 57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.7 (29.7, 41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.8 (30.5, 42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.4 (20.8, 28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.1 (21.0, 29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: n \u0026ndash; sample size, % \u0026ndash; percentage, SD \u0026ndash; standard deviation, kcal \u0026ndash; kilocalories, z-BMI \u0026ndash; body mass index z-score, \u0026micro;g \u0026ndash; microgram, ng \u0026ndash; nanogram, kg \u0026ndash; kilogram, bw \u0026ndash; body weight, P25\u0026ndash;25th percentile, P75\u0026ndash;75th percentile.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: a) Practice of leisure physical activity outside the school setting. p-values from the chi-square test, Student's t-test or Mann\u0026ndash;Whitney U test, as appropriate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSignificant values are in \u003cb\u003ebold\u003c/b\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the pubertal development of participants according to the Tanner scale at 10 and 13 years. The estimated percentage of participants in stage 1 of breast or genital rating was 26.6% in girls and 73.4% in boys at 10 years, while at 13 years, these percentages reduced, as expected, to 1.6% and 1.2%, respectively. At 13 years of age, 55.6% of the girls and 61.7% of the boys have reached stage 4 or 5 for the breast or genital rating. Despite that, regarding pubic hair, 61.2% of the girls and 31.4% of the boys have reached stage 4 or 5.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePubertal development of participants at 10- and 13-years old, stratified by sex.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePubic hair, 10 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBreast or genital rating\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e10 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAxillary hair, 13 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePubic hair, 13 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBreast or genital rating\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e, \u003cb\u003e13 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: n \u0026ndash; sample size, % \u0026ndash; percentage.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: a) Breast rating for girls or genital rating for boys.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the linear regression models to test the association between food contaminants exposure, individually and combined, with the global score of pubertal development. After adjusting for the participant\u0026rsquo;s exact age, maternal age, maternal education, the practice of leisure physical activity and total energy intake (model 2), a significant negative association was found between individual AA exposure at 7 years (-0.007 (95% CI: -0.013, -0.002)), 10 years (-0.006 (95% CI: -0.010, -0.003)) and 13 years (-0.005 (95% CI: -0.009, -0.001)) and a higher pubertal development global score in girls. On the contrary, there was a significant positive association for individual AA exposure at 13 years (0.003 (95% CI: 0.000, 0.007)) in boys. Regarding individual BPA exposure, a significant positive association with a higher pubertal development global score was found only in boys for exposures at 10 and 13 years of age. Testing the combined exposure in the model did not significantly change the results observed for the individual exposure to each food contaminant, except for the AA association in boys that lost its significance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between acrylamide (\u0026micro;g/day) and bisphenol A (ng/day) exposure and the global score of pubertal development applying linear regression models, stratified by sex (β and 95% confidence interval (CI)).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001 (-0.005, 0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.001 (-0.008, 0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006 (0.000, 0.012)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002 (-0.004, 0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.004 (-0.009, 0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.007 (-0.013, -0.002)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003 (-0.001, 0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001 (-0.004, 0.007)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.005 (-0.008, -0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.006 (-0.010, -0.003)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000 (-0.003, 0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000 (-0.004, 0.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.005 (-0.008, -0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.005 (-0.009, -0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004 (0.001, 0.007)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003 (0.000, 0.007)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02 (-0.48, 0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02 (-0.48, 0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35 (-0.18, 0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33 (-0.19, 0.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.16 (-0.59, 0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.15 (-0.58, 0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 (-0.31, 0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17 (-0.26, 0.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.07 (-0.45, 0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.07 (-0.45, 0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.46 (0.03, 0.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.46 (0.04, 0.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.12 (-0.46, 0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.13 (-0.47, 0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.47 (0.14, 0.81)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.49 (0.15, 0.82)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAA\u0026thinsp;+\u0026thinsp;BPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old, AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000 (-0.005, 0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.001 (-0.007, 0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005 (-0.001, 0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002 (-0.004, 0.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 years old, BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02 (-0.48, 0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03 (-0.48, 0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33 (-0.20, 0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33 (-0.20, 0.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old, AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.004 (-0.009, 0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.007 (-0.013, -0.002)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003 (-0.001, 0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001 (-0.004, 0.006)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 years old, BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.15 (-0.58, 0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.13 (-0.56, 0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 (-0.33, 0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16 (-0.28, 0.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old, AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.004 (-0.007, -0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.005 (-0.009, -0.002)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000 (-0.004, 0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000 (-0.004, 0.003)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years old, BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08 (-0.46, 0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.07 (-0.45, 0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.46 (0.03, 0.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.46 (0.04, 0.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old, AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-0.004 (-0.008, -0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-0.004 (-0.008, 0.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003 (0.000, 0.006)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002 (-0.001, 0.006)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 years old, BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.13 (-0.47, 0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.13 (-0.47, 0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.47 (0.13, 0.81)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.48 (0.14, 0.82)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: β \u0026ndash; regression coefficient, 95% CI \u0026ndash; 95% confidence interval, AA \u0026ndash; acrylamide; BPA \u0026ndash; bisphenol A.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 1: adjusted for participant\u0026rsquo;s exact age (at 10-year follow-up for girls and at 13-year follow-up for boys), maternal age, maternal education, and cross-sectional practice of leisure physical activity. Model 2: adjusted for model 1 plus cross-sectional total energy intake (kcal).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSignificant values are in \u003cb\u003ebold\u003c/b\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eConsidering data from a population-based birth cohort, the present study found an adverse effect of food contaminants exposure, namely acrylamide and bisphenol A, on pubertal development. In girls, higher exposure to AA at 7, 10 and 13 years of age was inversely associated with pubertal development at 10 and 13 years. In boys, higher exposure to AA at 13 years and higher exposure to BPA at 10 and 13 years of age was positively associated with precious pubertal development. The combined effect of these food contaminants was also tested, and the results remained the same, except for the effect of AA among boys, which lost its significance.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first study assessing the association between food contaminants exposure, estimated through collected dietary information, and pubertal development, measured through the Tanner scale. Moreover, this study followed a prospective and cross-sectional epidemiological design to the extent that the exposure was measured before or at the same time as the outcome was assessed. In this work, we only found one significant negative longitudinal association between higher exposure to AA at 7 years and later pubertal development in girls.\u003c/p\u003e \u003cp\u003eAccording to studies performed in animal models, it was plausible that AA and BPA exposure causes later puberty by disrupting the hypothalamic-pituitary-gonadal axis, reducing sex hormone concentrations in both female and male animals\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. On the other hand, BPA also has estrogen-mimicking properties, which may trigger early puberty in both sexes\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe previous epidemiological evidence on the association between AA and BPA dietary exposure and impaired pubertal development in humans is limited and contradictory. The comparison of the present findings with other studies is also difficult, considering the methodological differences across them. First, most previous studies estimated the exposure in spot urine or blood samples. From what we know, only one study performed in preschool-age Japanese children in 2006 estimated dietary acrylamide exposure using 3-day diet records\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Second, the moment of exposure assessment differs, which sometimes reflects the pre-natal exposure and other times reflects the post-natal exposure, especially for BPA-tested associations. Third, different methodologies to assess pubertal development were used across studies, i.e., using other scales rather than the Tanner scale, the interpretation of one single parameter or an overall pubertal development score, and measuring sex hormones in the blood to determine the pubertal stage. Fourth, the cross-sectional design of most studies and the small sample size. Fifth, the variability of the chosen potential confounders also differs, especially concerning BMI and total energy intake. Given the conceptual framework of this study and the potential role of AA and BPA as an endocrine disruptor, our final model was adjusted for sociodemographic characteristics, lifestyle factors, and total energy intake. Since participants' BMI could mediate the observed association, any adjustment or stratification to the model for this variable would be inappropriate.\u003c/p\u003e \u003cp\u003eRegarding AA, in line with our results, in a study involving 230 boys and 198 girls aged 3\u0026ndash;6 years, a positive association between dietary AA exposure and higher sex hormone levels was found exclusively in boys\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. A cross-sectional study using data from individuals aged 6\u0026ndash;19 years of NHANES 2013\u0026ndash;2016 found a negative correlation between blood acrylamide and glycidamide biomarkers and sex hormone levels in girls\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, contrary to our findings, these authors also found a significant negative association among boys\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Another recent Japanese study among adolescents aged 13\u0026ndash;14 years found that AA measured in urine was associated with lower testosterone levels and a delayed puberty stage in males\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Finally, other authors did not find significant associations between blood acrylamide and glycidamide biomarkers and sex hormones using cross-sectional data from NHANES 2003\u0026ndash;2004 of participants older than 12 years\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Nevertheless, all these studies adjusted their models to BMI, among other potential confounders, which may conditionate the interpretation and the comparison of the results.\u003c/p\u003e \u003cp\u003eFor BPA cross-sectional\u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and longitudinal\u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e studies did not find an association between urinary BPA and abnormalities in pubertal development in girls, which is in line with our results. In another cross-sectional study from the United Kingdom, although concentrations of urinary BPA have shown a positive association with the onset of thelarche, the authors failed to find a statistical significance for the hazard ratio\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. One South Korean study found that prenatal exposure to BPA was associated with early puberty but did not find a significant result considering childhood exposure\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Additionally, a systematic review with meta-analysis, including only studies performed with female participants, found no significant association between BPA exposure and pubertal development\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Among boys, aligned with the findings of this paper, a cross-sectional study performed among Chinese boys aged 9\u0026ndash;18 found a significant positive association between urinary BPA and early pubertal onset\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Still, contradictory to our results, some authors found positive associations with statistical significance between BPA exposure and precocious puberty in girls\u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In boys, several studies failed to find a significant association\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In one cohort study, including 250 Mexican boys, prenatal BPA exposure was associated with reduced odds of adrenarche and puberty. Still, no clear association was found between childhood BPA exposure and pubertal onset\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. There are some possible explanations for these differences. As observed for AA studies, most of the previously published results were adjusted for BMI, making direct comparison difficult, as the effect of food contaminants exposure on pubertal development may not be accurately measured in the adjusted model. Furthermore, the dual functionality of BPA, acting as an agonist or antagonist in the causal pathway, may explain the contradictory results of the BPA effect on early or later pubertal development.\u003c/p\u003e \u003cp\u003e It is also important to highlight that spot or first-morning urines may not correctly represent exposure to food contaminants, especially for those with relatively short half-lives, such as AA and BPA. In fact, the half-live ranges between 5\u0026ndash;8 hours for AA\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and approximately 6 hours for BPA body\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Furthermore, the intra-individual variability and the inconstant concentration of food contaminants in urine throughout the day may not be captured with a single sample collection\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOnly two cited studies assessed the effect of childhood combined exposures (phthalates and phenols)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. They failed to find a significant association with impaired pubertal development in girls and boys. Our findings revealed that significant associations of AA and BPA exposure (cross-sectionally and longitudinally) with abnormalities in the timing of puberty onset remained significant when combined exposure to these food contaminants was tested. This represents an important input to fill the gap in knowledge since it provides a more realistic perspective from real-world exposure.\u003c/p\u003e \u003cp\u003eLastly, the interpretation of a single pubertal parameter appears limited, considering the different velocities of pubic hair versus breast/genital rating in girls and boys\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Additionally, we cannot discard some misclassification in our sample, especially in boys. Puberty typically begins in boys about two years later than in girls, and many boys aged 10 to 13 are still prepubescent\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. However, boys in our cohort appear to experience a relatively rapid pace of pubertal development, progressing in genital stages compared to pubic hair within this age range. This justified the use of GRM to compute a global score of pubertal development, including the most relevant and discriminating parameters. We concluded from the reliability analysis (Table S2) that the high missing rate for axillary hair might indicate issues with this variable, conditioning its relevance to the model. Therefore, axillary hair was not included in the calculated global score of pubertal development.\u003c/p\u003e \u003cp\u003eOur analyses have some limitations that must be addressed. First, the sociodemographic characteristics of the eligible participants may suggest a potential presence of participation bias. However, given that statistically significant results were found in our sample for maternal characteristics, we hypothesise that the effects observed in the general population would be even more pronounced. Second, a possible misclassification of the pubertal stage, especially in boys, was detected. We try to overcome this limitation by computing a global score of pubertal development using a graded response model, as explained above. Third, we opted for a linear regression model since our outcome variables did not allow us to apply a mathematical longitudinal model (only two outcome observations). However, since the exposure was measured before the outcome, we were able to interpret the results longitudinally from an epidemiologic perspective.\u003c/p\u003e \u003cp\u003eNonetheless, this study had several strengths. First, the use of a prospective population-based birth cohort with extensive data collection on sociodemographic characteristics, food consumption, and anthropometric and pubertal measurements. Second, the study includes a large sample size of eligible participants, enhancing its statistical power. Third, a large comprehensive database with dietary information was used to estimate exposure to food contaminants. Fourth, the AA exposure assessment accounted for inter-individual and intra-individual variability. Fifth, the availability of 24-hour urine samples for a sub-sample of the GXXI cohort enabled a more accurate estimation of total daily BPA exposure. In fact, when combined with dietary data, this information allowed the construction of a random forest model, an approach rarely employed in previous research. Finally, the development of a global score of pubertal development, which integrated the different Tanner parameters, and enabled a more accurate interpretation of results by reducing errors of classification.\u003c/p\u003e \u003cp\u003eIn the past years, concerns regarding the potential effect of EDC exposure on adverse health outcomes related to puberty development have been raised\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. There is a plausible causal relation between the dysregulation of the sexual hormone system caused by dietary exposure to EDC, such as acrylamide and BPA, responsible for the increased adverse health outcomes and burden of diseases in future life stages. The findings of the present study highlight the importance of reducing daily exposure to both acrylamide and BPA in children and adolescents, as chronic intake was associated with adverse health effects, namely impaired puberty onset. We hope this knowledge will support public health researchers, food safety authorities, and policymakers to design updated guidelines, recommendations, and food policies to mitigate these risks.\u003c/p\u003e \u003cp\u003eIn conclusion, childhood and adolescent exposure to acrylamide and bisphenol A was associated with impaired timing of puberty onset. Higher exposure to acrylamide at 7, 10 and 13 years of age was negatively associated with pubertal development at 10 and 13 years in girls. A higher exposure to acrylamide at 13 years and a higher exposure to bisphenol A at 10 and 13 years were positively associated with precious pubertal development in boys. The combined exposure effect of acrylamide and bisphenol A did not significantly change the found associations. Further studies applying longitudinal models are needed to assess the exposure effects of these food contaminants on pubertal development and reduce the uncertainties surrounding these associations.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy design and participants\u003c/h2\u003e\n\u003cp\u003eThis study utilised data from Generation XXI (GXXI), an ongoing prospective population-based birth cohort established between April 2005-August 2006, across five public healthcare units providing obstetrical and neonatal care in the metropolitan area of Porto, Portugal, as previously described\u003csup\u003e45\u003c/sup\u003e. Recruitment was based on the following eligibility criteria: mothers residing in one of the six municipalities within the metropolitan area of Porto, delivering at the public hospitals serving these municipalities, and giving birth to live infants with a gestational age of at least 24 weeks. Between 24-72 hours post-delivery, mothers were invited to join the GXXI cohort, with a participation rate of 91%, resulting in the enrolment of 8,495 mothers and 8,647 children. Participants were subsequently invited for follow-up assessments at 4, 7, 10, and 13 years of age, with participation rates of 86%, 80%, 76%, and 54%, respectively. The lower participation rate of the last follow-up was attributed to the COVID-19 pandemic, which prematurely interrupted data collection in March 2020.\u003c/p\u003e\n\u003cp\u003eThis study analysed data from all follow-up evaluations. The eligibility criteria for inclusion were having at least one completed food diary, \u003cem\u003ei.e.\u003c/em\u003e at least two reported days within each follow-up, and having performed a sexual development evaluation at 10 and/or at 13 years old. Our final sample included 5279 participants.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eSociodemographic\u003c/u\u003e\u003c/em\u003e\u003cem\u003e\u003cu\u003echaracteristics and lifestyle factors\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSociodemographic characteristics were collected from the participants and mothers using standardised questionaries. Maternal age at baseline and maternal educational level (defined as the number of completed schooling years) were the variables considered and collected at baseline. The child\u0026rsquo;s sex was collected at baseline, and the exact age of the child was calculated based on the date on which the pubertal development assessment was conducted.\u003c/p\u003e\n\u003cp\u003eRegarding lifestyle factors, physical activity was considered a potential confounding variable in the association between exposure to food contaminants and pubertal development impairment. Thus, the practice (yes/no) of leisure physical activity outside the school was used at 4-, 7-, 10-, and 13-year follow-ups.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cu\u003eDietary intake and exposure to food contaminants\u003c/u\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBefore the face-to-face interview, parents (or primary caregivers) at the 4-, 7-, and 10-year follow-ups, as well as adolescents at the 13-year follow-up, were instructed by the research team, both orally and in writing, to complete a 3-day food diary, including two weekdays and one weekend day. Detailed information was collected for each food or beverage consumed, such as the time and place of consumption, brand, preparation method, cooking process, and quantity consumed. During the face-to-face interviews, trained researchers reviewed the food diaries. Trained nutritionists coded data from the 4-, 7-, and 10-year follow-ups using Food Processor SQL software\u003csup\u003e46\u003c/sup\u003e and processed data from the 13-year follow-up with the \"eAT24\" software. Dietary data from the 4- to 10-year follow-ups were harmonised in the \"eAT24\" software to ensure consistency. This software, developed for the Portuguese National Food, Nutrition, and Physical Activity Survey 2015-2016, integrates the Portuguese Food Composition Table and uses the FoodEx2 classification system, as previously described\u003csup\u003e47,48\u003c/sup\u003e. Finally, all food items and beverages were converted into energy and nutrients, and the individual mean daily intake was computed. Participants were eligible for inclusion in the present study only if their food diaries included data for at least two complete days in any follow-up evaluation.\u003c/p\u003e\n\u003cp\u003eThe daily dietary exposure to AA (\u0026micro;g/kg of body weight/day) was then calculated following previously described methods\u003csup\u003e9\u003c/sup\u003e. Data on AA levels in various food groups were obtained from the EFSA Scientific Opinion on Acrylamide in Food, published in 2015\u003csup\u003e8\u003c/sup\u003e. Ten cycles of random assignments were conducted, producing ten distinct estimated AA values for each consumption occasion.\u003c/p\u003e\n\u003cp\u003eA random forest model was used to estimate the daily exposure to BPA, as described elsewhere\u003csup\u003e49\u003c/sup\u003e. This methodology combined information on food group consumption, food packing material, and the total urinary concentration of BPA measured in 24-h urine of a sub-sample. A 2-times 5-fold cross-validation was applied to handle the possible overfitting of the model. The random forest was then applied to predict the total BPA daily exposure in the remaining sample and the remaining follow-up waves.\u003c/p\u003e\n\u003ch2\u003eAnthropometrics measurements\u003c/h2\u003e\n\u003cp\u003eTrained observers performed a physical examination and anthropometric measures at the 4-, 7‐, 10‐ and 13‐year‐old follow‐up evaluations. Height and weight were measured objectively during face-to-face interviews following standard procedures. Measurements were taken after a 12-hour fasting period, with participants dressed in light clothing and barefoot\u003csup\u003e50\u003c/sup\u003e. Height was recorded to the nearest centimetre using a wall stadiometer (SECA, Hamburg, Germany), while body weight was measured to the nearest tenth of a kilogram using a digital scale (SECA, Columbia, USA). Body mass index (BMI) was calculated as weight divided by height squared, and participants were classified based on age- and sex-specific BMI z-scores (z-BMI) provided by the World Health Organization\u003csup\u003e51\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003ePubertal development\u003c/h2\u003e\n\u003cp\u003ePubertal development was assessed at ages 10 and 13 using the Tanner scale, a standardized method for evaluating sexual maturation\u003csup\u003e42,43\u003c/sup\u003e. The scale encompasses different parameters, namely breast development in girls, genital development in boys and pubic hair development in both sexes. At 13 years old, axillary hair was evaluated for both sexes. The evaluation was conducted by trained professionals who received training from a single endocrinologist. Breast development in girls was assessed through visual inspection and palpation, while testicular volume was measured to evaluate genital development in boys using the Prader orchidometer. Each parameter was classified into five stages: 1 \u0026ndash; prepubertal; 2, 3, and 4 \u0026ndash; pubertal; and 5 \u0026ndash; postpubertal. When discrepancies arose between breast or testicular development and pubic hair staging, the former was prioritised.\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eAll study phases complied with the Ethical Principles for Medical Research Involving Human Subjects expressed in the Declaration of Helsinki \u003csup\u003e52\u003c/sup\u003e. The baseline and follow-up evaluations were approved by the University of Porto Medical School/ S. Jo\u0026atilde;o Hospital Centre Ethics Committee, except the 13-year follow-up approved by the ISPUP Ethics Committee. At baseline and follow-up evaluations, all procedures were explained to participants, and informed consent was signed by one of the parents or legal guardians (at 13 years, it was also signed by the participants). The Data Protection National Commission additionally approved the baseline evaluation. The study follows the present EU General Data Protection Regulation under close supervision of the Data Protection Office of ISPUP.\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eProportions were compared using the chi-square test, mean using the Student\u0026rsquo;s t-test and median using the Mann-Whitney U test. The analyses were stratified by sex.\u003c/p\u003e\n\u003cp\u003eA global score of pubertal development at 10 and 13 years old was created using graded response models (GRM), which enables handling ordered polytomous variables\u003csup\u003e53\u003c/sup\u003e. This model assumes that item discrimination is not equal across all items and that differences between each response category are not the same across all items. The present study used GRM to compute a global score of pubertal development, including items of pubic hair and breast/genital development, evaluated at 10 and 13 years old (supplemental material, Figure S1 and Table S3).\u003c/p\u003e\n\u003cp\u003eThe association between the global score of pubertal development and the participant\u0026rsquo;s exact age at 10- and 13-year follow-up was evaluated using the linear regression model. According to the strongest coefficient found, the exact age at 10-year follow-up in girls and the exact age at 13-year follow-up in boys were the variables that explained better the differences in the global score of puberty.\u003c/p\u003e\n\u003cp\u003eA linear regression model was used to test the associations between exposure to food contaminants, individually and combined, and pubertal development. Both cross-sectional and longitudinal practice of leisure physical activity and total energy intake were pointed as potential confounding variables and tested. Only the cross-sectional variables remained statistically significant, being those included in the final model. Thus, two models are presented in this paper. Model 1 was adjusted for the exact participants\u0026rsquo; age, maternal age, maternal education, and cross-sectional practice of leisure physical activity. Model 2 was adjusted for model 1 plus cross-sectional total energy intake (kcal). Moreover, the analysis was performed separately for each of the 10 different estimated values of AA and then combined using Rubin\u0026rsquo;s rules\u003csup\u003e54\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed with a 5% significance level, and missing data were treated at random. The R software version 4.2.1 for Windows was used.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data from Generation XXI are not publicly available due to privacy or ethical restrictions. The data can be made available for research proposals to the Generation XXI Executive Committee ([email protected]) upon request. Further information about Generation XXI can be obtained via the Generation XXI website [www.geracao21.com] or by emailing [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge the families enrolled in Generation XXI for their kindness, the participating hospitals and their staff for their help and support, and all previous and current members of the research and field team for their enthusiasm and perseverance.\u003c/p\u003e\n\u003cp\u003eG21 was funded by Programa Operacional de Sa\u0026uacute;de \u0026ndash; Sa\u0026uacute;de XXI, Quadro Comunit\u0026aacute;rio de Apoio III and Administra\u0026ccedil;\u0026atilde;o Regional de Sa\u0026uacute;de Norte (Regional Department of Ministry of Health).\u003c/p\u003e\n\u003cp\u003eThis particular study was supported through FEDER from the Operational Programme Factors of Competitiveness \u0026ndash; COMPETE and through national funding from the Foundation for Science and Technology \u0026ndash; FCT (Portuguese Ministry of Education and Science) under the project \u0026ldquo;FOCAcCIa: Exposure to food additives and contaminants from food processing and packaging: Defining patterns and their effects on adiposity and cognitive function from childhood to adolescence\u0026rdquo; (POCI-01-0145-FEDER-031949); and the FCT doctoral grant (DOI 10.54499/UI/BD/150785/2020) (SAC).\u003c/p\u003e\n\u003cp\u003eThe funding institutions had no role in this article's design, analysis or writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribute of authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSAC, CL and DT contributed to the design and implementation of the research. MS, CCS and SAC to the analysis of the results.\u003c/p\u003e\n\u003cp\u003eSAC wrote the original draft manuscript. SAC, MS, CCS, CL and DT reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUldbjerg, C. S. \u003cem\u003eet al.\u003c/em\u003e Prenatal and postnatal exposures to endocrine disrupting chemicals and timing of pubertal onset in girls and boys: a systematic review and meta-analysis. Hum Reprod Update 28, 687\u0026ndash;716 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez-Rodriguez, D., Franssen, D., Heger, S. \u0026amp; Parent, A.-S. Endocrine-disrupting chemicals and their effects on puberty. 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BMC Med Res Methodol 9, 57 (2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cohort, acrylamide, bisphenol A, children, adolescents, Tanner","lastPublishedDoi":"10.21203/rs.3.rs-6311918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6311918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndocrine-disrupting compounds, such as acrylamide(AA) and bisphenol A(BPA), are external substances usually found food that may influence pubertal development.\u003c/p\u003e\n\u003cp\u003eThis study aims to assess the association of food contaminants exposure (AA and BPA), individually and combined, on pubertal development in children and adolescents aged 4-13.\u003c/p\u003e\n\u003cp\u003eData from four waves of Portuguese population-based birth cohort Generation XXI was used(n=5279). Dietary information was gathered through food diaries. AA exposure was estimated combining food intake with EFSA occurrence data, while BPA exposure was predicted using a random forest model. Linear regression models tested the association food contaminants exposure-pubertal development.\u003c/p\u003e\n\u003cp\u003eA significant negative association was found in girls between individual AA exposure at 7-years(-0.007(95%CI:-0.013,-0.002)), 10-years(-0.006(95%CI:-0.010,-0.003)) and 13-years(-0.005(95%CI:-0.009,-0.001)). In boys, a significant positive association was found between BPA exposure at 10 and 13-years, and AA exposure at 13-years(0.003(95%CI:0.000,0.007)). The combined exposure did not significantly change the results observed for individual exposure to each food contaminant.\u003c/p\u003e","manuscriptTitle":"Associations between food contaminants exposure and pubertal development at 10 and 13 years old","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 18:58:17","doi":"10.21203/rs.3.rs-6311918/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"21b0b5c8-4c9e-478a-9b6c-409f267f445b","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47065368,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases"},{"id":47065369,"name":"Health sciences/Risk factors"},{"id":47065370,"name":"Health sciences/Diseases/Endocrine system and metabolic diseases"},{"id":47065371,"name":"Health sciences/Diseases/Endocrine system and metabolic diseases/Endocrine reproductive disorders"},{"id":47065372,"name":"Health sciences/Health care/Nutrition"}],"tags":[],"updatedAt":"2025-11-29T08:08:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-15 18:58:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6311918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6311918","identity":"rs-6311918","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}