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Hidden link between endocrine-disrupting chemicals and pediatric obesity

Hidden link between endocrine-disrupting chemicals and pediatric obesity

Article information

Clin Exp Pediatr. 2025;68(3):199-222
Publication date (electronic) : 2024 November 28
doi : https://doi.org/10.3345/cep.2024.00556
Department of Pediatrics, Inje University Sanggye Paik Hospital, Seoul, Korea
Corresponding author: Shin-Hye Kim, MD, PhD. Department of Pediatrics, Inje University Sanggye Paik Hospital, 1342, Dongil-ro, Nowon-gu, Seoul, Korea Email: s2635@paik.ac.kr
Received 2024 March 28; Revised 2024 October 22; Accepted 2024 October 22.

Abstract

The increasing prevalence of pediatric obesity has emerged as a significant public health concern. Among various contributing factors, exposure to endocrine-disrupting chemicals (EDCs) has gained recognition for its potential role. EDCs, including bisphenols, phthalates, per- and polyfluoroalkyl substances, polycyclic aromatic hydrocarbons, and organochlorines, disrupt hormonal regulation and metabolic processes, contributing to alterations in fat storage, appetite regulation, and insulin sensitivity. This study offers a comprehensive review of the current research linking EDC exposure to pediatric obesity by integrating the findings from experimental and epidemiological studies. It also addresses the complexities of interpreting this evidence in the context of public health, highlighting the urgent need for further research.

Key message

Studies indicate potential connections between exposure to endocrine-disrupting chemicals (EDCs) and childhood obesity. Variations in the impact of EDCs in epidemiological studies may result from differences in exposure concentrations and timing, measurement methods, and interactive effects of multiple EDCs. Longitudinal studies on exposure to multiple EDCs are crucial to elucidating their contribution to pediatric obesity and minimize the adverse health consequences of EDC exposure.

Introduction

Endocrine-disrupting chemicals (EDCs) are a diverse group of substances that interfere with the endocrine system and the body's network of hormone-producing glands. These chemicals can mimic, block, or disrupt normal hormonal function, leading to a multitude of health issues [1]. EDCs, which encompass a variety of substances, including phthalates, bisphenols, per- and polyfluoroalkyl substances (PFAS), organochlorines, and polycyclic aromatic hydrocarbons (PAHs) [2,3], are found in numerous consumer products, industrial emissions, and natural sources, rendering their exposure ubiquitous and virtually inevitable in daily life [4].

Pediatric obesity is a critical and growing public health concern characterized by the excessive accumulation of fat that poses a risk to child and adolescent health [5]. The prevalence of pediatric obesity has increased dramatically in recent decades [6], leading to a surge in obesity-related health complications such as type 2 diabetes, hypertension, precocious puberty, and psychological issues [7-9]. These conditions affect the child's immediate well-being and have long-term implications for their adult health, underscoring the urgency of addressing this epidemic.

Emerging research suggests a complex interplay between environmental factors and a genetic predisposition in the development of pediatric obesity. Among these environmental factors, EDC exposure has gained attention owing to its potential role in modulating the risk of obesity. Preliminary findings of epidemiological and experimental studies suggest that EDCs may disrupt hormonal balance and impact metabolism and fat storage mechanisms, potentially contributing to obesity [10].

This paper reviews the potential association between EDC exposure and the risk of childhood obesity by addressing the experimental and epidemiological evidence, highlighting the need for comprehensive research and targeted interventions to mitigate this pressing public health issue.

Bisphenol A

1. General characteristics

Bisphenols, including bisphenol A (BPA), bisphenol S (BPS), bisphenol F (BPF), bisphenol B (BPB), and bisphenol P (BPP), are a group of synthetic organic compounds widely used in the manufacture of polycarbonate plastics and epoxy resins [11]. These materials are prevalent in a variety of consumer products such as water and baby bottles, food storage containers, and food and beverage can linings. The structure of bisphenols, characterized by 2 hydroxyphenyl groups, enables them to mimic estrogen, thereby categorizing them as xenoestrogens. BPA, the most widely recognized bisphenol, was first synthesized in 1891 and has been used in plastic manufacturing since the 1950s [12]. Despite its widespread applications, concerns over the potential health risks of BPA due to its endocrine-disrupting properties have prompted increased scrutiny and the development of alternative bisphenols, including BPS, BPF, BPB, and BPP.

The primary route of human exposure to bisphenols is through dietary consumption, predominantly from food and beverages that are contaminated due to contact with bisphenol-containing materials. Other exposure routes include dermal contact, dust inhalation, and direct oral contact with products made from or coated with bisphenols. Once absorbed, BPA enters the bloodstream and is primarily metabolized in the liver through glucuronidation mediated by uridine 5'-diphospho-glucuronosyltransferase enzymes, resulting in BPA glucuronide formation. This metabolite is subsequently excreted, mostly through the urine, with over 90% of the conjugated metabolites eliminated within 24 hours. The measurement of total urinary bisphenol levels, typically assessed after deconjugation with β-glucuronidase, is a reliable biomarker for bisphenol exposure. Notably, the terminal half-life of BPA is longer after dermal exposure versus oral intake because the skin continues to absorb BPA into the bloodstream even after the initial exposure has ended.

2. Impact on obesity in experimental studies

BPA has been extensively studied for its effects on adipogenesis across various experimental studies (Fig. 1). EDCs such as BPA can also act through estrogen receptor pathways to influence adipogenesis. BPA can bind to estrogen receptors (ERα and ERβ) with lower affinity than estradiol. ER activation by BPA leads to increased expression of genes associated with adipocyte differentiation in human mesenchymal stem cells [13]. Furthermore, the interaction of BPA with ER can impede adiponectin release, thereby exacerbating inflammation in fat tissues and disrupting lipid regulation [14].

Fig. 1.

The potential mechanisms of endocrine-disrupting chemicals (EDCs) in the development of obesity. BPA, bisphenol A; PFAS, per- and polyfluoroalkyl substances; PAHs, polycyclic aromatic hydrocarbons.

BPA also activates the expression of peroxisome proliferator-activated receptor γ (PPARγ), which is essential for fat cell development and energy balance [15]. Studies involving human adipose-derived mesenchymal stem cells revealed that BPA exposure increased the mRNA levels of key adipogenic markers such as PPARγ, C/EBPα, and C/EBPβ. This finding indicates the potential of BPA to promote fat cell formation through ER pathways and potentially via an alternative ER pathway [13]. Additionally, BPA exposure leads to increased preadipocyte growth, greater lipid accumulation, higher proinflammatory cytokine levels, and alterations in genes involved in lipid processing, particularly FABP4 and CD36. This effect has been observed in 3T3-L1 adipocyte models and primary adipocytes derived from children [16,17].

Experimental studies have shown that BPA exposure leads to dysfunction of the brown adipose tissue, which is crucial for thermogenesis and energy expenditure. BPA reduces the expression of uncoupling protein-1 and β-adrenergic receptors in brown adipocytes, leading to decreased thermogenic capacity and energy expenditure while increasing fat accumulation [18]. In an in vitro model, early-life BPA exposure can induce modifications in DNA methylation and histone marks, leading to epigenetic changes in the genes involved in hepatic oxidation. These epigenetic alterations are associated with increased fat and lean mass as well as hepatic steatosis [19].

In utero and adult BPA exposure also affect the hypothalamic neurons involved in appetite regulation, such as the agouti-related peptide and neuropeptide Y, leading to increased appetite and potential weight gain [20]. Moreover, BPA disrupts the gut microbiota, leading to altered microbial composition, reduced short-chain fatty acids, and increased systemic lipopolysaccharides and contributing to obesity, metabolic disorders, and inflammation [21].

3. Association with childhood obesity in epidemiological studies

The relationship between prenatal BPA exposure and childhood obesity has garnered extensive attention, particularly in North America, Europe, and Asia (Table 1). A substantial body of evidence has indicated a positive correlation between prenatal BPA exposure and increased childhood adiposity. These studies frequently reported that early BPA exposure was linked to accelerated weight gain during early childhood and higher adiposity indicators such as body mass index (BMI) z scores, skinfold thickness, body fat percentage, and waist circumference (WC) [22-27]. However, a shift in this trend appears in the more recent literature. Studies published after 2020 reported no significant association between prenatal BPA exposure and adiposity measures in children aged 5–11 years [28,29]. This finding suggests a potential reevaluation of earlier findings or indicates that the impact of BPA may be more nuanced than previously understood. Interestingly, a study from China presented a unique finding, suggesting that prenatal BPA exposure correlates with a specific pattern of BMI trajectory characterized by a low BMI that increases rapidly within the first 2 years of life [30]. This suggests that BPA influences growth patterns that are not uniformly observable across different populations or age groups.

Prenatal exposure to EDCs and childhood obesity in epidemiologic studies

Research on postnatal BPA exposure and its effects on children, including studies from the United States (US) (through National Health and Nutrition Examination Survey [NHANES] data), Europe, Mexico, China, and Korea, primarily employed cross-sectional methodologies; only a few were prospective studies (Table 2). These studies generally indicated a potential link between postnatal BPA exposure, increased adiposity, and a higher risk of obesity in children. However, 2 prospective studies from the US revealed no significant relationship between BPA exposure in childhood and adiposity in later childhood [31,32]. Additionally, a serial cross-sectional study by Okubo et al. [33] utilizing the NHANES 2003–2014 data identified an association between higher BPA levels and obesity risk in 2003–2008 but variability in 2009– 2014. This inconsistency implies that the relationship between BPA exposure and obesity may be affected by several factors including exposure window, changes in BPA usage patterns, public awareness, and regulatory measures. A recent Korean study using Korean National Environmental Health Survey (KoNEHS) data indicated no significant association between urinary BPA concentrations and obesity in children aged 3–17 years [34]. Therefore, further studies are needed to explore how ethnicity-specific factors influence the relationship between BPA exposure and obesity risk.

Postnatal exposure to EDCs and childhood obesity in epidemiologic studies

Phthalates

1. General characteristics

Phthalates, a group of phthalic acid diesters recognized for their ability to make plastics more flexible and durable, have been extensively used since their introduction in the 1920s [35]. These chemicals are added to polyvinyl chloride (PVC) plastics, which are found in diverse consumer products from packaging and flooring to toys and medical devices. Moreover, phthalates are applied in nonplastic products such as personal care products, detergents, and fragrances because of their ability to enhance scents and extend cosmetic durability. Phthalates can leach from these products into the environment and food sources, leading to human exposure.

Based on their molecular weight, phthalates are categorized into low molecular weight (LMW) and high molecular weight (HMW). LMW phthalates, which include phthalates with ester side-chain lengths of one to 4 carbons, are primarily used in personal care products and cosmetics [4]. Common LMW phthalates include dimethyl phthalate, diethyl phthalate, dibutyl phthalate (DBP), and diisobutyl phthalate. These phthalates are found in products such as nail polish to minimize chipping as well as in fragrances as scent stabilizers. Due to their lower molecular weight, LMW phthalates are not as tightly bound to the products, allowing them to off-gas or leach out more readily, especially when exposed to high temperatures. HMW phthalates, which have ester side-chain lengths of 5 or more carbons, are used in a wide range of products, particularly in those that require durability and flexibility. The key HMW phthalates include di (2- ethylhexyl) phthalate (DEHP), diisononyl phthalate, and diisodecyl phthalate. These phthalates are commonly found in PVC products such as plastic tubing, food packaging and processing materials, containers, vinyl toys, vinyl floor coverings, and building products. HMW phthalates are preferred in these applications because of their increased permanency and durability attributed to the longer carbon chains in their chemical structures.

The primary route of phthalate exposure is through ingestion, particularly from consuming food and beverages that have contacted materials containing them.36) Phthalates can also be absorbed through the skin via personal care products or other items containing these chemicals. Another exposure pathway involves inhaling dust or fumes from products that emit phthalates into the air.

Phthalates are metabolized in the liver through phases I and II enzymatic reactions, including hydrolysis, oxidation, and conjugation [36]. The metabolites are subsequently excreted primarily through the urine, although some are excreted via feces. The half-life of phthalates in humans varies depending on the specific compound; however, they are generally metabolized and excreted relatively quickly, often within 24–48 hours. Biomonitoring of phthalate exposure typically involves the measurement of phthalate metabolites in the urine (Supplementary Table 1). These metabolites reflect phthalate processing in the body and are considered reliable indicators of exposure. Advanced analytical methods have enabled the detection of multiple phthalate metabolites and provided a comprehensive assessment of exposure levels.

2. Impact on obesity in experimental studies

Extensive experimental studies explored the mechanisms by which phthalates contribute to obesity (Fig. 1). Several studies demonstrated that mono (2-ethylhexyl) phthalate activates PPARγ, which induces adipocyte differentiation and lipid accumulation [37,38]. Similarly, research on DEHP substitutes has shown that these compounds and their metabolites can accelerate adipogenesis through PPARγ activation in human mature adipocytes [39]. Phthalates such as DBP and DEHP exhibit antiandrogenic activity in vitro. For example, a study of reporter gene assays demonstrated that DBP, mono-n-butyl phthalate, and DEHP display potent antiandrogenic activity [40]. This antiandrogenic action suggests that phthalates can disrupt the normal function of androgens, which are critical for maintaining metabolic health and preventing obesity.

Phthalates, including DEHP, undermine thyroid function by blocking thyroid-stimulating hormone (TSH) receptors, attaching to thyroid hormone transport proteins and modifying iodine absorption in the thyroid follicle cells [41]. Thyroid hormones are crucial for regulating metabolism, and the disruption of thyroid function can lead to weight gain and obesity. Evidence suggests that phthalates can disrupt endocrine function and contribute to obesity via various epigenetic mechanisms. In particular, phthalate exposure is associated with altered DNA methylation and histone modifications in genes related to adipogenesis and insulin resistance [19]. These epigenetic changes can affect metabolic processes and have long-term health implications, including transgenerational effects.

Furthermore, a mouse model of prenatal DEHP exposure demonstrated long-term disruptions in glucose metabolism, energy expenditure, adipogenesis, and gut dysbiosis in the offspring. These disturbances demonstrate the interconnectedness between the host and the gut microbiota in terms of modifying energy metabolism [39].

3. Association with childhood obesity from epidemiological studies

Research into prenatal phthalate exposure and its effects on childhood obesity has been conducted in the US, China, Mexico, and Spain (Table 1). Their findings are mixed; while nearly half of these studies suggest that prenatal exposure may lead to increased BMI z scores, higher overweight risk, and accelerated adiposity in early childhood, other studies reported no significant effects or negative associations. Notably, 2 cohort studies, one each from China and the US, reported that certain phthalate metabolites had a negative impact on fetal growth but were linked to increased adiposity in early childhood [42,43]. Conversely, studies such as a recent Korean prospective study associated phthalate exposure with a reduced skeletal muscle index by 6 years of age [44]. This finding suggests a complex relationship between prenatal phthalate exposure and various aspects of childhood physical development, highlighting the need for further research to fully understand these dynamics.

Research on postnatal phthalate exposure and its impact on childhood adiposity has primarily been conducted in Asian countries, notably China, with several studies emerging from the US (Table 2). These studies consistently showed that LMW and HMW phthalates are associated with increases in BMI z scores, WC, and the likelihood of being overweight and obese in children. Specifically, findings from the KoNEHS highlight that mono-(2-ethyl-5-carboxypentyl) phthalate, a metabolite of DEHP, was linked to a higher odds of obesity among Korean children [45]. Research highlighted the sex-specific effects of phthalate exposure on obesity and revealed that female children might face lower risks of obesity, whereas male children are more likely to exhibit increased obesity odds [46]. This indicates a complex interaction between phthalate exposure and biological sex in determining the obesity risk among children.

Per- and polyfluoroalkyl substances

1. General characteristics

PFAS are synthetic compounds characterized by multiple fluorine atoms attached to an alkyl chain [47]. Their carbon-fluorine bonds, which are among the strongest in organic chemistry, contribute to their resistance to degradation in the environment and human body. Since their introduction in the 1940s, PFAS have been celebrated for their remarkable resistance to water, oil, and heat, leading to their integration into a wide array of products including non-stick cookware, water-repellent apparel, stain-resistant textiles, cosmetics, firefighting foams, and various grease-resistant applications [47]. These compounds are generally categorized by their functional groups into 2 main types: sulfonic acids, such as perfluorooctane sulfonic acid (PFOS), and carboxylic acids, such as perfluorooctanoic acid (PFOA). Additionally, PFAS are classified into short- and long-chain types based on their carbon chain lengths. PFOS and PFOA, 2 extensively studied and widely used PFAS compounds, have been phased out in several countries because of their environmental persistence and potential health risks [47]. Short-chain PFAS, characterized by 6 or fewer carbon atoms, have emerged as less bioaccumulative alternatives to their long-chain counterparts. However, they also exhibit high environmental mobility [48]. Despite ongoing efforts to identify safer substitutes, identifying alternatives that do not compromise product quality or safety remains a significant challenge (Supplementary Table 2).

PFAS, widely used in consumer products and industrial applications, pose significant exposure risks through contaminated drinking water originating from industrial discharges, firefighting foams at military and airport facilities, and waste site leachate [49]. Food packaging materials containing PFAS, including microwave popcorn bags and fast-food wrappers, can leach these chemicals into food. Moreover, PFAS infiltrate the food chain, thereby contaminating fish and seafood. Common items such as non-stick cookware, stain-resistant textiles, water-repellent clothing, and some cosmetics contain PFAS, leading to exposure through direct contact or inhalation of contaminated dust. Although less prevalent, occupational exposure can indirectly affect the families of workers who handle PFAS. Pregnant women and nursing infants are also at risk, as PFAS can transfer through the placenta and breast milk, prompting concerns regarding developmental impacts and long-term health risks [50].

Notably, the half-life of PFAS—the duration over which half of the substance leaves the body—can span several years. For instance, the estimated half-life of PFOA in humans is approximately 2.7 years, whereas that of PFOS may be approximately 3.4 years [51]. Thus, PFAS can persist in the body well beyond the cessation of exposure, with longer-chain PFAS and those featuring specific functional groups being eliminated more slowly. PFAS are notable for their resilience against metabolic breakdown, resulting in their prolonged presence and potential accumulation in the human body [51].

These substances withstand typical metabolic transformations and remain unchanged, leading to their gradual excretion, primarily through the urine. The elimination rate varies by PFAS variant, individual physiology, and exposure intensity. Key factors influencing excretion rates include PFAS chain length, chemical structure, and personal physiological differences such as age, sex, genetics, and overall health.

Blood serum levels serve as the principal biomarkers for PFAS exposure assessments, enabling the detection of diverse PFAS compounds and the evaluation of individual exposures [44]. Long-term monitoring of blood PFAS levels is critical because of their extended half-life and health implications. Additional biomarkers include PFAS detected in the urine, breast milk, and liver tissue, providing a comprehensive overview of an individual's exposure and accumulation.

2. Impact on obesity in experimental studies

Several in vitro and in vivo studies have provided significant insight into the adipogenic potential of PFAS (Fig. 1). A comprehensive study evaluated the adipogenic potential of 10 different PFAS in murine 3T3-L1 fibroblasts. One study reported that perfluorohexane sulfonate (PFHxS) significantly increased adipogenesis in the absence of rosiglitazone, a known PPARγ agonist, suggesting that PFAS can act through mechanisms independent of PPARγ activation [52]. Further investigations have demonstrated the complex interaction of PFAS with thyroid hormone processes, including competitive binding to thyroid transport proteins and the modulation of clearance enzymes, thereby affecting thyroid hormone signaling in both stimulatory and inhibitory manners [53]. PFAS exposure has also been linked to immune system activation, notably through the AIM2 inflammasome, resulting in increased proinflammatory cytokine production and subsequent tissue inflammation [54]. This suggests that PFAS exposure may foster chronic low-grade inflammation, disrupt metabolic function, and promote fat accumulation. A pivotal study highlighted the role of PFAS in body weight regulation, revealing that individuals with higher initial plasma PFAS levels experienced more significant weight regain postdieting, particularly among women, which is likely attributable to a decelerated decrease in resting metabolic rate, indicating a direct impact of PFAS on energy expenditure regulation [55].

3. Association with childhood obesity in epidemiological studies

Longitudinal studies on prenatal exposure to PFAS and their association with childhood obesity are presented in Table 1. Research across Europe, the US, and Asia on prenatal exposure to PFAS and childhood obesity has revealed significant findings. Among 28 reviewed studies, 20 suggested that prenatal PFAS exposure could lead to increased adiposity in children, with varying effects reported across studies. Interestingly, some studies suggested that exposure to legacy PFAS compounds such as PFOS and PFOA might be associated with lower adiposity at birth and during infancy but trigger rapid adiposity accretion in early childhood [56-58]. This pattern suggests a possible link between PFAS exposure and the risk of infants born small for gestational age catching up rapidly, which could predispose them to obesity. Additionally, a sex-specific impact is apparent, with girls exhibiting a higher susceptibility to obesity following PFAS exposure, whereas boys show null or negative associations [59,60].

Epidemiological studies, predominantly from Europe and the US, explored the association between postnatal exposure to PFAS and childhood obesity and revealed mixed outcomes (Table 2). Contrary to findings related to prenatal exposure, a significant proportion of these studies (14 of 18) identified negative associations between postnatal PFAS exposure and measures of childhood adiposity such as BMI z scores, WC, and body fat percentage. Importantly, a notable cohort study from the US highlighted that specific PFAS types might influence body composition in children in distinct ways [61]. For instance, higher PFOS and PFHxS levels were linked to decreased subcutaneous fat accumulation, whereas other types, such as perfluorodecanoic acid and perfluorononanoic acid, were associated with increased visceral fat accrual. Visceral fat is of particular concern because of its association with an elevated risk of cardiometabolic disease [62]. These findings imply that postnatal PFAS exposure may not uniformly contribute to obesity but could affect body fat distribution in a way that predisposes children to different health risks, underlining the need for nuanced approaches in assessing the health impacts of PFAS.

Organochlorines

1. General characteristics

Organochlorines, synthetic organic compounds characterized by covalently bonded chlorine atoms, have been extensively used in a range of applications including pesticides (e.g., dichlorodiphenyltrichloroethane [DDT] and lindane), solvents (e.g., carbon tetrachloride and trichloroethylene), and plastic production (e.g., PVC) since the early 20th century [63]. Chlorophenols, another important group within this class, have been utilized in wood preservation, disinfection, and as antiseptics owing to their antimicrobial properties [64]. In addition, some chlorophenols are produced during water chlorination or the bleaching of wood pulp with chlorine [64]. The organochlorine pesticide DDT gained prominence in the 1940s because of its ability to control malaria and other insect-borne diseases [63]. However, the environmental persistence and potential health risks associated with organochlorines, including chlorophenols, led to the restriction or outright ban of these compounds across several countries by the late 20th century [63].

Organochlorines, known for their lipophilicity, accumulate in fatty tissues because of their resistance to metabolic breakdown [65]. Although they undergo limited metabolism in the liver into more water-soluble metabolites, the process is slow, resulting in their gradual excretion, primarily through the feces and, to a lesser extent, urine [66]. The elimination of these compounds from the body can span years and is influenced by specific organochlorines and individual metabolic differences. For instance, the half-life of DDT and its metabolites in humans can extend to several years, with some studies suggesting a potential duration of 10 years or longer [65]. Conversely, chlorophenols exhibit comparatively shorter persistence, with their half-life in the human body ranging from hours to days depending on factors such as the specific chlorophenol compound, environmental exposure levels, and individual metabolic rates [65].

The primary routes of exposure to organochlorines are dietary intake, where they accumulate in the food chain; dermal absorption, particularly in agricultural settings; and inhalation, especially in industrial environments where they are produced or utilized [67].

Biomonitoring typically measures the concentrations and metabolites of organochlorine in the blood and adipose tissue (Supplementary Table 3). This approach effectively indicates the extent of chemical accumulation in individuals and underscores the critical need for ongoing surveillance, particularly among at-risk groups, to manage and mitigate associated health risks [67].

2. Impact on obesity in experimental studies

Evidence from in vitro and in vivo studies suggests a link between organochlorine exposure and obesity, highlighting its potential obesogenic effects (Fig. 1). Organochlorines interfere with thyroid hormone signaling pathways, which are essential for metabolism and energy regulation. In vitro studies have shown that DDT inhibits TSH release and can hinder TSH receptor activity [68]. Additionally, organochlorines facilitate adipogenesis by activating PPARγ in various cell lines, including hepatocytes and 3T3-L1 [69].

Exposure to organochlorines results in epigenetic changes that can lead to obesity and metabolic disorders. Studies have shown that organochlorine exposure can result in hypomethylation of the PPARγ promoter and/or histone H3 (H3K27me3), which promotes adipogenesis and contributes to lipid accumulation and obesity [19].

Organochlorines reduce the thermogenic capacity of brown adipose tissue by affecting the expression of uncoupling protein-1 and β-adrenergic receptors, key components of the thermogenic machinery in brown adipocytes [18]. Moreover, organochlorines have been implicated in increased oxidative stress and inflammation, thereby contributing to the development of insulin resistance and disruption of glucose metabolism [70].

Additionally, organochlorines, including DDT and hexachlorocyclohexane, have been shown to alter the gut microbiota, leading to changes in bile acid metabolism and increased obesity risk in murine models [45].

3. Association with childhood obesity in epidemiological studies

Research investigating the impact of prenatal exposure to organochlorines on childhood obesity has been predominantly conducted in Europe and North America (Table 1). Among these studies, a significant number (17 of 22) indicated that prenatal exposure to organochlorines, such as DDT, PCB, and HCB, is linked to various indicators of adiposity in children. These indicators included the BMI z score, fat mass index, trunk fat percentage, and skinfold thickness. Notably, only a small subset of these studies reported no significant association, highlighting the complex nature of the relationship between prenatal organochlorine exposure and childhood obesity.

Research is relatively sparse on the effects of postnatal organochlorine exposure on childhood obesity (Table 2). Despite the heterogeneity in the chemicals evaluated across these studies, approximately half suggested that such exposure could contribute to increased childhood adiposity as indicated by metrics such as BMI z score, WC, and body fat percentage. However, the other half found no significant or negative relationships. Nonetheless, a study from the US identified a specific increase in adiposity linked to triclosan exposure, with this effect exclusively observed in overweight girls, suggesting that the effects of organochlorine exposure may be contingent on the child's pre-existing body composition [27]. Furthermore, a study from Korea observed a positive association between urinary chlorophenol levels and central adiposity in 7–8-year-old girls [71], which corroborates the findings of similar cross-sectional studies in Iran [72] and the US [73]. These observations highlight the need for comprehensive research to fully elucidate the relationship between postnatal organochlorine exposure and childhood obesity.

Polycyclic aromatic hydrocarbons

1. General characteristics

PAHs are a significant group of organic compounds composed of 2 or more fused aromatic (benzene) rings that are created through incomplete combustion or pyrolysis of organic materials such as coal, oil, gas, wood, garbage, and tobacco [42]. PAHs are ubiquitous in the environment including the air, water, soil, and food. PAHs have been the focal point of environmental health studies for many decades because of their potential carcinogenic and mutagenic properties. In 1983, the United States Environmental Protection Agency identified 16 PAHs as priority pollutants, underscoring concerns regarding their exposure, resilience, and toxicity [43]. These compounds are characterized by low water solubility, low vapor pressure, and high melting and boiling points, which contribute to their stability and persistence in the environment that create long-term ecological and health risks.

PAHs are categorized based on their molecular weights into LMW and HMW types [44]. LMW PAHs, which comprise 2 or 3 aromatic rings, are generally more volatile and water-soluble, which enhances their biodegradability. In contrast, HMW PAHs, which comprise 4 or more aromatic rings, tend to persist in the environment and bioaccumulate because of their stability and lipophilicity. Furthermore, PAHs are classified as alternants, which consist of only 6 carbon benzene rings, or nonalternants, which incorporate rings with fewer than 6 carbon atoms. The symmetrical electron distribution of alternant PAHs contributes to their environmental persistence, whereas nonalternant PAHs, with their irregular structures, may display varied chemical reactivities and environmental behaviors (Supplementary Table 4).

PAH exposure in humans predominantly occurs through inhalation, ingestion, and dermal contact, all of which are linked to various anthropogenic and natural sources [42]. Anthropogenic activities, including waste incineration; production processes in the iron, steel, aluminum, and cement industries; coal-tar pitch and dye manufacturing; and asphalt and rubber tire manufacturing, significantly contribute to environmental PAH pollution. Although less prominent, natural events such as volcanic eruptions and forest fires also contribute to ambient PAH levels. Inhalation exposure arises from air pollution, encompassing tobacco, wood smoke, and asphalt fumes, and presents a common risk, particularly in urban settings and among smokers [42]. Ingestion is another significant route, with PAHs entering the human diet through the consumption of grilled, smoked, or charred food items, including meat and various plant-based foods prepared over open flames that absorb these compounds during cooking [42]. Additionally, dermal contact with contaminated soil, dust, or direct handling of PAH-containing materials in occupational settings poses risks, facilitating the absorption of PAHs through the skin [46].

Upon entering the human body, PAHs undergo metabolism, predominantly in the liver and kidneys, facilitated by cytochrome P450 enzymes [42]. This metabolic process leads to the formation of hydroxy derivatives (OH-PAHs), which are subsequently eliminated via the bile and urine. Moreover, PAHs may accumulate in the adipose tissue and can be secreted in breast milk [74]. The biological half-life of these compounds varies, with 1-hydroxypyrene having a half-life of approximately 3.9 hours, whereas other OH-PAHs have a half-life of 2.5–6.1 hours [75]. In terms of monitoring PAH exposure, 1-hydroxypyrene serves as a commonly used urinary biomarker indicative of PAH exposure a few days before sampling. Other detectable urinary OH-PAHs offer insight into PAH exposure extent and recency (Supplementary Table 4).

2. Impact on obesity in experimental studies

Several laboratory studies elucidated the biological and molecular pathways through which PAHs contribute to obesity development (Fig. 1). A recent study revealed that PAH exposure leads to the increased proliferation of 3T3-L1 preadipocytes and lipogenesis along with elevated expression levels of genes including Fasn, Acaca, Cebpa, Pparg, Fabp4, Plin1, Rarres2, Adipoq, and Retn, which are crucial for adipocyte differentiation and fat cell development [76]. These changes have been associated with altered methylation of target genes, including PPARγ [19].

Benzo [a]pyrene, an extensively studied PAH compound, disrupts the normal process of fat breakdown within adipose tissues by impairing β-adrenergic stimulation, resulting in a notable increase in body weight and fat accumulation in mice [71]. Furthermore, naphthalene metabolites obstruct thyroid hormone receptor-mediated transcription in laboratory settings, potentially decreasing the basal metabolic rate and hindering fat breakdown within adipose tissues [72].

Chronic PAH exposure has been linked to increased expression of inflammatory cytokines (e.g., Tnfα, Il-1β, and Il-6) in fat cells and macrophages, indicating an inflammatory response that may further contribute to obesity [73].

3. Association with childhood obesity from epidemiological studies

Research into the link between prenatal exposure to PAHs and childhood obesity has predominantly relied on personal air monitoring, although such studies are relatively few (Table 1). Cohort studies in the US demonstrated that prenatal exposure to PAHs is associated with increased measures of adiposity in children, such as higher BMI z scores and body fat percentages, particularly at age 5–7 years [77]. Nevertheless, further analyses of BMI growth patterns suggested that the initial differences in adiposity observed in early childhood tend to decrease by adolescence [78].

Research on the association between postnatal exposure to PAHs and childhood obesity primarily used cross-sectional data, predominantly from North America (Table 2). These studies consistently highlighted the potential impact of PAHs on increasing the risk of obesity in children. Notably, NHANES data have shown associations between total urinary levels of PAH metabolites, including naphthalene, and higher instances of overweight and central obesity in the US pediatric population aged 6–19 years [79-81]. Additionally, a national study conducted in Canada observed positive associations between PAH metabolites and central obesity in children aged 3–5 years and 6–18 years, underscoring the pervasive nature of this relationship across different cohorts at younger ages [82]. Remarkably, KoNEHS data identified a significant association between 2-naphthol, a primary naphthalene metabolite, and obesity in Korean children aged 6–11 years, suggesting that regular physical activity might mitigate this effect [42]. These findings underscore the importance of monitoring PAH exposure and advocating preventive measures, including increased physical activity, to protect children against the obesity-related risks associated with environmental pollutants.

Conclusions

Research suggests potential associations between early-life exposure to EDCs, including bisphenols, phthalates, and PAHs, and the risk of obesity in children. This body of research, which encompasses both experimental and epidemiological investigations, underscores the adverse impact of EDCs on key biological processes such as hormonal regulation, metabolic function, and adipogenesis, which may collectively predispose children to obesity. Variability in the observed effects has been noted, likely attributable to differences in the concentration of exposures, timing relative to developmental stages, outcome assessment methods, and potential interactive effects of concurrent exposure to multiple EDCs. While the exact mechanisms remain under investigation, these findings highlight the need for further research to understand how EDC mixtures contribute to pediatric obesity and guide public health strategies for reducing EDC exposure.

Supplementary material

Supplementary Tables 1-4 are available at https://doi.org/10.3345/cep.2024.00556.

Supplementary Table 1.

Biomonitoring of phthalate exposure: common phthalates and their metabolites

cep-2024-00556-Supplementary-Table-1.pdf
Supplementary Table 2.

Overview of widely studied PFAS compounds

cep-2024-00556-Supplementary-Table-2.pdf
Supplementary Table 3.

Organochlorines and their metabolites for biomonitoring

cep-2024-00556-Supplementary-Table-3.pdf
Supplementary Table 4.

Polycyclic aromatic hydrocarbons representatives and their metabolites

cep-2024-00556-Supplementary-Table-4.pdf

Notes

Conflicts of interest

No potential conflict of interest relevant to this article was reported.

Funding

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Fig. 1.

The potential mechanisms of endocrine-disrupting chemicals (EDCs) in the development of obesity. BPA, bisphenol A; PFAS, per- and polyfluoroalkyl substances; PAHs, polycyclic aromatic hydrocarbons.

Table 1.

Prenatal exposure to EDCs and childhood obesity in epidemiologic studies

Study Country Study design Study population
Outcome Biomonitoring parameter Direction of relationship Findings
Sample size (n) Time of sampling Age at outcome (yr)
Bisphenols
Harley (2013) [83] US Cohort 311 1st and 2nd trimesters 9 BMIZ, WC, OV/OB, BF% Urine BPA Negative associations with BMIZ, BF%, and odds of OV/OB in girls, not in boys.
Valvi (2013) [25] Spain Cohort 348 1st and 3rd trimesters 4 BMIZ, WC, OV Urine BPA Positive associations with WC at age 4.
Braun (2014) [22] US Cohort 297 2nd and 3rd trimesters 2-5 BMIZ Urine BPA Positive associations with BMI increase per year from 2-5 yr.
Hoepner (2016) [23] US Cohort 375 3rd trimester 7 BMIZ, FMI, WC, BF% Urine BPA Positive associations with FMI, BF%, and WC at age 7.
Vafeiadi (2016) [24] Greece Cohort 235 1st trimester 4 BMIZ, WC, OB, Skinfolds Urine BPA BPA was negatively associated with BMI and adiposity measures in girls and positively in boys.
Yang (2017) [26] US Cohort 223 3rd trimester 8-14 BMIZ, WC, Skinfolds Urine BPA Positive associations with sum of skinfolds in girls.
Yeung (2019) [27] US Cohort 2920 At birth 0-3 BMIZ Infants’ dried blood spot BPA Positive associations with rapid infant weight gain and early childhood OB.
Braun (2019) [84] Canada Cohort 719 1st trimester 3.5 BMIZ, WC, WHR, Skinfolds Urine BPA Positive associations with waist-to-hip ratio at age 3.5.
Guo (2020) [85] China Cohort 190 At delivery 7 BMIZ, WC, OB Urine BPA Positive associations with WC and central OB at age 7.
Choi (2020) [86] Korea Cohort 59 2nd trimesters 2-8 BMI Urine BPA Methylation at cg19196862 (IGF2R) mediates the association between prenatal exposure and increased BMI at ages 2 and 4.
Berger (2021) [28] US Cohort 309 1st and 3rd trimesters 5 BMIZ, WC, OV Urine BPA No associations with adiposity at age 5.
Güil-Oumrait (2022) [87] Spain Cohort 954 1st and 3rd trimesters 11 BMIZ Urine BPA No associations with BMIZ at age 11.
Sol (2022) [88] Netherlands Cohort 1128 1st, 2nd, and 3rd trimesters 10 BMI, FMI Urine BPA No associations with BMI and FMI at age 10.
Xiong (2023) [30] China Cohort 826 1st, 2nd, and 3rd trimesters 2 BMI trajectories Urine BPA, BPS, BPF Positive associations with low-increasing BMI patterns in offspring's first 2 years.
Phthalates
Valvi (2015) [89] Spain Cohort 391 1st and 3rd trimesters Birth-7 BMIZ, WHR, OV Urine MEP, MiBP, MBzP, MnBP, MEHP, MEHHP, MEOHP, MECPP ∑HMWP was negatively associated with BMIZ at ages 4-7 in boys.
No associations between LMWP and adiposity.
Buckley (2016) [90] US Cohort 180 3rd trimester 2-9 BMIZ, BF% Urine MEP, MnBP, MiBP, MCPP, MBzP, MEHP, MEHHP, MEOHP, MECPP ∑DEHP was negatively associated with BF% at ages 2-9.
No associations between LMWP and adiposity.
Buckley (2016) [91] US Cohort 707 2nd and 3rd trimesters 4-7 BMIZ, OV/OB Urine MEP, MnBP, MiBP, MCPP, MEHP, MEHHP, MEOHP, MECPP MCPP was positively associated with OV/OB at ages 4-7.
MEP was negatively associated with BMIZ in girls.
Harley (2017) [92] US Cohort 345 1st and 2nd trimesters 5-12 BMIZ, WC, BF%, OV Urine MEP, MBP, MiBP, MBzP, MCOP, MCNP, MCPP, MEHP, MEOHP, MEHHP, MECPP MEP, MBzP and ∑DEHP were positively associated with odds for OV at ages 5-12.
MEP was positively associated with BMIZ and BF%.
Shoaff (2017) [93] US Cohort 219 2nd trimesters 8 BMI, WC, BF% Urine MEP, MBzP, MCPP, MnBP, MEHHP, MEOHP, MECPP No associations between phthalate metabolites and adiposity.
Yang (2017) [26] US Cohort 223 3rd trimester 8-14 BMIZ, WC, Skinfolds Urine MEP, MBzP, MEHP, MEHHP, MEOHP, MECPP MBzP was negatively associated with BMIZ.
MBHP was negatively associated with WC and skinfolds.
Vafeiadi (2018) [94] Greece Cohort 500 1st trimester 2-6 BMIZ, WC, WHR Urine MEP, MnBP, MiBP, MBzP, MEHP, MEHHP, MEOHP No associations between phthalate metabolites and adiposity.
Yang (2018) [95] Mexico Cohort 249 3rd trimester Birth-14 BMI trajectories Urine MEP, MiBP, MCPP, MBzP, MEHP, MEHHP, MEOHP, MECPP Highest BMI trajectories for the highest MECPP groups in females.
Highest BMI trajectories for the lowest MiBP, MBzP, MEHP, MEHHP groups in males.
Heggeseth (2019) [96] US Cohort 335 1st and 2nd trimesters 2-14 BMI trajectories Urine MEP, MnBP, MiBP, MBzP, MCOP, MCPP, MEHP, MEOHP, MEHHP, MECPP MEP was positively associated with BMI level across ages.
Bowman (2019) [97] Mexico Cohort 2239 1st, 2nd, and 3rd trimesters 8-17 BMIZ, WC, skinfolds Urine MEP, MiBP, MCPP, MBzP, MEHP, MEHHP, MEOHP, MECPP MBP and MiBP were positively associated with BMIZ in girls.
MBzP was positively associated with BMIZ and WC in boys.
MBzP was negatively associated with skinfold thickness in girls.
Lee (2020) [98] KR Cohort 481 2nd trimesters 6 BMIZ, BF%, SMI Urine MnBP, MEOHP, MEHHP MEHHP was negatively associated with BMIZ at age 6.
Phthalate metabolites were negatively associated with SMI at age 6.
Berger (2021) [28] US Cohort 309 1st and 3rd trimesters 5 BMIZ, WC, OV Urine MEP, MBP, MiBP, MBzP, MCPP, MCOP, MCNP, MEHP, MEHHP, MEOHP, MECPP MEP and MCNP were positively associated with odds of OV at age 5.
Li (2021) [99] China Cohort 814 1st, 2nd, and 3rd trimesters Birth-2 BMIZ Urine MEHP, MEOHP, MEHHP, MECPP DEHP metabolites were negatively associated with fetal growth, but positively associated with BMI in infancy.
Kupsco (2022) [100] Mexico Cohort 514 2nd and 3rd trimesters 4-12 Adiposity trajectory ΣDEHP, ΣDiBP, ΣDiNP, ΣDBP, MBzP, MCPP, MECPTP, MCNP, MEP ΣDEHP was associated with increased odds of being in the “high-high” class.
ΣDiNP was associated with greater odds of being in the “low-high” class.
Ferguson (2022) [101] US Cohort 780 1st and 3rd trimesters Birth-6 BMIZ Urine MEP, MBP, MiBP, MBzP, MCPP, MCOP, MCNP, MEHP, MEHHP, MEOHP, MECPP MEP, MBP, MBzP, and MiBP were negatively associated with BMIZ at birth and positively associated with BMIZ at ages 3-4.
Güil-Oumrait (2022) [87] Spain Cohort 954 1st and 3rd trimesters 11 BMIZ Urine MEP, MnBP, MiBP, MBzP, MEHP, MEHHP, MEOHP, MECPP No associations with BMIZ at age 11.
Gao (2022) [102] China Cohort 990 1st, 2nd, and 3rd trimesters Birth-6 BMI trajectories Urine MMP, MEP, MBP, MBzP, MEHP, MEOHP, MEHHP MEP and DEHP metabolites were positively associated with the highest BMI trajectories in girls.
Gao (2023) [103] China Cohort 2950 1st, 2nd, and 3rd trimesters Birth-6 Adiposity trajectory classes Urine MMP, MEP, MBP, MEHP, MEOHP, MEHHP MEP and phthalate mixture were positively associated with the rapidly increasing ABSI trajectory class.
PFAS
Andersen (2013) [104] Denmark Cohort 811 1st and 2nd trimesters, at delivery 7 BMI, WC, OV Maternal blood PFOS, PFOA No associations with BMI, WC, odds of OV at age 7.
Høyer (2015) [105] Ukraine Cohort 1022 2nd trimesters 5-9 BMI, WHtR Maternal blood PFOS, PFOA PFOS was positively associated with central OB.
Hartman (2017) [106] UK Cohort 359 girls 1st and 2nd trimesters 9 BMI, WC, Fat mass, BF% Maternal blood PFOS, PFOA, PFHxS, PFNA PFOS and PFOA was positively associated with BF% in girls at age 9.
Karlsen (2017) [107] Denmark Cohort 444 Postpartum 2 weeks 1.5-5 BMI Maternal blood PFOS, PFOA, PFHxS, PFNA, PFDA PFOS and PFOA were associated with increased BMI z scores and/or odds of OV.
Chen (2017) [57] Taiwan Cohort 429 At delivery 0-9 BMI Maternal blood PFOS, PFOA PFOS was associated with smaller body size at birth.
PFOS was associated with decreased BMI from 6 months to age 5, and then to increased BMI from ages 5-9.
Manzano-Salgado (2017) [108] Spain Cohort 1154 1st trimester Birth-7 BMIZ, OV Maternal blood PFOS, PFOA, PFNA, PFHxS No associated with BMIZ and odds of OV at ages 4-7.
Mora (2017) [59] US Cohort 1645 1st trimesters 3-7 BMI, WC, fat mass, BF% Maternal blood PFOA, PFOS, PFHxS, PFNA PFASs was associated with increases in adiposity in mid-childhood (mean 7.7 yr) only in girls.
Null association in boys.
Lauritzen (2018) [109] Norway and Sweden Cohort 412 2nd trimesters 5 BMI, Fat mass, BF% Maternal blood PFOS, PFOA PFOS was positively associated with BMIZ at age 5.
Shoaff (2018) [110] US Cohort 334 various 0-2 BMI, WC, BF% Maternal blood PFOS, PFOA, PFHxS, PFNA PFOA was linked to reduced BMI z score changes from 4 weeks to age 2.
Gyllenhammar (2018) [111] Sweden Cohort 182–193 3rd trimester, post­partum 3 weeks Birth-5 BMI Maternal blood PFOA, PFNA, PFDA, PFUnDA, PFHxS, PFOS PFNA, PFDA and PFUnDA were associated with reduced birth weight.
PFOA, PFNA, PFHxS, and PFOS were associated with increased childhood BMI.
Yeung (2019) [27] US Cohort 2920 At birth 0-3 BMIZ Infants’ dried blood spot PFOA, PFOS PFOS and PFOA was associated with lower BMI in early childhood.
Chen (2019) [112] China Cohort 404 At birth 5 BMI, WC, fat mass, BF%, WHtR Cord blood PFBS was positively associated with adiposity in girls.
PFOS, PFOA, PFNA, PFDA, PFUA, PFDoA, PFHxS, PFBS No associations in boys.
Martinsson (2020) [113] Sweden Cohort 1048 2nd trimesters 4 BMI, OV Maternal blood PFOS, PFOA, PFHxS, PFNA No associations with BMIZ and OV at age 4.
Vrijheid (2020) [114] Europe Cohort 1301 various 6-11 BMIZ, WCZ, Skinfolds, Fat mass Maternal blood PFOS, PFOA, PFHxS, PFNA, PFUnDA No associations with adiposity and odds of OV at ages 6-11.
Li (2021) [115] US Cohort 221 various 12 WC, Fat mass Maternal blood PFOS, PFHxS, PFOA, PFNA PFOA and PFHxS were positively associated with WC at age 12.
Horikoshi (2021) [58] Japan Cohort 597 At birth 1-5 BMI trajectories Cord blood PFOS and PFOA was associated with lower BMI during infancy, then associated with an increase in BMI in childhood.
PFOS, PFOA
Papadopoulou (2021) [116] UK, France, Spain, Lithuania, Norway, Greece Cohort 1101 2nd and 3rd trimesters 6-12 WC Maternal blood PFOA, PFNA, PFHxS, PFOS -PFNA was positively associated with WC.
Braun (2021) [56] US Cohort 345 various 0-12 BMI trajectories Maternal blood PFOA, PFOS, PFNA, PFHxS PFOA was associated with specific BMI trajectory pattern: lower infancy BMI, earlier BMI nadir, accelerated mid-childhood BMI gain, and higher BMI by age 12.
Zhang (2022) [60] China Cohort 206 At delivery 7 BMI, Fat mass, BF%, WC, WHtR, OV Maternal blood PFOA, PFOS, PFNA, PFDA, PFUA, PFHxS, PFDoA, PFBS, PFOSA, PFHpA PFHpA and PFOSA was negatively associated with adiposity.
PFAS mixture was negatively associated with adiposity in boys.
PFAS mixture was positively associated with adiposity in girls.
Bloom (2022) [117] US Cohort 803 1st trimester 4-8 BMI, WC, Fat mass, BF% Maternal blood PFHxS, PFOS, PFOSA, PFDS, PFOSA, PFDS, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA PFUnDA was positively associated with adiposity (fat mass and BF%) at age 4-8.
Higher PFASs were associated with higher adiposity in NHB and Asian/ Pacific islanders
Higher PFASs were associated with lower adiposity in NHW and Hispanics.
Sevelsted (2022) [118] Denmark Cohort 675 2nd trimesters, postpartum week 1 6-10 BMI, BF% Maternal blood PFOS, PFOA PFOS was linked to lower BMI and BF% in girls but higher BMI and BF% in boys at age 6.
Cai (2023) [119] Belgium Cohort 346 At birth Birth-8 BMIZ Cord blood No associations with BMI trajectories during infancy and childhood.
BMI trajectories PFOS, PFOA
Zhang (2023) [120] US Cohort 545 1st and 2nd trimesters 16-20 BMIZ, OB, BMI trajectories Maternal blood PFOS, PFOA, PFHxS, PFNA, EtFOSAA, MeFOSAA PFOS and PFNA were associated with higher OB risk at aged 16-20.
PFOS, EtFOSAA, and MeFOSAA were associated with higher rates of BMI gain after ages 9-11.
Dai (2023) [121] China Cohort 887 At birth Birth-10 BMI trajectories Cord blood Five PFAS congeners (PFBA, PFHpA, PFHxS, PFHpS, and PFDoDA) were associated with the high BMI trajectory group.
PFOS, PFOA, PFNA, PFDA, PFUnDA, PFDoA, PFDS, PFOSA, PFBS, PFHxS, PFHpA, PFHpS,
Cano-Sancho (2023) [122] Spain Cohort 1241 1st trimester 7 BMIZ, OV Maternal blood PFNA was associated with increased risk of OV at age 7.
PFOS, PFOA, PFHxS, PFNA
Starling (2024) [123] US Cohort 373 2nd and 3rd trime­sters 5 BF%, Fat mass, FMI, BMI Maternal blood PFOA and PFNA was positively associated with early childhood adiposity.
PFOS, PFOA, PFHxS, PFNA, PFDA No associations between PFAS mixtures and adiposity.
Sun (2024) [124] China Cohort 573 1st and 2nd trime­sters 4-6 BMIZ, WC, OV Maternal blood PFNA was positively associated with adiposity at ages 4-6.
PFOS, PFOA, PFNA, PFHxS, PFDA, PFUdA, PFTrDA, PFDoA PFOS, PFNA, PFUdA, PFTrDA were associated with risk of OV in age 6.
Chen (2024) [125] Singapore Cohort 783 At birth Birth-6 BMIZ, Fat mass, MRI-derived abdominal adiposity, OV Cord blood Short-chain PFAS was associated with higher abdominal adiposity at birth but not at age 6 years.
PFOS, PFOA, PFNA, PFDA, PFUnDA, PFDoA, PFDS, PFOSA, PFBS, PFHxS, PFHpA, PFHpS,
Organochlorine
Gladen (2000) [126] US Cohort 594 females various 14 Weight adjusted for height Maternal blood, cord blood, placenta DDE, PCB PCB was associated with higher weight for height in girls.
DDE was associated with higher weight for height in boys.
Gladen (2004) [127] US Cohort 304 males 3rd trimester 10-20 BMI, skinfolds, central OB Maternal blood o,p′-DDT, p,p′-DDT, p,p′-DDE No associations with adiposity in male adolescents.
Smink (2008) [128] Spain Cohort 482 At birth 6.5 BMI, OV, OB Cord blood HCB was associated with an increase in BMI and risk of OV/OB.
HCB
Cupul-Uicab (2013) [129] US Cohort 1915 3rd trimester 7 BMIZ, OV Maternal blood p,p′-DDT, p,p′-DDE, β-HCH, HCB, ∑PCB No associations with adiposity at age 7.
Valvi (2012) [130] Spain Cohort 344 1st trimester 6.5 OV ∑PCB, PCB-118, PCB-138, PCB-153, PCB180, DDE, DDT PCB and DDE was associated with increased risk of OV.
DDT was associated to OV in girls only.
Delvaux (2014) [131] Belgium Cohort 114 At birth 7-9 BMIZ, WC, WHtR Cord blood p,p'-DDE was associated with higher WC and WHtR in girls.
p,p′-DDE, HCB, ∑PCB
Dallaire (2014) [132] Canada Cohort 290 At birth 8-14 BMIZ Cord blood PCB-153 was associated with increased child BMI.
PCB-153
Tang-Péronard (2014) [133] Denmark Cohort 539 3rd trimester 5-7 BMI, WC Maternal blood DDE, ∑PCB PCB was associated with WC in 7-year-old girls.
DDE was associated with WC in 7-year-old girls only with overweight mothers.
Vafeiadi (2015) [181] Greece Cohort 531-689 1st trimester 0.5-4 BMIZ, central OB, skin folds p,p′-DDT, p,p′-DDE, p,p′-DDD, ∑DDTs, α-HCH, β-HCH, γ-HCH, ∑HCHs HCB was associated with a higher BMIZ, central OB, and greater sum of skinfold thickness.
DDE exposure was associated with higher BMIZ and central OB.
Agay-Shay (2015) [134] Spain Cohort 470 1st trimester 7 BMIZ,OV Maternal blood HCB, βHCH, PCB-138 and 180 were associated with increased BMI z scores.
DDE, HCB, βHCH, PCB-138, PCB-153, PCB-180 HCB, βHCH, PCB-138, and DDE were associated with higher OV risk.
Heggeseth (2015) [135] US Cohort 249 3rd trimester and at birth 2-7 BMI trajectories Maternal blood o,p′-DDT, p,p′-DDT, p,p′-DDE DDT and DDE are associated with a BMI growth pattern that is stable until age 5, then to increased growth up to age 9 in boys.
Warner (2017) [136] US Cohort 240 2nd trimester and at delivery 12 BMIZ, WC, BF% Maternal blood DDE and DDT were positively associated with BMIZ and WC at age 12 in boys.
o,p′-DDT, p,p′-DDT, p,p′-DDE
Karlsen (2017) [107] Denmark Cohort 444 Postpartum 2 weeks 1.5-5 BMI Maternal blood HCB was associated with increased BMI z scores and/or OV risk.
HCB, p,p’-DDE, PCB-138, PCB-153, PCB-180 No associations for PCBs, p,p’-DDE.
Lauritzen (2018) [109] Norway and Sweden Cohort 412 2nd trimester 5 BMI, Fat mass, BF%, OV Maternal blood PCB 153 was positively associated with BMIZ at age 5.
PCB 153, p,p’-DDE, HCB, β-HCH, t-NC
Kalloo (2018) [137] US Cohort 218 2nd trimester 8 BMIZ, WC, BF% Maternal urine No associations with adiposity at the age of 8.
Triclosan
Wang (2019) [138] UK Cohort 339 girls 1st and 2nd trimesters 9 BMI, BF%, FMI, Trunk Fat % Maternal blood No associations with adiposity at age 9 in girls.
PCB-118, PCB-138, PCB-153, PCB-180
Tahir (2020) [139] Canada Cohort 212 At birth 11 BMI, FMI Cord blood In girls, PCB 153 was associated with BMI and FMI.
PCB 153
Vrijheid (2020) [114] Europe Cohort 1301 various 6-11 BMIZ, WCZ, Skinfolds, Fat mass Maternal blood DDE, HCB, and sum of PCBs were associated with lower BMI.
DDE, HCB, PCBs (118, 138, 153, 170, 180)
Güil-Oumrait (2021) [140] Spain Cohort 379 At birth 4-18 BMIZ, WC, BF %, OV Cord blood HCB was associated with higher BMIZ and elevated BF% at age 14.
p,p’-DDE, HCB, PCB-138, PCB-150, PCB-180 DDT was associated with BMIZ.
Berger (2021) [28] US Cohort 309 1st and 3rd trimesters 5 BMIZ, WC, OV Maternal blood No associations with adiposity at age 5.
Triclosan, 2,4 DCP, 2,5-DCP
Cai (2023) [119] Belgium Cohort 346 At birth Birth-8 BMIZ, BMI trajectories Cord blood PCB-153 was associated with ΔBMIZ from 0 to 2 years.
p,p’-DDE, HCB, PCB-138, PCB-150, PCB-180 No associations with BMI trajectories during childhood.
Rouxel (2023) [141] France and Spain Cohort 1667 1st trimester 12 BMIZ, BF% Maternal blood PCB 138, 153 and 180, p,p'-DDE, β-HCH, HCB HCB and β-HCH were associated with higher BMIZ and BF% at age 12
Cano-Sancho (2023) [122] Spain Cohort 1241 1st trimester 7 BMIZ, OV Maternal blood HCB was positively associated with BMIZ and risk of OV.
DDE, HCB, βHCH, PCB-138, PCB-153, PCB-180 βHCH was positively associated with risk of OV.
PAHs
Rundle (2012) [77] US Cohort 702 3rd trimester 5-7 BMIZ, BF%, OB Personal air monitoring; Sum of 8 HMW PAHs PAH exposures was associated with higher BMIZ and obesity at age 5-7.
Rundle (2019) [78] US Cohort 505 3rd trimester 5-14 BMIZ trajectories Personal air monitoring; Sum of 8 HMW PAHs PAH exposures were associated with higher BMIZ and obesity at age 5-7.
With age, the differences in BMIZ tends to be diminished.
Kehm (2021) [142] US Cohort 196 girls 3rd trimester 11-20 BMIZ, WHtR, BF% Personal air monitoring; Sum of 8 HMW PAHs No associations with adiposity at age 11-20.

Direction of associations with adiposity: ▲, positive; ▽, negative; ↔, null.

Σ2-,3-OH-Flu, Σ2-,3-hydroxyfluorene; Σ2-,3-OH-Phe, Σ2-,3-hydroxyphenanthrene; 1-OH-Phe, 1-hydroxyphenanthrene; 1-OH-Pyr, 1-hydroxypyrene; 4-OH-Phe, 4-hydroxyphenanthrene; BF%, body fat percentage; BMIZ, body mass index z score; BPA, bisphenol A; DDE, dichlorodiphenyldichloroethane; EDCs, endocrine-disrupting chemicals; EtFOSAA, 2-(N-ethyl-perfluorooctane sulfonamide) acetate; FMI, fat mass index; HMW, high molecular weight; KR, Republic of Korea; LMW, low molecular weight; MBP, mono-n-butyl phthalate; MBZP, monobenzyl phthalate; MCINP, monocarboxyisonyl phthalate; MCIOP, mono-(4-methyl-7carboxyheptyl) phthalate; MCMHP, mono-[2-(carboxymethyl)hexyl] phthalate; MCNP, Mono(carboxy-isononyl) phthalate; MECPP mono-(2-ethyl-5-carboxypentyl) phthalate; MECPTP, Mono-2-ethyl-5-carboxypentyl terephthalate; MeFOSAA, 2-(N-methyl-perfluorooctane sulfonamide) acetate; MEHP, mono(2-ethylhexyl) phthalate; MEHHP, mono-(2-ethyl-5-hydroxylhexyl) phthalate; MEOHP, mono-(2-ethyl-5-oxohexyhl) phthalate; MEP, monoethyl phthalate; MHINP, mono(4-methyl-7-hydroxyoctyl) phthalate; MOINCH, mono-oxo isononyl oxy carbonyl cyclohexane carboxylic acid; MOINP, mono-(4-methyl-7-oxo-octyl) phthalate; MPHHP, 6-hydroxy-monopropylheptyl phthalate; NHB, Non-Hispanic Blacks; NHW, Non-Hispanic Whites; OB, obesity; OV, overweight; PAHs, polycyclic aromatic hydrocarbons; PCB, polychlorinated biphenyl; PFAS, per- and polyfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFDoA, perfluorododecanoic acid; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFTrDA, perfluorotridecanoic acid PFUdA, perfluoroundecanoic acid; SMI, skeletal muscle index; t-NC, trans-nonachlor; WC, waist circumference; WHtR, waist-to-height ratio.

Table 2.

Postnatal exposure to EDCs and childhood obesity in epidemiologic studies

Study Country Study design Study population
Outcome Biomonitoring parameter Direction of relationship Findings
Sample size (n) Time of sampling Age at outcome (yr)
Bisphenols
Trasande (2012) [143] US Cross-sectional 2,338 6-19 6-19 BMIZ, OB Urine BPA Positive associations with BMIZ and odds of OB.
Wang (2012) [144] China Cross-sectional 259 8-15 8-15 BMI Urine BPA Positive associations with BMIZ in girls aged 8-11 yr.
Eng (2013) [145] US Cross-sectional 3,370 6-18 6-18 OB, central OB Urine BPA Positive associations with OB and central OB.
Li (2013) [146] China Cross-sectional 1,326 9-18 9-18 OV, central OB Urine BPA Positive associations with OV and central OB in girls aged 9-12 yr.
Harley (2013) [83] US Cross-sectional 311 5, 9 5, 9 BMIZ, WC, OV, BF% Urine BPA No associations with adiposity at age 5.
Positive associations with adiposity at age 9.
Vafeiadi (2016) [24] Greece Cross-sectional 494 4 4 BMIZ, WC, OB, Skinfolds Urine BPA Positive associations with BMIZ, WC, and sum of skinfolds at age 4.
Li (2017) [147] US Cross-sectional 1,860 8-19 8-19 FMI, BF% Urine BPA Positive associations with elevated FMI and BF% in girls.
Deierlein (2017) [31] US Cohort 1,017 6-8 7-15 BMI, WC, BF% Urine BPA No associations with adiposity at ages 7-15.
Yang (2017) [26] Mexico Cross-sectional 249 8-14 8-14 BMI, WC, BF% Urine BPA Positive associations with BMI z score only in girls.
Okubo (2019) [33] US Cross-sectional 5,419 6-19 6-19 BMIZ, OB Urine BPA Children with higher urinary BPA concentrations had elevated odds of obesit y during 2003 to 2008, whereas these associations were inconsistent during 2009 to 2014.
Mustieles (2019) [148] Spain Cross-sectional 298 Boys 9-11 9-11 BMIZ, WHtR, Fat mass, OV, central OB Urine BPA BPA was associated with increased BMIZ and WHtR, as well as greater odds of OV and central OB.
Wu (2020) [149] US Cross-sectional 2,372 6-19 6-19 BMIZ, OB Urine BPA In the WQS regression model for OB, the WQS index significantly correlated with the outcome. 2,5-DCP (0.41), BPA (0.17), and MEP (0.14) were notably weighted.
Gajjar (2022) [32] US Cohort 212 8 12 BMIZ, WC, BF% Urine BPA, BPS No associations with adiposity at age 12.
Seo (2022) [34] KR Cross-sectional 2,351 3-17 3-17 BMIZ, OB Urine BPA No associations with adiposity at ages 3-17.
Deodati (2023) [150] Europe Cross-sectional 122 5-10 5-10 BMI, OB Urine BPA Positive association with OB in girls.
Phthalate
Teitelbaum (2012) [151] US Cohort 387 Hispanic and Black 6-8 After 1 year BMI, WC Urine MBP, MEP, MiBP, MCPP, MECPP, MEHHP, MEOHP, MEHP, MBzP Baseline MEP and ΣLMW phthalates were associated with an increase in adiposity over 1 year follow up.
Trasande (2013) [152] US Cross-sectional 2,884 6-19 6-19 BMIZ, OV, OB Urine MBP, MEP, MiBP, MCPP, MECPP, MEHHP, MEOHP, MEHP, MBzP ΣLMW phthalates was associated with higher BMIZ and odds for OV and OB in NHB.
Wang (2013) [153] China Cross-sectional 259 8-15 8-15 BMI, WC Urine MEHP, MEHHP, MEOHP, MCMHP, MECPP, MCHP, MBzP, MBP, MHBP, MEP, MiBP, MMP MEP and MEHP were positively associated with BMI and WC.
Zhang (2014) [154] China Cross-sectional 493 8-13 8-13 BMIZ, WC, BF%, skinfolds, OB Urine MEHP, MEHHP, MEOHP, MBP, MMP, MEP MEP and ΣLMW phthalates were associated with higher odds for OB in boys.
MEHP, MEHHP and ΣMEHP were associated with lower odds for OB in girls.
Hou (2015) [155] Taiwan Cross-sectional 270 6-15 6-15 BMI, WC, WHtR, skinfolds Urine MMP, MEP, MiBP, MnBP, MBzP, MEHP, MEOHP, MEHHP, MECPP MEP and DEHP metabolites were associated with adiposity.
Yang (2017) [26] Mexico Cross-sectional 249 8-14 8-14 BMI, WC, BF% Urine MEHP, MEHHP, MEOHP, MECPP, MCPP, MBzP, MEP, MiBP, MBP MEHP was inversely associated with sum of skinfold thickness in boys.
Kim (2018) [156] KR Cross-sectional 137 girls 6-13 6-13 BMIZ, WC, BF%, central OB Urine MEHP, MEHHP, MEOHP, MECPP Percentage fraction of MEHHP among the DEHP metabolites was positively associated with central OB in prepubertal girls.
Amin (2018) [157] Iran Cross-sectional 242 6-18 6-18 BMI, WC Urine MMP, MBP, MBzP, MEHP, MEHHP, MEOHP All of the measured phthalate metabolites were associated with higher BMI and WC.
Wu (2020) [149] US Cross-sectional 2,372 6-19 6-19 BMIZ, OB Urine MBzP, MEP, MiBP In the WQS regression model for OB, the WQS index significantly correlated with the outcome. 2,5-DCP (0.41), BPA (0.17), and MEP (0.14) were notably weighted.
Dong (2022) [158] China Cross-sectional 829 7-13 7-13 OV Urine MMP, MEP, MBP, MiBP, MEHP, MEOHP, MEHHP ΣPhthalates, MEP, MBP, MiBP, MEHP, and MEHHP were associated with increased odds for OV.
Seo (2022) [34] KR Cross-sectional 2,351 3-17 3-17 BMIZ, OB Urine MnBP, MBzP, MCOP, MCNP, MCPP, MEHHP, MEOHP, MECPP MECPP was associated with higher odds for OB.
Wang (2023) [159] China Cross-sectional 798 7-10 7-10 WC, central OB Urine MMP, MEP, MBP, MiBP, MEHP, MEOHP, MEHHP MEP and MiBP were associated with higher odds for central OB.
Li (2023) [160] China Cross-sectional 240 6-8 6-8 BMI, OB Urine MMP, EP, MnBP, MiBP, MEHP, MEOHP, MEHHP, MCEPP, MCMHP No associations with OB at ages 6-8.
Deodati (2023) [150] Europe Cross-sectional 122 5-10 5-10 BMI, OB Urine MEHP, MEOHP, MEHHP The first step of DEHP metabolic rate was significantly higher in obese girls.
PFAS
Domazet (2016) [161] Denmark Cohort 501 9-15 15-21 BMI, WC, BF%, OV, skinfolds Urine PFOS, PFOA PFOS was associated with elevated BMI, skinfolds, WC at ages 15-21.
Karsen (2017) [107] Denmark Cross-sectional 444 5 5 BMI Urine PFOS, PFOA, PFHxS, PFNA, PFDA PFNA and PFDA were negatively associated with BMI at age 5.
Harris (2017) [162] US Cross-sectional 653 6-10 6-10 BMI Blood PFOS, PFOA, PFHxS, Me-PFOSA-AcOH PFOA and PFDA were related with lower BMI.
Pinney (2019) [163] US Cohort 704 girls 6-8 18 BMI, WHtR Blood PFOA Baseline PFOA exposure was negatively associated with BMI and WHtR at age 18.
Fassler (2019) [164] US Cross-sectional 353 girls 6-8 6-8 BMI, WHtR, BF% Blood PFOA, PFOS, PFDA PFOA was negatively associated with BMIZ and BF%.
Scinicariello (2020) [165] US Cross-sectional 600 3-11 3-11 BMI Blood PFOA, PFNA, PFHxS, PFOS In boys, PFHxS was associated with decreased BMIZ.
Vrijheid (2020) [114] Europe Cross-sectional 1,301 6-11 6-11 BMIZ, WCZ, skinfolds, fat mass Blood PFOS, PFOA, PFHxS, PFNA, PFUnDA PFOA was negatively associated with BMIZ.
Domazet (2020) [166] Denmark Cross-sectional 242 9 9 BMI, BF%, fat mass Blood PFOS, PFOA, PFNA, PFDA, PFHxS PFNA, PFDA, and PFHxS were associated with decreased fat mass at age 9.
Li (2021) [167] China Cross-sectional 189 8-12 8-12 BMI, OV Blood PFHxA, PFHpA, PFBS, PFOA, PFBS, PFHxS, PFOS, PFHpA Obese/overweight children had lower levels of PFHpA, PFBS, and PFOS.
Papadopoulou (2021) [116] UK, France, Spain, Lithu­ ania, Norway, Greece Cross-sectional 1,101 6-12 6-12 WC Blood PFOA, PFNA, PFHxS, PFOS, PFUnDA PFAS mixture was negatively associated with WC.
Geiger (2021) [168] US Cross-sectional 2,473 12-18 12-18 BMI, WC, OV Blood PFOA, PFOS PFOA was associated with higher risk of OV.
Averina (2021) [169] Norway Cross-sectional 940 15-19 15-19 OB Blood ΣPFAS, PFOS, PFOA, PFNA, PFDA, PFUnDA, PFHpS PFHxS and PFHpS were positively associated with OB.
Canova (2021) [170] Italy Cross-sectional 6,669 8-11, 4-19 8-11, 4-19 BMI Blood PFOA, PFOS, PFNA PFAS mixture was negatively associated with BMI.
2,693
Janis (2021) [61] US Cohort 537 6-10 6-10, 11-16 BMIZ, total FMI, truncal FMI, LMI Blood PFOA, PFOS, PFDA, PFHxS, MeFOSAA, PFNA PFOS and PFHxS were related with less accrual of SQ fat mass.
PFDA and PFNA were related with greater accrual of truncal fat mass.
Li (2021) [115] US Cohort 221 3, 8, 12 12 WC, fat mass Blood PFOS, PFHxS, PFOA, PFNA No associations with adiposity at age 12.
Thomsen (2021) [171] Denmark Cross-sectional 109 10-14 10-14 BF% Blood PFOA, PFOS, PFDA, PFHxS PFOS and PFDA were related with less BF%.
Sevelsted (2022) [118] Denmark Cohort 533 6-18 months 6-10 BMI, BF% Blood PFOS, PFOA No associations with adiposity at age 6-10.
Schillemans (2023) [172] Europe Cross-sectional 1,957 12-18 12-18 BMIZ Blood PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFBS, PFHxS, PFHpS, PFOS Most PFASs were negatively associated with BMI.
Organochlorine
Dhooge (2010) [173] Belgium Cross-sectional 1,679 14-15 14-15 BMI Blood PCB-118, 138, 153, 180, HCB, p,p-DDE, HCB and ΣPCBs were negatively associated with BMI.
PCB-118 was positively associated with BMI.
Buser (2014) [174] US Cross-sectional 1,298 6-19 6-19 BMIZ, WC, OB Urine 2,4-DCP, 2,5-DCP, Triclosan 2,4-DCP and 2,5-DCP were positively associated with BMIZ, WC, and odds of OB among adolescents aged 12-19.
Li (2015) [175] US Cross-sectional 2,898 6-19 6-19 BMI, WC Urine Triclosan Negatively associated with BMI and WC.
Tang-Péronard (2015) [176] Denmark Cohort 509 8-10 8-10, 14-16, 20-22 BMIZ, BF%, WC, OB Urine PCBs-138, 153, 180, p,p-DDE, HCB No associations with subsequent adiposity after exposure.
Xue (2015) [177] India Cross-sectional 103 2-14 2-14 OB Urine Triclosan No associations with OB.
Lee (2016) [178] KR Cohort 158 7-9 After 1 yr BMIZ Blood PCB (1, 3, 4, 15, 19, 28, 37, 77, 81, 104, 105, 114, 123, 126, 155, 157, 167, 169, 188, 189, 202, 205, 206, 208), ox ychlordane, chlordane, heptachlor, heptachlor epoxide, a-HCH, g-HCH, d-HCH, o, p’-DDT, p,p’-DDD, o,p’-DDD, o,p’-DDE No associations with ΔBMI after 1 year.
Deierlein (2017) [31] US Cohort 1,017 6-8 7-15 BMI, WC, BF% Urine Enterolactone, 2,5-DCP, Triclosan Triclosan was positively associated with adiposity only among overweight girls.
Karlsen (2017) [107] Denmark Cross-sectional 349 5 5 BMIZ, WC Serum PCB 138, 153, 180, HCB, p,p’-DDE Negatively associated with BMI and WC.
Parastar (2018) [179] Iran Cross-sectional 242 6-18 6-18 BMIZ, WC Urine 2,4-DCP, 2,5-DCP, 2,4,5-TCP, 2,4,6-TCP Positively associated with adiposity at ages 6-18.
Kalloo (2018) [137] US Cohort 218 1-8 8 BMIZ, WC, BF% Urine Triclosan No associations with adiposity at the age of 8.
Wu (2020) [149] US Cross-sectional 2,372 6-19 6-19 BMIZ, OB Urine 2,4-DCP and 2,5-DCP In the WQS regression model for OB, the WQS index significantly correlated with the outcome. 2,5-DCP (0.41), BPA (0.17), and MEP (0.14) were notably weighted.
Seo (2021) [180] KR Cross-sectional 165 girls 7-8 7-8 BMI, WC, WHtR Urine 2,4-DCP, 2,5-DCP, 2,4,5-TCP, 2,4,6-TCP ΣChlorophenols was associated with WC and WHtR.
PAHs
Scinicariello (2014) [80] US Cross-sectional 3,189 6-19 6-19 BMIZ, WC, OV Urine 1-naphthol, 2-naphthol, 2-fluorene, 3-fluorene, 1-phenanthrene, 2-phenanthrene, 3-phenanthrene ΣPAHs and ΣNaphthalene metabolites were associated with risk of OV in ages 6-11.
Kim (2014) [79] US Cross-sectional 1,985 6-18 6-18 OB, central OB, WC Urine 1-naphthol, 2-naphthol, 2-fluorene, 3-fluorene, 1-phenanthrene, 2-phenanthrene, 3-phenanthrene ΣPAHs was associated with higher BMI and WC.
Poursafa (2018) [179] Iran Cross-sectional 186 6-18 6-18 OB, Central OB, WC Urine 1-naphthol, 2-naphthol, 1-hydroxypyrene, 9-phenanthrene ΣPAHs is associated with OB.
Bushnik (2020) [82] Canada Cross-sectional 3,667 3-18 3-18 BMI, WC, WHtR, central OB Urine naphthalene, fluorene, phenanthrene, pyrene metabolites ΣPAHs and ΣNaphthalene metabolites were associated with WHtR in ages 3-5, and associated with BMI, WC, and WHtR in ages 6-18.
Uche (2020) [81] US Cross-sectional 50,048 6-17 6-17 BMI, WC, WHtR, central OB Urine 2-naphthol, 9-fluorene, 1-phenan­ threne, 2-phenanthrene Phthalate metabolites were associated with obesity.
Kim (2023) [42] KR Cross-sectional 2,286 3-17 3-17 BMIZ, OV Urine 2-naphthol, 2-hydroxyfluorene, 1-OH-phenanthrene, 1-hydroxypyrene 2-naphthol was associated with higher BMIZ and odds of overweight.

Direction of associations with adiposity: ▲, positive; ▽, negative; ↔, null.

1-OH-Phe, 1-hydroxyphenanthrene; 1-OH-Pyr, 1-hydroxypyrene; 2-,3-OH-Flu, 2-,3-hydroxyfluorene; 2-,3-OH-Phe, 2-,3-hydroxyphenanthrene; 4-OH-Phe, 4-hydroxyphenanthrene; BF%, body fat percentage; BMIZ, body mass index z score; BPA, bisphenol A; BPS, bisphenol A; DDE, dichlorodiphenyldichloroethane; EDCs, endocrine-disrupting chemicals; EtFOSAA, 2-(N-ethyl-perfluorooctane sulfonamide) acetate; FMI, fat mass index; HMW, high molecular weight; KR, Republic of Korea; LMI, lean mass index; LMW, low molecular weight; MBP, mono-n-butyl phthalate; MBZP, monobenzyl phthalate; MCEPP, mono(2-ethyl-5-carboxypentyl) phthalate; MCINP, monocarboxyisonyl phthalate; MCIOP, mono-(4-methyl-7carboxyheptyl) phthalate; MCMHP, mono-[2-(carboxymethyl)hexyl] phthalate; MCNP, mono(carboxy-isononyl) phthalate; MECPP, mono-(2-ethyl-5-carboxypentyl) phthalate; MECPTP, mono-2-ethyl-5-carboxypentyl terephthalate; MeFOSAA, 2-(N-methyl-perfluorooctane sulfonamide) acetate; MEHHP, mono-(2-ethyl-5-hydroxylhexyl) phthalate; MEHP, mono(2-ethylhexyl) phthalate; MEOHP, mono-(2-ethyl-5-oxohexyhl) phthalate; MEP, monoethyl phthalate; Me-PFOSA-AcOH, 2-(N-methyl-perfluorooctane sulfonamide) acetate MHBP, mono(4-hydroxybutyl) phthalate; MHINP, mono(4-methyl-7-hydroxyoctyl) phthalate; MOINP, mono-(4-methyl-7-oxo-octyl) phthalate; MOINCH, mono-oxo isononyl oxy carbonyl cyclohexane carboxylic acid; MPHHP, 6-hydroxy-monopropylheptyl phthalate; NHB, Non-Hispanic Blacks; NHW, Non-Hispanic Whites; OB, obesity; OV, overweight; PAHs, polycyclic aromatic hydrocarbons; PCB, polychlorinated biphenyl; PFAS, per- and polyfluoroalkyl substances; PFDA, perfluorodecanoic acid; PFDoA, perfluorododecanoic acid; PFHpS, perfluoroheptane sulfonate; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PFTrDA, perfluorotridecanoic acid; PFUdA, perfluoroundecanoic acid; SMI, skeletal muscle index; SQ, subcutaneous; t-NC, trans-nonachlor; WC, waist circumference; WHtR, waist-to-height ratio.