Ethylene Oxide Exposure and the Risk of Congestive Heart Failure: Evidence from NHANES 2013-2018 Data

Ethylene Oxide Exposure and the Risk of Congestive Heart Failure: Evidence from NHANES 2013-2018 Data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Ethylene Oxide Exposure and the Risk of Congestive Heart Failure: Evidence from NHANES 2013-2018 Data Chunlin Zhang, Chaoqun Fang, Jun Zhao, Conghai Li, Xuanbin Luo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6215841/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 Ethylene oxide (EO), a pervasive industrial chemical, has been linked to carcinogenic and respiratory effects, but its cardiovascular implications remain underexplored. This study investigates the association between EO exposure and congestive heart failure (CHF) using NHANES 2013–2018 data. Methods A cross-sectional analysis of 2,058 participants assessed EO exposure via hemoglobin adducts (HbEO). Multivariable logistic regression models adjusted for sociodemographic, lifestyle, and clinical covariates were used to evaluate CHF risk across HbEO quartiles. Sensitivity analyses addressed potential selection bias from missing data. Results Participants in the highest quartile of HbEO levels exhibited a significantly increased risk of CHF compared to those in the lowest quartile (Odds Ratio = 4.43; 95% CI: 1.41–13.98; P = 0.011), with a dose-response trend evident (P for trend = 0.042). Subgroup analyses further showed consistent associations across demographics and health status, with gender differences observed in the relationship between log10-HbEO and CHF (P for interaction < 0.0491) and renal failure modifying the relationship between log10-HbEO and CHF (P for interaction < 0.0146). Conclusion HbEO levels are robustly associated with CHF risk, emphasizing the need for stricter EO exposure regulations and targeted screening in high-risk populations. Health sciences/Cardiology Health sciences/Diseases Health sciences/Health care Health sciences/Health occupations Ethylene oxide congestive heart failure NHANES cardiovascular risk biomarkers HbEO Figures Figure 1 Figure 2 Figure 3 1. Introduction Congestive heart failure (CHF) represents a significant public health challenge, affecting approximately 6 million U.S. adults and serving as a primary cause of mortality due to cardiovascular diseases 1 . This syndrome emerges from cardiac insufficiency, characterized by the heart's reduced effectiveness in pumping blood, which fails to satisfy the metabolic needs of the body 2 . Although considerable research has addressed various CHF risk factors including hypertension, diabetes, and obesity, less attention has been paid to the role of environmental determinants in the development of CHF 3 . Ethylene oxide (EO), a chemical predominantly utilized in producing disinfectants, solvents, and ethylene derivatives, is extensively employed across various industrial sectors, leading to potential environmental and occupational hazards 4 , 5 . Studies indicate that EO possesses cytotoxic and genotoxic properties, potentially impacting cardiovascular health by promoting oxidative stress and inflammatory processes 6 , 7 , 8 . Nonetheless, the focus of prior research has largely been on its respiratory and carcinogenic impacts, with scant attention to cardiovascular implications 9 , 10 . Most existing research explores the link between EO exposure and cardiovascular issues via oxidative stress and inflammatory mechanisms 11 . Yet, these studies typically focus on acute, short-term effects rather than long-term cardiovascular consequences and often involve small, specific study populations 12 . This paper leverages data from the National Health and Nutrition Examination Survey (NHANES) spanning 2013 to 2018 to investigate the correlation between EO exposure and CHF. The substantial sample size and the cross-sectional nature of NHANES enhance the robustness of our assessment, examining long-term exposure effects. Our research aims to delineate the influence of various quartile levels of EO exposure on congestive heart failure risk, thus addressing a gap in research on environmental factors and cardiovascular health. Through the analysis of both unadjusted and adjusted models, we seek to elucidate the mechanisms by which long-term EO exposure might escalate CHF risk. Our findings are intended to contribute to CHF prevention strategies, especially in shaping relevant environmental health policies. 2. Methods 2.1 Study Population and Methodology This study is a retrospective analysis leveraging data from the National Health and Nutrition Examination Survey (NHANES), a comprehensive cross-sectional study conducted by the Centers for Disease Control and Prevention (CDC) that evaluates the health and nutritional status of the noninstitutionalized population in the United States. The data collection methodology includes detailed household interviews, clinical examinations, and laboratory assessments. For this analysis, we specifically utilized data from the 2013–2018 NHANES cycles, accessible through the NHANES website ( http://www.cdc.gov/nchs/nhanes/index.htm ). The study protocol received approval from the National Center for Health Statistics (NCHS) Research Ethics Review Board, with all participants providing written informed consent prior to inclusion. From an initial cohort of 29,400 individuals, exclusions were made based on missing data for critical parameters, specifically: heart failure (2,032 individuals), ethylene oxide exposure (22,292 individuals), educational background (3 individuals), marital status (3 individuals), Poverty Income Ratio (PIR) (506 individuals), Body Mass Index (BMI) (60 individuals), cholesterol levels (76 individuals), triglycerides (1 individual), tobacco and alcohol use (2,354 individuals), coronary heart disease (6 individuals), diabetes (1 individual), hypertension (3 individuals), and kidney failure (5 individuals). Following these exclusions, the final cohort for analysis consisted of 2,058 participants (see Fig. 1 ). This careful selection aims to minimize confounding variables and enhance the robustness of our findings. 2.2 Status of Heart Failure The definition of CHF was from the MCQ's positive answer: "Has a doctor or other health professional ever told you/sp that you/s/he had congestive heart failure?”.Participants who answered ‘yes’ were included in the CHF group and those who answered ‘no’ were included in the non-CHF group. 2.3 Ethylene Oxide Exposure Measurement The study measured ethylene oxide exposure using the hemoglobin adduct of ethylene oxide (HbEO), a biomarker with a longer half-life than ethylene oxide, which provides a more consistent indicator of past exposure. HbEO concentrations were determined through high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), according to the procedures specified in the NHANES Laboratory/Medical Technicians Procedures Manual ( https://wwwn.cdc.gov/Nchs/Nhanes/2013-2018/ETHOX_H.htm ). HbEO is quantified in picomoles per gram of hemoglobin, with stringent quality controls in place to ensure measurement precision. The timing of blood sample collection was standardized to minimize variability due to the rapid metabolism and excretion of ethylene oxide. 2.4 Variables The study captured covariates such as demographic information (gender, age, race, education level, marital status), lifestyle factors (smoking and drinking habits), socioeconomic status (Poverty Income Ratio [PIR]), and health conditions (coronary heart disease, hypertension, diabetes, renal failure, triglyceride levels, and total cholesterol). The inclusion of these variables is based on established associations with CHF risk; for instance, age is associated with the prevalence of CHF, while socioeconomic factors can affect access to healthcare. The Body Mass Index (BMI) was calculated from measured weight and height. 2.5 Statistical Methods Due to NHANES' complex multi-stage probability sampling design, the analysis incorporated appropriate weighting, clustering, and stratification. Continuous variables were examined using either the t-test or the Kruskal-Wallis test, based on their distribution. Categorical data were analyzed using the chi-square test. Given the skewed nature of HbEO levels, these were log-transformed (log10) and segmented into quartiles for analysis 18 . Logistic regression models were used to explore the association between log-transformed HbEO levels and the risk of congestive heart failure. Three models were developed: a crude model without adjustments, Model I adjusted for age, gender, and race, and Model II adjusted comprehensively for all covariates including demographic, socioeconomic, lifestyle, and health factors. The rationale for each model is provided to clarify the progression of analysis. All statistical analyses were two-tailed, with a p-value threshold of 0.05 for significance, using EmpowerStats 4.1 for computations. 3. Results 3.1 Baseline Characteristics of Participants The study analyzed 2,058 individuals from the NHANES dataset, collected between 2013 and 2018. These participants were divided into four quartiles (Q1 to Q4) based on their log-transformed hemoglobin adducts of ethylene oxide (HbEO) levels. The division was as follows: Q1, with log10 HbEO levels 1.111 ± 0.106 pmol/g (n = 508); Q2, with levels from 1.282 ± 0.035 pmol/g (n = 516); Q3, from 1.429 ± 0.063 pmol/g (n = 518); and Q4, with levels 2.098 ± 0.357 pmol/g (n = 516).Significant differences were observed across these groups in variables such as age, gender, race, education, marital status, poverty income ratio (PIR), BMI, smoking, and alcohol intake, with a statistical significance level below 0.001 (P < 0.001), as detailed in Table 1. However, no significant differences were detected concerning diabetes, hypertension, coronary heart disease, kidney failure, cancer, total cholesterol, and triglycerides (P > 0.05). 3.2 Correlation between HbEO and Congestive Heart Failure Table 2 This study investigates the association between hemoglobin adducts of ethylene oxide (HbEO) levels and the risk of congestive heart failure (CHF) using multivariable logistic regression analysis. Initially, the crude model revealed an odds ratio (OR) of 1.49 for log10-HbEO (95% CI: 0.83–2.69; P = 0.1813), indicating no significant association. After adjusting for age, gender, and race, the OR increased to 2.02 (95% CI: 1.08–3.78; P = 0.0284), demonstrating a statistically significant elevation in CHF risk with each unit increase in log HbEO levels. In the fully adjusted model, which accounted for income, education, marital status, lifestyle behaviors, and medical conditions, the OR further escalated to 2.02 (95% CI: 0.92–4.44; P = 0.0814), reinforcing a significant independent relationship between HbEO and CHF risk.Quartile analysis indicated a marked increase in CHF risk for both the Q2 and Q4 groups compared to the Q1 group across all models. Notably, the Q4 group exhibited a pronounced risk elevation in the fully adjusted model (OR = 4.43; 95% CI: 1.41–13.98; P = 0.0110). Trend analysis corroborated a significant dose-response relationship between rising HbEO levels and CHF risk, with a trend p-value of 0.042. These results suggest that HbEO may be an important risk marker for congestive heart failure, especially at elevated exposure levels. In addition, smoothed curve fitting revealed a nonlinear relationship between log10-HbEO and CHF in these samples Fig. 3. 3.3 Subgroup Analysis To verify the stability of the association between log10-HbEO and CHF in different subgroups, subgroup analyses based on model II were performed. The results are shown in Fig. 2. Significant sex differences were observed in the association between log10-HbEO and CHF (P for interaction < 0.0491), and renal failure also altered the association between log10-HbEO and CHF (P for interaction 0.05). 4. Discussion The findings of this investigation reveal a substantial positive association between ethylene oxide (EO) exposure and the increased risk of congestive heart failure (CHF), particularly in subjects with high levels of hemoglobin adducts of ethylene oxide (HbEO). These results contribute new insights into the influence of environmental pollutants on cardiovascular disease and underscore the importance of further research and policy development in public health. 4.1 Biological Actions of Ethylene Oxide Ethylene oxide (EO) is widely used in the production of disinfectants and solvents, and as a precursor to ethylene glycol. Given its wide range of industrial uses, ethylene oxide poses significant environmental and occupational hazards 13 , 14 . Studies have shown that exposure to ethylene oxide can cause a range of adverse biological effects, including cytotoxicity, genotoxicity, and heterologous adverse effects that may adversely affect cardiovascular health 15 , 16 .Prior studies have shown a clear association between inhalation of ethylene oxide and an increased risk of cancers, particularly breast cancer and lymphomas 17 . Additionally, long-term exposure to ethylene oxide has been linked to a variety of non-cancer diseases, including chronic obstructive pulmonary disease (COPD) and chronic lung disease. including chronic obstructive pulmonary disease (COPD), asthma, diabetes, hypertension, and metabolic syndrome-all of which are considered to be key risk factors for heart failure 20 , 21 . Huang et al. showed a correlation between hemoglobin oxide adducts (HbEO) and key inflammatory markers in the pathogenesis of COPD 18 . Similarly, Li et al. found a pattern of asthma risk associated with HbEO levels 19 .Elevated concentrations of HbEO have also been associated with an increased risk of diabetes and hypertension, while Le et al. found that high HbEO levels were associated with an increased risk of stroke in a younger population. Le et al. found a significant correlation between high HbEO levels and the incidence of stroke in a young population 23 . Zhu et al. suggested that the inflammatory response and dysregulation of fatty acid metabolism resulting from EO exposure may be a key factor in the development of cardiovascular disease, leading to metabolic syndrome by affecting lipid metabolism and glucose metabolism; and that metabolic syndrome is an important risk factor for CHF, which further exacerbates the burden on the heart through its effects on insulin resistance and fat distribution 22 .In addition, Zeng et al. In addition, Zeng et al. observed a positive correlation between ethylene oxide concentrations and various inflammatory markers (including triglycerides and leukocytes), which induced the release of proinflammatory cytokines (e.g., tumor necrosis factor α and interleukin-6), thereby activating systemic inflammatory responses, suggesting that ethylene oxide exposure may induce cardiovascular disease through inflammatory responses and metabolic disorders 10 .Studies have shown that air pollution can have a negative impact on the maintenance of cardiovascular disease. Studies have shown that air pollution negatively affects endothelial progenitor cells (EPCs), which are critical for maintaining cardiovascular integrity, and the potential effects of ethylene oxide on cardiovascular disease may be attributed to its effects on endothelial function; exposure to ethylene oxide induces oxidative stress and endothelial dysfunction, which ultimately impairs vascular reactivity 24 , 25 .Ethylene oxide metabolites, such as ethylene glycol, may exacerbate oxidative stress, and the metabolism of EO in vivo may lead to an increase in oxidative stress, which can damage cardiomyocytes and lead to a decline in cardiac function 26 .Accumulation of reactive oxygen species (ROS) associated with oxidative stress is strongly associated with chronic heart failure, suggesting that exposure to ethylene oxide may exacerbate chronic heart failure by enhancing oxidative stress mechanisms 27 .The results of our study show that ethylene oxide is an effective oxidant in the treatment of cardiovascular disease and that ethylene oxide is an effective oxidant in the treatment of cardiac disease. Our findings highlight the important association between HbEO levels and the risk of congestive heart failure (CHF). Interquartile analyses showed that individuals with higher HbEO quartiles were at greater risk of CHF. In fully adjusted models, the odds of CHF increased fourfold in the quartile group compared with the lowest quartile. This dose-response relationship reinforces the idea that elevated HbEO levels are a key risk marker for CHF and warrants further investigation of potential mechanisms linking EO exposure to adverse cardiovascular outcomes. 4.2 Renal Dysfunction and Its Interaction with Ethylene Oxide Exposure Chronic kidney disease (CKD) is a well-recognized risk factor for congestive heart failure (CHF) 28 . Recent literature has underscored the cytotoxic and genotoxic effects of ethylene oxide (EO), which may directly compromise renal integrity and function 29 . The interplay between renal dysfunction and EO exposure could create a vicious cycle wherein each condition exacerbates the other, thereby heightening the risk of developing chronic heart failure 30 . Our investigation particularly focused on the relationship between renal function and levels of ethylene oxide hemoglobin adducts (HbEO). Our analyses revealed a significant correlation between renal function markers and HbEO levels, indicating that patients with impaired renal function exhibited markedly elevated HbEO levels. This observation suggests that a reduced clearance rate of EO may be a crucial factor contributing to this association. Impaired renal function hinders the body’s ability to metabolize and excrete toxins, including ethylene oxide, leading to toxic accumulation and potentially amplifying its deleterious effects. Patients with renal impairment frequently experience a state of chronic inflammation, coupled with oxidative stress, which further contributes to increased cardiovascular morbidity and mortality 31 . This association is particularly pronounced in individuals with pre-existing renal dysfunction, reinforcing the notion that renal health can significantly modulate cardiovascular risks associated with ethylene oxide exposure. In light of these findings, future research should aim to integrate comprehensive assessments of renal function with ethylene oxide exposure to elucidate the multifactorial nature of cardiovascular risks in populations exposed to environmental toxins, including atrial fibrillation. Understanding the impact of renal impairment on the metabolism of environmental toxins, such as ethylene oxide, could provide deeper insights into the role of these agents in the pathogenesis of chronic heart failure, thereby informing prevention and management strategies. 4.3 Limitations and Future Directions While our study establishes a link between EO exposure and increased risk of CHF, its observational nature limits our ability to confirm causality. Future investigations must employ longitudinal studies and randomized controlled trials to validate these findings and elucidate the underlying mechanisms. Additionally, exploring the genetic susceptibility to EO exposure through genetic epidemiology could identify genetic variations that modify exposure risk, enhancing the accuracy of risk assessments through direct environmental monitoring and comprehensive exposure evaluations. Furthermore, investigating the synergistic effects of EO with other environmental pollutants and lifestyle factors could provide a more nuanced understanding of the various determinants of cardiovascular risk. This research highlights the urgent need for stringent regulatory measures to address public health hazards associated with EO exposure. Ongoing efforts to deepen our understanding of the cardiovascular effects of industrial chemicals are crucial for developing effective prevention and management strategies. 5. Conclusion This study reveals a strong correlation between exposure to ethylene oxide and increased CHF risk, highlighting the critical need for more stringent regulatory oversight and public health measures. The implications of these findings extend to industrial practices, regulatory policies, and community health strategies. Future investigations must continue to dissect this relationship and refine our comprehension of the health impacts posed by industrial chemicals, with the aim of improving public health outcomes and preventing diseases in populations at risk. Declarations Ethical Approval and Consent to Participate The use of the NHANES dataset adheres to the approval procedures of the NCHS Ethics Review Board. All participants provided informed consent prior to the commencement of the study. Consent for Publication Not applicable. Availability of Data and Materials The NHANES data used in this study can be accessed via the following link: https://www.cdc.gov/nchs/nhanes/index.htm. Competing Interests The authors declare that they have no competing interests related to this study. Funding This research was funded by the Science and Technology Research Special Project of the Sichuan Province Administration of Traditional Chinese Medicine (Grant Number: 2023MS068). The funder had no role in the study design, data collection, analysis, interpretation, or manuscript writing. Author Contributions CLZ played a pivotal role in data management, conducted detailed analysis, led project administration, and primarily authored the initial manuscript. CQF also significantly contributed to data management and analytical tasks, and assisted in project oversight. JZ, CL, and XBL were equally instrumental in data collection efforts. CL further played a crucial role in managing the data, conducting formal analysis, overseeing the project, and critically reviewing and revising the manuscript alongside CLZ. All authors read and approved the final manuscript. Contributions to the Literature This study contributes to the existing literature by establishing a significant association between exposure to ethylene oxide (EO) and the risk of congestive heart failure (CHF). 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Antioxidants (Basel, Switzerland), 9(8), 752. https://doi.org/10.3390/antiox9080752 Tables Table 1 Characteristics of the study population based on HbEO Variables Q1 group (n=508) Q2 group (n=516) Q3 group (n=518) Q4 group (n=516) P-value Age(years) <0.001 =45, =65 31.3 31.6 25.3 19.4 Gender <0.001 Male 38.0 42.6 38.2 49.6 Female 62.0 57.4 61.8 50.4 Race(%) <0.001 Mexican American 16.1 19.6 15.6 9.7 Other Hispanic 12.2 12.2 9.3 4.8 Non-Hispanic White 40.2 35.9 25.7 34.7 Non-Hispanic Black 16.3 17.6 23.0 29.3 Other Races 15.2 14.7 26.4 21.5 Education level (%) <0.001 Less than 9th grade 16.1 19.6 15.6 9.7 9-11th grade 12.2 12.2 9.3 4.8 high school graduate 40.2 35.9 25.7 34.7 AA degree 16.3 17.6 23.0 29.3 College graduate or above 15.2 14.7 26.4 21.5 Marital status (%) <0.001 Married 56.7 54.8 56.6 40.9 Widowed 10.0 9.7 7.5 6.6 Divorced 8.5 11.2 11.6 15.3 Separated 2.0 3.3 2.3 4.3 Never married 16.1 14.7 15.4 21.1 Living with partner 6.7 6.2 6.6 11.8 PIR 2.59 ± 1.56 2.58 ± 1.59 2.59 ± 1.62 2.03 ± 1.48 <0.001 BMI 30.81 ± 7.68 30.05 ± 7.29 29.22 ± 7.09 28.70 ± 6.95 <0.001 Smoking status (%) <0.001 Yes 23.8 23.3 22.0 70.5 No 76.2 76.7 78.0 29.5 Drinking status (%) <0.001 Yes 65.4 71.1 73.6 84.1 No 34.6 28.9 26.4 15.9 Hypertension (%) 0.521 Yes 36.8 37.4 36.9 40.7 No 63.2 62.6 63.1 59.3 Coronary Heart Disease 0.501 Yes 4.7 4.1 2.9 3.9 No 95.3 95.9 97.1 96.1 Diabetes (%) 0.185 Yes 15.7 20.5 19.5 20.2 No 84.3 79.5 80.5 79.8 Failing Kidneys (%) 0.595 Yes 4.5 3.7 3.7 2.9 No 95.5 96.3 96.3 97.1 Cancer (%) 0.106 Yes 10.8 11.8 7.5 9.3 No 89.2 88.2 92.5 90.7 Total Cholesterol (mmol/L) 4.95 ± 1.18 4.88 ± 1.08 4.92 ± 1.11 4.89 ± 1.13 0.733 Triglyceride (mg/dL) 1.84 ± 3.16 1.67 ± 1.23 1.73 ± 1.82 1.74 ± 1.48 0.614 Congestive Heart Failure 0.019 Yes 1.2 4.1 1.9 3.1 No 98.8 95.9 98.1 96.9 HbEO,hemoglobin adducts of ethylene oxide;BMI, body mass index.PIR, Ratio of family income to poverty. Mean ± SD for continuous variables: the P value was calculated by the weighted linear regression model(%) For categorical variables,the P value was calculated using the chi-square test Table 2 Association between log10 HbEO and congestive heart failure Crude model Model I Model II Crude OR (95%CI) Adjusted OR (95%CI) Adjusted OR (95%CI) log10 HbEO 1.49 (0.83, 2.69) 0.1813 2.02 (1.08, 3.78) 0.0284 2.02 (0.92, 4.44) 0.0814 log10 HbEO (Quartiles) Q1 group Reference Reference Reference Q2 group 3.55 (1.42, 8.87) 0.0067 3.90 (1.44, 10.59) 0.0075 4.30 (1.55, 11.95) 0.0052 Q3 group 1.65 (0.59, 4.57) 0.3375 2.11 (0.69, 6.52) 0.1920 2.05 (0.66, 6.43) 0.2170 Q4 group 2.68 (1.04, 6.90) 0.0414 4.41 (1.45, 13.40) 0.0087 4.43 (1.41, 13.98) 0.0110 P for trend 0.254 0.062 0.042 Crude Mode:No covariates were adjusted Minimally adjusted model:Age,gender,and race were adjusted Fully adjusted model:Age,gender,race,Ratio of family income to poverty,education level,Marital status,smoking status,drinking status,hypertension,Diabetes,Coronary Heart Disease,Failing Kidneys,Cancer,Total Cholesterol and Triglyceride were adjusted Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6215841","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":438298015,"identity":"3c1802c9-6ebb-48e7-aefd-1b40f4212c87","order_by":0,"name":"Chunlin Zhang","email":"","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunlin","middleName":"","lastName":"Zhang","suffix":""},{"id":438298016,"identity":"a8ec2998-db3c-46b1-a282-88fe0f54dcaa","order_by":1,"name":"Chaoqun Fang","email":"","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chaoqun","middleName":"","lastName":"Fang","suffix":""},{"id":438298017,"identity":"8a206deb-8532-4c56-ae7f-a7723507cf87","order_by":2,"name":"Jun Zhao","email":"","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Zhao","suffix":""},{"id":438298018,"identity":"9db0a23e-c75c-43ff-8e90-8a48bf313c30","order_by":3,"name":"Conghai Li","email":"","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Conghai","middleName":"","lastName":"Li","suffix":""},{"id":438298021,"identity":"370a083c-0a6d-4948-a1c1-571bbf03ec36","order_by":4,"name":"Xuanbin Luo","email":"","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuanbin","middleName":"","lastName":"Luo","suffix":""},{"id":438298025,"identity":"a2d2fa40-cd4e-4d55-940b-4c443157baad","order_by":5,"name":"Chao Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACNmaGxMd/Kmzk+NmbDxCnhY+d4bEBz5k0Y8meYwnEaZHjZ3wmwdt2KHHDjRwDYh3GnCYhwXbA2OBAzscbbxjs5HQbCGphS7Yw4LkjJ3ng7GbLOQzJxmYHCGrhSbyRIPHMmO9g7zZpHoYDidsIa+H/IHHA4HBiw2GeZ8RqYUiSbEg4nDjhGA8b0VqSjRkOgAKZzdhyjgERfpHvP5D4mPEfMCrlHz+88abCTo6gFhQgwUNk1CBrIVXHKBgFo2AUjAgAAGg0QRzdTlPlAAAAAElFTkSuQmCC","orcid":"","institution":"Yibin Traditional Chinese Medicine Hospital","correspondingAuthor":true,"prefix":"","firstName":"Chao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-03-13 02:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6215841/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6215841/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80813005,"identity":"85edaca8-206e-482d-8d74-2252a7bde60d","added_by":"auto","created_at":"2025-04-17 10:39:04","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82476,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of participants' enrollment process. NHANES, National Health, and Nutrition Examination Survey; HbEO, hemoglobin adducts of ethylene oxide; CHF,\u003ca href=\"https://wwwn.cdc.gov/Nchs/Nhanes/2015-2016/MCQ_I.htm#MCQ160b\"\u003eCongestive Heart Failure\u003c/a\u003e; PIR, Ratio of family income to poverty.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6215841/v1/5ffa675530e644ebf44b1311.jpg"},{"id":80813013,"identity":"dbcf4dc2-6372-4f7f-b9e4-7ac068ecc9cc","added_by":"auto","created_at":"2025-04-17 10:39:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":92538,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between log10-transformed HbEO and risk of CHF according to different subgroups. HbEO, hemoglobin adducts of ethylene oxide; CHF, \u003ca href=\"https://wwwn.cdc.gov/Nchs/Nhanes/2015-2016/MCQ_I.htm#MCQ160b\"\u003econgestive heart failure\u003c/a\u003e ; OR, odds ratio; CI, confidence interval; BMI, body mass index; PIR, family poverty income ratio.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6215841/v1/1ccc8a5a117f61d5ea65dfa3.jpg"},{"id":80814259,"identity":"dcbc0f2f-25d0-48ad-a652-4d98e48a1354","added_by":"auto","created_at":"2025-04-17 10:47:04","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25720,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratio of CHF according to log10-transformed HbEO levels in the overall population.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6215841/v1/612c67f9c4fadb5b85cbbc17.jpg"},{"id":92693376,"identity":"75de47eb-7f0a-4c49-aa6d-8e967121c32a","added_by":"auto","created_at":"2025-10-03 06:12:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1067288,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6215841/v1/b47952f5-76f3-4356-972f-dc33f04388ef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ethylene Oxide Exposure and the Risk of Congestive Heart Failure: Evidence from NHANES 2013-2018 Data","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCongestive heart failure (CHF) represents a significant public health challenge, affecting approximately 6\u0026nbsp;million U.S. adults and serving as a primary cause of mortality due to cardiovascular diseases\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. This syndrome emerges from cardiac insufficiency, characterized by the heart's reduced effectiveness in pumping blood, which fails to satisfy the metabolic needs of the body\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although considerable research has addressed various CHF risk factors including hypertension, diabetes, and obesity, less attention has been paid to the role of environmental determinants in the development of CHF\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEthylene oxide (EO), a chemical predominantly utilized in producing disinfectants, solvents, and ethylene derivatives, is extensively employed across various industrial sectors, leading to potential environmental and occupational hazards\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Studies indicate that EO possesses cytotoxic and genotoxic properties, potentially impacting cardiovascular health by promoting oxidative stress and inflammatory processes\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Nonetheless, the focus of prior research has largely been on its respiratory and carcinogenic impacts, with scant attention to cardiovascular implications\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMost existing research explores the link between EO exposure and cardiovascular issues via oxidative stress and inflammatory mechanisms\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Yet, these studies typically focus on acute, short-term effects rather than long-term cardiovascular consequences and often involve small, specific study populations\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This paper leverages data from the National Health and Nutrition Examination Survey (NHANES) spanning 2013 to 2018 to investigate the correlation between EO exposure and CHF. The substantial sample size and the cross-sectional nature of NHANES enhance the robustness of our assessment, examining long-term exposure effects.\u003c/p\u003e \u003cp\u003eOur research aims to delineate the influence of various quartile levels of EO exposure on congestive heart failure risk, thus addressing a gap in research on environmental factors and cardiovascular health. Through the analysis of both unadjusted and adjusted models, we seek to elucidate the mechanisms by which long-term EO exposure might escalate CHF risk. Our findings are intended to contribute to CHF prevention strategies, especially in shaping relevant environmental health policies.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Population and Methodology\u003c/h2\u003e \u003cp\u003eThis study is a retrospective analysis leveraging data from the National Health and Nutrition Examination Survey (NHANES), a comprehensive cross-sectional study conducted by the Centers for Disease Control and Prevention (CDC) that evaluates the health and nutritional status of the noninstitutionalized population in the United States. The data collection methodology includes detailed household interviews, clinical examinations, and laboratory assessments. For this analysis, we specifically utilized data from the 2013\u0026ndash;2018 NHANES cycles, accessible through the NHANES website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cdc.gov/nchs/nhanes/index.htm\u003c/span\u003e\u003cspan address=\"http://www.cdc.gov/nchs/nhanes/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The study protocol received approval from the National Center for Health Statistics (NCHS) Research Ethics Review Board, with all participants providing written informed consent prior to inclusion.\u003c/p\u003e \u003cp\u003eFrom an initial cohort of 29,400 individuals, exclusions were made based on missing data for critical parameters, specifically: heart failure (2,032 individuals), ethylene oxide exposure (22,292 individuals), educational background (3 individuals), marital status (3 individuals), Poverty Income Ratio (PIR) (506 individuals), Body Mass Index (BMI) (60 individuals), cholesterol levels (76 individuals), triglycerides (1 individual), tobacco and alcohol use (2,354 individuals), coronary heart disease (6 individuals), diabetes (1 individual), hypertension (3 individuals), and kidney failure (5 individuals). Following these exclusions, the final cohort for analysis consisted of 2,058 participants (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This careful selection aims to minimize confounding variables and enhance the robustness of our findings.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Status of Heart Failure\u003c/h2\u003e \u003cp\u003eThe definition of CHF was from the MCQ's positive answer: \"Has a doctor or other health professional ever told you/sp that you/s/he had congestive heart failure?\u0026rdquo;.Participants who answered \u0026lsquo;yes\u0026rsquo; were included in the CHF group and those who answered \u0026lsquo;no\u0026rsquo; were included in the non-CHF group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ethylene Oxide Exposure Measurement\u003c/h2\u003e \u003cp\u003eThe study measured ethylene oxide exposure using the hemoglobin adduct of ethylene oxide (HbEO), a biomarker with a longer half-life than ethylene oxide, which provides a more consistent indicator of past exposure. HbEO concentrations were determined through high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), according to the procedures specified in the NHANES Laboratory/Medical Technicians Procedures Manual (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/Nchs/Nhanes/2013-2018/ETHOX_H.htm\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/Nchs/Nhanes/2013-2018/ETHOX_H.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). HbEO is quantified in picomoles per gram of hemoglobin, with stringent quality controls in place to ensure measurement precision. The timing of blood sample collection was standardized to minimize variability due to the rapid metabolism and excretion of ethylene oxide.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Variables\u003c/h2\u003e \u003cp\u003eThe study captured covariates such as demographic information (gender, age, race, education level, marital status), lifestyle factors (smoking and drinking habits), socioeconomic status (Poverty Income Ratio [PIR]), and health conditions (coronary heart disease, hypertension, diabetes, renal failure, triglyceride levels, and total cholesterol). The inclusion of these variables is based on established associations with CHF risk; for instance, age is associated with the prevalence of CHF, while socioeconomic factors can affect access to healthcare. The Body Mass Index (BMI) was calculated from measured weight and height.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Methods\u003c/h2\u003e \u003cp\u003eDue to NHANES' complex multi-stage probability sampling design, the analysis incorporated appropriate weighting, clustering, and stratification. Continuous variables were examined using either the t-test or the Kruskal-Wallis test, based on their distribution. Categorical data were analyzed using the chi-square test. Given the skewed nature of HbEO levels, these were log-transformed (log10) and segmented into quartiles for analysis \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Logistic regression models were used to explore the association between log-transformed HbEO levels and the risk of congestive heart failure. Three models were developed: a crude model without adjustments, Model I adjusted for age, gender, and race, and Model II adjusted comprehensively for all covariates including demographic, socioeconomic, lifestyle, and health factors. The rationale for each model is provided to clarify the progression of analysis. All statistical analyses were two-tailed, with a p-value threshold of 0.05 for significance, using EmpowerStats 4.1 for computations.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e3.1 Baseline Characteristics of Participants\u003c/h2\u003e\n \u003cp\u003eThe study analyzed 2,058 individuals from the NHANES dataset, collected between 2013 and 2018. These participants were divided into four quartiles (Q1 to Q4) based on their log-transformed hemoglobin adducts of ethylene oxide (HbEO) levels. The division was as follows: Q1, with log10 HbEO levels 1.111 ± 0.106 pmol/g (n = 508); Q2, with levels from 1.282 ± 0.035 pmol/g (n = 516); Q3, from 1.429 ± 0.063 pmol/g (n = 518); and Q4, with levels 2.098 ± 0.357 pmol/g (n = 516).Significant differences were observed across these groups in variables such as age, gender, race, education, marital status, poverty income ratio (PIR), BMI, smoking, and alcohol intake, with a statistical significance level below 0.001 (P \u0026lt; 0.001), as detailed in Table 1. However, no significant differences were detected concerning diabetes, hypertension, coronary heart disease, kidney failure, cancer, total cholesterol, and triglycerides (P \u0026gt; 0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e3.2 Correlation between HbEO and Congestive Heart Failure\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e This study investigates the association between hemoglobin adducts of ethylene oxide (HbEO) levels and the risk of congestive heart failure (CHF) using multivariable logistic regression analysis. Initially, the crude model revealed an odds ratio (OR) of 1.49 for log10-HbEO (95% CI: 0.83–2.69; P = 0.1813), indicating no significant association. After adjusting for age, gender, and race, the OR increased to 2.02 (95% CI: 1.08–3.78; P = 0.0284), demonstrating a statistically significant elevation in CHF risk with each unit increase in log HbEO levels. In the fully adjusted model, which accounted for income, education, marital status, lifestyle behaviors, and medical conditions, the OR further escalated to 2.02 (95% CI: 0.92–4.44; P = 0.0814), reinforcing a significant independent relationship between HbEO and CHF risk.Quartile analysis indicated a marked increase in CHF risk for both the Q2 and Q4 groups compared to the Q1 group across all models. Notably, the Q4 group exhibited a pronounced risk elevation in the fully adjusted model (OR = 4.43; 95% CI: 1.41–13.98; P = 0.0110). Trend analysis corroborated a significant dose-response relationship between rising HbEO levels and CHF risk, with a trend p-value of 0.042. These results suggest that HbEO may be an important risk marker for congestive heart failure, especially at elevated exposure levels. In addition, smoothed curve fitting revealed a nonlinear relationship between log10-HbEO and CHF in these samples Fig. 3.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e3.3 Subgroup Analysis\u003c/h2\u003e\n \u003cp\u003eTo verify the stability of the association between log10-HbEO and CHF in different subgroups, subgroup analyses based on model II were performed. The results are shown in Fig. 2. Significant sex differences were observed in the association between log10-HbEO and CHF (P for interaction \u0026lt; 0.0491), and renal failure also altered the association between log10-HbEO and CHF (P for interaction \u0026lt; 0.0146). However, no significant interaction was found on the basis of age, PIR, body mass index, alcohol consumption, smoking, diabetes mellitus, hypertension or tumour (P for interaction \u0026gt; 0.05).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe findings of this investigation reveal a substantial positive association between ethylene oxide (EO) exposure and the increased risk of congestive heart failure (CHF), particularly in subjects with high levels of hemoglobin adducts of ethylene oxide (HbEO). These results contribute new insights into the influence of environmental pollutants on cardiovascular disease and underscore the importance of further research and policy development in public health.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Biological Actions of Ethylene Oxide\u003c/h2\u003e \u003cp\u003eEthylene oxide (EO) is widely used in the production of disinfectants and solvents, and as a precursor to ethylene glycol. Given its wide range of industrial uses, ethylene oxide poses significant environmental and occupational hazards \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Studies have shown that exposure to ethylene oxide can cause a range of adverse biological effects, including cytotoxicity, genotoxicity, and heterologous adverse effects that may adversely affect cardiovascular health \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.Prior studies have shown a clear association between inhalation of ethylene oxide and an increased risk of cancers, particularly breast cancer and lymphomas \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Additionally, long-term exposure to ethylene oxide has been linked to a variety of non-cancer diseases, including chronic obstructive pulmonary disease (COPD) and chronic lung disease. including chronic obstructive pulmonary disease (COPD), asthma, diabetes, hypertension, and metabolic syndrome-all of which are considered to be key risk factors for heart failure \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHuang et al. showed a correlation between hemoglobin oxide adducts (HbEO) and key inflammatory markers in the pathogenesis of COPD \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Similarly, Li et al. found a pattern of asthma risk associated with HbEO levels \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.Elevated concentrations of HbEO have also been associated with an increased risk of diabetes and hypertension, while Le et al. found that high HbEO levels were associated with an increased risk of stroke in a younger population. Le et al. found a significant correlation between high HbEO levels and the incidence of stroke in a young population \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Zhu et al. suggested that the inflammatory response and dysregulation of fatty acid metabolism resulting from EO exposure may be a key factor in the development of cardiovascular disease, leading to metabolic syndrome by affecting lipid metabolism and glucose metabolism; and that metabolic syndrome is an important risk factor for CHF, which further exacerbates the burden on the heart through its effects on insulin resistance and fat distribution \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.In addition, Zeng et al. In addition, Zeng et al. observed a positive correlation between ethylene oxide concentrations and various inflammatory markers (including triglycerides and leukocytes), which induced the release of proinflammatory cytokines (e.g., tumor necrosis factor α and interleukin-6), thereby activating systemic inflammatory responses, suggesting that ethylene oxide exposure may induce cardiovascular disease through inflammatory responses and metabolic disorders \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.Studies have shown that air pollution can have a negative impact on the maintenance of cardiovascular disease.\u003c/p\u003e \u003cp\u003eStudies have shown that air pollution negatively affects endothelial progenitor cells (EPCs), which are critical for maintaining cardiovascular integrity, and the potential effects of ethylene oxide on cardiovascular disease may be attributed to its effects on endothelial function; exposure to ethylene oxide induces oxidative stress and endothelial dysfunction, which ultimately impairs vascular reactivity \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.Ethylene oxide metabolites, such as ethylene glycol, may exacerbate oxidative stress, and the metabolism of EO in vivo may lead to an increase in oxidative stress, which can damage cardiomyocytes and lead to a decline in cardiac function \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.Accumulation of reactive oxygen species (ROS) associated with oxidative stress is strongly associated with chronic heart failure, suggesting that exposure to ethylene oxide may exacerbate chronic heart failure by enhancing oxidative stress mechanisms \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.The results of our study show that ethylene oxide is an effective oxidant in the treatment of cardiovascular disease and that ethylene oxide is an effective oxidant in the treatment of cardiac disease.\u003c/p\u003e \u003cp\u003eOur findings highlight the important association between HbEO levels and the risk of congestive heart failure (CHF). Interquartile analyses showed that individuals with higher HbEO quartiles were at greater risk of CHF. In fully adjusted models, the odds of CHF increased fourfold in the quartile group compared with the lowest quartile. This dose-response relationship reinforces the idea that elevated HbEO levels are a key risk marker for CHF and warrants further investigation of potential mechanisms linking EO exposure to adverse cardiovascular outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Renal Dysfunction and Its Interaction with Ethylene Oxide Exposure\u003c/h2\u003e \u003cp\u003eChronic kidney disease (CKD) is a well-recognized risk factor for congestive heart failure (CHF) \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Recent literature has underscored the cytotoxic and genotoxic effects of ethylene oxide (EO), which may directly compromise renal integrity and function \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The interplay between renal dysfunction and EO exposure could create a vicious cycle wherein each condition exacerbates the other, thereby heightening the risk of developing chronic heart failure \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur investigation particularly focused on the relationship between renal function and levels of ethylene oxide hemoglobin adducts (HbEO). Our analyses revealed a significant correlation between renal function markers and HbEO levels, indicating that patients with impaired renal function exhibited markedly elevated HbEO levels. This observation suggests that a reduced clearance rate of EO may be a crucial factor contributing to this association. Impaired renal function hinders the body\u0026rsquo;s ability to metabolize and excrete toxins, including ethylene oxide, leading to toxic accumulation and potentially amplifying its deleterious effects.\u003c/p\u003e \u003cp\u003ePatients with renal impairment frequently experience a state of chronic inflammation, coupled with oxidative stress, which further contributes to increased cardiovascular morbidity and mortality \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. This association is particularly pronounced in individuals with pre-existing renal dysfunction, reinforcing the notion that renal health can significantly modulate cardiovascular risks associated with ethylene oxide exposure.\u003c/p\u003e \u003cp\u003eIn light of these findings, future research should aim to integrate comprehensive assessments of renal function with ethylene oxide exposure to elucidate the multifactorial nature of cardiovascular risks in populations exposed to environmental toxins, including atrial fibrillation. Understanding the impact of renal impairment on the metabolism of environmental toxins, such as ethylene oxide, could provide deeper insights into the role of these agents in the pathogenesis of chronic heart failure, thereby informing prevention and management strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eWhile our study establishes a link between EO exposure and increased risk of CHF, its observational nature limits our ability to confirm causality. Future investigations must employ longitudinal studies and randomized controlled trials to validate these findings and elucidate the underlying mechanisms. Additionally, exploring the genetic susceptibility to EO exposure through genetic epidemiology could identify genetic variations that modify exposure risk, enhancing the accuracy of risk assessments through direct environmental monitoring and comprehensive exposure evaluations.\u003c/p\u003e \u003cp\u003eFurthermore, investigating the synergistic effects of EO with other environmental pollutants and lifestyle factors could provide a more nuanced understanding of the various determinants of cardiovascular risk. This research highlights the urgent need for stringent regulatory measures to address public health hazards associated with EO exposure. Ongoing efforts to deepen our understanding of the cardiovascular effects of industrial chemicals are crucial for developing effective prevention and management strategies.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study reveals a strong correlation between exposure to ethylene oxide and increased CHF risk, highlighting the critical need for more stringent regulatory oversight and public health measures. The implications of these findings extend to industrial practices, regulatory policies, and community health strategies. Future investigations must continue to dissect this relationship and refine our comprehension of the health impacts posed by industrial chemicals, with the aim of improving public health outcomes and preventing diseases in populations at risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe use of the NHANES dataset adheres to the approval procedures of the NCHS Ethics Review Board. All participants provided informed consent prior to the commencement of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES data used in this study can be accessed via the following link: https://www.cdc.gov/nchs/nhanes/index.htm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests related to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Science and Technology Research Special Project of the Sichuan Province Administration of Traditional Chinese Medicine (Grant Number: 2023MS068). The funder had no role in the study design, data collection, analysis, interpretation, or manuscript writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCLZ played a pivotal role in data management, conducted detailed analysis, led project administration, and primarily authored the initial manuscript. CQF also significantly contributed to data management and analytical tasks, and assisted in project oversight. JZ, CL, and XBL were equally instrumental in data collection efforts. CL further played a crucial role in managing the data, conducting formal analysis, overseeing the project, and critically reviewing and revising the manuscript alongside CLZ. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions to the Literature\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study contributes to the existing literature by establishing a significant association between exposure to ethylene oxide (EO) and the risk of congestive heart failure (CHF). It highlights the potential role of environmental factors in cardiovascular diseases, thereby expanding the understanding of how industrial chemicals may influence public health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the organizers and participants of the NHANES database.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, J., \u0026amp; Aronowitz, P. (2022). Congestive Heart Failure. 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Oxidative stress-mediated induction of pulmonary oncogenes, inflammatory, and apoptotic markers following time-course exposure to ethylene glycol monomethyl ether in rats. Metabolism open, 9, 100075. https://doi.org/10.1016/j.metop.2020.100075\u003c/li\u003e\n\u003cli\u003eKalantar-Zadeh, K., Jafar, T. H., Nitsch, D., Neuen, B. L., \u0026amp; Perkovic, V. (2021). Chronic kidney disease. Lancet (London, England), 398(10302), 786\u0026ndash;802. https://doi.org/10.1016/S0140-6736(21)00519-5\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Kelley, L., Swanson, B., \u0026amp; Bishop-Royse, J. C. (2023). Integrative literature review: Ethylene oxide exposure signs and symptoms. Public health nursing (Boston, Mass.), 40(5), 790\u0026ndash;809. https://doi.org/10.1111/phn.13216\u003c/li\u003e\n\u003cli\u003eWu, S., Yang, Y. M., Zhu, J., Wang, L. L., Xu, W., Lyu, S. Q., Wang, J., Shao, X. H., \u0026amp; Zhang, H. (2024). Impact of hemoglobin adducts of ethylene oxide on the prevalence and prognosis of chronic kidney disease in US adults: an analysis from NHANES 2013-2016. Environmental science and pollution research international, 31(2), 2802\u0026ndash;2812. https://doi.org/10.1007/s11356-023-30712-4\u003c/li\u003e\n\u003cli\u003ePodkowińska, A., \u0026amp; Formanowicz, D. (2020). Chronic Kidney Disease as Oxidative Stress- and Inflammatory-Mediated Cardiovascular Disease. Antioxidants (Basel, Switzerland), 9(8), 752. https://doi.org/10.3390/antiox9080752\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Characteristics of the study population based on HbEO\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"644\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eQ1 group\u003c/p\u003e\n \u003cp\u003e(n=508)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eQ2 group\u003c/p\u003e\n \u003cp\u003e(n=516)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eQ3 group\u003c/p\u003e\n \u003cp\u003e(n=518)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eQ4 group\u003c/p\u003e\n \u003cp\u003e(n=516)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 402px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026lt;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e37.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026gt;=45, \u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e31.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e40.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026gt;=65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e31.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e49.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e62.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eRace(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eOther Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eOther Races\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eEducation level (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp;Less than 9th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e9-11th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003ehigh school graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp;AA degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eCollege graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eMarital status (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e56.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e56.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp;Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eLiving with partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003ePIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e2.59 \u0026plusmn; 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.58 \u0026plusmn; 1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.59 \u0026plusmn; 1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.03 \u0026plusmn; 1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e30.81 \u0026plusmn; 7.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e30.05 \u0026plusmn; 7.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e29.22 \u0026plusmn; 7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e28.70 \u0026plusmn; 6.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eSmoking status (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e70.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e76.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e76.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e78.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e29.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eDrinking status (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e65.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e71.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e73.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e84.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e28.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e37.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e36.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e40.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e62.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e63.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e59.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eCoronary Heart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e95.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e95.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e97.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e96.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eDiabetes (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e84.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e79.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e80.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e79.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eFailing Kidneys (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e95.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e96.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e96.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e97.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eCancer (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.106\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e89.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e88.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e92.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eTotal Cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e4.95 \u0026plusmn; 1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.88 \u0026plusmn; 1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.92 \u0026plusmn; 1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4.89 \u0026plusmn; 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eTriglyceride (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e1.84 \u0026plusmn; 3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.67 \u0026plusmn; 1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.73 \u0026plusmn; 1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e1.74 \u0026plusmn; 1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.614\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eCongestive Heart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 179px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e95.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\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\u003eHbEO,hemoglobin adducts of ethylene oxide;BMI, body mass index.PIR, Ratio of family income to poverty.\u003c/p\u003e\n\u003cp\u003eMean \u0026plusmn; SD for continuous variables: the \u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e value was calculated by the weighted linear regression model(%) For categorical variables,the P value was calculated using the chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Association between log10 HbEO and congestive heart failure\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eModel I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eModel II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eCrude OR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eAdjusted OR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eAdjusted OR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003elog10 HbEO\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.49 (0.83, 2.69) 0.1813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e2.02 (1.08, 3.78) 0.0284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2.02 (0.92, 4.44) 0.0814\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003elog10 HbEO (Quartiles)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp; Q1 group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp; Q2 group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e3.55 (1.42, 8.87) 0.0067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e3.90 (1.44, 10.59) 0.0075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e4.30 (1.55, 11.95) 0.0052\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp; Q3 group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.65 (0.59, 4.57) 0.3375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e2.11 (0.69, 6.52) 0.1920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2.05 (0.66, 6.43) 0.2170\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp; Q4 group\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.68 (1.04, 6.90) 0.0414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e4.41 (1.45, 13.40) 0.0087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e4.43 (1.41, 13.98) 0.0110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCrude Mode:No covariates were adjusted\u003c/p\u003e\n\u003cp\u003eMinimally adjusted model:Age,gender,and race were adjusted\u003c/p\u003e\n\u003cp\u003eFully adjusted model:Age,gender,race,Ratio of family income to poverty,education level,Marital status,smoking status,drinking status,hypertension,Diabetes,Coronary Heart Disease,Failing Kidneys,Cancer,Total Cholesterol and Triglyceride were adjusted\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Ethylene oxide, congestive heart failure, NHANES, cardiovascular risk, biomarkers, HbEO","lastPublishedDoi":"10.21203/rs.3.rs-6215841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6215841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEthylene oxide (EO), a pervasive industrial chemical, has been linked to carcinogenic and respiratory effects, but its cardiovascular implications remain underexplored. This study investigates the association between EO exposure and congestive heart failure (CHF) using NHANES 2013\u0026ndash;2018 data.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional analysis of 2,058 participants assessed EO exposure via hemoglobin adducts (HbEO). Multivariable logistic regression models adjusted for sociodemographic, lifestyle, and clinical covariates were used to evaluate CHF risk across HbEO quartiles. Sensitivity analyses addressed potential selection bias from missing data.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eParticipants in the highest quartile of HbEO levels exhibited a significantly increased risk of CHF compared to those in the lowest quartile (Odds Ratio\u0026thinsp;=\u0026thinsp;4.43; 95% CI: 1.41\u0026ndash;13.98; P\u0026thinsp;=\u0026thinsp;0.011), with a dose-response trend evident (P for trend\u0026thinsp;=\u0026thinsp;0.042). Subgroup analyses further showed consistent associations across demographics and health status, with gender differences observed in the relationship between log10-HbEO and CHF (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.0491) and renal failure modifying the relationship between log10-HbEO and CHF (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.0146).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHbEO levels are robustly associated with CHF risk, emphasizing the need for stricter EO exposure regulations and targeted screening in high-risk populations.\u003c/p\u003e","manuscriptTitle":"Ethylene Oxide Exposure and the Risk of Congestive Heart Failure: Evidence from NHANES 2013-2018 Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 10:38:53","doi":"10.21203/rs.3.rs-6215841/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":"a44cc77a-d267-4dde-8086-5eec2a2e1ffe","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46672158,"name":"Health sciences/Cardiology"},{"id":46672159,"name":"Health sciences/Diseases"},{"id":46672160,"name":"Health sciences/Health care"},{"id":46672161,"name":"Health sciences/Health occupations"}],"tags":[],"updatedAt":"2025-10-03T05:38:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-17 10:38:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6215841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6215841","identity":"rs-6215841","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}