Association between “A Body Shape Index” (ABSI) with periodontitis in a hypertension population from the NHANES 2009–2014

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The ABSI has also been shown to be positively and linearly correlated with the amount of visceral adiposity in the general population and with all-cause and cardiovascular disease (CVD). However, it is uncertain whether ABSI is associated with periodontitis in hypertensive patients. Methods A cross-sectional study of 2,482 hypertensive patients (mean age 65.2 ± 9.1 years) was conducted using the ABSI Z score, periodontitis as a dichotomous variable, the ABSI Z score as a continuous variable, and multiple covariates such as age, gender, and race. The data were analyzed using descriptive statistics, multiple logistic regression, subgroup analysis with EmpowerStats (version 4.2), and curve transformation plots were generated. Results In multivariate logistic regression analysis, ABSI Z score showed a significant positive association with periodontitis in the hypertensive population in all three models. When ABSI Z score was divided into low, medium, and high three groups, we observed that those with the highest ABSI Z score had a 20% increased risk of periodontitis among people with hypertension (OR = 1.2; 95%CI, 1.0-1.5, P = 0.046). We used smooth curve fitting to confirm the results and found that these results were still supported, and additional subgroup analyses showed that the positive association between ABSI Z score and periodontitis in hypertensive population was stable and consistent in the general population. Conclusion The present cross-sectional investigation showed a positive association between ABSI Z score and periodontitis in a hypertensive population. Health sciences/Diseases Health sciences/Risk factors A Body Shape Index ABSI Z score Periodontitis NHANES Cross-sectional study Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Periodontitis is a prevalent disease that affects more than 40% of adults in the United States, and globally, the severe form of the disease affects 11.2% of the population, making it the sixth most common human disease in the world 1 , 2 . The main risk factors for periodontal disease are poor oral hygiene among others 3 . People with periodontal disease experience symptoms such as pain and discomfort in the mouth, and the condition, if not prevented and further worsened, will lead to loss of attachment, resulting in periodontitis 4 . Periodontitis and hypertension are among the most common non-communicable chronic diseases in the world 5 . In addition to common risk factors, a growing body of evidence supports a possible association between the two diseases 6 . The inflammatory response caused by periodontitis may lead to elevated levels of systemic inflammation, which can affect vascular function and blood pressure regulation 7 . Periodontitis and hypertension share common risk factors, including genetic predisposition, advanced age, and unhealthy lifestyle choices like poor dietary habits and lack of physical activity 5 . These factors may play an important role in the development of both diseases. In recent years, researchers have increasingly used a variety of indicators to assess the accumulation of body fat and its impact on health, including the ABSI (A Body Shape Index). Research has shown a positive correlation between the ABSI and visceral obesity 8 , cardiovascular disease risk, and all-cause mortality 9 , with the ABSI being a more effective predictor of the potential health effects of obesity 10 . Specifically, one study analyzing the data found that for every one unit increase in ABSI, there was a 1.13-fold increase in mortality. Individuals with larger ABSI values had a 61% higher mortality rate compared to individuals with smaller ABSI values 11 . Therefore, simply relying on body weight to predict the health effects of obesity is not enough; we need to focus on the body shape of the individual 12 . ABSI, as a measure of roundness and visceral fat accumulation in the human body, focuses on the percentage of waist circumference in the roundness index, and is therefore scientifically important in assessing the health effects of obesity 13 . Oral health has been reported to be closely related to general health, including cardiovascular health such as hypertension 14 , 15 . In previous studies, the ABSI has been used primarily to assess cardiovascular disease and found a strong association between them 9 , 16 . However, no one has used the ABSI to assess periodontitis. Therefore, in this study, we explored the relationship between ABSI Z score and periodontitis in a hypertensive population to fill this information gap. Methods The study used data from the National Health and Nutrition Examination Survey (NHANES), approved by the Research Ethics Review Board of the National Center for Health Statistics. All methods were conducted in accordance with relevant guidelines, and all participants provided written permission at recruitment 17 ( NHANES - NCHS Research Ethics Review Board Approval (cdc.gov) ). The initial analysis of the study involved periodontitis data from 30,468 participants from 2009 to 2014. Inclusion criteria for the study included participants being 30 years of age and older and taking anti-hypertensive medications; NHANES participants received waist circumference, BMI, and height measurements; and participants received a periodontal exam during the oral health screening portion of the program. Exclusion criteria included participants who did not receive a complete periodontal exam or who received an exam but were not taking hypertension medication; very few participants were missing covariates such as education, marriage, hypertension, and sleep disorders. Ultimately, after screening, the study yielded a sample of 2,483 eligible individuals (Fig. 1 ). Classification of periodontitis According to the NHANES guidelines, only subjects 30 years of age and older underwent a full-mouth periodontal examination in which the loss of attachment and pocket depth around each tooth was measured 18 . Based on criteria provided by the CDC/AAP Case Definitions (Centers for Disease Control and Prevention/American Academy of Periodontology), we categorized periodontal status as mild, moderate, severe periodontitis, and no periodontitis. The detailed method of grading periodontitis is shown in Fig. 2 19 . Absence of periodontitis and mild inflammation were defined as having no periodontitis, whereas moderate and severe inflammation were defined as having periodontitis 20 . Table 1 characteristics of the study participants grouped by periodontitis status Characteristics Total Non-/mild periodontitis Moderate/severe periodontitis P-value N = 2,482 N = 1,017 N = 1,465 ABSI 1.3 ± 0.1 1.3 ± 0.1 1.3 ± 0.1 < 0.001 ABSI Z-score -0.0 ± 1.0 -0.1 ± 1.0 0.1 ± 1.0 < 0.001 Height (inches) 66.4 ± 4.1 66.1 ± 4.2 66.7 ± 4.1 < 0.001 BMI (kg/㎡) 30.6 ± 6.6 30.9 ± 6.5 30.3 ± 6.6 0.023 Waist (cm) 104.8 ± 15.0 104.7 ± 14.3 104.9 ± 15.6 0.815 Age (years) 65.2 ± 9.1 64.3 ± 9.0 65.7 ± 9.2 < 0.001 Gender (%) < 0.001 Male 1191 (48.0%) 382 (37.6%) 809 (55.2%) Female 1291 (52.0%) 635 (62.4%) 656 (44.8%) Education level (%) < 0.001 Less than high school 616 (24.8%) 174 (17.1%) 442 (30.2%) High school 598 (24.1%) 219 (21.6%) 379 (25.9%) More than high school 1265 (51.0%) 623 (61.3%) 642 (43.9%) Marital status (%) 0.050 Married 1405 (56.6%) 596 (58.6%) 809 (55.2%) Widowed 378 (15.2%) 162 (15.9%) 216 (14.7%) Divorced 353 (14.2%) 139 (13.7%) 214 (14.6%) Others 346 (13.9%) 120 (11.8%) 226 (15.4%) Race (%) < 0.001 Mexican American 264 (10.6%) 88 (8.7%) 176 (12.0%) Other Hispanic 208 (8.4%) 83 (8.2%) 125 (8.5%) Non-Hispanic White 1098 (44.2%) 528 (51.9%) 570 (38.9%) Non-Hispanic Black 706 (28.4%) 241 (23.7%) 465 (31.7%) Other Race-Including Multi-Racial 206 (8.3%) 77 (7.6%) 129 (8.8%) Annual alcohol consumption (%) 0.360 At least 12 alcohol drinks 1639 (68.4%) 666 (67.3%) 973 (69.1%) Less than 12 alcohol drinks 758 (31.6%) 323 (32.7%) 435 (30.9%) Fatigue/a week (%) 0.115 Never 1294 (54.2%) 510 (51.7%) 784 (56.0%) Moderately 661 (27.7%) 286 (29.0%) 375 (26.8%) Frequently 431 (18.1%) 190 (19.3%) 241 (17.2%) Number of flossing/a week (%) < 0.001 Never 789 (32.2%) 229 (22.7%) 560 (38.8%) Rarely 331 (13.5%) 138 (13.7%) 193 (13.4%) Moderately 395 (16.1%) 204 (20.3%) 191 (13.2%) Frequently 937 (38.2%) 436 (43.3%) 501 (34.7%) Sleep disorder (%) 0.231 Yes 836 (33.7%) 360 (35.4%) 476 (32.5%) No 1646 (66.3%) 657 (64.6%) 989 (67.5%) General health condition (%) < 0.001 Excellent 125 (5.2%) 59 (6.0%) 66 (4.7%) Very good 556 (23.1%) 264 (26.7%) 292 (20.6%) Good 999 (41.5%) 407 (41.1%) 592 (41.8%) Fair 580 (24.1%) 213 (21.5%) 367 (25.9%) Poor 147 (6.1%) 47 (4.7%) 100 (7.1%) Diabetes history (%) < 0.001 Yes 653 (26.3%) 225 (22.1%) 428 (29.2%) No 1692 (68.2%) 731 (71.9%) 961 (65.6%) Not recorded 137 (5.5%) 61 (6.0%) 76 (5.2%) * p < 0.05 Continuous variables: mean +/- SD, P value from linear regression Categorical variables: percentage, P value from Chi-square tests Definition of A Body Shape Index (ABSI) The Body Shape Index (ABSI) is an index used to assess the relationship between body shape and health risk, and was proposed by researchers at the City University of New York in 2012. ABSI normalizes waist circumference (WC) to body size by considering both weight and height, similar to how body mass index (BMI) normalizes weight in relation to height. ABSI is statistically independent of BMI, while the variability in non-normalized WC is largely explained by BMI 21 . We defined ABSI as derived from the NHANES reference population 22 : $$BMI= W\times {H}^{-2},$$ $$ABSI= WC/({\text{B}\text{M}\text{I}}^{(2/3)} \times {\text{H}}^{(1/2)} ),$$ where W refers to the weight, H refers to the height, and WC stands for waist circumference. We converted the ABSI into ABSI Z score based on the scores and categorized them into low, moderate, and high groups: low (ABSI Z score < -0.272), moderate (-0.272 ≤ ABSI Z score < 0.229), and high (ABSI Z score ≥ 0.229) 23 , thus following the general formula: $$Z-score= \frac{value - mean}{std. dev. }.$$ Covariates We combined 10 confounding factors that may influence the relationship between periodontitis and hypertension, including gender, age, race, education, marital status, annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition 24 . A detailed description of the covariates can be found on the NHANES website. Statistical analysis We integrated and statistically analyzed the data using the EmpowerStats (version 4.2; https://www.empowerstats.net/cn/ ) and R software (version 4.3.2; https://www.r-project.org/ ) packages. Categorical variables were expressed as percentages and continuous variables as standard deviations. We developed a multivariate logistic regression model to investigate the independent relationship between ABSI Z score and moderate/severe periodontitis in a hypertensive population. The strength of the relationship was determined by calculating the odds ratio (OR) with 95% confidence intervals, and ABSI Z score was categorized into three classes, with the lower class serving as the reference. We developed three models: model I was not adjusted for covariates; model II was adjusted for gender, age, marital status, education level and race; and model III added other covariates to model II, such as annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition. We also applied a smoothed curve transformation to explore the possible nonlinear relationship between ABSI Z score and periodontitis. In this study, p < 0.05 were considered statistically significant. Results General characteristics of the study population A total of 2842 patients were included after applying appropriate exclusion criteria. Figure 1 illustrates the process of screening participants. Covariates were dichotomously distributed according to no/mild or moderate/severe periodontitis. Table 1 summarizes the baseline characteristics of patients with and without periodontitis in the hypertensive population. Overall, there were significant differences between the no/mild periodontitis and moderate/severe periodontitis groups in terms of ABSI, ABSI Z-score, height, BMI, age, gender, race, marital status, education, number of flossing sessions, general health, and history of diabetes mellitus (P < 0.05). While there was no significant difference between waist circumference, Annual alcohol consumption, days of fatigue in a week, and sleep disorders (Table 1 ). Logistic regression analysis The relationship between ABSI Z-score and periodontitis in the hypertensive population is shown in Table 2 , which is the result of multivariate logistic regression analysis. In the original model, ABSI Z-score was significantly and positively correlated with periodontitis, with a ratio of 1.2 (95CI: 1.1,1.3, p < 0.001). The robust and favorable association in Model 2 remained highly significant (OR = 1.1; 95%CI: 1.0,1.2; p = 0.006) after accounting for factors such as gender, age, and race. Then in Model 3, which was built on the basis of Model 2, after adjusting for all variables, the correlation between ABSI and periodontitis remained statistically significant (OR = 1.1; 95%CI: 1.0,1.2; P = 0.015). After converting ABSI Z score from continuous to categorical variables, we observed a striking result. In all three models, the association between the high ABSI Z score group and periodontitis showed a statistically significant association. Participants in the highest group had a significant 20% increased risk of periodontitis compared to those in the low ABSI Z score group (OR = 1.2; 95% CI, 1.0-1.5, p = 0.046). This study found that increased ABSI Z-score were positively associated with the risk of developing periodontitis in hypertensive population and we confirmed the results using smoothed curve fitting as shown in Fig. 3 and found that the standard linear regression of the results was still supported. Table 2 Association of periodontitis with ABSI Z-score in the hypertensive population Exposure Unadjusted model OR (95% CI) p Adjusted Model I OR (95% CI) p Adjusted Model II OR (95% CI) p ABSI Z-score 1.2(1.1,1.3) < 0.001 1.1(1.0,1.2)0.006 1.1(1.0,1.2)0.015 ABSI Z-score (groups) Low 1.0 1.0 1.0 Moderate 1.3(1.1,1.6)0.013 1.2(0.9,1.5)0.128 1.2(0.9,1.5)0.129 High 1.4(1.2,1.7) < 0.001 1.2(1.0,1.5)0.040 1.2(1.0,1.5)0.046 * p < 0.05 Model 1: no adjustment for covariates. Model 2: adjusted for sex, age, marital status, education level and race. Model 3: adjusted for sex, age, marital status, education level, race, annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition. ABSI Z-score (groups): low (ABSI Z score < -0.272), moderate (-0.272 ≤ ABSI Z score < 0.229), and high (ABSI Z score ≥ 0.229). Subgroup analysis To evaluate the stability of the relationship between ABSI score and periodontitis in hypertensive populations, as well as to identify potential differences between the two in different populations, subgroup analyses were conducted. The results of these analyses are presented in Fig. 4 . Except for men who were widowed or divorced, rarely floss, moderately floss, and in excellent health condition, ABSI Z score was significantly positively associated with periodontitis in hypertensives. Furthermore, we observed that the 'interaction P-value' was greater than 0.05, suggesting that the positive correlation between the ABSI Z score and periodontitis in the hypertensive population is typically stable and consistent across the general population. Discussion In this cross-sectional study, we found for the first time an association between ABSI Z score and periodontitis in a hypertensive population. After studying 2,482 participants, it was found that periodontitis was positively associated with ABSI. Specifically, we observed a corresponding increase in the risk of developing periodontitis as ABSI Z score increased, and this association held true after accounting for confounding variables. In addition, our study revealed that the association between ABSI Z score and periodontitis in the hypertensive population was independent of a variety of other factors, including age, gender, race, marital status, education, frequency of flossing and general health. These findings emphasize the potential importance of ABSI value in the pathogenesis of periodontitis and provide useful clues for further research and intervention. In the past, the medical community used to widely use the body mass index, BMI, to measure the degree of obesity 25 . BMI is calculated as the weight divided by the square of the height, and the normal range of this index is from 18.5 to 24, and if it is more than 24, it is overweight, and if it is more than 28, it is obese 26 . In addition, the waist circumference indicator is used to measure central obesity 27 , men with a waist circumference of more than 90 centimeters and women with a waist circumference of more than 85 centimeters are abdominal obese 28 . It is not difficult to see that BMI, as well as WC, are relatively rough standards 22 , 29 . Therefore, scholars have been looking for more reliable, and easy-to-use indicators. In recent years, the indicators used to measure the accumulation of visceral fat and its impact have become increasingly recognized 29 , 30 . Among them, the widely acknowledged indicator is the Body Shape Index (ABSI) 31 . ABSI was proposed by scholars from the City College of New York in 2012 22 . ABSI has been suggested as an alternative parameter to reflect differences in body shape. Studies have indicated a positive correlation between ABSI and visceral fat, cardiovascular disease risk 12 , and all-cause mortality 32 . Many scholars have analyzed studies on large sample sizes in the US population, such as Aoki et al who found that ABSI could predict the risk of CVD manifestations more significantly than BMI 33 . This was also confirmed in a study by Wu et al 34 , who observed that anthropometric indicators including BMI, ABSI, etc. were strongly associated with hypertension risk, and that these new anthropometric indicators should be emphasized for better prevention and treatment of hypertension. Furthermore, a cross-sectional study by Lin et al 35 found that the score of ABSI was linearly correlated with the risk of kidney stone prevalence, which can be used as an important indicator for assessing the risk of kidney stones. Kuang M et al 36 found that ABSI may help define the risk of sarcopenia in overweight/obese individuals. In addition, some scholars have found that the ABSI combined with BMI best identifies the risk of obesity-related non-alcoholic fatty liver disease (NAFLD) and is significantly better than BMI or WC or ABSI 37 . Therefore, ABSI should be more closely monitored and preventive medical management than BMI. It is well known that hypertension is one of the major risk factors for cardiovascular disease 38 , so this study was chosen to be conducted in a hypertensive population; however, no one has yet conducted an in-depth study of the relationship between the ABSI Z score and periodontitis in a hypertensive population, so there is no reason why the relationship between the ABSI Z score and periodontitis should not be explored. If feasible, the ABSI Z score could also be used as an indicator to assess oral health, especially periodontal health. Where possible, every effort has been made to explain how they are linked. The possible reasons are summarized below. Relevant studies have confirmed that central obesity, with excessive accumulation of visceral adipose tissue, leads to vascular inflammation 39 , and the body's immune system is activated, leading to the release of inflammatory mediators and the onset of an inflammatory response 40 . These inflammatory mediators can circulate through the bloodstream to all parts of the body, including the periodontal tissues in the mouth 41 . In periodontal tissues, the release of inflammatory mediators causes vasodilatation, increased permeability, and infiltration of inflammatory cells, leading to an inflammatory response and damage to localized tissues 42 . The inflammatory response caused by vascular inflammation in the periodontal tissues may lead to symptoms such as gingival redness, swelling, bleeding, gingival pocket formation, and periodontal bone resorption, which eventually develops into periodontitis 43 . Conclusion It is concluded that by analyzing the data, we found a significant positive correlation between ABSI Z score and prevalence of periodontitis in hypertensive population. The results suggest that ABSI Z score is a valid predictor of a wide range of diseases and their inflammation, such as periodontitis. More studies on the causal and longitudinal relationships between ABSI Z score and risk of periodontitis are necessary. Abbreviations BMI, body mass index; WC, waist circumference; ABSI, Body Shape Index; NHANES, National Health and Nutrition Examination Survey; CI, confidence interval; OR, odds ratio; SD, standard deviation; AL, Attached Level; CDC-AAP, the Centers for Disease Control and Prevention and the American Academy of Periodontology; NAFLD, non-alcoholic fatty liver disease. Declarations Acknowledgements: We want to thank the NHANES databases for making this data available. Authors' contributions: Xuanyan Gu was responsible for study design, data collection, data merging, and data analysis, as well as drafting the manuscript. Shiyi Luo provided expertise in data interpretation. Fuqian Jin assisted in data merging. Jukun Song, Zhu Chen, and Jiangling Sun contributed to the review and editing process. All authors have reviewed and approved the final version of the manuscript. Funding: This work was supported by supported by the Guiyang Science and Technology Support Program (2022-4-12-4). Availability of data and materials: The complete dataset is accessible through the NHANES database, which can be located at the following link: https://www.cdc.gov/nchs/nhanes/index.htm. Ethics approval and consent to participate: The NHANES repository is both representative and openly available at no cost. Approval for the study's methodology was granted by the Research Ethics Review Board of the National Center for Health Statistics. Consent for publication: Not applicable. Competing interests: All authors declare no competing interests. References Kwon, T., Lamster, I. B. & Levin, L. Current Concepts in the Management of Periodontitis. International dental journal 71, 462–476, doi: 10.1111/idj.12630 (2021). Sanz, M. et al. Periodontitis and cardiovascular diseases: Consensus report. Journal of clinical periodontology 47, 268–288, doi: 10.1111/jcpe.13189 (2020). 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Cureus 14, e23886, doi: 10.7759/cureus.23886 (2022). Wu, L. D., Kong, C. H., Shi, Y., Zhang, J. X. & Chen, S. L. Associations between novel anthropometric measures and the prevalence of hypertension among 45,853 adults: A cross-sectional study. Frontiers in cardiovascular medicine 9, 1050654, doi: 10.3389/fcvm.2022.1050654 (2022). Lin, G., Zhan, F., Ren, W., Pan, Y. & Wei, W. Association between novel anthropometric indices and prevalence of kidney stones in US adults. World journal of urology 41, 3105–3111, doi: 10.1007/s00345-023-04582-x (2023). Biolo, G. et al. Inverse relationship between "a body shape index" (ABSI) and fat-free mass in women and men: Insights into mechanisms of sarcopenic obesity. Clinical nutrition (Edinburgh, Scotland) 34, 323–327, doi: 10.1016/j.clnu.2014.03.015 (2015). Kuang, M. et al. The value of combining the simple anthropometric obesity parameters, Body Mass Index (BMI) and a Body Shape Index (ABSI), to assess the risk of non-alcoholic fatty liver disease. Lipids in health and disease 21, 104, doi: 10.1186/s12944-022-01717-8 (2022). Raddaoui, Y. et al. Role of depression in blood pressure control. A cross-sectional multicentric study. La Tunisie medicale 102, 7–12, doi: 10.62438/tunismed.v102i1.4723 (2024). Ellulu, M. S., Patimah, I., Khaza'ai, H., Rahmat, A. & Abed, Y. Obesity and inflammation: the linking mechanism and the complications. Archives of medical science: AMS 13, 851–863, doi: 10.5114/aoms.2016.58928 (2017). Lastra, G. & Sowers, J. R. Obesity and cardiovascular disease: role of adipose tissue, inflammation, and the renin-angiotensin-aldosterone system. Hormone molecular biology and clinical investigation 15, 49–57, doi: 10.1515/hmbci-2013-0025 (2013). Abdulkhaleq, L. A. et al. The crucial roles of inflammatory mediators in inflammation: A review. Veterinary world 11, 627–635, doi: 10.14202/vetworld.2018.627-635 (2018). Cekici, A., Kantarci, A., Hasturk, H. & Van Dyke, T. E. Inflammatory and immune pathways in the pathogenesis of periodontal disease. Periodontology 2000 64, 57–80, doi: 10.1111/prd.12002 (2014). Papadopoulos, G. et al. Macrophage-specific TLR2 signaling mediates pathogen-induced TNF-dependent inflammatory oral bone loss. Journal of immunology (Baltimore, Md. : 1950) 190, 1148–1157, doi: 10.4049/jimmunol.1202511 (2013). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4562396","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":319682486,"identity":"0a041def-cd93-4300-94dd-1b601f47b59d","order_by":0,"name":"Xuanyan Gu","email":"","orcid":"","institution":"Medical College of Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Xuanyan","middleName":"","lastName":"Gu","suffix":""},{"id":319682488,"identity":"63ab3be2-1d94-423a-978d-a077bb93efe4","order_by":1,"name":"Shiyi Luo","email":"","orcid":"","institution":"Medical College of Guizhou University","correspondingAuthor":false,"prefix":"","firstName":"Shiyi","middleName":"","lastName":"Luo","suffix":""},{"id":319682490,"identity":"30044f94-fde7-4097-9683-de6b8d881682","order_by":2,"name":"Jiangling Sun","email":"","orcid":"","institution":"Guiyang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiangling","middleName":"","lastName":"Sun","suffix":""},{"id":319682491,"identity":"5a476ad9-1323-43b4-a2e4-650afc592a2e","order_by":3,"name":"Fuqian Jin","email":"","orcid":"","institution":"Guiyang Stomatological Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fuqian","middleName":"","lastName":"Jin","suffix":""},{"id":319682492,"identity":"e94c7fbb-1996-49af-a222-3082b0971de3","order_by":4,"name":"Jukun Song","email":"","orcid":"","institution":"The Affiliated Stomatological Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jukun","middleName":"","lastName":"Song","suffix":""},{"id":319682493,"identity":"a9dbbda6-c1d7-4ffc-8584-fa9c689ca215","order_by":5,"name":"Zhu Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYDACCQYGZiAlB+GxkaDFmHQtiQ1Ea5Gf3WP4uaDiTvp8/zMGDB/KDjPwz27Ar4Vxzhlj6RlnnuVuPHDGgHHGucMMEncO4NfCLJFjxszbdjh3Y2OPAYjBYCCRgF8LG1jLv8Pphs08Bsx/idHCA9bScDhBng2ohZEYLRISacXSPMcOG27gYSs42HMunUfiBgEt8jOSN37mqTksL99/eOODH2XWcvwzCGiBA4MDDAwHQC4lUj3Iugbi1Y6CUTAKRsEIAwDKyzyIsnU6rgAAAABJRU5ErkJggg==","orcid":"","institution":"Guiyang Stomatological Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhu","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-06-11 08:17:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4562396/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4562396/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-73998-1","type":"published","date":"2024-10-08T15:56:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60187832,"identity":"a72852a8-7686-490f-8e91-3f97cc38153f","added_by":"auto","created_at":"2024-07-12 19:12:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49264,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the participants selection from NHANES 2009–2014\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4562396/v1/16ffb5f272955349174137b9.png"},{"id":60187833,"identity":"d00388f1-ed04-40ec-bdaf-85babd9d79f6","added_by":"auto","created_at":"2024-07-12 19:12:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28316,"visible":true,"origin":"","legend":"\u003cp\u003eCDC-AAP periodontitis case definitions\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4562396/v1/eaeeb0054001c6d1c6e52492.png"},{"id":60188919,"identity":"ed69c7e0-3e76-46d3-bd27-a0013fb2b4ff","added_by":"auto","created_at":"2024-07-12 19:20:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35642,"visible":true,"origin":"","legend":"\u003cp\u003eDose-response relationship between ABSI Z-score and periodontitis\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4562396/v1/da01119716aefac1947c5a01.png"},{"id":60189242,"identity":"1d50044c-7d60-4d4b-be24-214cf4a01fc6","added_by":"auto","created_at":"2024-07-12 19:28:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":275812,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis for the association between ABSI Z-score and periodontitis in the hypertensive population\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4562396/v1/74b66ede79a130219c35dedc.png"},{"id":66597003,"identity":"6bfe5f67-603d-4d74-9458-557a0d9abdf1","added_by":"auto","created_at":"2024-10-14 16:01:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1020370,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4562396/v1/99c13fa7-8ad2-4886-9e3e-1e73d9c730a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between “A Body Shape Index” (ABSI) with periodontitis in a hypertension population from the NHANES 2009–2014","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePeriodontitis is a prevalent disease that affects more than 40% of adults in the United States, and globally, the severe form of the disease affects 11.2% of the population, making it the sixth most common human disease in the world\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The main risk factors for periodontal disease are poor oral hygiene among others\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. People with periodontal disease experience symptoms such as pain and discomfort in the mouth, and the condition, if not prevented and further worsened, will lead to loss of attachment, resulting in periodontitis\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePeriodontitis and hypertension are among the most common non-communicable chronic diseases in the world\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In addition to common risk factors, a growing body of evidence supports a possible association between the two diseases\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The inflammatory response caused by periodontitis may lead to elevated levels of systemic inflammation, which can affect vascular function and blood pressure regulation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Periodontitis and hypertension share common risk factors, including genetic predisposition, advanced age, and unhealthy lifestyle choices like poor dietary habits and lack of physical activity\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These factors may play an important role in the development of both diseases.\u003c/p\u003e \u003cp\u003eIn recent years, researchers have increasingly used a variety of indicators to assess the accumulation of body fat and its impact on health, including the ABSI (A Body Shape Index). Research has shown a positive correlation between the ABSI and visceral obesity\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, cardiovascular disease risk, and all-cause mortality\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, with the ABSI being a more effective predictor of the potential health effects of obesity\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Specifically, one study analyzing the data found that for every one unit increase in ABSI, there was a 1.13-fold increase in mortality. Individuals with larger ABSI values had a 61% higher mortality rate compared to individuals with smaller ABSI values\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Therefore, simply relying on body weight to predict the health effects of obesity is not enough; we need to focus on the body shape of the individual\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. ABSI, as a measure of roundness and visceral fat accumulation in the human body, focuses on the percentage of waist circumference in the roundness index, and is therefore scientifically important in assessing the health effects of obesity\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOral health has been reported to be closely related to general health, including cardiovascular health such as hypertension\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In previous studies, the ABSI has been used primarily to assess cardiovascular disease and found a strong association between them\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, no one has used the ABSI to assess periodontitis. Therefore, in this study, we explored the relationship between ABSI Z score and periodontitis in a hypertensive population to fill this information gap.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe study used data from the National Health and Nutrition Examination Survey (NHANES), approved by the Research Ethics Review Board of the National Center for Health Statistics. All methods were conducted in accordance with relevant guidelines, and all participants provided written permission at recruitment\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e( NHANES - NCHS Research Ethics Review Board Approval (cdc.gov) ). The initial analysis of the study involved periodontitis data from 30,468 participants from 2009 to 2014. Inclusion criteria for the study included participants being 30 years of age and older and taking anti-hypertensive medications; NHANES participants received waist circumference, BMI, and height measurements; and participants received a periodontal exam during the oral health screening portion of the program. Exclusion criteria included participants who did not receive a complete periodontal exam or who received an exam but were not taking hypertension medication; very few participants were missing covariates such as education, marriage, hypertension, and sleep disorders. Ultimately, after screening, the study yielded a sample of 2,483 eligible individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eClassification of periodontitis\u003c/h2\u003e \u003cp\u003eAccording to the NHANES guidelines, only subjects 30 years of age and older underwent a full-mouth periodontal examination in which the loss of attachment and pocket depth around each tooth was measured\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Based on criteria provided by the CDC/AAP Case Definitions (Centers for Disease Control and Prevention/American Academy of Periodontology), we categorized periodontal status as mild, moderate, severe periodontitis, and no periodontitis. The detailed method of grading periodontitis is shown in Fig.\u0026nbsp;2 \u003csup\u003e19\u003c/sup\u003e. Absence of periodontitis and mild inflammation were defined as having no periodontitis, whereas moderate and severe inflammation were defined as having periodontitis\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003echaracteristics of the study participants grouped by periodontitis status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-/mild periodontitis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate/severe periodontitis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;2,482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABSI Z-score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (inches)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/㎡)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104.8\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1191 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e382 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e809 (55.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1291 (52.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e635 (62.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e656 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e616 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e442 (30.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e598 (24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219 (21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e379 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1265 (51.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e623 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e642 (43.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1405 (56.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e596 (58.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e809 (55.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e378 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e216 (14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e353 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e346 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1098 (44.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e528 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e570 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e706 (28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e241 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e465 (31.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race-Including Multi-Racial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual alcohol consumption (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least 12 alcohol drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1639 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e666 (67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e973 (69.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 12 alcohol drinks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e758 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323 (32.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e435 (30.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue/a week (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1294 (54.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e784 (56.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286 (29.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e375 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e431 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e241 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of flossing/a week (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e789 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e229 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e560 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e193 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e395 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191 (13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e937 (38.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e436 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e501 (34.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep disorder (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e836 (33.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e476 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1646 (66.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e657 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e989 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral health condition (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcellent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e556 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e292 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e999 (41.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e407 (41.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e592 (41.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e580 (24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e367 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes history (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e653 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e428 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1692 (68.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e731 (71.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e961 (65.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot recorded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eContinuous variables: mean +/- SD, P value from linear regression\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCategorical variables: percentage, P value from Chi-square tests\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eDefinition of A Body Shape Index (ABSI)\u003c/h2\u003e \u003cp\u003eThe Body Shape Index (ABSI) is an index used to assess the relationship between body shape and health risk, and was proposed by researchers at the City University of New York in 2012. ABSI normalizes waist circumference (WC) to body size by considering both weight and height, similar to how body mass index (BMI) normalizes weight in relation to height. ABSI is statistically independent of BMI, while the variability in non-normalized WC is largely explained by BMI\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. We defined ABSI as derived from the NHANES reference population\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$BMI= W\\times {H}^{-2},$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$ABSI= WC/({\\text{B}\\text{M}\\text{I}}^{(2/3)} \\times {\\text{H}}^{(1/2)} ),$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere W refers to the weight, H refers to the height, and WC stands for waist circumference.\u003c/p\u003e \u003cp\u003eWe converted the ABSI into ABSI Z score based on the scores and categorized them into low, moderate, and high groups: low (ABSI Z score \u0026lt; -0.272), moderate (-0.272\u0026thinsp;\u0026le;\u0026thinsp;ABSI Z score\u0026thinsp;\u0026lt;\u0026thinsp;0.229), and high (ABSI Z score\u0026thinsp;\u0026ge;\u0026thinsp;0.229)\u003csup\u003e23\u003c/sup\u003e, thus following the general formula:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$Z-score= \\frac{value - mean}{std. dev. }.$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eWe combined 10 confounding factors that may influence the relationship between periodontitis and hypertension, including gender, age, race, education, marital status, annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. A detailed description of the covariates can be found on the NHANES website.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe integrated and statistically analyzed the data using the EmpowerStats (version 4.2; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.empowerstats.net/cn/\u003c/span\u003e\u003cspan address=\"https://www.empowerstats.net/cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) and R software (version 4.3.2; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ) packages. Categorical variables were expressed as percentages and continuous variables as standard deviations. We developed a multivariate logistic regression model to investigate the independent relationship between ABSI Z score and moderate/severe periodontitis in a hypertensive population. The strength of the relationship was determined by calculating the odds ratio (OR) with 95% confidence intervals, and ABSI Z score was categorized into three classes, with the lower class serving as the reference. We developed three models: model I was not adjusted for covariates; model II was adjusted for gender, age, marital status, education level and race; and model III added other covariates to model II, such as annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition. We also applied a smoothed curve transformation to explore the possible nonlinear relationship between ABSI Z score and periodontitis. In this study, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGeneral characteristics of the study population\u003c/h2\u003e \u003cp\u003eA total of 2842 patients were included after applying appropriate exclusion criteria. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the process of screening participants. Covariates were dichotomously distributed according to no/mild or moderate/severe periodontitis. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the baseline characteristics of patients with and without periodontitis in the hypertensive population. Overall, there were significant differences between the no/mild periodontitis and moderate/severe periodontitis groups in terms of ABSI, ABSI Z-score, height, BMI, age, gender, race, marital status, education, number of flossing sessions, general health, and history of diabetes mellitus (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While there was no significant difference between waist circumference, Annual alcohol consumption, days of fatigue in a week, and sleep disorders (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLogistic regression analysis\u003c/h2\u003e \u003cp\u003eThe relationship between ABSI Z-score and periodontitis in the hypertensive population is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which is the result of multivariate logistic regression analysis. In the original model, ABSI Z-score was significantly and positively correlated with periodontitis, with a ratio of 1.2 (95CI: 1.1,1.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The robust and favorable association in Model 2 remained highly significant (OR\u0026thinsp;=\u0026thinsp;1.1; 95%CI: 1.0,1.2; p\u0026thinsp;=\u0026thinsp;0.006) after accounting for factors such as gender, age, and race. Then in Model 3, which was built on the basis of Model 2, after adjusting for all variables, the correlation between ABSI and periodontitis remained statistically significant (OR\u0026thinsp;=\u0026thinsp;1.1; 95%CI: 1.0,1.2; P\u0026thinsp;=\u0026thinsp;0.015). After converting ABSI Z score from continuous to categorical variables, we observed a striking result. In all three models, the association between the high ABSI Z score group and periodontitis showed a statistically significant association. Participants in the highest group had a significant 20% increased risk of periodontitis compared to those in the low ABSI Z score group (OR\u0026thinsp;=\u0026thinsp;1.2; 95% CI, 1.0-1.5, p\u0026thinsp;=\u0026thinsp;0.046). This study found that increased ABSI Z-score were positively associated with the risk of developing periodontitis in hypertensive population and we confirmed the results using smoothed curve fitting as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and found that the standard linear regression of the results was still supported.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of periodontitis with ABSI Z-score in the hypertensive population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003cp\u003eOR (95% CI) p\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted Model I\u003c/p\u003e \u003cp\u003eOR (95% CI) p\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted Model II\u003c/p\u003e \u003cp\u003eOR (95% CI) p\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABSI Z-score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.2(1.1,1.3)\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1(1.0,1.2)0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1(1.0,1.2)0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABSI Z-score (groups)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3(1.1,1.6)0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2(0.9,1.5)0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2(0.9,1.5)0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.4(1.2,1.7)\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2(1.0,1.5)0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2(1.0,1.5)0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel 1: no adjustment for covariates.\u003c/p\u003e \u003cp\u003eModel 2: adjusted for sex, age, marital status, education level and race.\u003c/p\u003e \u003cp\u003eModel 3: adjusted for sex, age, marital status, education level, race, annual alcohol consumption, general health condition, number of flossing/a week, fatigue/a week, general health condition.\u003c/p\u003e \u003cp\u003eABSI Z-score (groups): low (ABSI Z score \u0026lt; -0.272), moderate (-0.272\u0026thinsp;\u0026le;\u0026thinsp;ABSI Z score\u0026thinsp;\u0026lt;\u0026thinsp;0.229), and high (ABSI Z score\u0026thinsp;\u0026ge;\u0026thinsp;0.229).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eTo evaluate the stability of the relationship between ABSI score and periodontitis in hypertensive populations, as well as to identify potential differences between the two in different populations, subgroup analyses were conducted. The results of these analyses are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Except for men who were widowed or divorced, rarely floss, moderately floss, and in excellent health condition, ABSI Z score was significantly positively associated with periodontitis in hypertensives. Furthermore, we observed that the 'interaction P-value' was greater than 0.05, suggesting that the positive correlation between the ABSI Z score and periodontitis in the hypertensive population is typically stable and consistent across the general population.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study, we found for the first time an association between ABSI Z score and periodontitis in a hypertensive population. After studying 2,482 participants, it was found that periodontitis was positively associated with ABSI. Specifically, we observed a corresponding increase in the risk of developing periodontitis as ABSI Z score increased, and this association held true after accounting for confounding variables. In addition, our study revealed that the association between ABSI Z score and periodontitis in the hypertensive population was independent of a variety of other factors, including age, gender, race, marital status, education, frequency of flossing and general health. These findings emphasize the potential importance of ABSI value in the pathogenesis of periodontitis and provide useful clues for further research and intervention.\u003c/p\u003e \u003cp\u003eIn the past, the medical community used to widely use the body mass index, BMI, to measure the degree of obesity\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. BMI is calculated as the weight divided by the square of the height, and the normal range of this index is from 18.5 to 24, and if it is more than 24, it is overweight, and if it is more than 28, it is obese\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In addition, the waist circumference indicator is used to measure central obesity\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, men with a waist circumference of more than 90 centimeters and women with a waist circumference of more than 85 centimeters are abdominal obese\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. It is not difficult to see that BMI, as well as WC, are relatively rough standards\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Therefore, scholars have been looking for more reliable, and easy-to-use indicators. In recent years, the indicators used to measure the accumulation of visceral fat and its impact have become increasingly recognized\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Among them, the widely acknowledged indicator is the Body Shape Index (ABSI)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. ABSI was proposed by scholars from the City College of New York in 2012\u003csup\u003e22\u003c/sup\u003e. ABSI has been suggested as an alternative parameter to reflect differences in body shape. Studies have indicated a positive correlation between ABSI and visceral fat, cardiovascular disease risk\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, and all-cause mortality\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Many scholars have analyzed studies on large sample sizes in the US population, such as Aoki et al who found that ABSI could predict the risk of CVD manifestations more significantly than BMI\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This was also confirmed in a study by Wu et al\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, who observed that anthropometric indicators including BMI, ABSI, etc. were strongly associated with hypertension risk, and that these new anthropometric indicators should be emphasized for better prevention and treatment of hypertension. Furthermore, a cross-sectional study by Lin et al\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e found that the score of ABSI was linearly correlated with the risk of kidney stone prevalence, which can be used as an important indicator for assessing the risk of kidney stones. Kuang M et al\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e found that ABSI may help define the risk of sarcopenia in overweight/obese individuals. In addition, some scholars have found that the ABSI combined with BMI best identifies the risk of obesity-related non-alcoholic fatty liver disease (NAFLD) and is significantly better than BMI or WC or ABSI\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Therefore, ABSI should be more closely monitored and preventive medical management than BMI. It is well known that hypertension is one of the major risk factors for cardiovascular disease\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, so this study was chosen to be conducted in a hypertensive population; however, no one has yet conducted an in-depth study of the relationship between the ABSI Z score and periodontitis in a hypertensive population, so there is no reason why the relationship between the ABSI Z score and periodontitis should not be explored. If feasible, the ABSI Z score could also be used as an indicator to assess oral health, especially periodontal health. Where possible, every effort has been made to explain how they are linked. The possible reasons are summarized below.\u003c/p\u003e \u003cp\u003eRelevant studies have confirmed that central obesity, with excessive accumulation of visceral adipose tissue, leads to vascular inflammation\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, and the body's immune system is activated, leading to the release of inflammatory mediators and the onset of an inflammatory response\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. These inflammatory mediators can circulate through the bloodstream to all parts of the body, including the periodontal tissues in the mouth\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. In periodontal tissues, the release of inflammatory mediators causes vasodilatation, increased permeability, and infiltration of inflammatory cells, leading to an inflammatory response and damage to localized tissues\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The inflammatory response caused by vascular inflammation in the periodontal tissues may lead to symptoms such as gingival redness, swelling, bleeding, gingival pocket formation, and periodontal bone resorption, which eventually develops into periodontitis\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIt is concluded that by analyzing the data, we found a significant positive correlation between ABSI Z score and prevalence of periodontitis in hypertensive population. The results suggest that ABSI Z score is a valid predictor of a wide range of diseases and their inflammation, such as periodontitis. More studies on the causal and longitudinal relationships between ABSI Z score and risk of periodontitis are necessary.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI, body mass index;\u003c/p\u003e\n\u003cp\u003eWC, waist circumference;\u003c/p\u003e\n\u003cp\u003eABSI, Body Shape\u0026nbsp;Index;\u003c/p\u003e\n\u003cp\u003eNHANES, National Health and Nutrition Examination Survey;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI, confidence interval;\u003c/p\u003e\n\u003cp\u003eOR, odds ratio;\u003c/p\u003e\n\u003cp\u003eSD, standard deviation;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAL, Attached Level;\u003c/p\u003e\n\u003cp\u003eCDC-AAP, the Centers for Disease Control and Prevention and the American Academy of\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePeriodontology;\u003c/p\u003e\n\u003cp\u003eNAFLD, non-alcoholic fatty liver disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe want to thank the NHANES databases for making this data available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eXuanyan Gu was responsible for study design, data collection, data merging, and data analysis, as well as drafting the manuscript. Shiyi Luo provided expertise in data interpretation. Fuqian Jin assisted in data merging. Jukun Song, Zhu Chen, and Jiangling Sun contributed to the review and editing process. All authors have reviewed and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by supported by the Guiyang Science and Technology Support Program (2022-4-12-4).\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The complete dataset is accessible through the NHANES database, which can be located at the following link: https://www.cdc.gov/nchs/nhanes/index.htm.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate: The NHANES repository is both representative and openly available at no cost. Approval for the study\u0026apos;s methodology was granted by the Research Ethics Review Board of the National Center for Health Statistics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKwon, T., Lamster, I. B. \u0026amp; Levin, L. Current Concepts in the Management of Periodontitis. 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Periodontology 2000 64, 57\u0026ndash;80, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/prd.12002\u003c/span\u003e\u003cspan address=\"10.1111/prd.12002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapadopoulos, G. \u003cem\u003eet al.\u003c/em\u003e Macrophage-specific TLR2 signaling mediates pathogen-induced TNF-dependent inflammatory oral bone loss. \u003cem\u003eJournal of immunology (Baltimore, Md.\u003c/em\u003e: 1950) 190, 1148\u0026ndash;1157, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4049/jimmunol.1202511\u003c/span\u003e\u003cspan address=\"10.4049/jimmunol.1202511\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"A Body Shape Index, ABSI Z score, Periodontitis, NHANES, Cross-sectional study","lastPublishedDoi":"10.21203/rs.3.rs-4562396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4562396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eA body Shape index (ABSI), defined as waist circumference (WC)/ (body mass index (BMI) \u003csup\u003e2/3\u003c/sup\u003e \u0026times; height \u003csup\u003e1/2\u003c/sup\u003e), is unique in that the ABSI is positively associated with visceral obesity and is independent of BMI. The ABSI has also been shown to be positively and linearly correlated with the amount of visceral adiposity in the general population and with all-cause and cardiovascular disease (CVD). However, it is uncertain whether ABSI is associated with periodontitis in hypertensive patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study of 2,482 hypertensive patients (mean age 65.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1 years) was conducted using the ABSI Z score, periodontitis as a dichotomous variable, the ABSI Z score as a continuous variable, and multiple covariates such as age, gender, and race. The data were analyzed using descriptive statistics, multiple logistic regression, subgroup analysis with EmpowerStats (version 4.2), and curve transformation plots were generated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn multivariate logistic regression analysis, ABSI Z score showed a significant positive association with periodontitis in the hypertensive population in all three models. When ABSI Z score was divided into low, medium, and high three groups, we observed that those with the highest ABSI Z score had a 20% increased risk of periodontitis among people with hypertension (OR\u0026thinsp;=\u0026thinsp;1.2; 95%CI, 1.0-1.5, P\u0026thinsp;=\u0026thinsp;0.046). We used smooth curve fitting to confirm the results and found that these results were still supported, and additional subgroup analyses showed that the positive association between ABSI Z score and periodontitis in hypertensive population was stable and consistent in the general population.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe present cross-sectional investigation showed a positive association between ABSI Z score and periodontitis in a hypertensive population.\u003c/p\u003e","manuscriptTitle":"Association between “A Body Shape Index” (ABSI) with periodontitis in a hypertension population from the NHANES 2009–2014","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-12 19:12:55","doi":"10.21203/rs.3.rs-4562396/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-05T06:39:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-14T17:28:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-04T17:45:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305080587345662970017256732911465306323","date":"2024-07-04T16:54:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217833898972114258862572387469605526162","date":"2024-07-04T10:31:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-04T10:07:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-26T18:02:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-13T07:45:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-12T10:46:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-11T08:15:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cb33ba94-6168-4020-92aa-efd0781ca807","owner":[],"postedDate":"July 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33799748,"name":"Health sciences/Diseases"},{"id":33799749,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-14T15:58:20+00:00","versionOfRecord":{"articleIdentity":"rs-4562396","link":"https://doi.org/10.1038/s41598-024-73998-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-08 15:56:50","publishedOnDateReadable":"October 8th, 2024"},"versionCreatedAt":"2024-07-12 19:12:55","video":"","vorDoi":"10.1038/s41598-024-73998-1","vorDoiUrl":"https://doi.org/10.1038/s41598-024-73998-1","workflowStages":[]},"version":"v1","identity":"rs-4562396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4562396","identity":"rs-4562396","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}