Income-related inequalities affect the association between obesity and periodontal disease: A cross-sectional analysis in Tokyo Metropolitan Districts

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However, it remains unclear whether SES modifies the relationship between obesity and periodontal disease. This study aimed to investigate the influence of SES on the association between obesity and periodontal disease. Material and Methods We used multilevel Poisson regression, adjusted for SES, to analyze the body mass index (BMI) and periodontal parameters of 962 participants (mean age 58.3 years; SD: 13.8). SES was assessed based on the average income and education levels of their residential areas. Results A significant association was observed between obesity and the proportion of teeth with probing pocket depth (PPD) ≥ 4 mm (ratio of means [RM]: 1.25, 95% confidence interval [CI]: 1.15, 1.38, p < 0.001), whereas the higher-income group exhibited a significantly lower proportion of teeth with PPD ≥ 4 mm (RM: 0.86, 95% CI: 0.77, 0.96, p = 0.007). Interaction analysis also revealed a significant interaction between obesity and the high-income group regarding the proportion of teeth with PPD ≥ 4 mm. The subgroup analysis demonstrated that the RM of obesity for the proportion of teeth with PPD ≥ 4 mm was higher in females than in males. Conclusions Income-related inequalities affect the association between obesity and periodontal disease. Among obese adults, those with low-to-middle-income levels may have a higher risk of periodontal disease than those with high-incomes. Clinical Relevance Comprehensive care and oral health education should be enhanced for obese individuals in low-income populations to mitigate their elevated risk of periodontal disease. socioeconomic status obesity periodontal disease health inequality body mass index income level Figures Figure 1 Introduction Obesity is a precursor to various non-communicable diseases, such as type 2 diabetes, [1] dyslipidemia,[ 2 ] hypertension,[ 3 ] cardiovascular diseases,[ 4 ] respiratory diseases,[ 5 ] and nonalcoholic fatty liver disease.[ 6 ] Numerous studies have investigated the association between periodontal disease and obesity.[ 7 – 10 ] A recent umbrella review[ 11 ] encompassing the existing evidence demonstrated a positive association between these two. Few longitudinal cohort studies support these findings,[ 12 , 13 ] although there is suggestive evidence of racial differences in the association between obesity and periodontitis, with reports indicating a stronger impact of obesity on periodontitis among Europeans and Japanese than among Americans or other Asian population.[ 14 ] However, some research suggests that there is insufficient evidence to support a causal relationship between periodontal disease and obesity.[ 15 ] Socioeconomic status (SES) is strongly associated with health behaviors such as dietary habits, smoking, and physical activity, and is known to influence various health-related factors, including obesity.[ 16 ] Furthermore, it is associated with the prevalence and severity of oral diseases[ 17 ] and has been suggested to contribute to health inequalities. At the 74th World Health Assembly, 2022, the World Health Organization set a goal of reducing health inequalities in oral diseases, conditions, and health.[ 18 ] Thus, we hypothesized that not only SES and obesity independently impact oral health, but the effect of obesity on oral health may also vary according to SES. Multiple inflammatory pathways are assumed to mediate the mechanisms linking the two. Stress is known to elevate inflammatory biomarkers.[ 19 ] Social pressure related to body image, including physical appearance associated with obesity, can contribute to stress. Additionally, low SES is considered to exacerbate everyday stress. Accordingly, individuals with obesity and low SES may have a heightened risk of worsening periodontal disease. However, no previous studies have investigated the effect of SES on the relationship between periodontal disease and obesity. Therefore, in this study, we aimed to examine the influence of SES on the association between obesity and periodontal disease in the Japanese population. Material and methods Study design and participants In this cross-sectional study, we extracted data for analysis from a comprehensive database that records information on all patients who visit the periodontal clinic of the Dental Hospital of Tokyo Medical and Dental University (TMDU), located in the center of the Tokyo Metropolitan District, for their first consultation. Therefore, prior power analysis was not performed for sample size calculation. Informed consent was obtained from all participants. The study design was approved by the Dental Research Ethics Committee of TMDU (approval number: 1085). The study was conducted following the Declaration of Helsinki of 1975, as revised in 2013, and was registered with the University Hospital Medical Information Network ( http://www.umin.ac.jp ) (clinical trial number: UMIN000046582). The research was also conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. The data of participants meeting the following inclusion criteria were used for the analysis. Inclusion criteria 1. Individuals who visited the periodontal clinic of the Dental Hospital of TMDU for their first consultation between October 2014 and February 2016. 2. Only residents of the Tokyo Metropolitan District, which has a radius of approximately 15 km from the hospital, were considered for inclusion to prevent accessibility bias due to distance from the hospital. 3. Participants aged 18 years or older. Exclusion criteria 1. Participants with missing values of either the independent or dependent variables. 2. Participants requiring a proxy for medical interviews or informed consent. Clinical examination Information on participants’ medical and social backgrounds was collected through medical interviews and health insurance records. Experienced periodontists conducted the dental examinations, which involved recording the number of remaining teeth, probing pocket depth (PPD), and bleeding on probing (BOP). A manual probe (15 UNC Color-Coded Probe, Hu-Friedy, USA) was used for examination. The PPD and BOP were evaluated at six points on each tooth, recording the deepest PPD and presence or absence of BOP for each tooth. The independent variable was the proportion of teeth with PPD ≥ 4 mm in relation to the total number of remaining teeth. Medical histories (e.g., diabetes, smoking habits, and prior periodontal therapy) were collected through medical interviews. Body mass index (BMI) was grouped into three categories: underweight (< 18.5), normal (18.5 to 25), and obese (≥ 25). Smoking status was classified as follows: never smoked, former smoker, or current smoker. Individuals who reported scaling and root planing, or those who were referred by their primary dentists, were identified as having a history of periodontal therapy. Information on place of residence and type of health insurance was obtained from participants’ registration data in their hospital records. Income and educational attainment were used to determine SES. Based on a previous study,[ 20 ] we used the average income within each participant’s residential ward as the income of individuals, as individual income data were not available. We calculated the average household income of the residents of the 23 wards of Tokyo as (taxable income)/(number of taxpayers) using data obtained from a survey conducted in 2019 by the Japanese Ministry of Internal Affairs and Communications ( https://www.soumu.go.jp/main_sosiki/jichi_zeisei/czaisei/czaisei_seido/ichiran09_19.html ). Income was categorized into the highest tertile and other categories and expressed in units of 1000 yen; 1000 yen was converted to 6.6 US dollars according to the exchange rate as of January 2024. Education level, as categorized into two groups—highest tertile and others, was based on the percentage of residents with university or higher education in each ward (≥ 16 years of formal education). We used the levels attributed to the participants’ residential wards as determined by a 2010 survey conducted by the Japanese Ministry of Internal Affairs and Communications (e-stat, https://www.e-stat.go.jp/ , in Japanese), given that individual education levels were not available. Statistical analysis Descriptive statistics were presented, indicating the mean (standard deviation [SD]) for continuous variables and the number (%) for categorical variables. The calculation of the proportions of teeth with PPD exceeding 4 mm relative to the total remaining teeth was conducted as follows: (number of teeth with PPD ≥ 4 mm) / (total number of teeth) × 100 (%). A comparison among the three BMI-based groups was performed using a one-way analysis of variance or Fisher’s exact test. Multilevel Poisson regression analyses were employed to determine the ratio of means (RM)[ 21 ] for the proportion of teeth with PPD exceeding 4 mm in relation to the total number of remaining teeth, given a skewed distribution.[ 21 ] The data were structured into multilevel models to account for participants nested in their ward of residence. In the multivariate analysis, explanatory variables included age, sex, diabetes, BMI, income, education level, smoking status, and history of periodontal therapy. To explore the interaction between BMI and income with respect to the proportions of teeth with PPD exceeding 4 mm, we conducted multivariate analyses with interaction terms, and margin plots were generated to model the interaction between BMI and income for the proportion of teeth with PPD ≥ 4 mm. The goodness of fit for the models was evaluated using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Statistical analyses were conducted using Stata software (version 17.0; Stata Corp LP, College Station, Texas, USA), with statistical significance set at p < 0.05. Results Of the 3310 individuals who visited the periodontal clinic of the Dental Hospital of Tokyo Medical and Dental University for their first consultation between October 2014 and February 2016, 1639 were included in the study; 1671 residing outside the Tokyo Metropolitan District were excluded. Subsequently, of the 1639, 677 individuals were excluded due to insufficient data, resulting in the inclusion of data from 962 participants for the analysis. Table 1 presents the demographic data, revealing that the mean age of the 962 participants (302 males and 660 females) was 58.3 years ( SD : 13.8). The mean BMI for the underweight, normal weight, and obese groups were 17.3 ( SD : 1.1), 21.7 ( SD : 1.8), and 27.7 ( SD : 2.5) kg/m 2 , respectively. The mean income for the high-, middle-, and low-income groups were 8061.6 ( SD : 2331.4), 4747.2 ( SD : 521.9), and 3665.6 ( SD : 128.3) thousand yen, respectively. The mean number of remaining teeth was 24.6 ( SD : 4.8), with mean proportions of teeth having PPD ≥ 4 mm at 30.8% ( SD : 28.3%). The mean proportion of teeth with BOP was 51.3% ( SD : 31.3%). Significant differences were observed among three BMI-based groups in terms of sex, BMI, diabetes, teeth with PPD ≥ 4 mm, and BOP positive teeth. Table 1 Characteristics of participants (N = 962) Characteristics All ( n = 962) BMI p -value* Underweight ( n = 127) Normal ( n = 651) Obesity ( n = 184) n (%) or mean (SD) n (%) or mean (SD) n (%) or mean (SD) n (%) or mean (SD) Age (in years) 58.3 (13.8) 58.1 (13.8) 59.0 (14.7) 58.3 (14.0) 0.81 Sex Female 660 (68.6%) 115 (90.6%) 444 (68.2%) 101 (54.9%) < 0.001 Male 302 (31.4%) 12 (9.5%) 207 (31.8%) 83 (45.1%) BMI (kg/m 2 ) 22.3 (3.6) 17.3 (1.1) 21.7 (1.8) 27.7 (2.5) < 0.001 Diabetes Yes 73 (7.6%) 3 (2.4%) 43 (6.6%) 27 (14.8%) < 0.001 Income level, mean yearly income in thousand yen / USD Highest, 8061.6 (SD: 2331.4) / 53,206.6 (SD: 15387.2) 179 (18.6%) 25 (19.7%) 120 (18.4%) 34 (18.5%) 0.55 Middle, 4747.2 (SD: 521.9) / 31,331.5 (SD: 3,444.5) 476 (49.5%) 69 (54.3%) 313 (48.1%) 94 (51.1%) Lowest, 3665.6 (SD: 128.3) / 2,419.6 (SD:846.8) 307 (31.9%) 33 (26.0%) 218 (33.5%) 56 (30.4%) Education level Highest 309 (32.1%) 48 (37.8%) 209 (32.1%) 52 (28.3%) 0.11 Middle 320 (33.3%) 43 (33.9%) 204 (31.3%) 73 (39.7%) Lowest 333 (34.6%) 36 (28.4%) 238 (36.6%) 59 (32.1%) Smoking Never 598 (62.3%) 83 (65.4%) 416 (63.9%) 99 (53.8%) 0.11 Former smoker 265 (27.6%) 30 (23.6%) 171 (26.3%) 64 (34.8%) Current smoker 99 (10.3%) 14 (11.0%) 64 (9.8%) 21 (11.4%) Dental health status Number of teeth 24.6 (4.8) 24.6 (4.5) 24.7 (4.8) 24.5 (5.1) 0.86 Teeth with PPD ≥ 4 mm (%) 30.8 (28.3) 24.4 (26.1) 29.8 (27.5) 39.0 (30.5) < 0.001 Teeth with BOP positive (%) 51.3 (31.3) 46.9 (30.1) 50.1 (31.3) 56.8 (31.6) 0.017 History of periodontal therapy Yes 361 (37.5%) 43 (33.9%) 258 (39.6%) 60 (32.6%) 0.15 A multivariate Poisson regression analysis showed that age, sex, BMI, income, smoking, and history of periodontal therapy were associated with the proportion of teeth with PPD ≥ 4 mm (Table 2 , multivariate models 1 and 2). Participants with obesity exhibited a significantly higher ratio of teeth with PPD ≥ 4 mm compared to those with normal BMI (RM: 1.25, 95% confidence interval [CI]: 1.14, 1.38, p < 0.001, Table 2 , multivariate model 2). The high-income group had a significantly lower ratio of teeth with PPDs ≥ 4 mm (RM: 0.86, 95% CI: 0.77, 0.96, p = 0.007, Table 2 , multivariate model 2) compared to the low-to-middle income group. Education level was not significantly associated with the proportion of teeth with PPD ≥ 4 mm. Smoking was significantly associated with the ratio of teeth with PPD ≥ 4 mm. Former and current smokers showed significantly higher RMs of 1.36 and 1.42 (95% CI: 1.18, 1.57 and 1.22, 1.66, p < 0.001 and p < 0.001: Table 2 , multivariate model 2), respectively, compared to those who never smoked for the proportion of teeth with PPDs ≥ 4 mm. Additionally, an examination of the interaction between BMI and income with the proportion of teeth having PPD ≥ 4 mm revealed significant interactions in the obesity and high-income group towards the ratio of teeth with PPD ≥ 4 mm (Table 2 , multivariate model 3, p = 0.033). Table 2 Multilevel Poisson regression analysis of the factors influencing the proportion of teeth with PPD ≥ 4 mm Crude model Multivariate model* Model 1 Model 2 Model 3 RM 95% CI p -value RM 95% CI p -value RM 95% CI p -value RM 95% CI p -value Age 1.00 1.00, 1.01 0.013 1.01 1.00, 1.01 0.004 1.01 1.00, 1.01 0.006 1.01 1.00, 1.01 0.004 Sex, Male 1.33 1.15, 1.54 < 0.001 1.20 1.06, 1.35 0.003 1.13 1.01, 1.27 0.036 1.13 1.01, 1.27 0.030 Diabetes 1.21 1.03, 1.42 0.019 1.09 0.96, 1.25 0.20 1.05 0.89, 1.22 0.56 1.05 0.89, 1.23 0.56 BMI < 18.5: underweight 0.83 0.69, 1.00 0.048 0.86 0.70, 1.05 0.13 0.88 0.70, 1.10 0.27 18.5–25: normal Reference Reference Reference ≥ 25: obesity 1.30 1.17, 1.44 < 0.001 1.25 1.14, 1.38 < 0.001 1.32 1.19, 1.45 < 0.001 Income Lowest to middle Reference Reference Reference Reference Highest 0.87 0.74, 1.03 0.11 0.88 0.79, 0.98 0.021 0.86 0.77, 0.96 0.007 0.94 0.81, 1.09 0.41 Education level Lowest to middle Reference Reference Reference Reference Highest 0.87 0.72, 1.04 0.13 0.95 0.82, 1.10 0.50 0.99 0.85, 1.16 0.92 0.99 0.85, 1.16 0.92 Smoking Never Reference Reference Reference Reference Former 1.44 1.23, 1.69 < 0.001 1.30 1.13, 1.59 < 0.001 1.36 1.18, 1.57 < 0.001 1.36 1.20, 1.57 < 0.001 Current 1.47 1.26, 1.72 < 0.001 1.40 1.20, 1.64 < 0.001 1.42 1.22, 1.66 < 0.001 1.43 1.23, 1.67 < 0.001 History of periodontal therapy 1.19 1.03, 1.37 0.018 1.20 1.05, 1.36 0.007 1.20 1.05, 1.37 0.008 1.21 1.06, 1.38 0.006 BMI x Income Underweight x Highest income 0.87 0.62, 0.22 0.41 Obesity x Highest income 0.74 0.56, 0.98 0.033 RM, ratio of means; CI, confidence interval; BMI: Body Mass Index; PPD: probing pocket depth. * Adjusted for all covariates listed Proportions of teeth with PPD ≥ 4 mm were estimated from the models with adjustments for covariates (Fig. 1 ). Among participants in the high-income group, the prevalence of teeth with PPD ≥ 4 mm did not differ based on BMI. However, in the low-to-middle-income group, it was observed that participants with obesity had a significantly higher proportion of teeth with PPD ≥ 4 mm. The multivariate model 3, which included the interaction terms, demonstrated the best fit according to AIC and BIC (Supplementary Table 1). A subgroup analysis was conducted to explore sex differences in the association between obesity and periodontal disease. Although the interaction between obesity and sex towards the proportion of teeth with PPD ≥ 4 mm was not significant, the RM of obesity for the proportion of teeth with PPD ≥ 4 mm showed a trend towards a higher RM of 1.33 (95% CI: 1.12, 1.58) in females compared to 1.13 (95% CI: 0.98, 1.29) in males (Table 3 ). Table 3 Adjusted associations between BMI and the proportion of teeth with PPD ≥ 4 mm by sex Male ( n = 302) Female ( n = 660) n (%) RM* (95%CI) p -value n (%) RM* (95%CI) p -value BMI Underweight 12 (4.0%) 0.84 (0.47, 1.52) 0.57 115 (17.4%) 0.89 (0.73, 1.07) 0.22 Normal 207 (68.5%) Reference 444 (67.3%) Reference Obesity 83 (27.5%) 1.13 (0.98, 1.29) 0.084 101 (15.3%) 1.33 (1.12, 1.58) 0.001 *RM adjusted for age, diabetes, income, education level, smoking, and history of periodontal therapy. Discussion To our knowledge, this was the first study to demonstrate the influence of income-related inequalities on the association between obesity and periodontal disease among the Japanese population. By examining the modifying role of SES, our findings contribute to a deeper understanding of how economic factors interplay with obesity to influence oral health. A BMI ≥ 25 and higher income not only independently affect the proportion of teeth with periodontal pockets but also exhibit interaction for it. The association between obesity and periodontal disease appeared to be negligible among individuals with higher incomes, whereas it was significant for those with lower incomes. Furthermore, the association between obesity and periodontal disease tended to be stronger in females than in males after adjusting for possible confounding factors. This study has the potential to contribute to raising awareness about obesity and periodontal disease prevention among low-income individuals and improve public assistance initiatives. Multiple mechanisms have been proposed to explain the association between obesity and periodontal disease.[ 22 ] An imbalance between pro-inflammatory adipokines produced by excess adipose tissue and anti-inflammatory adipokines, leads to a systemic state of mild inflammation.[ 23 , 24 ] This imbalance affects not only systemic health but also periodontal tissue destruction in obese individuals. [25, 26] Additionally, increased production of reactive oxygen species and free fatty acids by adipocytes may exacerbate inflammation and tissue destruction in periodontal tissues.[ 27 , 28 ] In this study, it was observed that the proportion of teeth with PPD ≥ 4 mm increased in the group with BMI ≥ 25, suggesting that the systemic chronic inflammatory state due to obesity may impact the progression of periodontal disease. Despite the limited consideration of body fat distribution and sex differences, BMI remains widely utilized in surveys owing to its simplicity and practicality. In Japan, a BMI ≥ 25 kg/m 2 [29] is classified as obesity, which differs from the Western criteria that identify a person with a BMI ≥ 30 kg/m 2 as obese. Nonetheless, several studies conducted in Japan have suggested a relationship between obesity and periodontal disease.[ 30 – 33 ] In both sexes, the risk of developing periodontal disease within five years is higher in the group with BMI ≥ 25 kg/m 2 compared to the group with BMI < 22 kg/m 2 , with the risk being greater for females than males.[ 34 ] Consistent with previous findings, we also found that a BMI ≥ 25 was associated with a higher risk of periodontal disease among females compared to males. Several studies have proposed possible underlying mechanisms. A study reported that in females, a high body adipose index combined with a low skeletal muscle index was significantly associated with an elevated odds ratio of periodontal disease by utilizing Dual-energy X-ray Absorptiometry, which allows for a more precise measurement of obesity than BMI.[ 35 ] However, it has been observed that females face higher social pressures[ 36 ] regarding their appearance, including body shape, than males. Consequently, females may experience greater stress related to being overweight, a condition that may be implicated in the progression of periodontitis. Evidence suggests that stress significantly impacts periodontitis.[ 37 ] However, the mechanisms underlying sex-related differences in the association between obesity and periodontal disease remain unclear. Interestingly, we found a statistically significant difference in the adverse effects of obesity on the proportion of teeth with periodontal pockets depending on income level. This study is the first to show a significant interaction between obesity, income, and the proportion of teeth with periodontal pockets. The relationship between SES and health is commonly mediated by lifestyle factors such as alcohol consumption, lack of exercise, and stress.[ 38 , 39 ] These factors, such as those not considered in this study, may be reflected in the results. Another hypothesis stated that high-income populations engage in meticulous oral hygiene and regular dental care. Individuals with a high SES generally have high health literacy[ 40 , 41 ]; moreover, high-income participants may be better able to pay for the costs of oral hygiene and dental care. These positive oral health behaviors may compensate for the adverse effects of obesity in those in the high-income group. Furthermore, a prior study noted that physical appearance related to obesity may impact employment, potentially affecting income.[ 42 ] Although the temporal relationship between income and obesity is unclear in this study, individuals with both low income and obesity may experience compounded stress from both factors, which could contribute to the progression of periodontal disease. Another interesting point is that we found inequalities in SES by income but not by education level. A previous study[ 43 ] reported that income had a significantly stronger association with dental implant usage than education. This study suggests that income inequality might be more strongly associated with health inequalities than education. This study had several limitations. First, there are limitations related to data collection. Owing to the inability to obtain individual income and education data, household income and education level were estimated as surrogates from residential areas. This may not accurately reflect the participants’ actual SES. While discrepancies exist between individual and area-level SES, the bias introduced by this method is considered nonsystematic rather than systematic. Therefore, the results of this study may have a wider confidence interval and the observed significant results may still be robust. Another limitation of this method is that the results may be associated with both income and education level disparities as well as other factors, such as the local environment. Further research using individual SES data is, thus, required to validate the results of this study. Moreover, detailed data on smoking habits, such as the duration of smoking and the number of cigarettes consumed per day are missing. While smoking status was categorized as “current smoker,” “former smoker,” and “never smoked,” we acknowledge that this classification does not fully account for the intensity of smoking, which is a key periodontal risk factor. Future studies should thus incorporate more comprehensive smoking data for a more detailed analysis. Another limitation regarding data collection is the inclusion of PPD ≥ 4 mm that may not be associated with active periodontitis, such as inactive pockets following successful periodontal therapy or pockets caused by non-periodontal factors, including root fractures. Given that the mechanism by which obesity influences periodontal disease is linked to inflammation, it is plausible that the interaction between obesity and SES would be more pronounced in active periodontal pockets. If an analysis limited to active periodontal pockets could be performed, stronger associations might be observed. Therefore, the inclusion of inactive pockets in this study likely introduced a bias that underestimated the true strength of the relationship. Nevertheless, the significant interaction between obesity and SES observed in this study suggests that the findings could be robust. Future studies should, thus, refine the classification of periodontal disease activity to account for these variations and further validate the results. Second, we adjusted for diabetes as it is a known confounder affecting both obesity and periodontal disease in this study. However, other systemic diseases that could potentially influence both conditions were not specifically adjusted for. Third, because this was a cross-sectional study, causality could not be determined. Cohort and life course studies should thus investigate the impact of SES more thoroughly in the future. Fourth, a preliminary power analysis was not conducted as this was an observational study using a database. The possibility of underestimation owing to the small sample size is present because of the lack of power analysis; however, the sample size of this study was considered sufficient to demonstrate significant differences. As additional examinations beyond those routinely performed in clinics were not necessary for this study, obtaining a large sample size without ethical concerns improved the generalizability of the study results. Fifth, because the data were collected during routine clinical practice, the pre-study calibration of the examiners was not performed in this study. Although all examiners were experienced periodontists, the lack of calibration could lead to non-differential misclassification, potentially leading to bias widening the confidence intervals. Despite this potential bias, the detection of statistically significant differences suggests that the results of the analysis could be robust. Lastly, a notable limitation of this study is the absence of Clinical Attachment Level (CAL) measurements, which are crucial for accurately assessing periodontitis. The lack of CAL data raises the possibility of overestimating the severity of periodontal disease. Future studies should incorporate CAL measurements to ensure more precise evaluation of periodontitis. Conclusions A significant association between obesity and the proportion of teeth with periodontal pockets was demonstrated in this study. The high-income group had a significantly lower proportion of teeth with PPD ≥ 4 mm compared to the low-to-middle-income group. Furthermore, adults with obesity with low-to-middle incomes may face a higher risk of periodontal disease than those with obesity who have higher incomes. Declarations Funding This work was supported by a Grant-in-Aid for Research from the Ministry of Education, culture, Sports, Science and Technology of Japan (grant number 23K15995 to NS and 19K10125 to KM). Conflicts of Interest The authors declare that they have no conflict of interest. Ethics approval This study was approved by the Research Ethics Committee of Tokyo Medical and Dental University Dental Hospital (approval number: 1085) and conducted in accordance with the Declaration of Helsinki of 1975, as revised in 2013. This study was registered at the University Hospital Medical Information Network (UMIN:http//www. umin. ac. jp/) (clinical trial number: UMIN000046582). Consent to participate Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. Data availability The datasets generated and/or analyzed in the current study are available from the corresponding author upon reasonable request. Code availability Not applicable. Author’s contributions NS, RM, KM, YI, JA, and TI developed the study concept. NA, TM, TS, and KT provided substantial assistance with the data collection. NS and RM performed statistical analyses and wrote the initial draft of the manuscript. The authors have reviewed and approved the final version of this manuscript. Acknowledgements The authors thank the staff of the Department of Periodontology of Institute of Science Tokyo for their assistance with data collection. This work was supported by a Grant-in-Aid for Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (grant number 23K15995 to NS and 19K10125 to KM). References Field AE, Coakley EH, Must A et al (2001) Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med 161:1581–1586. https://doi.org/10.1001/archinte.161.13.1581 Jung UJ, Choi MS (2014) Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. 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Int J Epidemiol 44:638–650. https://doi.org/10.1093/ije/dyv075 Kivimäki M, Virtanen M, Kawachi I et al (2015) Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: a meta-analysis of published and unpublished data from 222 120 individuals. Lancet Diabetes Endocrinol 3:27–34. https://doi.org/10.1016/s2213-8587(14)70178-0 Peres MA, Macpherson LMD, Weyant RJ et al (2019) Oral diseases: a global public health challenge. Lancet 394:249–260. https://doi.org/10.1016/s0140-6736(19)31146-8 Organization WH (2022) SEVENTY-FIFTH WORLD HEALTH ASSEMBLY Provisional agenda item 14.1 Book title Knight EL, Jiang Y, Rodriguez-Stanley J, Almeida DM, Engeland CG, Zilioli S (2021) Perceived stress is linked to heightened biomarkers of inflammation via diurnal cortisol in a national sample of adults. Brain Behav Immun 93:206–213. https://doi.org/10.1016/j.bbi.2021.01.015 Hong L, Liu Y, Hottel TL, Hoff GL, Cai J (2015) Neighborhood socio-economic context and emergency department visits for dental care in a U.S. Midwestern metropolis. Public Health 129:252–257. https://doi.org/10.1016/j.puhe.2014.11.014 Fekedulegn D, Andrew M, Violanti J, Hartley T, Charles L, Burchfiel C (2010) Comparison of Statistical Approaches to Evaluate Factors Associated With Metabolic Syndrome. J Clin Hypertens 12:365–373. https://doi.org/10.1111/j.1751-7176.2010.00264.x Jepsen S, Suvan J, Deschner J (2020) The association of periodontal diseases with metabolic syndrome and obesity. Periodontol 2000 83:125–153. https://doi.org/10.1111/prd.12326 Krysiak R, Handzlik-Orlik G, Okopien B (2012) The role of adipokines in connective tissue diseases. Eur J Nutr 51:513–528. https://doi.org/10.1007/s00394-012-0370-0 Adamczak M, Wiecek A (2013) The adipose tissue as an endocrine organ. Semin Nephrol 33:2–13. https://doi.org/10.1016/j.semnephrol.2012.12.008 Taylor JJ (2010) Cytokine regulation of immune responses to Porphyromonas gingivalis. Periodontol 2000 54:160–194. https://doi.org/10.1111/j.1600-0757.2009.00344.x Garlet GP (2010) Destructive and protective roles of cytokines in periodontitis: a re-appraisal from host defense and tissue destruction viewpoints. J Dent Res 89:1349–1363. https://doi.org/10.1177/0022034510376402 Tomofuji T, Yamamoto T, Tamaki N et al (2009) Effects of Obesity on Gingival Oxidative Stress in a Rat Model. J Periodontol 80:1324–1329. https://doi.org/10.1902/jop.2009.080621 Boden G (2008) Obesity and Free Fatty Acids. Endocrinol Metab Clin North Am 37:635–646. https://doi.org/10.1016/j.ecl.2008.06.007 Ogawa W, Hirota Y, Miyazaki S et al (2024) Definition, criteria, and core concepts of guidelines for the management of obesity disease in Japan. Endocr J 71:223–231. https://doi.org/10.1507/endocrj.ej23-0593 Ekuni D, Yamamoto T, Koyama R, Tsuneishi M, Naito K, Tobe K (2008) Relationship between body mass index and periodontitis in young Japanese adults. J Periodontal Res 43:417–421. https://doi.org/10.1111/j.1600-0765.2007.01063.x Katagiri S, Nitta H, Nagasawa T et al (2010) High prevalence of periodontitis in non-elderly obese Japanese adults. Obes Res Clin Pract 4:e247–342. https://doi.org/10.1016/j.orcp.2010.08.005 Morita T, Ogawa Y, Takada K et al (2009) Association between periodontal disease and metabolic syndrome. J Public Health Dent 69:248–253. https://doi.org/10.1111/j.1752-7325.2009.00130.x Saito T (2008) Obesity may be associated with periodontitis in elderly men. J Evid Based Dent Pract 8:97–98. https://doi.org/10.1016/j.jebdp.2008.03.015 Morita I, Okamoto Y, Yoshii S et al (2011) Five-year incidence of periodontal disease is related to body mass index. J Dent Res 90:199–202. https://doi.org/10.1177/0022034510382548 Zhu P, Li A, Cai Q et al (2023) Sex differences in the association between dual-energy x‐ray absorptiometry‐measured body composition and periodontitis. J Periodontol. https://doi.org/10.1002/jper.23-0162 Tomiyama AJ (2014) Weight stigma is stressful. A review of evidence for the Cyclic Obesity/Weight-Based Stigma model. Appetite 82:8–15. https://doi.org/10.1016/j.appet.2014.06.108 Aoki J, Zaitsu T, Ohshiro A, Aida J (2023) Association of Stressful Life Events with Oral Health Among Japanese Workers. J Epidemiol. https://doi.org/10.2188/jea.JE20220225 Phelan JC, Link BG (2005) Controlling disease and creating disparities: a fundamental cause perspective. J Gerontol B Psychol Sci Soc Sci 60 Spec No 2:27–33. https://doi.org/10.1093/geronb/60.special_issue_2.s27 Moore CJ, Cunningham SA (2012) Social position, psychological stress, and obesity: a systematic review. J Acad Nutr Diet 112:518–526. https://doi.org/10.1016/j.jand.2011.12.001 Edwards M, Davies M, Edwards A (2009) What are the external influences on information exchange and shared decision-making in healthcare consultations: a meta-synthesis of the literature. Patient Educ Couns 75:37–52. https://doi.org/10.1016/j.pec.2008.09.025 Benjafield AV, Ayas NT, Eastwood PR et al (2019) Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med 7:687–698. https://doi.org/10.1016/s2213-2600(19)30198-5 Kim TJ, von dem Knesebeck O (2018) Income and obesity: what is the direction of the relationship? A systematic review and meta-analysis. BMJ Open 8:e019862. https://doi.org/10.1136/bmjopen-2017-019862 Abbas H, Aida J, Saito M et al (2019) Income or education, which has a stronger association with dental implant use in elderly people in Japan? Int Dent J 69:454–462. https://doi.org/10.1111/idj.12491 Additional Declarations No competing interests reported. Supplementary Files ESM1.docx Cite Share Download PDF Status: Published Journal Publication published 15 Nov, 2025 Read the published version in Clinical Oral Investigations → Version 1 posted Editorial decision: Revision requested 30 Jul, 2025 Reviews received at journal 28 Jul, 2025 Reviewers agreed at journal 16 Jun, 2025 Reviews received at journal 06 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 04 Apr, 2025 Editor assigned by journal 25 Mar, 2025 Submission checks completed at journal 25 Mar, 2025 First submitted to journal 24 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Mikami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYDACZjYwxcMPJCRALMYGYrVIthGthQGihcHgGFQLQaDbzpb4uaDinozx/e7EGww1dgzMswlYY3aY7bD0jDPFPGbHeDdbMBxLZmCcc4CQFvYGad62BJCWbRIMbAcYGGckENTS/Jv3XwKPcRtIyz+itLAdk+ZtSOAxYANqYWwjTkua9YxjCTwSx3I3WyT2JfMQ9sv5Y8a3C2oS7Pmbz2688eGbnZwhoRADAWY4C+gkHsMZhHUgaQEBeeIidBSMglEwCkYQAAC66j048idwuAAAAABJRU5ErkJggg==","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":true,"prefix":"","firstName":"Risako","middleName":"","lastName":"Mikami","suffix":""},{"id":439046316,"identity":"063d834a-0be7-4479-9c93-86a38588c66b","order_by":2,"name":"Koji Mizutani","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Koji","middleName":"","lastName":"Mizutani","suffix":""},{"id":439046317,"identity":"0714e7aa-dcde-441f-b3c9-81e512024c7a","order_by":3,"name":"Norio Aoyama","email":"","orcid":"","institution":"Kanagawa Dental University","correspondingAuthor":false,"prefix":"","firstName":"Norio","middleName":"","lastName":"Aoyama","suffix":""},{"id":439046318,"identity":"387bfbd7-91b0-4745-a101-e74f1fed32c2","order_by":4,"name":"Takanori Matsuura","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Takanori","middleName":"","lastName":"Matsuura","suffix":""},{"id":439046319,"identity":"986f6835-ee8b-48a9-a9ea-7f3ef8b10aa9","order_by":5,"name":"Tomonari Suda","email":"","orcid":"","institution":"Secomedic Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tomonari","middleName":"","lastName":"Suda","suffix":""},{"id":439046320,"identity":"4ce84c6f-fc5a-4430-886f-fd4784663de4","order_by":6,"name":"Kohei Takeda","email":"","orcid":"","institution":"Higashi Sakura Dental Clinic","correspondingAuthor":false,"prefix":"","firstName":"Kohei","middleName":"","lastName":"Takeda","suffix":""},{"id":439046321,"identity":"15ebe599-4481-4025-8e9b-77b0fad8eec2","order_by":7,"name":"Jun Aida","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Aida","suffix":""},{"id":439046322,"identity":"0ed8dc4a-c4c1-4041-8ca8-7f77ce9e3a8a","order_by":8,"name":"Yuichi Izumi","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Izumi","suffix":""},{"id":439046323,"identity":"be8d86dd-cd9e-4715-9bd2-62f8f8735c6b","order_by":9,"name":"Takanori Iwata","email":"","orcid":"","institution":"Institute of Science Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Takanori","middleName":"","lastName":"Iwata","suffix":""}],"badges":[],"createdAt":"2025-03-25 03:38:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6299667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6299667/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00784-025-06638-1","type":"published","date":"2025-11-15T15:57:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80139209,"identity":"56c9623e-bcfe-410f-be4c-fbb3d1abb940","added_by":"auto","created_at":"2025-04-08 11:03:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30459,"visible":true,"origin":"","legend":"\u003cp\u003ePredictive margin plot modeled based on the multivariate analyses to assess the interaction between income and body mass index (BMI) on the proportion of teeth with probing pocket depth (PPD) ≥ 4 mm\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6299667/v1/a38b63275d146a292d98767a.png"},{"id":96105141,"identity":"7a3848bc-8f3d-4af7-8c48-1735b50ce868","added_by":"auto","created_at":"2025-11-17 16:09:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":988878,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6299667/v1/2772e120-c37c-46e3-8215-628b0c6e2674.pdf"},{"id":80139215,"identity":"e457bbd6-6a86-489c-9b05-bc855595093f","added_by":"auto","created_at":"2025-04-08 11:03:27","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15889,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6299667/v1/ec11341c3a59597be7eb4855.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Income-related inequalities affect the association between obesity and periodontal disease: A cross-sectional analysis in Tokyo Metropolitan Districts","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is a precursor to various non-communicable diseases, such as type 2 diabetes,\u003csup\u003e[1]\u003c/sup\u003e dyslipidemia,[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] hypertension,[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] cardiovascular diseases,[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] respiratory diseases,[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and nonalcoholic fatty liver disease.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Numerous studies have investigated the association between periodontal disease and obesity.[\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] A recent umbrella review[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] encompassing the existing evidence demonstrated a positive association between these two. Few longitudinal cohort studies support these findings,[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] although there is suggestive evidence of racial differences in the association between obesity and periodontitis, with reports indicating a stronger impact of obesity on periodontitis among Europeans and Japanese than among Americans or other Asian population.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] However, some research suggests that there is insufficient evidence to support a causal relationship between periodontal disease and obesity.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSocioeconomic status (SES) is strongly associated with health behaviors such as dietary habits, smoking, and physical activity, and is known to influence various health-related factors, including obesity.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Furthermore, it is associated with the prevalence and severity of oral diseases[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and has been suggested to contribute to health inequalities. At the 74th World Health Assembly, 2022, the World Health Organization set a goal of reducing health inequalities in oral diseases, conditions, and health.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Thus, we hypothesized that not only SES and obesity independently impact oral health, but the effect of obesity on oral health may also vary according to SES.\u003c/p\u003e \u003cp\u003eMultiple inflammatory pathways are assumed to mediate the mechanisms linking the two. Stress is known to elevate inflammatory biomarkers.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Social pressure related to body image, including physical appearance associated with obesity, can contribute to stress. Additionally, low SES is considered to exacerbate everyday stress. Accordingly, individuals with obesity and low SES may have a heightened risk of worsening periodontal disease. However, no previous studies have investigated the effect of SES on the relationship between periodontal disease and obesity. Therefore, in this study, we aimed to examine the influence of SES on the association between obesity and periodontal disease in the Japanese population.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design and participants\u003c/h2\u003e\n \u003cp\u003eIn this cross-sectional study, we extracted data for analysis from a comprehensive database that records information on all patients who visit the periodontal clinic of the Dental Hospital of Tokyo Medical and Dental University (TMDU), located in the center of the Tokyo Metropolitan District, for their first consultation. Therefore, prior power analysis was not performed for sample size calculation. Informed consent was obtained from all participants. The study design was approved by the Dental Research Ethics Committee of TMDU (approval number: 1085). The study was conducted following the Declaration of Helsinki of 1975, as revised in 2013, and was registered with the University Hospital Medical Information Network (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.umin.ac.jp\u003c/span\u003e\u003c/span\u003e) (clinical trial number: UMIN000046582). The research was also conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. The data of participants meeting the following inclusion criteria were used for the analysis.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eInclusion criteria\u003c/em\u003e\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e1. Individuals who visited the periodontal clinic of the Dental Hospital of TMDU for their first consultation between October 2014 and February 2016.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e2. Only residents of the Tokyo Metropolitan District, which has a radius of approximately 15 km from the hospital, were considered for inclusion to prevent accessibility bias due to distance from the hospital.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e3. Participants aged 18 years or older.\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003e\u003cem\u003eExclusion criteria\u003c/em\u003e\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e1. Participants with missing values of either the independent or dependent variables.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e2. Participants requiring a proxy for medical interviews or informed consent.\u003c/p\u003e\n \u003c/span\u003e\n\u003c/div\u003e\n\u003ch3\u003eClinical examination\u003c/h3\u003e\n\u003cp\u003eInformation on participants\u0026rsquo; medical and social backgrounds was collected through medical interviews and health insurance records. Experienced periodontists conducted the dental examinations, which involved recording the number of remaining teeth, probing pocket depth (PPD), and bleeding on probing (BOP). A manual probe (15 UNC Color-Coded Probe, Hu-Friedy, USA) was used for examination. The PPD and BOP were evaluated at six points on each tooth, recording the deepest PPD and presence or absence of BOP for each tooth. The independent variable was the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm in relation to the total number of remaining teeth.\u003c/p\u003e\n\u003cp\u003eMedical histories (e.g., diabetes, smoking habits, and prior periodontal therapy) were collected through medical interviews. Body mass index (BMI) was grouped into three categories: underweight (\u0026lt;\u0026thinsp;18.5), normal (18.5 to 25), and obese (\u0026ge;\u0026thinsp;25). Smoking status was classified as follows: never smoked, former smoker, or current smoker. Individuals who reported scaling and root planing, or those who were referred by their primary dentists, were identified as having a history of periodontal therapy.\u003c/p\u003e\n\u003cp\u003eInformation on place of residence and type of health insurance was obtained from participants\u0026rsquo; registration data in their hospital records. Income and educational attainment were used to determine SES. Based on a previous study,[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e] we used the average income within each participant\u0026rsquo;s residential ward as the income of individuals, as individual income data were not available.\u003c/p\u003e\n\u003cp\u003eWe calculated the average household income of the residents of the 23 wards of Tokyo as (taxable income)/(number of taxpayers) using data obtained from a survey conducted in 2019 by the Japanese Ministry of Internal Affairs and Communications (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.soumu.go.jp/main_sosiki/jichi_zeisei/czaisei/czaisei_seido/ichiran09_19.html\u003c/span\u003e\u003c/span\u003e). Income was categorized into the highest tertile and other categories and expressed in units of 1000 yen; 1000 yen was converted to 6.6 US dollars according to the exchange rate as of January 2024.\u003c/p\u003e\n\u003cp\u003eEducation level, as categorized into two groups\u0026mdash;highest tertile and others, was based on the percentage of residents with university or higher education in each ward (\u0026ge;\u0026thinsp;16 years of formal education). We used the levels attributed to the participants\u0026rsquo; residential wards as determined by a 2010 survey conducted by the Japanese Ministry of Internal Affairs and Communications (e-stat, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.e-stat.go.jp/\u003c/span\u003e\u003c/span\u003e, in Japanese), given that individual education levels were not available.\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eDescriptive statistics were presented, indicating the mean (standard deviation [SD]) for continuous variables and the number (%) for categorical variables. The calculation of the proportions of teeth with PPD exceeding 4 mm relative to the total remaining teeth was conducted as follows: (number of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm) / (total number of teeth) \u0026times; 100 (%). A comparison among the three BMI-based groups was performed using a one-way analysis of variance or Fisher\u0026rsquo;s exact test. Multilevel Poisson regression analyses were employed to determine the ratio of means (RM)[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] for the proportion of teeth with PPD exceeding 4 mm in relation to the total number of remaining teeth, given a skewed distribution.[\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] The data were structured into multilevel models to account for participants nested in their ward of residence. In the multivariate analysis, explanatory variables included age, sex, diabetes, BMI, income, education level, smoking status, and history of periodontal therapy. To explore the interaction between BMI and income with respect to the proportions of teeth with PPD exceeding 4 mm, we conducted multivariate analyses with interaction terms, and margin plots were generated to model the interaction between BMI and income for the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm. The goodness of fit for the models was evaluated using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Statistical analyses were conducted using Stata software (version 17.0; Stata Corp LP, College Station, Texas, USA), with statistical significance set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 3310 individuals who visited the periodontal clinic of the Dental Hospital of Tokyo Medical and Dental University for their first consultation between October 2014 and February 2016, 1639 were included in the study; 1671 residing outside the Tokyo Metropolitan District were excluded. Subsequently, of the 1639, 677 individuals were excluded due to insufficient data, resulting in the inclusion of data from 962 participants for the analysis. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the demographic data, revealing that the mean age of the 962 participants (302 males and 660 females) was 58.3 years (\u003cem\u003eSD\u003c/em\u003e: 13.8). The mean BMI for the underweight, normal weight, and obese groups were 17.3 (\u003cem\u003eSD\u003c/em\u003e: 1.1), 21.7 (\u003cem\u003eSD\u003c/em\u003e: 1.8), and 27.7 (\u003cem\u003eSD\u003c/em\u003e: 2.5) kg/m\u003csup\u003e2\u003c/sup\u003e, respectively. The mean income for the high-, middle-, and low-income groups were 8061.6 (\u003cem\u003eSD\u003c/em\u003e: 2331.4), 4747.2 (\u003cem\u003eSD\u003c/em\u003e: 521.9), and 3665.6 (\u003cem\u003eSD\u003c/em\u003e: 128.3) thousand yen, respectively. The mean number of remaining teeth was 24.6 (\u003cem\u003eSD\u003c/em\u003e: 4.8), with mean proportions of teeth having PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm at 30.8% (\u003cem\u003eSD\u003c/em\u003e: 28.3%). The mean proportion of teeth with BOP was 51.3% (\u003cem\u003eSD\u003c/em\u003e: 31.3%). Significant differences were observed among three BMI-based groups in terms of sex, BMI, diabetes, teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm, and BOP positive teeth.\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 participants (N\u0026thinsp;=\u0026thinsp;962)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;962)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;127)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;651)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;184)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003eor mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003eor mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003eor mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003eor mean (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (in years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.3 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.1 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.0 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58.3 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e660 (68.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115 (90.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e444 (68.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e101 (54.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e302 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e207 (31.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.3 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.7 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e27.7 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\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\u003eDiabetes\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e27 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\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\u003eIncome level, mean yearly income in thousand yen / USD\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest, 8061.6 (SD: 2331.4) / 53,206.6 (SD: 15387.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e179 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e120 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e34 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle, 4747.2 (SD: 521.9) / 31,331.5 (SD: 3,444.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e476 (49.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69 (54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e313 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e94 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLowest, 3665.6 (SD: 128.3) / 2,419.6 (SD:846.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e307 (31.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33 (26.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e218 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e56 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e309 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48 (37.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e209 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e320 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e204 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e73 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLowest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e333 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e238 (36.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e598 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83 (65.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e416 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e265 (27.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e171 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64 (9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDental health 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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of teeth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.6 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.7 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e24.5 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.8 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.4 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29.8 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e39.0 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\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\u003eTeeth with BOP positive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.3 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.9 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.1 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e56.8 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of periodontal therapy\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e361 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e258 (39.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA multivariate Poisson regression analysis showed that age, sex, BMI, income, smoking, and history of periodontal therapy were associated with the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate models 1 and 2). Participants with obesity exhibited a significantly higher ratio of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm compared to those with normal BMI (RM: 1.25, 95% confidence interval [CI]: 1.14, 1.38, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate model 2). The high-income group had a significantly lower ratio of teeth with PPDs\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (RM: 0.86, 95% CI: 0.77, 0.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate model 2) compared to the low-to-middle income group. Education level was not significantly associated with the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm. Smoking was significantly associated with the ratio of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm. Former and current smokers showed significantly higher RMs of 1.36 and 1.42 (95% CI: 1.18, 1.57 and 1.22, 1.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001: Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate model 2), respectively, compared to those who never smoked for the proportion of teeth with PPDs\u0026thinsp;\u0026ge;\u0026thinsp;4 mm.\u003c/p\u003e \u003cp\u003eAdditionally, an examination of the interaction between BMI and income with the proportion of teeth having PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm revealed significant interactions in the obesity and high-income group towards the ratio of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, multivariate model 3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033).\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\u003eMultilevel Poisson regression analysis of the factors influencing the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"22\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c5\" namest=\"c3\" rowspan=\"2\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"16\" nameend=\"c22\" namest=\"c7\"\u003e \u003cp\u003eMultivariate model*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c22\" namest=\"c19\"\u003e \u003cp\u003eModel 3\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.00, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.00, 1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15, 1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06, 1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.01, 1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.01, 1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03, 1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96, 1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.89, 1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.89, 1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5: underweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69, 1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.70, 1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.70, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.5\u0026ndash;25: normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c22\" namest=\"c19\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25: obesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17, 1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.14, 1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.19, 1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLowest to middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c22\" namest=\"c19\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74, 1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79, 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.77, 0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.81, 1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\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 \u003cp\u003eLowest to middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c22\" namest=\"c19\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72, 1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.82, 1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.85, 1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.85, 1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c22\" namest=\"c19\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23, 1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.13, 1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.18, 1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.20, 1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26, 1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.20, 1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.22, 1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.23, 1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHistory of periodontal therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03, 1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.05, 1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.05, 1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.06, 1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI x Income\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=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnderweight x Highest income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.62, 0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eObesity x Highest income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.56, 0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"21\" nameend=\"c21\" namest=\"c1\"\u003e \u003cp\u003eRM, ratio of means; CI, confidence interval; BMI: Body Mass Index; PPD: probing pocket depth. * Adjusted for all covariates listed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c22\" namest=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eProportions of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm were estimated from the models with adjustments for covariates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among participants in the high-income group, the prevalence of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm did not differ based on BMI. However, in the low-to-middle-income group, it was observed that participants with obesity had a significantly higher proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm. The multivariate model 3, which included the interaction terms, demonstrated the best fit according to AIC and BIC (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA subgroup analysis was conducted to explore sex differences in the association between obesity and periodontal disease. Although the interaction between obesity and sex towards the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm was not significant, the RM of obesity for the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm showed a trend towards a higher RM of 1.33 (95% CI: 1.12, 1.58) in females compared to 1.13 (95% CI: 0.98, 1.29) in males (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjusted associations between BMI and the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm by sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eMale (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eFemale (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;660)\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 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRM* (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRM* (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\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=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.47, 1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e115 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89 (0.73, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (68.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e444 (67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (0.98, 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e101 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.33 (1.12, 1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e*RM adjusted for age, diabetes, income, education level, smoking, and history of periodontal therapy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this was the first study to demonstrate the influence of income-related inequalities on the association between obesity and periodontal disease among the Japanese population. By examining the modifying role of SES, our findings contribute to a deeper understanding of how economic factors interplay with obesity to influence oral health. A BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 and higher income not only independently affect the proportion of teeth with periodontal pockets but also exhibit interaction for it. The association between obesity and periodontal disease appeared to be negligible among individuals with higher incomes, whereas it was significant for those with lower incomes. Furthermore, the association between obesity and periodontal disease tended to be stronger in females than in males after adjusting for possible confounding factors. This study has the potential to contribute to raising awareness about obesity and periodontal disease prevention among low-income individuals and improve public assistance initiatives.\u003c/p\u003e \u003cp\u003eMultiple mechanisms have been proposed to explain the association between obesity and periodontal disease.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] An imbalance between pro-inflammatory adipokines produced by excess adipose tissue and anti-inflammatory adipokines, leads to a systemic state of mild inflammation.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] This imbalance affects not only systemic health but also periodontal tissue destruction in obese individuals.\u003csup\u003e[25, 26]\u003c/sup\u003e Additionally, increased production of reactive oxygen species and free fatty acids by adipocytes may exacerbate inflammation and tissue destruction in periodontal tissues.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] In this study, it was observed that the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm increased in the group with BMI\u0026thinsp;\u0026ge;\u0026thinsp;25, suggesting that the systemic chronic inflammatory state due to obesity may impact the progression of periodontal disease.\u003c/p\u003e \u003cp\u003eDespite the limited consideration of body fat distribution and sex differences, BMI remains widely utilized in surveys owing to its simplicity and practicality. In Japan, a BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2 [29]\u003c/sup\u003e is classified as obesity, which differs from the Western criteria that identify a person with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e as obese. Nonetheless, several studies conducted in Japan have suggested a relationship between obesity and periodontal disease.[\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] In both sexes, the risk of developing periodontal disease within five years is higher in the group with BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e compared to the group with BMI\u0026thinsp;\u0026lt;\u0026thinsp;22 kg/m\u003csup\u003e2\u003c/sup\u003e, with the risk being greater for females than males.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] Consistent with previous findings, we also found that a BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 was associated with a higher risk of periodontal disease among females compared to males. Several studies have proposed possible underlying mechanisms. A study reported that in females, a high body adipose index combined with a low skeletal muscle index was significantly associated with an elevated odds ratio of periodontal disease by utilizing Dual-energy X-ray Absorptiometry, which allows for a more precise measurement of obesity than BMI.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] However, it has been observed that females face higher social pressures[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] regarding their appearance, including body shape, than males. Consequently, females may experience greater stress related to being overweight, a condition that may be implicated in the progression of periodontitis. Evidence suggests that stress significantly impacts periodontitis.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] However, the mechanisms underlying sex-related differences in the association between obesity and periodontal disease remain unclear.\u003c/p\u003e \u003cp\u003eInterestingly, we found a statistically significant difference in the adverse effects of obesity on the proportion of teeth with periodontal pockets depending on income level. This study is the first to show a significant interaction between obesity, income, and the proportion of teeth with periodontal pockets. The relationship between SES and health is commonly mediated by lifestyle factors such as alcohol consumption, lack of exercise, and stress.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] These factors, such as those not considered in this study, may be reflected in the results. Another hypothesis stated that high-income populations engage in meticulous oral hygiene and regular dental care. Individuals with a high SES generally have high health literacy[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]; moreover, high-income participants may be better able to pay for the costs of oral hygiene and dental care. These positive oral health behaviors may compensate for the adverse effects of obesity in those in the high-income group. Furthermore, a prior study noted that physical appearance related to obesity may impact employment, potentially affecting income.[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] Although the temporal relationship between income and obesity is unclear in this study, individuals with both low income and obesity may experience compounded stress from both factors, which could contribute to the progression of periodontal disease.\u003c/p\u003e \u003cp\u003eAnother interesting point is that we found inequalities in SES by income but not by education level. A previous study[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] reported that income had a significantly stronger association with dental implant usage than education. This study suggests that income inequality might be more strongly associated with health inequalities than education.\u003c/p\u003e \u003cp\u003eThis study had several limitations. First, there are limitations related to data collection. Owing to the inability to obtain individual income and education data, household income and education level were estimated as surrogates from residential areas. This may not accurately reflect the participants\u0026rsquo; actual SES. While discrepancies exist between individual and area-level SES, the bias introduced by this method is considered nonsystematic rather than systematic. Therefore, the results of this study may have a wider confidence interval and the observed significant results may still be robust. Another limitation of this method is that the results may be associated with both income and education level disparities as well as other factors, such as the local environment. Further research using individual SES data is, thus, required to validate the results of this study. Moreover, detailed data on smoking habits, such as the duration of smoking and the number of cigarettes consumed per day are missing. While smoking status was categorized as \u0026ldquo;current smoker,\u0026rdquo; \u0026ldquo;former smoker,\u0026rdquo; and \u0026ldquo;never smoked,\u0026rdquo; we acknowledge that this classification does not fully account for the intensity of smoking, which is a key periodontal risk factor. Future studies should thus incorporate more comprehensive smoking data for a more detailed analysis. Another limitation regarding data collection is the inclusion of PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm that may not be associated with active periodontitis, such as inactive pockets following successful periodontal therapy or pockets caused by non-periodontal factors, including root fractures. Given that the mechanism by which obesity influences periodontal disease is linked to inflammation, it is plausible that the interaction between obesity and SES would be more pronounced in active periodontal pockets. If an analysis limited to active periodontal pockets could be performed, stronger associations might be observed. Therefore, the inclusion of inactive pockets in this study likely introduced a bias that underestimated the true strength of the relationship. Nevertheless, the significant interaction between obesity and SES observed in this study suggests that the findings could be robust. Future studies should, thus, refine the classification of periodontal disease activity to account for these variations and further validate the results. Second, we adjusted for diabetes as it is a known confounder affecting both obesity and periodontal disease in this study. However, other systemic diseases that could potentially influence both conditions were not specifically adjusted for. Third, because this was a cross-sectional study, causality could not be determined. Cohort and life course studies should thus investigate the impact of SES more thoroughly in the future. Fourth, a preliminary power analysis was not conducted as this was an observational study using a database. The possibility of underestimation owing to the small sample size is present because of the lack of power analysis; however, the sample size of this study was considered sufficient to demonstrate significant differences. As additional examinations beyond those routinely performed in clinics were not necessary for this study, obtaining a large sample size without ethical concerns improved the generalizability of the study results. Fifth, because the data were collected during routine clinical practice, the pre-study calibration of the examiners was not performed in this study. Although all examiners were experienced periodontists, the lack of calibration could lead to non-differential misclassification, potentially leading to bias widening the confidence intervals. Despite this potential bias, the detection of statistically significant differences suggests that the results of the analysis could be robust. Lastly, a notable limitation of this study is the absence of Clinical Attachment Level (CAL) measurements, which are crucial for accurately assessing periodontitis. The lack of CAL data raises the possibility of overestimating the severity of periodontal disease. Future studies should incorporate CAL measurements to ensure more precise evaluation of periodontitis.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA significant association between obesity and the proportion of teeth with periodontal pockets was demonstrated in this study. The high-income group had a significantly lower proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm compared to the low-to-middle-income group. Furthermore, adults with obesity with low-to-middle incomes may face a higher risk of periodontal disease than those with obesity who have higher incomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis work was supported by a Grant-in-Aid for Research from the Ministry of Education, culture, Sports, Science and Technology of Japan (grant number 23K15995 to NS and 19K10125 to KM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e This study was approved by the Research Ethics Committee of Tokyo Medical and Dental University Dental Hospital (approval number: 1085) and conducted in accordance with the Declaration of Helsinki of 1975, as revised in 2013. This study was registered at the University Hospital Medical Information Network (UMIN:http//www. umin. ac. jp/) (clinical trial number: UMIN000046582).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003eThe datasets generated and/or analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e Not applicable.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u0026nbsp;\u003c/strong\u003eNS, RM, KM, YI, JA, and TI developed the study concept. NA, TM, TS, and KT provided substantial assistance with the data collection. NS and RM performed statistical analyses and wrote the initial draft of the manuscript. The authors have reviewed and approved the final version of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThe authors thank the staff of the Department of Periodontology of Institute of Science Tokyo for their assistance with data collection. This work was supported by a Grant-in-Aid for Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (grant number 23K15995 to NS and 19K10125 to KM).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eField AE, Coakley EH, Must A et al (2001) Impact of overweight on the risk of developing common chronic diseases during a 10-year period. 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Int Dent J 69:454\u0026ndash;462. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/idj.12491\u003c/span\u003e\u003cspan address=\"10.1111/idj.12491\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\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":"clinical-oral-investigations","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cloi","sideBox":"Learn more about [Clinical Oral Investigations](http://link.springer.com/journal/784)","snPcode":"784","submissionUrl":"https://submission.nature.com/new-submission/784/3","title":"Clinical Oral Investigations","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"socioeconomic status, obesity, periodontal disease, health inequality, body mass index, income level","lastPublishedDoi":"10.21203/rs.3.rs-6299667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6299667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eObesity is a risk factor for periodontal disease and is associated with socioeconomic status (SES). However, it remains unclear whether SES modifies the relationship between obesity and periodontal disease. This study aimed to investigate the influence of SES on the association between obesity and periodontal disease.\u003c/p\u003e\u003ch2\u003eMaterial and Methods\u003c/h2\u003e \u003cp\u003eWe used multilevel Poisson regression, adjusted for SES, to analyze the body mass index (BMI) and periodontal parameters of 962 participants (mean age 58.3 years; SD: 13.8). SES was assessed based on the average income and education levels of their residential areas.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA significant association was observed between obesity and the proportion of teeth with probing pocket depth (PPD)\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (ratio of means [RM]: 1.25, 95% confidence interval [CI]: 1.15, 1.38, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the higher-income group exhibited a significantly lower proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm (RM: 0.86, 95% CI: 0.77, 0.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007). Interaction analysis also revealed a significant interaction between obesity and the high-income group regarding the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm. The subgroup analysis demonstrated that the RM of obesity for the proportion of teeth with PPD\u0026thinsp;\u0026ge;\u0026thinsp;4 mm was higher in females than in males.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIncome-related inequalities affect the association between obesity and periodontal disease. Among obese adults, those with low-to-middle-income levels may have a higher risk of periodontal disease than those with high-incomes.\u003c/p\u003e\u003ch2\u003eClinical Relevance\u003c/h2\u003e \u003cp\u003eComprehensive care and oral health education should be enhanced for obese individuals in low-income populations to mitigate their elevated risk of periodontal disease.\u003c/p\u003e","manuscriptTitle":"Income-related inequalities affect the association between obesity and periodontal disease: A cross-sectional analysis in Tokyo Metropolitan Districts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-08 11:03:23","doi":"10.21203/rs.3.rs-6299667/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-30T21:29:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-28T06:36:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79013547667271989776199634867779758817","date":"2025-06-16T06:42:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-06T10:52:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192502557884325793952345892843755103891","date":"2025-04-04T13:17:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21860686952939676311538733494548222160","date":"2025-04-04T11:16:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-04T08:45:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-25T10:43:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-25T10:41:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clinical Oral Investigations","date":"2025-03-25T03:33:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clinical-oral-investigations","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cloi","sideBox":"Learn more about [Clinical Oral Investigations](http://link.springer.com/journal/784)","snPcode":"784","submissionUrl":"https://submission.nature.com/new-submission/784/3","title":"Clinical Oral Investigations","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8b5a3120-0343-4590-a7b4-66056472e1a8","owner":[],"postedDate":"April 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:03:56+00:00","versionOfRecord":{"articleIdentity":"rs-6299667","link":"https://doi.org/10.1007/s00784-025-06638-1","journal":{"identity":"clinical-oral-investigations","isVorOnly":false,"title":"Clinical Oral Investigations"},"publishedOn":"2025-11-15 15:57:29","publishedOnDateReadable":"November 15th, 2025"},"versionCreatedAt":"2025-04-08 11:03:23","video":"","vorDoi":"10.1007/s00784-025-06638-1","vorDoiUrl":"https://doi.org/10.1007/s00784-025-06638-1","workflowStages":[]},"version":"v1","identity":"rs-6299667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6299667","identity":"rs-6299667","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}