Association of Fetal Macrosomia and higher Blood Cadmium level among PFAS exposure participant from NHANES 2017-2018

Association of Fetal Macrosomia and higher Blood Cadmium level among PFAS exposure participant from NHANES 2017-2018 | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association of Fetal Macrosomia and higher Blood Cadmium level among PFAS exposure participant from NHANES 2017-2018 Rezaul Karim Ripon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4554990/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Concern about potential reproductive health effects has arisen from the interaction between environmental contaminants such as perfluoroalkyl substances (PFAS) and blood cadmium levels. Exposure to PFAS above the limit of detection impacts the reproductive health of people with elevated blood cadmium levels. Objective: To analyze the relationship between blood cadmium levels and different reproductive health outcomes in a large cohort exposed to PFAS above the limits of detection, considering sociodemographic factors and reproductive history. Methods: A community-based cross-sectional study was conducted among 143M NHANES participants from 2017-2018. Descriptive statistics for PFAS exposure were analyzed and bivariate and adjusted regression analyzes were used to evaluate the relationship between blood cadmium levels and reproductive health outcomes. Age, race, educational level, marital status, income-poverty ratio, and reproductive history were variables considered in the analysis. Results: 16% of participants whose PFAS and blood cd are above the detection limit showed fetal macrosomia. Participants with higher educational levels, particularly college graduates or higher, showed higher odds of experiencing detrimental Blood cadmium above the detection limit (aOR = 1.131, 95% CI: 1.008-1.269, p = 0.0355). Furthermore, people who had never been married were significantly more likely (aOR = 1.305, 95% CI: 1.122-1.518, p = 0.0006), and fetal macrosomia was significantly more likely (aOR = 1.065, 95% CI: 1.007-1.126, p = 0.0285) whose blood cd level is higher. Conclusion : The results highlight the importance of considering sociodemographic factors when it comes to environmental exposures and their effects on reproductive health. To inform public health interventions aimed at reducing the negative effects of environmental pollutants on reproductive health, future research should further investigate these relationships. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Health sciences/Medical research Health sciences/Risk factors Fatal Macrosomia PFAS Cadmium Figures Figure 1 Introduction While cadmium is a toxic heavy metal linked to metabolic alterations, PFAS are persistent environmental pollutants known for their endocrine-disrupting properties (Genchi et al., 2020a)(Genchi et al., 2020). The two contaminants have the potential to cause oxidative stress and inflammation, which could impact the growth and development of the fetus(Sunderland et al., 2019) (Genchi et al., 2020b). The aim of this study is to evaluate the levels of cadmium and PFAS in maternal blood, investigate how they relate to fetal macrosomia. These partnerships are essential for public health because they can help policies reduce harmful exposures and improve maternal and child health outcomes.Current research has identified several key points regarding the relationship between PFAS exposure and fetal macrosomia and higher blood cadmium levels. PFAS are widely recognized as persistent environmental pollutants with endocrine disrupting characteristics, which can disrupt hormonal systems, affecting fetal development and growth(Rickard et al., 2023). Maternal exposure to PFAS can cause adverse birth outcomes, such as low birth weight and preterm birth, according to previous studies, although the relationship with fetal macrosomia has been less investigated. Fetal growth can be affected by metabolic alterations and oxidative stress caused by cadmium, a toxic heavy metal(Wai et al., 2017). Higher blood cadmium levels in pregnant women have been shown to have negative effects on the health of the fetus, but its specific role in contributing to fetal macrosomia has not yet been investigated. Additionally, there is increasing evidence to suggest that combined exposure to environmental contaminants such as PFAS and cadmium may have synergistic effects, increasing the risk of adverse birth outcomes(Wai et al., 2017). To develop public health interventions that protect maternal and fetal health, it is essential to understand these interactions. Despite existing knowledge, several aspects of the association between PFAS exposure and fetal macrosomia and higher blood cadmium levels remain unknown. The specific mechanisms by which cadmium and PFAS individually or together contribute to fetal macrosomia have not yet been fully understood. There has been little research directly linking combined exposure to PFAS and cadmium with an increased risk of fetal macrosomia, and how these environmental contaminants interact to affect fetal growth has not been thoroughly investigated. Furthermore, the role of potential confounding factors, such as genetic predisposition, nutritional status, and other environmental exposures, in modulating the effects of PFAS and cadmium on fetal macrosomia is not well established. Additional research is needed on the variability of PFAS and cadmium exposure levels in different populations and their differential influence on fetal outcomes. To understand the complex interactions between environmental pollutants and fetal health, it is necessary to understand these gaps. Ultimately, this will help establish more effective public health policies and interventions. Understanding the relationship between fetal macrosomia and blood cadmium levels during PFAS exposure is critical for several reasons. Fetal macrosomia endangers the health of the mother and child, including birth complications and long-term health problems(Wai et al., 2017). Prevention strategies can be developed by investigating this association. Although both cadmium and PFAS are known contaminants, the effects of both on fetal growth are poorly understood. Investigation of these interactions can inform targeted public health interventions and regulatory policies that will protect pregnant women and developing fetuses from harmful exposures and improve overall maternal and child health outcomes. The research investigates how exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS), higher levels of cadmium in the blood, and the occurrence of fetal macrosomia, a condition in which a newborn has excessive birth weight, may be linked. Methodology Definition of Fetal macrosomia: We used the RHQ172 variable, which asks whether any of the respondent's births resulted in a baby weighing 9 pounds (4082 grams) or more at birth, to identify fetal macrosomia in the data set. The occurrence of fetal macrosomia is indicated with a response coded '1' (Yes). This variable allows for the direct identification of macrosomia cases in the data set, allowing us to filter and analyze these particular cases. Additionally, the variable RHD173, which records the age at which the respondent gave birth to a baby weighing 9 pounds or more, may provide more context for these cases. Statistical Analysis: A dataset from the NHANES database for 2017 and 2018 is loaded into R. These datasets include demographic data, medical questionnaires, drug use, and other health-related data. To create a complete data set containing all relevant variables, individual data tables are combined using SEQN(NHANES, 2021a). To facilitate the analysis, missing values are addressed, and categorical variables are converted to factor variables. The svydesign function of the survey package is used to create a survey design object by specifying IDs, strata, and weights. This object is then used in all survey-related analyses to account for the complex NHANES survey design. Weighted descriptive statistics are calculated to understand the distribution and traits of the study variables(NHANES, 2021b). The tbl_svysummary function is used for categorical and continuous variables, and a weighted bivariate analysis is performed to examine the relationships between various factors and health outcomes. Logistic regression models have been created to investigate how multiple predictors are related to the outcome variable. This includes models for health behavior, demographic variables, and other relevant factors. To assess the strength and significance of associations in the models, adjusted odds ratios, confidence intervals, and p values (<0.05) are calculated for each predictor. Results This table provides descriptive statistics for individuals with PFAS exposure above the detection level, summarizing various demographic and health-related variables for a total sample size of 14,368,694. The median age is 42 years, with an interquartile range (IQR) of 33 to 52 years. The racial composition includes 12% Mexican American, 6.5% Other Hispanic, 57% Non-Hispanic White, 12% Non-Hispanic Black, and 13% Other Race - Including Multi-Racial, indicating the majority are Non-Hispanic Whites. Health-related variables show 13% had a hysterectomy, 8% saw a doctor due to infertility, 9% were diagnosed with diabetes during pregnancy, and 16% had babies weighing 9 lbs or more. Additionally, 89% have blood cadmium levels at or above the detection limit [Table :1]. Individuals above the detection limit are generally older (median age 42 vs. 39 years). A higher percentage of Non-Hispanic Blacks (12% vs. 9.7%) and Other Races (14% vs. 7.7%) are above the detection limit, whereas Non-Hispanic Whites are more represented below the detection limit (56% vs. 60%). A higher percentage of individuals above the detection limit have seen a doctor due to infertility issues (9.8% vs. 1.5%). More individuals below the detection limit have been diagnosed with diabetes during pregnancy (10% vs. 8.6%) and are categorized as borderline diabetic (2.5% vs. 0.4%). A higher percentage of individuals above the detection limit have experienced fetal macrosomia (17% vs. 10%) [Table :2]. Individuals with a college degree or higher have a 13.1% [AOR (95% CI, P value): 1.131(1.008–1.269, 0.0355)] higher odds of having PFAS above detection limit compared to those with less than a 9th-grade education. Individuals who have never married have 30.5% higher odds [AOR (95% CI, P value): 1.305(1.122–1.518, 0.0005)] of having the PFAS above the detection limit compared to single individuals. Individuals with a history of fetal macrosomia have 6.5% higher odds [AOR (95% CI, P value): 1.065 (1.007–1.126, 0.0285)] of having the PFAS above detection limit compared to those without fetal macrosomia [Table :3][Figure 1 ]. Discussion The main finding is that, among people exposed to PFAS above the limit of detection, there is a significant correlation between elevated blood cadmium levels and the occurrence of fetal macrosomia. Notably, fetal macrosomia occurred in 16% of participants with elevated blood levels of PFAS and cadmium. Additionally, the study found that having higher educational levels and never having been married were related to a higher likelihood of having blood cadmium levels above the limit of detection. These findings highlight the need to take sociodemographic factors into account when assessing exposure to environmental contaminants and their effects on reproductive health, highlighting the need for targeted public health interventions to reduce these risks. Having higher levels of education and never having been married were correlated with a higher likelihood of having elevated blood cadmium levels. These results make it essential to take sociodemographic factors into account when evaluating the health effects of environmental pollutants. The findings emphasize the need for targeted public health interventions and policies to reduce exposure to PFAS and cadmium, which will reduce harmful effects on reproductive health and improve maternal and child health. Studies have found a connection between PFAS and adverse birth outcomes, but the connection with fetal macrosomia has been less investigated (Manzano-Salgado et al., 2017 ; Preston et al., 2020 ; Wai et al., 2017 ). 16% of participants in this study who had elevated levels of PFAS and cadmium had fetal macrosomia, supporting findings that cadmium can cause oxidative stress and disrupt metabolic processes, affecting fetal development (Genchi et al., 2020b ; Wai et al., 2017 ). Additionally, the study found that sociodemographic factors, such as higher educational levels and never being married, were related to higher cadmium levels. These findings reflect trends observed in other research and emphasize the importance of including social determinants in environmental health assessments. Fetal macrosomia is associated with an increased risk of birth complications, such as prolonged labor, cesarean delivery, and birth injuries (Preston et al., 2020 ; Wai et al., 2017 ). Macrosomia can cause hypoglycemia, obesity, and metabolic syndrome later in life for babies (Wai et al., 2017 ). The study's identification of a link emphasizes the importance of monitoring and managing exposure to environmental contaminants in pregnant women. When evaluating the risk profiles of pregnant patients, clinicians should consider these environmental factors and provide guidance on how to reduce exposure to harmful substances. This could result in better prenatal care, better maternal and fetal health outcomes, and information on public health policies aimed at reducing exposure to environmental toxins. There are several limitations to the study. First, its cross-sectional design precludes causality between exposure to PFAS and cadmium and the occurrence of fetal macrosomia. Second, there may be residual confounders that are not fully accounted for. These include genetic characteristics, detailed nutritional information, and other environmental exposures. Third, the study relies on self-reported reproductive histories, which could cause biases and inaccuracies in recall. The findings could also be affected by measurement errors when assessing blood levels of cadmium and PFAS. The study population may not fully represent all demographic groups, limiting the generalizability of the results. Future research should focus on longitudinal studies to establish causal relationships and uncover the mechanisms underlying the relationships between environmental exposures and fetal macrosomia. Genetic, nutritional, and other environmental exposures are some of the potential confounding factors that future research should also take into account. To increase accuracy, there is a need to improve measurement techniques for both exposure and health outcomes. Expanding the research to diverse populations will help generalize the findings and inform specific public health interventions. A deeper understanding of the impact of environmental contaminants on reproductive health will develop through these efforts. They will also guide policies to protect maternal and fetal well-being. Declarations Acknowledgements None Contributions R.R.: Methodology, Formal analysis, Review and editing. Ethics declarations Competing interests The author declares no competing interests. Data Availability Statement The data are available here: https://www.cdc.gov/nchs/nhanes/index.htm References Genchi, G., Sinicropi, M. S., Lauria, G., Carocci, A., & Catalano, A. (2020a). The effects of cadmium toxicity. In International Journal of Environmental Research and Public Health (Vol. 17, Issue 11). MDPI AG. https://doi.org/10.3390/ijerph17113782 Genchi, G., Sinicropi, M. S., Lauria, G., Carocci, A., & Catalano, A. (2020b). The effects of cadmium toxicity. In International Journal of Environmental Research and Public Health (Vol. 17, Issue 11). MDPI AG. https://doi.org/10.3390/ijerph17113782 Manzano-Salgado, C. B., Casas, M., Lopez-Espinosa, M. J., Ballester, F., Iñiguez, C., Martinez, D., Costa, O., Santa-Marina, L., Pereda-Pereda, E., Schettgen, T., Sunyer, J., & Vrijheid, M. (2017). Prenatal exposure to perfluoroalkyl substances and birth outcomes in a Spanish birth cohort. Environment International, 108 , 278–284. https://doi.org/10.1016/j.envint.2017.09.006 NHANES. (2021a). NHANES Tutorials - Weighting Module . https://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx NHANES. (2021b). NHANES Tutorials - Weighting Module . https://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx Preston, E. V., Webster, T. F., Claus Henn, B., McClean, M. D., Gennings, C., Oken, E., Rifas-Shiman, S. L., Pearce, E. N., Calafat, A. M., Fleisch, A. F., & Sagiv, S. K. (2020). Prenatal exposure to per- and polyfluoroalkyl substances and maternal and neonatal thyroid function in the Project Viva Cohort: A mixtures approach. Environment International , 139 . https://doi.org/10.1016/j.envint.2020.105728 Rickard, B. P., Overchuk, M., Tulino, J., Tan, X., Ligler, F. S., Bae-Jump, V. L., Fenton, S. E., & Rizvi, I. (2023). Exposure to select PFAS and PFAS mixtures alters response to platinum-based chemotherapy in endometrial cancer cell lines. Environmental Health: A Global Access Science Source, 22 (1). https://doi.org/10.1186/s12940-023-01034-2 Sunderland, E. M., Hu, X. C., Dassuncao, C., Tokranov, A. K., Wagner, C. C., & Allen, J. G. (2019). A review of the pathways of human exposure to poly- and perfluoroalkyl substances (PFASs) and present understanding of health effects. In Journal of Exposure Science and Environmental Epidemiology (Vol. 29, Issue 2, pp. 131–147). Nature Publishing Group. https://doi.org/10.1038/s41370-018-0094-1 Wai, K. M., Mar, O., Kosaka, S., Umemura, M., & Watanabe, C. (2017). Prenatal heavy metal exposure and adverse birth outcomes in Myanmar: A birth-cohort study. International Journal of Environmental Research and Public Health, 14 (11). https://doi.org/10.3390/ijerph14111339 Tables Table:1 Descriptive statistics among PFAS Exposed above detection level Variable N = 14,368,694 1 Age in year 42 (33, 52) Races Mexican American 1,761,203 (12%) Other Hispanic 931,033 (6.5%) Non-Hispanic White 8,211,933 (57%) Non-Hispanic Black 1,657,556 (12%) Other Race - Including Multi-Racial 1,806,969 (13%) Education level Less than 9th grade 516,293 (3.6%) 9-11th grade (Includes 12th grade with no diploma) 1,450,878 (10%) High school graduate/GED or equivalent 3,649,031 (25%) Some college or AA degree 5,256,349 (37%) College graduate or above 3,477,213 (24%) Marital status Married 7,874,192 (55%) Widowed 275,333 (1.9%) Divorced 1,682,475 (12%) Separated 758,675 (5.3%) Never married 1,953,806 (14%) Living with partner 1,805,282 (13%) Had a hysterectomy? Yes 1,808,548 (13%) No 12,560,146 (87%) Seen a DR b/c unable to become pregnant? Yes 1,152,258 (8.0%) No 13,216,435 (92%) During pregnancy, told you have diabetes Yes 1,294,115 (9.0%) No 12,957,839 (90%) Boarderline 116,740 (0.8%) Fatal macrosomia? Yes 2,252,405 (16%) No 12,116,289 (84%) Cadmium level At or above the detection limit 12,758,794 (89%) Below lower detection limit 1,609,900 (11%) 1 Median (IQR); n (%) Table 2: Bivariable analysis among blood cadmium and PFAS exposure above the detection limit Variable Above Detection limit, N = 11,272,970 1 Below the Detection limit, N = 3,095,724 1 Age in year 42 (34, 52) 39 (26, 48) Races Mexican American 1,325,735 (12%) 435,469 (14%) Other Hispanic 681,393 (6.0%) 249,640 (8.1%) Non-Hispanic White 6,339,471 (56%) 1,872,462 (60%) Non-Hispanic Black 1,358,173 (12%) 299,382 (9.7%) Other Race - Including Multi-Racial 1,568,198 (14%) 238,772 (7.7%) Education level Less than 9th grade 280,802 (2.5%) 235,490 (7.6%) 9-11th grade (Includes 12th grade with no diploma) 1,345,853 (12%) 105,025 (3.4%) High school graduate/GED or equivalent 2,534,970 (22%) 1,114,061 (36%) Some college or AA degree 4,249,520 (38%) 1,006,829 (33%) College graduate or above 2,842,894 (25%) 634,319 (20%) Marital status Married 6,257,361 (56%) 1,616,831 (52%) Widowed 238,580 (2.1%) 36,754 (1.2%) Divorced 1,314,945 (12%) 367,530 (12%) Separated 638,294 (5.7%) 120,381 (3.9%) Never married 1,241,917 (11%) 711,889 (23%) Living with partner 1,562,943 (14%) 242,339 (7.8%) Ratio of family income to poverty; 2.44 (1.35, 4.74) 1.83 (1.21, 3.74) Had a hysterectomy? Yes 1,393,031 (12%) 415,516 (13%) No 9,879,938 (88%) 2,680,208 (87%) Seen a DR b/c unable to become pregnant? Yes 1,105,342 (9.8%) 46,916 (1.5%) No 10,167,627 (90%) 3,048,808 (98%) During pregnancy, told you have diabetes Yes 970,627 (8.6%) 323,488 (10%) No 10,262,223 (91%) 2,695,616 (87%) Borderline 40,120 (0.4%) 76,620 (2.5%) Fetal macrosomia Yes 1,932,095 (17%) 320,309 (10%) No 9,340,874 (83%) 2,775,415 (90%) 1 Median (IQR); n (%) Table 3: Adjusted regression analysis among blood cadmium and PFAS exposure above the detection limit with health conditions. Predictors aOdds Ratio 95% CI Lower 95% CI Upper P-value Age in Year 0.996 0.989 1.002 0.144 Races Other Hispanic 0.922 0.858 0.99 0.0255 Non-Hispanic White 1.007 0.933 1.087 0.86 Non-Hispanic Black 0.941 0.864 1.026 0.171 Other Race - Including Multi-Racial 0.997 0.887 1.121 0.964 Mexican American Ref Ref Ref Ref Education Level 9-11th grade 1.01 0.932 1.095 0.804 High school graduate/GED 1.091 0.963 1.237 0.171 Some college or AA degree 1.059 0.968 1.159 0.212 College graduate or above 1.131 1.008 1.269 0.0355 Less than 9th grade Ref Ref Ref Ref Marital Status Widowed 1.003 0.898 1.12 0.961 Divorced 1.089 1.029 1.152 0.003 Separated 1.001 0.923 1.085 0.981 Never married 1.305 1.122 1.518 0.0005 Living with partner 1.028 0.898 1.177 0.691 Single Ref Ref Ref Ref Ratio of family income to poverty; 1.005 0.977 1.034 0.72 Had a hysterectomy? Yes 1.014 0.955 1.075 0.655 No Ref Ref Ref Ref Seen a DR b/c unable to become pregnant? Yes 1.021 0.916 1.138 0.71 No Ref Ref Ref Ref During pregnancy, told you have diabetes Yes 1.062 0.996 1.132 0.0677 No 0.987 0.839 1.16 0.87 Borderline Ref Ref Ref Ref Fetal macrosomia Yes 1.065 1.007 1.126 0.0285 No Ref Ref Ref Ref Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4554990","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":365140410,"identity":"68a7dbb0-4c44-4808-86c1-65e73cc9f45f","order_by":0,"name":"Rezaul Karim Ripon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACxgYgYZPAwMDDwAwVMmBgYCOoJY0kLWBwmAQt5rMPtz34uON8nvzs3gPMBTX3EvtnH97A8KHsME4tMucS2w1nnrldbHDnXALzjGPFiTPOpRUwzjiHW4sED2ObNG/b7cQNEjkGzDxsCcYMZ3gMmHnbCGo5lzh/BkjLvwRjeZCWv4S1HEhsuJEDMjxBzgCkhRG/FqBf2pITN9w5Y3CYty9BzvAMW8HBnnPpeLSwP3vwsc0ucf7sHsPHPN8SeOTOMG988KPMGqcWBngUSDAwHIAJHcCuEouWUTAKRsEoGAVYAQDXn1J94Iu+yQAAAABJRU5ErkJggg==","orcid":"","institution":"Harvard T H Chan School of Public Health","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rezaul","middleName":"Karim","lastName":"Ripon","suffix":""}],"badges":[],"createdAt":"2024-06-09 20:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4554990/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4554990/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66658265,"identity":"b43ec14a-e8b2-4d83-890b-675cd3c448b4","added_by":"auto","created_at":"2024-10-15 08:27:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24858,"visible":true,"origin":"","legend":"\u003cp\u003eAdjusted odd ratio interaction of higher. Blood Chromium and PFAS\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4554990/v1/868626b10bb34ed7ed5ae3cd.png"},{"id":66658688,"identity":"d29815fa-465e-46ae-8b5c-52c5da46fd3a","added_by":"auto","created_at":"2024-10-15 08:35:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":531265,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4554990/v1/2fb92c77-0fbe-4d23-ab53-b04da109399f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of Fetal Macrosomia and higher Blood Cadmium level among PFAS exposure participant from NHANES 2017-2018","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhile cadmium is a toxic heavy metal linked to metabolic alterations, PFAS are persistent environmental pollutants known for their endocrine-disrupting properties\u0026nbsp;(Genchi et al., 2020a)(Genchi et al., 2020). The two contaminants have the potential to cause oxidative stress and inflammation, which could impact the growth and development of the fetus(Sunderland et al., 2019)\u0026nbsp;(Genchi et al., 2020b). The aim of this study is to evaluate the levels of cadmium and PFAS in maternal blood, investigate how they relate to fetal macrosomia. These partnerships are essential for public health because they can help policies reduce harmful exposures and improve maternal and child health outcomes.Current research has identified several key points regarding the relationship between PFAS exposure and fetal macrosomia and higher blood cadmium levels. PFAS are widely recognized as persistent environmental pollutants with endocrine disrupting characteristics, which can disrupt hormonal systems, affecting fetal development and growth(Rickard et al., 2023). Maternal exposure to PFAS can cause adverse birth outcomes, such as low birth weight and preterm birth, according to previous studies, although the relationship with fetal macrosomia has been less investigated. Fetal growth can be affected by metabolic alterations and oxidative stress caused by cadmium, a toxic heavy metal(Wai et al., 2017). Higher blood cadmium levels in pregnant women have been shown to have negative effects on the health of the fetus, but its specific role in contributing to fetal macrosomia has not yet been investigated. Additionally, there is increasing evidence to suggest that combined exposure to environmental contaminants such as PFAS and cadmium may have synergistic effects, increasing the risk of adverse birth outcomes(Wai et al., 2017). To develop public health interventions that protect maternal and fetal health, it is essential to understand these interactions.\u003c/p\u003e\n\u003cp\u003eDespite existing knowledge, several aspects of the association between PFAS exposure and fetal macrosomia and higher blood cadmium levels remain unknown. The specific mechanisms by which cadmium and PFAS individually or together contribute to fetal macrosomia have not yet been fully understood. There has been little research directly linking combined exposure to PFAS and cadmium with an increased risk of fetal macrosomia, and how these environmental contaminants interact to affect fetal growth has not been thoroughly investigated. Furthermore, the role of potential confounding factors, such as genetic predisposition, nutritional status, and other environmental exposures, in modulating the effects of PFAS and cadmium on fetal macrosomia is not well established. Additional research is needed on the variability of PFAS and cadmium exposure levels in different populations and their differential influence on fetal outcomes. To understand the complex interactions between environmental pollutants and fetal health, it is necessary to understand these gaps. Ultimately, this will help establish more effective public health policies and interventions.\u003c/p\u003e\n\u003cp\u003eUnderstanding the relationship between fetal macrosomia and blood cadmium levels during PFAS exposure is critical for several reasons. Fetal macrosomia endangers the health of the mother and child, including birth complications and long-term health problems(Wai et al., 2017). Prevention strategies can be developed by investigating this association. Although both cadmium and PFAS are known contaminants, the effects of both on fetal growth are poorly understood. Investigation of these interactions can inform targeted public health interventions and regulatory policies that will protect pregnant women and developing fetuses from harmful exposures and improve overall maternal and child health outcomes. The research investigates how exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS), higher levels of cadmium in the blood, and the occurrence of fetal macrosomia, a condition in which a newborn has excessive birth weight, may be linked.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eDefinition of Fetal macrosomia:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe used the RHQ172 variable, which asks whether any of the respondent\u0026apos;s births resulted in a baby weighing 9 pounds (4082 grams) or more at birth, to identify fetal macrosomia in the data set. The occurrence of fetal macrosomia is indicated with a response coded \u0026apos;1\u0026apos; (Yes). This variable allows for the direct identification of macrosomia cases in the data set, allowing us to filter and analyze these particular cases. Additionally, the variable RHD173, which records the age at which the respondent gave birth to a baby weighing 9 pounds or more, may provide more context for these cases.\u003c/p\u003e\n\u003cp\u003eStatistical Analysis:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA dataset from the NHANES database for 2017 and 2018 is loaded into R. These datasets include demographic data, medical questionnaires, drug use, and other health-related data. To create a complete data set containing all relevant variables, individual data tables are combined using SEQN(NHANES, 2021a). To facilitate the analysis, missing values are addressed, and categorical variables are converted to factor variables. The svydesign function of the survey package is used to create a survey design object by specifying IDs, strata, and weights. This object is then used in all survey-related analyses to account for the complex NHANES survey design. Weighted descriptive statistics are calculated to understand the distribution and traits of the study variables(NHANES, 2021b). The tbl_svysummary function is used for categorical and continuous variables, and a weighted bivariate analysis is performed to examine the relationships between various factors and health outcomes. Logistic regression models have been created to investigate how multiple predictors are related to the outcome variable. This includes models for health behavior, demographic variables, and other relevant factors. To assess the strength and significance of associations in the models, adjusted odds ratios, confidence intervals, and p values (\u0026lt;0.05) are calculated for each predictor.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis table provides descriptive statistics for individuals with PFAS exposure above the detection level, summarizing various demographic and health-related variables for a total sample size of 14,368,694. The median age is 42 years, with an interquartile range (IQR) of 33 to 52 years. The racial composition includes 12% Mexican American, 6.5% Other Hispanic, 57% Non-Hispanic White, 12% Non-Hispanic Black, and 13% Other Race - Including Multi-Racial, indicating the majority are Non-Hispanic Whites. Health-related variables show 13% had a hysterectomy, 8% saw a doctor due to infertility, 9% were diagnosed with diabetes during pregnancy, and 16% had babies weighing 9 lbs or more. Additionally, 89% have blood cadmium levels at or above the detection limit [Table :1].\u003c/p\u003e \u003cp\u003eIndividuals above the detection limit are generally older (median age 42 vs. 39 years). A higher percentage of Non-Hispanic Blacks (12% vs. 9.7%) and Other Races (14% vs. 7.7%) are above the detection limit, whereas Non-Hispanic Whites are more represented below the detection limit (56% vs. 60%). A higher percentage of individuals above the detection limit have seen a doctor due to infertility issues (9.8% vs. 1.5%). More individuals below the detection limit have been diagnosed with diabetes during pregnancy (10% vs. 8.6%) and are categorized as borderline diabetic (2.5% vs. 0.4%). A higher percentage of individuals above the detection limit have experienced fetal macrosomia (17% vs. 10%) [Table :2].\u003c/p\u003e \u003cp\u003eIndividuals with a college degree or higher have a 13.1% [AOR (95% CI, P value): 1.131(1.008\u0026ndash;1.269, 0.0355)] higher odds of having PFAS above detection limit compared to those with less than a 9th-grade education. Individuals who have never married have 30.5% higher odds [AOR (95% CI, P value): 1.305(1.122\u0026ndash;1.518, 0.0005)] of having the PFAS above the detection limit compared to single individuals. Individuals with a history of fetal macrosomia have 6.5% higher odds [AOR (95% CI, P value): 1.065 (1.007\u0026ndash;1.126, 0.0285)] of having the PFAS above detection limit compared to those without fetal macrosomia [Table :3][Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main finding is that, among people exposed to PFAS above the limit of detection, there is a significant correlation between elevated blood cadmium levels and the occurrence of fetal macrosomia. Notably, fetal macrosomia occurred in 16% of participants with elevated blood levels of PFAS and cadmium. Additionally, the study found that having higher educational levels and never having been married were related to a higher likelihood of having blood cadmium levels above the limit of detection. These findings highlight the need to take sociodemographic factors into account when assessing exposure to environmental contaminants and their effects on reproductive health, highlighting the need for targeted public health interventions to reduce these risks.\u003c/p\u003e \u003cp\u003eHaving higher levels of education and never having been married were correlated with a higher likelihood of having elevated blood cadmium levels. These results make it essential to take sociodemographic factors into account when evaluating the health effects of environmental pollutants. The findings emphasize the need for targeted public health interventions and policies to reduce exposure to PFAS and cadmium, which will reduce harmful effects on reproductive health and improve maternal and child health.\u003c/p\u003e \u003cp\u003eStudies have found a connection between PFAS and adverse birth outcomes, but the connection with fetal macrosomia has been less investigated (Manzano-Salgado et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Preston et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). 16% of participants in this study who had elevated levels of PFAS and cadmium had fetal macrosomia, supporting findings that cadmium can cause oxidative stress and disrupt metabolic processes, affecting fetal development (Genchi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Wai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the study found that sociodemographic factors, such as higher educational levels and never being married, were related to higher cadmium levels. These findings reflect trends observed in other research and emphasize the importance of including social determinants in environmental health assessments.\u003c/p\u003e \u003cp\u003eFetal macrosomia is associated with an increased risk of birth complications, such as prolonged labor, cesarean delivery, and birth injuries (Preston et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Macrosomia can cause hypoglycemia, obesity, and metabolic syndrome later in life for babies (Wai et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The study's identification of a link emphasizes the importance of monitoring and managing exposure to environmental contaminants in pregnant women. When evaluating the risk profiles of pregnant patients, clinicians should consider these environmental factors and provide guidance on how to reduce exposure to harmful substances. This could result in better prenatal care, better maternal and fetal health outcomes, and information on public health policies aimed at reducing exposure to environmental toxins.\u003c/p\u003e \u003cp\u003eThere are several limitations to the study. First, its cross-sectional design precludes causality between exposure to PFAS and cadmium and the occurrence of fetal macrosomia. Second, there may be residual confounders that are not fully accounted for. These include genetic characteristics, detailed nutritional information, and other environmental exposures. Third, the study relies on self-reported reproductive histories, which could cause biases and inaccuracies in recall. The findings could also be affected by measurement errors when assessing blood levels of cadmium and PFAS. The study population may not fully represent all demographic groups, limiting the generalizability of the results.\u003c/p\u003e \u003cp\u003eFuture research should focus on longitudinal studies to establish causal relationships and uncover the mechanisms underlying the relationships between environmental exposures and fetal macrosomia. Genetic, nutritional, and other environmental exposures are some of the potential confounding factors that future research should also take into account. To increase accuracy, there is a need to improve measurement techniques for both exposure and health outcomes. Expanding the research to diverse populations will help generalize the findings and inform specific public health interventions. A deeper understanding of the impact of environmental contaminants on reproductive health will develop through these efforts. They will also guide policies to protect maternal and fetal well-being.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.R.: Methodology, Formal analysis, Review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests.\u003c/p\u003e\n\u003cp\u003eData Availability Statement\u003c/p\u003e\n\u003cp\u003eThe data are available here: https://www.cdc.gov/nchs/nhanes/index.htm\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGenchi, G., Sinicropi, M. S., Lauria, G., Carocci, A., \u0026amp; Catalano, A. (2020a). The effects of cadmium toxicity. In International Journal of Environmental Research and Public Health (Vol. 17, Issue 11). MDPI AG. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph17113782\u003c/span\u003e\u003cspan address=\"10.3390/ijerph17113782\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGenchi, G., Sinicropi, M. S., Lauria, G., Carocci, A., \u0026amp; Catalano, A. (2020b). The effects of cadmium toxicity. In International Journal of Environmental Research and Public Health (Vol. 17, Issue 11). MDPI AG. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph17113782\u003c/span\u003e\u003cspan address=\"10.3390/ijerph17113782\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManzano-Salgado, C. B., Casas, M., Lopez-Espinosa, M. J., Ballester, F., I\u0026ntilde;iguez, C., Martinez, D., Costa, O., Santa-Marina, L., Pereda-Pereda, E., Schettgen, T., Sunyer, J., \u0026amp; Vrijheid, M. (2017). Prenatal exposure to perfluoroalkyl substances and birth outcomes in a Spanish birth cohort. Environment International, \u003cem\u003e108\u003c/em\u003e, 278\u0026ndash;284. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2017.09.006\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2017.09.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNHANES. (2021a). \u003cem\u003eNHANES Tutorials - Weighting Module\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNHANES. (2021b). \u003cem\u003eNHANES Tutorials - Weighting Module\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/nchs/nhanes/tutorials/weighting.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePreston, E. V., Webster, T. F., Claus Henn, B., McClean, M. D., Gennings, C., Oken, E., Rifas-Shiman, S. L., Pearce, E. N., Calafat, A. M., Fleisch, A. F., \u0026amp; Sagiv, S. K. (2020). Prenatal exposure to per- and polyfluoroalkyl substances and maternal and neonatal thyroid function in the Project Viva Cohort: A mixtures approach. \u003cem\u003eEnvironment International\u003c/em\u003e, \u003cem\u003e139\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envint.2020.105728\u003c/span\u003e\u003cspan address=\"10.1016/j.envint.2020.105728\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRickard, B. P., Overchuk, M., Tulino, J., Tan, X., Ligler, F. S., Bae-Jump, V. L., Fenton, S. E., \u0026amp; Rizvi, I. (2023). Exposure to select PFAS and PFAS mixtures alters response to platinum-based chemotherapy in endometrial cancer cell lines. Environmental Health: A Global Access Science Source, \u003cem\u003e22\u003c/em\u003e(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12940-023-01034-2\u003c/span\u003e\u003cspan address=\"10.1186/s12940-023-01034-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSunderland, E. M., Hu, X. C., Dassuncao, C., Tokranov, A. K., Wagner, C. C., \u0026amp; Allen, J. G. (2019). A review of the pathways of human exposure to poly- and perfluoroalkyl substances (PFASs) and present understanding of health effects. In \u003cem\u003eJournal of Exposure Science and Environmental Epidemiology\u003c/em\u003e (Vol. 29, Issue 2, pp. 131\u0026ndash;147). Nature Publishing Group. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41370-018-0094-1\u003c/span\u003e\u003cspan address=\"10.1038/s41370-018-0094-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWai, K. M., Mar, O., Kosaka, S., Umemura, M., \u0026amp; Watanabe, C. (2017). Prenatal heavy metal exposure and adverse birth outcomes in Myanmar: A birth-cohort study. International Journal of Environmental Research and Public Health, \u003cem\u003e14\u003c/em\u003e(11). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph14111339\u003c/span\u003e\u003cspan address=\"10.3390/ijerph14111339\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable:1 Descriptive statistics among PFAS Exposed above detection level\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN = 14,368,694\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e42 (33, 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRaces\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,761,203 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e931,033 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e8,211,933 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,657,556 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other Race - Including Multi-Racial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,806,969 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Less than 9th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e516,293 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 9-11th grade (Includes 12th grade with no diploma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,450,878 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; High school graduate/GED or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e3,649,031 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Some college or AA degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e5,256,349 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; College graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e3,477,213 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e7,874,192 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e275,333 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,682,475 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e758,675 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Never married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,953,806 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Living with partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,805,282 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003eHad a hysterectomy?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,808,548 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e12,560,146 (87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003eSeen a DR b/c unable to become pregnant?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,152,258 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e13,216,435 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003eDuring pregnancy, told you have diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,294,115 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e12,957,839 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Boarderline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e116,740 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003eFatal macrosomia?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e2,252,405 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e12,116,289 (84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCadmium level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; At or above the detection limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e12,758,794 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Below lower detection limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e1,609,900 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.7763%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e Median (IQR); n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2237%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Bivariable analysis among blood cadmium and PFAS exposure above the detection limit\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003eAbove Detection limit, N = 11,272,970\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003eBelow the Detection limit, N = 3,095,724\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e42 (34, 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e39 (26, 48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRaces\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Mexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,325,735 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e435,469 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e681,393 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e249,640 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e6,339,471 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e1,872,462 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,358,173 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e299,382 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other Race - Including Multi-Racial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,568,198 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e238,772 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Less than 9th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e280,802 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e235,490 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 9-11th grade (Includes 12th grade with no diploma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,345,853 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e105,025 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; High school graduate/GED or equivalent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e2,534,970 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e1,114,061 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Some college or AA degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e4,249,520 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e1,006,829 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; College graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e2,842,894 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e634,319 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e6,257,361 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e1,616,831 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e238,580 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e36,754 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,314,945 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e367,530 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e638,294 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e120,381 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Never married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,241,917 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e711,889 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Living with partner\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,562,943 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e242,339 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003eRatio of family\u003cstrong\u003e\u0026nbsp;income\u003c/strong\u003e to poverty;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e2.44 (1.35, 4.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e1.83 (1.21, 3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003eHad a hysterectomy?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,393,031 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e415,516 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e9,879,938 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e2,680,208 (87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003eSeen a DR b/c unable to become pregnant?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,105,342 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e46,916 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e10,167,627 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e3,048,808 (98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003eDuring pregnancy, told you have diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e970,627 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e323,488 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e10,262,223 (91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e2,695,616 (87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Borderline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e40,120 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e76,620 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003eFetal macrosomia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e1,932,095 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e320,309 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46.8354%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.2722%;\"\u003e\n \u003cp\u003e9,340,874 (83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.8924%;\"\u003e\n \u003cp\u003e2,775,415 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e Median (IQR); n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Adjusted regression analysis among blood cadmium and PFAS exposure above the detection limit with health conditions. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOdds Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eAge in Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eRaces\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eOther Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.0255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eOther Race - Including Multi-Racial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e9-11th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eHigh school graduate/GED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eSome college or AA degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eCollege graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.0355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eLess than 9th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e1.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eLiving with partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eRatio of family\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eincome to poverty;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eHad a hysterectomy?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eSeen a DR b/c unable to become pregnant?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eDuring pregnancy, told you have diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.0677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Borderline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003eFetal macrosomia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003e1.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003e1.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003e0.0285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58.121%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9.87261%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.5096%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0318%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.465%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fatal Macrosomia, PFAS, Cadmium","lastPublishedDoi":"10.21203/rs.3.rs-4554990/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4554990/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Concern about potential reproductive health effects has arisen from the interaction between environmental contaminants such as perfluoroalkyl substances (PFAS) and blood cadmium levels. Exposure to PFAS above the limit of detection impacts the reproductive health of people with elevated blood cadmium levels.\u003c/p\u003e\n\u003cp\u003eObjective: To analyze the relationship between blood cadmium levels and different reproductive health outcomes in a large cohort exposed to PFAS above the limits of detection, considering sociodemographic factors and reproductive history.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A community-based cross-sectional study was conducted among 143M NHANES participants from 2017-2018. Descriptive statistics for PFAS exposure were analyzed and bivariate and adjusted regression analyzes were used to evaluate the relationship between blood cadmium levels and reproductive health outcomes. Age, race, educational level, marital status, income-poverty ratio, and reproductive history were variables considered in the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 16% of participants whose PFAS and blood cd are above the detection limit showed fetal macrosomia. Participants with higher educational levels, particularly college graduates or higher, showed higher odds of experiencing detrimental Blood cadmium above the detection limit (aOR = 1.131, 95% CI: 1.008-1.269, p = 0.0355). Furthermore, people who had never been married were significantly more likely (aOR = 1.305, 95% CI: 1.122-1.518, p = 0.0006), and fetal macrosomia was significantly more likely (aOR = 1.065, 95% CI: 1.007-1.126, p = 0.0285) whose blood cd level is higher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The results highlight the importance of considering sociodemographic factors when it comes to environmental exposures and their effects on reproductive health. To inform public health interventions aimed at reducing the negative effects of environmental pollutants on reproductive health, future research should further investigate these relationships.\u003c/p\u003e","manuscriptTitle":"Association of Fetal Macrosomia and higher Blood Cadmium level among PFAS exposure participant from NHANES 2017-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 08:27:11","doi":"10.21203/rs.3.rs-4554990/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"19a1deea-05c4-474f-9759-7dba054744ec","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38856514,"name":"Earth and environmental sciences/Environmental sciences"},{"id":38856515,"name":"Earth and environmental sciences/Environmental social sciences"},{"id":38856516,"name":"Health sciences/Medical research"},{"id":38856517,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-15T08:27:11+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-15 08:27:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4554990","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4554990","identity":"rs-4554990","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}