Associations between the Exposure of Polycyclic Aromatic Hydrocarbons and the Risk of Cancers Related to Deregulation of Estrogen Receptors: NHANES 2001-2016

Associations between the Exposure of Polycyclic Aromatic Hydrocarbons and the Risk of Cancers Related to Deregulation of Estrogen Receptors: NHANES 2001-2016 | 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 Research Article Associations between the Exposure of Polycyclic Aromatic Hydrocarbons and the Risk of Cancers Related to Deregulation of Estrogen Receptors: NHANES 2001-2016 tao Y, Naiji Yu, Weishi Cheng, Kai Kang, Yijun Wu, ailin Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4800682/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Estrogen receptor signaling is one of the most investigated pathways that associates with the endocrine-disrupting abilities of polycyclic aromatic hydrocarbons (PAHs). This study we aimed to investigate the relationships between specific PAHs exposure and cancers associated with estrogen receptor (ER) deregulation. Methods: We conducted a cross-sectional analysis of National Health and Nutrition Examination Survey (NHANES) 2001-2016 data. A history of the four types of cancers related to ERs deregulation (prostate, breast, uterine and ovarian cancer) was obtained by self-report. Exposure of PAHs was assessed by measuring ten urinary PAH metabolites. Logistic regression models were fitted to estimate the associations between specific urinary PAHs (uPAHs) and each type of cancers. Results: Exposure to certain uPAHs metabolites was linked to an increased risk of breast, uterine, and ovarian cancers. Notably, 9-hydroxyfluorene (9-OHFlu) demonstrated a dose-response relationship with elevated breast cancer risk (OR [95%CI]: 2.39 [1.09, 5.23], p for trend <0.001). Tertile analyses indicated that 2-Hydroxyfluorene (2-OHFlu) and 1-Hydroxypyrene (1-OHPyr) might increase the risk of breast and uterine cancer, respectively. Conversely, 2-Hydroxynapthalene (2-OHNap) and 1-Hydroxyphenanthrene (1-OHPhe) might be protect factors of ovarian cancer. No significant associations were found between the ten uPAHs metabolites and prostate cancer. Conclusions: Our study suggested that PAHs exposure was associated with an increased risk of breast cancer, particularly 9-OHFlu, in a dose-response manner. Additionally, PAHs exposure might increase the incidence of uterine cancer but decrease the risk of ovarian cancer. Polycyclic Aromatic Hydrocarbons Estrogen Receptors Cancers Figures Figure 1 Figure 2 1. Background Polycyclic aromatic hydrocarbons (PAHs), which consist of two or more fused aromatic hydrocarbon rings, are one of the most widely distributed persistent organic pollutants (POPs) in our environment [ 1 ][ 2 ]. PAHs originate from both natural and anthropogenic sources, with the latter now being the primary contributors. These man-made sources include the incomplete combustion of organic polymer compounds, petroleum, coal, and wood [ 3 ][ 4 ]. People are exposed to PAHs mainly by inhalation, ingestion, and direct contact [ 1 ][ 3 ]. Once inside the body, PAHs are metabolized by liver, and subsequently excreted in urine [ 5 ][ 6 ]. Therefore, urinary PAHs (uPAHs) metabolites are appropriate bio-markers of PAHs exposure and often used by bio-monitoring investigations [ 7 ][ 8 ]. PAHs are typical carcinogenic, teratogenic and mutagenic substances [ 9 ]. The high lipophilicity of PAHs increases the cancer risk and mutagenic risk after exposing to PAHs [ 10 ]. Previous epidemiological studies have illustrated that PAHs exposure in occupational environments could increase the risk of various cancers including lung, bladder, skin, breast, and larynx cancers [ 1 ][ 11 ][ 12 ][ 13 ][ 14 ][ 15 ][ 18 ]. Furthermore, PAHs are vital endocrine disrupting chemicals (EDCs). Estrogen receptor signaling is one of the most investigated pathways associated with the endocrine-disrupting abilities of PAHs, involving both estrogen receptors (ERs) and aryl hydrocarbon receptors (AhRs) [ 16 ]. Additionally, observational studies have demonstrated that EDC which are evidenced to interfere with normal hormone signaling might be associated with the development of malignancies [ 17 ]. Generally, cancers related to deregulation of ERs include breast cancer, prostate cancer, ovarian cancer and uterine cancer. Worldwide, breast cancer and prostate cancer are the most commonly diagnosed malignancy in women and men, respectively. Specially, prostate cancer ranks as the sixth leading cause of cancer death among men, while breast cancer is the second most common cause of death from cancer in women. Moreover, ovarian cancer is considered as the most lethal gynecological malignancy in the Western world [ 42 ] and uterine cancer is the most common cancer of the female reproductive tract in developed countries [ 43 ]. Although several studies demonstrated the relationships between PAHs exposure and breast cancer [ 13 ][ 14 ][ 15 ], they have not assessed the contribution of the exact components of complex PAHs mixtures. Moreover, the association between PAHs exposure and the risk of prostate cancer remains contradictory [ 28 ]. To the best of our knowledge, no previous studies have evaluated the associations between PAH components and the risk of breast and prostate cancers. Our study aims to investigate the impacts of exact components of complex PAHs mixtures on the four types of cancers related to deregulation of ERs. 2. Methods 2.1 Study Population Sample data were obtained from eight National Health and Nutrition Examination Survey (NHANES) cycles (2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016), which is an ongoing program conducted by the Centers for Disease Control (CDC) to assess the exposure of nutrition, environmental chemicals and health status of the US general populations (http://www.cdc.gov/nchs/nhanes.htm). The NHANES surveys include demographic, socioeconomic, dietary, and health-related questions, along with a comprehensive examination component that encompasses medical, physiological measurements, and laboratory tests. 2.2 Exposure Variables Urinary monohydroxylated metabolites of PAHs were measured based on laboratory manual procedures. Briefly, urine samples were collected by experienced technicians, labelled, frozen at -20℃ or below, and stored on dry ice according to laboratory procedures. uPAHs were examined with isotope dilution gas chromatography/tandem mass spectrometry (GC-MS/MS). Detailed procedures are available on the NHANES website. Ten uPAHs analytes, including 1-hydroxynapthalene (1-OHNap), 2-hydroxynapthalene (2-OHNap), 2-hydroxyfluorene (2-OHFlu), 3-hydroxyfluorene (3-OHFlu), 9-hydroxyfluorene (9-OHFlu), 1-hydroxypyrene (1-OHPyr), 1-hydroxyphenanthrene (1-OHPhe), 2-hydroxyphenanthrene (2-OHPhe), 3-hydroxyphenanthrene (3-OHPhe), and 4-hydroxyphenanthrene (4-OHPhe), were obtained from NHANES 2001-2016. All of the ten analytes were measured in ng/L. Urinary creatinine concentration was used to correct the variability of urinary analytes of PAHs (pg/g). The distribution of uPAHs analytes is listed in Table 2. 2.3 Outcome Variables The outcome variables for our analysis includes prostate, breast, ovarian and uterine cancer. These outcomes were determined by the participant response on the medical questionnaires: 1) Prostate Cancer (Yes/No), “Have you ever been told you have prostate cancer?”; 2) Breast Cancer (Yes/No), “Have you ever been told you have breast cancer?”; 3) Ovarian Cancer (Yes/No), “Have you ever been told you have ovarian cancer?”; 4) Uterine Cancer (Yes/No), “Have you ever been told you have uterine cancer?”. 2.4 Covariates Covariates in the present analysis included three parts: demographic variables, lifestyle variables and anthropometric variables. Demographic variables included age, gender, race/ethnicity, level of education, marital status and family income. Physical activity, smoking status and alcohol consumption were categorized as lifestyle variables. Anthropometric variable only contained body mass index (BMI). Age was regarded as a continuous variable While sex was a dichotomous variable. Race/ethnicity was classified into Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race. Family income was calculated as the family poverty-to-income ratio (PIR). BMI was categorized according to World Health Organization cutoffs as lean or normal weight (30.0 kg/m 2 ). All remaining covariates were categorical variables. Details of the above variables were displayed in Table 1 and Supplemental Table 1. 2.5 Statistical Analysis Statistical analysis was conducted in accordance with CDC analytical reporting guidelines for complex NHANES data(https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx). A sample weight was assigned to each participant in the NHANES. The present analysis also considered masked variance and applied the recommended weighting methodology. Descriptive analysis was used for exploring demographic characteristics of study participants. The comparison of continuous variables was conducted with Kruscal Whallis H test. Categorical variables were compared with chi-squared test or Fisher’s exact test. Demographic, lifestyle, and anthropometric variables were presented as mean (SD) or frequency (percentage). Mean, Geometric means (GM), and distribution of specific uPAHs were estimated. The exposure of PAHs was analyzed by categorization into tertiles (Tertile 1, Tertile 2 and Tertile 3). Logistic regression model was applied to analyze the associations between specific uPAHs (both as continuous variable and divided into tertiles) and the incidence of the four types of cancers (breast, prostate, ovarian and uterine cancer). Besides, we also placed the each continuous uPAHs variable into the logistic regression model to obtain the p-values for trend. Specially, the logistic regression model was adjusted for age, race, PIR category, level of education, marital status, BMI, smoking status, alcohol consumption, and physical activity. Before conducting logistic regression analysis, the corrected concentrations of uPAHs were subjected to log10 transformation. The results were presented as odds ratio (OR) and 95% confidence interval (CI]. A p-value ≤ 0.05 was considered as statistically significant. All analyses were conducted using the statistical software packages R (http://www.R-project.org; The R Foundation) and Empower Stats (http://www.empower stats.com, X&Y Solutions, Inc.). 3 Results 3.1 Characteristics of Participants There were 102956 participants of NHANES 2001-2016 included in the present study, and 21299 participants were tested for uPAHs and urinary creatinine data. Participants with missing or incomplete questionnaires regarding prostate, breast, ovarian and uterine cancer were excluded. Finally, a total of 13566 participants remained, including 486 participants with any types of cancers related to deregulation of ERs and 13080 without. (Figure 1) Table 1 shows the demographic, lifestyle, and anthropometric characteristics of subjects included in the analysis. The average age (SD) was 48.89 (18.04) years. The majority of participants were non-Hispanic White (45.13%), received education above high school (50.40%), were married or cohabiting (60.70%), had never smoked (54.19%), did not have alcohol consumption (77.16%), and were classified into less than moderate physical activity group (49.13%). Approximately 29.13% of subjects were obese. According to the PIR category, 42.11% of subjects fell into the 1.3-3.5 range. About 1.50%, 1.45%, 0.28%, and 0.41% participants were diagnosed with prostate, breast, ovarian and uterine cancer, respectively. Distributions of uPAHs concentrations are displayed in Table 2. The GM of urinary concentrations for 1-OHNap, 2-OHNap, 2-OHFlu, 3-OHFlu, 9-OHFlu, 1-OHPyr, 1-OHPhe, 2-OHPhe, 3-OHPhe, 4-OHPhe were 2332.86 ng/L (30.72%), 4161.91 ng/L (54.81%), 272.78 ng/L (3.59%), 108.98 ng/L (1.44%), 306.86 ng/L (4.04%), 99.25 ng/L (1.31%), 129.69 ng/L (1.71%), 65.61 ng/L (0.86%), 89.99 ng/L (1.19%), and 25.29 ng/L (0.33%), respectively. Comparisons of these characteristics between participants with and without any types of cancers related to deregulation of ERs are shown in Supplemental Table 1 and 2. 3.2 Associations Between Specific uPAHs and Cancers Related to Deregulation of ERs Associations between specific uPAHs and various cancer types were presented in Table 3 and Figure 2. As displayed in Table 3, a unit increase in 9-OHFlu was associated with a 139% increase in the odds of breast cancer (p=0.029) [Figure 2B]. While other uPAHs may influence the likelihood of developing prostate, breast, ovarian, or uterine cancer, no significant differences were observed. To further investigate the associations between specific uPAHs and each type of cancers, we conducted tertile analyses [Table 3]. Similarly, there were no significant difference between uPAHs and prostate cancer. However, 9-OHFlu was associated with an increased risk of breast cancer in a dose-response relationship (Tertile 1 vs. Tertile 3, OR [95%CI]: 2.72 [1.36, 5.43], p for trend <0.001). The results also indicated that 1-OHPyr could elevate the risk of breast cancer (Tertile 1 vs. Tertile 2, OR [95%CI]: 1.60 [1.04, 2.47]) though the trend was not significant (p for trend 0.67). As for ovarian cancer and uterine cancer, the results showed that 2-OHNap (Tertile 1 vs. Tertile 2, OR [95%CI]: 0.13 [0.03, 0.61]) and 1-OHPhe (Tertile 1 vs. Tertile 2, OR [95%CI]: 0.33 [0.11, 0.99]) appeared to reduce ovarian cancer risk, whereas 2-OHFlu (Tertile 1 vs. Tertile 2, OR [95%CI]: 2.56 [1.06, 6.16]) might increase the incidence of uterine cancer. However, no significant trends were detected for these associations (p for trend 0.80, 0.50 and 0.15, respectively). 4 Discussion The present study investigated relationships of PAHs exposure and cancers related to deregulation of ERs in the general U.S. population using a nationally-representative sample. Our results illustrated that the potential relevance between uPAHs and each type of cancers varied depending on specific uPAHs and the types of cancer. We observed that 9-OHFlu was positively associated with breast cancer, with a clear dose-dependent relationship. Additionally, 1-OHPyr appeared to increase the risk of breast cancer, while 2-OHFlu was associated with an elevated risk of uterine cancer. Conversely, 2-OHNap and 1-OHPhe might serve as protective factors against ovarian cancer. There might be no significant associations between PAHs exposure and prostate cancer. ERs are expressed in cells distributed throughout the female genital tract and breast [17]. In human prostate, ERs were found in both prostate stromal and epithelial cells [19]. As for ER-positive cells, oestrogen could promote DNA instability, cellular hyperplasia and neoplastic transformation of normal epithelial cells into carcinomas after binding to ERs [17]. Furthermore, previous studies have illustrated that the activation of estrogen signaling was associated with carcinogenicity and progression of uterine, breast, ovarian and prostate cancer [17][22]. Estrogen receptor signaling is one of the most investigated pathways related to the endocrine-disrupting abilities of PAHs [18]. Various PAHs were previously reported to be agonist or antagonist of ERs [16], which could be explained in three aspects. Firstly, several investigations demonstrated that PAHs and hydroxyl PAHs had different roles in the estrogenicity [18][20][21]. Secondly, when PAHs bind to AhRs, the activated AhRs could indirectly interfere with ER-responsive trans-activation functions or directly compete with estrogen[18]. Finally, metabolism or bio-accumulation of PAHs varied in different tissues and cells[18]. Additionally, PAHs shown differential actions between ERα and ERβ, which could always play different roles in the estrogen signaling [16]. Therefore, specific PAHs might have different effects on various cancers, and different PAHs might have different effects on specific kind of cancers. This assumption was also supported by the findings of the present study. Our results revealed a dose-response relationship between increased concentrations of 9-OHFlu and elevated breast cancer risk. Besides, 1-OHPyr and 2-OHFlu were implicated in the carcinogenicity of breast cancer and uterine cancer, respectively. Previous studies also showed that women exposed to PAHs from multiple sources, such as occupational, ambient air, and smoking, had a higher incidence of breast cancer [13][14][15][23]. F Our current analysis further identified the specific PAHs in the PAHs mixture contributing to the progression of breast cancer. However, there was no epidemic studies to investigate the role of PAHs on uterine cancer. Fortunately, the findings of PAHs administration in animals and cells could support these results. Previous laboratory evidence indicated that both 1-OHPyr and 2-OHFlu showed strong estrogenic activity [24][25]. Although there were no laboratory evidence directly investigating the association between 9-OHFlu and ERs, we hypothesize the 9-OHFlu might show similar estrogenic activity to 2-OHFlu because they were both hydroxyl fluorene (OH-Flu). Additionally, as a kind of aryl hydrocarbon, 9-OHFlu could activated AhRs. promoting the development of breast cancer [27]. Recent research demonstrated that exposure to OH-Flu were associated with lower DNA methylation of AHRR in lung cancer [26]. AHRR, a suppressor of the AhR pathway, has been shown to inhibit AhR-driven breast cancer growth in two different murine models when over-expressed [27]. These findings suggested that 9-OHFlu plays a vital role in the carcinogenicity and progression of breast cancer, and targeting the mechanism of the carcinogenicity of 9-OHFlu might have therapeutic benefits, but further investigation is needed. We observed that there were no significant relationships between all of the ten uPAHs and risk of prostate cancer. Although part of the ten uPAHs were evidenced as agonist of ERs, high dosage PAHs exposure was related to reduction of serum testosterone (T) concentration and exerted anti-androgenic effects by competing with androgen binding to androgen receptor (AR) [33][34]. According to the reliance of prostate cancer to the AR signaling, the effect of PAHs on T and AR signaling might impair the effect of PAHs on ERs. Besides, gender differences in the genotoxic capabilities of PAHs could exist. Males typically exhibit lower cytochrome P450 (CYP) enzyme activity and greater DNA repair capacity compared to females, making them less susceptible to PAH-induced chromosomal damage and oxidative stress [1][35]. A number of epidemiological studies also investigated the associations between occupational PAHs exposure and prostate cancer [28]. Part of them demonstrated that PAHs exposure was implicated in prostate carcinogenesis in petroleum workers, chimney sweeps and hairdressers [28][29]. However, others demonstrated non-significant elevated risks of prostate cancer associated with occupational exposure to coals and oils [30][31]. Additionally, Rybicki et al. indicated that occupational PAHs exposure increased risk of prostate cancer in men with GSTP1 Val 105 variant, rather than in the entire male population [32]. All in all, more studies are needed to confirm the associations and mechanisms between PAHs and prostate cancer risk. Our results showed that 2-OHNap and 1-OHPhe might be protective factors against ovarian cancer. Previous studies have demonstrated that the elevated risk of ovarian cancer is strongly linked to the activation of Erα [36]. ERβ is always recognized as a vital tumor suppressor in ovarian cancer [37]. Besides, normal ovarian tissue generally contains high level of ERβ, predominantly expressed in granulosa cells, theca cells, surface epithelium and corpus luteum [38]. A laboratory study have indicated that 1-OHNap and 9-OHPhe can selectively induce the transcriptional activity of ERβ without affecting Erα [25]. As the similar structures of between 1-OHNap and 2-OHNap, and between 1OHPhe and 9-OHPhe, we hypothesize that 2-OHNap and 1-OHPhe might exert similar effects on ERα and ERβ despite the lack of direct studies on these relationships. Furthermore, using exogenous estrogens as hormone replacement therapy (HRT) in premenopausal women has been associated with a significantly decreased relative risk of ovarian cancer [39]. However, long-term HRT use in post-menopausal women was associated with an elevated risk of ovarian cancer [40], possibly due to a reduction in the total number of ovulations, a major risk factor for ovarian cancer [41]. Consequently, further investigation is warranted into the associations between PAH exposure and ovarian cancer risk, as our study shows no significant trends and few studies have addressed this issue. Our research has several advantages. First, the data we used have external validity and national relevance. Second, the present study includes large sample size, random sample selection, and uniform data collection. Third, the relationships between ten specific PAHs and four types of cancer were investigated from an epidemiological perspective, which could provide possible mechanistic implications for further explorations and clinical translations. However, this study also has some limitations. Firstly, the nature of cross-sectional studies makes it unable to draw a causal association between the present results. Fortunately, the laboratory evidence supports the assumption that exposure to part of specific PAHs could elevate the risk of breast and uterine cancer. Second, while we adjusted for some covariates, additional factors such as dietary influences were not considered. Third, NHANES questionnaire data are based on participant self-reported, therefore, there might exist recall bias. Finally, the present study used uPAHs concentrations to present the specific PAHs exposure. Due to individual variations in liver and kidney metabolic capacity, urinary PAHs may affect the assessment of internal PAHs exposure levels. To the best of our knowledge, there were no methods and techniques to detect the markers of PAHs in blood. 5 Conclusions Our study suggests that PAHs exposure was associated with an increased risk of breast cancer in a dose-response relationship, especially with 9-OHFlu. Additionally, PAHs exposure appears to elevate the incidence of uterine cancer while potentially reducing the risk of ovarian cancer. To better understand these associations, future longitudinal studies should aim to identify threshold exposure levels and validate the connections between PAHs and the risks of uterine and ovarian cancers. Abbreviations Declarations Competing interests We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted. Acknowledgements None. Funding support This work was supported by Postdoctoral Fellowship Program of CPSF (No. GZB20230481), Post doctor Research Fund of West China Hospital, Sichuan University (No. 2024HXBH149, No. 2024HXBH006), National Natural Science Foundation of China (No. 82303773, No. 82303772, No. 82303694), Natural Science Foundation of Sichuan Province (No. 2024NSFSC1908), Key Research and Development Program of Sichuan Province (No. 23ZDYF2836). Ethics approval and consent to participate This study was conducted according to the guideline laid down in the Declaration of Helsinki, and all procedures involving study participants were approved by the Institutional Review Board of the National Center for Health Statistics (NCHS). All participants provided written informed consent. Contributors YT, YNJ and CWS contributed equally as first authors of this manuscript. YT are responsible for the conception and design of the study. YNJ interpreted the analysis. YT and YNJ were responsible for the acquisition of data. YT and YNJ wrote the first draft of the manuscript and interpreted the data and wrote the final version. All authors critically revised the article for important intellectual content and approved the final version. ZAL and WYJ obtained public funding. Consent for publication All authors have read and approved the final draft. Availability of data and materials Sample data were obtained from eight National Health and Nutrition Examination Survey (NHANES) cycles (2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016), which is an ongoing program conducted by the Centers for Disease Control (CDC) to assess the exposure of nutrition, environmental chemicals and health status of the US general populations (http://www.cdc.gov/nchs/nhanes.htm). References Sun K, Song Y, He F, et al. 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Mutagen. 2014;55(6):472-481. https://doi.org/10.1002/em.21866 Langdon SP, Herrington CS, Hollis RL, et al. Estrogen Signaling and Its Potential as a Target for Therapy in Ovarian Cancer. Cancers (Basel) 2020;12(6):1647. https://doi.org/10.3390/cancers12061647 Lee J-Y, Kim HS, Song Y-S. Genistein as a Potential Anticancer Agent against Ovarian Cancer. J. Tradit. Complement. Med. 2011;2(2):96-104. https://doi.org/10.1016/s2225-4110(16)30082-7 Drummond AE, Fuller PJ. The importance of ER beta signalling in the ovary. Endocrinology 2010;205(1):15-23. https://doi.org/10.1677/JOE-09-0379 Risch HA. Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone. J. Natl. Cancer Inst. 1998;90(23):1774-1786. https://doi.org/10.1093/jnci/90.23.1774 Beral V, Gaitskell K, Hermon C, et al. Menopausal hormone use and ovarian cancer risk: Individual participant meta-analysis of 52 epidemiological studies. Lancet 2015;385(9980):1835-1842. https://doi.org/10.1016/S0140-6736(14)61687-1 Trabert B, Tworoger SS, O’Brien KM, et al. The Risk of Ovarian Cancer Increases with an Increase in the Lifetime Number of Ovulatory Cycles: An Analysis from the Ovarian Cancer Cohort Consortium (OC3). Cancer Res 2020;80(5):1210-1218. https://doi.org/10.1158/0008-5472.CAN-19-2850 Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018:68(6):394-424. https://doi.org/10.3322/caac.21492 Colombo N. Creutzberg C, Amant F, et al. ESMO-ESGO-ESTRO consensus conference on endometrial cancer: diagnosis, treatment and follow-up. Ann Oncol. 2016;27(1):16-41. https://doi.org/10.1093/annonc/mdv484 Tables Table 1. General Characteristics of Participants Analyzed, NHANES 2001-2016. NHABES= National Health and Nutrition Examination Survey; SD=Standard Deviation; n=Numbers of Participants; %=Weighted Percentage; BMI=Body Mass Index; PIR=Income-to-Poverty Ratio. Variables Participants (n = 13566) Age (years, mean ± SD) 48.89±18.04 Gender, n (%) Male 6657 (49.07) Female 6909 (50.93) Race/Ethnicity , n (%) Mexican American 2314 (17.06) Other Hispanic 1123 (8.28) Non-Hispanic White 6122 (45.13) Non-Hispanic Black 2809 (20.71) Other Race 1198 (8.83) Education, n (%) Under high school 3586 (26.43) High school or equivalent 3143 (23.17) Above high school 6837 (50.40) Marital Status , n (%) Married/cohabiting 8235 (60.70) Living alone 5331 (39.30) BMI, n (%) 30 4787 (35.29) PIR category , n (%) 3.5 3952 (29.13) Smoking Status , n (%) never 7352 (54.19) former 3865 (28.49) current 2349 (17.32) Physical Activity , n (%) Less than moderate 6665 (49.13) Moderate 2163 (15.94) Vigorous 4738 (34.93) Alcohol consump tion , n (%) Never 10468 (77.16) Moderate 1112 (8.20) Heavy 1986 (14.64) Prostate Cancer, n (%) No 13362 (98.50) Yes 204 (1.50) Breast Cancer, n (%) No 13369 (98.55) Yes 197 (1.45) Ovarian Cancer, n (%) No 13528 (99.72) Yes 38 (0.28) Uterine Cancer, n (%) No 13511 (99.59) Yes 55 (0.41) Table 2. Distribution of uPAHs Levels Among Participants, NHANES 2001-2016. 1-OHNap=1-Hydroxynapthalene; 2-OHNap=2-Hydroxynapthalene; 3-OHFlu=3-Hydroxyfluorene; 2-OHFlu=2-Hydroxyfluorene; 3-OHPhe=3-Hydroxyphenanthrene; 1-OHPhe=1-Hydroxyphenanthrene; 2-OHPhe=2-Hydroxyphenanthrene; 1-OHPyr=1-Hydroxypyrene; 9-OHFlu=9-Hydroxyfluorene; 4-OHPhe=4-Hydroxyphenanthrene; SD=Standard Deviation; GM=Geometric Means; 95%CI= 95% Confidence Interval; uPAHs=urinary Polycyclic Aromatic Hydrocarbons. uPAHs ( mean ± SD) Mean GM (95% CI) Min 5% th 10% th 25% th 50% th 75% th 90% th 95% th Max 1-OHNap 5732.02 2332.86 (2272.26 2395.08) 4.2 258 391 785 1886 6447 18047.72 30812.4 35920000 2-OHNap 6765.30 4161.91 (4076.60 4249.01) 9.3 550.25 843 1768.25 4142.5 9981.25 20576.5 30024.625 590676 3-OHFlu 241.99 108.98 (106.43 111.60) 1.4 15 21.29 41 86.3 260.925 916.19 1531.05 23854.6 2-OHFlu 481.53 272.78 (267.10 278.58) 2.8 40 60 115.825 239 599.5 1630 2570.385 21700 3-OHPhe 128.17 89.99 (88.05 91.99) 2.8 16 23 43.65 87 180 361.12 556.86 126202 1-OHPhe 168.02 129.69 (127.58 131.82) 2.8 27 38 69 130 243 434.9 612.9 13743 2-OHPhe 86.31 65.51 (64.19 66.85) 2.1 12.87 18.4 34 66 127 234.96 334.18 6355 1-OHPyr 152.34 99.25 (97.38 101.16) 2.1 16 25.9 49.5 96 203 424 649 21710 9-OHFlu 443.28 306.86 (299.72 314.18) 10.5 54 76 145.7 301.6 628.75 1210.36 1861.05 65656.6 4-OHPhe 35.10 25.29 (24.54 26.07) 3.5 5.7 7.1 12 25 50.375 96 136 2235.1 Table 3. Multivariate Logistic Regression Analysis of the Associations Between Specific uPAHs Exposure and Cancer Types. uPAHs=urinary Polycyclic Aromatic Hydrocarbons; 1-OHNap=1-Hydroxynapthalene; 2-OHNap=2-Hydroxynapthalene; 3-OHFlu=3-Hydroxyfluorene; 2-OHFlu=2-Hydroxyfluorene; 3-OHPhe=3-Hydroxyphenanthrene; 1-OHPhe=1-Hydroxyphenanthrene; 2-OHPhe=2-Hydroxyphenanthrene; 1-OHPyr=1-Hydroxypyrene; 9-OHFlu=9-Hydroxyfluorene; 4-OHPhe=4-Hydroxyphenanthrene; OR= Odds Ratio; 95%CI= 95% Confidence Interval. Logistic regression analysis was adjusted for age, race, PIR category, level of education, marital status, BMI, smoking status, alcohol consumption, and physical activity. uPAHs Prostate Cancer Breast Cancer Ovarian Cancer Uterine Cancer Adjusted OR (95% CI) p for trend Adjusted OR (95% CI) p for trend Adjusted OR (95% CI) p for trend Adjusted OR (95% CI) p for trend 1- OHNap 0.66 0.99 0.36 0.50 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 0.96 (0.58, 1.58) 1.38 (0.81, 2.35) 1.03 (0.32, 3.30) 0.54 (0.21, 1.40) Tertile 3 0.89 (0.52, 1.51) 1.06 (0.60, 1.89) 1.65 (0.51, 5.30) 1.25 (0.53, 2.96) 2- OHNap 0.74 0.07 0.80 0.41 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 0.99 (0.63, 1.56) 0.68 (0.42, 1.08) 0.13 (0.03, 0.61) 0.98 (0.42, 2.28) Tertile 3 0.90 (0.51, 1.58) 0.64 (0.38, 1.09) 0.87 (0.33, 2.29) 0.67 (0.26, 1.73) 3- OHFlu 0.78 0.92 0.19 0.57 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 0.94 (0.59, 1.51) 1.02 (0.66, 1.59) 0.56 (0.21, 1.48) 1.72 (0.80, 3.71) Tertile 3 1.11 (0.66, 1.85) 0.96 (0.54, 1.69) 0.52 (0.15, 1.81) 1.15 (0.44, 3.01) 2- OHFlu 0.59 0.87 0.20 0.15 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 0.88 (0.55, 1.39) 1.06 (0.68, 1.66) 0.57 (0.22, 1.45) 2.56 (1.06, 6.16) Tertile 3 0.88 (0.53, 1.47) 0.94 (0.55, 1.60) 0.52 (0.16, 1.66) 2.03 (0.76, 5.44) 3- OHPhe 0.96 0.25 0.82 0.61 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.08 (0.62, 1.87) 1.38 (0.79, 2.43) 0.38 (0.09, 1.57) 1.50 (0.62, 3.62) Tertile 3 0.98 (0.54, 1.78) 1.41 (0.75, 2.65) 1.34 (0.38, 4.67) 0.59 (0.17, 2.02) 1- OHPhe 0.48 0.95 0.50 0.35 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.32 (0.83, 2.08) 1.42 (0.86, 2.34) 0.33 (0.11, 0.99) 1.77 (0.70, 4.51) Tertile 3 1.19 (0.72, 1.94) 1.03 (0.62, 1.73) 0.70 (0.28, 1.77) 1.63 (0.65, 4.09) 2- OHPhe 0.75 0.20 0.79 0.42 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.31 (0.75, 2.26) 1.26 (0.71, 2.26) 1.01 (0.28, 3.65) 2.10 (0.73, 6.03) Tertile 3 0.91 (0.50, 1.66) 1.49 (0.81, 2.75) 1.23 (0.29, 5.20) 1.62 (0.53, 4.97) 1- OHPyr 0.39 0.67 0.99 0.55 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.19 (0.77, 1.85) 1.60 (1.04, 2.47) 0.43 (0.15, 1.30) 1.28 (0.58, 2.81) Tertile 3 1.23 (0.72, 2.12) 0.73 (0.41, 1.30) 1.12 (0.41, 3.02) 1.29 (0.52, 3.15) 9- OHFlu 0.77 <0.001 0.41 0.89 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.14 (0.63, 2.07) 1.87 (0.96, 3.64) 1.60 (0.41, 6.16) 1.35 (0.44, 4.09) Tertile 3 0.92 (0.48, 1.75) 2.72 (1.36, 5.43) 1.85 (0.42, 8.17) 1.10 (0.35, 3.50) 4- OHPhe 0.34 0.57 0.92 0.37 Tertile 1 1.00 1.00 1.00 1.00 Tertile 2 1.44 (0.57, 3.65) 0.65 (0.27, 1.58) 0.002 (0.00, 3.07) 0.55 (0.10, 3.10) Tertile 3 1.63 (0.58, 4.63) 0.78 (0.28, 2.16) 0.29 (0.006, 13.04) 0.43 (0.06, 2.95) Additional Declarations No competing interests reported. Supplementary Files SupplementalTable1.docx SupplementalTable2.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Mar, 2025 Reviews received at journal 10 Mar, 2025 Reviewers agreed at journal 04 Mar, 2025 Reviews received at journal 03 Mar, 2025 Reviewers agreed at journal 20 Feb, 2025 Reviewers agreed at journal 12 Feb, 2025 Reviewers invited by journal 19 Aug, 2024 Editor invited by journal 29 Jul, 2024 Editor assigned by journal 26 Jul, 2024 Submission checks completed at journal 26 Jul, 2024 First submitted to journal 25 Jul, 2024 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. 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NHABES= National Health and Nutrition Examination Survey; N=Numbers of Participants.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4800682/v1/8b5b0c3d38ae5d14c913f420.png"},{"id":63016902,"identity":"4a731519-e458-4391-acf4-411dcb355224","added_by":"auto","created_at":"2024-08-22 06:54:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81838,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate Logistic Regression Analysis of the Associations Between Specific uPAHs Exposure and Cancer Types.\u003c/p\u003e\n\u003cp\u003e1) uPAHs=urinary Polycyclic Aromatic Hydrocarbons; 1-OHNap=1-Hydroxynapthalene; 2-OHNap=2-Hydroxynapthalene; 3-OHFlu=3-Hydroxyfluorene; 2-OHFlu=2-Hydroxyfluorene; 3-OHPhe=3-Hydroxyphenanthrene; 1-OHPhe=1-Hydroxyphenanthrene; 2-OHPhe=2-Hydroxyphenanthrene; 1-OHPyr=1-Hydroxypyrene; 9-OHFlu=9-Hydroxyfluorene; 4-OHPhe=4-Hydroxyphenanthrene; OR= Odds Ratio; 95%CI= 95% Confidence Interval.\u003c/p\u003e\n\u003cp\u003e2) Logistic regression analysis was adjusted for age, race, PIR category, level of education, marital status, BMI, smoking status, alcohol consumption, and physical activity.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4800682/v1/236eec89824961b89611a710.png"},{"id":63017967,"identity":"a061573a-3682-49c4-af6b-0adef0a93eb8","added_by":"auto","created_at":"2024-08-22 07:02:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1195243,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4800682/v1/30e95d53-d685-49b4-a660-22cec894cab3.pdf"},{"id":63016901,"identity":"f22f88de-2ef6-4d1c-9c36-05a34d1ed0bd","added_by":"auto","created_at":"2024-08-22 06:54:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16682,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4800682/v1/47bb12b9c1cfbc9e0dbe30c7.docx"},{"id":63016899,"identity":"7c09faee-8d37-4d6d-84d8-146ee3ee97cf","added_by":"auto","created_at":"2024-08-22 06:54:54","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13883,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4800682/v1/5b06a33069eaae82ed2d501d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations between the Exposure of Polycyclic Aromatic Hydrocarbons and the Risk of Cancers Related to Deregulation of Estrogen Receptors: NHANES 2001-2016","fulltext":[{"header":"1. Background","content":"\u003cp\u003ePolycyclic aromatic hydrocarbons (PAHs), which consist of two or more fused aromatic hydrocarbon rings, are one of the most widely distributed persistent organic pollutants (POPs) in our environment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. PAHs originate from both natural and anthropogenic sources, with the latter now being the primary contributors. These man-made sources include the incomplete combustion of organic polymer compounds, petroleum, coal, and wood [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. People are exposed to PAHs mainly by inhalation, ingestion, and direct contact [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Once inside the body, PAHs are metabolized by liver, and subsequently excreted in urine [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, urinary PAHs (uPAHs) metabolites are appropriate bio-markers of PAHs exposure and often used by bio-monitoring investigations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePAHs are typical carcinogenic, teratogenic and mutagenic substances [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The high lipophilicity of PAHs increases the cancer risk and mutagenic risk after exposing to PAHs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Previous epidemiological studies have illustrated that PAHs exposure in occupational environments could increase the risk of various cancers including lung, bladder, skin, breast, and larynx cancers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, PAHs are vital endocrine disrupting chemicals (EDCs). Estrogen receptor signaling is one of the most investigated pathways associated with the endocrine-disrupting abilities of PAHs, involving both estrogen receptors (ERs) and aryl hydrocarbon receptors (AhRs) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, observational studies have demonstrated that EDC which are evidenced to interfere with normal hormone signaling might be associated with the development of malignancies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Generally, cancers related to deregulation of ERs include breast cancer, prostate cancer, ovarian cancer and uterine cancer. Worldwide, breast cancer and prostate cancer are the most commonly diagnosed malignancy in women and men, respectively. Specially, prostate cancer ranks as the sixth leading cause of cancer death among men, while breast cancer is the second most common cause of death from cancer in women. Moreover, ovarian cancer is considered as the most lethal gynecological malignancy in the Western world [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and uterine cancer is the most common cancer of the female reproductive tract in developed countries [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough several studies demonstrated the relationships between PAHs exposure and breast cancer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], they have not assessed the contribution of the exact components of complex PAHs mixtures. Moreover, the association between PAHs exposure and the risk of prostate cancer remains contradictory [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To the best of our knowledge, no previous studies have evaluated the associations between PAH components and the risk of breast and prostate cancers. Our study aims to investigate the impacts of exact components of complex PAHs mixtures on the four types of cancers related to deregulation of ERs.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSample data were obtained from eight National Health and Nutrition Examination Survey (NHANES) cycles (2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016), which is an ongoing program conducted by the\u0026nbsp;Centers for Disease Control\u0026nbsp;(CDC) to assess the exposure of nutrition, environmental chemicals and health status of the US general populations (http://www.cdc.gov/nchs/nhanes.htm).\u0026nbsp;The NHANES surveys include demographic, socioeconomic, dietary, and health-related questions, along with a comprehensive examination component that encompasses medical, physiological measurements, and laboratory tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Exposure Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUrinary monohydroxylated metabolites of PAHs were measured based on laboratory manual procedures. Briefly, urine samples were collected by experienced technicians, labelled, frozen at -20℃\u0026nbsp;or below, and stored on dry ice according to laboratory procedures. uPAHs were examined with isotope dilution gas chromatography/tandem mass spectrometry (GC-MS/MS). Detailed procedures are available on the NHANES website. Ten uPAHs analytes, including 1-hydroxynapthalene\u0026nbsp;(1-OHNap), 2-hydroxynapthalene (2-OHNap), 2-hydroxyfluorene (2-OHFlu), 3-hydroxyfluorene (3-OHFlu), 9-hydroxyfluorene\u0026nbsp;(9-OHFlu), 1-hydroxypyrene (1-OHPyr), 1-hydroxyphenanthrene (1-OHPhe), 2-hydroxyphenanthrene (2-OHPhe), 3-hydroxyphenanthrene (3-OHPhe), and 4-hydroxyphenanthrene (4-OHPhe), were obtained from NHANES 2001-2016. All of the ten analytes were measured in ng/L. Urinary creatinine concentration was used to correct the variability of urinary analytes of PAHs (pg/g). The distribution of uPAHs analytes is listed in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3\u0026nbsp;Outcome Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcome variables for our analysis includes prostate, breast, ovarian and uterine cancer. These outcomes were determined by the participant response on the medical questionnaires: 1) Prostate Cancer (Yes/No), “Have you ever been told you have prostate cancer?”; 2) Breast Cancer (Yes/No), “Have you ever been told you have breast cancer?”; 3) Ovarian Cancer (Yes/No), “Have you ever been told you have ovarian cancer?”; 4) Uterine Cancer (Yes/No), “Have you ever been told you have uterine cancer?”.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4\u0026nbsp;Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCovariates in the present analysis included three parts: demographic variables, lifestyle variables and anthropometric variables. Demographic variables included age, gender, race/ethnicity, level of education, marital status and family income. Physical activity, smoking status and alcohol consumption were categorized as lifestyle variables. Anthropometric variable only contained body mass index (BMI). Age was regarded as a continuous variable While sex was a dichotomous variable. Race/ethnicity was classified into Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race. Family income was calculated as the family poverty-to-income ratio\u0026nbsp;(PIR). BMI was categorized according to World Health Organization cutoffs as lean or normal weight (\u0026lt;25 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25.0-30 kg/m\u003csup\u003e2\u003c/sup\u003e), and obese (\u0026gt;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e). All remaining covariates were categorical variables. Details of the above variables were displayed in Table 1 and Supplemental Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was conducted in accordance with CDC analytical reporting guidelines for complex NHANES data(https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx). A sample weight was assigned to each participant in the NHANES. The present analysis also considered masked variance and applied the recommended weighting methodology. Descriptive analysis was used for exploring demographic characteristics of study participants. The comparison of continuous variables was conducted with Kruscal Whallis H test. Categorical variables were compared with chi-squared test or Fisher’s exact test. Demographic, lifestyle, and anthropometric variables were presented as mean (SD) or frequency (percentage). Mean, Geometric means (GM), and distribution of specific uPAHs were estimated. The exposure of PAHs was analyzed by categorization into tertiles (Tertile 1, Tertile 2 and Tertile 3). Logistic regression model was applied to analyze the associations between specific uPAHs (both as continuous variable and divided into tertiles) and the incidence of the four types of cancers (breast, prostate, ovarian and uterine cancer). Besides, we also placed the each continuous uPAHs variable into the logistic regression model to obtain the p-values for trend. Specially, the logistic regression model was adjusted for age, race, PIR category, level of education, marital status, BMI, smoking status, alcohol consumption, and physical activity. Before conducting logistic regression analysis, the corrected concentrations of uPAHs were subjected to log10 transformation. The results were presented as odds ratio (OR) and 95% confidence interval (CI]. A p-value ≤ 0.05 was considered as statistically significant. All analyses were conducted using the statistical software packages R (http://www.R-project.org; The R Foundation) and Empower Stats (http://www.empower stats.com, X\u0026amp;Y Solutions, Inc.).\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1\u0026nbsp;Characteristics of Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were 102956 participants of NHANES 2001-2016 included in the present study, and 21299 participants were tested for uPAHs and urinary creatinine data. Participants with missing or incomplete questionnaires regarding prostate, breast, ovarian and uterine cancer were excluded. Finally, a total of 13566 participants remained, including 486 participants with any types of cancers related to deregulation of ERs and 13080 without. (Figure 1)\u003c/p\u003e\n\u003cp\u003eTable 1 shows the demographic, lifestyle, and anthropometric characteristics of subjects included in the analysis. The average age (SD) was 48.89 (18.04) years. The majority of participants were non-Hispanic White (45.13%), received education above high school (50.40%), were married or cohabiting (60.70%), had never smoked (54.19%), did not have alcohol consumption (77.16%), and were classified into less than moderate physical activity group (49.13%). Approximately 29.13% of subjects were obese. According to the PIR category, 42.11% of subjects fell into the 1.3-3.5 range. About 1.50%, 1.45%, 0.28%, and 0.41% participants were diagnosed with prostate, breast, ovarian and uterine cancer, respectively. Distributions of uPAHs concentrations are displayed in Table 2. The GM of urinary concentrations for 1-OHNap, 2-OHNap, 2-OHFlu, 3-OHFlu, 9-OHFlu, 1-OHPyr, 1-OHPhe, 2-OHPhe, 3-OHPhe, 4-OHPhe were \u0026nbsp;2332.86\u0026nbsp;ng/L\u0026nbsp;(30.72%), 4161.91 ng/L (54.81%), 272.78 ng/L (3.59%), 108.98 ng/L (1.44%), 306.86 ng/L (4.04%), 99.25 ng/L (1.31%), 129.69 ng/L (1.71%), 65.61 ng/L (0.86%), 89.99 ng/L (1.19%), and 25.29 ng/L (0.33%), respectively. Comparisons of these characteristics between participants with and without any types of cancers related to deregulation of ERs are shown in Supplemental Table 1 and 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2\u0026nbsp;Associations Between Specific uPAHs and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCancers Related to Deregulation of ERs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAssociations between specific uPAHs and various cancer types were presented in Table 3 and Figure 2. As displayed in Table 3, a unit increase in 9-OHFlu was associated with a 139% increase in the odds of breast cancer (p=0.029) [Figure 2B]. While other uPAHs may influence the likelihood of developing prostate, breast, ovarian, or uterine cancer, no significant differences were observed. To further investigate the associations between specific uPAHs and each type of cancers, we conducted tertile analyses [Table 3]. Similarly, there were no significant difference between uPAHs and prostate cancer. However, 9-OHFlu was associated with an increased risk of breast cancer\u0026nbsp;in a dose-response relationship\u0026nbsp;(Tertile 1 vs. Tertile 3, OR [95%CI]: 2.72 [1.36, 5.43], p for trend \u0026lt;0.001). The results also indicated that 1-OHPyr could elevate the risk of breast cancer (Tertile 1 vs. Tertile 2, OR [95%CI]: 1.60 [1.04, 2.47]) though the trend was not significant (p for trend 0.67). As for ovarian cancer and uterine cancer, the results showed that 2-OHNap (Tertile 1 vs. Tertile 2, OR [95%CI]: 0.13 [0.03, 0.61]) and 1-OHPhe (Tertile 1 vs. Tertile 2, OR [95%CI]: 0.33 [0.11, 0.99]) appeared to reduce ovarian cancer risk, whereas 2-OHFlu (Tertile 1 vs. Tertile 2, OR [95%CI]: 2.56 [1.06, 6.16]) might increase the incidence of uterine cancer. However, no significant trends were detected for these associations (p for trend 0.80, 0.50 and 0.15, respectively).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe present study investigated relationships of PAHs exposure and cancers related to deregulation of ERs in the general U.S. population using a nationally-representative sample. Our results illustrated that the potential relevance between uPAHs and each type of cancers varied depending on specific uPAHs and the types of cancer. We observed that 9-OHFlu was positively associated with breast cancer, with a clear dose-dependent relationship. Additionally, 1-OHPyr appeared to increase the risk of breast cancer, while 2-OHFlu was associated with an elevated risk of uterine cancer. Conversely, 2-OHNap and 1-OHPhe might serve as protective factors against ovarian cancer. There might be no significant associations between PAHs exposure and prostate cancer.\u003c/p\u003e\n\u003cp\u003eERs are expressed in cells distributed throughout the female genital tract and breast [17]. In human prostate, ERs were found in both prostate stromal and epithelial cells [19]. As for ER-positive cells, oestrogen could promote DNA instability, cellular hyperplasia and neoplastic transformation of normal epithelial cells into carcinomas after binding to ERs [17]. Furthermore, previous studies have illustrated that the activation of estrogen signaling was associated with carcinogenicity and progression of uterine, breast, ovarian and prostate cancer [17][22]. Estrogen\u0026nbsp;receptor signaling is one of the most investigated pathways related to the endocrine-disrupting abilities of PAHs [18]. Various PAHs were previously reported to be agonist or antagonist of ERs [16], which could be explained in three aspects. Firstly, several investigations demonstrated that PAHs and hydroxyl PAHs had different roles in the estrogenicity [18][20][21]. Secondly, when PAHs bind to AhRs, the activated AhRs could indirectly interfere with ER-responsive trans-activation functions or directly compete with estrogen[18]. Finally, metabolism or bio-accumulation of PAHs varied in different tissues and cells[18]. Additionally, PAHs shown differential actions between ERα and ERβ, which could always play different roles in the estrogen signaling\u0026nbsp;[16]. Therefore, specific PAHs might have different effects on various cancers, and different PAHs might have different effects on specific kind of cancers. This assumption was also supported by the findings of the present study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur results revealed a dose-response relationship between increased concentrations of 9-OHFlu and elevated breast cancer risk. Besides, 1-OHPyr and 2-OHFlu were implicated in the carcinogenicity of breast cancer and uterine cancer, respectively. Previous studies also showed that women exposed to PAHs from multiple sources, such as occupational, ambient air, and smoking, had a higher incidence of breast cancer [13][14][15][23]. F Our current analysis further identified the specific PAHs in the PAHs mixture contributing to the progression of breast cancer. However, there was no epidemic studies to investigate the role of PAHs on uterine cancer. Fortunately, the findings of PAHs administration in animals and cells could support these results. Previous laboratory evidence indicated that both 1-OHPyr and 2-OHFlu showed strong estrogenic activity [24][25]. Although there were no laboratory\u0026nbsp;evidence directly investigating the association between 9-OHFlu and ERs, we hypothesize the 9-OHFlu might show similar estrogenic activity to 2-OHFlu because they were both hydroxyl fluorene (OH-Flu). Additionally, as a kind of aryl hydrocarbon, 9-OHFlu could activated AhRs. promoting the development of breast cancer [27]. Recent research demonstrated that exposure to OH-Flu were associated with lower DNA methylation of AHRR in lung cancer [26]. AHRR, a suppressor of the AhR pathway, has been shown to inhibit AhR-driven breast cancer growth in two different murine models when over-expressed [27]. These findings suggested that 9-OHFlu plays a vital role in the carcinogenicity and progression of breast cancer, and targeting the mechanism of the carcinogenicity of 9-OHFlu might have therapeutic benefits, but further investigation is needed.\u003c/p\u003e\n\u003cp\u003eWe observed that there were no significant relationships between all of the ten uPAHs and risk of prostate cancer. Although part of the ten uPAHs were evidenced as agonist of ERs, high dosage PAHs exposure was related to reduction of serum testosterone (T) concentration and exerted anti-androgenic effects by competing with androgen binding to androgen receptor (AR) [33][34]. According to the reliance of prostate cancer to the AR signaling, the effect of PAHs on T and AR signaling might impair the effect of PAHs on ERs. Besides, gender differences in the genotoxic capabilities of PAHs could exist. Males typically exhibit lower cytochrome P450 (CYP) enzyme activity and greater DNA repair capacity compared to females, making them less susceptible to PAH-induced chromosomal damage and oxidative stress [1][35]. A number of epidemiological studies also investigated the associations between occupational PAHs exposure and prostate cancer [28]. Part of them demonstrated that PAHs exposure was implicated in prostate carcinogenesis in petroleum workers, chimney sweeps and hairdressers [28][29]. However, others demonstrated non-significant elevated risks of prostate cancer associated with occupational exposure to coals and oils [30][31]. Additionally, Rybicki et al. indicated that occupational PAHs exposure increased risk of prostate cancer in men with GSTP1 Val\u003csup\u003e105\u003c/sup\u003e variant, rather than in the entire male population [32]. All in all, more studies are needed to confirm the associations and mechanisms between PAHs and prostate cancer risk.\u003c/p\u003e\n\u003cp\u003eOur results showed that 2-OHNap and 1-OHPhe might be protective factors against ovarian cancer. Previous studies have demonstrated that the elevated risk of ovarian cancer is strongly linked to the activation of Erα\u0026nbsp;[36]. ERβ is always recognized as a vital tumor suppressor in ovarian cancer [37]. Besides, normal ovarian tissue generally contains high level of ERβ, predominantly expressed in granulosa cells, theca cells, surface epithelium and corpus luteum [38]. A\u0026nbsp;laboratory study have indicated that 1-OHNap and 9-OHPhe can selectively induce the transcriptional activity of ERβ\u0026nbsp;without affecting Erα\u0026nbsp;[25].\u0026nbsp;As the similar structures of between 1-OHNap and 2-OHNap, and between 1OHPhe and 9-OHPhe, we hypothesize that 2-OHNap and 1-OHPhe might exert similar effects on ERα and ERβ despite the lack of direct studies on these relationships.\u0026nbsp;Furthermore, using exogenous estrogens as hormone replacement therapy (HRT) in premenopausal women has been associated with a significantly decreased relative risk of ovarian cancer [39]. However, long-term HRT use in post-menopausal women was associated with an elevated risk of ovarian cancer [40], possibly due to a reduction in the total number of ovulations, a major risk factor for ovarian cancer [41]. Consequently, further investigation is warranted into the associations between PAH exposure and ovarian cancer risk, as our study shows no significant trends and few studies have addressed this issue. Our research has several advantages. First, the data we used have external validity and national relevance. Second, the present study includes large sample size, random sample selection, and uniform data collection. Third, the relationships between ten specific PAHs and four types of cancer were investigated from an epidemiological perspective, which could provide possible mechanistic implications for further explorations and clinical translations.\u003c/p\u003e\n\u003cp\u003eHowever, this study also has some limitations. Firstly, the nature of cross-sectional studies makes it unable to draw a causal association between the present results. Fortunately, the laboratory evidence supports the assumption that exposure to part of specific PAHs could elevate the risk of breast and uterine cancer. Second, while we adjusted for some covariates, additional factors such as dietary influences were not considered. Third, NHANES questionnaire data are based on participant self-reported, therefore, there might exist recall bias. Finally, the present study used uPAHs concentrations to present the specific PAHs exposure. Due to individual variations in liver and kidney metabolic capacity, urinary PAHs may affect the assessment of internal PAHs exposure levels. To the best of our knowledge, there were no methods and techniques to detect the markers of PAHs in blood.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eOur study suggests that PAHs exposure was associated with an increased risk of breast cancer in a dose-response relationship, especially with 9-OHFlu. Additionally, PAHs exposure appears to elevate the incidence of uterine cancer while potentially reducing the risk of ovarian cancer. To better understand these associations, future longitudinal studies should aim to identify threshold exposure levels and validate the connections between PAHs and the risks of uterine and ovarian cancers.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eWe declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements None.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding support This work was supported by Postdoctoral Fellowship Program of CPSF (No. GZB20230481), Post doctor Research Fund of West China Hospital, Sichuan University (No. 2024HXBH149, No. 2024HXBH006), National Natural Science Foundation of China (No. 82303773, No. 82303772, No. 82303694), Natural Science Foundation of Sichuan Province (No. 2024NSFSC1908), Key Research and Development Program of Sichuan Province (No. 23ZDYF2836).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e This study was conducted according to the guideline laid down in the Declaration of Helsinki, and all procedures involving study participants were approved by the Institutional Review Board of the National Center for Health Statistics (NCHS). All participants provided written informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors\u003c/strong\u003e YT, YNJ and CWS contributed equally as first authors of this manuscript. YT are responsible for the conception and design of the study. YNJ interpreted the analysis. YT and YNJ were responsible for the acquisition of data. YT and YNJ wrote the first draft of the manuscript and interpreted the data and wrote the final version. All authors critically revised the article for important intellectual content and approved the final version. ZAL and WYJ obtained public funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e All authors have read and approved the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e Sample data were obtained from eight National Health and Nutrition Examination Survey (NHANES) cycles (2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016), which is an ongoing program conducted by the Centers for Disease Control (CDC) to assess the exposure of nutrition, environmental chemicals and health status of the US general populations (http://www.cdc.gov/nchs/nhanes.htm).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSun K, Song Y, He F, et al. A review of human and animals exposure to polycyclic aromatic hydrocarbons: Health risk and adverse effects, photo-induced toxicity and regulating effect of microplastics. 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Chemosphere 2021;276:130211. https://doi.org/10.1016/j.chemosphere.2021.130211\u003c/li\u003e\n \u003cli\u003eJiang RL, Xiao BC, Na YU, et al. Research advance in toxic effects of PAHs on aquatic animals. Mar. Fish. 2014;36:372-383.\u003c/li\u003e\n \u003cli\u003eCampo L, Rossella F, Pavanello S, et al. Urinary profiles to assess polycyclic aromatic hydrocarbons exposure in coke-oven workers. Toxicol. Lett. 2010;192(1):72-78. https://doi.org/10.1016/j.toxlet.2008.12.018\u003c/li\u003e\n \u003cli\u003eMoorthy B, Chu C, Carlin DJ. Polycyclic aromatic hydrocarbons: from metabolism to lung cancer. Toxicol Sci 2015;145(1):5-15. https://doi.org/10.1093/toxsci/kfv040\u003c/li\u003e\n \u003cli\u003eWagner M, Bolm-Audorff U, Hegewald J, et al. Occupational polycyclic aromatic hydrocarbon exposure and risk of larynx cancer: a systematic review and meta-analysis. Occup Environ Med 2015;72(3):226-233. https://doi.org/10.1136/oemed-2014-102317\u003c/li\u003e\n \u003cli\u003eLee DG, Burstyn I, Lai AS, et al. Women\u0026apos;s occupational exposure to polycyclic aromatic hydrocarbons and risk of breast cancer. Occup Environ Med 2019;76(1):22-29. https://doi.org/10.1136/oemed-2018-105261\u003c/li\u003e\n \u003cli\u003eStults WP, Wei Y. Ambient air emissions of polycyclic aromatic hydrocarbons and female breast cancer incidence in US. Med Oncol 2018;35(6):88. https://doi.org/10.1007/s12032-018-1150-3\u003c/li\u003e\n \u003cli\u003eWhite AJ, Bradshaw PT, Herring AH, et al. Exposure to multiple sources of polycyclic aromatic hydrocarbons and breast cancer incidence. Environ Int 2016;89-90:185-192. https://doi.org/10.1016/j.envint.2016.02.009\u003c/li\u003e\n \u003cli\u003eZhang Y, Dong S, Wang H, et al. Biological impact of environmental polycyclic aromatic hydrocarbons (ePAHs) as endocrine disruptors. Environ Pollut 2016;213:809-824. https://doi.org/10.1016/j.envpol.2016.03.050\u003c/li\u003e\n \u003cli\u003eGibson DA, Saunders PT. Endocrine disruption of oestrogen action and female reproductive tract cancers. Endocr Relat Cancer 2014;21(2):T13-T31. https://doi.org/10.1530/ERC-13-0342\u003c/li\u003e\n \u003cli\u003eZhang Y, Dong S, Wang H, et al. Biological impact of environmental polycyclic aromatic hydrocarbons (ePAHs) as endocrine disruptors. Environ Pollut 2016;213:809-824. https://doi.org/10.1016/j.envpol.2016.03.050\u003c/li\u003e\n \u003cli\u003eDi Zazzo E, Galasso G, Giovannelli P, et al. Prostate cancer stem cells: the role of androgen and estrogen receptors. Oncotarget 2016;7(1):193-208. https://doi.org/10.18632/oncotarget.6220\u003c/li\u003e\n \u003cli\u003eOhta R, Takagi A, Ohmukai H, et al. Ovariectomized mouse uterotrophic assay of 36 chemicals. J. Toxicol. Sci. 2012;37(5):879e889. https://doi.org/10.2131/jts.37.879\u003c/li\u003e\n \u003cli\u003eVan de Wiele T, Vanhaecke L, Boeckaert C, et al. Human colon microbiota transform polycyclic aromatic hydrocarbons to estrogenic metabolites. Environ. Health Perspect. 2005;113(1):6e10. https://doi.org/10.1289/ehp.7259\u003c/li\u003e\n \u003cli\u003eBonkhoff H. Estrogen receptor signaling in prostate cancer: Implications for carcinogenesis and tumor progression. Prostate 2018;78(1):2-10. https://doi.org/10.1002/pros.23446\u003c/li\u003e\n \u003cli\u003ePedersen JE, Strandberg-Larsen K, Andersson M, et al. Breast cancer among Danish women occupationally exposed to diesel exhaust and polycyclic aromatic hydrocarbons, 1964-2016. Scand J Work Environ Health 2021;47(2):154-162. https://doi.org/10.5271/sjweh.3923\u003c/li\u003e\n \u003cli\u003eKamiya M, Toriba A, Onoda Y, et al. Evaluation of estrogenic activities of hydroxylated polycyclic aromatic hydrocarbons in cigarette smoke condensate. Food Chem Toxicol 2005;43(7):1017-1027. https://doi.org/10.1016/j.fct.2005.02.004\u003c/li\u003e\n \u003cli\u003eSievers CK, Shanle EK, Bradfield CA, et al. Differential action of monohydroxylated polycyclic aromatic hydrocarbons with estrogen receptors \u0026alpha; and \u0026beta;. Toxicol Sci 2013;132(2):359-367. https://doi.org/10.1093/toxsci/kfs287\u003c/li\u003e\n \u003cli\u003eAlhamdow A, Essig YJ, Krais AM, et al. Fluorene exposure among PAH-exposed workers is associated with epigenetic markers related to lung cancer. Occup Environ Med 2020;77(7):488-495. https://doi.org/10.1136/oemed-2020-106413\u003c/li\u003e\n \u003cli\u003eVogel C, Lazennec G, Kado SY, et al. Targeting the Aryl Hydrocarbon Receptor Signaling Pathway in Breast Cancer Development. Front Immunol 2021;12:625346. https://doi.org/10.3389/fimmu.2021.625346\u003c/li\u003e\n \u003cli\u003eDoolan G, Benke G, Giles G. An update on occupation and prostate cancer. Asian Pac J Cancer Prev 2014;15(2):501-516. https://doi.org/10.7314/apjcp.2014.15.2.501\u003c/li\u003e\n \u003cli\u003ePukkala E, Martinsen JI, Lynge E, et al. Occupation and cancer follow-up of 15 million people in five nordic countries. Acta Oncologica 2009;48(5):646-790. https://doi.org/10.1080/02841860902913546\u003c/li\u003e\n \u003cli\u003eFritschi L, Glass DC, Tabrizi JS, et al. Occupational risk factors for prostate cancer and benign prostatic hyperplasia: a case-control study in Western Australia. Occupational and Environmental Med 2007;64(1):60-5. https://doi.org/10.1136/oem.2006.027706\u003c/li\u003e\n \u003cli\u003eGirschik J, Glass D, Ambrosini GL, et al. Could mining be protective against prostate cancer? A study and literature review. Occupational \u0026amp; Environmental Med 2010;67(6):365-74. https://doi.org/10.1136/oem.2009.047092\u003c/li\u003e\n \u003cli\u003eRybicki BA, Neslund-Dudas C, Nock NL, et al. Prostate cancer risk from occupational exposure to polycyclic aromatic hydrocarbons interacting with the GSTP1 Ile105Val polymorphism. Cancer Detect Prev 2006;30(5):412-422. https://doi.org/10.1016/j.cdp.2006.09.004\u003c/li\u003e\n \u003cli\u003eEvanson M, Van Der Kraak GJ. Stimulatory effects of selected PAHs on testosterone production in goldfish and rainbow trout and possible mechanisms of action. Comp Biochem Physiol C Toxicol Pharmacol 2001;130(2):249-258. https://doi.org/10.1016/s1532-0456(01)00246-0\u003c/li\u003e\n \u003cli\u003eOh S. Disturbance in testosterone production in leydig cells by polycyclic aromatic hydevrepocarbons. Dev Reprod 2014;18(4):187-195. https://doi.org/10.12717/devrep.2014.18.4.187\u003c/li\u003e\n \u003cli\u003eGuo H, Huang K, Zhang X, et al. Women are more susceptible than men to oxidative stress and chromosome damage caused by polycyclic aromatic hydrocarbons exposure. Environ. Mol. Mutagen. 2014;55(6):472-481. https://doi.org/10.1002/em.21866\u003c/li\u003e\n \u003cli\u003eLangdon SP, Herrington CS, Hollis RL, et al. Estrogen Signaling and Its Potential as a Target for Therapy in Ovarian Cancer. Cancers (Basel) 2020;12(6):1647. https://doi.org/10.3390/cancers12061647\u003c/li\u003e\n \u003cli\u003eLee J-Y, Kim HS, Song Y-S. Genistein as a Potential Anticancer Agent against Ovarian Cancer. J. Tradit. Complement. Med. 2011;2(2):96-104. https://doi.org/10.1016/s2225-4110(16)30082-7\u003c/li\u003e\n \u003cli\u003eDrummond AE, Fuller PJ. The importance of ER beta signalling in the ovary. Endocrinology 2010;205(1):15-23. https://doi.org/10.1677/JOE-09-0379\u003c/li\u003e\n \u003cli\u003eRisch HA. Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone. J. Natl. Cancer Inst. 1998;90(23):1774-1786. https://doi.org/10.1093/jnci/90.23.1774\u003c/li\u003e\n \u003cli\u003eBeral V, Gaitskell K, Hermon C, et al. Menopausal hormone use and ovarian cancer risk: Individual participant meta-analysis of 52 epidemiological studies. Lancet 2015;385(9980):1835-1842. https://doi.org/10.1016/S0140-6736(14)61687-1\u003c/li\u003e\n \u003cli\u003eTrabert B, Tworoger SS, O\u0026rsquo;Brien KM, et al. The Risk of Ovarian Cancer Increases with an Increase in the Lifetime Number of Ovulatory Cycles: An Analysis from the Ovarian Cancer Cohort Consortium (OC3). Cancer Res 2020;80(5):1210-1218. https://doi.org/10.1158/0008-5472.CAN-19-2850\u003c/li\u003e\n \u003cli\u003eBray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018:68(6):394-424. https://doi.org/10.3322/caac.21492\u003c/li\u003e\n \u003cli\u003eColombo N. Creutzberg C, Amant F, et al. ESMO-ESGO-ESTRO consensus conference on endometrial cancer: diagnosis, treatment and follow-up. Ann Oncol. 2016;27(1):16-41. https://doi.org/10.1093/annonc/mdv484\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. General Characteristics of Participants Analyzed, NHANES 2001-2016.\u003c/p\u003e\n\u003cp\u003eNHABES= National Health and Nutrition Examination Survey; SD=Standard Deviation; n=Numbers of Participants; %=Weighted Percentage; BMI=Body Mass Index; PIR=Income-to-Poverty Ratio.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"463\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003eParticipants \u003cstrong\u003e(n = 13566)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years, mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e48.89\u0026plusmn;18.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e6657 (49.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e6909 (50.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Mexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e2314 (17.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e1123 (8.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Non-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e6122 (45.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Non-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e2809 (20.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Other Race\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e1198 (8.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Under high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e3586 (26.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;High school or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e3143 (23.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Above high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e6837 (50.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Married/cohabiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e8235 (60.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Living alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e5331 (39.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026lt;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e4075 (30.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;25-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e4704 (34.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026gt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e4787 (35.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePIR category\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026lt;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e3902 (28.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1.3-3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e5712 (42.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026gt;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e3952 (29.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking Status\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e7352 (54.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e3865 (28.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;current\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e2349 (17.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical Activity\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Less than moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e6665 (49.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e2163 (15.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Vigorous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e4738 (34.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econsump\u003c/strong\u003e\u003cstrong\u003etion\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e10468 (77.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e1112 (8.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Heavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e1986 (14.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProstate Cancer, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e13362 (98.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e204 (1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreast Cancer, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e13369 (98.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e197 (1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOvarian Cancer, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e13528 (99.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e38 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUterine Cancer, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e13511 (99.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.172786177105834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.827213822894166%\" valign=\"top\"\u003e\n \u003cp\u003e55 (0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2.\u0026nbsp;Distribution of uPAHs Levels Among Participants, NHANES 2001-2016.\u003c/p\u003e\n\u003cp\u003e1-OHNap=1-Hydroxynapthalene; 2-OHNap=2-Hydroxynapthalene; 3-OHFlu=3-Hydroxyfluorene; 2-OHFlu=2-Hydroxyfluorene; 3-OHPhe=3-Hydroxyphenanthrene; 1-OHPhe=1-Hydroxyphenanthrene; 2-OHPhe=2-Hydroxyphenanthrene; 1-OHPyr=1-Hydroxypyrene; 9-OHFlu=9-Hydroxyfluorene; 4-OHPhe=4-Hydroxyphenanthrene; SD=Standard Deviation; GM=Geometric Means; 95%CI= 95% Confidence Interval; uPAHs=urinary Polycyclic Aromatic Hydrocarbons.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"108%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003euPAHs (\u003c/strong\u003e\u003cstrong\u003emean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGM (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e25%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e50%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e75%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e90%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003csup\u003eth\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1-OHNap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e5732.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e2332.86\u0026nbsp;(2272.26 2395.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e1886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e6447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e18047.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e30812.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e35920000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e2-OHNap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e6765.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e4161.91\u0026nbsp;(4076.60 4249.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e550.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e1768.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e4142.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e9981.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e20576.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e30024.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e590676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e3-OHFlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e241.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e108.98\u0026nbsp;(106.43 111.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e21.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e86.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e260.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e916.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e1531.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e23854.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e2-OHFlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e481.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e272.78\u0026nbsp;(267.10 278.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e115.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e599.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e1630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e2570.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e21700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e3-OHPhe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e128.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e89.99\u0026nbsp;(88.05 91.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e43.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\" valign=\"top\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e361.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e556.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e126202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1-OHPhe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e168.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e129.69\u0026nbsp;(127.58 131.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e434.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e612.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e13743\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e2-OHPhe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e86.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e65.51\u0026nbsp;(64.19 66.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e12.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\"\u003e\n \u003cp\u003e18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e234.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e334.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e6355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e1-OHPyr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e152.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e99.25\u0026nbsp;(97.38 101.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e49.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e21710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e9-OHFlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e443.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e306.86\u0026nbsp;(299.72 314.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e145.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e301.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e628.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e1210.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e1861.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e65656.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.829787234042554%\" valign=\"top\"\u003e\n \u003cp\u003e4-OHPhe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\" valign=\"top\"\u003e\n \u003cp\u003e35.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.085106382978722%\" valign=\"top\"\u003e\n \u003cp\u003e25.29\u0026nbsp;(24.54 26.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.319148936170213%\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.382978723404255%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e50.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.446808510638298%\"\u003e\n \u003cp\u003e2235.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3.\u0026nbsp;Multivariate Logistic Regression\u0026nbsp;Analysis\u0026nbsp;of the Associations Between Specific uPAHs Exposure and Cancer Types.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003euPAHs=urinary Polycyclic Aromatic Hydrocarbons; 1-OHNap=1-Hydroxynapthalene; 2-OHNap=2-Hydroxynapthalene; 3-OHFlu=3-Hydroxyfluorene; 2-OHFlu=2-Hydroxyfluorene; 3-OHPhe=3-Hydroxyphenanthrene; 1-OHPhe=1-Hydroxyphenanthrene; 2-OHPhe=2-Hydroxyphenanthrene; 1-OHPyr=1-Hydroxypyrene; 9-OHFlu=9-Hydroxyfluorene; 4-OHPhe=4-Hydroxyphenanthrene; OR= Odds Ratio; 95%CI= 95% Confidence Interval.\u003c/li\u003e\n \u003cli\u003eLogistic regression analysis was adjusted for age, race, PIR category, level of education, marital status, BMI, smoking status, alcohol consumption, and physical activity.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1071\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.15032679738562%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003euPAHs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.03548085901027%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eProstate Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.942110177404295%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreast Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.782446311858077%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOvarian Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.089635854341736%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUterine Cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.811088295687885%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.41889117043121%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.91375770020534%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.316221765913758%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.91375770020534%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.137577002053389%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.248459958932237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.240246406570842%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep for trend\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-\u003c/strong\u003e\u003cstrong\u003eOHNap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.96 (0.58, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.38 (0.81, 2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.03 (0.32, 3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.54 (0.21, 1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.52, 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.60, 1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.65 (0.51, 5.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.25 (0.53, 2.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-\u003c/strong\u003e\u003cstrong\u003eOHNap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.99 (0.63, 1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.68 (0.42, 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.13 (0.03, 0.61)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.42, 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.90 (0.51, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.64 (0.38, 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.33, 2.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.67 (0.26, 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3-\u003c/strong\u003e\u003cstrong\u003eOHFlu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.59, 1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.02 (0.66, 1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.56 (0.21, 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.72 (0.80, 3.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.11 (0.66, 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.96 (0.54, 1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.15, 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.15 (0.44, 3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-\u003c/strong\u003e\u003cstrong\u003eOHFlu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.55, 1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.68, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.57 (0.22, 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.56 (1.06, 6.16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.88 (0.53, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.55, 1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.16, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e2.03 (0.76, 5.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3-\u003c/strong\u003e\u003cstrong\u003eOHPhe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.08 (0.62, 1.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.38 (0.79, 2.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.38 (0.09, 1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.50 (0.62, 3.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.54, 1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.41 (0.75, 2.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.34 (0.38, 4.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.59 (0.17, 2.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-\u003c/strong\u003e\u003cstrong\u003eOHPhe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.32 (0.83, 2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.42 (0.86, 2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33 (0.11, 0.99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.77 (0.70, 4.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.19 (0.72, 1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.03 (0.62, 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.70 (0.28, 1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.63 (0.65, 4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-\u003c/strong\u003e\u003cstrong\u003eOHPhe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.31 (0.75, 2.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.26 (0.71, 2.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.01 (0.28, 3.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e2.10 (0.73, 6.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.50, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.49 (0.81, 2.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.23 (0.29, 5.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.62 (0.53, 4.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-\u003c/strong\u003e\u003cstrong\u003eOHPyr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.19 (0.77, 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.60 (1.04, 2.47)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.43 (0.15, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.28 (0.58, 2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.23 (0.72, 2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.41, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.12 (0.41, 3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.29 (0.52, 3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e9-\u003c/strong\u003e\u003cstrong\u003eOHFlu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.14 (0.63, 2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.87 (0.96, 3.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.60 (0.41, 6.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.35 (0.44, 4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e0.92 (0.48, 1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.72 (1.36, 5.43)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.85 (0.42, 8.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.10 (0.35, 3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4-\u003c/strong\u003e\u003cstrong\u003eOHPhe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.44 (0.57, 3.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.65 (0.27, 1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.002 (0.00, 3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.55 (0.10, 3.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.14179104477612%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Tertile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.365671641791044%\" valign=\"top\"\u003e\n \u003cp\u003e1.63 (0.58, 4.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.649253731343284%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.78 (0.28, 2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5559701492537314%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.458955223880597%\" valign=\"top\"\u003e\n \u003cp\u003e0.29 (0.006, 13.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.302238805970148%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.671641791044776%\" valign=\"top\"\u003e\n \u003cp\u003e0.43 (0.06, 2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.395522388059701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Polycyclic Aromatic Hydrocarbons, Estrogen Receptors, Cancers","lastPublishedDoi":"10.21203/rs.3.rs-4800682/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4800682/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Estrogen receptor signaling is one of the most investigated pathways that associates with the endocrine-disrupting abilities of polycyclic aromatic hydrocarbons (PAHs). This study we aimed to investigate the relationships between specific PAHs exposure and cancers associated with estrogen receptor (ER) deregulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a cross-sectional analysis of National Health and Nutrition Examination Survey (NHANES) 2001-2016 data. A history of the four types of cancers related to ERs deregulation (prostate, breast, uterine and ovarian cancer) was obtained by self-report. Exposure of PAHs was assessed by measuring ten urinary PAH metabolites. Logistic regression models were fitted to estimate the associations between specific urinary PAHs (uPAHs) and each type of cancers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eExposure to certain uPAHs metabolites was linked to an increased risk of breast, uterine, and ovarian cancers. Notably, 9-hydroxyfluorene (9-OHFlu) demonstrated a dose-response relationship with elevated breast cancer risk (OR [95%CI]: 2.39 [1.09, 5.23], p for trend \u0026lt;0.001). \u0026nbsp;Tertile analyses indicated that 2-Hydroxyfluorene (2-OHFlu) and 1-Hydroxypyrene (1-OHPyr) might increase the risk of breast and uterine cancer, respectively. Conversely, 2-Hydroxynapthalene (2-OHNap) and 1-Hydroxyphenanthrene (1-OHPhe) might be protect factors of ovarian cancer. No significant associations were found between the ten uPAHs metabolites and prostate cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur study suggested that PAHs exposure was associated with an increased risk of breast cancer, particularly 9-OHFlu, in a dose-response manner. Additionally, PAHs exposure might increase the incidence of uterine cancer but decrease the risk of ovarian cancer.\u003c/p\u003e","manuscriptTitle":"Associations between the Exposure of Polycyclic Aromatic Hydrocarbons and the Risk of Cancers Related to Deregulation of Estrogen Receptors: NHANES 2001-2016","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-22 06:54:49","doi":"10.21203/rs.3.rs-4800682/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-11T20:22:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-10T17:05:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9991958010946642769902406229111851545","date":"2025-03-04T10:35:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-03T15:05:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46901457724860719643531699231288022362","date":"2025-02-20T05:11:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185446301650335954332517270726780445715","date":"2025-02-12T12:45:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-19T15:20:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-29T06:30:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-26T08:10:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-26T08:09:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-07-25T09:29:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4f793f07-c2a8-4808-a97b-07baea62b1c0","owner":[],"postedDate":"August 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-11T05:38:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-22 06:54:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4800682","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4800682","identity":"rs-4800682","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}