The association between the body roundness index and the risk of rheumatoid arthritis: a cross-sectional study based on NHANES

The association between the body roundness index and the risk of rheumatoid arthritis: a cross-sectional study based on NHANES | 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 The association between the body roundness index and the risk of rheumatoid arthritis: a cross-sectional study based on NHANES Zhou Zheng, Huaguo Wang, Xiang Chen, Ruizhou Chen, Xinyi Wu, Longcha Liu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5339298/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 Objective: There is increasing evidence of an association between rheumatoid arthritis (RA) and obesity. However, the precise relationship between BRI, a novel indicator of visceral fat, and RA remains unclear. The objective of this study was to investigate the relationship between BRI and RA risk. Methods: A cross-sectional study was conducted using data from the NHANES from 2011 to 2020. A logistic regression analysis was employed to investigate the correlation between the BRI and RA risk, and restricted cubic splines (RCS) and fitting curve analysis were used to capture the potential non-linear relationship. Furthermore, a piecewise two-stage logistic regression model combined with smoothing techniques was employed to explore the potential threshold effect of BRI on RA risk. Results: A total of 6.25% (830/13,273) of the 13,273 participants aged 20 and above included in the study were diagnosed with RA. The adjusted OR values for BRI and RA in Q2 (3.666, 4.924), Q3 (4.924, 6.477), and Q4 (6.470, 20.970) were compared with those for individuals with lower BRI-Q1 (1.049, 3.666). The ORs for the remaining categories were 1.22 (95% CI: 0.91–1.64, p = 0.181), 1.64 (95% CI: 1.25–2.17, p < 0.001) and 2.04 (95% CI: 1.55–2.70, p < 0.001), respectively. The results of the trend analysis showed that the adjusted OR for the trend was 1.28 (95% CI: 1.18–1.38, P < 0.001). The results of the RCS analysis indicated a significant linear correlation between the risk of RA and increasing BRI ( p -value for the overall <0.001, p -value for non-linearity = 0.627). A sensitivity analysis demonstrated that when BRI was treated as a continuous variable, the observed association remained, with an adjusted OR of 1.12 (95% confidence interval: 1.08-1.15, P < 0.001). Subgroup analysis indicated that BRI interacted with smoking status, age and marital status, with never smokers, those under 50 and those living with a partner being more susceptible to BRI. Conclusions: A significant positive correlation was observed between the risk of RA and BRI, particularly in individuals who had never smoked, were under the age of 50, and living with a partner. It is proposed that maintaining an appropriate BRI may contribute to a reduction in the incidence of RA. Health sciences/Health care Health sciences/Rheumatology Rheumatoid Arthritis Body Roundness Index Obesity Cross-sectional study NHANES Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Rheumatoid arthritis (RA) is a systemic autoimmune disease that is characterised by persistent inflammation of the synovial joints. This ultimately results in joint destruction and deformity 1 . It affects approximately 0.5-1% of the global population 2 , particularly among women and North Americans 3 . The onset and development of RA is a long-term, multi-step process that is influenced by a complex interplay of genetic, environmental, and chance factors 4 . The initial symptoms are typically subtle and may not be immediately apparent, allowing the disease to progress and worsen over time 5 . This ultimately leads to irreversible damage to the joints and other bodily systems, which is the most common medical cause of loss of motor function in American adults 6 . Consequently, early detection and elimination of risk factors are crucial for effectively reducing the incidence of RA. In 2015, after 25 years of follow-up, Marchand et al. finally concluded that long-term weight gain is strongly associated with an increased risk of RA, and that weight gain ≥20 kg can lead to a more than threefold increase in the risk of RA 7 . As obesity may play a key role in inflammatory and autoimmune diseases 8 , an increasing number of studies consider obesity, especially abdominal obesity, as a risk factor for RA 8, 9 . In light of the limitations of body mass index (BMI) in assessing adipose tissue distribution, Thomas et al. proposed the body roundness index (BRI) in 2013 as a means of predicting body fat and visceral adipose tissue volume 10 . BRI is an innovative human body composition indicator that quantifies body roundness based on an elliptical model predicted by human body contours. The method employs eccentricity as a means of determining the ratio of visceral fat to total body fat, thereby providing a more comprehensive distribution of visceral fat and body fat percentage 10 . It has been found to be associated with a variety of diseases, including diabetes, insulin resistance, metabolic syndrome and hyperuricemia 11-13 . However, the precise relationship between BRI and RA remains unclear. The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional survey designed to assess the health and nutritional status of the US population 14 . The objective of this study is to analyse data from the NHANES survey collected between 2011 and 2020 in order to elucidate the association between BRI and RA risk and to provide new ideas and strategies for the prevention and intervention of RA. 2. Materials and Methods 2.1 Study population This cross-sectional study employed data from the NHANES, conducted by the Centers for Disease Control and Prevention between 2011 and 2020. The survey gathers a comprehensive array of health-related data, encompassing demographic characteristics, physical examination results, laboratory findings, and dietary habits. The National Center for Health Statistics obtained approval from the ethics review board prior to gathering this information. Prior to their involvement in NHANES, all participants were required to provide written informed consent. The data is publicly accessible on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm). No further approval from the Institutional Review Board was required for the secondary analysis 15 . The study population comprised individuals aged 20 years or older who completed the survey. The study excluded pregnant women, individuals with missing data in the rheumatoid arthritis questionnaire, those diagnosed with other types of arthritis, and those with missing data on height or waist circumference, as well as other covariates. 2.2 Rheumatoid arthritis In the study questionnaire, participants were asked in MCQ160A if a doctor or other health professional had ever informed them that they had been diagnosed with arthritis. Those who responded in the affirmative were subsequently queried in MCQ195 regarding the specific type of arthritis diagnosed. Those who indicated that they had been diagnosed with rheumatoid arthritis (RA) were classified as having this condition. 2.3 Body Roundness Index In accordance with the formula developed by Thomas et al 16 , the Body Roundness Index(BRI) is calculated as: 364.2 − 365.5 × √(1 − [waist circumference / 2π]^2 / [0.5 × height]^2), where both waist circumference and height are measured in centimetres, the corresponding codes are BMXWAIST and BMXHT, respectively. As there is no reference range for BRI, this study divided BRI into four groups based on quartiles to explore the association between different levels of BRI and RA. 2.4 Covariates The potential covariates identified in the relevant literature were subjected to a comprehensive evaluation 17-19 . These included demographic factors such as gender and age, as well as socioeconomic indicators such as race/ethnicity, education level, marital status, and family income. Lifestyle factors were also taken into account, including physical activity, smoking status, and alcohol consumption. A review of the medical history was also conducted, encompassing conditions such as hypertension, diabetes, and hyperlipidemia Dietary intake data were also considered, encompassing calorie consumption, protein consumption, carbohydrate consumption, fat consumption, caffeine consumption, and fibre consumption. The participants were classified according to their race/ethnicity as Mexican American, non-Hispanic White, non-Hispanic Black, or other races. The participants were classified according to their level of education, which was categorised as less than 9 years, 9 to 12 years, and more than 12 years. The variable of marital status was defined in accordance with the following categories: those who were living with a partner (including those who were married) and those who were living alone. In accordance with a report published by the US government, family income was classified into three categories based on the poverty income ratio (PIR): low (PIR ≤ 1.3), medium (PIR > 1.3 to 3.5), and high (PIR > 3.5) 20 . Physical activity was classified into four distinct categories: moderate, vigorous, sedentary, and other. The term "moderate" denotes engagement in sporting or fitness activities that result in a moderate elevation of breathing or heart rate, amounting to a minimum of 10 consecutive minutes on a typical weekly basis. The term "vigorous" is defined as engagement in sports or fitness activities that cause a significant increase in breathing or heart rate, for a minimum of 10 consecutive minutes within a typical week. The term 'sedentary' is used to describe an individual who spends the majority of their time seated, with a minimum of 570 minutes spent in this position on a typical day 21 . This definition excludes any activities that could be classified as either moderate or vigorous. Any activities that do not align with the aforementioned classifications are classified as "other". The participants were classified according to their smoking status, which was divided into three categories: never smokers (those who had smoked less than 100 cigarettes), former smokers (those who had smoked more than 100 cigarettes and had ceased smoking), and current smokers (those who had smoked more than 100 cigarettes and were still smoking). The classification of drinking status comprises three categories: non-drinkers, who rarely consume alcohol (having less than 12 drinks per year); occasional drinkers, who drink more often than once a month but less frequently than once a week; and frequent drinkers, who have alcohol more than once a week. The identification of hypertension and diabetes was based on responses to questions in the questionnaire regarding whether the participants had been informed by a medical professional of such conditions. A diagnosis of hyperlipidemia is made when serum triglyceride concentrations reach 150 mg/dL or above, total cholesterol is 200 mg/dL or above, LDL cholesterol is 130 mg/dL or above, and HDL cholesterol is 40 mg/dL or below in males and 50 mg/dL or below in females. Alternatively, a diagnosis may be made if the patient is taking medication to lower cholesterol levels (lipid-lowering medication) 22 . Dietary intake data are obtained through a 24-hour recall interview, which is a method of estimating food and beverage consumption from midnight to midnight. This process entails the documentation of the specific types and quantities of all foods and beverages consumed, including water, over the designated period. Subsequently, the data is subjected to analysis in order to ascertain the intake of energy and nutrients, as well as other components, utilising the tools of nutritional analysis. 2.5 Statistical analyses In this retrospective analysis of publicly available datasets, categorical data are expressed as percentages n(p%), whereas continuous data are reported either as the Mean (± standard deviation, SD) for normally distributed variables or as the Median (interquartile range, IQR) for non-normally distributed variables. Group comparisons were conducted using an independent-samples t-test for parametric data, the Kruskal-Wallis test for non-parametric data, and the chi-square test for categorical variables. A logistic regression analysis was conducted to calculate the odds ratios (OR) with their corresponding 95% confidence intervals (CI), with the objective of assessing the association between the BRI and RA. Additionally, we employed RCS regression with knots positioned at the 5th, 35th, 65th, and 95th percentiles of the BRI distribution to evaluate the potential nonlinear relationship between BRI and RA, and to model the dose-response association between the two while adjusting for all potential covariates. Moreover, we conducted curve fitting to examine the correlation between BRI and the prevalence of RA. Finally, we employed a piecewise two-stage logistic regression model with smoothing techniques, supported by the likelihood-ratio test and bootstrap resampling method, to investigate the potential threshold effects of BRI on RA and to identify any inflection points. In the sensitivity analysis, BRI was treated as a continuous variable, and the relationship between BRI and RA was explored. Furthermore, subgroup analyses were conducted to ascertain the modifying effects on the relationship between BRI and RA, including variables such as gender, age (less than 50 years vs. 50 years or older), marital status (living with a partner vs. living alone), education level (less than 9 years vs. 9 years or more), family income (per capita income ratio PIR ≤1.3 vs. PIR >1.3), smoking status (never smoker vs. former or current smoker), drinking status (non-drinkers vs. occasional or frequent drinkers), hypertension (normal blood pressure vs. hypertension), diabetes (normal blood glucose vs. prediabetes or diabetes), and hyperlipidemia (normal blood lipids vs. hyperlipidemia). To assess heterogeneity among the subgroups and explore interactions between these and BRI, we employed a multivariate logistic regression and a likelihood ratio test. All statistical analyses were conducted using the DecisionLinc software,version 1.0, in conjunction with the R programming environment, version 4.3.3, accessible via the R Project for Statistical Computing website (http://www.R-project.org, R Foundation, Shanghai, China). The last access record was on 1 September 2024. The determination of statistical significance was based on two-tailed P -values, with a threshold set at P < 0.05. The data analysis was conducted over the period between 1 February 2024 and 30 August 2024. 3. Results 3.1 Study Population A total of 45,462 participants completed the interview, of whom 19,182 were under the age of 20. The following exclusions were made: pregnant women (n = 279), incomplete arthritis questionnaire responses (n = 1,975), diagnoses of other arthritis conditions (n = 3,860), absence of height or waist circumference data (n = 2,091), and missing covariate information (n = 4,802). Consequently, the cross-sectional analysis incorporated data from 13,273 participants in the NHANES, conducted between 2011 and 2020. Of the total number of participants, 830 (6.25%) were diagnosed with RA. A comprehensive illustration of the inclusion and exclusion criteria is provided in Figure 1 . 3.2 Baseline Characteristics Table 1 presents the baseline characteristics of the study population, categorised according to the presence of RA. In general, individuals with RA exhibit higher BRI, older age, greater excessive caffeine intake, and lower intake of calories, protein, carbohydrates, fats, and fibre, in comparison to those without RA. Furthermore, there is a higher prevalence of RA among females, Non-Hispanic Blacks, individuals with lower education levels, those living alone, people with lower incomes, less physically active individuals, smokers, those with lower frequency of alcohol consumption, hypertensive patients, diabetic patients, and patients with hyperlipidemia. 3.3 Relationship between BRI and RA The univariate analysis demonstrated that BRI, age, gender, marital status, race, family income, physical activity, smoking status, drinking status, hypertension, diabetes, hyperlipidemia, calorie consumption, protein consumption, carbohydrate consumption, fat consumption, caffeine consumption, and fibre consumption are associated with RA, as presented in Table 2 . Upon categorising BRI into quartiles for analysis, a significant positive association between BRI and RA was identified, after adjusting for all potential confounding variables. Compared to individuals in the lower BRI Q1 [1.049, 3.666], the adjusted odds ratios (OR) for the association between BRI and RA in the Q2 (3.666, 4.924], Q3 (4.924, 6.477], and Q4 [6.477, 20.970] were 1.22 (95% CI: 0.91-1.64, p=0.181), 1.64 (95% CI: 1.25-2.17, p<0.001), and 2.04 (95% CI: 1.55-2.70, p<0.001), respectively ( Table 3 ). The RCS analysis revealed a linear relationship between BRI and RA ( p -value for the overall <0.001, p -value for non-linearity = 0.627) ( Figure 2 ). Additionally, curve fitting analysis demonstrated a positive correlation between BRI and the prevalence of RA ( Figure 3 ). The threshold analysis indicated that participants with a BRI below 6.22 had an odds ratio (OR) of 1.17 (95% CI: 1.08-1.27, p < 0.001) for developing RA, while those with a BRI of 6.22 or higher had an OR of 1.09 (95% CI: 1.04-1.14, p < 0.001) (Table 4). The log-likelihood ratio test P -value of 0.194 between the models estimated above and below the threshold of 6.22 provides evidence in favour of a linear relationship between BRI and RA, indicating the absence of significant inflection points. 3.4 Sensitivity Analysis In the sensitivity analysis, the BRI was treated as a continuous variable. The results consistently indicated a significant positive correlation between BRI and RA in models adjusted for different covariates. The correlation coefficients were 1.16 (95% CI: 1.13-1.19, p <0.001), 1.16 (95% CI: 1.12-1.19, p <0.001), and 1.12 (95% CI: 1.08-1.15, p <0.001), respectively ( Table 3 ). 3.5. The subgroup analysis and interaction test A series of subgroup analyses was conducted to assess potential effect modifications in the association between the BRI and RA. After stratifying by gender, education level, family income, drinking status, hypertension, diabetes, and hyperlipidemia, no significant interactions were identified within any of the subgroups (P > 0.05). Nevertheless, the subgroup analysis did reveal an interactive effect between BRI and specific factors, including smoking status, age, and marital status. Specifically, never-smokers, individuals under the age of 50, and those living with a partner demonstrated a heightened vulnerability to the effects of BRI ( Figure 4 ). Furthermore, through the utilisation of visualisation techniques, we conducted a more in-depth investigation into the interactive effects between BRI and a range of variables, including smoking status, age, and marital status ( Figure 5, Figure 6, Figure 7 ). 4. Discussion The findings of this cross-sectional study demonstrate a statistically significant positive correlation between the BRI and an elevated risk of developing RA. In all models that were adjusted for a variety of variables, the correlation remained significant, which lends support to the reliability of BRI as a potential risk predictor for RA. The results of the RCS and threshold analysis indicated a linear relationship between BRI and RA risk. The results of the sensitivity analysis demonstrate that there is an 12% increase in the risk of RA for every unit increase in BRI. Moreover, the subgroup analysis revealed that individuals who have never smoked, those under the age of 50, and those living with a partner exhibited heightened vulnerability to BRI. To the best of our knowledge, this is the inaugural study to examine the correlation between BRI and the risk of developing RA. It can therefore be surmised that the reduction of adipose tissue, particularly visceral fat, through the implementation of a regular exercise regime and the maintenance of a healthy body weight may prove an effective method of reducing the risk of developing RA. Over the past three decades, there has been a marked increase in the prevalence of overweight and obesity among adults globally, representing a significant challenge to public health 23 . The expansion of abnormal adipose tissue, particularly visceral fat, has the capacity to secrete inflammatory and lipid factors that disrupt homeostatic processes, thereby leading to pathological alterations such as oxidative stress, cellular proliferation and insulin resistance 24, 25 . The most commonly used measure of obesity, BMI, is limited in its ability to assess the specific distribution of adipose tissue 26 . A meta-analysis has demonstrated that BRI is a more effective predictor than waist-to-hip ratio, BMI and body fat percentage in identifying obesity, cardiovascular disease, insulin resistance and metabolic syndrome 3, 27 . A cross-sectional study conducted in the UK has indicated that a higher waist circumference is associated with a higher prevalence of RA. This relationship persists even after adjustment for BMI, which underscores the potential significance of central obesity in autoimmune diseases such as RA 28 . Additionally, there is a positive correlation between adipose tissue mass and the risk of developing RA 29 . Furthermore, a notable increase in BMI has been linked to the development of osteoarthritis in the knee and hip joints 30 . The above research is consistent with our findings. Although there is a growing body of literature on RA and obesity, there is still a gap in the field regarding the relationship between BRI and RA. In light of these considerations, the potential of BRI as a predictor of RA risk is substantial, given its status as a newly developed obesity index. It is widely accepted that visceral fat cells represent the primary source of pro-inflammatory cytokines and chemokines (such as IL-8, IL-1, IL-6, and TNF-α) in obese individuals 31 . Moreove, adipocytes are capable of producing adipokines, including adiponectin and leptin, which can result in oxidative stress and dyslipidemia within the body 32 . As demonstrated by Hojgaard, elevated levels of these biomessengers in obese subjects result in sustained inflammation within the body 33 . The following pathophysiological processes may increase the risk of RA in individuals with obesity: Firstly, interleukin-1 (IL-1), interleukin-6 (IL-6) and tumour necrosis factor alpha (TNF-α) have been demonstrated to stimulate the production of autoantibodies and the activation of inflammatory cells 34 . These, in turn, together with fibroblast-like synoviocytes, activate osteoclasts, which results in persistent synovitis and joint destruction 35 . Secondly, the differentiation of T cells into a pro-inflammatory phenotype is affected due to the dysregulation of adipokines and impaired resolution of inflammation 36 , which leads to persistent synovitis and joint destruction 37 . Thirdly, there is evidence that obesity is involved in the activation of the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome, which has been demonstrated to promote the production of pro-inflammatory cytokines, thereby exacerbating RA 38 . Furthermore, the activation of the NLRP3 inflammasome is associated with insulin resistance, which leads to various metabolic disorders and exacerbates systemic inflammation, thereby indirectly affecting the onset of RA 39 . Finally, an inverse relationship has been identified between adiposity and circulating 25-hydroxyvitamin D concentrations 40 , while a positive association exists with serum estradiol levels 41 . The presence of insufficient vitamin D and elevated estrogen levels has been correlated with heightened susceptibility to multiple autoimmune conditions 42 , suggesting that these hormonal imbalances may be instrumental in the pathogenesis of RA. A Mendelian randomization analysis indicated that interventions to reduce smoking and excessive obesity can significantly reduce the risk of RA 43 . The findings of this study are in alignment with the current results. Moreover, significant interactive effects between BRI and specific factors, including smoking status, age, and marital status, were identified through subgroup analyses. In particular, never-smokers, individuals under the age of 50, and those living with a partner exhibited a greater susceptibility to the influence of BRI, and the association between BRI and the risk of RA was stronger. This study represents the inaugural multicentre, large-sample cross-sectional investigation to examine the correlation between the BRI and the risk of RA. It possesses several notable advantages. Firstly, the data for this study are derived from the NHANES, a reliable and comprehensive dataset with a large sample size. Secondly, three distinct logistic regression models were constructed, with various confounding variables adjusted, thus ensuring the reliability of the results. Thirdly, comprehensive subgroup analyses were conducted, with all other covariates adjusted in each analysis to ensure the generalisability of the findings. In conclusion, this pioneering study has identified the potential of BRI as a predictor for RA risk. However, it is important to acknowledge the limitations of the study. Firstly, the cross-sectional design of this study precludes the possibility of establishing a causal relationship between BRI and the risk of RA. Secondly, the presence or absence of RA in this study was determined based on a questionnaire survey. It is important to note that the response rate of NHANES has decreased from 76.62% to 48.24% over the past two decades 44 . This may introduce some recall bias and nonresponse bias, which could affect the reliability of the data. Thirdly, although regression models, stratified analyses and sensitivity analyses were employed to minimise bias, it remains a significant challenge to completely eliminate the influence of confounding factors. The results of this study encourage the further investigation of BRI as a potential indicator for assessing the risk of RA. However, the validation of these findings is contingent upon the undertaking of more detailed and in-depth studies in the future. Conclusion The findings of our study demonstrate a statistically significant positive linear correlation between BRI and the risk of RA in the US adult population. This effect is more pronounced among three groups: non-smokers, individuals under the age of 50, and those living with a partner. The objective of this study is to enhance public awareness of BRI as a novel measure of obesity and to elucidate the correlation between visceral fat, as represented by BRI, and the risk of RA. Moreover, the study seeks to promote the maintenance of a healthy body habitus as a means of reducing the incidence of RA. Declarations Supplementary Materials The following supplementary information is available for reference: Table S1: Association of Covariates with Rheumatoid Arthritis Risk, Adjusted for All Variables. Author contributions Conceptualization, Z.Z., H.W., and X.C.; Methodology, Z.Z., H.W., and C.F.; Software, M.H.; Validation, L.L. and C.F.; Formal analysis, Z.Z. and H.W.; Investigation, X.C. and L.L.; Resources, M.H.; Data curation, Z.Z., H.W., and R.C.; Writing—original draft preparation, Z.Z.; Writing—review and editing, H.W., X.C., and X.W.; Visualization, L.L.; Supervision, C.F.; Project administration, M.H.; Funding acquisition, M.H. All authors have contributed to the article and have read and agreed to the published version of the manuscript. Funding The work was supported by the China Science and Technology Administration of Wenzhou (Y20220730) and the key laboratory of clinical laboratory diagnosis and transformation research of Zhejiang province (2022E10022) . Institutional Review Board Statement Ethical review and approval were waived for this study because no additional institutional review board approval was required for the secondary analysis. Informed Consent Statement The authorization for NHANES was granted by the Ethics Review Committee of the National Center for Health Statistics (NCHS), with all participants having signed written informed consent forms prior to their participation. Data availability Statement The publicly accessible datasets utilized in this study are available online. The names of the repositories and their respective access codes can be found online at http://www.cdc.gov/nchs/nhanes.htm Acknowledgments We greatly appreciate all of the study participants. 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Diabetes 2007, 56 (7), 1761-72. So, A. K.; Martinon, F., Inflammation in gout: mechanisms and therapeutic targets. Nat Rev Rheumatol 2017, 13 (11), 639-647. Ye, Q.; Yan, T.; Shen, J.; Shi, X.; Luo, F.; Ren, Y., Sulforaphene targets NLRP3 inflammasome to suppress M1 polarization of macrophages and inflammatory response in rheumatoid arthritis. J Biochem Mol Toxicol 2023, 37 (7), e23362. Wortsman, J.; Matsuoka, L. Y.; Chen, T. C.; Lu, Z.; Holick, M. F., Decreased bioavailability of vitamin D in obesity. Am J Clin Nutr 2000, 72 (3), 690-3. Rohrmann, S.; Shiels, M. S.; Lopez, D. S.; Rifai, N.; Nelson, W. G.; Kanarek, N.; Guallar, E.; Menke, A.; Joshu, C. E.; Feinleib, M.; Sutcliffe, S.; Platz, E. A., Body fatness and sex steroid hormone concentrations in US men: results from NHANES III. Cancer Causes Control 2011, 22 (8), 1141-51. Arnson, Y.; Amital, H.; Shoenfeld, Y., Vitamin D and autoimmunity: new aetiological and therapeutic considerations. Ann Rheum Dis 2007, 66 (9), 1137-42. Zhao, S. S.; Holmes, M. V.; Zheng, J.; Sanderson, E.; Carter, A. R., The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: Mendelian randomization study. Rheumatology (Oxford) 2022, 61 (5), 2167-2175. Zhang, X.; Ma, N.; Lin, Q.; Chen, K.; Zheng, F.; Wu, J.; Dong, X.; Niu, W., Body Roundness Index and All-Cause Mortality Among US Adults. JAMA Netw Open 2024, 7 (6), e2415051. Tables Table 1. Population characteristics by RA status. Variables Overall No Arthritis Rheumatoid Arthritis p -value (N = 13273) (N = 12,443) (N = 830) BRI, Mean (SD) 5.32 ( 2.33) 5.24 ( 2.29) 6.50 ±(2.57) <0.001 Age(years),Median(IQR) 43.00 (31.00 -58.00) 42.00 (30.00 -56.00) 61.00 (51.00 - 69.00) <0.001 CalorieConsumption(kcal/d) 2,006.00 2,021.00 1,844.50 <0.001 Median(IQR) (1,489.00 -2,668.00) (1,499.00 -2,686.00) (1,337.00 - 2,408.00) ProteinConsumption(g/d) 75.33 76.1 64.28 <0.001 Median(IQR) (53.63 - 103.17) (54.36 - 104.02) (46.53 - 91.79) CarbohydrateConsumption(g/d) 235.83 237.44 218.86 <0.001 Median(IQR) (169.47 - 317.33) (170.55 - 319.70) (157.63 - 290.28) FatConsumption(g/d) 75.97 76.35 70.97 <0.001 Median(IQR) (51.42 - 108.00) (51.68 - 108.54) (47.65 - 100.02) CaffineConsumption(mg/d) 90 89 102.5 0.009 Median(IQR) (9.00 - 194.00) (9.00 - 193.00) (14.00 - 206.00) FibreConsumption(g/d) 14.7 14.8 12.75 <0.001 Median(IQR) (9.50 - 22.00) (9.60 - 22.20) (8.40 - 19.20) Gender, n (p%) <0.001 Female 6,426.00 (48.41%) 5,951.00 (47.83%) 475.00 (57.23%) Male 6,847.00 (51.59%) 6,492.00 (52.17%) 355.00 (42.77%) Race/Ethnicity , n (p%) <0.001 Mexican American 1,804.00 (13.59%) 1,706.00 (13.71%) 98.00 (11.81%) Non-Hispanic Black 3,117.00 (23.48%) 2,843.00 (22.85%) 274.00 (33.01%) Non-Hispanic White 4,778.00 (36.00%) 4,478.00 (35.99%) 300.00 (36.14%) Other 3,574.00 (26.93%) 3,416.00 (27.45%) 158.00 (19.04%) Education Level(years), n (p%) <0.001 12 7,962.00 (59.99%) 7,548.00 (60.66%) 414.00 (49.88%) Marital Status, n (p%) 0.041 Living Alone 5,428.00 (40.90%) 5,060.00 (40.67%) 368.00 (44.34%) Living With a partner 7,845.00 (59.10%) 7,383.00 (59.33%) 462.00 (55.66%) Family Income, n (p%) <0.001 PIR 3.5 4,316.00 (32.52%) 4,105.00 (32.99%) 211.00 (25.42%) Physical Activity, n (p%) <0.001 Sedentary 1,088.00 (8.20%) 998.00 (8.02%) 90.00 (10.84%) Moderate activity 3,384.00 (25.50%) 3,156.00 (25.36%) 228.00 (27.47%) Vigorous activity 3,786.00 (28.52%) 3,690.00 (29.66%) 96.00 (11.57%) Other 5,015.00 (37.78%) 4,599.00 (36.96%) 416.00 (50.12%) Smoking Status, n (p%) <0.001 Never 8,073.00 (60.82%) 7,661.00 (61.57%) 412.00 (49.64%) Former 2,634.00 (19.84%) 2,403.00 (19.31%) 231.00 (27.83%) Current 2,566.00 (19.33%) 2,379.00 (19.12%) 187.00 (22.53%) Drinking Status, n (p%) <0.001 Non-drinkers 3,088.00 (23.27%) 2,810.00 (22.58%) 278.00 (33.49%) Occasional drinkers 6,003.00 (45.23%) 5,665.00 (45.53%) 338.00 (40.72%) Frequent drinkers 4,182.00 (31.51%) 3,968.00 (31.89%) 214.00 (25.78%) Hypertension, n (p%) <0.001 Normal 9,441.00 (71.13%) 9,105.00 (73.17%) 336.00 (40.48%) Hypertension 3,832.00 (28.87%) 3,338.00 (26.83%) 494.00 (59.52%) Diabetes, n (p%) <0.001 Normal 10,954.00(82.53%) 10,426.00(83.79%) 528.00 (63.61%) Prediabetes 888.00 (6.69%) 813.00 (6.53%) 75.00 (9.04%) Diabetes 1,431.00 (10.78%) 1,204.00 (9.68%) 227.00 (27.35%) Hyperlipidemia, n (p%) <0.001 Normal 4,686.00 (35.30%) 4,520.00 (36.33%) 166.00 (20.00%) Hyperlipidemia 8,587.00 (64.70%) 7,923.00 (63.67%) 664.00 (80.00%) BRI, Body Roundness Index; SD, Standard Deviation; IQR, Interquartile Range; PIR, Poverty Income Ratio. Mean (SD) for normally distributed variables: the P -value was calculated by independent-samples t-test; Median (IQR) for non-normally distributed variables: the P -value was calculated by Kruskal-Wallis test; n(p%) for categorical variables: the P -value was calculated by chi-square test. Table 2. Association of covariates and RA risk. Variables OR（95%_CI） p -Value Variables OR（95%_CI） p -Value BRI 1.21 (1.18 -1.24) <0.001 Age (years) 1.06 (1.05 -1.06) <0.001 Gender Smoking Status Female 1(Ref) Never 1(Ref) Male 0.69 (0.59 -0.79) <0.001 Former 1.79 (1.51 -2.11) <0.001 Race/Ethnicity Current 1.46 (1.22 -1.74) <0.001 Mexican American 1(Ref) Drinking Status Non-Hispanic White 1.17 (0.93 -1.48) 0.199 Non-drinkers 1(Ref) Non-Hispanic Black 1.68 (1.33 -2.14) <0.001 Occasional drinkers 0.60 (0.51 -0.71) <0.001 Other 0.81 (0.62 -1.05) 0.101 Frequent drinkers 0.55 (0.45 -0.66) <0.001 Education Level(years) Hypertension <9 1(Ref) Normal 1(Ref) 9-12 0.85 (0.70 -1.04) 0.117 Hypertension 4.01 (3.47 -4.64) 12 0.59 (0.50 -0.71) <0.001 Diabetes Marital Status Normal 1(Ref) Living With a partner 1(Ref) Prediabetes 1.82 (1.41 -2.33) <0.001 Living Alone 1.16 (1.01 -1.34) 0.037 Diabetes 3.72 (3.15 -4.39) <0.001 Family Income Hyperlipidemia PIR <= 1.3 1(Ref) Normal 1(Ref) (1.3,3.5] 0.69 (0.58 -0.81) <0.001 Hyperlipidemia 2.28 (1.92 -2.72) 3.5 0.57 (0.48 -0.68) <0.001 Calorie Consumption(kcal/d) 1.00 (1.00 -1.00) <0.001 Physical Activity Protein Consumption (g/d) 0.99 (0.99 -0.99) <0.001 Sedentary 1(Ref) Carbohydrate Consumption(g/d) 1.00 (1.00 -1.00) <0.001 Moderate activity 0.80 (0.62 -1.04) 0.087 Fat Consumption (g/d) 1.00 (1.00 -1.00) <0.001 Vigorous activity 0.29 (0.21 -0.39) <0.001 Caffeine Consumption (mg/d) 1.00 (1.00 -1.00) <0.001 Other 1.00 (0.79 -1.28) 0.98 Fibre Consumption (g/d) 0.98 (0.97 -0.99) <0.001 BRI, Body Roundness Index; PIR , Poverty Income Ratio; OR, odds ratio; CI, confidence interval; Ref: reference. Table 3. Association between BRI and RA. Body Roundness Index(BRI) Model 1 Model 2 Model 3 OR (95% CI) p -Value OR (95% CI) p -Value OR (95% CI) p -Value Continuous 1.16(1.13-1.19) <0.001 1.16(1.12-1.19) <0.001 1.12(1.08-1.15) <0.001 Quartiles Q1[1.049, 3.666] 1(Ref) 1(Ref) 1(Ref) Q2(3.666, 4.924] 1.31(0.99-1.75) 0.063 1.33(1.00-1.78) 0.05 1.22(0.91-1.64) 0.181 Q3(4.924, 6.477] 1.87(1.44-2.46) <0.001 1.89(1.45-2.50) <0.001 1.64(1.25-2.17) <0.001 Q4(6.477, 20.970] 2.68(2.08-3.49) <0.001 2.65(2.04-3.48) <0.001 2.04(1.55-2.70) <0.001 OR for Trend 1.40(1.30-1.52) 1.39(1.29-1.51) 1.28(1.18-1.38) P for Trend <0.001 <0.001 <0.001 Model 1: Adjusted for sociodemographic variables, including age, gender, marital status, race/ethnicity, education level, and family income. Model 2: Adjusted for sociodemographic variables as well as dietary and lifestyle habits, including physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, and caffeine consumption. Model 3: Adjusted for sociodemographic variables, dietary and lifestyle habits, and clinical conditions, including hyperlipidemia, diabetes, and hypertension. Q, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference. Table 4. Threshold effect analysis of the relationship of BRI with rheumatoid arthritis (RA). Body Roundness Index(BRI) Adjusted Model OR (95% CI) p -value <6.22 1.17（1.08-1.27） <0.001 ≥6.22 1.09（1.04-1.14） <0.001 Log-likelihood ratio test 0.194 OR, odds ratio; CI, confidence interval. Adjustments were made for all potential variables, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fiber consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension. Only 99% of the data is displayed. Additional Declarations No competing interests reported. Supplementary Files TableS1AssociationofCovariateswithRheumatoidArthritisRiskAdjustedforAllVariables..docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-5339298","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":379348580,"identity":"3049426e-fd99-4345-8d6e-c47fbba5e09b","order_by":0,"name":"Zhou Zheng","email":"","orcid":"","institution":"First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhou","middleName":"","lastName":"Zheng","suffix":""},{"id":379348581,"identity":"be80de48-58b2-47c1-bced-96b7084aeb0b","order_by":1,"name":"Huaguo Wang","email":"","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Huaguo","middleName":"","lastName":"Wang","suffix":""},{"id":379348583,"identity":"631ab317-9f64-49d9-9006-a81ad56d9867","order_by":2,"name":"Xiang Chen","email":"","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Chen","suffix":""},{"id":379348584,"identity":"c33739e9-c569-493a-85bf-7b722d241bb6","order_by":3,"name":"Ruizhou Chen","email":"","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ruizhou","middleName":"","lastName":"Chen","suffix":""},{"id":379348586,"identity":"033f8aa2-0065-4c6f-a012-691c3e4267e2","order_by":4,"name":"Xinyi Wu","email":"","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Wu","suffix":""},{"id":379348587,"identity":"a6698c1a-d333-424f-9772-8a2cbd4db3e2","order_by":5,"name":"Longcha Liu","email":"","orcid":"","institution":"First Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Longcha","middleName":"","lastName":"Liu","suffix":""},{"id":379348588,"identity":"d7d5f17a-7cec-4d84-bb83-80ca630294af","order_by":6,"name":"Cheng Fu","email":"","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Fu","suffix":""},{"id":379348594,"identity":"3d784aaf-982c-437b-8755-fda8835f1706","order_by":7,"name":"Mingpeng Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACef6G9B+J//7J8bM3EKnFcMaBBxIf2A4YS/YcINaaA4kPJGewHUjccCOBSB2MDYcTjHl47iTOnPl44w2GGptoglrYmdsSknkknhn3S6cVWzAcS8ttIGzLmYTDPAbMsjNn55hJAO0krIXhQP7HZp4EZsYNN88QrSUhmXHGgcOKG27wEKkFGMhpDB8b0oCBDPRLAjF+AUZlGkNigw0wKg9vvPGhxoYIhyEBA4kEUpRDtJCqYxSMglEwCkYGAABbwkXzYE1QdAAAAABJRU5ErkJggg==","orcid":"","institution":"Ruian Hospital of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Mingpeng","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2024-10-27 01:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5339298/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5339298/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71564475,"identity":"45e50668-9052-488c-a1c7-a6cb406975e0","added_by":"auto","created_at":"2024-12-16 17:23:41","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":262745,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of participant selection for the study. Participants were excluded if they were pregnant, had missing data in the rheumatoid arthritis questionnaire, were diagnosed with other types of arthritis, or had missing data on height or waist circumference, along with other covariates.\u003c/p\u003e","description":"","filename":"Figure1.Flowchartofparticipantselectionforthestudy..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/9e789be904b1e939fcf0cf49.jpeg"},{"id":71565138,"identity":"a79b82b9-703a-4d2f-a01b-c4848dfdd81e","added_by":"auto","created_at":"2024-12-16 17:31:41","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125566,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between BRI and RA odds ratio. Solid and dashed lines in the figure represent the predicted values and the 95% confidence intervals, respectively. Adjustments were made for all potential variables, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension. Only 99% of the data is displayed.\u003c/p\u003e","description":"","filename":"Figure2.AssociationbetweenBRIandRAoddsratio..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/d5beb778722ca4150d1d2a4a.jpeg"},{"id":71564476,"identity":"c44e0279-7de2-41e3-905f-bde1cd428aba","added_by":"auto","created_at":"2024-12-16 17:23:42","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58992,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between BRI and the prevalence of RA. Solid and dashed lines in the figure represent the predicted values and the 95% confidence intervals, respectively. Adjustments were made for all potential variables, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension.\u003c/p\u003e","description":"","filename":"Figure3.AssociationbetweenBRIandtheprevalenceofRA..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/cf778b83b22484fd80644a54.jpeg"},{"id":71564480,"identity":"07b25ae6-fa91-4e46-ba4f-32a201f7fc44","added_by":"auto","created_at":"2024-12-16 17:23:43","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3057218,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis forest plot of the relationship between BRI and RA. Except for the stratification component itself, each stratification factor was adjusted for all other variables (age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption，hyperlipidemia, diabetes, and hypertension).\u003c/p\u003e","description":"","filename":"Figure4.SubgroupanalysisforestplotoftherelationshipbetweenBRIandRA..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/40c29d2491e6e02d471e8492.jpeg"},{"id":71564479,"identity":"e48dc7f5-84b1-483c-8764-d11a223b9863","added_by":"auto","created_at":"2024-12-16 17:23:42","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":194871,"visible":true,"origin":"","legend":"\u003cp\u003eThe interactive effect of BRI with smoking status. Adjustments were made for all potential variables except for smoking status itself, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension.\u003c/p\u003e","description":"","filename":"Figure5.TheinteractiveeffectofBRIwithsmokingstatus..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/3496775da4a1a9d2b1d2685f.jpeg"},{"id":71564478,"identity":"c20ffe9b-7161-4e00-90f3-46087c704ec4","added_by":"auto","created_at":"2024-12-16 17:23:42","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":190276,"visible":true,"origin":"","legend":"\u003cp\u003eThe interactive effect of BRI with age. Adjustments were made for all potential variables except for age itself, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension.\u003c/p\u003e","description":"","filename":"Figure6.TheinteractiveeffectofBRIwithage..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/b52c1c8f3e36bad3ef4fcd2c.jpeg"},{"id":71564481,"identity":"d39670d5-d1dc-432e-b859-ce840eb8b7c6","added_by":"auto","created_at":"2024-12-16 17:23:43","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":207928,"visible":true,"origin":"","legend":"\u003cp\u003eThe interactive effect of BRI with marital status. Adjustments were made for all potential variables except for marital status itself, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension.\u003c/p\u003e","description":"","filename":"Figure7.TheinteractiveeffectofBRIwithmaritalstatus..jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/48b13724bc7d81e1f722c927.jpeg"},{"id":72238838,"identity":"b6b21321-718f-4417-b01b-79fa59fb256c","added_by":"auto","created_at":"2024-12-24 06:16:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5001513,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/da33e0c6-c4c2-4379-8f3c-08b688b1e45c.pdf"},{"id":71564482,"identity":"50399caa-a8c2-4586-a131-cdafc65fc61b","added_by":"auto","created_at":"2024-12-16 17:23:43","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":21526,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1AssociationofCovariateswithRheumatoidArthritisRiskAdjustedforAllVariables..docx","url":"https://assets-eu.researchsquare.com/files/rs-5339298/v1/139796a53f7c1205df50bf7e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association between the body roundness index and the risk of rheumatoid arthritis: a cross-sectional study based on NHANES","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRheumatoid arthritis (RA) is a systemic autoimmune disease that is characterised by persistent inflammation of the synovial joints. This ultimately results in joint destruction and deformity\u003csup\u003e1\u003c/sup\u003e. It affects approximately 0.5-1% of the global population\u003csup\u003e2\u003c/sup\u003e, particularly among women and North Americans\u003csup\u003e3\u003c/sup\u003e. The onset and development of RA is a long-term, multi-step process that is influenced by a complex interplay of genetic, environmental, and chance factors\u003csup\u003e4\u003c/sup\u003e. The initial symptoms are typically subtle and may not be immediately apparent, allowing the disease to progress and worsen over time\u003csup\u003e5\u003c/sup\u003e. This ultimately leads to irreversible damage to the joints and other bodily systems, which is the most common medical cause of loss of motor function in American adults\u003csup\u003e6\u003c/sup\u003e. Consequently, early detection and elimination of risk factors are crucial for effectively reducing the incidence of RA.\u003c/p\u003e\n\u003cp\u003eIn 2015, after 25 years of follow-up, Marchand et al. finally concluded that long-term weight gain is strongly associated with an increased risk of RA, and that weight gain \u0026ge;20 kg can lead to a more than threefold increase in the risk of RA\u003csup\u003e7\u003c/sup\u003e. As obesity may play a key role in inflammatory and autoimmune diseases\u003csup\u003e8\u003c/sup\u003e, an increasing number of studies consider obesity, especially abdominal obesity, as a risk factor for RA\u003csup\u003e8, 9\u003c/sup\u003e. In light of the limitations of body mass index (BMI) in assessing adipose tissue distribution, Thomas et al. proposed the body roundness index (BRI) in 2013 as a means of predicting body fat and visceral adipose tissue volume\u003csup\u003e10\u003c/sup\u003e. BRI is an innovative human body composition indicator that quantifies body roundness based on an elliptical model predicted by human body contours. The method employs eccentricity as a means of determining the ratio of visceral fat to total body fat, thereby providing a more comprehensive distribution of visceral fat and body fat percentage\u003csup\u003e10\u003c/sup\u003e. It has been found to be associated with a variety of diseases, including diabetes, insulin resistance, metabolic syndrome and hyperuricemia\u003csup\u003e11-13\u003c/sup\u003e. However, the precise relationship between BRI and RA remains unclear.\u003c/p\u003e\n\u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) is a cross-sectional survey designed to assess the health and nutritional status of the US population\u003csup\u003e14\u003c/sup\u003e. The objective of this study is to analyse data from the NHANES survey collected between 2011 and 2020 in order to elucidate the association between BRI and RA risk and to provide new ideas and strategies for the prevention and intervention of RA.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study employed data from the NHANES, conducted by the Centers for Disease Control and Prevention between 2011 and 2020. The survey gathers a comprehensive array of health-related data, encompassing demographic characteristics, physical examination results, laboratory findings, and dietary habits. The National Center for Health Statistics obtained approval from the ethics review board prior to gathering this information. Prior to their involvement in NHANES, all participants were required to provide written informed consent. The data is publicly accessible on the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm). No further approval from the Institutional Review Board was required for the secondary analysis\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe study population comprised individuals aged 20 years or older who completed the survey. The study excluded pregnant women, individuals with missing data in the rheumatoid arthritis questionnaire, those diagnosed with other types of arthritis, and those with missing data on height or waist circumference, as well as other covariates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Rheumatoid arthritis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the study questionnaire, participants were asked in MCQ160A if a doctor or other health professional had ever informed them that they had been diagnosed with arthritis. Those who responded in the affirmative were subsequently queried in MCQ195 regarding the specific type of arthritis diagnosed. Those who indicated that they had been diagnosed with rheumatoid arthritis (RA) were classified as having this condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Body Roundness Index\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn accordance with the formula developed by Thomas et al\u003csup\u003e16\u003c/sup\u003e, the Body Roundness Index(BRI) is calculated as: 364.2 \u0026minus; 365.5 \u0026times; \u0026radic;(1 \u0026minus; [waist circumference / 2\u0026pi;]^2 / [0.5 \u0026times; height]^2), where both waist circumference and height are measured in centimetres, the corresponding codes are BMXWAIST and BMXHT, respectively. As there is no reference range for BRI, this study divided BRI into four groups based on quartiles to explore the association between different levels of BRI and RA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe potential covariates identified in the relevant literature were subjected to a comprehensive evaluation\u003csup\u003e17-19\u003c/sup\u003e. These included demographic factors such as gender and age, as well as socioeconomic indicators such as race/ethnicity, education level, marital status, and family income. Lifestyle factors were also taken into account, including physical activity, smoking status, and alcohol consumption. A review of the medical history was also conducted, encompassing conditions such as hypertension, diabetes, and hyperlipidemia Dietary intake data were also considered, encompassing calorie consumption, protein consumption, carbohydrate consumption, fat consumption, caffeine consumption, and fibre consumption.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe participants were classified according to their race/ethnicity as Mexican American, non-Hispanic White, non-Hispanic Black, or other races. The participants were classified according to their level of education, which was categorised as less than 9 years, 9 to 12 years, and more than 12 years. The variable of marital status was defined in accordance with the following categories: those who were living with a partner (including those who were married) and those who were living alone. In accordance with a report published by the US government, family income was classified into three categories based on the poverty income ratio (PIR): low (PIR\u0026nbsp;\u0026le;\u0026nbsp;1.3), medium (PIR \u0026gt; 1.3 to 3.5), and high (PIR \u0026gt; 3.5)\u003csup\u003e20\u003c/sup\u003e. Physical activity was classified into four distinct categories: moderate, vigorous, sedentary, and other. The term \u0026quot;moderate\u0026quot; denotes engagement in sporting or fitness activities that result in a moderate elevation of breathing or heart rate, amounting to a minimum of 10 consecutive minutes on a typical weekly basis. The term \u0026quot;vigorous\u0026quot; is defined as engagement in sports or fitness activities that cause a significant increase in breathing or heart rate, for a minimum of 10 consecutive minutes within a typical week. The term \u0026apos;sedentary\u0026apos; is used to describe an individual who spends the majority of their time seated, with a minimum of 570 minutes spent in this position on a typical day\u003csup\u003e21\u003c/sup\u003e. This definition excludes any activities that could be classified as either moderate or vigorous. Any activities that do not align with the aforementioned classifications are classified as \u0026quot;other\u0026quot;.\u003c/p\u003e\n\u003cp\u003eThe participants were classified according to their smoking status, which was divided into three categories: never smokers (those who had smoked less than 100 cigarettes), former smokers (those who had smoked more than 100 cigarettes and had ceased smoking), and current smokers (those who had smoked more than 100 cigarettes and were still smoking). The classification of drinking status comprises three categories: non-drinkers, who rarely consume alcohol (having less than 12 drinks per year); occasional drinkers, who drink more often than once a month but less frequently than once a week; and frequent drinkers, who have alcohol more than once a week. The identification of hypertension and diabetes was based on responses to questions in the questionnaire regarding whether the participants had been informed by a medical professional of such conditions. A diagnosis of hyperlipidemia is made when serum triglyceride concentrations reach 150 mg/dL or above, total cholesterol is 200 mg/dL or above, LDL cholesterol is 130 mg/dL or above, and HDL cholesterol is 40 mg/dL or below in males and 50 mg/dL or below in females. Alternatively, a diagnosis may be made if the patient is taking medication to lower cholesterol levels (lipid-lowering medication)\u003csup\u003e22\u003c/sup\u003e. Dietary intake data are obtained through a 24-hour recall interview, which is a method of estimating food and beverage consumption from midnight to midnight. This process entails the documentation of the specific types and quantities of all foods and beverages consumed, including water, over the designated period. Subsequently, the data is subjected to analysis in order to ascertain the intake of energy and nutrients, as well as other components, utilising the tools of nutritional analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this retrospective analysis of publicly available datasets, categorical data are expressed as percentages n(p%), whereas continuous data are reported either as the Mean (\u0026plusmn; standard deviation, SD) for normally distributed variables or as the Median (interquartile range, IQR) for non-normally distributed variables. Group comparisons were conducted using an independent-samples t-test for parametric data, the Kruskal-Wallis test for non-parametric data, and the chi-square test for categorical variables. A logistic regression analysis was conducted to calculate the odds ratios (OR) with their corresponding 95% confidence intervals (CI), with the objective of assessing the association between the BRI and RA.\u003c/p\u003e\n\u003cp\u003eAdditionally, we employed RCS regression with knots positioned at the 5th, 35th, 65th, and 95th percentiles of the BRI distribution to evaluate the potential nonlinear relationship between BRI and RA, and to model the dose-response association between the two while adjusting for all potential covariates. Moreover, we conducted curve fitting to examine the correlation between BRI and the prevalence of RA. Finally, we employed a piecewise two-stage logistic regression model with smoothing techniques, supported by the likelihood-ratio test and bootstrap resampling method, to investigate the potential threshold effects of BRI on RA and to identify any inflection points.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the sensitivity analysis, BRI was treated as a continuous variable, and the relationship between BRI and RA was explored. Furthermore, subgroup analyses were conducted to ascertain the modifying effects on the relationship between BRI and RA, including variables such as gender, age (less than 50 years vs. 50 years or older), marital status (living with a partner vs. living alone), education level (less than 9 years vs. 9 years or more), family income (per capita income ratio PIR \u0026le;1.3 vs. PIR \u0026gt;1.3), smoking status (never smoker vs. former or current smoker), drinking status (non-drinkers vs. occasional or frequent drinkers), hypertension (normal blood pressure vs. hypertension), diabetes (normal blood glucose vs. prediabetes or diabetes), and hyperlipidemia (normal blood lipids vs. hyperlipidemia). To assess heterogeneity among the subgroups and explore interactions between these and BRI, we employed a multivariate logistic regression and a likelihood ratio test.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using the DecisionLinc software,version 1.0, in conjunction with the R programming environment, version 4.3.3, accessible via the R Project for Statistical Computing website (http://www.R-project.org, R Foundation, Shanghai, China). The last access record was on 1 September 2024. The determination of statistical significance was based on two-tailed \u003cem\u003eP\u003c/em\u003e-values, with a threshold set at P \u0026lt; 0.05. The data analysis was conducted over the period between 1 February 2024 and 30 August 2024.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 45,462 participants completed the interview, of whom 19,182 were under the age of 20. The following exclusions were made: pregnant women (n = 279), incomplete arthritis questionnaire responses (n = 1,975), diagnoses of other arthritis conditions (n = 3,860), absence of height or waist circumference data (n = 2,091), and missing covariate information (n = 4,802). Consequently, the cross-sectional analysis incorporated data from 13,273 participants in the NHANES, conducted between 2011 and 2020. Of the total number of participants, 830 (6.25%) were diagnosed with RA. A comprehensive illustration of the inclusion and exclusion criteria is provided in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Baseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e presents the baseline characteristics of the study population, categorised according to the presence of RA. In general, individuals with RA exhibit higher BRI, older age, greater excessive caffeine intake, and lower intake of calories, protein, carbohydrates, fats, and fibre, in comparison to those without RA. Furthermore, there is a higher prevalence of RA among females, Non-Hispanic Blacks, individuals with lower education levels, those living alone, people with lower incomes, less physically active individuals, smokers, those with lower frequency of alcohol consumption, hypertensive patients, diabetic patients, and patients with hyperlipidemia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Relationship between BRI and RA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe univariate analysis demonstrated that BRI, age, gender, marital status, race, family income, physical activity, smoking status, drinking status, hypertension, diabetes, hyperlipidemia, calorie consumption, protein consumption, carbohydrate consumption, fat consumption, caffeine consumption, and fibre consumption are associated with RA, as presented in \u003cstrong\u003eTable 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eUpon categorising BRI into quartiles for analysis, a significant positive association between BRI and RA was identified, after adjusting for all potential confounding variables. Compared to individuals in the lower BRI Q1 [1.049, 3.666], the adjusted odds ratios (OR) for the association between BRI and RA in the Q2 (3.666, 4.924], Q3 (4.924, 6.477], and Q4 [6.477, 20.970] were 1.22 (95% CI: 0.91-1.64, p=0.181), 1.64 (95% CI: 1.25-2.17, p\u0026lt;0.001), and 2.04 (95% CI: 1.55-2.70, p\u0026lt;0.001), respectively (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe RCS analysis revealed a linear relationship between BRI and RA (\u003cem\u003ep\u003c/em\u003e-value for the overall \u0026lt;0.001, \u003cem\u003ep\u003c/em\u003e-value for non-linearity = 0.627) (\u003cstrong\u003eFigure 2\u003c/strong\u003e). Additionally, curve fitting analysis demonstrated a positive correlation between BRI and the prevalence of RA (\u003cstrong\u003eFigure 3\u003c/strong\u003e). The threshold analysis indicated that participants with a BRI below 6.22 had an odds ratio (OR) of 1.17 (95% CI: 1.08-1.27, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) for developing RA, while those with a BRI of 6.22 or higher had an OR of 1.09 (95% CI: 1.04-1.14, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) (Table 4). The log-likelihood ratio test \u003cem\u003eP\u003c/em\u003e-value of 0.194 between the models estimated above and below the threshold of 6.22 provides evidence in favour of a linear relationship between BRI and RA, indicating the absence of significant inflection points.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Sensitivity Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the sensitivity analysis, the BRI was treated as a continuous variable. The results consistently indicated a significant positive correlation between BRI and RA in models adjusted for different covariates. The correlation coefficients were 1.16 (95% CI: 1.13-1.19, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), 1.16 (95% CI: 1.12-1.19, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), and 1.12 (95% CI: 1.08-1.15, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), respectively (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. The subgroup analysis and interaction test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA series of subgroup analyses was conducted to assess potential effect modifications in the association between the BRI and RA. After stratifying by gender, education level, family income, drinking status, hypertension, diabetes, and hyperlipidemia, no significant interactions were identified within any of the subgroups (P \u0026gt; 0.05). Nevertheless, the subgroup analysis did reveal an interactive effect between BRI and specific factors, including smoking status, age, and marital status. Specifically, never-smokers, individuals under the age of 50, and those living with a partner demonstrated a heightened vulnerability to the effects of BRI (\u003cstrong\u003eFigure 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eFurthermore, through the utilisation of visualisation techniques, we conducted a more in-depth investigation into the interactive effects between BRI and a range of variables, including smoking status, age, and marital status (\u003cstrong\u003eFigure 5, Figure 6, Figure 7\u003c/strong\u003e).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe findings of this cross-sectional study demonstrate a statistically significant positive correlation between the BRI and an elevated risk of developing RA. In all models that were adjusted for a variety of variables, the correlation remained significant, which lends support to the reliability of BRI as a potential risk predictor for RA. The results of the RCS and threshold analysis indicated a linear relationship between BRI and RA risk. The results of the sensitivity analysis demonstrate that there is an 12% increase in the risk of RA for every unit increase in BRI. Moreover, the subgroup analysis revealed that individuals who have never smoked, those under the age of 50, and those living with a partner exhibited heightened vulnerability to BRI. To the best of our knowledge, this is the inaugural study to examine the correlation between BRI and the risk of developing RA. It can therefore be surmised that the reduction of adipose tissue, particularly visceral fat, through the implementation of a regular exercise regime and the maintenance of a healthy body weight may prove an effective method of reducing the risk of developing RA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOver the past three decades, there has been a marked increase in the prevalence of overweight and obesity among adults globally, representing a significant challenge to public health\u003csup\u003e23\u003c/sup\u003e. The expansion of abnormal adipose tissue, particularly visceral fat, has the capacity to secrete inflammatory and lipid factors that disrupt homeostatic processes, thereby leading to pathological alterations such as oxidative stress, cellular proliferation and insulin resistance\u003csup\u003e24, 25\u003c/sup\u003e. The most commonly used measure of obesity, BMI, is limited in its ability to assess the specific distribution of adipose tissue\u003csup\u003e26\u003c/sup\u003e. A meta-analysis has demonstrated that BRI is a more effective predictor than waist-to-hip ratio, BMI and body fat percentage in identifying obesity, cardiovascular disease, insulin resistance and metabolic syndrome\u003csup\u003e3, 27\u003c/sup\u003e. A cross-sectional study conducted in the UK has indicated that a higher waist circumference is associated with a higher prevalence of RA. This relationship persists even after adjustment for BMI, which underscores the potential significance of central obesity in autoimmune diseases such as RA\u003csup\u003e28\u003c/sup\u003e. Additionally, there is a positive correlation between adipose tissue mass and the risk of developing RA\u003csup\u003e29\u003c/sup\u003e. Furthermore, a notable increase in BMI has been linked to the development of osteoarthritis in the knee and hip joints\u003csup\u003e30\u003c/sup\u003e. The above research is consistent with our findings. Although there is a growing body of literature on RA and obesity, there is still a gap in the field regarding the relationship between BRI and RA. In light of these considerations, the potential of BRI as a predictor of RA risk is substantial, given its status as a newly developed obesity index.\u003c/p\u003e\n\u003cp\u003eIt is widely accepted that visceral fat cells represent the primary source of pro-inflammatory cytokines and chemokines (such as IL-8, IL-1, IL-6, and TNF-\u0026alpha;) in obese individuals\u003csup\u003e31\u003c/sup\u003e. Moreove, adipocytes are capable of producing adipokines, including adiponectin and leptin, which can result in oxidative stress and dyslipidemia within the body\u003csup\u003e32\u003c/sup\u003e. As demonstrated by Hojgaard, elevated levels of these biomessengers in obese subjects result in sustained inflammation within the body\u003csup\u003e33\u003c/sup\u003e. The following pathophysiological processes may increase the risk of RA in individuals with obesity: Firstly, interleukin-1 (IL-1), interleukin-6 (IL-6) and tumour necrosis factor alpha (TNF-\u0026alpha;) have been demonstrated to stimulate the production of autoantibodies and the activation of inflammatory cells\u003csup\u003e34\u003c/sup\u003e. These, in turn, together with fibroblast-like synoviocytes, activate osteoclasts, which results in persistent synovitis and joint destruction\u003csup\u003e35\u003c/sup\u003e. Secondly, the differentiation of T cells into a pro-inflammatory phenotype is affected due to the dysregulation of adipokines and impaired resolution of inflammation\u003csup\u003e36\u003c/sup\u003e, which leads to persistent synovitis and joint destruction\u003csup\u003e37\u003c/sup\u003e. Thirdly, there is evidence that obesity is involved in the activation of the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome, which has been demonstrated to promote the production of pro-inflammatory cytokines, thereby exacerbating RA\u003csup\u003e38\u003c/sup\u003e. Furthermore, the activation of the NLRP3 inflammasome is associated with insulin resistance, which leads to various metabolic disorders and exacerbates systemic inflammation, thereby indirectly affecting the onset of RA\u003csup\u003e39\u003c/sup\u003e. Finally, an inverse relationship has been identified between adiposity and circulating 25-hydroxyvitamin D concentrations\u003csup\u003e40\u003c/sup\u003e, while a positive association exists with serum estradiol levels\u003csup\u003e41\u003c/sup\u003e. The presence of insufficient vitamin D and elevated estrogen levels has been correlated with heightened susceptibility to multiple autoimmune conditions\u003csup\u003e42\u003c/sup\u003e, suggesting that these hormonal imbalances may be instrumental in the pathogenesis of RA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA Mendelian randomization analysis indicated that interventions to reduce smoking and excessive obesity can significantly reduce the risk of RA\u003csup\u003e43\u003c/sup\u003e. The findings of this study are in alignment with the current results. Moreover, significant interactive effects between BRI and specific factors, including smoking status, age, and marital status, were identified through subgroup analyses. In particular, never-smokers, individuals under the age of 50, and those living with a partner exhibited a greater susceptibility to the influence of BRI, and the association between BRI and the risk of RA was stronger.\u003c/p\u003e\n\u003cp\u003eThis study represents the inaugural multicentre, large-sample cross-sectional investigation to examine the correlation between the BRI and the risk of RA. It possesses several notable advantages. Firstly, the data for this study are derived from the NHANES, a reliable and comprehensive dataset with a large sample size. Secondly, three distinct logistic regression models were constructed, with various confounding variables adjusted, thus ensuring the reliability of the results. Thirdly, comprehensive subgroup analyses were conducted, with all other covariates adjusted in each analysis to ensure the generalisability of the findings. In conclusion, this pioneering study has identified the potential of BRI as a predictor for RA risk. However, it is important to acknowledge the limitations of the study. Firstly, the cross-sectional design of this study precludes the possibility of establishing a causal relationship between BRI and the risk of RA. Secondly, the presence or absence of RA in this study was determined based on a questionnaire survey. It is important to note that the response rate of NHANES has decreased from 76.62% to 48.24% over the past two decades\u003csup\u003e44\u003c/sup\u003e. This may introduce some recall bias and nonresponse bias, which could affect the reliability of the data. Thirdly, although regression models, stratified analyses and sensitivity analyses were employed to minimise bias, it remains a significant challenge to completely eliminate the influence of confounding factors. The results of this study encourage the further investigation of BRI as a potential indicator for assessing the risk of RA. However, the validation of these findings is contingent upon the undertaking of more detailed and in-depth studies in the future.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of our study demonstrate a statistically significant positive linear correlation between BRI and the risk of RA in the US adult population. This effect is more pronounced among three groups: non-smokers, individuals under the age of 50, and those living with a partner. The objective of this study is to enhance public awareness of BRI as a novel measure of obesity and to elucidate the correlation between visceral fat, as represented by BRI, and the risk of RA. Moreover, the study seeks to promote the maintenance of a healthy body habitus as a means of reducing the incidence of RA.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following supplementary information is available for reference: Table S1: Association of Covariates with Rheumatoid Arthritis Risk, Adjusted for All Variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Z.Z., H.W., and X.C.; Methodology, Z.Z., H.W., and C.F.; Software, M.H.; Validation, L.L. and C.F.; Formal analysis, Z.Z. and H.W.; Investigation, X.C. and L.L.; Resources, M.H.; Data curation, Z.Z., H.W., and R.C.; Writing\u0026mdash;original draft preparation, Z.Z.; Writing\u0026mdash;review and editing, H.W., X.C., and X.W.; Visualization, L.L.; Supervision, C.F.; Project administration, M.H.; Funding acquisition, M.H. All authors have contributed to the article and have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was supported by the China Science and Technology Administration of Wenzhou (Y20220730) and the key laboratory of clinical laboratory diagnosis and transformation research of Zhejiang province (2022E10022) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical review and approval were waived for this study because no additional institutional review board approval was required for the secondary analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authorization for NHANES was granted by the Ethics Review Committee of the National Center for Health Statistics (NCHS), with all participants having signed written informed consent forms prior to their participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e \u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe publicly accessible datasets utilized in this study are available online. The names of the repositories and their respective access codes can be found online at\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehttp://www.cdc.gov/nchs/nhanes.htm\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe greatly appreciate all of the study participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNgian, G. S., Rheumatoid arthritis. \u003cem\u003eAust Fam Physician \u003c/em\u003e\u003cstrong\u003e2010,\u003c/strong\u003e \u003cem\u003e39\u003c/em\u003e (9), 626-8.\u003c/li\u003e\n\u003cli\u003evan der Woude, D.; van der Helm-van Mil, A. H. 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K.; Martinon, F., Inflammation in gout: mechanisms and therapeutic targets. \u003cem\u003eNat Rev Rheumatol \u003c/em\u003e\u003cstrong\u003e2017,\u003c/strong\u003e \u003cem\u003e13\u003c/em\u003e (11), 639-647.\u003c/li\u003e\n\u003cli\u003eYe, Q.; Yan, T.;\u0026nbsp; Shen, J.;\u0026nbsp; Shi, X.;\u0026nbsp; Luo, F.; Ren, Y., Sulforaphene targets NLRP3 inflammasome to suppress M1 polarization of macrophages and inflammatory response in rheumatoid arthritis. \u003cem\u003eJ Biochem Mol Toxicol \u003c/em\u003e\u003cstrong\u003e2023,\u003c/strong\u003e \u003cem\u003e37\u003c/em\u003e (7), e23362.\u003c/li\u003e\n\u003cli\u003eWortsman, J.; Matsuoka, L. Y.;\u0026nbsp; Chen, T. C.;\u0026nbsp; Lu, Z.; Holick, M. F., Decreased bioavailability of vitamin D in obesity. \u003cem\u003eAm J Clin Nutr \u003c/em\u003e\u003cstrong\u003e2000,\u003c/strong\u003e \u003cem\u003e72\u003c/em\u003e (3), 690-3.\u003c/li\u003e\n\u003cli\u003eRohrmann, S.; Shiels, M. S.;\u0026nbsp; Lopez, D. S.;\u0026nbsp; Rifai, N.;\u0026nbsp; Nelson, W. G.;\u0026nbsp; Kanarek, N.;\u0026nbsp; Guallar, E.;\u0026nbsp; Menke, A.;\u0026nbsp; Joshu, C. E.;\u0026nbsp; Feinleib, M.;\u0026nbsp; Sutcliffe, S.; Platz, E. A., Body fatness and sex steroid hormone concentrations in US men: results from NHANES III. \u003cem\u003eCancer Causes Control \u003c/em\u003e\u003cstrong\u003e2011,\u003c/strong\u003e \u003cem\u003e22\u003c/em\u003e (8), 1141-51.\u003c/li\u003e\n\u003cli\u003eArnson, Y.; Amital, H.; Shoenfeld, Y., Vitamin D and autoimmunity: new aetiological and therapeutic considerations. \u003cem\u003eAnn Rheum Dis \u003c/em\u003e\u003cstrong\u003e2007,\u003c/strong\u003e \u003cem\u003e66\u003c/em\u003e (9), 1137-42.\u003c/li\u003e\n\u003cli\u003eZhao, S. S.; Holmes, M. V.;\u0026nbsp; Zheng, J.;\u0026nbsp; Sanderson, E.; Carter, A. R., The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: Mendelian randomization study. \u003cem\u003eRheumatology (Oxford) \u003c/em\u003e\u003cstrong\u003e2022,\u003c/strong\u003e \u003cem\u003e61\u003c/em\u003e (5), 2167-2175.\u003c/li\u003e\n\u003cli\u003eZhang, X.; Ma, N.;\u0026nbsp; Lin, Q.;\u0026nbsp; Chen, K.;\u0026nbsp; Zheng, F.;\u0026nbsp; Wu, J.;\u0026nbsp; Dong, X.; Niu, W., Body Roundness Index and All-Cause Mortality Among US Adults. \u003cem\u003eJAMA Netw Open \u003c/em\u003e\u003cstrong\u003e2024,\u003c/strong\u003e \u003cem\u003e7\u003c/em\u003e (6), e2415051.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Population characteristics by RA status.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"653\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 199px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eNo Arthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003eRheumatoid Arthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(N = 13273)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e(N = 12,443)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e(N = 830)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eBRI, Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e5.32 ( 2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e5.24 ( 2.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e6.50 \u0026plusmn;(2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eAge(years),Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e43.00 (31.00 -58.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e42.00 (30.00 -56.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e61.00 (51.00 - 69.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eCalorieConsumption(kcal/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e2,006.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,021.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e1,844.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eMedian(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(1,489.00 -2,668.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e(1,499.00 -2,686.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e(1,337.00 - 2,408.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eProteinConsumption(g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e75.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e76.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e64.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp;Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(53.63 - 103.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;(54.36 - 104.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;(46.53 - 91.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eCarbohydrateConsumption(g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e235.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e237.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e218.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eMedian(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(169.47 - 317.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;(170.55 - 319.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;(157.63 - 290.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eFatConsumption(g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e75.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e76.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e70.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eMedian(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;(51.42 - 108.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e(51.68 - 108.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e(47.65 - 100.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eCaffineConsumption(mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e102.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eMedian(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(9.00 - 194.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;(9.00 - 193.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e(14.00 - 206.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eFibreConsumption(g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e12.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003eMedian(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e(9.50 - 22.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e(9.60 - 22.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;(8.40 - 19.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eGender, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e6,426.00 (48.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e5,951.00 (47.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e475.00 (57.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e6,847.00 (51.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e6,492.00 (52.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e355.00 (42.77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eRace/Ethnicity , n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Mexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e1,804.00 (13.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e1,706.00 (13.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e98.00 (11.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,117.00 (23.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,843.00 (22.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e274.00 (33.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,778.00 (36.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e4,478.00 (35.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e300.00 (36.14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,574.00 (26.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,416.00 (27.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e158.00 (19.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eEducation Level(years), n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e2,371.00 (17.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,170.00 (17.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e201.00 (24.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;9-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e2,940.00 (22.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,725.00 (21.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e215.00 (25.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026gt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e7,962.00 (59.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7,548.00 (60.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e414.00 (49.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eMarital Status, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Living Alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e5,428.00 (40.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e5,060.00 (40.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e368.00 (44.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Living With a partner\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e7,845.00 (59.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7,383.00 (59.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e462.00 (55.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eFamily Income, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;PIR \u0026lt;= 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,049.00 (30.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,715.00 (29.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e334.00 (40.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;(1.3,3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,908.00 (36.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e4,623.00 (37.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e285.00 (34.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;PIR \u0026gt; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,316.00 (32.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e4,105.00 (32.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e211.00 (25.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003ePhysical Activity, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e1,088.00 (8.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e998.00 (8.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e90.00 (10.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,384.00 (25.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,156.00 (25.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e228.00 (27.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Vigorous activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,786.00 (28.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,690.00 (29.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e96.00 (11.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e5,015.00 (37.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e4,599.00 (36.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e416.00 (50.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eSmoking Status, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e8,073.00 (60.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7,661.00 (61.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e412.00 (49.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e2,634.00 (19.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,403.00 (19.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e231.00 (27.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Current\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e2,566.00 (19.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,379.00 (19.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e187.00 (22.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eDrinking Status, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,088.00 (23.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2,810.00 (22.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e278.00 (33.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Occasional drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e6,003.00 (45.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e5,665.00 (45.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e338.00 (40.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Frequent drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,182.00 (31.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,968.00 (31.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e214.00 (25.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eHypertension, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e9,441.00 (71.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e9,105.00 (73.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e336.00 (40.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e3,832.00 (28.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3,338.00 (26.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e494.00 (59.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eDiabetes, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e10,954.00(82.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e10,426.00(83.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e528.00 (63.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Prediabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e888.00 (6.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e813.00 (6.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e75.00 (9.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e1,431.00 (10.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e1,204.00 (9.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e227.00 (27.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003eHyperlipidemia, n (p%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\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: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e4,686.00 (35.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e4,520.00 (36.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e166.00 (20.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 199px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003e8,587.00 (64.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7,923.00 (63.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003e664.00 (80.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBRI, Body Roundness Index; SD, Standard Deviation; IQR, Interquartile Range; PIR, Poverty Income Ratio. Mean (SD) for normally distributed variables: the \u003cem\u003eP\u003c/em\u003e-value was calculated by independent-samples t-test; Median (IQR) for non-normally distributed variables: the \u003cem\u003eP\u003c/em\u003e-value was calculated by Kruskal-Wallis test; n(p%) for categorical variables: the \u003cem\u003eP\u003c/em\u003e-value was calculated by chi-square test.\u003c/p\u003e\n\u003cp\u003eTable 2. Association of covariates and RA risk.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"759\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003eOR（95%_CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003eOR（95%_CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;BRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.21 (1.18 -1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.06 (1.05 -1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eSmoking Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.69 (0.59 -0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.79 (1.51 -2.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Race/Ethnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Current\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.46 (1.22 -1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Mexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eDrinking Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Non-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.17 (0.93 -1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eNon-drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Non-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.68 (1.33 -2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Occasional drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.60 (0.51 -0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.81 (0.62 -1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Frequent drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.55 (0.45 -0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Education Level(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 9-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.85 (0.70 -1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e4.01 (3.47 -4.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.59 (0.50 -0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Marital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Living With a partner\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Prediabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.82 (1.41 -2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Living Alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.16 (1.01 -1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e3.72 (3.15 -4.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Family Income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Hyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; PIR \u0026lt;= 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; (1.3,3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.69 (0.58 -0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eHyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e2.28 (1.92 -2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; PIR \u0026gt; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.57 (0.48 -0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eCalorie Consumption(kcal/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.00 (1.00 -1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Physical Activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eProtein Consumption (g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.99 (0.99 -0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Sedentary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eCarbohydrate Consumption(g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.00 (1.00 -1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Moderate activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.80 (0.62 -1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eFat Consumption (g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.00 (1.00 -1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Vigorous activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.29 (0.21 -0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eCaffeine Consumption (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.00 (1.00 -1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\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: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e1.00 (0.79 -1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 226px;\"\u003e\n \u003cp\u003eFibre Consumption (g/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e0.98 (0.97 -0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBRI, Body Roundness Index; PIR , Poverty Income Ratio; OR, odds ratio; CI, confidence interval; Ref: reference.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3. Association between BRI and RA.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"733\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 165px;\"\u003e\n \u003cp\u003eBody Roundness Index(BRI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;Model 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;Model 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;Model 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContinuous\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.16(1.13-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.16(1.12-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.12(1.08-1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\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: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuartiles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eQ1[1.049, 3.666]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eQ2(3.666, 4.924]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.31(0.99-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.33(1.00-1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.22(0.91-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003eQ3(4.924, 6.477]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.87(1.44-2.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.89(1.45-2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.64(1.25-2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\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: 165px;\"\u003e\n \u003cp\u003eQ4(6.477, 20.970]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2.68(2.08-3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2.65(2.04-3.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2.04(1.55-2.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\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: 165px;\"\u003e\n \u003cp\u003eOR for Trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.40(1.30-1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.39(1.29-1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e1.28(1.18-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for Trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 1: Adjusted for sociodemographic variables, including age, gender, marital status, race/ethnicity, education level, and family income.\u003c/p\u003e\n\u003cp\u003eModel 2: Adjusted for sociodemographic variables as well as dietary and lifestyle habits, including physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fibre consumption, and caffeine consumption.\u003c/p\u003e\n\u003cp\u003eModel 3: Adjusted for sociodemographic variables, dietary and lifestyle habits, and clinical conditions, including hyperlipidemia, diabetes, and hypertension.\u003c/p\u003e\n\u003cp\u003eQ, quartiles; OR, odds ratio; CI, confidence interval; Ref: reference.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4. Threshold effect analysis of the relationship of BRI with rheumatoid arthritis (RA).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"676\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 225px;\"\u003e\n \u003cp\u003eBody Roundness Index(BRI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 451px;\"\u003e\n \u003cp\u003eAdjusted Model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eOR (95% CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 225px;\"\u003e\n \u003cp\u003e\u0026lt;6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003e1.17（1.08-1.27）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\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: 225px;\"\u003e\n \u003cp\u003e\u0026ge;6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003e1.09（1.04-1.14）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\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: 225px;\"\u003e\n \u003cp\u003eLog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 225px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0.194\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR, odds ratio; CI, confidence interval. Adjustments were made for all potential variables, including age, gender, marital status, race/ethnicity, education level, family income, physical activity, drinking status, smoking status, protein consumption, calorie consumption, carbohydrate consumption, fat consumption, fiber consumption, caffeine consumption, hyperlipidemia, diabetes, and hypertension. Only 99% of the data is displayed.\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":"Rheumatoid Arthritis, Body Roundness Index, Obesity, Cross-sectional study, NHANES","lastPublishedDoi":"10.21203/rs.3.rs-5339298/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5339298/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003eThere is increasing evidence of an association between rheumatoid arthritis (RA) and obesity. However, the precise relationship between BRI, a novel indicator of visceral fat, and RA remains unclear. The objective of this study was to investigate the relationship between BRI and RA risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA cross-sectional study was conducted using data from the NHANES from 2011 to 2020. A logistic regression analysis was employed to investigate the correlation between the BRI and RA risk, and restricted cubic splines (RCS) and fitting curve analysis were used to capture the potential non-linear relationship. Furthermore, a piecewise two-stage logistic regression model combined with smoothing techniques was employed to explore the potential threshold effect of BRI on RA risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 6.25% (830/13,273) of the 13,273 participants aged 20 and above included in the study were diagnosed with RA. The adjusted OR values for BRI and RA in Q2 (3.666, 4.924), Q3 (4.924, 6.477), and Q4 (6.470, 20.970) were compared with those for individuals with lower BRI-Q1 (1.049, 3.666). The ORs for the remaining categories were 1.22 (95% CI: 0.91–1.64, p = 0.181), 1.64 (95% CI: 1.25–2.17, p \u0026lt; 0.001) and 2.04 (95% CI: 1.55–2.70, p \u0026lt; 0.001), respectively. The results of the trend analysis showed that the adjusted OR for the trend was 1.28 (95% CI: 1.18–1.38, P \u0026lt; 0.001). The results of the RCS analysis indicated a significant linear correlation between the risk of RA and increasing BRI (\u003cem\u003ep\u003c/em\u003e-value for the overall \u0026lt;0.001, \u003cem\u003ep\u003c/em\u003e-value for non-linearity = 0.627). A sensitivity analysis demonstrated that when BRI was treated as a continuous variable, the observed association remained, with an adjusted OR of 1.12 (95% confidence interval: 1.08-1.15, P \u0026lt; 0.001). Subgroup analysis indicated that BRI interacted with smoking status, age and marital status, with never smokers, those under 50 and those living with a partner being more susceptible to BRI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eA significant positive correlation was observed between the risk of RA and BRI, particularly in individuals who had never smoked, were under the age of 50, and living with a partner. It is proposed that maintaining an appropriate BRI may contribute to a reduction in the incidence of RA.\u003c/p\u003e","manuscriptTitle":"The association between the body roundness index and the risk of rheumatoid arthritis: a cross-sectional study based on NHANES","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-16 17:23:26","doi":"10.21203/rs.3.rs-5339298/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":"a8be943d-9dd2-4bca-a693-64bc00af2adf","owner":[],"postedDate":"December 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":40391350,"name":"Health sciences/Health care"},{"id":40391351,"name":"Health sciences/Rheumatology"}],"tags":[],"updatedAt":"2025-02-23T23:38:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-16 17:23:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5339298","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5339298","identity":"rs-5339298","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}