Bisphenol A and cancer: a critical review of the epidemiologic literature with an emphasis on exposure assessment

Bisphenol A and cancer: a critical review of the epidemiologic literature with an emphasis on exposure assessment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Bisphenol A and cancer: a critical review of the epidemiologic literature with an emphasis on exposure assessment Neela Guha, Gwendolyn Osborne, M. Elizabeth Marder, Martha Sandy, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6742025/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract BACKGROUND: Bisphenol A (BPA) is a high production volume chemical that has been used for decades in numerous consumer and industrial applications. Daily exposure to BPA is likely; it is readily detected in >90% of the general population despite being rapidly metabolized and excreted. BPA’s toxicity, including endocrine disrupting activity, has sparked public health concern. We comprehensively reviewed the epidemiologic literature on the carcinogenicity of BPA and highlighted exposure assessment considerations that impact study interpretation. METHODS: Multiple biomedical databases were searched through February 2025 for peer-reviewed cancer epidemiology studies that assessed associations with BPA exposure. Studies of the following designs (or a variant) were included: cohort, case-control, cross-sectional. A detailed bias assessment was conducted with guidance from the Report on Carcinogens handbook and the International Agency for Research on Cancer Monographs Preamble. RESULTS: Of the 139 records identified, 43 epidemiological studies were reviewed; all were conducted in the general population. We focused the review on cancers of the breast and prostate because they had the highest number of cohort or case-control studies, but all cancer sites were summarized in the appendix for completeness. Associations with BPA were inconsistent within and across studies. Interpretation was hampered by the high potential for exposure measurement error and the inability to characterize past BPA exposure, necessary to assess cancer outcomes with long latency. The majority of studies relied on biomonitoring using short-term biomarkers of recent BPA exposure, and measured BPA in urine at a single time point post-diagnosis; this failed to capture the critical time window of susceptibility, rule out reverse causation, or characterize temporal variation in BPA exposure. CONCLUSIONS: The epidemiologic evidence was inadequate to evaluate the carcinogenicity of BPA – mainly due to exposure measurement error and misclassification, limited number of studies by cancer site, and the lack of consistency across studies. The inadequate evidence base cannot rule out potential carcinogenicity of BPA in humans. Future studies conducted within highly exposed occupational cohorts, with prospective and longitudinal collection of quantitative exposure data and assessment of cancer morbidity or acute endpoints involved in established mechanisms of carcinogenesis are likely to be informative. Bisphenol A Cancer Epidemiology Biomonitoring Exposure Misclassification Review Figures Figure 1 1. Introduction 1.a. Rationale Bisphenol A (BPA) is a high production volume chemical, with over 13 billion pounds estimated to have entered the global market in 2022 alone [1]. In the US, domestic production has exceeded 1 billion pounds each year for at least two decades. BPA has been extensively used over decades in many industrial applications (e.g., mostly in the manufacture of epoxy resins and polycarbonate plastics) and in a wide variety of consumer products (e.g., baby bottles, toys, reusable water bottles and food containers, polyvinyl chloride stretch films, papers, cardboards, thermal receipts, dental sealants, medical devices and equipment) [2]. BPA has been shown to leach from many of these products [3], leading to its release into the environment and subsequent human exposure. BPA has been detected in a variety of environmental samples, including water, dust, sewage leachates, and indoor and outdoor air [3, 4]. BPA has also been detected in urine samples from the majority (>90%) of the general population in several large biomonitoring studies [5-7]. BPA is ubiquitously detected in human biospecimens despite its short half-life and that it is not a persistent chemical. This suggests frequent, widespread, and continuous exposure. There have been some regulatory efforts to prohibit or limit the use of BPA [8, 9], and some studies suggest that median urinary levels of BPA have decreased in the general population in the US, including California, following restrictions or prohibitions on its use [5, 10-12]. However, BPA is still in many consumer products [13] and workers continue to be exposed [14]. The general population has been primarily exposed to BPA through ingestion from food and beverage containers coated internally with BPA-containing epoxy resins [3, 9], though this has declined in recent years given the move away from such resins [15]. However, some BPA exposure of the general population continues through diet, as well as via dermal contact and inhalation. The CDC last analyzed urinary BPA in US adults recruited from the general population in the 2015-2016 NHANES cycle. The median unadjusted concentration of BPA in urine was 1.1 micrograms per liter urine (μg/L), and the median adjusted for creatinine (Cr) was 1.02 micrograms per gram Cr (μg/g) [5]. In comparison, an occupational study of US adults reported a range of creatinine-adjusted total BPA urinary concentrations of 0.78–18,900 μg/g (median 98.7 μg/g, over 80 times the median of 1.21 μg/g reported in US adults in NHANES during the overlapping 2013-2014 study period) [5, 16]. Global reviews also report higher occupational BPA exposure (up to 685.9 μg/g Cr) than in the general population [8, 14]. BPA measurements reflect recent exposure and there is considerable temporal, intra-individual, and inter-individual variation [17-19]. BPA is rapidly absorbed and distributed throughout the body with some studies suggesting that adipose tissue may serve as a reservoir for BPA [3, 20, 21]. It is then primarily metabolized via conjugation, leading to the formation of the predominant metabolites BPA-glucuronide (BPA-G) and BPA-sulfate (BPA-S). BPA and its metabolites are rapidly eliminated; toxicokinetic studies demonstrate a half-life of less than 6 hours following ingestion [22] but there may be high inter-individual variability in enzymatic conjugation capacity by life stage, xenobiotic and drug exposure, genetic polymorphisms, or disease status [23-26]. Public health concerns over BPA [27] are related to its documented properties as an endocrine disrupter [28] and observations that it exhibits several key characteristics of carcinogens [29]. The potential carcinogenicity of BPA has not been previously reviewed by any leading health agencies, including the International Agency for Research on Cancer (IARC), the US Environmental Protection Agency (US EPA), the National Institute for Occupational Safety and Health (NIOSH), the National Toxicology Program (NTP) Report on Carcinogens, or the US Food and Drug Administration (US FDA). IARC recommended that BPA be evaluated with “high” priority [30, 31], but has not yet conducted their review as of early 2025. BPA was also placed in a “high” priority group by the Carcinogen Identification Committee (CIC), a group of scientists designated as the “State’s Qualified Experts” for California’s Proposition 65 [32]. OEHHA staff critically reviewed the carcinogenicity of BPA in a document [33] that was prepared for a public meeting of the CIC which convened in December 2022 [34]. The CIC declined to add BPA to the Proposition 65 List of Carcinogens by 6 “no” votes and 5 “yes” votes [33, 34]. The CIC considered three streams of evidence (epidemiologic, animal carcinogenicity, and mechanistic studies) in their evaluation, and considered the epidemiologic evidence inadequate to evaluate the carcinogenicity of BPA. 1.b. Objectives We conducted a comprehensive and critical review of the published epidemiologic literature on the carcinogenicity of BPA, with an extensive summary of the characteristics of exposure assessment and study design needed to interpret the epidemiological studies. We focused the review on breast and prostate cancers, hormonally related cancers for which at least two cohort or case-control studies were available. All other cancer sites are described in an appendix. These data were publicly reviewed by the CIC in 2022 [33] and here are further extended to include papers published until February 2025. 2. Methods This review is presented in a format that balances best practices and advantages of systematic and narrative reviews, with a focus on key issues [35-40]. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was followed as a guide for reporting this review [41, 42]. 2.a. Eligibility criteria Criteria for inclusion were all peer-reviewed, published analytical epidemiologic studies that estimated associations between exposure levels and cancer outcomes [43]. Excluded records were conference abstracts, reviews without primary data, descriptive epidemiological studies and studies of uterine leiomyoma which generally does not progress to malignancy. Cross-sectional studies were reviewed for completeness even though we acknowledge that their design does not permit causal inference of BPA and cancer [44]. Cross-sectional studies were briefly cited but excluded from further detailed review due to limitations for causal inference: a temporal association could not be established, reverse causation was possible, and disease prevalence was not a good proxy for incidence [45]. Studies of BPA and precancerous lesions were not found. Studies of BPA and acute endpoints related to carcinogenesis were covered in the review of mechanistic evidence organized by key characteristics of carcinogens[29]. Studies on cancer survival and progression would not be informative for causal inference of BPA as a cause of cancer and therefore were a priori excluded from this review. The inclusion and exclusion of studies is shown in Figure 1. 2.b. Information sources and search strategy A professional librarian (NF) conducted comprehensive literature searches on the carcinogenicity of BPA in humans using a PECO strategy using a systematic approach similar to that used by the NTP Report on Carcinogens [37]. Primary searches were conducted on December 14, 2021 in PubMed, Embase, Scopus, and SciFinder n . The literature searches were supplemented with a public data call-in period from January 28 to March 14, 2022 and searches in other data sources (e.g., reports by other health agencies, review articles). Additional focused searches in PubMed were conducted up to February 2025 (by GO and NG) and found 16 additional relevant publications using the following terms: ((("bisphenol A") AND (cancer)) AND (epidemiology)) AND (("2021"[Date - Publication]: "3000"[Date - Publication])). An overview of the systematic literature search strategy, the literature search terms in PECO format, and the dates the searches were executed is presented in Appendix Table 1. 2.c. Selection process Two scientists (NG, GO) independently completed the screening for each title and abstract, following the predefined inclusion and exclusion criteria. Sciome Workbench for Interactive Computer-Facilitated Text-mining Active Screener (SWIFT AS) [46] was used as a tool to facilitate the initial screening of references from the primary searches. After initial screening in SWIFT AS, HAWC (Health Assessment Workspace Collaborative, https://hawcproject.org) was used as a tool to further screen and tag the literature by keyword [47]. 2.d. Data items and data collection process Two scientists (NG, GO) independently collected the following data from the included publications: study characteristics, study design, population selection, details on exposure and outcome assessment, exposure levels, statistical analysis methods, organ site and details including International Classification of Diseases (ICD) codes, units of effect measurement, measure of effect (e.g. relative risk, odds ratio, etc.), p-value for test for trend, exposure category or level, exposed cases or deaths, potential confounders and covariates, strengths, limitations, other noteworthy comments, and confidence in the evidence. These data were entered into Table Builder, a web-based application designed to capture systematically extracted data and to generate tables for reports [47]. Tables 1 and 2 present only select study design elements and highlight key information critical to the interpretation of the evidence for each study. For example, a latency period between BPA measurement and cancer diagnosis would be noted only if it were too short to detect the outcome. 2.e. Study bias assessment Two scientists (NG, GO) independently and systematically evaluated the quality of each included study for selection bias, information bias, and confounding through a domain-based approach according to guidance from the NTP Report on Carcinogens Handbook [36, 37] and the IARC Monographs preamble [35]. Study evaluations and judgement of potential biases were recorded into Table Builder [47]. Studies were not rated for risk of bias on various domains; rather each domain was evaluated and described thoroughly when notable [38, 40]. For the bias assessment, the domain of information bias from exposure assessment was identified as a key consideration for assessing epidemiological studies of BPA and cancer. An exposure scientist (MEM) critically reviewed these data with consideration of: the exposure assessment method (e.g., was a standard assay used?), the timing of the exposure assessment with respect to cancer diagnosis (e.g., prospective, retrospective, concurrent or cross-sectional), the quality assurance parameters used to validate a given method (e.g., the inter- and intra-assay coefficients of variation, the correlation between repeated measurements of exposure (if any), the treatment of values below a limit of detection), the BPA analyte or proxy, the biologic matrix sampled, and the potential for contamination in either sample handling or processing that could impact the analysis. Potential confounders were identified for the cancers of the breast and prostate (Appendix Table 2). First, risk factors for these cancer sites were identified from IARC [48], the American Cancer Society [49-53], and the World Cancer Research Fund [54-56]. Next, a literature search was performed to identify whether these risk factors were also associated with BPA exposure, to be considered potential confounders. Directed acyclic graphs were used to visualize the relationships between variables. In general, for the hormonally related cancers, there is evidence that BPA exposure/level is associated with age [57], race/ethnicity [57], obesity [58-63], diabetes [64-67], and tobacco smoke exposure (for breast cancer) [68]. When interpreting the evidence, we considered the direction of these biases on the observed associations [38, 40]. 2.f. Synthesis methods The studies included in the review were described in Tables 1, 2 and Appendix Table 3. Hill guidelines [69] for causal inference were taken into consideration for synthesizing the evidence qualitatively. A statistical approach to evidence synthesis (e.g., meta-analysis) was not undertaken in this manuscript. We considered combining risk estimates across studies of BPA to be inappropriate due the difficulty interpreting a risk estimate associated with BPA measurement at a single time point and the heterogeneity between studies in the methods of assessment and exposure metrics presented. 3. Main text Our literature search identified 139 studies using the search terms for epidemiologic studies of cancer and BPA exposure (Appendix Table 1; Figure 1). Forty-three studies met the inclusion criteria and were reviewed in detail. Two meta-analyses [70, 71] were excluded due to the difficulty interpreting a combined risk estimate for BPA and cancer due to heterogeneity in methods for exposure assessment and reporting (see Section 2.f). The review of the epidemiological evidence identified a need to review the exposure assessment methods in detail prior to interpreting the studies of BPA and cancer. There was substantial heterogeneity in study methods for assessing BPA exposure including the timing when BPA samples were taken, the biological matrix and the BPA analyte sampled, the potential for contamination and the quality assurance parameters for BPA detection. These factors are summarized in detail below and precede the review of the epidemiological studies, which is organized by cancer site to facilitate hazard identification. 3.1 EXPOSURE MEASUREMENT ERROR IN EPIDEMIOLOGIC STUDIES OF BPA AND CANCER The greatest challenge to interpreting the reviewed human cancer studies was the reliable characterization of long-term BPA exposure. Exposure misclassification was a major concern; most studies assessed BPA exposure at a single time point using short-lived biomarkers. There were several additional methodological issues that could affect information bias, including measuring BPA in samples collected post-diagnosis. The direction and impact of the sources of bias are summarized below and in greater detail in the hazard identification document [33]. 3.1.1 Single BPA measurement Despite large temporal variation in BPA levels, most studies measured BPA at a single time point using short-lived biomarkers that reflect current exposures [72-78]. Poor reproducibility of repeated urinary BPA measurements has been reported [19, 76-85]: correlation coefficients ranged from 0.22 to 0.57 for serial urinary BPA measurements over 1 to 6 month periods [61, 86]. Therefore, a single biological measurement or even multiple measurements in close proximity (e.g. hours, days) are unlikely to provide accurate estimates of long-term BPA exposure. Multiple longitudinal samples are required to improve confidence in BPA exposure classification [87]. Exposure status in individuals is expected to be misclassified irrespective of disease status (non-differential), which could bias risk estimates towards the null. 3.1.2 Timing of BPA exposure assessment BPA was measured primarily after outcome ascertainment in several case-control and cross-sectional studies, which presents several challenges: Reverse causation: Disease status may alter BPA levels, therefore post-diagnostic measurements may be misleading. Missed critical windows: Post-diagnostic samples fail to capture exposure during critical time windows of susceptibility, which could precede cancer development by 10-20 years, and thereby fail to detect true causal effects. Temporal variations: Due to significant fluctuations in BPA levels over time, post-diagnostic samples may not be predictive of BPA levels prior to diagnosis. Data on outcome and exposure (post-diagnostic BPA measurements) were collected simultaneously in studies of cross-sectional design. Therefore, by design these BPA studies cannot establish temporality, a key consideration for causal inference. This is an important consideration particularly for exposures with large temporal variation and also for cancer outcomes, given the long latency period for disease development following exposure. 3.1.3 Methods for BPA exposure assessment BPA was primarily measured in biological matrices (i.e., biomonitoring) and, to a lesser extent, using questionnaires (one study) [88, 89] and job exposure matrices (JEM) (four studies) [88-93]. Generally, for questionnaires, non-differential exposure misclassification with bias towards the null is likely in cohort studies. There is no evidence to suggest that BPA exposure classification would differentially depend on whether a person developed cancer (in cohort studies). However, in case-control studies, differential over-recall of exposure in cases resulting in bias away from the null is possible given that the general public may have been aware of BPA use in the linings of cans and bottles. JEMs were used in population-based studies in which few participants had substantial occupational BPA exposure; therefore, such JEMs were underpowered to detect BPA exposure in the studies reviewed [94]. Furthermore, JEMs do not capture the primary source of BPA exposure of dietary exposure in the general population. Bias towards the null is likely. For the biomonitoring studies, analytical chemistry methods, such as mass spectrometry (MS)-based methods, are considered the most accurate and precise methods for measuring BPA [95]. The “gold standard” for measuring BPA in urine biomonitoring studies is solid-phase extraction coupled with isotope dilution–HPLC (high-performance liquid chromatography)–MS/MS because of its high level of accuracy, negligible interference, and ability to identify chemical structures [27, 96]; although the major limitation is the high cost per sample [27]. Liquid chromatography (LC) with fluorescence detection (FD)-based methods can be less sensitive – the limit of detection (LOD) is generally higher than for MS-based methods (see below) [27]. ELISA (enzyme-linked immunosorbent assay) is cost-effective but is not the preferred method to detect BPA. ELISA can be less specific than analytical chemistry methods due to potential for cross-reactivity with other substances, however if information about cross-reactivity and standard validations are included, these data should be considered valid [27]. Bias towards the null is likely with less sensitive methods, while the direction cannot be predicted with less specific methods. 3.1.4 Quality assurance parameters for BPA detection Quality control (QC) for BPA detection in epidemiologic studies can be evaluated using several performance parameters, such as LOD, limit of quantification (LOQ), repeatability, recovery, linearity and range of calibration curve. For the LOD and LOQ, defined as the lowest concentration of the analyte that can be reliably detected or quantified, higher values indicate lower sensitivity to detect a BPA analyte [97]. Detection limits vary between assay methods, laboratories, and even within a laboratory over time [98]. This can result in a large percentage of imputed measurements, which are subject to exposure misclassification, likely non-differential, and bias risk estimates towards the null. The number of participants with BPA levels below the LOD can be substantial (up to 60-85%) in studies using less-sensitive methods or in populations with relatively low BPA exposure; for example, only 14.8% of samples in López-Carrillo et al. (2021) were above the study LOD, which was 2.78 ng/ml, the highest reported LOD in any epidemiologic study reviewed. To address this issue, studies either omit or impute values for samples below the LOD (e.g., assigning a value of zero, the LOD, or some function of the LOD). Both approaches introduce bias into the analysis to varying degrees, based on the sample size, proportion of observations below the LOD, and the imputation method used [98-104]. Studies with low detection rates are of concern due to the potential for measurement error introduced when imputing a large number of BPA levels for analysis. 3.1.5 Biological matrix Urine is considered the optimal biological matrix for measuring BPA [72, 105]. To enable comparisons between individuals, urinary concentrations of chemicals such as BPA are often adjusted, most commonly for creatinine [106]. Studies that report only unadjusted urinary levels may introduce bias, either towards or away from the null [107, 108]. The type of urine sample may also affect the sensitivity of the assay. Spot urine samples could poorly estimate chronic BPA exposure [78] because of its potentially large variation over time [109]. A first morning urine void or 12-hour overnight samples may be more concentrated than a simple spot sample and therefore have greater sensitivity to detect an effect [110]. Measuring BPA in highly concentrated urine samples could result in greater potential for detection and hence attenuate the effect of potential exposure misclassification [19]. The use of dilute samples may result in bias towards the null due to greater difficulty in detecting the BPA analyte. Serum quantification of BPA is more challenging partly because levels are typically orders of magnitude lower than those in urine [105, 111-113] and are likely less reliable due to pharmacokinetics (rapid metabolism and excretion) and, without rigorous QC efforts, the potential for external contamination [72]. The higher BPA concentrations in urine compared to other tissues and fluids facilitates quantification. Lower blood concentrations of BPA biomarkers increase the likelihood that external contamination obscures true exposures [72]. While some studies suggest that adipose tissues may serve as a reservoir for BPA [21], additional data are needed to verify this and better characterize the intra-individual variability in BPA measurements in breast adipose tissue. 3.1.6 BPA Analyte BPA is rapidly metabolized and excreted as conjugated metabolites, mainly as a glucuronide (BPA-G) and to a lesser extent as a sulfate (BPA-S) [113]. The free (unconjugated) form of BPA (BPA-F) represents a small fraction of total BPA in the body and may reflect contamination of BPA-F leaching into a sample from external sources [113, 114]. Total BPA is comprised of BPA-F and at least one conjugated BPA metabolite; it is considered optimal for assessing exposure to BPA [115, 116]. Single analyte approaches (e.g., BPA-F, BPA-G, BPA-S) do not capture all forms of BPA and therefore underestimate exposure [24-26, 117] and likely bias towards the null. 3.1.7 Contamination BPA can be a component of collection materials or analytical equipment [27], which could contaminate samples in biomonitoring studies and inflate exposure levels in all study participants. Samples could also be contaminated by environmental sources of BPA, which would overestimate exposure [105, 114, 118]. Because BPA is ubiquitous, the reference group may have some level of background BPA exposure; this would attenuate risk estimates towards the null. Measuring the conjugated form of BPA reflects BPA metabolism and therefore can limit the effect of potential BPA contamination during sampling or analysis. There are several QC measures to minimize BPA contamination (e.g., use of BPA-free materials, strict cleaning protocols for lab equipment and surfaces, engineering controls such as use of clean rooms) or estimate contamination levels (e.g., use of blank samples without BPA alongside actual samples, performing replicate tests on the same sample to identify variability caused by contamination, use of homogeneous matrix-based quality control materials within the expected concentration ranges of the study samples as well as spiking samples with known quantities of BPA to assess recovery rates and identify potential contamination or loss during analytical procedures, and calibrating and maintaining equipment) [118, 119]. Such QC measures were carefully assessed for each publication reviewed. CRITICAL REVIEW OF EPIDEMOLOGIC STUDIES OF BPA AND CANCER 3.2 Breast Cancer Breast cancer was the most studied outcome of the epidemiologic studies identified (16 studies). All but three of these studies adjusted for obesity/body mass index (BMI), an important potential confounder [91, 120, 121]; only two studies stratified the analyses by hormone receptor subtype (estrogen or progesterone receptors) [122, 123]. Table 1 presents details of the exposure characteristics of these studies and their results, including the major strengths and limitations identified using the domain-based approach to study assessment. Biomonitoring was used to estimate BPA exposure in all but one study [91], which used a JEM in an exploratory case-control study conducted in a general population sample in Massachusetts, USA. The prevalence of occupational BPA exposure was low (<1% only BPA, 12% any BPA); therefore, there was inadequate statistical power to detect an association. An OR of 0.8 (95% confidence interval (CI): 0.5–1.4) was reported for both the categories of ‘only BPA exposure’ (two exposed cases) and ‘BPA plus other xenoestrogens’ (23 exposed cases). The analyses could not disentangle the effect of BPA from other co-exposures and the models were not adjusted for BMI. Other limitations were the lack of information on intensity and level of exposure and the crude categorization of “any” vs “no” exposure and combining groups of women in the low and high intensity exposure subgroups. Grouping the few women with high intensity with those of low intensity of exposure (expected to be the majority of women) would attenuate risk estimates towards the null. For the review of the breast cancer evidence, the biomonitoring studies are presented first by biological matrix, and then by the timing of collection for urine sampling. 3.2.a Urinary BPA measurements BPA was measured in urine in 11 reports of breast cancer: one nested case-control study [123], seven case-control studies [117, 120-122, 124-126], and three cross-sectional analyses from the NHANES [127-129]. Samples were adjusted for creatinine in all but one study [117]. Timing of urine sample collection was also considered, since a first morning urine void may be more concentrated than a simple spot sample and therefore have greater sensitivity to detect effects [110]. Results and characteristics were mixed among the three breast cancer studies that measured BPA in first morning void or overnight urine [117, 121, 123] and also among the six studies that either collected spot urine samples [120, 125, 128] or did not specify the sample type [122, 124, 126] (e.g., first morning void, overnight samples, etc.). The latter studies that did not specify sample type also lacked reporting on other important study details (e.g., BPA analyte, QC measures, risk estimates). All but one study [123] had the potential for reverse causation because samples were collected after diagnosis. The majority of studies used LC with MS for detection and collected a single urine sample for each participant, which was post-diagnosis in the cross-sectional and case-control studies. Limitations were the inability to characterize long-term BPA exposure in all studies due to the single sample, failure to establish a temporal association, and the potential for reverse causation from biomarker measurements in post-diagnostic samples. The Multiethnic Cohort [123] was the only study to measure total BPA prospectively before diagnosis. There was no association with postmenopausal breast cancer for the highest tertile of BPA level (>1.76 ng/mg). The OR was 0.84 (95% CI: 0.67–1.06) for the 2nd tertile (>0.84 to ≤1.76 ng/mg BPA) when compared to the lowest tertile (≤0.84 ng/mg BPA). This general pattern of association did not change in several sensitivity analyses stratified by hormone receptor positivity, BMI, years of follow-up, stage at diagnosis ( in situ vs invasive cancer), or by use of hormone replacement therapy (HRT) at urine collection. Reverse causation was not a concern, but collection of a single urine sample was a limitation. Although at least one validation measure was presented, within-batch variability was high (21.9%). BPA was correlated with several other chemicals, which were not adjusted for in the analyses. The time window of susceptibility to breast cancer may have been missed, as only women in their 60s were sampled. In a case-control study from Mexico, Lopez-Carrillo et al. [121] found positive associations with urinary free BPA detected at levels 7–10 times greater than the other studies that measured total BPA in urine [117, 120]. The OR for the highest exposure category (>12.05 μg/l BPA-F) was 2.31 (95% CI: 1.43–3.74) and the increase remained in sensitivity analyses among women whose urinary BPA had a recovery ≥ 80% (odds ratio (OR): 1.66; 95% CI: 1.28–2.14) and after excluding women with undetectable BPA (OR: 4.43; 95% CI: 1.89–10.42). Limitations were the use of FD, a high LOD and subsequently a large percentage of samples (85.2%) below the LOD, for which exposure levels were imputed. Therefore, it is unclear if the contrast between this and other studies is due to actual differences between exposures or measurement error. The analyses were adjusted for creatinine levels and age, but not obesity or other potential confounders. In a case-control study from Tehran, Iran [117] of 41 breast cancer mastectomy patients and 11 reduction mammoplasty patients, all lifetime non-smokers, the OR was 10.59 (95% CI: 1.62–65.7) for BPA measured in first morning spot urine samples without adjustment for creatinine. ELISA was used, but the potential to cross-react with other substances could explain the high detection of BPA in both cases (93%) and controls (82%). Breast adipose tissue samples were also collected; BPA concentrations in urine and tissue were correlated in cases (r = 0.896, p-value 0.05). Study participants were not matched on potential confounders; the lack of matching in the design does not ensure comparability between the case and control groups. It was not reported how samples below LOD were treated. Of the five reports that collected spot urine [120, 125, 127, 128], only one reported a positive association. A case-control study from Wuhan, China reported an OR of 1.54 (95% CI: 1.34–1.77) per μg/g unit increase in total BPA [120]. ORs above 1.0 were also reported in analyses of the interaction of high and low BPA levels with several SNPs in the cytochrome P450 genes (CYP19A1, CYP1A1, CYP17A1, CYP2E1, CYP24A1), but severe limitations in reporting study details and analyses warrant cautious interpretation of these findings. There was no correction for multiple comparisons; observed associations could reflect false positive results. Selection bias was difficult to assess due to lack of detailed description of the differences between people included in the study versus those who were eligible, limited detail on sociodemographic characteristics, and no information on response rates. This study matched controls to cases by abortion status (not further defined) even though it is not a risk factor for breast cancer nor a confounder in its association with BPA. Analyses were not adjusted for BMI. There was potential for bias towards the null because the 1st and 2nd tertiles of BPA exposure were combined and compared to the last tertile. Null or inverse associations with log-transformed BPA levels (analyte unspecified) were reported in a case-control study from Long Island, USA [125]. The ORs for breast cancer incidence were 0.91 (95% CI: 0.8–1.02) overall, 0.78 (95% CI: 0.66–0.93) in women with a BMI 25 kg/m². Results were similar when restricted to breast cancer-specific mortality. There was no internal consistency in the analyses reported by quintile of BPA exposure, and there did not appear to be an exposure-response relationship (p-value for test for trend was not reported). The BPA analyte was not specified, there was a lack of reporting on QC measures, a relatively high LOD, and imputation of exposure levels for nearly a fifth (18.3%) of the samples below LOD. The three studies that did not specify the type of urine sample (all case-control design) were also limited by lack of reporting study details. Two studies, from India and Taiwan, did not report a risk estimate but found higher concentrations of BPA analytes in the urine of cases than in controls [124, 126]. Inconsistent results were observed within a population-based case-control study of postmenopausal breast cancer conducted in two centers in Poland [122]. Although BPA-G levels were higher in Warsaw than in Lodz, a positive association was observed with BPA-G analyzed as a continuous variable in Lodz only (OR, 1.32; 95% CI: 1.00–1.73) but not in Warsaw (OR: 0.94; 95% CI: 0.81–1.11). For categorical analyses, the OR was increased (OR: 1.7; 95% CI: 1.15–2.52) in only the 2nd quartile (2.06–4.16 BPA-G ng/mg) of the overall analyses and also in analyses restricted to ER-negative breast cancer. The lack of reporting of the LOD or QC measures are further limitations. 3.2.b Breast adipose tissue BPA measurements Two small hospital-based case-control studies measured BPA in tissue [117, 130] from breast cancer mastectomy cases and breast reduction mammoplasty controls. Both studies took measures to limit contamination (including use of BPA-free sampling materials). The presence of selection bias was difficult to assess due to the presentation of few sociodemographic variables. Selection bias was a concern in both studies as all participants were selected from a single referral center (which may not reflect the underlying study population), controls were younger than cases, and neither study matched cases and controls on potential confounders. One study reported difficulty in enrolling healthy controls from the same referral center [117]. In Massachusetts, Reeves et al. [130] conducted one of the few studies to have collected more than one biological sample per person. Cases were women undergoing unilateral or bilateral mastectomy for breast cancer treatment and controls were undergoing elective reduction mammoplasty. In cases, a normal tissue sample away from the tumor was collected; a subset also provided a tissue sample from the unaffected breast to simulate tissue samples from controls. Another subset of cases and controls had two samples collected from the same breast. BPA levels were highly variable both within-breast and between breasts, with coefficients of variation ranging from 8.9% to 141.4% in replicate samples with BPA >LOQ. An OR of 0.9 (95% CI: 0.4–2.0) was reported for cases with detectable BPA-F (>LOQ of 0.38 ng/g) in breast adipose tissue, using a group of ‘reduction mammoplasty controls’ (instead of an unexposed/low exposed) as the reference category. The analyses were difficult to interpret as the ratio of the odds of exposure in case vs. control groups was not calculated. Limitations of this study were that the LOQ was relatively high, and exposure levels were imputed for a large percentage (69.4%) of samples below the LOQ. Kesharvarz-Maleki et al. [117] measured BPA in urine as well as in breast adipose tissue using ELISA (see Section 3.2.a). Cross-reactivity with other substances could explain the very high OR for BPA in breast adipose tissue (OR: 54.96; 95% CI: 2.08–1372.55). A strength of this study was that BPA was measured in most participants in two biological matrices, which was correlated in cases (P 0.05). The breast adipose tissue sample was collected in proximity to the tumor in cases and therefore may not approximate the normal tissue physiology for comparison to the controls. Other limitations were collection of a single sample per matrix, nearly half (45%) of the control tissue samples were below the LOD, not reporting how samples below the LOD were treated. 3.2.c Serum BPA measurements Three breast cancer studies measured BPA in serum [131-133]; all were limited by use of a single sample. In a case-cohort analysis of the Spanish arm of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort [132], there was a 4.7% increase in the risk of breast cancer (hazard ratio (HR): 1.047; 95% CI: 0.98–1.12) for every 5 ng/ml increase in total BPA level, measured in samples collected at enrollment, prospectively before diagnosis. The median follow-up was 17 years. This study was limited by the relatively high LOD and the imputation of exposure levels for nearly a third of participants below the LOD (30.6%). Case-control studies from Korea [133] and Nigeria [131] reported higher serum BPA levels in cases than in controls, but no risk estimates were reported. 3.3 Prostate cancer Six studies of prostate cancer (seven reports) estimated exposure to BPA using different methods; four were cross-sectional and are not described further [127, 134-136]. Both a case-control study and case-cohort analysis found an association [88, 89, 132] (Table 3). A hospital-based case-control study in Hong Kong assessed cumulative BPA exposure through ingestion using a tool reconstructed through questionnaire data and a literature review of BPA levels, similar to construction of a JEM [88, 89]. Increasing cumulative BPA exposure was associated with prostate cancer, with a significant exposure-response (OR high exposure: 1.88; 95% CI: 1.24–2.86; p -value for trend = 0.014). Misclassification of BPA exposure was possible as there were no considerations of exposure variations over time. In a case-cohort analysis within the Spanish EPIC cohort [132], prospectively measured serum BPA was not associated with prostate cancer in linear models but there was an increased risk of prostate cancer with every ng/ml increase in total BPA level (HR: 1.04; 95% CI: 0.99–1.08) and in tertiles compared to those below the LOD. This study was limited in its exposure assessment by a single sample, the use of serum as a biological matrix, and a relatively high LOD. 3.4 Other cancers The appendix presents the results of the epidemiologic studies of BPA and other cancer sites: colorectum, gallbladder, lung, bone, skin, cervix, endometrium/uterus, ovary, bladder, eye, brain, thyroid, lymphohematopoietic system, all cancers combined. The results were inconsistent and there were limitations in the design and reporting for many of these studies (Please see Appendix and Appendix Table 3). 4. Discussion This is the first critical review on the carcinogenicity of BPA to focus on the challenges with exposure characterization of BPA in cancer epidemiologic studies and the direction of potential sources of bias in each study. These data were first presented in December 2022 at a public meeting of California’s Proposition 65 CIC [33, 34] and have since been summarized in subsequent review publications [137, 138]. Although at least one recent review of the human evidence related to carcinogenicity of BPA [137] and two meta-analyses of breast cancer have been published [70, 71], OEHHA [33] was the first such review to comprehensively summarize the characteristics of exposure assessment and study design needed to interpret the epidemiological studies. After careful consideration and thoughtful deliberation by the CIC of all lines of evidence (epidemiology, animal bioassays, mechanistic evidence), BPA was not placed on the Proposition 65 list of carcinogens, with a vote of five in favor and six against. The CIC deemed the available epidemiologic evidence inadequate. There were few epidemiologic studies on BPA and cancer. For many cancers, a single study was available; there was inadequate evidence to make a conclusion on these sites. The majority of the studies focused on breast cancer (n=16), where the evidence was inconsistent. For the other cancer sites with more than one study (prostate, thyroid, endometrium, colorectum, lung), some positive associations were observed; however, limitations in methodology for all studies warrant cautious interpretation. For assessing study quality, special attention was given to the assessment of biases, which in observational studies are usually grouped into selection bias, information bias and confounding [37, 139]. Confounding is an important consideration for causal inference in observational studies, and few of these studies adequately adjusted for important confounders. However, information bias from exposure assessment was found to be the key consideration for evaluating this body of evidence. Our review summarized information on the methods of assessing exposure to BPA from previous reviews [27, 95] to interpret the impact of potential biases in interpreting the epidemiologic studies. The major limitation of all studies was the inability to reliably capture long-term BPA exposure due to the potential for considerable measurement error. Sources for this error stemmed from how the methods (i.e. biomonitoring, questionnaires, JEMs) were applied. For biomonitoring studies, sources of measurement error were BPA’s short half-life, collection of a single BPA measurement, and timing of BPA assessment. None of the studies successfully evaluated, or accounted for, temporal variation in BPA exposure within and across individuals. Thereby, it was difficult to correctly assign individuals in these studies to categories or levels of BPA exposure and to detect associations with chronic disease outcomes, such as cancer. Questionnaires and JEMs have the ability to evaluate past exposure to BPA, which is more relevant to studying cancer outcomes due to the long latency period between onset of exposure and disease diagnosis [140]. However, questionnaires and JEMs query suspected exposures from specific sources and therefore may not capture the widespread exposures to BPA from multiple sources [87, 141]. JEMs were primarily used in general population studies where occupational exposures were low [90-93] and the primary exposure route is ingestion. Therefore this method may lack the sensitivity to detect an association with BPA [94], if one exists. One study from Hong Kong attempted to characterize cumulative BPA exposure via ingestion using a tool reconstructed through questionnaire data and a literature review of BPA levels, similar to construction of a JEM [88, 89]. Given that biomarkers of BPA exposure are short lived, the approach of Tse et al. could be a more cost-effective method for estimating long-term BPA exposure in future studies but requires validation. However, questionnaire approaches to assess BPA exposure [88, 89] are inherently limited in the general population, given many varied sources of exposure that are not typically sufficiently incorporated into questionnaires and, in many cases, are unknown to the participant [13, 87, 141]. For example, one attempt to validate a dietary exposure assessment questionnaire tool found that known dietary sources of BPA exposure explained less than half the variability in urinary BPA levels, regardless of diet assessment method. This study used a food frequency questionnaire with 24-hour recalls over multiple days with daily biomonitoring measures in healthy adults [87]. Biomonitoring was used in the majority of studies, in which BPA was measured in samples generally collected at a single point in time. While biomonitoring has the advantage to account for exposures from all possible sources and better reflect internal circulating BPA levels [27], BPA biomarkers are short-lived and only capture recent exposure. Therefore, a single biomarker measurement does not account for the potentially large temporal variations in BPA exposure that may occur across hours, days, weeks, and years [17-19]. None of the biomonitoring studies reviewed collected samples longitudinally at multiple time points. Timing of exposure assessment was also a concern in the biomonitoring studies, for which the majority measured BPA in biological samples after cancer diagnosis using a cross-sectional design. Only a few collected biological samples prospectively [123, 132, 142, 143]. Studies of cross-sectional design could not establish a temporal association because exposure and outcome data are collected concurrently and there were no data from other evidence streams to inform on temporality. Reverse causation is possible since BPA levels may be altered by physiological or behavioral changes associated with the onset of disease and treatment [144, 145]. Failure to detect true causal effects is also a concern since exposure was assessed long after the expected time window for cancer causation, which is generally considered to occur many years prior to a cancer diagnosis. Moreover, the prenatal and neonatal periods could represent the most vulnerable windows of exposure to BPA [146], as evidenced by rodent studies of low-dose BPA prenatal and neonatal exposure that demonstrate subsequent alterations in estrous cycles and in the prostate and mammary gland tissues of those animals later in life [27]. None of the cancer studies reviewed estimated BPA exposure during these time periods. Cross-sectional studies were reviewed for completeness with the acknowledgement that their design did not permit causal inference of the association between BPA and cancer. Furthermore, many of these studies lacked key details in data reporting. Cross-sectional designs were also limited by the use of prevalent cases and thus there is concern of length-biased sampling, in which individuals with the longest lasting disease are more likely to be selected into the study [45]. This can be an important consideration for cancers with higher rates of survival, such as breast, prostate, and thyroid cancers. Prevalent cases could differ in characteristics related to BPA levels (such as exposure patterns or metabolism) that could affect their survival compared to the incident cases captured in case-control or cohort designs. It is worth noting that case-control studies that measured BPA in biological samples post-diagnosis were similarly uninformative. However, the case-control studies enrolled incident cases whereas cross-sectional studies enrolled prevalent cases; a crucial distinction for causal inference which was the objective of the hazard identification exercise. In addition, there was large variation in BPA measurement assay quality between studies, as denoted by the LOD or LOQs. The LOD and LOQ for total BPA in any matrix (urine, serum, or breast adipose tissue) in the studies that used MS-based methods were all below 0.5 nanograms per milliliter (ng/ml) or gram (ng/g), with many studies reporting LODs in urine below 0.05 ng/ml. However, some studies using non-MS-based methods reported higher LODs or LOQs, resulting in BPA being detected in fewer subjects. The approaches taken in handling data where BPA was not detected, such as imputing BPA levels or omitting individuals with non-detectable levels, can introduce bias in exposure characterization [98-104]. For example, Lopez-Carrillo et al. [121] reported an LOD of 2.78 ng/ml, the highest reported LOD in any epidemiologic study reviewed, and only 14.8% of samples tested in this study were above this LOD. As a result, most samples included in the analyses were imputed, which could result in exposure measurement error. Therefore, it is difficult for the reviewed epidemiologic studies to correctly assign individuals to categories or levels of BPA exposure. If the sources of measurement error result in non-differential exposure misclassification, risk estimates would likely be biased towards the null. Imputing exposures could result in bias either away from or towards the null. Furthermore, since exposure to BPA is widespread in the population, exposure contrasts may be low, which also reduces the sensitivity of these studies to detect an effect. None of the epidemiologic studies of cancer outcomes were conducted in highly exposed workers, a population that could allow assessment of high exposures with large exposure contrasts. Future efforts to assess the carcinogenicity of BPA in epidemiologic studies could harness existing biomonitoring efforts in workers highly exposed to BPA, with prospective, longitudinal collection of quantitative exposure measures [147]. For example, NIOSH established a cohort in 2013–2014 to measure BPA exposure in 77 US manufacturing workers from six companies that either made or used BPA, BPA-based resins, or BPA-filled waxes [16]. These workers handled BPA, often in large quantities, and were exposed to BPA mainly by inhalation and dermal absorption. Each participant provided seven urine samples over two consecutive workdays. On average, workers in the NIOSH study had urinary BPA levels approximately 70 times higher than adults in the US general population. There may be insufficient follow-up time currently to detect cancer outcomes as well as limited statistical power to detect associations for any particular cancer site. Informative future epidemiologic studies in highly exposed workers could assess acute endpoints involved in the established mechanisms of carcinogenesis [29, 148] coupled with high quality exposure data, as a more cost- and time-effective approach to evaluating the carcinogenicity of BPA. In summary, there are inadequate epidemiologic data on BPA, although this does not rule out its potential for carcinogenicity. There is a wealth of data on BPA’s potential carcinogenicity from animal bioassays and mechanistic studies [29]. Notably, BPA will also be reviewed by IARC, as it has been assigned a high priority based on relevant published mechanistic and animal bioassay evidence [30]. 5. Conclusions The epidemiologic evidence was inadequate to determine the carcinogenicity of BPA due to limitations in reliably characterizing long-term BPA exposure in study participants, few studies by cancer site and heterogeneity among those studies. However, there is a large evidence base indicating potential mechanisms of carcinogenesis. Future studies that are likely to be informative on the carcinogenic potential of BPA could be conducted within worker populations who are still highly exposed to BPA. This could involve prospective and longitudinal collection of exposure data (e.g., quantitative measurements, biomonitoring) with follow-up for outcomes such as cancer morbidity or acute effects involving established mechanisms of carcinogenesis. Abbreviations μg, microgram BMI, body mass index BPA, bisphenol A BPA-F, free bisphenol A BPA-G, BPA-glucuronide BPA-S, BPA-sulfate CI, confidence interval CIC, Carcinogen Identification Committee CYP450, cytochrome P450 ELISA, enzyme-linked immunosorbent assay EPIC, European Prospective Investigation into Cancer and Nutrition FD, fluorescence detection g, gram HAWC, Health Assessment Workspace Collaborative JEM, job exposure matrix HPLC, high-performance liquid chromatography HR, hazard ratio HRT, hormone replacement therapy IARC, International Agency for Research on Cancer LC, liquid chromatography LOD, limit of detection LOQ, limit of quantification ml, milliliter MS, mass spectrometry NTP, National Toxicology Program ng, nanogram OR, odds ratio PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses QC, quality control RR, relative risk SWIFT AS, Sciome Workbench for Interactive Computer-Facilitated Text-mining Active Screener US EPA, United States Environmental Protection Agency US FDA, United States Food and Drug Administration Declarations Ethics approval and consent to participate: N/A Consent for publication: All authors consent to publication. Availability of data and materials: All authors consent. This review and its protocol were not registered. Competing interests: None Funding: None Authors' contributions: NG and GO made equal contributions to preparing this manuscript for publication. NG drafted this manuscript and all co-authors contributed to the final text. NG, GO, MEM conceptualized the work and drafted the hazard identification document, which was the basis for this manuscript. The initial summarization, tabulation, and interpretation of the data were done by MEM for exposure characteristics and methods and NG, GO for the epidemiological studies. NF conducted the initial literature search. All other authors contributed to the execution and review of the final draft. Acknowledgements: We thank Ms. Lina Kamil for her assistance with earlier aspects of the literature review and the internal OEHHA reviewers for their careful review of the manuscript. 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Epidemiologic studies of BPA and breast cancer: exposure characterization and results by exposure matrix and year of publication Reference; Location; Years of BPA measurement; Study design Exposure assessment details 1 Analytical method and analyte 2 BPA levels LOD or LOQ (% below LOD) and methods for samples below LOD/LOQ Methods to limit contamination? QC measures? Main results Comments Exposure category or level Risk estimate (95% CI) Exposed cases Job exposure matrix Aschengrau et al. (1998) US 1983-1986 Case-control JEM based on NIOSH/NOES database, chemical production and usage information, and expert judgment of certified industrial hygienist Ever/never exposure (9.6% exposed to BPA; 0.8% exposed to BPA only) NA NA Adjusted OR Information bias: Possible. Next-of-kin interview; crude assignments (any vs no exposure); JEM used in general population with low occupational exposure prevalence to any or only BPA Confounding: No adjustment for BMI or job co-exposures Unexposed to xenoestrogens 1 158 Any BPA 0.8 (0.5–1.4) 25 BPA + other xenoestrogens 0.8 (0.5–1.4) 23 Only BPA – 2 Biomonitoring: Urine Trabert et al. (2014) Poland 2000–2003 Case-control Urine: single 12-hour overnight sample Method: HPLC-MS/MS Analyte: BPA-G Geometric mean (ng/mg): 4.11 (cases), 3.92 (controls) LOD: NR [cited method reports LOD of 0.005 ng/ml] (2.80%) Methods: Imputed as 0.1 g/mg Cr or included in first quartile Limit contamination: NR QC: NR Post-menopausal: OR, BPA-G (ng/mg Cr) Information bias: Measurement of urinary BPA-G may not adequately reflect exposure to BPA, due to the inter-individual variability in BPA glucuronidation. Confounding : Models may have over-adjusted for covariates. Log-transformed 1.04 (0.91–1.17) 575 7.80 1.09 (0.73–1.63) 143 Trend-test p -value: 0.59 Morgan et al. (2017) US (NHANES) 2005–2010 Cross-sectional Urine: spot sample Method: HPLC-MS/MS Analyte: Total BPA Geometric mean (ng/g): 1.06 (cases), 1.16 (controls) LOD/LOQ: NR Methods: Included in reference group Reported in NHANES OR, BPA (ng/g Cr) Selection bias: NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design. Information bias: Self-reported cancers susceptible to outcome misclassification. < LOD to 50% 1 44 ≥ 50% (0.42–1.23) 0.76 (0.45–1.3) 34 OR, BPA (ng/g Cr) < LOD to 50% 1 44 ≥ 50% (0.42–1.23) 0.73 (NR) 34 Yang et al. (2018) Taiwan 2013–2014 Case-control Urine: first morning void sample Method: HPLC Analyte: NR Mean (ng/mg): 14.17 (cases), 5.95 (controls) LOD/LOQ: NR Methods: Imputed as LOD/2 Limit contamination: NR QC: NR No risk estimate Notes: lack of details in reporting. The purpose of this study was to test whether exposure to BPA and phthalate metabolites, estimated from urinary concentrations, would be associated with ADAM33 expression and methylation profile between breast cancer patients and healthy controls. Parada et al. (2019) US 2007, 2010 Case-control Urine: spot sample Method: HPLC-MS/MS Analyte: Total BPA Median (ng/mg): 1.53 (cases), 1.69 (controls) LOD (ng/ml): 0.04 (18.3%) Methods: Imputed as the LOD/√2 Limit contamination: NR QC: NR OR, BPA (μg/g Cr) Selection bias: Large sample size Information bias : Exposure assessment expected to be of high quality; BPA analyses conducted by CDC laboratory. Narrow exposure range with low contrast, limiting ability to detect an effect. Exposure proxy may be affected by background contamination. Ln(BPA) 0.91 (0.8–1.02) NR < LOD–0.950 1 174 0.958–1.38 0.76 (0.53–1.09) 132 1.38–2.04 0.76 (0.53–1.09) 135 2.05–3.63 0.8 (0.56–1.15) 142 3.63–388 0.75 (0.52–1.08) 128 Trend-test p -value: 0.11 Keshavarz-Maleki et al. (2021) Iran 2018–2019 Case-control Urine: first morning void sample Method: ELISA Analyte: Total BPA 3 Geometric mean (ng/ml): 1.69 (cases), 0.83 (controls) LOD (ng/ml): 0.01 (7.32% cases, 18.18% controls) Methods: NR Limit contamination: Yes QC: NR OR, BPA (ng/ml) Selection bias: Selection of all subjects from single referral center may not reflect the underlying study population. Reported difficulty in enrolling healthy controls from same referral center. Limited number of sociodemographic variables presented. Controls not matched to cases, and may not reflect source population. Small sample size. Information bias: ELISA may cross-react with other substances. Unadjusted for creatinine. Exposure proxy may be affected by other substances. Notes: BPA measured in 2 matrices Continuous 10.59 (1.62–65.7) NR Lopez-Carrillo et al. (2021) Mexico 2007–2011 Case-control Urine: first morning void sample Method: HPLC/FD Analyte: Free BPA 4 Geometric mean (ng/ml): 20.81 (all), 28.11 (cases), 13.42 (controls) LOD (ng/ml): 2.78 (85.2%) Methods: Imputed as LOD/√2 (1.97 μg/l) Limit contamination: Yes QC: Yes OR, BPA (μg/l) Information bias : high LOD; BPA was imputed for the majority of cases (82%) and controls (88%); BPA-F susceptible to contamination Confounding : BMI not adjusted All women ≤1.39 1 319 All women 1.40–12.05 0.73 (0.39–1.35) 18 All women >12.05 2.31 (1.43–3.74) 57 Muthusamy et al. (2021) India NR Case-control Urine: spot sample Method: HPLC/FD Analyte: NR Mean (ng/ml): 5.76 (cases), 1.18 (controls) LOQ (ng/ml): 0.5 (16% cases, 36% controls) Methods: NR Limit contamination: NR QC: Yes No risk estimate Notes: lack of details in reporting. Wu et al. (2021) US 2001–2006 Nested case-control Urine: first morning void or overnight sample Method: LC-HRAM-MS Analyte: Total BPA Geometric mean (ng/mg) (95% CI): 1.17 (1.08–1.28) (cases), 1.15 (1.06–1.25) (controls) LOQ (ng/ml): 0.001 (2%) Methods: Imputed as LOQ/2 Limit contamination: NR QC: Yes OR, BPA (ng/g Cr) Information bias : BPA measured prospectively; however exposure proxy susceptible to background contamination. High within-batch variability (21.9%). Samples from postmenopausal women may reflect irrelevant time window of exposure. Notes: Several sensitivity analyses conducted by hormone receptor positivity (“ER+ or PR+”, or “ER– and PR–“), BMI, years follow-up, stage at diagnosis), use of hormone replacement therapy (HRT), race/ethnicity. ≤0.84 1 372 >0.84 to ≤1.76 0.84 (0.67–1.06) 313 >1.76 0.95 (0.75–1.21) 347 Trend-test p -value: 0.53 He et al. (2022) China 2016–2019 Case-control Urine: spot sample Method: UHPLC-HRMS Analyte: Total BPA without deconjugated BPA-S Geometric mean (ng/mg): 2.45 (IQR: 0.87–6.15) (cases), 1.19 (IQR: 0.60–2.15) (controls) LOD (ng/ml): 0.031 (% NR) Methods: Imputed as LOD/√2 Limit contamination: Yes QC: Yes OR, BPA (μg/g Cr) Selection bias: No detailed description of the analyzed vs target population, no information on response rates Information bias: False positives possible due to multiple comparisons of interactions between BPA and several SNPs in CYP genes Confounding: BMI not adjusted for Notes: Severe limitations in reporting study details and analyses. Inappropriate reference categories in stratified analyses Per μg/g unit increment (cont.) 1.54 (1.34–1.77) 302 ≤1.71 1 138 > 1.71 2.48 (1.78–3.49) 164 Cathey et al. (2023) US (NHANES) 2005–2016 Cross-sectional Urine: spot sample Method: HPLC-MS/MS Analyte: Total BPA Geometric mean (ng/mL): 1.49 (IQR: 2.40) LOD: NR (8.5%) Methods: Imputed as LOD/√2 Reported in NHANES OR, BPA (ng/g Cr) Selection bias: NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design. Information bias: Self-reported cancers susceptible to outcome misclassification. Notes: Cross-sectional design used to inform hypotheses in emerging cohort studies, not for causal inference. Sensitivity analyses stratified by race/ethnicity and sex to inform future analyses on disparities in associations between environmental exposures and cancer outcomes. Per IQR increase 1.06 (0.78–1.43) NR Xiong et al. (2025) US (NHANES) 2005–2014 Cross-sectional Urine: spot sample Method: HPLC-MS/MS Analyte: Total BPA Median (ng/ml): 0.41 (IQR: 1.52; range: -0.36–1.16) LOD (ng/ml): 0.40 (2005–2012); 0.20 (2013–2014) (9.54%) Methods: Imputed as LOD/√2 Reported in NHANES OR , BPA (ng/ml) Selection bias: NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design. Information bias: Self-reported cancers susceptible to outcome misclassification. Log10 BPA 0.95 (0.76 – 1.19) NR -1.96–0.00 1 NR 0.10–0.92 0.78 (0.45 – 1.37) NR 0.96–6.87 0.83 (0.44 – 1.56) NR Trend-test p -value: 0.511 Biomonitoring: Breast adipose tissue Reeves et al. (2018) US 2014–2015 Case-control Breast adipose tissue sample (one or more) Method: HPLC-MS/MS Analyte: BPA-F 3 Mean (ng/g): 0.71 (cases), 0.66 (controls) LOQ (ng/g): 0.38 (73.9% cases, 65.2% controls) Methods: Imputed as 0 Limit contamination: Yes QC: Yes OR, Detectable BPA (>LOQ of 0.38 ng/g) Selection bias: Possible. Controls were reduction mammoplasty patients that may not represent the source population. Information bias : BPA levels were highly variable both within-breast and between breasts Notes: Only study to account for repeated measurements; small sample size; unclear how the ORs were calculated (all cases were compared to controls). Controls 1 14 Cases 0.9 (0.4–2) 36 Keshavarz-Maleki et al. (2021) Iran 2018–2019 Case-control Breast adipose tissue sample Method: ELISA Analyte: Total BPA 3 Geometric mean (ng/g): 3.50 (cases), 1.50 (controls) LOD (pg/g): 0.065 (26.83% cases, 45.46% controls) Methods: NR Limit contamination: Yes QC: NR OR, BPA (ng/ml) Selection bias: Possible. All subjects selected from single referral center. Reported difficulty in enrolling healthy controls from same referral center. Limited number of sociodemographic variables presented. Controls not matched to cases, and may not reflect source population. Small sample size. Information bias: ELISA may cross-react with other substances. Unadjusted for creatinine. Exposure proxy may be affected by other substances. Notes: BPA measured in 2 matrices. Continuous 54.96 (2.08–1372.55) NR Biomonitoring: Serum Ajayi et al. (2014) Nigeria NR Case-control Serum sample Method: HPLC Analyte: NR Mean (ng/ml): 7.9 (cases), 2.99 (controls) LOD (ng/ml): 0.2 (% NR) Methods: NR Limit contamination: NR QC: Yes No risk estimate Notes: lack of details in reporting Yang et al. (2009) Korea 1994–1997 Case-control Serum sample Method: HPLC/FD Analyte: Conjugated BPA Mean (ng/ml): 1.69 Median: 0.043 LOD (ng/ml): 0.012 (49.2%) Methods: Imputed as LOD/2 Limit contamination: NR QC: NR No risk estimate Notes: lack of details in reporting Salamanca-Fernandez et al. (2021) Spain (EPIC study) 1992–1996 Case-cohort Serum sample Method: UHPLC-MS/MS Analyte: Total BPA Geometric mean (ng/ml): 1.12 (cases) LOD (ng/ml): 0.2 (24.3% cases, 36.6% controls) Methods: Imputed as the LOD/√2 Limit contamination: NR QC: NR HR, continuous Information bias : ~30% of samples <LOD were imputed. Serum may under-detect BPA exposure Notes: Large study with prospective sample collection and adequate follow-up time (median 16.9 years). BPA levels (5 ng/ml increase) 1.047 (0.98–1.12) 2306 Log2(BPA) 1.011 (0.97–1.06) 2306 HR, BPA (ng/ml) < LOD 1 705 0.2–1.8 0.82 (0.61–1.1) 562 1.8–5.1 0.875 (0.65–1.18) 556 5.1–68.9 1.127 (0.84–1.51) 483 1 All biomonitoring studies were limited by a single measurement of BPA per biological matrix 2 Adjusted for creatinine, unless otherwise noted 3 unadjusted for creatinine 4 unadjusted concentrations of BPA analytes were included in the analysis with urinary creatinine added as a separate independent variable, per the method of Barr et al. 2005 Cr, creatinine NR, not reported Cont., continuous ELISA, Enzyme linked immunosorbent assay HPLC, High-pressure liquid chromatography HPLC/FD, High-pressure liquid chromatography equipped with a fluorescence detector HPLC-MS/MS, High-pressure liquid chromatography with tandem mass spectrometry detection LC/HRAM-MS, liquid chromatography-high-resolution accurate-mass mass spectrometry UHPLC-HRMS, Ultrahigh-performance liquid chromatography-high-resolution mass spectrometry UHPLC-MS/MS, Ultra-high performance liquid chromatography with tandem mass spectrometry detection Table 2. Epidemiologic studies of BPA and prostate cancer: exposure characterization and results by exposure matrix and year of publication Reference; Location; Years of BPA measurement; Study design Exposure assessment details 1 Analytical method and analyte 2 BPA levels LOD or LOQ (% below LOD) and Methods for samples below LOD/LOQ Methods to limit contamination? QC measures? Main results Comments Exposure category or level Risk estimate (95% CI) Exposed cases Questionnaire Tse et al. (2017; 2018) China 2011–2016 Case-control Tool that reconstructed BPA exposure through questionnaire data (use of specific types of food and beverage containers and handling conditions) Cumulative BPA index: low, middle, high NA NA OR, Cumulative BPA Index (main model) Selection bias: Possible. Use of hospital controls may differ in lifestyle habits from general population. Information bias: Misclassification of BPA exposure possible: no considerations of exposure variations over time, exposure through sources other than specific types of food and beverage containers. Low 1 75 Middle 1.66 (1.15–2.4) 232 High 1.88 (1.24–2.86) 124 Trend-test p-value: 0.014 Never 1 NR Ever 2.1 (1.0–4.3) 9 Biomonitoring: Urine Tarapore et al. (2014) US NR Cross-sectional Urine: spot sample Method: HPLC-ESI-MS/MS Analyte: Total BPA Geometric mean (ng/mg): 5.74 (cases), 1.43 (controls) LOD (ng/ml): 0.05 (% NR) Method: Imputed as the LOD/√2 Limit contamination: NR QC: Yes No risk estimate. Salamanca-Fernandez et al. (2021) Spain 1992–1996 Case-cohort Urine: spot sample Method: UHPLC-MS/MS Analyte: Total BPA Geometric mean (ng/ml): 1.33 (cases) LOD (ng/ml): 0.2 (24.3% cases, 36.6% controls) Method: Imputed as the LOD/√2 Limit contamination: NR QC: NR HR, continuous Large study with prospective sample collection and adequate follow-up time (median 16.9 years). ~30% of samples <LOD were imputed. BPA levels (5 ng/ml increase) 0.99 (0.92–1.06) NR Log2(BPA) 1.04 (0.99–1.08) NR HR, BPA (ng/ml) < LOD 1 NR 0.2–1.8 1.40 (1.05–1.88) NR 1.8–5.1 1.37 (1.02–1.82) NR 5.1–68.9 1.31 (0.98–1.74) NR Cathey et al. (2023) US (NHANES) 2005–2016 Cross-sectional Urine: spot sample Method: HPLC-MS/MS Analyte: Total BPA Geometric mean (ng/mL): 1.49 (IQR: 2.40) LOD: NR (8.5%) Methods: Imputed as LOD/√2 Reported in NHANES OR, BPA (ng/g Cr) Selection bias: NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design. Information bias: Self-reported cancers susceptible to outcome misclassification. Notes: Cross-sectional design used to inform hypotheses in emerging cohort studies, not for causal inference. Sensitivity analyses stratified by race/ethnicity and sex to inform future analyses on disparities in associations between environmental exposures and cancer outcomes. Per IQR increase 0.80 (0.58–1.12) NR Per IQR increase 0.87 (0.51–1.48) NR Alvarez-Gonzalez et al. (2024) Spain 2018–2023 Cross-sectional Urine: spot sample Method: GC-MS Analyte: NR Median (ng/ml): 20.0 (IQR: 13.1–27.4) (cases); 10.0 (IQR: 3.6–15.4) (controls) LOD: NR Methods: NR Limit contamination: NR QC: NR OR, BPA Notes: lack of details in reporting Full model 1.32 (1.09–1.59) NR Backwards variable selection 1.28 (1.09–1.51) NR Wang et al. (2024) China 2009–2019 Cross-sectional Urine: spot sample Method: HPLC Analyte: NR Mean (μg/g Cr): 1.20 (cases); 0.79 (control) LOD (μg/l): 0.12 Methods: Imputed as LOD/√2 Limit contamination: yes QC: Yes OR, BPA (μg/g Cr) <0.45 1 21 ≥0.45 – < 1.43 2.87 (1.16–7.12) 96 ≥1.43 7.33 (2.63–20.43) 72 1 All biomonitoring studies were limited by a single measurement of BPA per biological matrix 2 Adjusted for creatinine, unless otherwise noted Cr, creatinine NR, not reported HPLC-ESI-MS/MS, High-performance liquid chromatography coupled with electrospray triple-quadrupole mass spectrometry HPLC-MS/MS, High-pressure liquid chromatography with tandem mass spectrometry detection UHPLC-MS/MS, Ultra-high performance liquid chromatography with tandem mass spectrometry detection Additional Declarations No competing interests reported. Supplementary Files 3BPAepiappendixMay18.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Jul, 2025 Reviews received at journal 30 Jun, 2025 Reviews received at journal 19 Jun, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers invited by journal 28 May, 2025 Editor assigned by journal 26 May, 2025 Submission checks completed at journal 26 May, 2025 First submitted to journal 25 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6742025","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":473698107,"identity":"294ecce7-3862-4aa7-9320-4bfe4a167870","order_by":0,"name":"Neela Guha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIie3NoQvCQBTH8bei5ebqCaL/wg2DCP4xJ4LJLAZBQbg0+wbi32Ayv/FglmleEHTFJDibgoJos3iuCd43/cL78ABMpt/MQhggAHuOZ/iFQYhfBHIQS+UhjeIE8TrfVhseIZ4VVEuJ/EyaXiTD6fJQr6yVDAMF9bKOiKQn0F5S23eYIFtBe6Elu1MW3mc08h0no7uCkZ4kDMgek+S2B2QpkEJL4q6gSnRwfRaJ0NtwN4j3GrKiND0OtzXOOun+0m/VSivNl/esAs9z/uqWW5hMJtMf9ACQmlOl16SvoAAAAABJRU5ErkJggg==","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":true,"prefix":"","firstName":"Neela","middleName":"","lastName":"Guha","suffix":""},{"id":473698108,"identity":"d1905421-b0c1-4c8e-8b28-f51f1f33d776","order_by":1,"name":"Gwendolyn Osborne","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"Gwendolyn","middleName":"","lastName":"Osborne","suffix":""},{"id":473698109,"identity":"b82682dd-316f-40a3-b00b-a8209aa019f0","order_by":2,"name":"M. Elizabeth Marder","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Elizabeth","lastName":"Marder","suffix":""},{"id":473698111,"identity":"63684693-1678-4556-a7be-89313d7fd520","order_by":3,"name":"Martha Sandy","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"Martha","middleName":"","lastName":"Sandy","suffix":""},{"id":473698114,"identity":"4fc1dd7d-d5cf-4c44-9fa7-75564dbe7aac","order_by":4,"name":"Meng Sun","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Sun","suffix":""},{"id":473698117,"identity":"0126aecc-5f2c-469a-851d-ed8ceabbe20a","order_by":5,"name":"Nancy Firchow","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"Nancy","middleName":"","lastName":"Firchow","suffix":""},{"id":473698119,"identity":"24586d5b-322c-405d-8837-a5e9df0e1537","order_by":6,"name":"Vincent Cogliano","email":"","orcid":"","institution":"California Office of Environmental Health Hazard Assessment","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Cogliano","suffix":""}],"badges":[],"createdAt":"2025-05-25 06:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6742025/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6742025/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85643041,"identity":"8082970a-2235-4c69-b7d5-ca7a3e3961c9","added_by":"auto","created_at":"2025-06-30 08:05:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224049,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA diagram to document study inclusion and exclusion\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6742025/v1/e1dcb1a1568d0be8f80e16c9.png"},{"id":85644492,"identity":"9033650f-07cb-4497-8034-7115246e3292","added_by":"auto","created_at":"2025-06-30 08:13:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9120746,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6742025/v1/8d388c1b-ed2a-4f03-b432-3a968fe8b331.pdf"},{"id":85643042,"identity":"12393b37-53dc-419c-bb6e-499c8ba1ddc5","added_by":"auto","created_at":"2025-06-30 08:05:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":141936,"visible":true,"origin":"","legend":"","description":"","filename":"3BPAepiappendixMay18.docx","url":"https://assets-eu.researchsquare.com/files/rs-6742025/v1/1460623d3c5be25666381e2b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bisphenol A and cancer: a critical review of the epidemiologic literature with an emphasis on exposure assessment","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e1.a. Rationale\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBisphenol A (BPA) is a high production volume chemical, with over 13 billion pounds estimated to have entered the global market in 2022 alone [1]. In the US, domestic production has exceeded 1 billion pounds each year for at least two decades. BPA has been extensively used over decades in many industrial applications (e.g., mostly in the manufacture of epoxy resins and polycarbonate plastics) and in a wide variety of consumer products (e.g., baby bottles, toys, reusable water bottles and food containers, polyvinyl chloride stretch films, papers, cardboards, thermal receipts, dental sealants, medical devices and equipment) [2]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBPA has been shown to leach from many of these products [3], leading to its release into the environment and subsequent human exposure.\u0026nbsp;BPA\u0026nbsp;has been detected in a variety of environmental samples, including water, dust, sewage leachates, and indoor and outdoor air\u0026nbsp;[3, 4]. BPA has also been detected in urine samples from the majority (\u0026gt;90%) of the general population in several large biomonitoring studies\u0026nbsp;[5-7]. BPA is ubiquitously detected in human biospecimens despite its short half-life and that it is not a persistent chemical. \u0026nbsp;This suggests frequent, widespread, and continuous exposure. There have been some regulatory efforts to prohibit or limit the use of BPA\u0026nbsp;[8, 9], and\u0026nbsp;some studies suggest that median urinary levels of BPA have decreased in the general population in the US, including California, following restrictions or prohibitions on its use\u0026nbsp;[5, 10-12]. However,\u0026nbsp;BPA is still in many consumer products\u0026nbsp;[13]\u0026nbsp;and\u0026nbsp;workers continue to be exposed\u0026nbsp;[14].\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe general population has been primarily exposed to BPA through ingestion from food and beverage containers coated internally with BPA-containing epoxy resins [3, 9], though this has declined in recent years given the move away from such resins [15].\u0026nbsp;However,\u0026nbsp;some BPA exposure of the general population continues through diet, as well as via dermal contact and inhalation. The CDC last analyzed urinary BPA in US adults recruited from the general population in the 2015-2016 NHANES cycle. The median unadjusted concentration of BPA in urine was 1.1 micrograms per liter urine (\u0026mu;g/L), and the median adjusted for creatinine (Cr) was 1.02 micrograms per gram Cr (\u0026mu;g/g)\u0026nbsp;[5]. In comparison, an occupational study of US adults reported a range of creatinine-adjusted total BPA urinary concentrations of 0.78\u0026ndash;18,900 \u0026mu;g/g (median 98.7 \u0026mu;g/g, over 80 times the median of 1.21 \u0026mu;g/g reported in US adults in NHANES during the overlapping 2013-2014 study period)\u0026nbsp;[5, 16]. Global reviews also report higher occupational BPA exposure (up to 685.9 \u0026mu;g/g Cr) than in the general population\u0026nbsp;[8, 14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBPA measurements reflect recent exposure and there is\u0026nbsp;considerable\u0026nbsp;temporal, intra-individual, and inter-individual variation [17-19]. BPA is rapidly absorbed and distributed throughout the body with some studies suggesting that adipose tissue may serve as a reservoir for BPA\u0026nbsp;[3, 20, 21]. It is then primarily metabolized via conjugation, leading to the formation of the predominant metabolites BPA-glucuronide (BPA-G) and BPA-sulfate (BPA-S). BPA and its metabolites are rapidly eliminated;\u0026nbsp;toxicokinetic studies demonstrate a half-life of less than\u0026nbsp;6 hours following ingestion\u0026nbsp;[22]\u0026nbsp;but there may be high inter-individual variability in enzymatic conjugation capacity by life stage, xenobiotic and drug exposure, genetic polymorphisms, or\u0026nbsp;disease status\u0026nbsp;[23-26].\u003c/p\u003e\n\u003cp\u003ePublic health concerns over BPA [27] are related to its documented properties as an endocrine disrupter [28] and observations that it exhibits several key characteristics of carcinogens [29].\u0026nbsp;The potential carcinogenicity of BPA has not been previously reviewed by any leading health agencies, including the International Agency for Research on Cancer (IARC), the US Environmental Protection Agency (US EPA), the National Institute for Occupational Safety and Health (NIOSH), the National Toxicology Program (NTP) Report on Carcinogens, or the US Food and Drug Administration (US FDA). IARC recommended that BPA be evaluated with \u0026ldquo;high\u0026rdquo; priority\u0026nbsp;[30, 31], but has not yet conducted their review as of early 2025. BPA was also placed in a \u0026ldquo;high\u0026rdquo; priority group by the Carcinogen Identification Committee (CIC), a group of scientists designated as the \u0026ldquo;State\u0026rsquo;s Qualified Experts\u0026rdquo; for California\u0026rsquo;s Proposition 65\u0026nbsp;[32].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOEHHA staff critically reviewed the carcinogenicity of BPA in a document [33] that was prepared for a public meeting of the CIC which convened in December 2022 [34]. \u0026nbsp; The CIC declined to add BPA to the Proposition 65 List of Carcinogens by 6 \u0026ldquo;no\u0026rdquo; votes and 5 \u0026ldquo;yes\u0026rdquo; votes [33, 34]. The CIC considered three streams of evidence (epidemiologic, animal carcinogenicity, and mechanistic studies) in their evaluation, and considered the epidemiologic evidence inadequate to evaluate the carcinogenicity of BPA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e1.b. Objectives\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a comprehensive and critical review of the published epidemiologic literature on the carcinogenicity of BPA, with an extensive summary of the characteristics of exposure assessment and study design needed to interpret the epidemiological studies. We focused the review on breast and prostate cancers, hormonally related cancers for which at least two cohort or case-control studies were available. All other cancer sites are described in an appendix. These data were publicly reviewed by the CIC in 2022 [33] and here are further extended to include papers published until February 2025.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis review is presented in a format that balances best practices and advantages of systematic and narrative reviews, with a focus on key issues [35-40]. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was followed as a guide for reporting this review [41, 42].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.a. Eligibility criteria\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCriteria for inclusion were all peer-reviewed, published analytical epidemiologic studies that estimated associations between exposure levels and cancer outcomes \u0026nbsp;[43]. Excluded records were conference abstracts, reviews without primary data, descriptive epidemiological studies and studies of uterine leiomyoma which generally does not progress to malignancy. Cross-sectional studies were reviewed for completeness even though we acknowledge that their design does not permit causal inference of BPA and cancer [44].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCross-sectional studies were briefly cited but excluded from further detailed review due to limitations for causal inference: a temporal association could not be established, reverse causation was possible, and disease prevalence was not a good proxy for incidence [45].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudies of BPA and precancerous lesions were not found. Studies of BPA and acute endpoints related to carcinogenesis were covered in the review of mechanistic evidence organized by key characteristics of carcinogens[29]. Studies on cancer survival and progression would not be informative for causal inference of BPA as a cause of cancer and therefore were \u003cem\u003ea priori\u003c/em\u003e excluded from this review.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe inclusion and exclusion of studies is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.b. Information sources and search strategy\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA professional librarian (NF) conducted comprehensive literature searches on the carcinogenicity of BPA in humans using a PECO strategy using a systematic approach similar to that used by the NTP Report on Carcinogens [37]. \u0026nbsp; Primary searches were conducted on December 14, 2021 in PubMed, Embase, Scopus, and SciFinder\u003csup\u003en\u003c/sup\u003e.\u0026nbsp; The literature searches were supplemented with a public data call-in period from January 28 to March 14, 2022 and searches in other data sources (e.g., reports by other health agencies, review articles). Additional focused searches in PubMed were conducted up to February 2025 (by GO and NG) and found 16 additional relevant publications using the following terms: (((\u0026quot;bisphenol A\u0026quot;) AND (cancer)) AND (epidemiology)) AND ((\u0026quot;2021\u0026quot;[Date - Publication]: \u0026quot;3000\u0026quot;[Date - Publication])). An overview of the systematic literature search strategy, the literature search terms in PECO format, and the dates the searches were executed is presented in Appendix Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.c. Selection process\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo scientists (NG, GO) independently completed the screening for each title and abstract, following the predefined inclusion and exclusion criteria. Sciome Workbench for Interactive Computer-Facilitated Text-mining Active Screener (SWIFT AS) [46] was used as a tool to facilitate the initial screening of references from the primary searches. After initial screening in SWIFT AS, HAWC (Health Assessment Workspace Collaborative, https://hawcproject.org) was used as a tool to further screen and tag the literature by keyword [47].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.d. Data items and data collection process\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo scientists (NG, GO) independently collected the following data from the included publications: study characteristics, study design, population selection, details on exposure and outcome assessment, exposure levels, statistical analysis methods, organ site and details including International Classification of Diseases (ICD) codes, units of effect measurement, measure of effect (e.g. relative risk, odds ratio, etc.), p-value for test for trend, exposure category or level, exposed cases or deaths, potential confounders and covariates, strengths, limitations, other noteworthy comments, and confidence in the evidence. These data were entered into Table Builder, a web-based application designed to capture systematically extracted data and to generate tables for reports [47]. Tables 1 and 2 present only select study design elements and highlight key information critical to the interpretation of the evidence for each study. For example, a latency period between BPA measurement and cancer diagnosis would be noted only if it were too short to detect the outcome.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.e. Study bias assessment\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo scientists (NG, GO) independently and systematically evaluated the quality of each included study for selection bias, information bias, and confounding through a domain-based approach according to guidance from the NTP Report on Carcinogens Handbook [36, 37] and the IARC Monographs preamble [35]. Study evaluations and judgement of potential biases were recorded into Table Builder [47]. Studies were not rated for risk of bias on various domains; rather each domain was evaluated and described thoroughly when notable [38, 40].\u003c/p\u003e\n\u003cp\u003eFor the bias assessment, the domain of information bias from exposure assessment was identified as a key consideration for assessing epidemiological studies of BPA and cancer. An exposure scientist (MEM) critically reviewed these data with consideration of:\u0026nbsp;the exposure assessment method (e.g., was a standard assay used?), the timing of the exposure assessment with respect to cancer diagnosis (e.g., prospective, retrospective, concurrent or cross-sectional), the quality assurance parameters used to validate a given method (e.g.,\u0026nbsp;the inter- and intra-assay coefficients of variation,\u0026nbsp;the correlation between repeated measurements of exposure (if any), the treatment of values below a limit of detection), the\u0026nbsp;BPA analyte or proxy, the biologic matrix sampled, and the potential for contamination in either sample handling or processing that could impact the analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePotential confounders were identified for the cancers of the breast and prostate (Appendix Table 2). First, risk factors for these cancer sites were identified from IARC [48], the American Cancer Society [49-53], and the World Cancer Research Fund [54-56]. Next, a literature search was performed to identify whether these risk factors were also associated with BPA exposure, to be considered potential confounders. Directed acyclic graphs were used to visualize the relationships between variables. In general, for the hormonally related cancers, there is evidence that BPA exposure/level is associated with age [57], race/ethnicity [57], obesity [58-63], diabetes [64-67], and tobacco smoke exposure (for breast cancer) [68].\u003c/p\u003e\n\u003cp\u003eWhen interpreting the evidence, we considered the direction of these biases on the observed associations [38, 40].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.f. Synthesis methods\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies included in the review were described in Tables 1, 2 and Appendix Table 3. Hill guidelines [69] for causal inference were taken into consideration for synthesizing the evidence qualitatively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA statistical approach to evidence synthesis (e.g., meta-analysis) was not undertaken in this manuscript. We considered combining risk estimates across studies of BPA to be inappropriate due the difficulty interpreting a risk estimate associated with BPA measurement at a single time point and the heterogeneity between studies in the methods of assessment and exposure metrics presented.\u003c/p\u003e"},{"header":"3.\tMain text","content":"\u003cp\u003eOur literature search identified 139 studies using the search terms for epidemiologic studies of cancer and BPA exposure (Appendix Table 1; Figure 1). Forty-three studies met the inclusion criteria and were reviewed in detail. Two meta-analyses\u0026nbsp;[70, 71]\u0026nbsp;were excluded due to the difficulty interpreting a combined risk estimate for BPA and cancer due to heterogeneity in methods for exposure assessment and reporting (see Section 2.f).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe review of the epidemiological evidence identified a need to review the exposure assessment methods in detail prior to interpreting the studies of BPA and cancer. There was substantial heterogeneity in study methods for assessing BPA exposure including the timing when BPA samples were taken, the biological matrix and the BPA analyte sampled, the potential for contamination and the quality assurance parameters for BPA detection. These factors are summarized in detail below and precede the review of the epidemiological studies, which is organized by cancer site to facilitate hazard identification.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.1 EXPOSURE MEASUREMENT ERROR IN EPIDEMIOLOGIC STUDIES OF BPA AND CANCER\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe greatest challenge to interpreting the reviewed human cancer studies was the reliable characterization of long-term BPA exposure. Exposure misclassification was a major concern; most studies assessed BPA exposure at a single time point using short-lived biomarkers. There were several additional methodological issues that could affect information bias, including measuring BPA in samples collected post-diagnosis. The direction and impact of the sources of bias are summarized below and\u0026nbsp;in greater detail in the hazard identification document [33].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.1 Single BPA measurement\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite large temporal variation in BPA levels, most studies measured BPA at a single time point using short-lived biomarkers that reflect current exposures [72-78]. Poor reproducibility of repeated urinary BPA measurements has been reported\u0026nbsp;[19, 76-85]: correlation coefficients ranged from 0.22 to 0.57\u0026nbsp;for serial urinary BPA measurements over 1 to 6 month periods\u0026nbsp;[61, 86].\u003c/p\u003e\n\u003cp\u003eTherefore, a single biological measurement or even multiple measurements in close proximity (e.g. hours, days) are unlikely to provide accurate estimates of long-term BPA exposure. Multiple longitudinal samples are required to improve confidence in BPA exposure classification [87]. Exposure status in individuals is expected to be misclassified irrespective of disease status (non-differential), which could bias risk estimates towards the null.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.2 Timing of BPA\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003cu\u003eexposure assessment\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBPA was measured primarily after outcome ascertainment in several case-control and cross-sectional studies, which presents several challenges:\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eReverse causation: Disease status may alter BPA levels, therefore post-diagnostic measurements may be misleading.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMissed critical windows: \u0026nbsp;Post-diagnostic samples fail to capture exposure during critical time windows of susceptibility, which\u0026nbsp;could precede cancer development by 10-20 years, and thereby\u0026nbsp;fail to detect true causal effects.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTemporal variations: Due to significant fluctuations in BPA levels over time, post-diagnostic samples may not\u0026nbsp;be predictive of BPA levels\u0026nbsp;prior to diagnosis.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eData on outcome and exposure (post-diagnostic BPA measurements) were collected simultaneously in studies of cross-sectional design. Therefore, by design these BPA studies cannot establish temporality, a key consideration for causal inference. This is an important consideration particularly for exposures with large temporal variation and also for cancer outcomes, given the long latency period for disease development following exposure. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.3 Methods for BPA\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003cu\u003eexposure assessment\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBPA was primarily measured in biological matrices (i.e., biomonitoring) and,\u0026nbsp;to a lesser extent, using questionnaires (one study) [88, 89] and\u0026nbsp;job exposure matrices (JEM) (four studies)\u0026nbsp;[88-93].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenerally, for questionnaires, non-differential exposure misclassification with bias towards the null is likely in cohort studies. There is no evidence to suggest that BPA exposure classification would differentially depend on whether a person developed cancer (in cohort studies). However, in case-control studies, differential over-recall of exposure in cases resulting in bias away from the null is possible given that the general public may have been aware of BPA use in the linings of cans and bottles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJEMs were used in population-based studies in which few participants had substantial occupational BPA exposure; therefore, such JEMs were underpowered to detect BPA exposure in the studies reviewed [94]. Furthermore, JEMs do not capture the primary source of BPA exposure of dietary exposure in the general population. Bias towards the null is likely.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the biomonitoring studies, analytical chemistry methods, such as mass spectrometry (MS)-based methods, are considered the most accurate and precise methods for measuring BPA [95].\u0026nbsp;The \u0026ldquo;gold standard\u0026rdquo; for measuring BPA in urine biomonitoring studies is solid-phase extraction coupled with isotope dilution\u0026ndash;HPLC (high-performance liquid chromatography)\u0026ndash;MS/MS because of its high level of accuracy, negligible interference, and ability to identify chemical structures\u0026nbsp;[27, 96]; although the major limitation is the high cost per sample\u0026nbsp;[27]. \u0026nbsp;Liquid chromatography (LC) with fluorescence detection (FD)-based methods can be less sensitive \u0026ndash; the limit of detection (LOD) is generally higher than for MS-based methods (see below)\u0026nbsp;[27]. ELISA (enzyme-linked immunosorbent assay) is cost-effective but is not the preferred method to detect BPA. ELISA can be less specific than analytical chemistry methods due to potential for cross-reactivity with other substances,\u0026nbsp;however if information about cross-reactivity and standard validations are included, these\u0026nbsp;data\u0026nbsp;should be considered valid\u0026nbsp;[27].\u0026nbsp; Bias towards the null is likely with less sensitive methods, while the direction cannot be predicted with less specific methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.4 Quality assurance parameters for BPA detection\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuality control (QC) for BPA detection in epidemiologic studies can be evaluated using several performance parameters, such as LOD, limit of quantification (LOQ), repeatability, recovery, linearity and range of calibration curve. For the LOD and LOQ, defined as the lowest concentration of the analyte that can be reliably detected or quantified, higher values indicate lower sensitivity to detect a BPA analyte [97]. Detection limits vary between assay methods, laboratories, and even within a laboratory over time [98].\u0026nbsp;This can result in a large percentage of imputed measurements, which are subject to exposure misclassification, likely non-differential, and bias risk estimates towards the null.\u003c/p\u003e\n\u003cp\u003eThe number of participants with BPA levels below the LOD can be substantial (up to 60-85%) in studies using less-sensitive methods or in populations with relatively\u0026nbsp;low\u0026nbsp;BPA exposure; for example, only 14.8% of samples in L\u0026oacute;pez-Carrillo et al. (2021) were above the study LOD, which was 2.78 ng/ml, the highest reported LOD in any epidemiologic study reviewed. To address this issue, studies either omit or impute values for samples below the LOD (e.g., assigning a value of zero, the LOD, or some function of the LOD). Both approaches introduce bias into the analysis to varying degrees, based on the sample size, proportion of observations below the LOD, and the imputation method used [98-104]. Studies with low detection rates are of concern due to the potential for measurement error introduced when imputing a large number of BPA levels for analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.5 Biological matrix\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUrine is considered the optimal biological matrix for measuring BPA [72, 105]. To enable comparisons between individuals, urinary concentrations of chemicals such as BPA are often adjusted, most commonly for creatinine [106]. Studies that report only unadjusted urinary levels may introduce bias, either towards or away from the null [107, 108].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe type of urine sample may also affect the sensitivity of the assay. Spot urine samples could poorly estimate chronic BPA exposure [78] because of its potentially large variation\u0026nbsp;over time\u0026nbsp;[109]. A first morning urine void or 12-hour overnight samples may be more concentrated than a simple spot sample and therefore have greater sensitivity to detect an effect\u0026nbsp;[110].\u0026nbsp;Measuring BPA in highly concentrated urine samples could result in greater potential for detection and hence attenuate the effect of potential exposure misclassification\u0026nbsp;[19]. The use of dilute samples may result in bias towards the null due to greater difficulty in detecting the BPA analyte.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSerum quantification of BPA is more challenging partly because levels are typically orders of magnitude lower than those in urine [105, 111-113] and are likely less reliable due to pharmacokinetics (rapid metabolism and excretion) and, without rigorous QC efforts, the potential for external contamination [72].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe higher BPA concentrations in urine compared to other tissues and fluids facilitates quantification. Lower blood concentrations of BPA biomarkers increase the likelihood that external contamination obscures true exposures [72]. While some studies suggest that adipose tissues may serve as a reservoir for BPA [21], additional data are needed to verify this and better characterize the intra-individual variability in BPA measurements in breast adipose tissue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.6 BPA Analyte\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBPA is rapidly metabolized and excreted as conjugated metabolites, mainly as a glucuronide (BPA-G) and to a lesser extent as a sulfate (BPA-S) [113]. The free (unconjugated) form of BPA (BPA-F) represents a small fraction of total BPA in the body and may reflect contamination of BPA-F leaching into a sample from external sources [113, 114]. Total BPA is comprised of BPA-F and at least one conjugated BPA metabolite; it is considered optimal for assessing exposure to BPA [115, 116]. Single analyte approaches (e.g., BPA-F, BPA-G, BPA-S) do not capture all forms of BPA and therefore underestimate exposure [24-26, 117] and likely\u0026nbsp;bias towards the null.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.1.7\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003eContamination\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBPA can be a component of collection materials or analytical equipment [27], which could contaminate samples in biomonitoring studies and inflate exposure levels in all study participants. Samples could also be contaminated by environmental sources of BPA, which would overestimate exposure\u0026nbsp;[105, 114, 118].\u0026nbsp;Because BPA is ubiquitous, the reference group may have some level of background BPA exposure; this would attenuate risk estimates towards the null. Measuring the conjugated form of BPA reflects BPA metabolism and therefore can limit the effect of potential BPA contamination during sampling or analysis.\u003c/p\u003e\n\u003cp\u003eThere are several QC measures to minimize BPA contamination (e.g., use of BPA-free materials, strict cleaning protocols for lab equipment and surfaces, engineering controls such as use of clean rooms) or estimate contamination levels (e.g., use of blank samples without BPA alongside actual samples, performing replicate tests on the same sample to identify variability caused by contamination, use of homogeneous matrix-based quality control materials within the expected concentration ranges of the study samples as well as spiking samples with known quantities of BPA to assess recovery rates and identify potential contamination or loss during analytical procedures, and calibrating and maintaining equipment) [118, 119]. Such QC measures were carefully assessed for each publication reviewed. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCRITICAL REVIEW OF EPIDEMOLOGIC STUDIES OF BPA AND CANCER\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.2 Breast Cancer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBreast cancer was the most studied outcome of the epidemiologic studies identified (16 studies). All but three of these studies adjusted for obesity/body mass index (BMI), an important potential confounder [91, 120, 121]; only two studies stratified the analyses by hormone receptor subtype (estrogen or progesterone receptors) [122, 123]. Table 1 presents details of the exposure characteristics of these studies and their results, including the major strengths and limitations identified using the domain-based approach to study assessment.\u003c/p\u003e\n\u003cp\u003eBiomonitoring was used to estimate BPA exposure in all but one study [91], which used a JEM in an exploratory case-control study conducted in a general population sample in Massachusetts, USA. The prevalence of occupational BPA exposure was low (\u0026lt;1% only BPA, 12% any BPA); therefore, there was inadequate statistical power to detect an association. An OR of 0.8 (95% confidence interval (CI): 0.5\u0026ndash;1.4) was reported for both the categories of \u0026lsquo;only BPA exposure\u0026rsquo; (two exposed cases) and \u0026lsquo;BPA plus other xenoestrogens\u0026rsquo; (23 exposed cases). The analyses could not disentangle the effect of BPA from other co-exposures and the models were not adjusted for BMI. Other limitations were the lack of information on intensity and level of exposure and the crude categorization of \u0026ldquo;any\u0026rdquo; vs \u0026ldquo;no\u0026rdquo; exposure and combining groups of women in the low and high intensity exposure subgroups. Grouping the few women with high intensity with those of low intensity of exposure (expected to be the majority of women) would attenuate risk estimates towards the null.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the review of the breast cancer evidence, the biomonitoring studies are presented first by biological matrix, and then by the timing of collection for urine sampling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.2.a Urinary BPA measurements\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBPA was measured in urine in 11 reports of breast cancer: one nested case-control study [123], seven case-control studies [117, 120-122, 124-126], and three cross-sectional analyses from the NHANES [127-129]. Samples were adjusted for creatinine in all but one study [117]. Timing of urine sample collection was also considered, since a first morning urine void may be more concentrated than a simple spot sample and therefore have greater sensitivity to detect effects [110]. Results and characteristics were mixed among the three breast cancer studies that measured BPA in first morning void or overnight urine [117, 121, 123] and also among the six studies that either collected spot urine samples [120, 125, 128] or did not specify the sample type [122, 124, 126] (e.g., first morning void, overnight samples, etc.). The latter studies that did not specify sample type also lacked reporting on other important study details (e.g., BPA analyte, QC measures, risk estimates). All but one study [123] had the potential for reverse causation because samples were collected after diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe majority of studies used LC with MS for detection and collected a single urine sample for each participant, which was post-diagnosis in the cross-sectional and case-control studies. Limitations were the inability to characterize long-term BPA exposure in all studies due to the single sample, failure to establish a temporal association, and the potential for reverse causation from biomarker measurements in post-diagnostic samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Multiethnic Cohort [123] was the only study to measure total BPA prospectively before diagnosis. There was no association with postmenopausal breast cancer for the highest tertile of BPA level (\u0026gt;1.76 ng/mg). The OR was 0.84 (95% CI: 0.67\u0026ndash;1.06) for the 2nd tertile (\u0026gt;0.84 to \u0026le;1.76 ng/mg BPA) when compared to the lowest tertile (\u0026le;0.84 ng/mg BPA). This general pattern of association did not change in several sensitivity analyses stratified by hormone receptor positivity, BMI, years of follow-up, stage at diagnosis (\u003cem\u003ein situ\u003c/em\u003e vs invasive cancer), or by use of hormone replacement therapy (HRT) at urine collection. Reverse causation was not a concern, but collection of a single urine sample was a limitation. Although at least one validation measure was presented, within-batch variability was high (21.9%). BPA was correlated with several other chemicals, which were not adjusted for in the analyses. The time window of susceptibility to breast cancer may have been missed, as only women in their 60s were sampled.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn a case-control study from Mexico, Lopez-Carrillo et al. [121] found positive associations with urinary free BPA detected at levels 7\u0026ndash;10 times greater than the other studies that measured total BPA in urine [117, 120]. The OR for the highest exposure category (\u0026gt;12.05 \u0026mu;g/l BPA-F) was 2.31 (95% CI: 1.43\u0026ndash;3.74) and the increase remained in sensitivity analyses among women whose urinary BPA had a recovery \u0026ge; 80% (odds ratio (OR): 1.66; 95% CI: 1.28\u0026ndash;2.14) and after excluding women with undetectable BPA (OR: 4.43; 95% CI: 1.89\u0026ndash;10.42). Limitations were the use of FD, a high LOD and subsequently a large percentage of samples (85.2%) below the LOD, for which exposure levels were imputed. Therefore, it is unclear if the contrast between this and other studies is due to actual differences between exposures or measurement error. The analyses were adjusted for creatinine levels and age, but not obesity or other potential confounders.\u003c/p\u003e\n\u003cp\u003eIn a case-control study from Tehran, Iran [117] of 41 breast cancer mastectomy patients and 11 reduction mammoplasty patients, all lifetime non-smokers, the OR was 10.59 (95% CI: 1.62\u0026ndash;65.7) for BPA measured in first morning spot urine samples without adjustment for creatinine. ELISA was used, but the potential to cross-react with other substances could explain the high detection of BPA in both cases (93%) and controls (82%). Breast adipose tissue samples were also collected; BPA concentrations in urine and tissue were correlated in cases (r = 0.896, p-value \u0026lt; 0.001), but not in controls (p-value \u0026gt; 0.05). Study participants were not matched on potential confounders; the lack of matching in the design does not ensure comparability between the case and control groups. It was not reported how samples below LOD were treated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf the five reports that collected spot urine [120, 125, 127, 128], only one reported a positive association. A case-control study from Wuhan, China reported an OR of 1.54 (95% CI: 1.34\u0026ndash;1.77) per \u0026mu;g/g unit increase in total BPA [120]. ORs above 1.0 were also reported in analyses of the interaction of high and low BPA levels with several SNPs in the cytochrome P450 genes (CYP19A1, CYP1A1, CYP17A1, CYP2E1, CYP24A1), but severe limitations in reporting study details and analyses warrant cautious interpretation of these findings. There was no correction for multiple comparisons; observed associations could reflect false positive results. Selection bias was difficult to assess due to lack of detailed description of the differences between people included in the study versus those who were eligible, limited detail on sociodemographic characteristics, and no information on response rates. This study matched controls to cases by abortion status (not further defined) even though it is not a risk factor for breast cancer nor a confounder in its association with BPA. Analyses were not adjusted for BMI. There was potential for bias towards the null because the 1st and 2nd tertiles of BPA exposure were combined and compared to the last tertile.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNull or inverse associations with log-transformed BPA levels (analyte unspecified) were reported in a case-control study from Long Island, USA [125]. The ORs for breast cancer incidence were 0.91 (95% CI: 0.8\u0026ndash;1.02) overall, 0.78 (95% CI: 0.66\u0026ndash;0.93) in women with a BMI \u0026lt;25 kg/m\u0026sup2;, and 1.04 (95% CI: 0.87-1.24) in women with a BMI \u0026gt; 25 kg/m\u0026sup2;. Results were similar when restricted to breast cancer-specific mortality. There was no internal consistency in the analyses reported by quintile of BPA exposure, and there did not appear to be an exposure-response relationship (p-value for test for trend was not reported). The BPA analyte was not specified, there was a lack of reporting on QC measures, a relatively high LOD, and imputation of exposure levels for nearly a fifth (18.3%) of the samples below LOD.\u003c/p\u003e\n\u003cp\u003eThe three studies that did not specify the type of urine sample (all case-control design) were also limited by lack of reporting study details.\u0026nbsp;Two studies, from India and Taiwan, did not report a risk estimate but found higher concentrations of BPA analytes in the urine of cases than in controls [124, 126].\u0026nbsp;Inconsistent results were observed within a population-based case-control study of postmenopausal breast cancer conducted in two centers in Poland\u0026nbsp;[122]. Although BPA-G levels were higher in Warsaw than in Lodz, a positive association was observed with BPA-G analyzed as a continuous variable in Lodz only (OR, 1.32; 95% CI: 1.00\u0026ndash;1.73) but not in Warsaw (OR: 0.94; 95% CI: 0.81\u0026ndash;1.11). For categorical analyses, the OR was increased (OR: 1.7; 95% CI: 1.15\u0026ndash;2.52) in only the 2nd quartile (2.06\u0026ndash;4.16 BPA-G ng/mg) of the overall analyses and also in analyses restricted to ER-negative breast cancer. The lack of reporting of the LOD or QC measures are further limitations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.2.b Breast adipose tissue BPA measurements\u0026nbsp;\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo small hospital-based case-control studies measured BPA in tissue [117, 130] from breast cancer mastectomy cases and breast reduction mammoplasty controls. Both studies took measures to limit contamination (including use of BPA-free sampling materials). The presence of selection bias was difficult to assess due to the presentation of few sociodemographic variables. Selection bias was a concern in both studies as all participants were selected from a single referral center (which may not reflect the underlying study population), controls were younger than cases, and neither study matched cases and controls on potential confounders. One study reported difficulty in enrolling healthy controls from the same referral center [117].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Massachusetts, Reeves et al. [130] conducted one of the few studies to have collected more than one biological sample per person. Cases were women undergoing unilateral or bilateral mastectomy for breast cancer treatment and controls were undergoing elective reduction mammoplasty. In cases, a normal tissue sample away from the tumor was collected; a subset also provided a tissue sample from the unaffected breast to simulate tissue samples from controls. Another subset of cases and controls had two samples collected from the same breast. BPA levels were highly variable both within-breast and between breasts, with coefficients of variation ranging from 8.9% to 141.4% in replicate samples with BPA \u0026gt;LOQ. An OR of 0.9 (95% CI: 0.4\u0026ndash;2.0) was reported for cases with detectable BPA-F (\u0026gt;LOQ of 0.38 ng/g) in breast adipose tissue, using a group of \u0026lsquo;reduction mammoplasty controls\u0026rsquo; (instead of an unexposed/low exposed) as the reference category. The analyses were difficult to interpret as the ratio of the odds of exposure in case vs. control\u0026nbsp;groups was not calculated. Limitations of this study were that the LOQ was relatively high, and exposure levels were imputed for a large percentage (69.4%) of samples below the LOQ.\u003c/p\u003e\n\u003cp\u003eKesharvarz-Maleki et al. [117] measured BPA in urine as well as in breast adipose tissue using ELISA (see Section 3.2.a). Cross-reactivity with other substances could explain the very high OR for BPA in breast adipose tissue (OR: 54.96; 95% CI: 2.08\u0026ndash;1372.55). A strength of this study was that BPA was measured in most participants in two biological matrices, which was correlated in cases (P \u0026lt; 0.001, R = 0.896), but not in controls (P \u0026gt; 0.05). The breast adipose tissue sample was collected in proximity to the tumor in cases and therefore may not approximate the normal tissue physiology for comparison to the controls. Other limitations were collection of a single sample per matrix, nearly half (45%) of the control tissue samples were below the LOD, not reporting how samples below the LOD were treated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003e3.2.c Serum BPA measurements\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree breast cancer studies measured BPA in serum [131-133]; all were limited by use of a single sample. In a case-cohort analysis of the Spanish arm of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort [132], there was a 4.7% increase in the risk of breast cancer (hazard ratio (HR): 1.047; 95% CI: 0.98\u0026ndash;1.12) for every 5 ng/ml increase in total BPA level, measured in samples collected at enrollment, prospectively before diagnosis. The median follow-up was 17 years. This study was limited by the relatively high LOD and the imputation of exposure levels for nearly a third of participants below the LOD (30.6%). Case-control studies from Korea [133] and Nigeria [131] reported higher serum BPA levels in cases than in controls, but no risk estimates were reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Prostate cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSix studies of prostate cancer (seven reports) estimated exposure to BPA using different methods; four were cross-sectional and are not described further [127, 134-136]. Both a case-control study and case-cohort analysis found an association [88, 89, 132]\u0026nbsp;(Table 3).\u0026nbsp;A hospital-based case-control study in Hong Kong assessed cumulative BPA exposure through ingestion using a tool reconstructed through questionnaire data and a literature review of BPA levels, similar to construction of a JEM\u0026nbsp;[88, 89]. Increasing cumulative BPA exposure was associated with prostate cancer, with a significant exposure-response (OR high exposure: 1.88; 95% CI: 1.24\u0026ndash;2.86; \u003cem\u003ep\u003c/em\u003e-value for trend = 0.014). Misclassification of BPA exposure was possible as there were no considerations of exposure variations over time. In a case-cohort analysis within the Spanish EPIC cohort\u0026nbsp;[132], prospectively measured serum BPA was not associated with prostate cancer in linear models but there was an increased risk of prostate cancer with every ng/ml increase in total BPA level (HR: 1.04; 95% CI: 0.99\u0026ndash;1.08) and in tertiles compared to those below the LOD. This study was limited in its exposure assessment by a single sample, the use of serum as a biological matrix, and a relatively high LOD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Other cancers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe appendix presents the results of the epidemiologic studies of BPA and other cancer sites: colorectum, gallbladder, lung, bone, skin, cervix, endometrium/uterus, ovary, bladder, eye, brain, thyroid, lymphohematopoietic system, all cancers combined. The results were inconsistent and there were limitations in the design and reporting for many of these studies (Please see Appendix and Appendix Table 3).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis is the first critical review on the carcinogenicity of BPA to focus on the challenges with exposure characterization of BPA in cancer epidemiologic studies and the direction of potential sources of bias in each study. These data were first presented in December 2022 at a public meeting of California\u0026rsquo;s Proposition 65 CIC [33, 34] and have since been summarized in subsequent review publications [137, 138].\u0026nbsp;Although at least one recent review of the human evidence related to carcinogenicity of BPA\u0026nbsp;[137]\u0026nbsp;and two meta-analyses of breast cancer have been published\u0026nbsp;[70, 71],\u0026nbsp;OEHHA [33] was the first such review to comprehensively summarize the characteristics of exposure assessment and study design needed to interpret the epidemiological studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter careful consideration and thoughtful deliberation by the CIC of all lines of evidence (epidemiology, animal bioassays, mechanistic evidence), BPA was not placed on the Proposition 65 list of carcinogens, with a vote of five in favor and six against. The CIC deemed the available epidemiologic evidence inadequate. There were few epidemiologic studies on BPA and cancer. For many cancers, a single study was available; there was inadequate evidence to make a conclusion on these sites. The majority of the studies focused on breast cancer (n=16), where the evidence was inconsistent. For the other cancer sites with more than one study (prostate, thyroid, endometrium, colorectum, lung), some positive associations were observed; however, limitations in methodology for all studies warrant cautious interpretation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor assessing study quality, special attention was given to the assessment of biases, which in observational studies are usually grouped into selection bias, information bias and confounding [37, 139]. Confounding is an important consideration for causal inference in observational studies, and few of these studies adequately adjusted for important confounders. However, information bias from exposure assessment was found to be the key consideration for evaluating this body of evidence. Our review summarized information on\u0026nbsp;the methods of assessing exposure to BPA from previous reviews\u0026nbsp;[27, 95]\u0026nbsp;to interpret the impact of potential biases in interpreting\u0026nbsp;the epidemiologic studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe major limitation of all studies was the inability to reliably capture long-term BPA exposure due to the potential for considerable measurement error.\u0026nbsp;Sources for this error stemmed from how the methods (i.e.\u0026nbsp;biomonitoring, questionnaires, JEMs)\u0026nbsp;were applied. For biomonitoring studies, sources of measurement error were\u0026nbsp;BPA\u0026rsquo;s short half-life, collection of a single BPA measurement,\u0026nbsp;and timing of BPA assessment. None of the studies successfully evaluated, or accounted for, temporal variation in BPA exposure within and across individuals. Thereby, it was difficult to correctly assign individuals in these studies to categories or levels of BPA exposure and to detect associations with chronic disease outcomes, such as cancer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQuestionnaires and JEMs have the ability to evaluate past exposure to BPA, which is more relevant to studying cancer outcomes due to the long latency period between onset of exposure and disease diagnosis [140]. However, questionnaires and JEMs query suspected exposures from specific sources and therefore\u0026nbsp;may not capture the widespread exposures to BPA from multiple sources\u0026nbsp;[87, 141]. JEMs were primarily used in general population studies where occupational exposures were low\u0026nbsp;[90-93]\u0026nbsp;and the primary exposure route is ingestion. Therefore this method may lack the sensitivity to detect an association with BPA\u0026nbsp;[94], if one exists.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne study from Hong Kong attempted to characterize cumulative BPA exposure via ingestion using a tool reconstructed through questionnaire data and a literature review of BPA levels, similar to construction of a JEM [88, 89].\u0026nbsp;Given that biomarkers of BPA exposure are short lived, the approach of Tse et al. could be a more cost-effective method for estimating long-term BPA exposure in future studies\u0026nbsp;but requires validation. However, questionnaire approaches to assess BPA exposure\u0026nbsp;[88, 89]\u0026nbsp;are inherently limited in the general population, given many varied sources of exposure that are not typically sufficiently incorporated into questionnaires and, in many cases, are unknown to the participant\u0026nbsp;[13, 87, 141]. For example, one attempt to validate a dietary exposure assessment questionnaire tool found that known dietary sources of BPA exposure explained less than half the variability in urinary BPA levels, regardless of diet assessment method. This study used a food frequency questionnaire with 24-hour recalls over multiple days with daily biomonitoring measures in healthy adults\u0026nbsp;[87].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBiomonitoring was used in the majority of studies, in which BPA was measured in samples generally collected at a single point in time. While biomonitoring has the advantage to\u0026nbsp;account for exposures from all possible sources and better reflect internal circulating BPA levels [27], BPA biomarkers are short-lived and only capture recent exposure. Therefore, a single biomarker measurement does not account for the potentially large temporal variations in BPA exposure that may occur across hours, days, weeks, and years [17-19].\u0026nbsp;None of the biomonitoring studies reviewed collected samples longitudinally at multiple time points.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTiming of exposure assessment was also a concern in the biomonitoring studies, for which the majority measured BPA in biological samples after cancer diagnosis using a cross-sectional design.\u0026nbsp;Only a few collected biological samples prospectively [123, 132, 142, 143]. Studies of cross-sectional design could not establish a temporal association because exposure and outcome data are collected concurrently and there were no data from other evidence streams to inform on temporality. Reverse causation is possible since BPA levels may be altered by physiological or behavioral changes associated with the onset of disease and treatment [144, 145].\u0026nbsp;Failure to detect true causal effects is also a concern since exposure was assessed long after the expected time window for cancer causation, which is generally considered to occur many years prior to a cancer diagnosis. Moreover, the prenatal and neonatal periods could represent the most vulnerable windows of exposure to BPA\u0026nbsp;[146], as evidenced by rodent studies of low-dose BPA prenatal and neonatal exposure that demonstrate subsequent alterations in estrous cycles and in the prostate and mammary gland tissues of those animals later in life\u0026nbsp;[27]. None of the cancer studies reviewed estimated BPA exposure during these time periods.\u003c/p\u003e\n\u003cp\u003eCross-sectional studies were reviewed for completeness with the acknowledgement that their design did not permit causal inference of the association between BPA and cancer. Furthermore, many of these studies lacked key details in data reporting. Cross-sectional designs were also limited by the use of prevalent cases and thus there is concern of length-biased sampling, in which individuals with the longest lasting disease are more likely to be selected into the study [45]. This can be an important consideration for cancers with higher rates of survival, such as breast, prostate, and thyroid cancers. Prevalent cases could differ in characteristics related to BPA levels (such as exposure patterns or metabolism) that could affect their survival compared to the incident cases captured in case-control or cohort designs.\u003c/p\u003e\n\u003cp\u003eIt is worth noting that case-control studies that measured BPA in biological samples post-diagnosis were similarly uninformative. However, the case-control studies enrolled incident cases whereas cross-sectional studies enrolled prevalent cases; a crucial distinction for causal inference which was the objective of the hazard identification exercise.\u003c/p\u003e\n\u003cp\u003eIn addition, there was large variation in BPA measurement assay quality between studies, as denoted by the LOD or LOQs. The LOD and LOQ for total BPA in any matrix (urine, serum, or breast adipose tissue) in the studies that used MS-based methods were all below 0.5 nanograms per milliliter (ng/ml) or gram (ng/g), with many studies reporting LODs in urine below 0.05 ng/ml. However, some studies using non-MS-based methods reported higher LODs or LOQs, resulting in BPA being detected in fewer subjects. The approaches taken in handling data where BPA was not detected, such as imputing BPA levels or omitting individuals with non-detectable levels, can introduce bias in exposure characterization [98-104]. For example, Lopez-Carrillo et al. [121] reported an LOD of 2.78 ng/ml, the highest reported LOD in any epidemiologic study reviewed, and only 14.8% of samples tested in this study were above this LOD. As a result, most samples included in the analyses were imputed, which could result in exposure measurement error. Therefore, it is difficult for the reviewed epidemiologic studies to correctly assign individuals to categories or levels of BPA exposure.\u0026nbsp;If the sources of measurement error result in non-differential exposure misclassification, risk estimates would likely be biased towards the null. Imputing exposures could result in bias either away from or towards the null. Furthermore, since exposure to BPA is widespread in the population, exposure contrasts may be low, which also reduces the sensitivity of these studies to detect an effect. None of the epidemiologic studies of cancer outcomes were conducted in highly exposed workers, a population that could allow assessment of high exposures with large exposure contrasts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture efforts to assess the carcinogenicity of BPA in epidemiologic studies could harness existing biomonitoring efforts in workers highly exposed to BPA, with prospective, longitudinal collection of quantitative exposure measures [147]. For example, NIOSH established a cohort in 2013\u0026ndash;2014 to measure BPA exposure in 77 US manufacturing workers from six companies that either made or used BPA, BPA-based resins, or BPA-filled waxes [16]. These workers handled BPA, often in large quantities, and were exposed to BPA mainly by inhalation and dermal absorption. Each participant provided seven urine samples over two consecutive workdays. On average, workers in the NIOSH study had urinary BPA levels approximately 70 times higher than adults in the US general population. There may be insufficient follow-up time currently to detect cancer outcomes as well as limited statistical power to detect associations for any particular cancer site. Informative future epidemiologic studies in highly exposed workers could assess acute endpoints involved in the established mechanisms of carcinogenesis [29, 148] coupled with high quality exposure data, as a more cost- and time-effective approach to evaluating the carcinogenicity of BPA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, there are inadequate epidemiologic data on BPA, although this does not rule out its potential for carcinogenicity. There is a wealth of data on BPA\u0026rsquo;s potential carcinogenicity from animal bioassays and mechanistic studies [29]. Notably, BPA will also be reviewed by IARC, as it has been assigned a high priority based on relevant published mechanistic and animal bioassay evidence [30].\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe epidemiologic evidence was inadequate to determine the carcinogenicity of BPA due to limitations in reliably characterizing long-term BPA exposure in study participants, few studies by cancer site and heterogeneity among those studies. However, there is a large evidence base indicating potential mechanisms of carcinogenesis. Future studies that are likely to be informative on the carcinogenic potential of BPA could be conducted within worker populations who are still highly exposed to BPA. This could involve prospective and longitudinal collection of exposure data (e.g., quantitative measurements, biomonitoring) with follow-up for outcomes such as cancer morbidity or acute effects involving established mechanisms of carcinogenesis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u0026mu;g, microgram\u003c/p\u003e\n\u003cp\u003eBMI, body mass index\u003c/p\u003e\n\u003cp\u003eBPA, bisphenol A\u003c/p\u003e\n\u003cp\u003eBPA-F, free bisphenol A\u003c/p\u003e\n\u003cp\u003eBPA-G, BPA-glucuronide\u003c/p\u003e\n\u003cp\u003eBPA-S, BPA-sulfate\u003c/p\u003e\n\u003cp\u003eCI, confidence interval\u003c/p\u003e\n\u003cp\u003eCIC, Carcinogen Identification Committee\u003c/p\u003e\n\u003cp\u003eCYP450, cytochrome P450\u003c/p\u003e\n\u003cp\u003eELISA, enzyme-linked immunosorbent assay\u003c/p\u003e\n\u003cp\u003eEPIC, European Prospective Investigation into Cancer and Nutrition\u003c/p\u003e\n\u003cp\u003eFD, fluorescence detection\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eg, gram\u003c/p\u003e\n\u003cp\u003eHAWC, Health Assessment Workspace Collaborative\u003c/p\u003e\n\u003cp\u003eJEM, job exposure matrix\u003c/p\u003e\n\u003cp\u003eHPLC, high-performance liquid chromatography\u003c/p\u003e\n\u003cp\u003eHR, hazard ratio\u003c/p\u003e\n\u003cp\u003eHRT, hormone replacement therapy\u003c/p\u003e\n\u003cp\u003eIARC, International Agency for Research on Cancer\u003c/p\u003e\n\u003cp\u003eLC, liquid chromatography\u003c/p\u003e\n\u003cp\u003eLOD, limit of detection\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLOQ, limit of quantification\u003c/p\u003e\n\u003cp\u003eml, milliliter\u003c/p\u003e\n\u003cp\u003eMS, mass spectrometry\u003c/p\u003e\n\u003cp\u003eNTP, National Toxicology Program\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eng, nanogram\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOR, odds ratio\u003c/p\u003e\n\u003cp\u003ePRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQC, quality control\u003c/p\u003e\n\u003cp\u003eRR, relative risk\u003c/p\u003e\n\u003cp\u003eSWIFT AS, Sciome Workbench for Interactive Computer-Facilitated Text-mining Active Screener\u003c/p\u003e\n\u003cp\u003eUS EPA, United States Environmental Protection Agency\u003c/p\u003e\n\u003cp\u003eUS FDA, United States Food and Drug Administration\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: N/A\u003c/p\u003e\n\u003cp\u003eConsent for publication: All authors consent to publication.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: All authors consent. This review and its protocol were not registered.\u003c/p\u003e\n\u003cp\u003eCompeting interests: None\u003c/p\u003e\n\u003cp\u003eFunding: None\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions: NG and GO made equal contributions to preparing this manuscript for publication. NG drafted this manuscript and all co-authors contributed to the final text. NG, GO, MEM conceptualized the work and drafted the hazard identification document, which was the basis for this manuscript. The initial summarization, tabulation, and interpretation of the data were done by MEM for exposure characteristics and methods and NG, GO for the epidemiological studies. NF conducted the initial literature search. All other authors contributed to the execution and review of the final draft.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: We thank Ms. Lina Kamil for her assistance with earlier aspects of the\u0026nbsp;literature review and the internal OEHHA reviewers for their careful review of the manuscript.\u003c/p\u003e\n\u003cp\u003eNote\u003c/p\u003e\n\u003cp\u003eThe views expressed are those of the authors and do not necessarily represent those of the Office of Environmental Health Hazard Assessment (OEHHA), the California Environmental Protection Agency, or the State of California.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eResearch and Markets: \u003cstrong\u003eBisphenol-A (BPA) Market\u0026mdash;Growth, Trends, COVID-19 Impact, and Forecast (2022\u0026ndash;2027)\u003c/strong\u003e. 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In\u003cem\u003e.\u003c/em\u003e Atlanta, GA: Centers for Disease Control and Prevention: WTC Health Program; 2014: 1\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eGerona RR, Pan J, Zota AR, Schwartz JM, Friesen M, Taylor JA, Hunt PA, Woodruff TJ: \u003cstrong\u003eDirect measurement of Bisphenol A (BPA), BPA glucuronide and BPA sulfate in a diverse and low-income population of pregnant women reveals high exposure, with potential implications for previous exposure estimates: a cross-sectional study\u003c/strong\u003e. \u003cem\u003eEnviron Health\u0026nbsp;\u003c/em\u003e2016, \u003cstrong\u003e15\u003c/strong\u003e:50.\u003c/li\u003e\n \u003cli\u003eBao W, Liu B, Rong S, Dai SY, Trasande L, Lehmler HJ: \u003cstrong\u003eAssociation Between Bisphenol A Exposure and Risk of All-Cause and Cause-Specific Mortality in US Adults\u003c/strong\u003e. \u003cem\u003eJAMA Netw Open\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e3\u003c/strong\u003e(8):e2011620.\u003c/li\u003e\n \u003cli\u003eSarink D, Franke AA, White KK, Wu AH, Cheng I, Quon B, Le Marchand L, Wilkens LR, Yu H, Merritt MA: \u003cstrong\u003eBPA, Parabens, and Phthalates in Relation to Endometrial Cancer Risk: A Case-Control Study Nested in the Multiethnic Cohort\u003c/strong\u003e. \u003cem\u003eEnviron Health Perspect\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e129\u003c/strong\u003e(5):57702.\u003c/li\u003e\n \u003cli\u003eGenco M, Anderson-Shaw L, Sargis RM: \u003cstrong\u003eUnwitting Accomplices: Endocrine Disruptors Confounding Clinical Care\u003c/strong\u003e. \u003cem\u003eJ Clin Endocrinol Metab\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e105\u003c/strong\u003e(10):e3822\u0026ndash;3827.\u003c/li\u003e\n \u003cli\u003ePedersini R, di Mauro P, Bosio S, Zanini B, Zanini A, Amoroso V, Turla A, Vassalli L, Ardine M, Monteverdi S\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eChanges in eating habits and food preferences in breast cancer patients undergoing adjuvant chemotherapy\u003c/strong\u003e. \u003cem\u003eSci Rep\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e11\u003c/strong\u003e(1):12975.\u003c/li\u003e\n \u003cli\u003eDelb\u0026egrave;s G, Levacher C, Habert R: \u003cstrong\u003eEstrogen effects on fetal and neonatal testicular development\u003c/strong\u003e. \u003cem\u003eReproduction\u0026nbsp;\u003c/em\u003e2006, \u003cstrong\u003e132\u003c/strong\u003e(4):527\u0026ndash;538.\u003c/li\u003e\n \u003cli\u003eLoomis D, Guha N, Hall AL, Straif K: \u003cstrong\u003eIdentifying occupational carcinogens: an update from the IARC Monographs\u003c/strong\u003e. \u003cem\u003eOccup Environ Med\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e75\u003c/strong\u003e(8):593\u0026ndash;603.\u003c/li\u003e\n \u003cli\u003eGuyton KZ, Rieswijk L, Wang A, Chiu WA, Smith MT: \u003cstrong\u003eKey Characteristics Approach to Carcinogenic Hazard Identification\u003c/strong\u003e. \u003cem\u003eChem Res Toxicol\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e31\u003c/strong\u003e(12):1290\u0026ndash;1292.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Epidemiologic studies of BPA and breast cancer: exposure characterization and results by exposure matrix and year of publication\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"960\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference; Location;\u0026nbsp;\u003cbr\u003e\u0026nbsp;Years of BPA measurement; Study design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure assessment details\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalytical method and analyte\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPA levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOD or LOQ (% below LOD) and methods for samples below LOD/LOQ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethods to limit contamination?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eQC measures?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure category or level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk estimate\u003cbr\u003e\u0026nbsp;(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposed cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" valign=\"top\" style=\"width: 960px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob exposure matrix\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAschengrau et al. (1998)\u003c/p\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003cp\u003e1983-1986\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"5\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eJEM based on NIOSH/NOES database, chemical production and usage information, and expert judgment of certified industrial hygienist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eEver/never exposure (9.6% exposed to BPA; 0.8% exposed to BPA only)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Possible. Next-of-kin interview; crude assignments (any vs no exposure); JEM used in general population with low occupational exposure prevalence to any or only BPA\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eConfounding:\u003c/strong\u003e No adjustment for BMI or job co-exposures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eUnexposed to xenoestrogens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAny BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.8 (0.5\u0026ndash;1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eBPA + other xenoestrogens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.8 (0.5\u0026ndash;1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eOnly BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" valign=\"top\" style=\"width: 960px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomonitoring: Urine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTrabert et al. (2014)\u003c/p\u003e\n \u003cp\u003ePoland\u003c/p\u003e\n \u003cp\u003e2000\u0026ndash;2003\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: single 12-hour overnight sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eBPA-G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mg): 4.11 (cases), 3.92 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD: NR [cited method reports LOD of 0.005 ng/ml] (2.80%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as 0.1 g/mg Cr or included in first quartile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003ePost-menopausal: OR, BPA-G (ng/mg Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Measurement of urinary BPA-G may not adequately reflect exposure to BPA, due to the inter-individual variability in BPA glucuronidation.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eConfounding\u003c/strong\u003e: Models may have over-adjusted for covariates.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLog-transformed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.04 (0.91\u0026ndash;1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt; 2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.06\u0026ndash;4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.7 (1.15\u0026ndash;2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4.17\u0026ndash;7.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.02 (0.67\u0026ndash;1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026gt; 7.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.09 (0.73\u0026ndash;1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eTrend-test \u003cem\u003ep\u003c/em\u003e-value: 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eMorgan et al. (2017)\u003c/p\u003e\n \u003cp\u003eUS (NHANES)\u003c/p\u003e\n \u003cp\u003e2005\u0026ndash;2010\u003c/p\u003e\n \u003cp\u003eCross-sectional\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/g): 1.06 (cases), 1.16 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD/LOQ: NR\u003c/p\u003e\n \u003cp\u003eMethods: Included in reference group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eReported in NHANES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Self-reported cancers susceptible to outcome misclassification.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt; LOD to 50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026ge; 50% (0.42\u0026ndash;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.76 (0.45\u0026ndash;1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt; LOD to 50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026ge; 50% (0.42\u0026ndash;1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.73 (NR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYang et al. (2018)\u003c/p\u003e\n \u003cp\u003eTaiwan\u003c/p\u003e\n \u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: first morning void sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC\u003c/p\u003e\n \u003cp\u003eAnalyte: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean (ng/mg): 14.17 (cases), 5.95 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD/LOQ: NR\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eNo risk estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eNotes: lack of details in reporting.\u003c/p\u003e\n \u003cp\u003eThe purpose of this study was to test whether exposure to BPA and phthalate metabolites, estimated from urinary concentrations, would be associated with ADAM33 expression and methylation profile between breast cancer patients and healthy controls.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eParada et al. (2019)\u003c/p\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003cp\u003e2007, 2010\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMedian (ng/mg): 1.53 (cases), 1.69 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.04 (18.3%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as the LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (\u0026mu;g/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u0026nbsp;\u003c/strong\u003eLarge sample size\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias\u003c/strong\u003e: Exposure assessment expected to be of high quality; BPA analyses conducted by CDC laboratory. Narrow exposure range with low contrast, limiting ability to detect an effect. Exposure proxy may be affected by background contamination.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLn(BPA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.91 (0.8\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt; LOD\u0026ndash;0.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.958\u0026ndash;1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.76 (0.53\u0026ndash;1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.38\u0026ndash;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.76 (0.53\u0026ndash;1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.05\u0026ndash;3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.8 (0.56\u0026ndash;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.63\u0026ndash;388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.75 (0.52\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eTrend-test \u003cem\u003ep\u003c/em\u003e-value: 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eKeshavarz-Maleki et al. (2021)\u003c/p\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: first morning void sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: ELISA\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/ml): 1.69 (cases), 0.83 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.01 (7.32% cases, 18.18% controls)\u003c/p\u003e\n \u003cp\u003eMethods: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: Yes\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e Selection of all subjects from single referral center may not reflect the underlying study population. Reported difficulty in enrolling healthy controls from same referral center. Limited number of sociodemographic variables presented. Controls not matched to cases, and may not reflect source population. Small sample size.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e ELISA may cross-react with other substances. Unadjusted for creatinine. Exposure proxy may be affected by other substances.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e BPA measured in 2 matrices\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eContinuous\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10.59 (1.62\u0026ndash;65.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLopez-Carrillo et al. (2021)\u003c/p\u003e\n \u003cp\u003eMexico\u003c/p\u003e\n \u003cp\u003e2007\u0026ndash;2011\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: first morning void sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC/FD\u003c/p\u003e\n \u003cp\u003eAnalyte: Free BPA\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/ml): 20.81 (all), 28.11 (cases), 13.42 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 2.78 (85.2%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2 (1.97 \u0026mu;g/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: Yes\u003c/p\u003e\n \u003cp\u003eQC: Yes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (\u0026mu;g/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias\u003c/strong\u003e: high LOD; BPA was imputed for the majority of cases (82%) and controls (88%); BPA-F susceptible to contamination\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eConfounding\u003c/strong\u003e: BMI not adjusted\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAll women \u0026le;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAll women 1.40\u0026ndash;12.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.73 (0.39\u0026ndash;1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAll women \u0026gt;12.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2.31 (1.43\u0026ndash;3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eMuthusamy et al. (2021)\u003c/p\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC/FD\u003c/p\u003e\n \u003cp\u003eAnalyte: NR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean (ng/ml): 5.76 (cases), 1.18 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOQ (ng/ml): 0.5 (16% cases, 36% controls)\u003c/p\u003e\n \u003cp\u003eMethods: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;No risk estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e lack of details in reporting.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eWu et al. (2021)\u003c/p\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003cp\u003e2001\u0026ndash;2006\u003c/p\u003e\n \u003cp\u003eNested case-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: first morning void or overnight sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: LC-HRAM-MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mg) (95% CI): 1.17 (1.08\u0026ndash;1.28) (cases), 1.15 (1.06\u0026ndash;1.25) (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOQ (ng/ml): 0.001 (2%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOQ/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias\u003c/strong\u003e: BPA measured prospectively; however exposure proxy susceptible to background contamination. High within-batch variability (21.9%). Samples from postmenopausal women may reflect irrelevant time window of exposure.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Several sensitivity analyses conducted by hormone receptor positivity (\u0026ldquo;ER+ or PR+\u0026rdquo;, or \u0026ldquo;ER\u0026ndash; and PR\u0026ndash;\u0026ldquo;), BMI, years follow-up, stage at diagnosis), use of hormone replacement therapy (HRT), race/ethnicity.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026le;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026gt;0.84 to \u0026le;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.84 (0.67\u0026ndash;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e313\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026gt;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.95 (0.75\u0026ndash;1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eTrend-test \u003cem\u003ep\u003c/em\u003e-value: 0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eHe et al. (2022)\u003c/p\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003cp\u003e2016\u0026ndash;2019\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: UHPLC-HRMS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA without deconjugated BPA-S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mg): 2.45 (IQR: 0.87\u0026ndash;6.15) (cases), 1.19 (IQR: 0.60\u0026ndash;2.15) (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.031 (% NR)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: Yes\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (\u0026mu;g/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e No detailed description of the analyzed vs target population, no information on response rates\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e False positives possible due to multiple comparisons of interactions between BPA and several SNPs in CYP genes\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eConfounding:\u003c/strong\u003e BMI not adjusted for\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Severe limitations in reporting study details and analyses. Inappropriate reference categories in stratified analyses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePer \u0026mu;g/g unit increment (cont.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.54 (1.34\u0026ndash;1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026le;1.71\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026gt; 1.71\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2.48 (1.78\u0026ndash;3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eCathey et al. (2023)\u003c/p\u003e\n \u003cp\u003eUS (NHANES)\u003c/p\u003e\n \u003cp\u003e2005\u0026ndash;2016\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mL): 1.49 (IQR: 2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD: NR (8.5%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eReported in NHANES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Self-reported cancers susceptible to outcome misclassification.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u0026nbsp;\u003c/strong\u003eCross-sectional design used to inform hypotheses in emerging cohort studies, not for causal inference. Sensitivity analyses stratified by race/ethnicity and sex to inform future analyses on disparities in associations between environmental exposures and cancer outcomes.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePer IQR increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.06 (0.78\u0026ndash;1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eXiong et al. (2025)\u003c/p\u003e\n \u003cp\u003eUS (NHANES)\u003c/p\u003e\n \u003cp\u003e2005\u0026ndash;2014\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMedian (ng/ml): 0.41 (IQR: 1.52; range: -0.36\u0026ndash;1.16)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.40 (2005\u0026ndash;2012); 0.20 (2013\u0026ndash;2014) (9.54%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eReported in NHANES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR , BPA (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Self-reported cancers susceptible to outcome misclassification.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLog10 BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.95 (0.76 \u0026ndash; 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e-1.96\u0026ndash;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.10\u0026ndash;0.92\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.78 (0.45 \u0026ndash; 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.96\u0026ndash;6.87\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.83 (0.44 \u0026ndash; 1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eTrend-test \u003cem\u003ep\u003c/em\u003e-value: 0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" valign=\"top\" style=\"width: 960px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomonitoring: Breast adipose tissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eReeves et al. (2018)\u003c/p\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eBreast adipose tissue sample (one or more)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: BPA-F\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean (ng/g): 0.71 (cases), 0.66 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOQ (ng/g): 0.38 (73.9% cases, 65.2% controls)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: Yes\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, Detectable BPA (\u0026gt;LOQ of 0.38 ng/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e Possible. Controls were reduction mammoplasty patients that may not represent the source population.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias\u003c/strong\u003e: BPA levels were highly variable both within-breast and between breasts\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Only study to account for repeated measurements; small sample size; unclear how the ORs were calculated (all cases were compared to controls).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eCases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.9 (0.4\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eKeshavarz-Maleki et al. (2021)\u003c/p\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eBreast adipose tissue sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: ELISA\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/g): 3.50 (cases), 1.50 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (pg/g): 0.065 (26.83% cases, 45.46% controls)\u003c/p\u003e\n \u003cp\u003eMethods: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: Yes\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eOR, BPA (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e Possible. All subjects selected from single referral center. Reported difficulty in enrolling healthy controls from same referral center. Limited number of sociodemographic variables presented. Controls not matched to cases, and may not reflect source population. Small sample size.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e ELISA may cross-react with other substances. Unadjusted for creatinine. Exposure proxy may be affected by other substances.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e BPA measured in 2 matrices.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eContinuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e54.96 (2.08\u0026ndash;1372.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\" valign=\"top\" style=\"width: 960px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomonitoring: Serum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAjayi et al. (2014)\u003c/p\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eSerum sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC\u003c/p\u003e\n \u003cp\u003eAnalyte: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean (ng/ml): 7.9 (cases), 2.99 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.2 (% NR)\u003c/p\u003e\n \u003cp\u003eMethods: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eNo risk estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eNotes: lack of details in reporting\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYang et al. (2009)\u003c/p\u003e\n \u003cp\u003eKorea\u003c/p\u003e\n \u003cp\u003e1994\u0026ndash;1997\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eSerum sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC/FD\u003c/p\u003e\n \u003cp\u003eAnalyte: Conjugated BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMean (ng/ml): 1.69\u003c/p\u003e\n \u003cp\u003eMedian: 0.043\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.012 (49.2%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eNo risk estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003eNotes: lack of details in reporting\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSalamanca-Fernandez et al. (2021)\u003c/p\u003e\n \u003cp\u003eSpain (EPIC study)\u003c/p\u003e\n \u003cp\u003e1992\u0026ndash;1996\u003c/p\u003e\n \u003cp\u003eCase-cohort\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eSerum sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: UHPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eGeometric mean (ng/ml): 1.12 (cases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.2 (24.3% cases, 36.6% controls)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as the LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eHR, continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias\u003c/strong\u003e: \u0026nbsp;~30% of samples \u0026lt;LOD were imputed. Serum may under-detect BPA exposure\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Large study with prospective sample collection and adequate follow-up time (median 16.9 years).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eBPA levels (5 ng/ml increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.047 (0.98\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eLog2(BPA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.011 (0.97\u0026ndash;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eHR, BPA (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt; LOD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.2\u0026ndash;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.82 (0.61\u0026ndash;1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.8\u0026ndash;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.875 (0.65\u0026ndash;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5.1\u0026ndash;68.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.127 (0.84\u0026ndash;1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e All biomonitoring studies were limited by a single measurement of BPA per biological matrix\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eAdjusted for creatinine, unless otherwise noted\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eunadjusted for creatinine\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e unadjusted concentrations of BPA analytes were included in the analysis with urinary creatinine added as a separate independent variable, per the method of Barr et al. 2005\u003c/p\u003e\n\u003cp\u003eCr, creatinine\u003c/p\u003e\n\u003cp\u003eNR, not reported\u003c/p\u003e\n\u003cp\u003eCont., continuous\u003c/p\u003e\n\u003cp\u003eELISA, Enzyme linked immunosorbent assay\u003c/p\u003e\n\u003cp\u003eHPLC, High-pressure liquid chromatography\u003c/p\u003e\n\u003cp\u003eHPLC/FD, High-pressure liquid chromatography equipped with a fluorescence detector\u003c/p\u003e\n\u003cp\u003eHPLC-MS/MS, High-pressure liquid chromatography with tandem mass spectrometry detection\u003c/p\u003e\n\u003cp\u003eLC/HRAM-MS, liquid chromatography-high-resolution accurate-mass mass spectrometry\u003c/p\u003e\n\u003cp\u003eUHPLC-HRMS, Ultrahigh-performance liquid chromatography-high-resolution mass spectrometry\u003c/p\u003e\n\u003cp\u003eUHPLC-MS/MS, Ultra-high performance liquid chromatography with tandem mass spectrometry detection\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEpidemiologic studies of BPA and prostate cancer: exposure characterization and results by exposure matrix\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and year of publication\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"942\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference; Location;\u0026nbsp;\u003cbr\u003e\u0026nbsp;Years of BPA measurement; Study design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure assessment details\u003csup\u003e1\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalytical method and analyte\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPA levels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOD or LOQ (% below LOD) and Methods for samples below LOD/LOQ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethods to limit contamination?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eQC measures?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure category or level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk estimate\u003cbr\u003e\u0026nbsp;(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposed cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 942px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestionnaire\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTse et al. (2017; 2018)\u003c/p\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003cp\u003e2011\u0026ndash;2016\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCase-control\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"7\" valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eTool that reconstructed BPA exposure through questionnaire data (use of specific types of food and beverage containers and handling conditions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCumulative BPA index: low, middle, high\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eOR, Cumulative BPA Index (main model)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e Possible. Use of hospital controls may differ in lifestyle habits from general population.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Misclassification of BPA exposure possible: no considerations of exposure variations over time, exposure through sources other than specific types of food and beverage containers.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.66 (1.15\u0026ndash;2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.88 (1.24\u0026ndash;2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eTrend-test p-value: 0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eEver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.1 (1.0\u0026ndash;4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 942px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomonitoring: Urine\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTarapore et al. (2014)\u003c/p\u003e\n \u003cp\u003eUS\u003c/p\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003cp\u003eCross-sectional\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-ESI-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mg): 5.74 (cases), 1.43 (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.05 (% NR)\u003c/p\u003e\n \u003cp\u003eMethod: Imputed as the LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eNo risk estimate.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSalamanca-Fernandez et al. (2021)\u003c/p\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003cp\u003e1992\u0026ndash;1996\u003c/p\u003e\n \u003cp\u003eCase-cohort\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: UHPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eGeometric mean (ng/ml): 1.33 (cases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLOD (ng/ml): 0.2 (24.3% cases, 36.6% controls)\u003c/p\u003e\n \u003cp\u003eMethod: Imputed as the LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eHR, continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eLarge study with prospective sample collection and adequate follow-up time (median 16.9 years). ~30% of samples \u0026lt;LOD were imputed.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eBPA levels (5 ng/ml increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.99 (0.92\u0026ndash;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eLog2(BPA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.04 (0.99\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eHR, BPA (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt; LOD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.2\u0026ndash;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.40 (1.05\u0026ndash;1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.8\u0026ndash;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.37 (1.02\u0026ndash;1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5.1\u0026ndash;68.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.31 (0.98\u0026ndash;1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eCathey et al. (2023)\u003c/p\u003e\n \u003cp\u003eUS (NHANES)\u003c/p\u003e\n \u003cp\u003e2005\u0026ndash;2016\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC-MS/MS\u003c/p\u003e\n \u003cp\u003eAnalyte: Total BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eGeometric mean (ng/mL): 1.49 (IQR: 2.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLOD: NR (8.5%)\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eReported in NHANES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eOR, BPA (ng/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelection bias:\u003c/strong\u003e NHANES is a large, representative study with high quality exposure assessment. Potential for length-biased sampling due to cross-sectional design.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInformation bias:\u003c/strong\u003e Self-reported cancers susceptible to outcome misclassification.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u0026nbsp;\u003c/strong\u003eCross-sectional design used to inform hypotheses in emerging cohort studies, not for causal inference. Sensitivity analyses stratified by race/ethnicity and sex to inform future analyses on disparities in associations between environmental exposures and cancer outcomes.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003ePer IQR increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.80 (0.58\u0026ndash;1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003ePer IQR increase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.87 (0.51\u0026ndash;1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAlvarez-Gonzalez et al. (2024)\u003c/p\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003cp\u003e2018\u0026ndash;2023\u003c/p\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: GC-MS\u003c/p\u003e\n \u003cp\u003eAnalyte: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMedian (ng/ml): 20.0 (IQR: 13.1\u0026ndash;27.4) (cases); 10.0 (IQR: 3.6\u0026ndash;15.4) (controls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLOD: NR\u003c/p\u003e\n \u003cp\u003eMethods: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eLimit contamination: NR\u003c/p\u003e\n \u003cp\u003eQC: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eOR, BPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e lack of details in reporting\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eFull model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.32 (1.09\u0026ndash;1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eBackwards variable selection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.28 (1.09\u0026ndash;1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eWang et al. (2024)\u003c/p\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003cp\u003e2009\u0026ndash;2019\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eUrine: spot sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMethod: HPLC\u003c/p\u003e\n \u003cp\u003eAnalyte: NR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eMean (\u0026mu;g/g Cr): 1.20 (cases); 0.79 (control)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLOD (\u0026mu;g/l): 0.12\u003c/p\u003e\n \u003cp\u003eMethods: Imputed as LOD/\u0026radic;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eLimit contamination: yes\u003c/p\u003e\n \u003cp\u003eQC: Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eOR, BPA (\u0026mu;g/g Cr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026ge;0.45 \u0026ndash; \u0026lt; 1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.87 (1.16\u0026ndash;7.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026ge;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e7.33 (2.63\u0026ndash;20.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 234px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e All biomonitoring studies were limited by a single measurement of BPA per biological matrix\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eAdjusted for creatinine, unless otherwise noted\u003c/p\u003e\n\u003cp\u003eCr, creatinine\u003c/p\u003e\n\u003cp\u003eNR, not reported\u003c/p\u003e\n\u003cp\u003eHPLC-ESI-MS/MS, High-performance liquid chromatography coupled with electrospray triple-quadrupole mass spectrometry\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHPLC-MS/MS, High-pressure liquid chromatography with tandem mass spectrometry detection\u003c/p\u003e\n\u003cp\u003eUHPLC-MS/MS, Ultra-high performance liquid chromatography with tandem mass spectrometry detection\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enhe","sideBox":"Learn more about [Environmental Health](http://ehjournal.biomedcentral.com)","snPcode":"12940","submissionUrl":"https://submission.nature.com/new-submission/12940/3","title":"Environmental Health","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bisphenol A, Cancer, Epidemiology, Biomonitoring, Exposure Misclassification, Review","lastPublishedDoi":"10.21203/rs.3.rs-6742025/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6742025/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBACKGROUND: Bisphenol A (BPA) is a high production volume chemical that has been used for decades in numerous consumer and industrial applications. Daily exposure to BPA is likely; it is readily detected in \u0026gt;90% of the general population despite being rapidly metabolized and excreted. BPA’s toxicity, including endocrine disrupting activity, has sparked public health concern. We comprehensively reviewed the epidemiologic literature on the carcinogenicity of BPA and highlighted exposure assessment considerations that impact study interpretation.\u003c/p\u003e\n\u003cp\u003eMETHODS: Multiple biomedical databases were searched through February 2025 for peer-reviewed cancer epidemiology studies that assessed associations with BPA exposure. Studies of the following designs (or a variant) were included: cohort, case-control, cross-sectional. A detailed bias assessment was conducted with guidance from the Report on Carcinogens handbook and the International Agency for Research on Cancer Monographs Preamble.\u003c/p\u003e\n\u003cp\u003eRESULTS: Of the 139 records identified, 43 epidemiological studies were reviewed; all were conducted in the general population. We focused the review on cancers of the breast and prostate because they had the highest number of cohort or case-control studies, but all cancer sites were summarized in the appendix for completeness. Associations with BPA were inconsistent within and across studies. Interpretation was hampered by the high potential for exposure measurement error and the inability to characterize past BPA exposure, necessary to assess cancer outcomes with long latency. The majority of studies relied on biomonitoring using short-term biomarkers of recent BPA exposure, and measured BPA in urine at a single time point post-diagnosis; this failed to capture the critical time window of susceptibility, rule out reverse causation, or characterize temporal variation in BPA exposure.\u003c/p\u003e\n\u003cp\u003eCONCLUSIONS: The epidemiologic evidence was inadequate to evaluate the carcinogenicity of BPA – mainly due to exposure measurement error and misclassification, limited number of studies by cancer site, and the lack of consistency across studies. The inadequate evidence base cannot rule out potential carcinogenicity of BPA in humans. Future studies conducted within highly exposed occupational cohorts, with prospective and longitudinal collection of quantitative exposure data and assessment of cancer morbidity or acute endpoints involved in established mechanisms of carcinogenesis are likely to be informative.\u003c/p\u003e","manuscriptTitle":"Bisphenol A and cancer: a critical review of the epidemiologic literature with an emphasis on exposure assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-30 08:05:41","doi":"10.21203/rs.3.rs-6742025/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-10T12:27:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-30T14:38:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-19T14:58:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265023526176173699310105545441599237521","date":"2025-05-29T11:09:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202768654179689442648593207107847291167","date":"2025-05-29T10:48:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-28T12:47:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-26T06:41:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-26T06:36:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Health","date":"2025-05-25T06:13:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enhe","sideBox":"Learn more about [Environmental Health](http://ehjournal.biomedcentral.com)","snPcode":"12940","submissionUrl":"https://submission.nature.com/new-submission/12940/3","title":"Environmental Health","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e44ecac7-abe8-4393-80c4-a6a18cd26773","owner":[],"postedDate":"June 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T08:40:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-30 08:05:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6742025","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6742025","identity":"rs-6742025","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}