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. 2025 Sep 11;4(1):97–106. doi: 10.1021/envhealth.5c00129

Occurrence Patterns of Bisphenol Analogues in Human Blood, Subcutaneous Fat, and Visceral Fat

Peng Jiao †, Yue Gao ‡,§, Aijing Li ‡, Zhenhua Lu ∥, Mei Du ‡,§, Jinghai Song ∥,*, Maoyong Song ‡,*
PMCID: PMC12813706  PMID: 41562030

Abstract

Bisphenol analogues (BPs) are well-established endocrine-disrupting chemicals (EDCs). While they are generally not classified as persistent organic pollutants due to their relatively rapid metabolism and urinary excretion, a fraction can accumulate in tissues, including the adipose. This bioaccumulation raises concerns about the potential for prolonged endocrine disruption and chronic toxicity. This study investigated the distribution and accumulation of nine BPs in human blood, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). By comparing the detection rates and concentrations of BPs in paired blood and adipose samples, we found that certain BPs (particularly BPF, BPE, and BPA-G) exhibit preferential accumulation in adipose tissues. The accumulation propensity was slightly higher in SAT than in VAT. Correlation analysis revealed that the sources of the same BP in VAT and SAT were highly consistent, whereas most BPs in adipose tissues had significantly different sources compared with those in blood. Further analysis suggested that age and obesity might be key factors influencing the differential accumulation of BPs in adipose tissues. Since accumulated BPs can be slowly or substantially released during lipolysis, our findings highlight that the adipose tissue reservoir of BPs may play an important role in their long-term toxic effects.

Keywords: bisphenol analogues, human exposure, distribution, adipose, accumulation

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1. Introduction

Bisphenol A (BPA) is one of the chemicals with the highest production volume globally. BPA has been widely used in the production of polymers such as polycarbonate, e. The extensive exposure of BPA to humans and its associated health hazards ha poxy resin, polysulfone, and polyacrylate have led many countries to formulate relevant regulations to restrict the use of BPA. Therefore, many chemicals have been used as alternatives to BPA in industrial production. For example, bisphenol S (BPS) is gradually replacing BPA in the production of consumer goods such as can coatings, thermal paper, and baby bottles. These chemicals are collectively referred to as bisphenol analogues (BPs) because they have a chemical structure similar to that of BPA. Compared to BPA, the potential toxicity of most BPs remains poorly understood. Even so, the production and application of these BPs have been increasing in recent years, − raising human exposure.

Numerous BPs have been detected in various human samples including urine, blood, breast milk, umbilical cord blood, and placenta. In most cases, BPA remains the most abundant bisphenol analogue in human samples. Gao et al. reported the internal exposure levels of BPs in the serum of populations from typical urban industrial areas, identifying the presence of BPA, BPP, BPB, BPF, BPAF, and BPS. Owczarek et al. assessed human exposure to 11 BPs. The detection rates for BPA, BPS, BPBP, BPP, BPM, BPG, BPF, and BPE exceeded 50%, and BPS had the highest average concentration. Bisphenols are metabolized in the human body and excreted via urine, making urine a reliable matrix for assessing human exposure to BPs. According to a Canadian government report, the highest urinary BPA concentrations in adolescents decreased over time between 2007 and 2015. A similar trend was observed in a Danish study, which reported a 57% decline in median urinary BPA concentrations from 2009 to 2017, showing that the detection rates of BPS and BPF in urine increased to 86 and 87%, respectively. Another study revealed that urinary BPS concentrations in a Saudi Arabian population were higher than those of BPA and BPF. These findings suggest that the presence of BPs in humans is gradually increasing.

BPs are well-established endocrine-disrupting chemicals (EDCs). Growing evidence demonstrates that BPs exert multifaceted toxic effects, including neurotoxicity, reproductive impairment, and endocrine disruption. , Developmental exposure to BPF (2 μg/kg body weight (bw) per day, E15–P21) disrupts subventricular zone neurogenesis and olfactory behavior in adult mice. BPAF delays gonadal migration and depletes germ cell progenitors, ultimately compromising fertility in male zebrafish. BPB and BPAF alter uterine immune landscapes and gene expression profiles, elevating uterine disease risk in mice. Epidemiological studies further underscore their health impacts. BPS and BPA are associated with increased risks of cardiovascular disease and coronary heart disease. , Prenatal BPA exposure correlates with preterm birth, childhood allergic disorders, and metabolic syndromes. Given these systemic effects, such as spanning developmental, reproductive, and metabolic health, elucidating BP bioaccumulation is critical for assessing their long-term health risks.

Chemicals accumulated in adipose tissue may be released slowly or in large quantities during lipolysis, , exerting potential adverse effects on human health. Most BPs are rapidly metabolized in the human body and excreted in urine within 12 h. Therefore, bisphenol compounds are generally not considered to exhibit the characteristics of persistent organic pollutants. However, due to the lipophilic nature of many BPs, they may accumulate in adipose tissue. , Current research on BPs in adipose tissue primarily focuses on BPA. Fernandez et al. detected BPA in female adipose tissue samples. BPAs were detected in over half of the samples with an average concentration of 3.16 μg/kg. Wang et al. identified BPA in adipose tissue from a New York population, with a detection rate of 90% and a median concentration of 5.65 ng/g wet weight. In vitro studies have revealed that BPs significantly disrupt adipose tissue function and promote metabolic dysfunction. A mixture of BPA, BPS, and BPF demonstrated obesogenic effects by promoting adipogenesis in human adipose-derived stem cells. BPA exposure impaired metabolic function in human adipocytes, suppressing proinflammatory adipokine expression and reducing glucose uptake in subcutaneous adipose tissue. These experimental findings are supported by epidemiological evidence showing positive associations between urinary BPA/BPF levels and increased prevalence of abdominal obesity in human populations. Our previous study indicated that exposure to BPA in adipose tissue may be associated with the occurrence of obesity. However, the presence of other BPs in human adipose tissue remains unclear.

In this study, we collected blood and white adipose tissue (WAT), including visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) samples, from volunteers undergoing abdominal surgery. Then the occurrence patterns of BPs in human blood, subcutaneous fat, and visceral fat were investigated. Here we attempted to demonstrate the fat accumulation tendency of each BP based on the concentration, distribution, and correlation characteristics of BPs in Blood, SAT, and VAT. This research will provide new insight into the exposure risks of BPs.

2. Materials and Methods

2.1. Reagents and Materials

The molecular structures of the nine BPs are listed in Table S1. BPA, BPF, BPE, BPS, BPAF, BPC, and BPP were purchased from Sigma-Aldrich (USA). Bisphenol A glucuronide (BPA-G) and bisphenol A sulfate (BPA-S) were obtained from Toronto Research Chemicals (Canada). BPS-d 8, BPA-d 16, and BPAF-d 4 were purchased from CDN Isotopes (Canada). HPLC-grade methanol (MeOH), acetonitrile (ACN), ethyl acetate (EAC), and ammonium hydroxide (NH4OH) were supplied by Fisher Scientific (USA). HPLC-grade formic acid (FA) and phosphoric acid (H3PO4) were purchased from MREDA Technology Inc. (USA). Ultrapure water (18.2 ΩM·cm) was produced using a Milli-Q system (Millipore, USA). Standard stock solutions (1 mg/mL) were prepared in methanol and stored at −20 °C. Working standard solutions (1, 5, 10, 50, and 100 ng/mL) were prepared by diluting the stock solutions with methanol.

2.2. Sample Collection

Blood, subcutaneous fat, and visceral fat samples were collected from Beijing Hospital with approval from the Medical Ethics Committee (2021BJYYEC-330-02). Volunteers undergoing abdominal surgery were recruited and provided informed consent. Inclusion criteria were: age >18 years and body mass index (BMI) ≥ 18.5 kg/m2. Demographic data (age, sex, and BMI) were recorded. Blood samples were collected on the day of surgery using BD Vacutainer tubes. Adipose samples (50–200 mg) were collected from excised tissues after surgery, rinsed with saline, and dried with gauze. All samples were stored at −80 °C until analysis.

2.3. Blood Sample Pretreatment

A 0.5 mL blood sample was spiked with 20 ng of mixed internal standard and then placed at room temperature for 30 min after well blended. The sample was diluted by addition of equal volume of 4% (w/w) H3PO4 and loaded onto a solid-phase extraction (SPE) (Prime HLB, Waters, USA). The SPE column was washed with 2 mL of 5% MeOH/H2O and then dried with a vacuum pump. Then the column was eluted with 2 mL of 5% NH4OH/MeOH, 2 mL of ACN, and 1 mL of MeOH, and the eluate was collected with a 15 mL tube. The eluate was evaporated to dryness using a gentle stream of nitrogen and redissolved in 0.2 mL of MeOH for later instrumental analysis.

2.4. Adipose Sample Pretreatment

First, 200 mg of adipose tissue was mixed with 20 ng of mixed internal standard and equilibrated at room temperature for 30 min. Then 100 μL of ACN was added to the sample and homogenized for 1 min using a TissueLyser (Qiagen, Venlo, the Netherlands). The sample was homogenized again for 1 min by addition of 1 mL of acetonitrile. Next, the homogenate was centrifuged at 12,000 rpm at 4 °C for 5 min, and the supernatant was transferred into a 15 mL polypropylene tube (Corning Inc., Corning, USA). The residual on the homogenate and tube walls was treated repeatedly. The combined supernatant was purified using Prime HLB SPE pretreated with methanol and ultrapure water. The SPE column loaded with the sample was washed with 1 mL of 5% methanol first and then sequentially eluted by 2 mL of methanol and 2 mL of ACN. The eluates were mixed together and evaporated to dryness. Finally, the sample was redissolved in 0.5 mL of methanol for instrumental analysis.

2.5. Instrumental Analysis

BPs in serum and adipose samples were identified and quantified by high-performance liquid chromatography-tandem mass spectrometry (LCMS-8050, Shimadzu, Japan) according to our previous study. An ACQUITY UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm) was used for chromatographic separation. The negative ion electrospray ionization (ESI) source was operated at an interface voltage of 3 kV and an interface temperature of 300 °C. The mass spectrometer was operated in multiple reaction monitoring (MRM) mode, and the optimized mass spectrometry parameters are listed in Table S2. Blank and spiked samples were analyzed every 15 samples to assess contamination and monitor recovery during the analysis. Limit of detection (LOD) and limit of quantification (LOQ) were calculated as signal-to-noise ratios of 3.3 and 10, respectively. The concentrations of BPs below the limit of detection (LOD) were replaced by LOD divided by the square root of 2 (LOD/√2). LOD and LOQ for each target compound are shown in Table S3.

2.6. Data Analysis

The data were primarily analyzed using IBM SPSS Statistics 26 (IBM, USA) and Origin 2023 (OriginLab, USA). The Kolmogorov–Smirnov test was applied to assess the data distribution. Normally distributed data were analyzed using one-way ANOVA followed by Dunnett’s post hoc test for multiple comparisons. Non-normally distributed data were evaluated by using the Kruskal–Wallis test. The Spearman’s rank correlation coefficient was used to examine associations between two data sets. The relationships between BPs concentrations and demographic variables were assessed by using nonlinear regression and multiple linear regression models. All statistical analyses were based on two-tailed hypothesis testing, with a p < 0.05 considered statistically significant.

3. Results and Discussion

3.1. Study Population Characteristics

The study included 88 volunteers who provided VAT, 76 volunteers who provided SAT, and 76 volunteers who provided blood samples. Among these, 66 volunteers provided all three sample types (VAT, SAT, and blood). In the paired samples, the number of participants was approximately equal across three age groups: < 60 years, 60–70 years, and >70 years. The cohort consisted of 34 males and 32 females, achieving a nearly 1:1 gender ratio. Based on BMI classification, participants were divided into normal weight, overweight, and obese groups, with each group containing a comparable number of individuals. The demographic characteristics of the recruited volunteers are presented in Table S4.

3.2. Concentrations of BPs in Blood, SAT, and VAT

Nine BPs were detected in blood, SAT, and VAT (Table ). The predominant compounds detected in blood were BPA-S, BPC, BPA, BPP, and BPA-G, with detection frequencies ranging from 60.6 to 100%, while other BPs showed lower detection rates (3–48.5%). BPA exhibited the highest mean concentration (8.28 ng/g), followed by BPA-S (1.37 ng/g) and BPC (1.22 ng/g). BPA-G, BPS, BPAF, and BPP were detected at lower concentrations (0.01–0.13 ng/g). BPE and BPF levels were below the limit of detection (LOD). These findings are consistent with previous reports for BPAF and BPS. The BPA concentration in our study was higher than that reported by Gao et al. in serum but within the same order of magnitude and lower than levels observed in occupationally exposed populations.

1. Concentration of BPs in VAT, SAT, and Blood .

  concentrations (ng/g)
   concentrations (ng/g)
   concentrations (ng/mL)
analyte mean median 25th 75th DF analyte mean median 25th 75th DF analyte mean median 25th 75th DF
VAT SAT blood
BPA-S 2.86 <LOD <LOD 1.98 62.1% BPA-S 2.04 1.05 <LOD 2.32 72.7% BPA-S 1.37 0.97 0.67 1.64 100.0%
BPA-G 1.57 0.19 0.14 0.55 98.5% BPA-G 1.30 0.30 0.15 1.74 98.5% BPA-G 0.13 0.07 <LOD 0.16 60.6%
BPS 0.41 <LOD <LOD 0.23 45.5% BPS 0.20 <LOD <LOD 0.27 40.9% BPS 0.01 <LOD <LOD <LOD 3.0%
BPF 6.14 <LOD <LOD 1.27 31.8% BPF 4.07 <LOD <LOD 4.90 40.9% BPF <LOD <LOD <LOD 0.14 43.9%
BPE 0.90 0.15 <LOD 0.39 63.6% BPE 0.72 0.15 <LOD 0.55 57.6% BPE <LOD <LOD <LOD <LOD 22.7%
BPA 9.50 6.65 <LOD 11.25 68.2% BPA 11.07 8.71 <LOD 16.37 74.2% BPA 8.28 7.51 3.66 11.44 98.5%
BPAF 0.18 0.10 <LOD 0.17 74.2% BPAF 0.17 0.13 <LOD 0.19 72.7% BPAF 0.05 <LOD <LOD 0.08 48.5%
BPC 5.09 <LOD <LOD 1.28 47.0% BPC 1.39 <LOD <LOD 0.60 39.4% BPC 1.22 1.00 0.77 1.45 100.0%
BPP 0.44 0.13 <LOD 0.24 97.0% BPP 0.34 0.17 <LOD 0.37 98.5% BPP 0.15 0.13 0.10 0.17 92.4%
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a

<LOD: below the limit of detection.

The major BPs detected in SAT were BPA-G, BPP, BPA, BPAF, BPA-S, and BPE, with detection frequencies of 57.6–98.5%, while other BPs were detected in 39.4–40.9% of samples. BPA had the highest mean concentration (11.07 ng/g), followed by BPF (4.07 ng/g), BPA-S (2.04 ng/g), BPC (1.39 ng/g), and BPA-G (1.3 ng/g). BPS, BPE, BPAF, and BPP were present at lower levels (0.17–0.72 ng/g). The dominant BPs in VAT were BPA-G, BPP, BPAF, BPA, BPE, and BPA-S, with detection rates of 62.1–98.5%, while other BPs were detected in 31.8–47% of samples. BPA also showed the highest mean concentration (9.5 ng/g), followed by BPF (6.14 ng/g), BPC (5.09 ng/g), BPA-S (2.86 ng/g), and BPA-G (1.57 ng/g). BPS, BPE, BPAF, and BPP were present at lower concentrations (0.18–0.9 ng/g). A small sample study reported BPA in breast adipose tissue from women with a concentration range of 1.19–8.73 ng/g. In our study, BPA levels in VAT and SAT were higher than it. Another study on New York populations found a median BPA concentration of 5.65 ng/g in fat, which was lower than our findings in VAT and SAT, possibly due to cumulative exposure increases over the past decade.

3.3. Distribution Characteristics of BPs in Blood, SAT, and VAT

Detection frequencies were first compared across blood, VAT, and SAT (Figure a). SAT and VAT showed similar BP detection patterns. BPA-S, BPA, and BPC had higher detection rates in blood than in adipose tissue. BPA-G, BPS, BPE, and BPAF were more frequently detected in adipose tissue than in blood. BPP and BPF showed similar detection frequencies in both blood and adipose tissue.

1.

1

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Distribution Characteristics of BPs in Blood, SAT, and VAT. (a) Detection frequency of BPs in blood, SAT, and VAT. (b) Composition profile of BPs in blood, SAT, and VAT. (c) Accumulative tendency of BPs in VAT and SAT.

Next, the compositional profiles of BPs across different biological matrices were analyzed based on their mean concentrations (Figure b). For blood samples, BPA dominated the BP profile, accounting for 72.6% of the total detected BPs. BPA-S (12.0%) and BPC (10.7%) were the secondary major components. Other BPs constituted minor proportions (0.1–1.5%). For SAT, BPA remained the predominant compound, at 51.9% of total BPs. BPF (19.1%) and BPA-S (9.6%) showed significantly higher proportions compared to blood. Other BPs maintained relatively low proportions (0.8–6.5%). For VAT, BPA represented 35.1% of total BPs, maintaining its dominance but at a reduced proportion compared to that of SAT. BPF (22.7%), BPC (18.8%), and BPA-S (10.6%) showed an increased accumulation. Other BPs constituted 0.7–5.8% of the total. BPA remains the dominant BP in blood, SAT, and VAT. However, compared to blood, the proportion of BPA in SAT and VAT is significantly decreased, while the proportions of BPF, BPE, and BPA-G are significantly increased. In contrast to blood and SAT, the proportion of BPC in VAT is significantly increased. These findings demonstrate chemically specific partitioning between blood and adipose tissues, suggesting differential accumulation behaviors among BPs. The preferential accumulation of these BPs (e.g., BPF, BPE) may be due to their different affinity for lipid-rich tissues or metabolic behaviors.

We also attempted to demonstrate the fat accumulation tendency of BPs using the concentration ratio of bisphenol compounds in fat to blood in individuals. As shown in Figure c, the order of BPs accumulation tendency in SAT and VAT was BPF > BPE > BPA-G > BPAF > BPP > BPA-S > BPA > BPC. Furthermore, BPs showed a slightly higher accumulation tendency in SAT than in VAT. This may be because SAT is more readily formed than VAT for the general population. For BPF, BPE, and BPA-G, their fat accumulation tendency aligns with their proportional distribution in adipose tissue. Although BPA, BPC, and BPA-S do not exhibit high accumulation tendencies, their high concentrations result in higher concentrations in adipose tissue compared to other BPs. However, BPC, despite showing the lowest fat accumulation tendency, had a significantly higher proportion in VAT than in SAT and blood. This discrepancy may be due to its relatively low concentration and a few high-concentration values.

Research on the fat accumulation behavior of BPs remains limited, with most studies focusing only on their concentrations in white adipose tissue (WAT). For instance, a study in Southern Spain reported BPA at a detection frequency of 86.8% in WAT, with a maximum concentration of 7.88 ng/g. While the sequestration of EDCs in WAT may protect more sensitive organs from acute exposure overload, it could also result in chronic low-dose exposure to the body. Furthermore, the bidirectional exchange of xenobiotics between WAT and blood means that conditions such as lipolysis or inflammation may promote the release of stored pollutants into circulation, potentially leading to systemic health effects. Understanding the accumulation patterns of BPs across different adipose depots is crucial for elucidating the equilibrium between chemical storage and circulatory redistribution. Our findings demonstrate that BPs accumulate similarly in VAT and SAT, with strong positive correlations for individual BPs between these depotsa pattern consistent with certain persistent organic pollutants. The accumulated BPs may disrupt WAT homeostasis, promoting a pro-oxidative and pro-inflammatory microenvironment, which is a recognized risk factor for various chronic diseases, as seen with other lipophilic pollutants.

3.4. Correlation Analysis of BPs in Blood, SAT, and VAT

The relationships among BPs in Blood, SAT, and VAT were examined by using Spearman correlation analysis. As shown in Figure a, in VAT, BPA-G, BPE, BPC, and BPP exhibited significant positive correlations with BPA-S, while BPE, BPA, BPC, and BPP showed significant positive correlations with BPA-G. Additionally, BPA-S, BPA-G, BPF, BPE, BPA, and BPP were all significantly positively correlated with BPC, and BPA-S, BPA-G, BPE, and BPC were significantly positively correlated with BPP. The correlations among BPs in SAT were similar to those in visceral fat, suggesting that the storage sources of these BPs in both adipose tissues are comparable. In contrast, the relationships among BPs in blood significantly differed from those in SAT and VAT. Only BPC and BPP showed significant positive correlations with BPA-S, while BPE, BPA, and BPP exhibited significant positive correlations with BPAF. Furthermore, BPA-S, BPA, BPAF, and BPC were significantly positively correlated with BPP. These findings indicate that the metabolism and accumulation of these compounds in blood differ from those in adipose tissue.

2.

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Correlation Analysis of BPs in Blood, SAT, and VAT. (a) Intragroup correlation analysis of BPs in VAT, SAT, and blood. (b) Intergroup correlation analysis of BPs between VAT, SAT, and blood.

We next analyzed the intergroup correlations of BPs in blood, SAT, and VAT. As shown in Figure b, the concentration of BPA in blood was significantly negatively correlated with BPA-S, BPA-G, BPE, BPC, and BPP in both SAT and VAT, suggesting that BPA in blood and these BPs in adipose tissue may have different exposure pathways. In contrast, BPAF in blood was significantly positively correlated with BPA-S, BPA-G, BPE, BPC, and BPP in VAT, as well as with BPA-S, BPA-G, BPF, BPE, and BPP in SAT, indicating that BPAF in blood and these BPs in adipose tissue may share similar exposure pathways. Between SAT and VAT, most BPs showed either no significant correlation or significant positive correlations, except for BPA in VAT, which was significantly negatively correlated with BPA-G, BPC, and BPP in SAT. Notably, the same BP exhibited positive correlations between SAT and VAT, suggesting that the origins of identical BPs in SAT and VAT are highly consistent.

While logKow is widely used as an indicator of chemical lipophilicity and serves as a key parameter for predicting bioaccumulation potential and assessing the health impacts of EDCs, our analysis revealed no significant correlation between the adipose tissue accumulation of BPs and their respective logKow values. This apparent discrepancy may be attributed to extensive biotransformation of BPs in vivo. Following gastrointestinal absorption, BPA undergoes substantial metabolism in the gut wall and liver, where it is primarily converted to BPA-glucuronide and BPA-sulfate conjugates. These hydrophilic metabolites exhibit markedly increased water solubility, facilitating rapid renal clearance and urinary excretion. Available evidence suggests that other bisphenols (BPS, BPF, and BPAF) undergo similar metabolic fates, being predominantly converted to glucuronide and sulfate conjugates. , These findings highlight the need for future research to specifically address the potential biological effects and distribution patterns of BP metabolites as their physicochemical properties and pharmacokinetic behaviors may differ substantially from the parent compounds.

3.5. Association of BPs Concentrations and Demographic Information

To show the association of BPs concentrations and demographic characteristics, participants were categorized into two groups according to gender (male and female), three groups according to age (<60, 60–70, >70 years), and three groups according to age BMI (normal, overweight, and obese). According to World Health Organization (WHO) recommended cutoff values for BMI in China, underweight was defined as BMI < 18.5 kg/m2, normal weight as BMI 18.5–23.9 kg/m2, overweight as BMI 24–27.9 kg/m2, and obesity as BMI ≥ 28 kg/m2 (WHO, 2004). Compound concentrations were expressed as the median and interquartile range (IQR), i.e., 50th (25th–75th). As shown in Table , in blood samples, no significant differences were observed in the concentrations of any BPs across BMI or sex groups and only BPA-S exhibited significant differences among age groups. In VAT, no significant differences were found in BP concentrations across BMI or sex groups, but BPA-G, BPE, and BPP showed significant differences among age groups, with higher concentrations in younger individuals. In SAT, no significant differences were detected in BP concentrations across age or sex groups, but BPF displayed significant differences among BMI groups, with the highest concentrations in obese individuals. These findings suggest that age and obesity level may be key factors influencing the differential accumulation of BPs in adipose tissue. However, due to the lack of long-term exposure data and detailed fat metabolism information, further research is needed to elucidate the mechanisms of BPs accumulation and release in adipose tissue.

2. Difference Analysis of BPs Concentration under Age, BMI, and Gender in Blood, VAT, and SAT.

    BPA-S BPA-G BPF BPE BPA BPAF BPC BPP
blood
age (years) <60 0.93 (0.69, 1.41) 0.08 (0.01, 0.17) 0.17 (0.17, 0.17) 0.02 (0.02, 0.02) 5.90 (3.18, 10.11) 0.04 (0.02, 0.12) 1.18 (0.91, 1.61) 0.12 (0.11, 0.16)
  60–70 1.39 (0.90, 2.65) 0.07 (0.01, 0.16) 0.17 (0.16, 0.17) 0.02 (0.02, 0.02) 5.61 (1.23, 11.02) 0.02 (0.02, 0.11) 1.05 (0.72, 1.35) 0.13 (0.11, 0.18)
  >70 0.78 (0.54, 1.15) 0.06 (0.01, 0.14) 0.17 (0.13, 0.17) 0.02 (0.02, 0.02) 9.62 (7.32, 11.65) 0.02 (0.02, 0.02) 0.90 (0.75, 1.11) 0.13 (0.10, 0.15)
  p value 0.033 0.886 0.56 0.849 0.108 0.285 0.148 0.661
BMI (kg/m2) <24 1.58 (0.09, 4.36) 0.16 (0.01, 0.99) 0.23 (0.04, 0.78) 0.07 (0.02, 0.49) 9.81 (0.23, 20.57) 0.05 (0.01, 0.15) 1.04 (0.43, 3.18) 0.19 (0.01, 1.48)
  24–28 1.18 (0.76, 2.26) 0.06 (0.01, 0.15) 0.17 (0.13, 0.24) 0.02 (0.02, 0.02) 7.51 (4.92, 10.93) 0.02 (0.02, 0.06) 1.04 (0.79, 1.40) 0.12 (0.11, 0.17)
  >28 0.84 (0.56, 1.29) 0.09 (0.04, 0.16) 0.17 (0.17, 0.17) 0.02 (0.02, 0.02) 5.35 (1.62, 9.25) 0.02 (0.02, 0.15) 1.07 (0.88, 1.62) 0.13 (0.11, 0.15)
  p value 0.088 0.498 0.876 0.096 0.098 0.261 0.168 0.955
gender male 1.12 (0.62, 1.54) 0.07 (0.01, 0.16) 0.17 (0.14, 0.17) 0.02 (0.02, 0.02) 7.86 (4.00, 11.60) 0.02 (0.02, 0.07) 1.08 (0.82, 1.44) 0.14 (0.12, 0.17)
  female 0.94 (0.72, 1.65) 0.07 (0.01, 0.15) 0.17 (0.17, 0.17) 0.02 (0.02, 0.03) 6.74 (3.51, 10.27) 0.02 (0.02, 0.10) 0.97 (0.73, 1.37) 0.12 (0.09, 0.15)
  p value 0.98 0.542 0.241 0.463 0.362 0.481 0.362 0.114
VAT
age (years) <60 0.88 (0.58, 2.06) 0.41 (0.19, 1.25) 0.67 (0.67, 3.46) 0.23 (0.10, 0.46) 3.84 (0.06, 10.21) 0.09 (0.07, 0.16) 0.40 (0.23, 2.60) 0.17 (0.13, 0.31)
  60–70 0.58 (0.58, 1.97) 0.17 (0.12, 0.41) 0.67 (0.67, 0.67) 0.10 (0.10, 0.15) 5.26 (0.06, 10.99) 0.11 (0.07, 0.16) 0.23 (0.23, 1.33) 0.09 (0.07, 0.16)
  >70 0.58 (0.58, 1.32) 0.15 (0.11, 0.19) 0.67 (0.67, 0.67) 0.17 (0.10, 0.30) 8.75 (1.17, 11.25) 0.10 (0.07, 0.17) 0.23 (0.23, 0.27) 0.10 (0.08, 0.14)
  p value 0.494 0.006 0.226 0.045 0.567 0.659 0.16 0.005
BMI (kg/m2) <24 1.43 (0.34, 9.53) 0.48 (0.04, 4.54) 3.15 (0.67, 45.27) 0.97 (0.07, 13.38) 7.07 (0.06, 24.09) 0.13 (0.06, 0.29) 3.15 (0.22, 45.74) 0.18 (0.05, 0.75)
  24–28 1.15 (0.58, 5.12) 0.20 (0.15, 1.70) 0.67 (0.67, 0.81) 0.13 (0.10, 0.68) 3.92 (0.06, 9.36) 0.09 (0.07, 0.25) 0.23 (0.23, 0.38) 0.14 (0.10, 0.27)
  >28 0.66 (0.58, 1.69) 0.38 (0.15, 0.90) 0.67 (0.67, 1.85) 0.14 (0.10, 0.37) 8.16 (0.41, 10.87) 0.09 (0.07, 0.11) 0.41 (0.23, 1.33) 0.13 (0.09, 0.25)
  p value 0.161 0.289 0.81 0.994 0.531 0.145 0.193 0.573
gender male 0.62 (0.58, 1.8) 0.18 (0.15, 0.42) 0.67 (0.67, 0.67) 0.13 (0.10, 0.27) 5.44 (0.06, 11.90) 0.1 (0.07, 0.16) 0.23 (0.23, 0.71) 0.11 (0.09, 0.16)
  female 0.76 (0.58, 2.17) 0.21 (0.14, 1.12) 0.67 (0.67, 1.52) 0.16 (0.10, 0.47) 7.37 (0.06, 9.41) 0.1 (0.07, 0.17) 0.29 (0.23, 1.57) 0.14 (0.08, 0.31)
  p value 0.611 0.663 0.223 0.253 0.969 0.816 0.094 0.415
SAT
age (years) <60 1.37 (0.58, 2.71) 0.56 (0.17, 2.50) 2.42 (0.67, 5.83) 0.14 (0.10, 0.63) 5.66 (0.06, 12.61) 0.13 (0.07, 0.20) 0.23 (0.23, 0.55) 0.18 (0.11, 0.45)
  60–70 1.57 (0.58, 2.32) 0.30 (0.20, 1.34) 0.67 (0.67, 1.00) 0.10 (0.10, 0.60) 9.89 (1.39, 14.46) 0.13 (0.07, 0.19) 0.23 (0.23, 0.57) 0.16 (0.10, 0.41)
  >70 0.58 (0.58, 1.12) 0.18 (0.13, 0.39) 0.67 (0.67, 3.14) 0.17 (0.10, 0.46) 11.54 (6.55, 18.65) 0.14 (0.07, 0.19) 0.23 (0.23, 0.60) 0.14 (0.09, 0.19)
  p value 0.163 0.139 0.197 0.899 0.123 0.927 0.963 0.320
BMI (kg/m2) <24 1.85 (0.50, 10.83) 1.18 (0.07, 8.23) 2.21 (0.67, 30.63) 1.05 (0.07, 14.23) 8.27 (0.06, 34.53) 0.17 (0.07, 0.85) 1.54 (0.23, 25.78) 0.26 (0.05, 1.94)
  24–28 1.00 (0.58, 2.23) 0.26 (0.13, 0.96) 0.67 (0.67, 4.12) 0.20 (0.10, 0.97) 8.34 (1.39, 14.19) 0.12 (0.08, 0.16) 0.23 (0.23, 1.46) 0.15 (0.10, 0.26)
  >28 1.33 (0.58, 2.64) 0.63 (0.16, 1.97) 3.15 (0.67, 7.75) 0.10 (0.10, 0.40) 10.93 (4.98, 21.83) 0.17 (0.07, 0.26) 0.23 (0.23, 0.75) 0.20 (0.14, 0.37)
  p value 0.793 0.524 0.008 0.475 0.288 0.562 0.312 0.194
gender male 0.94 (0.58, 2.07) 0.30 (0.15, 0.95) 0.67 (0.67, 1.97) 0.21 (0.10, 0.82) 8.51 (0.06, 15.63) 0.11 (0.07, 0.19) 0.23 (0.23, 0.23) 0.16 (0.10, 0.22)
  female 1.20 (0.58, 2.68) 0.33 (0.15, 1.89) 0.67 (0.67, 7.80) 0.10 (0.10, 0.48) 9.00 (1.68, 15.28) 0.15 (0.09, 0.20) 0.23 (0.23, 1.14) 0.18 (0.10, 0.40)
  p value 0.334 0.888 0.130 0.283 0.727 0.271 0.111 0.465
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3.6. Association of BPs Fat Accumulation Tendency and Obesity

Studies have demonstrated that BPs analogues exposure may be associated with obesity. − However, the accumulation tendency of BPs within adipose tissue and their correlation with obesity remain relatively unexplored. Therefore, we examined the association between the fat accumulation tendency of BPs and BMI using restricted cubic spline (RCS) regression analysis and multivariate linear regression. Additionally, the fat accumulation tendency of BPs using the concentration ratio of bisphenol compounds in fat to blood; and all BPs concentrations were natural-log (ln) transformed to minimize the influence of extreme values due to their non-normal distribution. The RCS results showed that BPAF accumulation tendency in VAT (p-nonlinear <0.001) had a significant nonlinear (L-shaped) association with BMI, and BPA accumulation tendency in SAT (p-nonlinear <0.018) had a significant nonlinear association with BMI (Figure ). For BPA-S, BPA-G, BPF, BPE, BPAF, BPC, and BPP, no statistically significant nonlinear associations were found (p-nonlinear >0.05). The multivariate linear regression results showed that the fat accumulation of BPA-G in SAT was positively associated with BMI (β = 0.325, 95% confidence interval (CI): 0.081–3.599, p = 0.041) without adjustment for covariates (model 1) (Tables S5 and S6). Age and gender were considered as potentially important covariates that may influence obesity. After adjusting for age and sex covariates (model 2), the fat accumulation tendency of BPs was not associated with BMI. These results indicate that the fat accumulation tendency of BPA-S, BPA-G, BPF, BPE, BPAF, BPC, and BPP is not influenced by BMI. This may be because BMI is not an accurate indicator of obesity, it mainly reflects overall body weight and cannot distinguish between fat and nonfat tissues. For further study, the body fat percentage maybe a better indicator of body fat content.

3.

3

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Association between the risk of obesity and the concentration ratio of bisphenols in lipids and blood. Note: Restricted cubic spline functions were used to analyze the association between log-transformed BPs accumulation tendency in adipose tissue and BMI, adjusting covariates including age and gender. The shaded areas represent 95% confidence intervals.

4. Conclusion

Our study demonstrates that BPs are ubiquitously present in human blood, VAT, and SAT. While BP sources were highly consistent across adipose depots, they differed significantly from blood profiles. BPs exhibited distinct adipose accumulation tendencies, with a slightly higher propensity in SAT than VAT. Among these BPs, BPF, BPE, and BPA-G showed preferential accumulation in adipose tissues. We also revealed that BP accumulation patterns are influenced by both age and obesity. These findings carry important toxicological implications, as adipose-accumulated BPs may be substantially released during lipolysis, posing potential long-term health risks.

Supplementary Material

eh5c00129_si_001.pdf (164.7KB, pdf)

Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grant Nos. 22125606 and 22241604), Chinese Academy of Sciences Project for Young Scientists in Basic Research (No. YSBR-086), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0750300), and Research Start-up Funding Project of Kashi University (No. 022024666).

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/envhealth.5c00129.

  • The structure, molecular weight, and Log Kow of target BPs; the optimized mass spectrometer parameter and MRM for bisphenols; the LOQ and LOD in BPs determination; characteristics of participants; linear regression analysis of VAT/blood with BMI; and linear regression analysis of SAT/blood with BMI (PDF)

⊥.

P.J. and Y.G. contributed equally to this work.

The authors declare no competing financial interest.

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