Combined influence of oral health behaviors and nutritional and inflammatory status on risk of all-cause mortality among US population, NHANES 2011-2018

Combined influence of oral health behaviors and nutritional and inflammatory status on risk of all-cause mortality among US population, NHANES 2011-2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Combined influence of oral health behaviors and nutritional and inflammatory status on risk of all-cause mortality among US population, NHANES 2011-2018 Wanjun Deng, Peng Han, Qi Liu, Yongjian Zhang, Tao Zuo, Huihua Xiong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4296391/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Oral health and inflammation and nutritional status are interconnected, each bearing significant correlation with long-term prognoses in populations. We investigated the interactions and correlations among nutritional and inflammatory indictors, oral health, and all-cause mortality. Methods : A nationally representative prospective cohort sample was recruited from the National Health and Nutrition Examination Survey (NHANES) conducted in the United States from 2011 to 2018, selecting individuals aged 40 or above (n=10573; weighted population: 7229522) with comprehensive oral health assessments and related biomarkers. Oral health was quantified using multiple indicators to construct an Oral Health Index (OHI), and the Prognostic Nutritional Index (PNI) was employed to reflect general inflammatory and nutritional status. The independent effects of OHI and PNI on all-cause mortality were examined across the population, alongside their interactive prognostic implications. Results : The study included 10573 participants with complete oral health and related data. Adjusted models revealed that better self- assessed oral health (HR=0.80; 95%CI: 0.67-0.96) and more frequent use of dental floss (HR=0.94; 95%CI: 0.91-0.98) were associated with lower all-cause mortality rates. Conversely, individuals with dental visits exceeding five years (HR=1.35; 95%CI: 1.13-1.62), occupational oral health hazards (HR=1.33; 95%CI: 1.00-1.76), or no history of periodontal cleaning or treatment (HR=1.37; 95%CI: 1.09-1.73) faced higher mortality rates. A higher PNI indicated a lower all-cause mortality risk (HR=0.9; p<0.001). The correlation between the constructed OHI and all-cause mortality was confirmed (HR=0.99, P<0.001), with interaction analysis showing a significantly increased impact of OHI on prognosis at lower PNI levels. Conclusion : This cohort study observed the effects of oral health and nutritional/inflammatory statuses on all-cause mortality, identifying the lowest risk of mortality among populations with high OHI and PNI levels. oral health PNI NHANES all-cause mortality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction The World Dental Federation (FDI) redefines oral health as a complex entity, integrating functions essential for speaking, smiling, tasting, touching, chewing, swallowing, and facial expressions[1, 2]. Various factors, including sociopsychological, economic-cultural aspects, and health behavior practices, interplay with individual physiological characteristics, and play pivotal roles in overall health outcomes[2]. Therefore, a more precise assessment of population oral health, along with an understanding of the synergy between oral health status and clinical dental care needs, were crucial for improving overall health outcomes for the population[1]. Poor oral health and dental habits significantly impact overall health[3]. Research indicates a strong link between oral health and various diseases, such as hypertension[4], diabetes[5, 6], cardiovascular diseases[7, 8], respiratory issues[9, 10], cognitive decline[11, 12], and cancers[9]. Consequently, the rise in disease incidence related to oral health problems precipitates a decline in population-wide health status. Potential biological mechanisms may involve inflammatory mediators entering the bloodstream because of oral conditions, leading to systemic chronic inflammation, thereby facilitating the progression of diseases[13-16]. Moreover, poor nutritional status resulting from oral health problems can diminish general physiological conditions, leading to organ dysfunction[17, 18]. Thus, it is significant to consider oral health as a systemic issue and understand its impact on individual health. Systemic inflammation and nutritional status can be quantified using various hematological markers. The Prognostic Nutritional Index (PNI), calculated through levels of peripheral blood lymphocytes and serum albumin, evaluates the systemic status regarding nutrition, immunity, and inflammation, serving as a comprehensive and reliable biomarker[19]. Initially, PNI was utilized to assess preoperative nutritional status, surgical risk, and postoperative complications in surgical patients[20, 21]. However, subsequent research has indicated that PNI is closely associated with the prognosis of various diseases, including heart failure[22], stroke[23, 24], diabetic nephropathy[25], liver fibrosis[26], and cancer[27-30]. However, a comprehensive systematic study that explicates the impact of oral health, systemic inflammation, and nutritional status on all-cause mortality remains absent. Therefore, utilizing the National Health and Nutrition Examination Survey (NHANES) database, we conducted a population-based prospective study to investigate the relationship between overall oral health status and the inflammatory nutritional index, PNI, in relation to all-cause mortality among the population. 2. Methods The National Health and Nutrition Examination Survey (NHANES) assesses the health and nutritional status of the U.S. population through a stratified multistage sampling methodology. This program gathers demographic and health-related information through interviews and physical examinations. The data, emblematic of the diverse U.S. demographics, facilitate analyses of various health indicators. These analyses are further refined using specialized survey weights, thereby guaranteeing accurate national prevalence estimates. 2.1 Study population During the 2011-2018 NHANES cycles, individuals were considered for inclusion in assessments of dental health perception, quality of life queries, and comprehensive oral health examinations. Our analysis centered on 15066 adults who were 40 years or older with accessible oral health information. We excluded participants for insufficient covariate data (n = 3544), lack of oral health data (n = 429), the absence of blood biomarkers (n = 506), and missing of outcomes (n = 14). Consequently, the study progressed with a cohort of 10573 individuals. Tracking of mortality outcomes was synchronized with the National Death Index, culminating on December 31, 2019. 2.2 Sociodemographic characteristics, healthy behaviors and conditions. Sociodemographic characteristics include gender (male and female), race and ethnicity (Mexican American, Non-Hispanic White, Non-Hispanic Black and Others), educational level (High school), and family poverty income ratio (3.5). Healthy behaviors consist of Body Mass Index (BMI), smoking status (never smoker, former smoker, current smoker) and alcohol consumption (lifetime abstainer, former, current). In addition, healthy conditions include hypertension (yes/no) and diabetes (yes/no). 2.3 Oral health status assessment In recent years, self-assessed health status assessment systems for diseases and health-related conditions have been extensively employed in population surveys. Prior research indicates that self-assessed oral health issues can reliably predict oral health status, exhibiting a high level of reliability and validity comparable to the outcomes of dental examinations conducted by professionals. Self-assessment of Oral Health (SOH) was conducted by asking “Rate the health of your teeth and gums”, with responses categorized as good (include excellent, very good and good) and poor (include fair or poor). Dental Visit Frequency (DVF) was determined by asking “When did you last visit a dentist”, with the responses consist of <2 years, 2-5 years, and more than 5 years. Periodontal Treatment History (PTH) was ascertained through the question " ever had treatment for gum disease such as scaling, root planning, and deep cleaning ", with answers being yes or no. Health-Related Occupational Impairment (HROI) was evaluated by asking " How often during the last year have you had difficulty doing usual jobs or attending school because of problems with teeth, mouth or dentures ", with possible responses being yes (exclude never) or no (never). Dental Floss Usage Frequency (DFUF) was obtained by inquiring " How many days use dental floss/device in the last seven days ", with answers ranging from 0 to 7 days. Periodontal Disease (PD) assessment encompassed queries such as " Do you think you might have gum disease ", " How often last year had aching in mouth ", and " ever been told of bone loss around teeth ". An affirmative response to any of these questions indicated the presence of periodontal disease, characterized by symptoms such as gum swelling, recession, pain or infection, or tooth mobility. 2.4 Calculation of the Prognostic Nutritional Index (PNI) PNI = ALB (g/L) + 5 × PBL (×10^9/L), Alb = serum albumin in grams per deciliter, and PBL= peripheral blood lymphocyte in 10^9 per deciliter. 2.5 Evaluation of mortality This study's primary outcome was all-cause mortality, defined as death from any cause. The follow-up period spanned from the initial interview to either the date of death or the study's conclusion on December 31, 2019, whichever occurred first. 2.6 Statistical analysis This study incorporated sample weights, clustering, and stratification in all analyses to ensure national representativeness. Using univariate Cox regression, we evaluated oral health indicators potentially influencing mortality outcomes. Positive findings were included in a multivariable Cox proportional hazards regression model to estimate hazard ratios (HR) and 95% confidence intervals for the association between oral health indicators and overall mortality. The final multivariate model was adjusted for age, gender, race and ethnicity, BMI, family income to poverty ratio, education level, smoking status, alcohol consumption, and health factors (e.g., hypertension and diabetes). Positive oral health indicators from the multivariable Cox regression analysis were incorporated to constructed nomogram and generated Oral Health Index (OHI). Using time-dependent Receiver Operating Characteristic (TimeROC) curves, the most effective prognostic indicator identified was the OHI. To assess the interaction between multiple inflammatory markers (including PNI), and OHI on mortality, multivariable Cox proportional hazards regression models adjusted for the same covariates were used to estimate mortality risk. Finally, restricted cubic splines (RCS) and Cox proportional hazards models elucidated the linear/non-linear relationship between OHI and the risk of all-cause mortality. 3. Results 3.1 Baseline characteristics In this study, we analyzed a cohort consisting of individuals aged 40 years and older. We excluded participants lacking data for variables under consideration, ultimately established a sample size of 10573 participants (Fig1). This sample represents a weighted population of 7,229,523 individuals. The gender distribution was balanced, with 48% female participants and 52% male participants. Regarding ethnic composition, Mexican American, Non-Hispanic White, Non-Hispanic Black and Others comprised 5.8%, 73%, 9.3%, and 12% of the cohort, respectively. We documented other baseline characteristics of the cohort, including household income, educational levels, smoking and drinking habits, body mass index (BMI), and the prevalence of fundamental health conditions such as hypertension and diabetes. These characteristics are detailed in Table 1. Our findings revealed that a significant majority of the participants self-assessment of oral health as good (73%) compared with poor (27%). However, a considerable proportion (40%) reported having periodontal disease. The majority had visited a dentist within the last two years (75%). And 25% of participants had undergone periodontal treatment. Regarding dental floss usage, 28% of the individuals did not use dental floss in the past week, whereas 36% used it daily. Additionally, 9.1 % participants had difficulty doing usual jobs or attending school because of problems with oral health. Table 1 Baseline characteristics of US population oral health behaviors. Overall Oral Health Self-Assessment Dental Visit Frequency Characteristic N = 10573 (100%) 1 poor , N = 3610 (27%) 1 good , N = 6963 (73%) 1 p-value 2 5 year , N = 1821 (13%) 1 p-value 2 Age <0.001 <0.001 40 to 59 5,225 (57%) 1,898 (62%) 3,327 (56%) 3,668 (57%) 766 (63%) 791 (54%) 60~ 5,348 (43%) 1,712 (38%) 3,636 (44%) 3,572 (43%) 746 (37%) 1,030 (46%) Gender 0.004 <0.001 male 5,201 (48%) 1,844 (52%) 3,357 (47%) 3,365 (46%) 765 (51%) 1,071 (56%) female 5,372 (52%) 1,766 (48%) 3,606 (53%) 3,875 (54%) 747 (49%) 750 (44%) Race and ethnicity <0.001 <0.001 Mexican American 1,239 (5.8%) 633 (10%) 606 (4.1%) 801 (5.0%) 202 (7.8%) 236 (8.2%) Non-Hispanic White 4,488 (73%) 1,276 (63%) 3,212 (77%) 3,103 (75%) 579 (67%) 806 (67%) Non-Hispanic Black 2,326 (9.3%) 886 (13%) 1,440 (8.1%) 1,492 (8.3%) 372 (12%) 462 (13%) Other 2,520 (12%) 815 (14%) 1,705 (11%) 1,844 (12%) 359 (14%) 317 (11%) Educational attainment(%) <0.001 <0.001 High school 5,871 (64%) 1,525 (48%) 4,346 (70%) 4,512 (70%) 713 (54%) 646 (41%) Family poverty income ratio(%) <0.001 <0.001 <1.3 2,999 (17%) 1,467 (29%) 1,532 (12%) 1,564 (12%) 543 (25%) 892 (38%) 1.3 to < 3.5 4,041 (35%) 1,485 (43%) 2,556 (32%) 2,650 (31%) 663 (45%) 728 (45%) ≥3.5 3,533 (48%) 658 (27%) 2,875 (56%) 3,026 (57%) 306 (30%) 201 (17%) Alcohol drinking status(%) 0.095 0.003 Lifetime abstainer 1,447 (9.6%) 464 (9.5%) 983 (9.6%) 1,000 (9.4%) 216 (12%) 231 (9.3%) Former drink 1,900 (16%) 576 (14%) 1,324 (17%) 1,342 (17%) 258 (13%) 300 (14%) Current drink 7,226 (74%) 2,570 (76%) 4,656 (73%) 4,898 (73%) 1,038 (76%) 1,290 (77%) Smoking status (%) <0.001 <0.001 Lifetime abstainer 5,562 (53%) 1,579 (40%) 3,983 (57%) 4,159 (57%) 717 (47%) 686 (36%) Former 3,151 (31%) 1,061 (31%) 2,090 (30%) 2,138 (31%) 460 (30%) 553 (29%) Current 1,860 (17%) 970 (29%) 890 (12%) 943 (13%) 335 (23%) 582 (35%) Weight status, BMI <0.001 0.004 18-24 2,161 (21%) 637 (18%) 1,524 (22%) 1,526 (21%) 272 (17%) 363 (21%) 28 5,189 (49%) 1,957 (54%) 3,232 (47%) 3,454 (47%) 807 (53%) 928 (53%) Prevalent hypertension(%) 5,221 (44%) 1,914 (50%) 3,307 (42%) <0.001 3,453 (43%) 783 (46%) 985 (50%) <0.001 Prevalent diabetes(%) 2,096 (15%) 863 (20%) 1,233 (13%) <0.001 1,336 (14%) 319 (16%) 441 (21%) <0.001 Table 1 (continued) Overall Periodontal Treatment History Oral Health-Related Occupational Impairment Periodontal Disease Characteristic N = 10573 (100%) 1 Yes , N = 2787 (25%) 1 No , N = 7786 (75%) 1 p-value 2 No , N = 9336 (91%) 1 Yes , N = 1237 (9.1%) 1 p-value 2 Yes , N = 4465 (40%) 1 No , N = 6108 (60%) 1 p-value 2 Age 0.4 0.004 0.4 40 to 59 5,225 (57%) 1,402 (56%) 3,823 (58%) 4,540 (57%) 685 (64%) 2,297 (58%) 2,928 (57%) 60~ 5,348 (43%) 1,385 (44%) 3,963 (42%) 4,796 (43%) 552 (36%) 2,168 (42%) 3,180 (43%) Gender 0.2 0.029 0.6 male 5,201 (48%) 1,358 (50%) 3,843 (48%) 4,582 (48%) 619 (52%) 2,135 (49%) 3,066 (48%) female 5,372 (52%) 1,429 (50%) 3,943 (52%) 4,754 (52%) 618 (48%) 2,330 (51%) 3,042 (52%) Race and ethnicity <0.001 <0.001 <0.001 Mexican American 1,239 (5.8%) 380 (7.0%) 859 (5.4%) 1,043 (5.4%) 196 (9.4%) 572 (6.5%) 667 (5.3%) Non-Hispanic White 4,488 (73%) 974 (69%) 3,514 (75%) 4,066 (74%) 422 (60%) 1,799 (71%) 2,689 (75%) Non-Hispanic Black 2,326 (9.3%) 646 (11%) 1,680 (8.9%) 1,989 (8.8%) 337 (15%) 1,062 (11%) 1,264 (8.4%) Other 2,520 (12%) 787 (14%) 1,733 (11%) 2,238 (11%) 282 (16%) 1,032 (12%) 1,488 (12%) Educational attainment(%) 0.063 <0.001 <0.001 High school 5,871 (64%) 1,715 (67%) 4,156 (64%) 5,289 (66%) 582 (52%) 2,445 (61%) 3,426 (67%) Family poverty income ratio(%) <0.001 <0.001 <0.001 <1.3 2,999 (17%) 599 (13%) 2,400 (18%) 2,481 (16%) 518 (31%) 1,408 (21%) 1,591 (14%) 1.3 to < 3.5 4,041 (35%) 1,096 (35%) 2,945 (35%) 3,565 (34%) 476 (39%) 1,737 (37%) 2,304 (33%) ≥3.5 3,533 (48%) 1,092 (51%) 2,441 (47%) 3,290 (50%) 243 (30%) 1,320 (42%) 2,213 (52%) Alcohol drinking status(%) 0.9 0.11 Lifetime abstainer 1,447 (9.6%) 342 (7.5%) 1,105 (10%) 1,275 (9.6%) 172 (9.6%) 544 (8.6%) 903 (10%) Former drink 1,900 (16%) 526 (15%) 1,374 (17%) 1,697 (16%) 203 (16%) 795 (16%) 1,105 (16%) Current drink 7,226 (74%) 1,919 (77%) 5,307 (73%) 6,364 (74%) 862 (75%) 3,126 (75%) 4,100 (73%) Smoking status (%) <0.001 <0.001 <0.001 Lifetime abstainer 5,562 (53%) 1,451 (46%) 4,111 (55%) 5,002 (54%) 560 (42%) 2,074 (44%) 3,488 (58%) Former 3,151 (31%) 904 (36%) 2,247 (29%) 2,821 (31%) 330 (26%) 1,381 (33%) 1,770 (29%) Current 1,860 (17%) 432 (17%) 1,428 (17%) 1,513 (15%) 347 (32%) 1,010 (23%) 850 (13%) Weight status, BMI 0.14 0.2 0.002 18-24 2,161 (21%) 515 (19%) 1,646 (21%) 1,944 (21%) 217 (19%) 821 (19%) 1,340 (22%) 28 5,189 (49%) 1,426 (52%) 3,763 (48%) 4,536 (48%) 653 (52%) 2,354 (52%) 2,835 (46%) Prevalent hypertension(%) 5,221 (44%) 1,396 (48%) 3,825 (43%) 0.005 4,523 (43%) 698 (51%) <0.001 2,321 (49%) 2,900 (41%) <0.001 Prevalent diabetes(%) 2,096 (15%) 565 (16%) 1,531 (15%) 0.2 1,786 (15%) 310 (20%) <0.001 982 (17%) 1,114 (14%) <0.001 Table1(continued) Overall Dental Floss Usage Frequency Characteristic N = 10573 (100%) 1 0 , N = 3614 (28%) 3 1 , N = 593 (6.6%) 3 2 , N = 840 (8.6%) 3 3 , N = 827 (8.8%) 3 4 , N = 506 (5.6%) 3 5 , N = 375 (4.7%) 3 6 , N = 124 (1.7%) 3 7 , N = 3694 (36%) 3 p-value 2 Age <0.001 40 to 59 5,225 (57%) 1,452(51%) 341(65%) 469(61%) 495(64%) 309(68%) 233(70%) 62(57%) 1,864(55%) 60~ 5,348 (43%) 2,162(49%) 252(35%) 371(39%) 332(36%) 197(32%) 142(30%) 62(43%) 1,830(45%) Gender <0.001 male 5,201 (48%) 2,093(58%) 322(53%) 438(55%) 372(45%) 233(44%) 147(41%) 57(41%) 1,539(41%) female 5,372 (52%) 1,521(42%) 271(47%) 402(45%) 455(55%) 273(56%) 228(59%) 67(59%) 2,155(59%) Race and ethnicity <0.001 Mexican American 1,239 (5.8%) 416(6.4%) 67(5.4%) 103(6.2%) 102(5.4%) 59(4.6%) 36(3.5%) 9(3.0%) 447(6.0%) Non-Hispanic White 4,488 (73%) 1,549(70%) 280(78%) 360(74%) 345(75%) 214(77%) 188(79%) 66(82%) 1,486(72%) Non-Hispanic Black 2,326 (9.3%) 911(12%) 115(7.0%) 189(9.3%) 178(8.7%) 119(8.7%) 81(7.5%) 22(6.1%) 711(8.4%) Other 2,520 (12%) 738(11%) 131(9.8%) 188(10%) 202(11%) 114(9.7%) 70(9.9%) 27(9.4%) 1,050(14%) Educational attainment(%) <0.001 High school 5,871 (64%) 1,459(50%) 369(71%) 493(68%) 523(70%) 331(69%) 275(78%) 99(86%) 2,322(69%) Family poverty income ratio(%) <0.001 <1.3 2,999 (17%) 1,473(28%) 126(11%) 209(14%) 167(11%) 96(11%) 68(8.8%) 23(8.9%) 837(14%) 1.3 to < 3.5 4,041 (35%) 1,460(41%) 206(32%) 324(31%) 332(36%) 191(33%) 128(30%) 34(25%) 1,366(32%) ≥3.5 3,533 (48%) 681(31%) 261(57%) 307(55%) 328(53%) 219(57%) 179(62%) 67(67%) 1,491(54%) Alcohol drinking status(%) 0.026 Lifetime abstainer 1,447 (9.6%) 511(11%) 72(9.1%) 98(6.2%) 124(9.9%) 57(7.9%) 38(7.7%) 14(9.4%) 533(9.7%) Former drink 1,900 (16%) 568(14%) 103(15%) 149(16%) 132(14%) 80(16%) 68(16%) 25(10%) 775(19%) Current drink 7,226 (74%) 2,535(74%) 418(76%) 593(78%) 571(76%) 369(76%) 269(77%) 85(80%) 2,386(71%) Smoking status (%) <0.001 Lifetime abstainer 5,562 (53%) 1,535(44%) 338(57%) 480(58%) 503(58%) 294(58%) 218(59%) 75(61%) 2,119(54%) Former 3,151 (31%) 1,172(31%) 164(29%) 235(30%) 200(27%) 143(29%) 100(30%) 39(30%) 1,098(32%) Current 1,860 (17%) 907(26%) 91(15%) 125(13%) 124(14%) 69(13%) 57(11%) 10(8.9%) 477(13%) Weight status, BMI 0.001 18-24 2,161 (21%) 721(19%) 114(20%) 142(17%) 129(14%) 95(23%) 72(20%) 28(21%) 860(25%) <18 76 (0.8%) 36(0.8%) 3(0.3%) 4(0.2%) 4(1.0%) 1(28 5,189 (49%) 1,808(51%) 303(51%) 429(50%) 442(55%) 264(50%) 201(52%) 56(43%) 1,686(44%) Prevalent hypertension(%) 5,221 (44%) 1,962(50%) 267(40%) 385(40%) 383(39%) 246(44%) 170(43%) 50(44%) 1,758(43%) <0.001 Prevalent diabetes(%) 2,096 (15%) 862(19%) 119(17%) 180(16%) 140(13%) 87(12%) 45(9.4%) 15(16%) 648(13%) <0.001 1 n (unweighted) (%); 2 chi-squared test with Rao & Scott's second-order correction; 3 n (unweighted)(%). 3.2 Association between oral health indicators and mortality In the cohort of 10573 individuals included in this study, by the cut-off date of December 31, 2019, a total of 905 all-cause mortality cases were recorded. Analysis revealed that individuals with positive self-assessed oral health, those who had undergone periodontal treatment, individuals who had visited a dentist within the last two years, those not experiencing work impairment due to oral health issues, and people with more frequent use of dental floss within a 7-day period exhibited a lower risk of all-cause mortality (Table 2). After adjusted for covariates, compared to those with poor self-assessed oral health, the hazard ratio (HR) for all-cause mortality for individuals with good oral health was 0.80 (95% CI, 0.67-0.96). Individuals without periodontal treatment exhibit adverse outcomes (HR=1.37,95% CI, 1.09-1.73) compared to their treated counterparts, suggesting an elevated risk. Furthermore, relative to individuals who had visited a dentist within the last two years, the hazard ratios (HRs) for those visiting a dentist within 2-5 years and those over 5 years were 1.16 (95% CI, 0.87-1.56) and 1.35 (95% CI, 1.13-1.62), respectively. Moreover, for individuals experiencing work impairment due to oral health issues compared to those who did not, the HR was 1.33 (95% CI, 1.00-1.76). Additionally, with each additional day of dental floss use within a 7-day period, the HR decreased to 0.94 (95% CI, 0.91-0.98), suggesting a protective effect against all-cause mortality. This study demonstrated the significant association between oral health indicators and all-cause mortality risk. Table 2 Association of oral health behaviors with all-cause mortality among US population age 40 years or older, NHANES, 2011 to 2018. Mortality outcome Death/No. Weighted death (%) Hazard ratio (95 % CI) Age adjusted a Model 1 b Model 2 c Oral Health Self-Assessment poor 332/3610 2509745(0.08) 1 [Reference] 1 [Reference] 1 [Reference] good 573/6963 4719777(0.06) 0.71(0.60- 0.84) 0.78(0.65- 0.94) 0.80(0.67- 0.96) Dental Visit Frequency 5 year 275/1821 1817099(0.13) 1.74(1.42- 2.12) 1.39(1.15- 1.69) 1.35(1.13- 1.62) Oral Health-Related Occupational Impairment No 803/9336 6380345(0.06) 1 [Reference] 1 [Reference] 1 [Reference] Yes 102/1237 849178(0.08) 1.46(1.11- 1.93) 1.46(1.11- 1.93) 1.33(1.00- 1.76) Periodontal Treatment History Yes 160/2787 1322413(0.05) 1 [Reference] 1 [Reference] 1 [Reference] No 745/7786 5907110(0.07) 1.41(1.12- 1.79) 1.35(1.06- 1.72) 1.37(1.09- 1.73) Dental Floss Usage Frequency / / 0.93(0.89- 0.96) 0.94(0.91- 0.98) 0.94(0.91- 0.98) a. Multivariable regression analysis was adjusted for age as a covariate. b. The multivariable regression analysis was further adjusted for gender (male/female), race and ethnicity (non-Hispanic Black, Hispanic, non-Hispanic White, other), educational level(High school), and family poverty income ratio (<1.3, 1.3 to 3.5 ≥3.5). c. Additional adjustments were made for Body Mass Index (BMI), smoking status (never, former, current), alcohol consumption (lifetime abstainer, former, current), hypertension (yes/no) and diabetes (yes/no). 3.3 Construction of Nomogram and Oral Health Index To comprehensively evaluate the oral health status of the population, we integrated dental visit frequency, periodontal treatment history, oral health-related occupational impairment and dental floss usage frequency into a nomogram (Fig. 2) through multivariate Cox regression analysis to derive Oral Health Index (OHI). Kaplan-Meier (KM) analysis indicated that groups with higher scores on OHI exhibited lower all-cause mortality rates compared to those with lower scores ( P <0.001, Fig. 3). To assess the accuracy of the OHI in predicting all-cause mortality, we evaluated its performance using the area under the receiver operating characteristic (ROC) curve (AUC). The result demonstrated that the AUC for OHI (0.64, 95% CI 0.60-0.67) was superior to the population’s self-assessment of oral health (0.52, 95% CI 0.49-0.55) and any single health behavior (Fig. 4). Consequently, OHI demonstrated superior discriminative and calibration properties for predicting all-cause mortality, representing the critical role in all-cause mortality risk. 3.4 Interaction between OHI and PNI It is widely acknowledged that inflammatory and nutritional markers are closely linked to all-cause mortality in populations[24, 28]. Consequently, we explored the relationship between seven inflammatory or nutritional markers and all-cause mortality using univariate Cox regression analysis (Sup Table 2). We further investigated the correlation between the OHI and various inflammatory and nutritional markers. Endless, study showed an interaction between the Prognostic Nutritional Index (PNI) and OHI ( P <0.001). The interaction effect demonstrated a significant decline in the HR with an increase in OHI, indicating a reduced risk of all-cause mortality. This pattern of decline is consistent across three distinct levels of the PNI (46.5, 52, and 58.5, obtained through interaction analysis). The steeper slope observed at lower PNI, indicting adverse nutritional status, suggested that the impact of OHI on reducing hazard ratio becomes more pronounced (Fig 5). This result displayed the importance of considering nutritional status when evaluating the predictive power of OHI for all-cause mortality. It highlighted the nuanced relationship between oral health, nutritional status, and mortality risk, suggesting a synergistic effect where both factors are integral to assessing health outcomes. 3.5 Linearity/non-linearity association between OHI and mortality. In this study, employing Restricted Cubic Splines (RCS) and adjusting for multiple potential confounding factors, we investigated the relationship between OHI and all-cause mortality. Statistical analysis revealed no significant non-linear relationship between OHI and all-cause mortality ( P =0.145, Fig 6). 4. Discussion In this study, we investigated the impact of oral health on all-cause mortality within a nationally representative prospective cohort of adults aged over 40. Our findings uniquely demonstrate the independent effects of oral health-related factors (including factors Self-assessment of Oral Health (SOH), Dental Visit Frequency (DVF), Periodontal Treatment History (PTH), Health-Related Occupational Impairment (HROI), Dental Floss Usage Frequency (DFUF)) on mortality rates. Subsequently, factors DVF, PTH, HROI, and DFUF were incorporated into a Cox proportional hazards model to construct an Oral Health Index (OHI). The analysis revealed that individuals with higher OHI scores exhibited a lower risk of all-cause mortality compared to participants with lower scores. Furthermore, we discovered that the impact of the OHI on mortality rates is modulated by the nutritional status of the population. To our knowledge, our study is the first to predict population mortality risk through OHI constructed from oral health behavior. Additionally, this is the inaugural investigation into the combined effect of oral health behavior and inflammatory nutritional status on the mortality of adults over the age of 40. The association between certain oral health factors and mortality has been well established[31-33]. Tomoki Tanaka reported that indicators of poor oral status, such as the number of natural teeth, chewing ability, articulatory oral motor skills, tongue pressure, and subjective difficulties in eating and swallowing, significantly predicted future physical decline and increased mortality[31]. Jiao Yu found that edentulism was linked to a reduced survival time[33]. Utilizing data from the Golestan Cohort Study in Iran, which included individuals aged 40 to 75, Emily Vogtmann discovered that greater tooth loss was associated with increased overall mortality and death from cardiovascular disease, cancer, and injuries[34]. Poor oral health, including tooth loss, periodontal disease, dry mouth, and self- assessed oral health, has been correlated with mortality[35]. However, the majority of these studies have focused on the correlation between reduced tooth count, gingivitis, and other oral disease states with mortality rates. Our study primarily focuses on the impact of oral health behaviors, including factors DVF, PTH, HROI, and DFUF on mortality rates. We interpret factor DFUF as personal oral care habits, factors DVF and PTH as oral care and treatment received in a clinical setting, and factor HROI as the influence of oral health on social activities. Cox regression analysis indicates that factors including DVF, PTH, HROI, and DFUF independently affect population mortality rates, aligning with previous research findings. Annlia Paganini-Hill reported that nightly toothbrushing, daily flossing, and regular dental visits significantly reduce the risk of all-cause mortality, with the absence of these behaviors increasing mortality by up to 50%[36]. Another study utilizing NHANES data suggested that infrequent dental visits, especially intervals exceeding five years, are associated with a higher risk of mortality from all causes, cardiovascular diseases, and cancer. Visits less than annually for examination and less than biannually for treatment were found to be beneficial[37]. These findings are consistent with our research, further suggesting that changes in oral health behavior can contribute to improved population outcomes. Previous research often focused on the impact of individual oral health behaviors on mortality, neglecting the comprehensive effects of overall oral health behaviors. Therefore, to thoroughly and objectively assess the oral health status of populations, we incorporated factors DVF, PTH, HROI, and DFUF into a nomogram and developed a novel Oral Health Index (OHI). Unlike Self-assessment of Oral Health and individual oral health behaviors, the OHI evaluates the comprehensive condition of oral health through multiple factors, potentially making it a superior predictor of cancer prognosis, as evidenced by the superior Area Under the Curve (AUC) value demonstrated in our analysis (Figure 1). Our findings indicate that individuals with a high OHI have a significantly reduced long-term mortality rate. The mechanism for this significant decrease in population mortality risk may be attributed to the OHI being a comprehensive and relatively objective oral health assessment tool, which minimizes the bias associated with single subjective oral condition evaluations or individual oral health behaviors. Research has highlighted the reciprocal relationship between nutrition and oral health, illustrating how inadequate nutrition can worsen oral health issues like dental caries, periodontal diseases, and oral cancer[1, 20]. Conversely, oral health conditions can significantly impact nutritional intake and status[14, 18]. This bidirectional connection underscores the necessity for integrated management strategies in oral health and nutrition to improve overall health and quality of life. However, studies exploring the link between oral health and systemic inflammation are scarce. E Muñoz Aguilera reported that systemic inflammation acts as a partial intermediary in the relationship between periodontitis and hypertension[38]. Another review emphasizes the pivotal role of systemic inflammation, exacerbated by obesity, in worsening periodontal disease. It notes that adipose tissue acts as an inflammatory organ by secreting cytokines that mediate metabolic and inflammatory pathways, highlighting inflammation as a crucial link in this association[39]. Previous studies have shown that the Prognostic Nutritional Index (PNI), derived from serum albumin levels and lymphocyte counts, serves as an integrated indicator of nutritional status and immune response, acting as a predictor of survival across various diseases[19]. There is growing evidence of PNI's pivotal role as a prognostic marker in diverse conditions, including cancer[27-30], acute heart failure[40], autoimmune diseases[41], chronic kidney disease[42, 43], and more[23-26]. Cox regression analysis has identified PNI as an independent risk factor for prognosis. However, to our knowledge, no studies have yet explored the correlation between PNI and oral health in predicting population mortality rates. Our research is the first to demonstrate an interaction between the Oral Health Index (OHI) and PNI in mortality prediction. In populations with lower PNI levels, indicating average to poor nutritional and inflammatory states, the impact of OHI on prognosis significantly increases. This suggests that individuals with poorer nutritional status should pay closer attention to their oral health. As PNI levels rise, the effect of an increased OHI score on reducing risk ratios diminishes. Additionally, individuals with lower PNI and OHI levels may face higher mortality risks, while those with higher PNI levels and good oral health can significantly reduce their risk of death. 4.1. Strengths and limitations Our study shows distinct strengths and relative limitations. A key strength is its comprehensive inclusion of participants from a nationally representative U.S. survey and the consideration of various confounders, enhancing the generalizability of our findings. Additionally, we utilized easily assessable oral health factors and constructed corresponding nomograms, facilitating improved oral healthcare guidance for a broad population, ultimately yielding more precise survival benefits. Furthermore, our study investigates the correlations between oral health and nutritional and inflammatory indicators, further exploring the potential mechanisms by which oral health impacts prognoses. However, our Oral Health Index was developed using existing data from the NHANES database, which may not the perfect indicator of oral health. Other unknown factors of oral health status assessment on survival necessitates further research. 5. Conclusion In this prospective cohort study involving a nationally representative sample of American adults over 40, superior oral health behaviors and enhanced nutritional and inflammatory status were found to correlate with a decreased risk of all-cause mortality. These insights are crucial for guiding improvements in oral health behaviors and the management of systemic inflammation and nutritional status in the general population. Through detailed analysis of these factors, healthcare professionals may be better to assess an individual's oral and overall health, enabling the formulation of more effective interventions to enhance long-term outcomes. Declarations Acknowledgements Not applicable. Authors’ contributions Conceptualization, QL and HHX; Data curation, WJD; Formal analysis, WJD and PH; Investigation, HHX; Methodology, WJD, PHand QL; Resources, YJZ, TZ and HHX; Software, PH and HHX; Validation, YJZ and TZ; Writing – original draft, PH and WJD. Funding Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article [and its supplementary information files]. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no conflict of interest. Author details Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430000, People’s Republic of China References Kapila, Y.L., Oral health's inextricable connection to systemic health: Special populations bring to bear multimodal relationships and factors connecting periodontal disease to systemic diseases and conditions. Periodontol 2000, 2021. 87 (1): p. 11-16. Glick, M., et al., A new definition for oral health developed by the FDI World Dental Federation opens the door to a universal definition of oral health. J Am Dent Assoc, 2016. 147 (12): p. 915-917. Hakeem, F.F., E. Bernabé, and W. Sabbah, Association Between Oral Health and Frailty Among American Older Adults. J Am Med Dir Assoc, 2021. 22 (3): p. 559-563.e2. Li, Y., et al., The association of periodontal disease and oral health with hypertension, NHANES 2009-2018. BMC Public Health, 2023. 23 (1): p. 1122. Genco, R.J. and W.S. Borgnakke, Diabetes as a potential risk for periodontitis: association studies. Periodontol 2000, 2020. 83 (1): p. 40-45. Kudiyirickal, M.G. and J.M. Pappachan, Diabetes mellitus and oral health. Endocrine, 2015. 49 (1): p. 27-34. Hopkins, S., et al., Oral Health and Cardiovascular Disease. Am J Med, 2023. Priyamvara, A., et al., Periodontal Inflammation and the Risk of Cardiovascular Disease. Curr Atheroscler Rep, 2020. 22 (7): p. 28. Aida, J., et al., Oral health and cancer, cardiovascular, and respiratory mortality of Japanese. J Dent Res, 2011. 90 (9): p. 1129-35. Pathak, J.L., et al., The role of oral microbiome in respiratory health and diseases. Respir Med, 2021. 185 : p. 106475. Nakamura, T., et al., Oral dysfunctions and cognitive impairment/dementia. J Neurosci Res, 2021. 99 (2): p. 518-528. Wei, T., et al., Association between adverse oral conditions and cognitive impairment: A literature review. Front Public Health, 2023. 11 : p. 1147026. Chi, A.C., et al., Oral manifestations of systemic disease. Am Fam Physician, 2010. 82 (11): p. 1381-8. Luo, H., et al., Oral Health, Diabetes, and Inflammation: Effects of Oral Hygiene Behaviour. Int Dent J, 2022. 72 (4): p. 484-490. Eltay, E.G. and T. Van Dyke, Resolution of inflammation in oral diseases. Pharmacol Ther, 2023. 247 : p. 108453. Sreenivasan, P.K., et al., Reductions in clinical inflammation and oral neutrophils with improving oral hygiene. Clin Oral Investig, 2021. 25 (10): p. 5785-5793. Jayasinghe, T.N., et al., Protein Intake and Oral Health in Older Adults-A Narrative Review. Nutrients, 2022. 14 (21). Presskreischer, R., et al., Eating disorders and oral health: a scoping review. J Eat Disord, 2023. 11 (1): p. 55. Bullock, A.F., et al., Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis. Eur J Clin Nutr, 2020. 74 (11): p. 1519-1535. Fang, K.H., et al., Preoperative prognostic nutritional index predicts prognosis of patients with oral cavity cancer. Oral Dis, 2022. 28 (7): p. 1816-1830. Gao, X., et al., The Fib-PNI-MLR Score, an Integrative Model of Coagulation Cascades, Nutrition Status, and Systemic Inflammatory Response, Predicts Urological Outcomes After Surgery in Patients With Non-Metastatic Renal Cell Carcinoma. Front Oncol, 2020. 10 : p. 555152. Chen, M.Y., et al., Association Between Prognostic Nutritional Index and Prognosis in Patients With Heart Failure: A Meta-Analysis. Front Cardiovasc Med, 2022. 9 : p. 918566. Gu, M., et al., Malnutrition and poststroke depression in patients with ischemic stroke. J Affect Disord, 2023. 334 : p. 113-120. Huang, L.F., M.L. Zhu, and Y.R. Ye, Association of nutritional indices and prognosis of stroke patients: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci, 2023. 27 (12): p. 5803-5811. Zhang, J., et al., Prognostic Nutritional Index as a Predictor of Diabetic Nephropathy Progression. Nutrients, 2022. 14 (17). Chen, G., et al., Prognostic nutritional index (PNI) and risk of non-alcoholic fatty liver disease and advanced liver fibrosis in US adults: Evidence from NHANES 2017-2020. Heliyon, 2024. 10 (4): p. e25660. Dai, M. and Q. Sun, Prognostic and clinicopathological significance of prognostic nutritional index (PNI) in patients with oral cancer: a meta-analysis. Aging (Albany NY), 2023. 15 (5): p. 1615-1627. Hua, X., et al., The Value of Prognostic Nutritional Index (PNI) in Predicting Survival and Guiding Radiotherapy of Patients With T1-2N1 Breast Cancer. Front Oncol, 2019. 9 : p. 1562. Niu, Z. and B. Yan, Prognostic and clinicopathological effect of the prognostic nutritional index (PNI) in patients with cervical cancer: a meta-analysis. Ann Med, 2023. 55 (2): p. 2288705. Zhang, X., et al., Combining the Fibrinogen-to-Pre-Albumin Ratio and Prognostic Nutritional Index (FPR-PNI) Predicts the Survival in Elderly Gastric Cancer Patients After Gastrectomy. Onco Targets Ther, 2020. 13 : p. 8845-8859. Tanaka, T., et al., Oral Frailty as a Risk Factor for Physical Frailty and Mortality in Community-Dwelling Elderly. J Gerontol A Biol Sci Med Sci, 2018. 73 (12): p. 1661-1667. Watanabe, Y., et al., Oral health for achieving longevity. Geriatr Gerontol Int, 2020. 20 (6): p. 526-538. Yu, J., et al., Oral Health and Mortality Among Older Adults: A Doubly Robust Survival Analysis. Am J Prev Med, 2023. 64 (1): p. 9-16. Vogtmann, E., et al., Oral health and mortality in the Golestan Cohort Study. Int J Epidemiol, 2017. 46 (6): p. 2028-2035. Kotronia, E., et al., Oral health and all-cause, cardiovascular disease, and respiratory mortality in older people in the UK and USA. Sci Rep, 2021. 11 (1): p. 16452. Paganini-Hill, A., S.C. White, and K.A. Atchison, Dental health behaviors, dentition, and mortality in the elderly: the leisure world cohort study. J Aging Res, 2011. 2011 : p. 156061. Xu, K., et al., Association between dental visit behavior and mortality: a nationwide longitudinal cohort study from NHANES. Clin Oral Investig, 2023. 28 (1): p. 37. Muñoz Aguilera, E., et al., Is systemic inflammation a missing link between periodontitis and hypertension? Results from two large population-based surveys. J Intern Med, 2021. 289 (4): p. 532-546. Pamuk, F. and A. Kantarci, Inflammation as a link between periodontal disease and obesity. Periodontol 2000, 2022. 90 (1): p. 186-196. Chien, S.C., et al., Malnutrition in acute heart failure with preserved ejection fraction: clinical correlates and prognostic implications. ESC Heart Fail, 2019. 6 (5): p. 953-964. Öz, N., et al., Evaluation of the prognostic nutritional index (PNI) as a tool for assessing disease activity in rheumatoid arthritis patients. Clin Rheumatol, 2024. Zhang, J., et al., Relationship between immune nutrition index and all-cause and cause-specific mortality in U.S. adults with chronic kidney disease. Front Nutr, 2023. 10 : p. 1264618. Yu, J.H., Y. Chen, and M.G. Yin, Association between the prognostic nutritional index (PNI) and all-cause mortality in patients with chronic kidney disease. Ren Fail, 2023. 45 (2): p. 2264393. Additional Declarations No competing interests reported. Supplementary Files Suptable1.xls SupTable2.xls Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-4296391","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":293982821,"identity":"6849aa24-b95a-4e30-b55e-864bcc528d4c","order_by":0,"name":"Wanjun 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1","display":"","copyAsset":false,"role":"figure","size":37000,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for population selection from NHANES 2011-2018in this study.\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/68ff519f26bf5c94bedf9bc1.png"},{"id":55551259,"identity":"7c6adbb7-663a-4444-9da7-71d377785be0","added_by":"auto","created_at":"2024-04-29 21:56:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":20828,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNomogram to evaluate the oral health status of the population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/a3027f1072cc277ec171d829.png"},{"id":55551263,"identity":"c6a42fb6-47c1-4cb7-9dd7-8604b6eeb20f","added_by":"auto","created_at":"2024-04-29 21:56:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26702,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier (KM) analysis to investigate the association of OHI and all-cause mortality rates\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Binder13.png","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/54d8136d9d935f152c3e6ae9.png"},{"id":55551261,"identity":"8b9baad4-baed-4201-ac75-d0a44017731f","added_by":"auto","created_at":"2024-04-29 21:56:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":29996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe AUC of OHI and other oral health 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linearity/non-linearity association between OHI and mortality\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Binder16.png","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/8e6165e20bbe664e8dad85cf.png"},{"id":55552146,"identity":"4f8695d8-1537-43aa-ac19-5cd3ebd723c8","added_by":"auto","created_at":"2024-04-29 22:13:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1319027,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/a6bd2c09-4c37-4486-8a1e-d7215be4fd1e.pdf"},{"id":55551260,"identity":"e733fc8b-269c-4815-865d-e0e094f54b41","added_by":"auto","created_at":"2024-04-29 21:56:24","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22528,"visible":true,"origin":"","legend":"","description":"","filename":"Suptable1.xls","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/16cc5dab7d3c8f5e042a9614.xls"},{"id":55551265,"identity":"b2e330ed-1363-40b3-af86-241b37ff8c2d","added_by":"auto","created_at":"2024-04-29 21:56:26","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":26112,"visible":true,"origin":"","legend":"","description":"","filename":"SupTable2.xls","url":"https://assets-eu.researchsquare.com/files/rs-4296391/v1/3213fb8da04192a27ec7d37d.xls"}],"financialInterests":"No competing interests reported.","formattedTitle":"Combined influence of oral health behaviors and nutritional and inflammatory status on risk of all-cause mortality among US population, NHANES 2011-2018","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe World Dental Federation (FDI) redefines oral health as a complex entity, integrating functions essential for speaking, smiling, tasting, touching, chewing, swallowing, and facial expressions[1, 2]. Various factors, including sociopsychological, economic-cultural aspects, and health behavior practices, interplay with individual physiological characteristics, and play pivotal roles in overall health outcomes[2]. Therefore, a more precise assessment of population oral health, along with an understanding of the synergy between oral health status and clinical dental care needs, were crucial for improving overall health outcomes for the population[1].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePoor oral health and dental habits significantly impact overall health[3]. Research indicates a strong link between oral health and various diseases, such as hypertension[4], diabetes[5, 6], cardiovascular diseases[7, 8], respiratory issues[9, 10], cognitive decline[11, 12], and cancers[9]. Consequently, the rise in disease incidence related to oral health problems precipitates a decline in population-wide health status. Potential biological mechanisms may involve inflammatory mediators entering the bloodstream because of oral conditions, leading to systemic chronic inflammation, thereby facilitating the progression of diseases[13-16]. Moreover, poor nutritional status resulting from oral health problems can diminish general physiological conditions, leading to organ dysfunction[17, 18]. Thus, it is significant to consider oral health as a systemic issue and understand its impact on individual health.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSystemic inflammation and nutritional status can be quantified using various hematological markers. The Prognostic Nutritional Index (PNI), calculated through levels of peripheral blood lymphocytes and serum albumin, evaluates the systemic status regarding nutrition, immunity, and inflammation, serving as a comprehensive and reliable biomarker[19]. Initially, PNI was utilized to assess preoperative nutritional status, surgical risk, and postoperative complications in surgical patients[20, 21]. However, subsequent research has indicated that PNI is closely associated with the prognosis of various diseases, including heart failure[22], stroke[23, 24], diabetic nephropathy[25], liver fibrosis[26], and cancer[27-30].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, a comprehensive systematic study that explicates the impact of oral health, systemic inflammation, and nutritional status on all-cause mortality remains absent. Therefore, utilizing the National Health and Nutrition Examination Survey (NHANES) database, we conducted a population-based prospective study to investigate the relationship between overall oral health status and the inflammatory nutritional index, PNI, in relation to all-cause mortality among the population.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) assesses the health and nutritional status of the U.S. population through a stratified multistage sampling methodology. This program gathers demographic and health-related information through interviews and physical examinations. The data, emblematic of the diverse U.S. demographics, facilitate analyses of various health indicators. These analyses are further refined using specialized survey weights, thereby guaranteeing accurate national prevalence estimates.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003e2.1 Study population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDuring the 2011-2018 NHANES cycles, individuals were considered for inclusion in assessments of dental health perception, quality of life queries, and comprehensive oral health examinations. Our analysis centered on 15066 adults who were 40 years or older with accessible oral health information. We excluded participants for insufficient covariate data (n = 3544), lack of oral health data (n = 429), the absence of blood biomarkers (n = 506), and missing of outcomes (n = 14). Consequently, the study progressed with a cohort of 10573 individuals. Tracking of mortality outcomes was synchronized with the National Death Index, culminating on December 31, 2019.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003e2.2 Sociodemographic characteristics, healthy behaviors and conditions. \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSociodemographic characteristics include gender (male and female), race and ethnicity (Mexican American, Non-Hispanic White, Non-Hispanic Black and Others), educational level (\u0026lt;High school, High school,\u0026gt;High school), and family poverty income ratio (\u0026lt; 1.3,1.3-3.5,\u0026gt;3.5). Healthy behaviors consist of Body Mass Index (BMI), smoking status (never smoker, former smoker, current smoker) and alcohol consumption (lifetime abstainer, former, current). In addition, healthy conditions include hypertension (yes/no) and diabetes (yes/no).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3 Oral health status assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn recent years, self-assessed health status assessment systems for diseases and health-related conditions have been extensively employed in population surveys. Prior research indicates that self-assessed oral health issues can reliably predict oral health status, exhibiting a high level of reliability and validity comparable to the outcomes of dental examinations conducted by professionals.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSelf-assessment of Oral Health\u003c/em\u003e (SOH) was conducted by asking \u0026ldquo;Rate the health of your teeth and gums\u0026rdquo;, with responses categorized as good (include excellent, very good and good) and poor (include fair or poor). \u003cem\u003eDental Visit Frequency\u003c/em\u003e (DVF) was determined by asking \u0026ldquo;When did you last visit a dentist\u0026rdquo;, with the responses consist of \u0026lt;2 years, 2-5 years, and more than 5 years. \u003cem\u003ePeriodontal Treatment History\u003c/em\u003e (PTH) was ascertained through the question \u0026quot; ever had treatment for gum disease such as scaling, root planning, and deep cleaning \u0026quot;, with answers being yes or no.\u003cem\u003e Health-Related Occupational Impairment\u003c/em\u003e (HROI) was evaluated by asking \u0026quot; How often during the last year have you had difficulty doing usual jobs or attending school because of problems with teeth, mouth or dentures \u0026quot;, with possible responses being yes (exclude never) or no (never). \u003cem\u003eDental Floss Usage Frequency\u003c/em\u003e (DFUF) was obtained by inquiring \u0026quot; How many days use dental floss/device in the last seven days \u0026quot;, with answers ranging from 0 to 7 days. \u003cem\u003ePeriodontal Disease\u003c/em\u003e (PD) assessment encompassed queries such as \u0026quot; Do you think you might have gum disease \u0026quot;, \u0026quot; How often last year had aching in mouth \u0026quot;, and \u0026quot; ever been told of bone loss around teeth \u0026quot;. An affirmative response to any of these questions indicated the presence of periodontal disease, characterized by symptoms such as gum swelling, recession, pain or infection, or tooth mobility. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003e \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4 Calculation of the Prognostic Nutritional Index (PNI)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePNI = ALB (g/L) + 5 \u0026times; PBL (\u0026times;10^9/L), Alb = serum albumin in grams per deciliter,\u003c/p\u003e\n\u003cp\u003eand PBL= peripheral blood lymphocyte in 10^9 per deciliter.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003e2.5 Evaluation of mortality\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026apos;s primary outcome was all-cause mortality, defined as death from any cause. The follow-up period spanned from the initial interview to either the date of death or the study\u0026apos;s conclusion on December 31, 2019, whichever occurred first.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003e2.6 Statistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study incorporated sample weights, clustering, and stratification in all analyses to ensure national representativeness. Using univariate Cox regression, we evaluated oral health indicators potentially influencing mortality outcomes. Positive findings were included in a multivariable Cox proportional hazards regression model to estimate hazard ratios (HR) and 95% confidence intervals for the association between oral health indicators and overall mortality. The final multivariate model was adjusted for age, gender, race and ethnicity, BMI, family income to poverty ratio, education level, smoking status, alcohol consumption, and health factors (e.g., hypertension and diabetes). Positive oral health indicators from the multivariable Cox regression analysis were incorporated to constructed nomogram and generated Oral Health Index (OHI). Using time-dependent Receiver Operating Characteristic (TimeROC) curves, the most effective prognostic indicator identified was the OHI. To assess the interaction between multiple inflammatory markers (including PNI), and OHI on mortality, multivariable Cox proportional hazards regression models adjusted for the same covariates were used to estimate mortality risk. Finally, restricted cubic splines (RCS) and Cox proportional hazards models elucidated the linear/non-linear relationship between OHI and the risk of all-cause mortality.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cem\u003e3.1 Baseline characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we analyzed a cohort consisting of individuals aged 40 years and older. We excluded participants lacking data for variables under consideration, ultimately established a sample size of 10573 participants (Fig1). This sample represents a weighted population of 7,229,523 individuals. The gender distribution was balanced, with 48% female participants and 52% male participants. Regarding ethnic composition, Mexican American, Non-Hispanic White, Non-Hispanic Black and Others comprised 5.8%, 73%, 9.3%, and 12% of the cohort, respectively. We documented other baseline characteristics of the cohort, including household income, educational levels, smoking and drinking habits, body mass index (BMI), and the prevalence of fundamental health conditions such as hypertension and diabetes. These characteristics are detailed in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings revealed that a significant majority of the participants self-assessment of oral health as good (73%) compared with poor (27%). However, a considerable proportion (40%) reported having periodontal disease. The majority had visited a dentist within the last two years (75%). And 25% of participants had undergone periodontal treatment. Regarding dental floss usage, 28% of the individuals did not use dental floss in the past week, whereas 36% used it daily. Additionally, 9.1 % participants had difficulty doing usual jobs or attending school because of problems with oral health.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Baseline characteristics of US population oral health behaviors.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.224489795918368%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eOral Health Self-Assessment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eDental Visit Frequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003eN = 10573 (100%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003epoor\u003c/strong\u003e, N = 3610 (27%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003egood\u003c/strong\u003e, N = 6963 (73%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;2 year\u003c/strong\u003e, N = 7240 (75%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-5 year\u003c/strong\u003e, N = 1512 (12%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;5 year\u003c/strong\u003e, N = 1821 (13%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e40 to 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,225 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,898 (62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,327 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,668 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e766 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e791 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e60~\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,348 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,712 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,636 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,572 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e746 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,030 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,201 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,844 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,357 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,365 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e765 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,071 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,372 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,766 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,606 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,875 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e747 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e750 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace and ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e1,239 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e633 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e606 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e801 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e202 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e236 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e4,488 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,276 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,212 (77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,103 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e579 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e806 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e2,326 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e886 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,440 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,492 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e372 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e462 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e2,520 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e815 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,705 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,844 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e359 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e317 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational attainment(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026lt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e980 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e504 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e476 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e526 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e159 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e295 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e3,722 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,581 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,141 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,202 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e640 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e880 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026gt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,871 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,525 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e4,346 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e4,512 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e713 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e646 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily poverty income ratio(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026lt;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e2,999 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,467 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,532 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,564 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e543 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e892 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e1.3 to \u0026lt; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e4,041 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,485 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,556 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,650 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e663 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e728 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026ge;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e3,533 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e658 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,875 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,026 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e306 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e201 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol drinking status(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e1,447 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e464 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e983 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,000 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e216 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e231 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eFormer drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e1,900 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e576 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,324 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,342 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e258 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e300 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eCurrent drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e7,226 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,570 (76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e4,656 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e4,898 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,038 (76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,290 (77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,562 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,579 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,983 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e4,159 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e717 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e686 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e3,151 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,061 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,090 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,138 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e460 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e553 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e1,860 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e970 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e890 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e943 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e335 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e582 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight status, BMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e18-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e2,161 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e637 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,524 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,526 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e272 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e363 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026lt;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e76 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e28 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e48 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e47 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e10 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e19 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e24-28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e3,147 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e988 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,159 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e2,213 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e423 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e511 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u0026gt;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,189 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,957 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,232 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,454 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e807 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e928 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent hypertension(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e5,221 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,914 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,307 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e3,453 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e783 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e985 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.27659574468085%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent diabetes(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.702127659574469%\"\u003e\n \u003cp\u003e2,096 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e863 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,233 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e1,336 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e319 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\u003e\n \u003cp\u003e441 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.574468085106384%\"\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\u003e\u003cstrong\u003eTable 1 (continued)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeriodontal Treatment History\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eOral Health-Related Occupational Impairment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeriodontal Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003eN = 10573 (100%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e, N = 2787 (25%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e, N = 7786 (75%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e, N = 9336 (91%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e, N = 1237 (9.1%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e, N = 4465 (40%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e, N = 6108 (60%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e40 to 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,225 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,402 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,823 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,540 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e685 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,297 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,928 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e60~\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,348 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,385 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,963 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,796 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e552 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,168 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,180 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,201 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,358 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,843 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,582 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e619 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,135 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,066 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,372 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,429 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,943 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,754 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e618 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,330 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,042 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace and ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1,239 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e380 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e859 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,043 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e196 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e572 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e667 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4,488 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e974 (69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,514 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,066 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e422 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,799 (71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,689 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2,326 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e646 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,680 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,989 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e337 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,062 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,264 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2,520 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e787 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,733 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,238 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e282 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,032 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,488 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational attainment(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e980 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e218 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e762 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e830 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e150 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e394 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e586 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3,722 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e854 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,868 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,217 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e505 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,626 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,096 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026gt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,871 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,715 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,156 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e5,289 (66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e582 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,445 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,426 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily poverty income ratio(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2,999 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e599 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,400 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,481 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e518 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,408 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,591 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e1.3 to \u0026lt; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e4,041 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,096 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,945 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,565 (34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e476 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,737 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,304 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026ge;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3,533 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,092 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,441 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,290 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e243 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,320 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,213 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol drinking status(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1,447 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e342 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,105 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,275 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e172 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e544 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e903 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eFormer drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1,900 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e526 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,374 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,697 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e203 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e795 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,105 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eCurrent drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e7,226 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,919 (77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e5,307 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e6,364 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e862 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,126 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,100 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,562 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,451 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,111 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e5,002 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e560 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,074 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,488 (58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3,151 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e904 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,247 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,821 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e330 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,381 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,770 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e1,860 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e432 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,428 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,513 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e347 (32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,010 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e850 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight status, BMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e18-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2,161 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e515 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,646 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,944 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e217 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e821 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,340 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026lt;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e76 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e18 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e58 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e64 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e12 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e35 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e41 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e24-28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e3,147 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e828 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,319 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,792 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e355 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,255 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,892 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u0026gt;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,189 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,426 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,763 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,536 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e653 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,354 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,835 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent hypertension(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e5,221 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,396 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e3,825 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e4,523 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e698 (51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,321 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e2,900 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent diabetes(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\"\u003e\n \u003cp\u003e2,096 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e565 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,531 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,786 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e310 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e982 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e1,114 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\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\u003e\u003cstrong\u003eTable1(continued)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.26530612244898%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.142857142857143%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.59183673469387%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eDental Floss Usage Frequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003eN = 10573 (100%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e, N = 3614 (28%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e, N = 593 (6.6%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e, N = 840 (8.6%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e, N = 827 (8.8%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e, N = 506 (5.6%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e, N = 375 (4.7%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e, N = 124 (1.7%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e, N = 3694 (36%)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e40 to 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,225 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,452(51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e341(65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e469(61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e495(64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e309(68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e233(70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e62(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,864(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e60~\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,348 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,162(49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e252(35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e371(39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e332(36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e197(32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e142(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e62(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,830(45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,201 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,093(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e322(53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e438(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e372(45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e233(44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e147(41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e57(41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,539(41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,372 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,521(42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e271(47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e402(45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e455(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e273(56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e228(59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e67(59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,155(59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace and ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e1,239 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e416(6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e67(5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e103(6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e102(5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e59(4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e36(3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e9(3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e447(6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e4,488 (73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,549(70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e280(78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e360(74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e345(75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e214(77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e188(79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e66(82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,486(72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e2,326 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e911(12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e115(7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e189(9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e178(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e119(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e81(7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e22(6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e711(8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e2,520 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e738(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e131(9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e188(10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e202(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e114(9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e70(9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e27(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,050(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational attainment(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026lt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e980 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e538(8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e35(2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e54(2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e51(2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e27(1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e15(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e2(0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e258(3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e3,722 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,617(42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e189(27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e293(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e253(27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e148(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e85(21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e23(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,114(28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026gt;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,871 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,459(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e369(71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e493(68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e523(70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e331(69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e275(78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e99(86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,322(69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily poverty income ratio(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026lt;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e2,999 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,473(28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e126(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e209(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e167(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e96(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e68(8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e23(8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e837(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e1.3 to \u0026lt; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e4,041 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,460(41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e206(32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e324(31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e332(36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e191(33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e128(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e34(25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,366(32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026ge;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e3,533 (48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e681(31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e261(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e307(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e328(53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e219(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e179(62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e67(67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,491(54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol drinking status(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e1,447 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e511(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e72(9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e98(6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e124(9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e57(7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e38(7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e14(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e533(9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eFormer drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e1,900 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e568(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e103(15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e149(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e132(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e80(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e68(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e25(10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e775(19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eCurrent drink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e7,226 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,535(74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e418(76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e593(78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e571(76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e369(76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e269(77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e85(80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,386(71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eLifetime abstainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,562 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,535(44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e338(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e480(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e503(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e294(58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e218(59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e75(61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e2,119(54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e3,151 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,172(31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e164(29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e235(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e200(27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e143(29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e100(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e39(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,098(32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e1,860 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e907(26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e91(15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e125(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e124(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e69(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e57(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e10(8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e477(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight status, BMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e18-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e2,161 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e721(19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e114(20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e142(17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e129(14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e95(23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e72(20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e28(21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e860(25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026lt;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e76 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e36(0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e3(0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e4(0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e4(1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e1(\u0026lt;0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e3(0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e1(0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e24(1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e24-28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e3,147 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,049(29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e173(28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e265(33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e252(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e146(27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e99(28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e39(36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,124(30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u0026gt;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,189 (49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,808(51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e303(51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e429(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e442(55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e264(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e201(52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e56(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,686(44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent hypertension(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e5,221 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,962(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e267(40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e385(40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e383(39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e246(44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e170(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e50(44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e1,758(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.130434782608695%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalent diabetes(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.608695652173913%\"\u003e\n \u003cp\u003e2,096 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e862(19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e119(17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e180(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e140(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e87(12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e45(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\"\u003e\n \u003cp\u003e15(16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.782608695652174%\"\u003e\n \u003cp\u003e648(13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.521739130434782%\"\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\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003en (unweighted) (%); \u003csup\u003e2\u003c/sup\u003echi-squared test with Rao \u0026amp; Scott\u0026apos;s second-order correction; \u003csup\u003e3\u003c/sup\u003en (unweighted)(%).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2 Association between oral health indicators and mortality\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the cohort of 10573 individuals included in this study, by the cut-off date of December 31, 2019, a total of 905 all-cause mortality cases were recorded. Analysis revealed that individuals with positive self-assessed oral health, those who had undergone periodontal treatment, individuals who had visited a dentist within the last two years, those not experiencing work impairment due to oral health issues, and people with more frequent use of dental floss within a 7-day period exhibited a lower risk of all-cause mortality (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter adjusted for covariates, compared to those with poor self-assessed oral health, the hazard ratio (HR) for all-cause mortality for individuals with good oral health was 0.80 (95% CI, 0.67-0.96). Individuals without periodontal treatment exhibit adverse outcomes (HR=1.37,95% CI, 1.09-1.73) compared to their treated counterparts, suggesting an elevated risk. Furthermore, relative to individuals who had visited a dentist within the last two years, the hazard ratios (HRs) for those visiting a dentist within 2-5 years and those over 5 years were 1.16 (95% CI, 0.87-1.56) and 1.35 (95% CI, 1.13-1.62), respectively. Moreover, for individuals experiencing work impairment due to oral health issues compared to those who did not, the HR was 1.33 (95% CI, 1.00-1.76). Additionally, with each additional day of dental floss use within a 7-day period, the HR decreased to 0.94 (95% CI, 0.91-0.98), suggesting a protective effect against all-cause mortality. This study demonstrated the significant association between oral health indicators and all-cause mortality risk.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Association of oral health behaviors with all-cause mortality among US population age 40 years or older, NHANES, 2011 to 2018.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.46938775510204%\" rowspan=\"2\"\u003e\n \u003cp\u003eMortality outcome\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\"\u003e\n \u003cp\u003eDeath/No.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.142857142857143%\" rowspan=\"2\"\u003e\n \u003cp\u003eWeighted death (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.97959183673469%\" colspan=\"3\"\u003e\n \u003cp\u003eHazard ratio (95 % CI)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.680851063829785%\"\u003e\n \u003cp\u003eAge adjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.659574468085108%\"\u003e\n \u003cp\u003eModel 1\u003csup\u003eb \u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.659574468085108%\"\u003e\n \u003cp\u003eModel 2\u003csup\u003ec\u0026nbsp;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eOral Health Self-Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003epoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e332/3610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e2509745(0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e573/6963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e4719777(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.71(0.60- 0.84)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78(0.65- 0.94)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.80(0.67- 0.96)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eDental Visit Frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026lt;2 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e481/7240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e4408016(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e2-5 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e149/1512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e1004408(0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e1.27(0.94- 1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.15(0.86- 1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.16(0.87- 1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026gt;5 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e275/1821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e1817099(0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.74(1.42- 2.12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.39(1.15- 1.69)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.35(1.13- 1.62)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.329896907216494%\" colspan=\"2\"\u003e\n \u003cp\u003eOral Health-Related Occupational Impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e803/9336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e6380345(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e102/1237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e849178(0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.46(1.11- 1.93)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.46(1.11- 1.93)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.33(1.00- 1.76)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003ePeriodontal Treatment History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e160/2787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e1322413(0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1 [Reference]\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e745/7786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e5907110(0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41(1.12- 1.79)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.35(1.06- 1.72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.37(1.09- 1.73)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.711340206185568%\"\u003e\n \u003cp\u003eDental Floss Usage Frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.649484536082475%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.93(0.89- 0.96)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94(0.91- 0.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94(0.91- 0.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003ea. Multivariable regression analysis was adjusted for age as a covariate.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003eb. The multivariable regression analysis was further adjusted for gender (male/female), race and ethnicity (non-Hispanic Black, Hispanic, non-Hispanic White, other), educational level(\u0026lt;High school, High school,\u0026gt;High school), and family poverty income ratio (\u0026lt;1.3, 1.3 to 3.5\u0026nbsp;\u0026ge;3.5).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\"\u003e\n \u003cp\u003ec. Additional adjustments were made for Body Mass Index (BMI), smoking status (never, former, current), alcohol consumption (lifetime abstainer, former, current), hypertension (yes/no) and diabetes (yes/no).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.3 Construction of Nomogram and Oral Health Index\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo comprehensively evaluate the oral health status of the population, we integrated dental visit frequency, periodontal treatment history, oral health-related occupational impairment and dental floss usage frequency into a nomogram (Fig. 2) through multivariate Cox regression analysis to derive Oral Health Index (OHI). Kaplan-Meier (KM) analysis indicated that groups with higher scores on OHI exhibited lower all-cause mortality rates compared to those with lower scores (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, Fig. 3). To assess the accuracy of the OHI in predicting all-cause mortality, we evaluated its performance using the area under the receiver operating characteristic (ROC) curve (AUC). The result demonstrated that the AUC for OHI (0.64, 95% CI 0.60-0.67) was superior to the population\u0026rsquo;s self-assessment of oral health (0.52, 95% CI 0.49-0.55) and any single health behavior (Fig. 4). Consequently, OHI demonstrated superior discriminative and calibration properties for predicting all-cause mortality, representing the critical role in all-cause mortality risk.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.4 Interaction between OHI and PNI\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIt is widely acknowledged that inflammatory and nutritional markers are closely linked to all-cause mortality in populations[24, 28]. Consequently, we explored the relationship between seven inflammatory or nutritional markers and all-cause mortality using univariate Cox regression analysis (Sup Table 2). We further investigated the correlation between the OHI and various inflammatory and nutritional markers. Endless, study showed an interaction between the Prognostic Nutritional Index (PNI) and OHI (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). The interaction effect demonstrated a significant decline in the HR with an increase in OHI, indicating a reduced risk of all-cause mortality. This pattern of decline is consistent across three distinct levels of the PNI (46.5, 52, and 58.5, obtained through interaction analysis). The steeper slope observed at lower PNI, indicting adverse nutritional status, suggested that the impact of OHI on reducing hazard ratio becomes more pronounced (Fig 5). This result displayed the importance of considering nutritional status when evaluating the predictive power of OHI for all-cause mortality. It highlighted the nuanced relationship between oral health, nutritional status, and mortality risk, suggesting a synergistic effect where both factors are integral to assessing health outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.5 Linearity/non-linearity association between OHI and mortality.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, employing Restricted Cubic Splines (RCS) and adjusting for multiple potential confounding factors, we investigated the relationship between OHI and all-cause mortality. Statistical analysis revealed no significant non-linear relationship between OHI and all-cause mortality (\u003cem\u003eP\u003c/em\u003e=0.145, Fig 6).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we investigated the impact of oral health on all-cause mortality within a nationally representative prospective cohort of adults aged over 40. Our findings uniquely demonstrate the independent effects of oral health-related factors (including factors \u003cem\u003eSelf-assessment of Oral Health\u003c/em\u003e (SOH), \u003cem\u003eDental Visit Frequency\u003c/em\u003e (DVF), \u003cem\u003ePeriodontal Treatment History\u003c/em\u003e (PTH), \u003cem\u003eHealth-Related Occupational Impairment\u003c/em\u003e (HROI),\u003cem\u003e\u0026nbsp;Dental Floss Usage Frequency\u003c/em\u003e (DFUF)) on mortality rates. Subsequently, factors DVF, PTH, HROI, and DFUF were incorporated into a Cox proportional hazards model to construct an Oral Health Index (OHI). The analysis revealed that individuals with higher OHI scores exhibited a lower risk of all-cause mortality compared to participants with lower scores. Furthermore, we discovered that the impact of the OHI on mortality rates is modulated by the nutritional status of the population. To our knowledge, our study is the first to predict population mortality risk through OHI constructed from oral health behavior. Additionally, this is the inaugural investigation into the combined effect of oral health behavior and inflammatory nutritional status on the mortality of adults over the age of 40.\u003c/p\u003e\n\u003cp\u003eThe association between certain oral health factors and mortality has been well established[31-33]. Tomoki Tanaka reported that indicators of poor oral status, such as the number of natural teeth, chewing ability, articulatory oral motor skills, tongue pressure, and subjective difficulties in eating and swallowing, significantly predicted future physical decline and increased mortality[31]. Jiao Yu found that edentulism was linked to a reduced survival time[33]. Utilizing data from the Golestan Cohort Study in Iran, which included individuals aged 40 to 75, Emily Vogtmann discovered that greater tooth loss was associated with increased overall mortality and death from cardiovascular disease, cancer, and injuries[34]. Poor oral health, including tooth loss, periodontal disease, dry mouth, and self- assessed oral health, has been correlated with mortality[35]. However, the majority of these studies have focused on the correlation between reduced tooth count, gingivitis, and other oral disease states with mortality rates.\u003c/p\u003e\n\u003cp\u003eOur study primarily focuses on the impact of oral health behaviors, including factors DVF,\u0026nbsp;PTH,\u0026nbsp;HROI, and\u0026nbsp;DFUF\u0026nbsp;on mortality rates. We interpret factor\u0026nbsp;DFUF\u0026nbsp;as personal oral care habits, factors DVF and\u0026nbsp;PTH\u0026nbsp;as oral care and treatment received in a clinical setting, and factor\u0026nbsp;HROI\u0026nbsp;as the influence of oral health on social activities. Cox regression analysis indicates that factors including DVF,\u0026nbsp;PTH,\u0026nbsp;HROI, and\u0026nbsp;DFUF\u0026nbsp;independently affect population mortality rates, aligning with previous research findings. Annlia Paganini-Hill reported that nightly toothbrushing, daily flossing, and regular dental visits significantly reduce the risk of all-cause mortality, with the absence of these behaviors increasing mortality by up to 50%[36]. Another study utilizing NHANES data suggested that infrequent dental visits, especially intervals exceeding five years, are associated with a higher risk of mortality from all causes, cardiovascular diseases, and cancer. Visits less than annually for examination and less than biannually for treatment were found to be beneficial[37]. These findings are consistent with our research, further suggesting that changes in oral health behavior can contribute to improved population outcomes.\u003c/p\u003e\n\u003cp\u003ePrevious research often focused on the impact of individual oral health behaviors on mortality, neglecting the comprehensive effects of overall oral health behaviors. Therefore, to thoroughly and objectively assess the oral health status of populations, we incorporated factors DVF, PTH, HROI, and DFUF into a nomogram and developed a novel Oral Health Index (OHI). Unlike Self-assessment of Oral Health and individual oral health behaviors, the OHI evaluates the comprehensive condition of oral health through multiple factors, potentially making it a superior predictor of cancer prognosis, as evidenced by the superior Area Under the Curve (AUC) value demonstrated in our analysis (Figure 1). Our findings indicate that individuals with a high OHI have a significantly reduced long-term mortality rate. The mechanism for this significant decrease in population mortality risk may be attributed to the OHI being a comprehensive and relatively objective oral health assessment tool, which minimizes the bias associated with single subjective oral condition evaluations or individual oral health behaviors.\u003c/p\u003e\n\u003cp\u003eResearch has highlighted the reciprocal relationship between nutrition and oral health, illustrating how inadequate nutrition can worsen oral health issues like dental caries, periodontal diseases, and oral cancer[1, 20]. Conversely, oral health conditions can significantly impact nutritional intake and status[14, 18]. This bidirectional connection underscores the necessity for integrated management strategies in oral health and nutrition to improve overall health and quality of life. However, studies exploring the link between oral health and systemic inflammation are scarce. E Mu\u0026ntilde;oz Aguilera reported that systemic inflammation acts as a partial intermediary in the relationship between periodontitis and hypertension[38]. Another review emphasizes the pivotal role of systemic inflammation, exacerbated by obesity, in worsening periodontal disease. It notes that adipose tissue acts as an inflammatory organ by secreting cytokines that mediate metabolic and inflammatory pathways, highlighting inflammation as a crucial link in this association[39].\u003c/p\u003e\n\u003cp\u003ePrevious studies have shown that the Prognostic Nutritional Index (PNI), derived from serum albumin levels and lymphocyte counts, serves as an integrated indicator of nutritional status and immune response, acting as a predictor of survival across various diseases[19]. There is growing evidence of PNI\u0026apos;s pivotal role as a prognostic marker in diverse conditions, including cancer[27-30], acute heart failure[40], autoimmune diseases[41], chronic kidney disease[42, 43], and more[23-26]. Cox regression analysis has identified PNI as an independent risk factor for prognosis. However, to our knowledge, no studies have yet explored the correlation between PNI and oral health in predicting population mortality rates. Our research is the first to demonstrate an interaction between the Oral Health Index (OHI) and PNI in mortality prediction. In populations with lower PNI levels, indicating average to poor nutritional and inflammatory states, the impact of OHI on prognosis significantly increases. This suggests that individuals with poorer nutritional status should pay closer attention to their oral health. As PNI levels rise, the effect of an increased OHI score on reducing risk ratios diminishes. Additionally, individuals with lower PNI and OHI levels may face higher mortality risks, while those with higher PNI levels and good oral health can significantly reduce their risk of death.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.1. Strengths and limitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur study shows distinct strengths and relative limitations. A key strength is its comprehensive inclusion of participants from a nationally representative U.S. survey and the consideration of various confounders, enhancing the generalizability of our findings. Additionally, we utilized easily assessable oral health factors and constructed corresponding nomograms, facilitating improved oral healthcare guidance for a broad population, ultimately yielding more precise survival benefits. Furthermore, our study investigates the correlations between oral health and nutritional and inflammatory indicators, further exploring the potential mechanisms by which oral health impacts prognoses. However, our Oral Health Index was developed using existing data from the NHANES database, which may not the perfect indicator of oral health. Other unknown factors of oral health status assessment on survival necessitates further research.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this prospective cohort study involving a nationally representative sample of American adults over 40, superior oral health behaviors and enhanced nutritional and inflammatory status were found to correlate with a decreased risk of all-cause mortality. These insights are crucial for guiding improvements in oral health behaviors and the management of systemic inflammation and nutritional status in the general population. Through detailed analysis of these factors, healthcare professionals may be better to assess an individual\u0026apos;s oral and overall health, enabling the formulation of more effective interventions to enhance long-term outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, QL and HHX; Data curation, WJD; Formal analysis, WJD and PH; Investigation, HHX; Methodology, WJD, PHand QL; Resources, YJZ, TZ and HHX; Software, PH and HHX; Validation, YJZ and TZ; Writing \u0026ndash; original draft, PH and WJD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, Hubei, 430000, People\u0026rsquo;s Republic of China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKapila, Y.L., \u003cem\u003eOral health\u0026apos;s inextricable connection to systemic health: Special populations bring to bear multimodal relationships and factors connecting periodontal disease to systemic diseases and conditions.\u003c/em\u003e Periodontol 2000, 2021. \u003cstrong\u003e87\u003c/strong\u003e(1): p. 11-16.\u003c/li\u003e\n\u003cli\u003eGlick, M., et al., \u003cem\u003eA new definition for oral health developed by the FDI World Dental Federation opens the door to a universal definition of oral health.\u003c/em\u003e J Am Dent Assoc, 2016. \u003cstrong\u003e147\u003c/strong\u003e(12): p. 915-917.\u003c/li\u003e\n\u003cli\u003eHakeem, F.F., E. Bernab\u0026eacute;, and W. Sabbah, \u003cem\u003eAssociation Between Oral Health and Frailty Among American Older Adults.\u003c/em\u003e J Am Med Dir Assoc, 2021. \u003cstrong\u003e22\u003c/strong\u003e(3): p. 559-563.e2.\u003c/li\u003e\n\u003cli\u003eLi, Y., et al., \u003cem\u003eThe association of periodontal disease and oral health with hypertension, NHANES 2009-2018.\u003c/em\u003e BMC Public Health, 2023. \u003cstrong\u003e23\u003c/strong\u003e(1): p. 1122.\u003c/li\u003e\n\u003cli\u003eGenco, R.J. and W.S. Borgnakke, \u003cem\u003eDiabetes as a potential risk for periodontitis: association studies.\u003c/em\u003e Periodontol 2000, 2020. \u003cstrong\u003e83\u003c/strong\u003e(1): p. 40-45.\u003c/li\u003e\n\u003cli\u003eKudiyirickal, M.G. and J.M. Pappachan, \u003cem\u003eDiabetes mellitus and oral health.\u003c/em\u003e Endocrine, 2015. \u003cstrong\u003e49\u003c/strong\u003e(1): p. 27-34.\u003c/li\u003e\n\u003cli\u003eHopkins, S., et al., \u003cem\u003eOral Health and Cardiovascular Disease.\u003c/em\u003e Am J Med, 2023.\u003c/li\u003e\n\u003cli\u003ePriyamvara, A., et al., \u003cem\u003ePeriodontal Inflammation and the Risk of Cardiovascular Disease.\u003c/em\u003e Curr Atheroscler Rep, 2020. \u003cstrong\u003e22\u003c/strong\u003e(7): p. 28.\u003c/li\u003e\n\u003cli\u003eAida, J., et al., \u003cem\u003eOral health and cancer, cardiovascular, and respiratory mortality of Japanese.\u003c/em\u003e J Dent Res, 2011. \u003cstrong\u003e90\u003c/strong\u003e(9): p. 1129-35.\u003c/li\u003e\n\u003cli\u003ePathak, J.L., et al., \u003cem\u003eThe role of oral microbiome in respiratory health and diseases.\u003c/em\u003e Respir Med, 2021. \u003cstrong\u003e185\u003c/strong\u003e: p. 106475.\u003c/li\u003e\n\u003cli\u003eNakamura, T., et al., \u003cem\u003eOral dysfunctions and cognitive impairment/dementia.\u003c/em\u003e J Neurosci Res, 2021. \u003cstrong\u003e99\u003c/strong\u003e(2): p. 518-528.\u003c/li\u003e\n\u003cli\u003eWei, T., et al., \u003cem\u003eAssociation between adverse oral conditions and cognitive impairment: A literature review.\u003c/em\u003e Front Public Health, 2023. \u003cstrong\u003e11\u003c/strong\u003e: p. 1147026.\u003c/li\u003e\n\u003cli\u003eChi, A.C., et al., \u003cem\u003eOral manifestations of systemic disease.\u003c/em\u003e Am Fam Physician, 2010. \u003cstrong\u003e82\u003c/strong\u003e(11): p. 1381-8.\u003c/li\u003e\n\u003cli\u003eLuo, H., et al., \u003cem\u003eOral Health, Diabetes, and Inflammation: Effects of Oral Hygiene Behaviour.\u003c/em\u003e Int Dent J, 2022. \u003cstrong\u003e72\u003c/strong\u003e(4): p. 484-490.\u003c/li\u003e\n\u003cli\u003eEltay, E.G. and T. Van Dyke, \u003cem\u003eResolution of inflammation in oral diseases.\u003c/em\u003e Pharmacol Ther, 2023. \u003cstrong\u003e247\u003c/strong\u003e: p. 108453.\u003c/li\u003e\n\u003cli\u003eSreenivasan, P.K., et al., \u003cem\u003eReductions in clinical inflammation and oral neutrophils with improving oral hygiene.\u003c/em\u003e Clin Oral Investig, 2021. \u003cstrong\u003e25\u003c/strong\u003e(10): p. 5785-5793.\u003c/li\u003e\n\u003cli\u003eJayasinghe, T.N., et al., \u003cem\u003eProtein Intake and Oral Health in Older Adults-A Narrative Review.\u003c/em\u003e Nutrients, 2022. \u003cstrong\u003e14\u003c/strong\u003e(21).\u003c/li\u003e\n\u003cli\u003ePresskreischer, R., et al., \u003cem\u003eEating disorders and oral health: a scoping review.\u003c/em\u003e J Eat Disord, 2023. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 55.\u003c/li\u003e\n\u003cli\u003eBullock, A.F., et al., \u003cem\u003eRelationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis.\u003c/em\u003e Eur J Clin Nutr, 2020. \u003cstrong\u003e74\u003c/strong\u003e(11): p. 1519-1535.\u003c/li\u003e\n\u003cli\u003eFang, K.H., et al., \u003cem\u003ePreoperative prognostic nutritional index predicts prognosis of patients with oral cavity cancer.\u003c/em\u003e Oral Dis, 2022. \u003cstrong\u003e28\u003c/strong\u003e(7): p. 1816-1830.\u003c/li\u003e\n\u003cli\u003eGao, X., et al., \u003cem\u003eThe Fib-PNI-MLR Score, an Integrative Model of Coagulation Cascades, Nutrition Status, and Systemic Inflammatory Response, Predicts Urological Outcomes After Surgery in Patients With Non-Metastatic Renal Cell Carcinoma.\u003c/em\u003e Front Oncol, 2020. \u003cstrong\u003e10\u003c/strong\u003e: p. 555152.\u003c/li\u003e\n\u003cli\u003eChen, M.Y., et al., \u003cem\u003eAssociation Between Prognostic Nutritional Index and Prognosis in Patients With Heart Failure: A Meta-Analysis.\u003c/em\u003e Front Cardiovasc Med, 2022. \u003cstrong\u003e9\u003c/strong\u003e: p. 918566.\u003c/li\u003e\n\u003cli\u003eGu, M., et al., \u003cem\u003eMalnutrition and poststroke depression in patients with ischemic stroke.\u003c/em\u003e J Affect Disord, 2023. \u003cstrong\u003e334\u003c/strong\u003e: p. 113-120.\u003c/li\u003e\n\u003cli\u003eHuang, L.F., M.L. Zhu, and Y.R. Ye, \u003cem\u003eAssociation of nutritional indices and prognosis of stroke patients: a systematic review and meta-analysis.\u003c/em\u003e Eur Rev Med Pharmacol Sci, 2023. \u003cstrong\u003e27\u003c/strong\u003e(12): p. 5803-5811.\u003c/li\u003e\n\u003cli\u003eZhang, J., et al., \u003cem\u003ePrognostic Nutritional Index as a Predictor of Diabetic Nephropathy Progression.\u003c/em\u003e Nutrients, 2022. \u003cstrong\u003e14\u003c/strong\u003e(17).\u003c/li\u003e\n\u003cli\u003eChen, G., et al., \u003cem\u003ePrognostic nutritional index (PNI) and risk of non-alcoholic fatty liver disease and advanced liver fibrosis in US adults: Evidence from NHANES 2017-2020.\u003c/em\u003e Heliyon, 2024. \u003cstrong\u003e10\u003c/strong\u003e(4): p. e25660.\u003c/li\u003e\n\u003cli\u003eDai, M. and Q. Sun, \u003cem\u003ePrognostic and clinicopathological significance of prognostic nutritional index (PNI) in patients with oral cancer: a meta-analysis.\u003c/em\u003e Aging (Albany NY), 2023. \u003cstrong\u003e15\u003c/strong\u003e(5): p. 1615-1627.\u003c/li\u003e\n\u003cli\u003eHua, X., et al., \u003cem\u003eThe Value of Prognostic Nutritional Index (PNI) in Predicting Survival and Guiding Radiotherapy of Patients With T1-2N1 Breast Cancer.\u003c/em\u003e Front Oncol, 2019. \u003cstrong\u003e9\u003c/strong\u003e: p. 1562.\u003c/li\u003e\n\u003cli\u003eNiu, Z. and B. Yan, \u003cem\u003ePrognostic and clinicopathological effect of the prognostic nutritional index (PNI) in patients with cervical cancer: a meta-analysis.\u003c/em\u003e Ann Med, 2023. \u003cstrong\u003e55\u003c/strong\u003e(2): p. 2288705.\u003c/li\u003e\n\u003cli\u003eZhang, X., et al., \u003cem\u003eCombining the Fibrinogen-to-Pre-Albumin Ratio and Prognostic Nutritional Index (FPR-PNI) Predicts the Survival in Elderly Gastric Cancer Patients After Gastrectomy.\u003c/em\u003e Onco Targets Ther, 2020. \u003cstrong\u003e13\u003c/strong\u003e: p. 8845-8859.\u003c/li\u003e\n\u003cli\u003eTanaka, T., et al., \u003cem\u003eOral Frailty as a Risk Factor for Physical Frailty and Mortality in Community-Dwelling Elderly.\u003c/em\u003e J Gerontol A Biol Sci Med Sci, 2018. \u003cstrong\u003e73\u003c/strong\u003e(12): p. 1661-1667.\u003c/li\u003e\n\u003cli\u003eWatanabe, Y., et al., \u003cem\u003eOral health for achieving longevity.\u003c/em\u003e Geriatr Gerontol Int, 2020. \u003cstrong\u003e20\u003c/strong\u003e(6): p. 526-538.\u003c/li\u003e\n\u003cli\u003eYu, J., et al., \u003cem\u003eOral Health and Mortality Among Older Adults: A Doubly Robust Survival Analysis.\u003c/em\u003e Am J Prev Med, 2023. \u003cstrong\u003e64\u003c/strong\u003e(1): p. 9-16.\u003c/li\u003e\n\u003cli\u003eVogtmann, E., et al., \u003cem\u003eOral health and mortality in the Golestan Cohort Study.\u003c/em\u003e Int J Epidemiol, 2017. \u003cstrong\u003e46\u003c/strong\u003e(6): p. 2028-2035.\u003c/li\u003e\n\u003cli\u003eKotronia, E., et al., \u003cem\u003eOral health and all-cause, cardiovascular disease, and respiratory mortality in older people in the UK and USA.\u003c/em\u003e Sci Rep, 2021. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 16452.\u003c/li\u003e\n\u003cli\u003ePaganini-Hill, A., S.C. White, and K.A. Atchison, \u003cem\u003eDental health behaviors, dentition, and mortality in the elderly: the leisure world cohort study.\u003c/em\u003e J Aging Res, 2011. \u003cstrong\u003e2011\u003c/strong\u003e: p. 156061.\u003c/li\u003e\n\u003cli\u003eXu, K., et al., \u003cem\u003eAssociation between dental visit behavior and mortality: a nationwide longitudinal cohort study from NHANES.\u003c/em\u003e Clin Oral Investig, 2023. \u003cstrong\u003e28\u003c/strong\u003e(1): p. 37.\u003c/li\u003e\n\u003cli\u003eMu\u0026ntilde;oz Aguilera, E., et al., \u003cem\u003eIs systemic inflammation a missing link between periodontitis and hypertension? Results from two large population-based surveys.\u003c/em\u003e J Intern Med, 2021. \u003cstrong\u003e289\u003c/strong\u003e(4): p. 532-546.\u003c/li\u003e\n\u003cli\u003ePamuk, F. and A. Kantarci, \u003cem\u003eInflammation as a link between periodontal disease and obesity.\u003c/em\u003e Periodontol 2000, 2022. \u003cstrong\u003e90\u003c/strong\u003e(1): p. 186-196.\u003c/li\u003e\n\u003cli\u003eChien, S.C., et al., \u003cem\u003eMalnutrition in acute heart failure with preserved ejection fraction: clinical correlates and prognostic implications.\u003c/em\u003e ESC Heart Fail, 2019. \u003cstrong\u003e6\u003c/strong\u003e(5): p. 953-964.\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;z, N., et al., \u003cem\u003eEvaluation of the prognostic nutritional index (PNI) as a tool for assessing disease activity in rheumatoid arthritis patients.\u003c/em\u003e Clin Rheumatol, 2024.\u003c/li\u003e\n\u003cli\u003eZhang, J., et al., \u003cem\u003eRelationship between immune nutrition index and all-cause and cause-specific mortality in U.S. adults with chronic kidney disease.\u003c/em\u003e Front Nutr, 2023. \u003cstrong\u003e10\u003c/strong\u003e: p. 1264618.\u003c/li\u003e\n\u003cli\u003eYu, J.H., Y. Chen, and M.G. Yin, \u003cem\u003eAssociation between the prognostic nutritional index (PNI) and all-cause mortality in patients with chronic kidney disease.\u003c/em\u003e Ren Fail, 2023. \u003cstrong\u003e45\u003c/strong\u003e(2): p. 2264393.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\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":"oral health, PNI, NHANES, all-cause mortality","lastPublishedDoi":"10.21203/rs.3.rs-4296391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4296391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Oral health and inflammation and nutritional status are interconnected, each bearing significant correlation with long-term prognoses in populations. We investigated the interactions and correlations among nutritional and inflammatory indictors, oral health, and all-cause mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A nationally representative prospective cohort sample was recruited from the National Health and Nutrition Examination Survey (NHANES) conducted in the United States from 2011 to 2018, selecting individuals aged 40 or above (n=10573; weighted population: 7229522) with comprehensive oral health assessments and related biomarkers. Oral health was quantified using multiple indicators to construct an Oral Health Index (OHI), and the Prognostic Nutritional Index (PNI) was employed to reflect general inflammatory and nutritional status. The independent effects of OHI and PNI on all-cause mortality were examined across the population, alongside their interactive prognostic implications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The study included 10573 participants with complete oral health and related data. Adjusted models revealed that better self- assessed oral health (HR=0.80; 95%CI: 0.67-0.96) and more frequent use of dental floss (HR=0.94; 95%CI: 0.91-0.98) were associated with lower all-cause mortality rates. Conversely, individuals with dental visits exceeding five years (HR=1.35; 95%CI: 1.13-1.62), occupational oral health hazards (HR=1.33; 95%CI: 1.00-1.76), or no history of periodontal cleaning or treatment (HR=1.37; 95%CI: 1.09-1.73) faced higher mortality rates. A higher PNI indicated a lower all-cause mortality risk (HR=0.9; p\u0026lt;0.001). The correlation between the constructed OHI and all-cause mortality was confirmed (HR=0.99, P\u0026lt;0.001), with interaction analysis showing a significantly increased impact of OHI on prognosis at lower PNI levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This cohort study observed the effects of oral health and nutritional/inflammatory statuses on all-cause mortality, identifying the lowest risk of mortality among populations with high OHI and PNI levels.\u003c/p\u003e","manuscriptTitle":"Combined influence of oral health behaviors and nutritional and inflammatory status on risk of all-cause mortality among US population, NHANES 2011-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 21:56:19","doi":"10.21203/rs.3.rs-4296391/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":"4fc732be-dc35-4f8a-90fb-6446a42b9ace","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-09T09:38:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 21:56:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4296391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4296391","identity":"rs-4296391","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}