The Association between Sarcopenic Obesity and Impaired Activities of Daily Living among Middle-aged and Elderly Chinese: A Study Based on CHARLS

The Association between Sarcopenic Obesity and Impaired Activities of Daily Living among Middle-aged and Elderly Chinese: A Study Based on CHARLS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Association between Sarcopenic Obesity and Impaired Activities of Daily Living among Middle-aged and Elderly Chinese: A Study Based on CHARLS Yaowen Zhu, Jinhui Jia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8899879/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Objective This study aimed to investigate the association between sarcopenic obesity (SO) and impairments in basic activities of daily living (BADL) and instrumental activities of daily living (IADL) among middle-aged and elderly individuals. Methods Data were derived from the China Health and Retirement Longitudinal Study (CHARLS), with a final sample of 4,477 participants. Participants were categorized into four exposure groups: normal (no sarcopenia or obesity, n = 1,504), possible sarcopenia \(\:n=841\) , obesity alone \(\:n=\text{1,870}\) , and sarcopenic obesity \(\:SO,n=262\) . Using BADL/IADL impairment as the outcome, multivariable logistic regression with stepwise adjustment across multiple models was employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Results Baseline prevalence of BADL/IADL impairment showed a gradient increase across the four groups, with the highest rates observed in the SO group (18.32% for BADL, 45.80% for IADL). In the fully adjusted model, SO was significantly associated with both IADL impairment (OR = 1.90, 95% CI: 1.42–2.55) and BADL impairment (OR = 1.73, 95% CI: 1.15–2.58). No significant associations were found between obesity alone and IADL/BADL impairment. Possible sarcopenia was positively associated with IADL impairment (OR = 1.35, 95% CI: 1.10–1.66). Conclusion Sarcopenia-related exposures, particularly sarcopenic obesity, are significantly associated with ADL impairment. These findings suggest that both muscle mass/strength and body fat management should be prioritized in the prevention and control of functional decline among the elderly. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Figures Figure 1 1. Introduction With the acceleration of population aging, the burden of functional limitations and disability in later life has surged rapidly, becoming one of the core challenges facing China's public health and long-term care systems. Impairments in activities of daily living (ADL) not only directly undermine older adults' self-care abilities but are also associated with higher healthcare utilization and mortality risks. Therefore, identifying intervenable upstream risk factors is of significant importance.Sarcopenia and obesity represent two major key phenotypes influencing physical function and health outcomes in the elderly population. Sarcopenia is characterized by a decline in skeletal muscle mass, muscle strength, and physical performance.[ 1 ], It is widely associated with adverse outcomes such as falls[ 2 , 3 ]、functional decline[ 3 ]、cardiovascular diseases[ 4 ]、depression[ 5 ]、 [ 5 ], cognitive impairment, hospitalization, and death[ 6 ];其Diagnostic criteria have been continuously refined under the promotion of guidelines such as AWGS and EWGSOP. When sarcopenia and obesity coexist in the same individual, known as "sarcopenic obesity" (SO), the two can be linked through inflammation[ 7 , 8 ]、insulin resistance[ 7 ]、Endocrinology and muscle fat infiltration[ 9 ]Pathways such as these can produce overlapping or synergistic adverse effects, thereby amplifying the risks of cardiac metabolism and functional decline. These mechanistic clues provide biological rationality for the potential link between SO and functional disorders, including ADL. Obesity is often associated with fractures.[ 10 ],cardiovascular disease[ 11 ],Respiratory function impairment[ 12 ]Abdominal obesity is associated with the onset of diseases leading to hospitalisation and disability risks, thereby increasing the incidence of ADL impairment. Korean literature has documented that abdominal obesity affects future activities of daily living.[ 13 ]Sarcopenia is also a significant contributor to ADL impairment, with muscle loss and reduced strength serving as key predictors of ADL decline.[ 14 ]Previous studies indicate a high degree of overlap between the trajectories of sarcopenia and obesity-related sarcopenia in middle-aged and elderly Chinese individuals and their activities of daily living (ADL).[ 15 ]Obesity with sarcopenia is also quite common.[ 16 ] Individuals with osteoarthritis experience impaired musculoskeletal integrity, abnormal gait patterns and functional limitations, which not only substantially increase their risk of falls but also render them more susceptible to frailty and disability.[ 17 ]It manifests as frailty and functional decline, and is associated with a significantly increased mortality rate among patients.[ 18 ] However, despite the recognition that sarcopenia may compound the dual risks of muscle loss and obesity, longitudinal studies examining the association between sarcopenia and activities of daily living (ADL) impairment among middle-aged and elderly Chinese populations using nationally representative samples remain insufficient. Consequently, this study utilises baseline and 2018 follow-up data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS) cohort to analyse the relationship between sarcopenia, obesity, sarcopenic obesity, and the occurrence of ADL disability. This provides a reference basis for the prevention and intervention of ADL disability. 2. Methods 2.1. Study Design and Population The data for this cohort study were obtained from the China Health and Retirement Longitudinal Study (CHARLS), an ongoing nationally representative cohort study. Detailed information regarding the study design and sampling methods of CHARLS has been described elsewhere [19, 20]. Briefly, at baseline (2011), 17,705 respondents from CHARLS were surveyed across 150 counties in 28 provinces in China, followed by follow-up visits every 2-3 years (2013, 2015, 2018, 2020). All respondents were interviewed by systematically trained interviewers using standardized questionnaires. We conducted a longitudinal study spanning seven years (2011-2018), using the population data from 2011 as the baseline. After excluding subjects who were diagnosed with ADL disability at baseline or lacked information during follow-up, we longitudinally monitored and observed eligible subjects until 2018. Of the initially screened 17,705 participants, those who were under 45 years old (n = 404), had missing obesity data (n = 4679), incomplete ADL disability information in 2018 (n = 2626), missing neck pain data and confirmed ADL disability in 2011 (n = 3582), and individuals with missing covariates (n = 250) were excluded. Finally, this longitudinal analysis included 6740 participants (Figure 1). This included 4514 individuals without ADL disability and 1956 individuals with new-onset ADL disability. Figure 1 illustrates the flowchart describing our study designFigure 1. 2.2. Assessment of sarcopenic obesity Obesity status was evaluated based on Body Mass Index (BMI) and waist circumference measurements. Specifically, obesity was diagnosed when BMI reached or exceeded 28 kg/m² [22] or when waist circumference was ≥85 cm for males and ≥80 cm for females[23]，Waist circumference was measured with a flexible tape measure, while height and weight were determined in an upright posture using a Seca™ 213 stadiometer (Seca Hangzhou Co., Ltd., China) and an Omron™ HN-286 scale (Kerui Technology Yangzhou Co., Ltd.), respectively The assessment of sarcopenia status was based on the 2019 consensus recommendations issued by the Asian Working Group for Sarcopenia (AWGS) [24]，which are more suitable for the Chinese population. Specifically, sarcopenia was defined as a reduction in skeletal muscle mass accompanied by either decreased physical function or reduced muscle strength. Given the absence of data on Dual-energy X-ray Absorptiometry (DXA) or Bioelectrical Impedance Analysis (BIA) in the CHARLS dataset, we employed a muscle mass equation that has demonstrated satisfactory agreement with DXA measurements in the Chinese population to calculate participants' appendicular skeletal muscle mass (ASM) [25] The skeletal muscle mass index (SMI) was calculated as follows: SMI = ASM / height². The cut-off value for low SMI was defined as the lowest 20% of SMI values stratified by gender within the study population: 7 kg/m² for males and 5.28 kg/m² for females. Muscle strength was evaluated using grip strength measured with a Yuejian™ WL-1000 dynamometer (Nantong Yuejian Physical Examination Equipment Co., Ltd.), with participants performing two measurements of grip strength for each hand in turn. According to the AWGS 2019 recommendations, low muscle strength was defined as a maximum grip strength of <28 kg for males or <18 kg for females across the four measurements. Physical function was assessed through the 5-time chair stand test and the 5-meter gait speed test, with low physical function defined as a time of ≥12 seconds on the 5-time chair stand test or a gait speed of <1.0 m/s. Diagnostic criteria for sarcopenic obesityThe diagnostic criteria for sarcopenic obesity are based on the latest expert consensus issued by the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) in 2022: sarcopenic obesity is defined as the coexistence of obesity and sarcopenia[26, 27]. 2.3. ADL Disability Activities of Daily Living (ADL) refer to the fundamental self-care abilities required for individuals to maintain basic independent living, including functional activities such as dressing, eating, bathing, toileting, mobility, and transfers. ADL disability typically indicates an individual's difficulty or reliance on assistance in one or more fundamental daily activities, serving as a key indicator for assessing functional independence and self-care capacity. ADL is often combined with higher-level instrumental activities of daily living (IADL, such as shopping, transportation, and financial management) to comprehensively reflect an individual's overall functional status[28]. ADL impairment directly reflects diminished functional independence, typically accompanied by a marked increase in the requirement for home care or professional nursing resources. Among community-dwelling and institutionalised elderly populations, limitations in ADL demonstrate a significant positive correlation with long-term care needs, serving as a crucial functional indicator for predicting chronic care requirements[29].Moreover, ADL disability has been extensively demonstrated to correlate with adverse health outcomes. A study of individuals aged ≥65 years revealed that ADL dependency was significantly associated with increased healthcare utilisation, heightened comorbidity burden, and elevated mortality risk, suggesting that ADL disability holds substantial prognostic predictive value.[29, 30]。Among elderly residents in care homes, diminished ADL capabilities are similarly closely associated with increased mortality risk, further underscoring the link between disability severity and life prognosis.[30]。 Beyond physical functional impairments, ADL limitations are also closely associated with psychological and cognitive health. Research indicates that ADL disability increases the risk of developing depressive symptoms and may mediate the relationship between depression and cognitive decline, suggesting that functional impairment significantly influences psychological and cognitive states.[31].Concurrently, limitations in Activities of Daily Living (ADL) frequently coincide with a marked decline in health-related quality of life (QoL). Studies involving critically ill patients and ICU survivors indicate that individuals with ADL impairment exhibit significantly lower quality of life across both physical and psychological dimensions compared to those who retain functional capacity.[32]。The systematic review further indicates that chronic pain and multimorbidity may accelerate declines in activities of daily living (ADL) function, whilst impaired ADL in turn heightens the risk of falls, fall-related injuries and long-term disability, thereby establishing a detrimental cycle of functional deterioration.[33]。 2.4. Determination of Covariates Based on prior research, this study controlled for potential confounding factors . [34, 35].Socio-economic demographic characteristics include age, gender (male and female), educational attainment (illiterate, primary school, secondary school, senior secondary school and above), place of residence (rural and urban), and marital status (married/cohabiting and other). Health-related factors include smoking (current/former/never smoker), alcohol consumption (frequency of drinking in the past year [none, less than once a month, more than once a month]), body mass index (BMI, continuous variable), and night-time sleep duration (continuous variable). Chronic diseases include hypertension and diabetes. Chronic disease data were derived from the questionnaire: "Have you been diagnosed by a doctor with a chronic disease? Including stroke, heart disease, and arthritis. BMI was calculated as weight (kg) divided by height (m) squared. BMI categories were defined as follows: BMI < 18.5 kg/m², 18.5 kg/m² ≤ BMI < 24 kg/m², and BMI ≥ 24 kg/m². Participants were classified as having hypertension if they self-reported a doctor-diagnosed condition, or if their systolic blood pressure (BP) was ≥140 mmHg or diastolic BP was ≥90 mmHg. Diabetes was defined as participants reporting a doctor-diagnosed condition, or having fasting blood glucose ≥126 mg/dl, non-fasting blood glucose ≥200 mg/dl, or glycated haemoglobin ≥6.5%. 2.5. Statistical Analysis In the dataset, categorical variables were described by frequency (percentage). Normally distributed continuous variables were described by mean (standard deviation), while non-normally distributed continuous variables were described by median (interquartile range). Comparisons were performed using χ² tests and analysis of variance (where applicable). Logistic regression analysis examined the prospective association between sarcopenic obesity and ADL disability, expressed as odds ratios (OR) with 95% confidence intervals (CI). To account for potential confounding factors, we employed multivariate-adjusted models. Specifically, the baseline model was an unadjusted single regression model. Model 1 adjusted for gender, age, marital status, place of residence, BMI, night-time sleep duration, smoking status, and alcohol consumption status; Model 2 further adjusted for alcohol consumption status, smoking status, sleep duration, and BMI on top of Model 1; Model 3 further adjusted for chronic disease history, including hypertension, diabetes, and stroke, on top of Model 2. Additionally, we conducted stratified analyses to assess potential interactions among various variables. Specifically, we examined interactions based on the following factors: gender, age, marital status, place of residence, BMI, nocturnal sleep duration, smoking status, alcohol consumption status, and hypertension and diabetes mellitus. Statistical analyses were performed using R version 4.5.0, with P < 0.05 considered statistically significant. 3. Results Table 1 Baseline characteristics of study participants Table 1 variable Total (n=4477) normal (n=1504) possible sarcopenia (n=841) obesity (n=1870) sarcopenic obesity (n=262) statistic p.value age 59.63 ± 8.87 56.69 ± 7.50 66.15 ± 8.30 58.27 ± 8.28 65.33 ± 8.96 310.20 <0.0001 BMI 23.87 ± 4.12 22.07 ± 2.06 19.85 ± 2.25 26.87 ± 3.54 25.66 ± 4.76 1348.88 <0.0001 WC 85.10 ± 12.93 77.64 ± 10.91 75.30 ± 9.05 94.36 ± 8.64 93.26 ± 8.62 1254.81 <0.0001 sleep 6.21 ± 1.87 6.24 ± 1.82 5.93 ± 2.13 6.32 ± 1.75 6.07 ± 2.01 8.98 <0.0001 sex 204.88 <0.0001 female 2795(62.43) 768(51.06) 470(55.89) 1350(72.19) 207(79.01) male 1682(37.57) 736(48.94) 371(44.11) 520(27.81) 55(20.99) residence_place 127.86 <0.0001 rural 3017(67.39) 1082(71.94) 666(79.19) 1109(59.30) 160(61.07) urban 1460(32.61) 422(28.06) 175(20.81) 761(40.70) 102(38.93) marry 39.42 <0.0001 married with spouse present 3697(82.58) 1255(83.44) 658(78.24) 1594(85.24) 190(72.52) Other 780(17.42) 249(16.56) 183(21.76) 276(14.76) 72(27.48) edu 133.36 <0.0001 High school or above 330( 7.37) 132( 8.78) 27( 3.21) 158( 8.45) 13( 4.96) Illiteracy 2275(50.82) 684(45.48) 540(64.21) 885(47.33) 166(63.36) Middle school 803(17.94) 311(20.68) 83( 9.87) 382(20.43) 27(10.31) Primary school 1069(23.88) 377(25.07) 191(22.71) 445(23.80) 56(21.37) age2 595.33 <0.0001 <60 2295(51.26) 1010(67.15) 155(18.43) 1058(56.58) 72(27.48) ≥60 2182(48.74) 494(32.85) 686(81.57) 812(43.42) 190(72.52) sleeptime 7.78 0.05 <7 2455(54.84) 815(54.19) 495(58.86) 997(53.32) 148(56.49) ≥7 2022(45.16) 689(45.81) 346(41.14) 873(46.68) 114(43.51) smoke 151.01 <0.0001 current smoke 1163(25.98) 514(34.18) 273(32.46) 332(17.75) 44(16.79) former 336( 7.51) 111( 7.38) 60( 7.13) 147( 7.86) 18( 6.87) never smoke 2978(66.52) 879(58.44) 508(60.40) 1391(74.39) 200(76.34) drink_freqency_last_year 48.69 <0.0001 1m 920(20.55) 373(24.80) 187(22.24) 323(17.27) 37(14.12) no 3243(72.44) 1007(66.95) 605(71.94) 1418(75.83) 213(81.30) hypertension 214.13 <0.0001 no 2582(57.67) 1052(69.95) 534(63.50) 890(47.59) 106(40.46) yes 1895(42.33) 452(30.05) 307(36.50) 980(52.41) 156(59.54) DM 82.16 <0.0001 no 3903(87.18) 1376(91.49) 769(91.44) 1547(82.73) 211(80.53) yes 574(12.82) 128( 8.51) 72( 8.56) 323(17.27) 51(19.47) obesity 2619.05 <0.0001 low weight 309( 6.90) 69( 4.59) 235(27.94) 5( 1.91) normal 2178(48.65) 1178(78.32) 561(66.71) 344(18.40) 95(36.26) obesity 651(14.54) 257(17.09) 45( 5.35) 947(50.64) 90(34.35) over weight 1339(29.91) 579(30.96) 72(27.48) heart 42.59 <0.0001 no 3889(86.87) 1355(90.09) 755(89.77) 1556(83.21) 223(85.11) yes 588(13.13) 149( 9.91) 86(10.23) 314(16.79) 39(14.89) stroke 13.40 <0.01 no 4394(98.15) 1490(99.07) 827(98.34) 1822(97.43) 255(97.33) yes 83( 1.85) 14( 0.93) 14( 1.66) 48( 2.57) 7( 2.67) arthritis 0.46 0.93 no 2526(56.42) 846(56.25) 477(56.72) 1060(56.68) 143(54.58) yes 1951(43.58) 658(43.75) 364(43.28) 810(43.32) 119(45.42) BADL 49.73 <0.0001 no 4051(90.48) 1405(93.42) 733(87.16) 1699(90.86) 214(81.68) yes 426( 9.52) 99( 6.58) 108(12.84) 171( 9.14) 48(18.32) IADL 126.58 <0.0001 no 3237(72.30) 1181(78.52) 517(61.47) 1397(74.71) 142(54.20) yes 1240(27.70) 323(21.48) 324(38.53) 473(25.29) 120(45.80) Sarcopenia 5565.66 <0.0001 no 3374(75.36) 1504(100.00) 1870(100.00) possible 399( 8.91) 193(22.95) 206(78.63) yes 704(15.72) 648(77.05) 56(21.37) sarcopenia 4477.00 <0.0001 no 3374(75.36) 1504(100.00) 1870(100.00) yes 1103(24.64) 841(100.00) 262(100.00) 3.2 Longitudinal Associations Between Obesity, Sarcopenia, Sarcopenic Obesity, and Risk of ADL Impairment Multivariate logistic regression analyses using "non-sarcopenic, non-obese" as the reference group revealed that in the fully adjusted model (Model 3), sarcopenic obesity was independently associated with IADL impairment, OR 1.90 (95% CI 1.42–2.55); Possible sarcopenia was also associated with IADL impairment, OR 1.35 (95% CI 1.10–1.66), whereas simple obesity showed no significant association (OR 1.11, 95% CI 0.93–1.32). Regarding BADL impairment, sarcopenic obesity remained significantly associated (OR 1.73, 95% CI 1.15–2.58), whereas possible sarcopenia and simple obesity did not reach statistical significance (OR 1.16, 95% CI 0.85–1.59; OR 1.19, 95% CI 0.90–1.56 respectively) （Table 2）. Table 2 presents the odds ratios (OR) and 95% confidence intervals (CI) for obesity, sarcopenia, sarcopenic obesity, and ADL disability. Data are presented as OR (95% CI). Unadjusted model: No adjustment for confounders Model 1: Adjusted for age, place of residence, educational attainment, marital status Model 2: Further adjusted for alcohol consumption, smoking status, and sleep duration based on Model 1 Model 3: Further adjusted for various chronic conditions (hypertension, diabetes) on top of Model 2. Model 4: Further adjusted for depressive symptoms on top of Model 3. Table 2 character crude model Model 1 Model 2 Model 3 95%CI P 95%CI P 95%CI P 95%CI P g~~IADL~group4 normal ref ref ref ref possible sarcopenia 2.29(1.90,2.76) <0.0001 1.34(1.09,1.65) 0.005 1.34(1.09,1.64) 0.01 1.35(1.10,1.66) 0.004 obesity 1.24(1.05,1.45) 0.01 1.17(0.99,1.38) 0.07 1.16(0.98,1.38) 0.09 1.11(0.93,1.32) 0.24 sarcopenic obesity 3.09(2.35,4.06) <0.0001 1.98(1.48,2.64) <0.0001 1.96(1.47,2.63) <0.0001 1.9(1.42,2.55) <0.0001 p for trend(character2integer) <0.0001 <0.001 0.001 0.01 g~~BADL~group4 normal ref ref ref ref possible sarcopenia 2.09(1.57,2.79) <0.0001 1.13(0.82,1.54) 0.46 1.14(0.83,1.56) 0.43 1.16(0.85,1.59) 0.36 obesity 1.43(1.10,1.85) 0.01 1.29(1.00,1.68) 0.05 1.28(0.98,1.67) 0.07 1.19(0.90,1.56) 0.22 sarcopenic obesity 3.18(2.19,4.62) <0.0001 1.83(1.23,2.72) 0.003 1.82(1.22,2.72) 0.003 1.73(1.15,2.58) 0.01 p for trend(character2integer) <0.0001 0.003 0.004 0.03 3.3 Subgroup Analysis We explored interactions in the association between obesity, sarcopenia, and sarcopenic obesity with ADL disability through subgroup analysis.（subgroups Table 3）。We found no interaction between the subgroups. BADL subgroup Table 3 character normal possible sarcopenia p obesity p sarcopenic obesity p p for trend(character2integer) p for interaction sex 0.68 male ref 1.01(0.64,1.59) 0.96 1.13(0.74,1.71) 0.58 1.35(0.58,2.89) 0.46 0.44 female ref 1.30(0.82, 2.06) 0.27 1.29(0.89, 1.92) 0.19 2.04(1.22, 3.41) 0.01 0.02 age2 0.84 ≥60 ref 1.13(0.77,1.66) 0.53 1.23(0.86,1.80) 0.26 1.68(1.03,2.72) 0.04 0.05 <60 ref 1.40(0.67,2.71) 0.34 1.17(0.76,1.81) 0.47 2.17(0.89,4.72) 0.06 0.2 sleeptime 0.38 ≥7 ref 0.80(0.49,1.27) 0.34 0.89(0.59,1.34) 0.58 1.29(0.69,2.36) 0.41 0.76 <7 ref 1.66(1.07,2.58) 0.02 1.60(1.10,2.35) 0.02 2.43(1.38,4.21) 0.002 0.003 residence_place 0.38 rural ref 1.11(0.77,1.61) 0.58 1.36(0.98,1.89) 0.07 1.73(1.02,2.86) 0.04 0.02 urban ref 1.46(0.77,2.74) 0.24 0.99(0.60,1.66) 0.97 1.86(0.92,3.69) 0.08 0.45 edu 0.42 Illiteracy ref 1.40(0.91,2.15) 0.12 1.43(0.97,2.13) 0.08 1.62(0.93,2.78) 0.09 0.07 Middle school ref 1.02(0.37, 2.61) 0.97 0.91(0.46, 1.84) 0.80 2.44(0.69, 7.57) 0.14 0.65 Primary school ref 1.03(0.52,2.00) 0.94 1.41(0.80,2.51) 0.24 2.51(1.06,5.69) 0.03 0.05 High school or above ref 0.31(0.04, 1.61) 0.20 0.50(0.15, 1.59) 0.25 2.53(0.21,18.78) 0.39 0.5 marry 0.44 married with spouse present ref 1.18(0.82,1.68) 0.37 1.18(0.87,1.61) 0.29 2.13(1.33,3.35) 0.001 0.02 Other ref 1.14(0.56, 2.34) 0.72 1.38(0.72, 2.69) 0.34 1.07(0.44, 2.57) 0.88 0.58 smoke 0.91 current smoke ref 0.93(0.51, 1.66) 0.80 1.30(0.74, 2.28) 0.36 1.72(0.58, 4.44) 0.29 0.23 never smoke ref 1.35(0.89,2.04) 0.16 1.28(0.90,1.83) 0.17 2.13(1.30,3.46) 0.002 0.02 former ref 0.77(0.27,2.14) 0.62 0.81(0.34,1.95) 0.64 0.66(0.12,2.84) 0.59 0.57 drink_freqency_last_year 0.89 no ref 1.35(0.92,2.00) 0.13 1.35(0.96,1.90) 0.09 2.07(1.28,3.30) 0.003 0.01 >1m ref 0.88(0.47,1.63) 0.68 1.03(0.59,1.78) 0.93 1.16(0.38,3.10) 0.78 0.83 <1m ref 0.69(0.14, 2.88) 0.62 0.89(0.26, 3.06) 0.85 1.39(0.10,11.37) 0.78 0.98 hypertension 0.14 yes ref 1.53(0.93,2.54) 0.10 1.34(0.88,2.09) 0.19 2.43(1.40,4.23) 0.002 0.01 no ref 1.00(0.65,1.52) 1.00 1.22(0.85,1.77) 0.28 1.09(0.51,2.15) 0.81 0.34 DM 0.23 no ref 1.13(0.80,1.58) 0.49 1.09(0.81,1.48) 0.57 1.76(1.11,2.73) 0.01 0.09 yes ref 1.19(0.45,3.12) 0.72 1.90(0.95,4.09) 0.08 1.52(0.51,4.31) 0.43 0.12 IADL subgroup character normal possible sarcopenia p obesity p sarcopenic obesity p p for trend(character2integer) p for interaction sex 0.55 male ref 1.22(0.89,1.66) 0.22 1.16(0.87,1.56) 0.31 2.00(1.10,3.60) 0.02 0.06 female ref 1.40(1.06,1.85) 0.02 1.04(0.83,1.30) 0.74 1.79(1.26,2.55) 0.001 0.16 age2 0.02 ≥60 ref 1.45(1.11,1.90) 0.01 1.34(1.02,1.75) 0.03 1.68(1.16,2.45) 0.01 0.02 <60 ref 1.19(0.79,1.78) 0.39 0.89(0.70,1.13) 0.33 2.69(1.59,4.50) <0.001 0.54 sleeptime 0.13 ≥7 ref 1.24(0.91,1.70) 0.17 0.85(0.66,1.11) 0.24 1.57(0.99,2.45) 0.05 0.96 <7 ref 1.40(1.06,1.85) 0.02 1.31(1.04,1.67) 0.02 2.07(1.39,3.07) <0.001 0.001 residence_place 0.78 rural ref 1.34(1.06,1.70) 0.02 1.09(0.88,1.34) 0.43 1.67(1.16,2.42) 0.01 0.09 urban ref 1.29(0.83,2.01) 0.25 1.05(0.76,1.46) 0.78 2.12(1.27,3.53) 0.004 0.12 edu 0.4 Illiteracy ref 1.45(1.11,1.90) 0.01 1.12(0.88,1.42) 0.35 1.69(1.16,2.46) 0.01 0.1 Middle school ref 1.44(0.73,2.76) 0.28 1.36(0.85,2.19) 0.20 3.85(1.51,9.58) 0.004 0.03 Primary school ref 1.01(0.65,1.55) 0.98 0.93(0.64,1.33) 0.68 2.02(1.07,3.77) 0.03 0.44 High school or above ref 0.59(0.14,2.01) 0.42 0.75(0.35,1.60) 0.46 0.71(0.09,3.52) 0.71 0.46 marry 0.39 married with spouse present ref 1.36(1.08,1.70) 0.01 1.02(0.84,1.24) 0.81 1.83(1.30,2.57) <0.001 0.1 Other ref 1.27(0.78, 2.08) 0.34 1.39(0.90, 2.16) 0.13 1.80(0.96, 3.40) 0.07 0.05 smoke 0.43 current smoke ref 1.17(0.81, 1.70) 0.40 1.31(0.91, 1.89) 0.14 1.46(0.71, 2.90) 0.29 0.1 never smoke ref 1.39(1.06,1.81) 0.02 1.04(0.84,1.29) 0.73 1.83(1.29,2.59) 1m ref 1.34(0.86,2.10) 0.20 1.50(1.01,2.24) 0.05 1.80(0.82,3.86) 0.14 0.03 <1m ref 2.20(0.99, 4.89) 0.05 0.92(0.46, 1.83) 0.81 2.85(0.70, 12.02) 0.14 0.63 hypertension 0.47 yes ref 1.55(1.10,2.17) 0.01 1.24(0.94,1.65) 0.13 1.88(1.24,2.84) 0.003 0.03 no ref 1.25(0.96,1.63) 0.10 1.00(0.80,1.26) 0.98 1.94(1.24,3.02) 0.003 0.2 DM 0.25 no ref 1.30(1.05,1.62) 0.02 1.01(0.84,1.22) 0.90 1.62(1.17,2.25) 0.004 0.22 yes ref 1.60(0.79,3.24) 0.19 1.84(1.08,3.21) 0.03 3.76(1.77,8.12) <0.001 0.001 4. Discussion This study analysed follow-up data from a national cohort between 2011 and 2018, revealing that: ① Compared with "normal" status, sarcopenic obesity (SO) significantly increased the subsequent risk of IADL and BADL functional limitations (IADL: adjusted effect 1.90, 95% CI 1.42–2.55; BADL: 1.73, 1.15–2.58), with an increasing trend from "normal → obese → possible sarcopenia → SO" (trend test for IADL P = 0.01; BADL P = 0.03). ② After full adjustment, simple obesity no longer showed significant associations with IADL/BADL; ③ Probable sarcopenia correlated with IADL (but not BADL) (1.35, 1.10–1.66), suggesting diminished muscle strength/physical capacity earlier impacts instrumental activities. ④ Age interacted with IADL outcomes, with SO exerting greater influence among ≥ 60-year-olds. Overall, findings underscore the central role of "sarcopenic components" rather than mere fat excess in functional decline. Our findings broadly align with prevailing trends in prior domestic and international research. A seminal cohort study reported as early as 2004 that sarcopenic obesity substantially elevates the risk of impaired daily living abilities in older adults: compared with those with sarcopenia alone, obesity alone, or normal body composition, sarcopenic obese older adults exhibited a two- to threefold increased risk of IADL disability during follow-up.[ 36 ]Recent nationwide studies in China have similarly confirmed the adverse impact of sarcopenic obesity on functional capacity in older adults: compared with non-sarcopenic obese individuals, sarcopenic obese older adults exhibit a significantly elevated risk of ADL impairment, with an OR of approximately 3.99 (95% CI: 2.50–6.09).[ 37 ]这Evidence supports the conclusion of this study that the coexistence of sarcopenia and obesity significantly impairs the ability of older adults to live independently.[ 18 ]However, findings from certain research studies do not entirely align with those of the present investigation. For instance, Cavdar et al. observed in their study of elderly outpatients in Turkey that the occurrence of sarcopenic obesity, as diagnosed according to the ESPEN/EASO criteria, did not significantly increase the risk of developing ADL or IADL impairment.[ 38 ]The discrepancy may stem from differences in study population characteristics and diagnostic criteria: Cavdar et al.'s relatively small sample size (n = 408) yielded a sarcopenic obesity prevalence of only 6.9%, and their definition of SO required stricter conditions such as BMI ≥ 30 kg/m², potentially underestimating the functional impact on moderately overweight individuals with reduced muscle mass. Concurrently, the study population comprised hospitalised elderly patients, whose overall health status and functional capacity may differ significantly from community-dwelling older adults. The higher baseline prevalence of functional limitations may have diminished the statistical power for detecting the impact of SO. Furthermore, some scholars have proposed the existence of an "obesity paradox" among frail elderly individuals, suggesting that higher BMI may offer some degree of protection against declines in certain functional indicators.[ 39 , 40 ]This phenomenon is primarily observed in individuals with mild to moderate overweight, potentially reflecting compensatory mechanisms during disease progression. However, it does not apply to those with severe obesity or concomitant sarcopenia, and its conclusions remain controversial. Overall, given the large population base and extended follow-up period of this study, the findings more accurately reflect the hazards of sarcopenic obesity among community-dwelling older adults. Our findings align with the majority of existing evidence, further underscoring the detrimental role of sarcopenic obesity in functional decline among the elderly. This warrants heightened attention within clinical and public health spheres. The mechanisms through which sarcopenic obesity increases the risk of ADL impairment in older adults may be multifaceted. Firstly, mechanical loading factors: sarcopenic obesity combines reduced skeletal muscle mass with excessive fat accumulation, readily causing biomechanical imbalance. Insufficient muscular strength impairs the elderly's ability to maintain stability and balance during daily activities such as standing, walking, and stair climbing. Concurrently, excessive body weight increases stress loads on weight-bearing structures like joints and the spine, rendering movements more laborious and heightening susceptibility to overuse injuries and pain. Under this dual burden, individuals with sarcopenic obesity experience premature fatigue and reduced exercise tolerance. Long-term, this accelerates degenerative changes in bones and joints alongside muscle function decline, ultimately heightening the risk of activity limitations and disability. Secondly, inflammatory responses and metabolic disorders: Chronic low-grade inflammation is considered a key pathway linking sarcopenic obesity to functional impairment. In an obese state, adipose tissue secretes markedly elevated levels of pro-inflammatory cytokines (such as IL-6, TNF-α, and C-reactive protein). Research indicates that inflammatory markers (e.g., high-sensitivity C-reactive protein) are consistently higher in frail obese elderly individuals compared to the general population. Persistent inflammation promotes muscle protein breakdown and inhibits myofibrillar regeneration, while simultaneously triggering metabolic abnormalities like insulin resistance. This leads to further muscle atrophy and diminished physical function.[ 41 – 44 ]In the long term, inflammation-mediated muscle wasting and metabolic dysfunction will markedly increase the likelihood of functional decline in older adults. Furthermore, cognitive and psychological factors: both sarcopenia and obesity may indirectly exacerbate ADL impairment by affecting mental and psychological health.[ 45 ]Research indicates that sarcopenia is closely associated with depressive mood and cognitive decline in older adults.[ 45 – 47 ];Obesity may also be associated with cardiovascular disease.[ 48 ]Chronic inflammation increases the risk of cognitive impairment and dementia.[ 49 ]Furthermore, individuals with sarcopenic obesity often reduce physical activity and social engagement due to physical limitations. Prolonged difficulties with activities of daily living may lead to psychological issues such as diminished self-esteem, depression, and loneliness. These psychological factors, in turn, reduce their willingness and ability to participate in daily activities, accelerating further functional decline and creating a vicious cycle. The "double blow" of SO exerts a more potent impact on function through multiple pathways: Intramuscular fat infiltration and diminished muscle fibre quality weaken muscle strength and power; The chronic low-grade inflammation-insulin resistance axis (involving hypertrophic adipose tissue and dysregulated myogenic/adipogenic factors) further inhibits myoglobin synthesis and repair; Increased weight-bearing demands coupled with reduced physical activity create a vicious cycle, accelerating declines in performing complex instrumental activities (e.g., shopping, managing finances, household chores); Intertwined with comorbidities (metabolic syndrome, musculoskeletal disorders, depression), amplifying the "temporal" disparity between early impairment in IADLs and late impairment in BADLs. Related CHARLS research also indicates that functional limitations and psychological states mutually influence each other, thereby exacerbating adverse trajectories. This study holds significant implications for public health and clinical practice. Firstly, the findings suggest that individuals with sarcopenic obesity should be prioritised as key targets for preventing functional decline in older adults. Within community and clinical settings, regular assessment mechanisms for body composition in middle-aged and elderly individuals should be established to identify high-risk individuals concurrently exhibiting sarcopenia and overweight/obesity at an early stage. For this population, comprehensive interventions should be implemented promptly, including tailored resistance exercise programmes to enhance muscle strength, alongside nutritional guidance (such as optimised protein intake and vitamin D supplementation) to improve muscle quality.[ 50 ], and implementing weight management and dietary interventions to reduce excess fat[ 50 ]Existing research indicates that early identification and intervention for sarcopenia and sarcopenic obesity may help slow the progression of activities of daily living (ADL) impairment. Consequently, healthcare practice should strengthen health management for elderly individuals with sarcopenic obesity, incorporating screening and intervention for sarcopenic obesity into routine elderly health examinations and community care programmes. From a clinical perspective, healthcare professionals should heighten vigilance regarding sarcopenic obesity. While managing chronic conditions, attention must be paid to patients' muscular and weight status, employing multidisciplinary interventions (including exercise rehabilitation, nutritional guidance, and psychological support) to enhance physical function. Such measures hold significant importance for prolonging healthy independent living in older adults and reducing care burdens. This study also has certain limitations that warrant mention. Firstly, muscle mass indicators were not measured directly via dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA), but estimated using predictive formulas based on height and weight. This may introduce errors, potentially leading to inaccurate assessments of sarcopenia. Secondly, ADL impairment outcomes were assessed via self-reported questionnaires. The absence of objective, quantitative measurements of daily functional capacity may introduce recall bias and information bias influenced by respondent subjectivity. Thirdly, due to data limitations, we were unable to incorporate several potential confounding factors, such as dietary nutrient intake, daily physical activity levels, prior history of muscle training, and cognitive function and social support. These factors may simultaneously influence both body composition and ADL capacity; their uncontrolled presence may impact the results. Fourthly, the exposure factors in this study (sarcopenia, obesity, and their combination) were assessed only at baseline, with no consideration given to changes in individual body composition or muscle strength during follow-up. Consequently, we were unable to analyse the impact of phenotypic shifts over time on ADL function. These limitations should be considered when generalising the study's conclusions. Future research could improve upon this design through more rigorous methodologies, such as employing direct measurement techniques for muscle mass and function, refining outcome measures, and incorporating additional relevant confounding variables to further validate our findings. Future research directions: Firstly, it is recommended to incorporate time-varying exposure variables into longitudinal studies to dynamically monitor the trajectories of changes in muscle mass, muscle strength, and body fat among older adults. For instance, methods such as latent class trajectory models could be employed to characterise the evolution of sarcopenic obesity status over time and its impact on declining activities of daily living (ADL) function. Such longitudinal analysis would more precisely capture the developmental process of sarcopenic obesity, thereby identifying critical intervention windows. Secondly, deeper exploration of biological mechanisms is required. Future studies should collect biological data such as inflammatory markers, muscle metabolic indicators, and hormone levels to elucidate the role of chronic inflammation and endocrine alterations in SO-induced functional impairment. This will clarify the causal chain linking sarcopenic obesity to changes in muscle mass, neuromuscular function, and the central nervous system. Finally, interventional studies or randomised controlled trials should be conducted to evaluate the efficacy of comprehensive interventions targeting populations with sarcopenic obesity. For instance, through exercise training (combining resistance training with aerobic exercise)[ 51 , 52 ]、Nutritional supplementation (increasing intake of protein, vitamin D, and omega-3 fatty acids, etc.)[ 52 – 54 ]as well as weight-loss treatments and other multi-pronged approaches[ 55 ], To observe its effects on enhancing muscle strength, improving physical function, and preventing activities of daily living (ADL) impairment in older adults. The aforementioned research will provide direct evidence for formulating effective clinical and public health strategies, thereby advancing early intervention and prevention of age-related functional decline associated with sarcopenic obesity and promoting the attainment of healthy ageing objectives. Conclusion Baseline sarcopenic obesity significantly increases the future risk of ADL disability in middle-aged and elderly individuals, with this association remaining robust after full adjustment. The independent effect of obesity is weaker and partially influenced by comorbidities, suggesting sarcopenia may not yet present a pronounced risk. Enhanced early identification and comprehensive intervention targeting sarcopenic obese populations are warranted, balancing muscle gain with fat reduction to reduce the incidence of ADL disability and disease burden.Author Contributions YZ organized and processed the data, and completed the writing of the manuscript. JJ reviewed and revised the manuscript Declarations Ethical Approval The data used in this study were from the China Health and Retirement Longitudinal Study (CHARLS). CHARLS was approved by the Ethical Review Committee of Peking University (IRB approval number: IRB00001052-11015). All participants provided written informed consent at the time of enrollment. As this study is a secondary analysis of de-identified, publicly available data, no additional ethical approval was required. Consent to Participate Not applicable. This study is based on de-identified, publicly available data from the CHARLS study. Written informed consent was obtained from all original CHARLS participants by the Peking University research team. Consent to Publish Not applicable. Funding This study was supported by the Health Commission of Hongkou District, Shanghai. （Project Number：HKGYQYXM-2026-13）The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Availability of Data and Materials The data supporting this study are from the China Health and Retirement Longitudinal Study (CHARLS), which is publicly available. The datasets can be accessed at the CHARLS official website (http://charls.pku.edu.cn) upon reasonable request and registration. Competing Interests The authors declare that they have no competing interests. References Papadopoulou, S.K., Sarcopenia: A Contemporary Health Problem among Older Adult Populations. Nutrients, 2020. 12 (5). 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Crimmins, The impact of insulin resistance and inflammation on the association between sarcopenic obesity and physical functioning. Obesity (Silver Spring), 2012. 20 (10): p. 2101-6. Hong, S.H. and K.M. Choi, Sarcopenic Obesity, Insulin Resistance, and Their Implications in Cardiovascular and Metabolic Consequences. Int J Mol Sci, 2020. 21 (2). Poggiogalle, E., et al., Sarcopenic obesity and insulin resistance: Application of novel body composition models. Nutrition, 2020. 75-76 : p. 110765. Levine, M.E. and E.M. Crimmins, Sarcopenic obesity and cognitive functioning: the mediating roles of insulin resistance and inflammation? Curr Gerontol Geriatr Res, 2012. 2012 : p. 826398. Li, Q., et al., Association between depressive symptoms and sarcopenia among middle-aged and elderly individuals in China: the mediation effect of activities of daily living (ADL) disability. BMC Psychiatry, 2024. 24 (1): p. 432. Wang, S., et al., Longitudinal association between ADL disability and depression in middle-aged and elderly: national cohort study. J Nutr Health Aging, 2025. 29 (2): p. 100450. Chen, X., et al., Effects of Virtual Reality Rehabilitation Training on Cognitive Function and Activities of Daily Living of Patients With Poststroke Cognitive Impairment: A Systematic Review and Meta-Analysis. Arch Phys Med Rehabil, 2022. 103 (7): p. 1422-1435. Piché, M.E., A. Tchernof, and J.P. Després, Obesity Phenotypes, Diabetes, and Cardiovascular Diseases. Circ Res, 2020. 126 (11): p. 1477-1500. Selman, A., et al., The Role of Obesity and Diabetes in Dementia. Int J Mol Sci, 2022. 23 (16). Singh, A., et al., Implications of Protein and Sarcopenia in the Prognosis, Treatment, and Management of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). Nutrients, 2024. 16 (5). Eglseer, D., et al., Nutritional and exercise interventions in individuals with sarcopenic obesity around retirement age: a systematic review and meta-analysis. Nutr Rev, 2023. 81 (9): p. 1077-1090. Nilsson, M.I., et al., Obesity and Metabolic Disease Impair the Anabolic Response to Protein Supplementation and Resistance Exercise: A Retrospective Analysis of a Randomized Clinical Trial with Implications for Aging, Sarcopenic Obesity, and Weight Management. Nutrients, 2024. 16 (24). Kim, Y.C., et al., Recent Advances in Nutraceuticals for the Treatment of Sarcopenic Obesity. Nutrients, 2023. 15 (17). Nederveen, J.P., M.I. Nilsson, and M.A. Tarnopolsky, Multi-ingredient supplementation for combating sarcopenia and polymorbidity. Curr Opin Clin Nutr Metab Care, 2025. 28 (6): p. 452-462. Batsis, J.A. and D.T. Villareal, Sarcopenic obesity in older adults: aetiology, epidemiology and treatment strategies. Nat Rev Endocrinol, 2018. 14 (9): p. 513-537. Additional Declarations No competing interests reported. Supplementary Files BADL.xlsx IADL.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 21 Apr, 2026 Reviews received at journal 06 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviews received at journal 31 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers invited by journal 25 Feb, 2026 Editor invited by journal 25 Feb, 2026 Editor assigned by journal 17 Feb, 2026 Submission checks completed at journal 17 Feb, 2026 First submitted to journal 17 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8899879","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":597197747,"identity":"5c49835a-b0e0-4855-84ec-4766a0b5f711","order_by":0,"name":"Yaowen Zhu","email":"","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yaowen","middleName":"","lastName":"Zhu","suffix":""},{"id":597197748,"identity":"05031ac6-92ad-4380-97b1-75c0556e88cc","order_by":1,"name":"Jinhui Jia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYHCChAMMPBIMBgyMjQ8SKmxI09Js8OBMGgl2GTAwsEk+bDtEWKX8jISHB37IWOSZSyS3VSSwHWDgb+9OwKuFsedAwsEeHoliyxmJbTcSeO4wSJw5uwGvFmb2hoQDPDwSiRtugLRIPGMwkMjFr4WNmSHh4B+oloIEg8OEtfAAbTkMs4UhIYEILRI8BxIOy4C0nHnYLJFwII2HoF/kZ+Qkf3zbU5e44Xj6w48//9nI8bf34tcCdFoCMNiQuASUgwD7AQaGH0SoGwWjYBSMgpELAAqUTk+upqqTAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jinhui","middleName":"","lastName":"Jia","suffix":""}],"badges":[],"createdAt":"2026-02-17 10:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8899879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8899879/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104168739,"identity":"d07d7ce9-aff6-4d4a-8c43-cde2d7a8c724","added_by":"auto","created_at":"2026-03-08 14:35:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45843,"visible":true,"origin":"","legend":"\u003cp\u003eThe Ethics Review Committee of Peking University approved the CHARLS study. All respondents signed the informed consent form [19]. This study followed the STROBE guidelines for enhancing observational research reporting in epidemiology[21].\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8899879/v1/b78c2c1592da6db1cea49a1b.png"},{"id":104404613,"identity":"206aa36d-b67a-4e41-9bde-b0ccbf5e3237","added_by":"auto","created_at":"2026-03-11 12:20:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1687274,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8899879/v1/5c99ff20-048d-4f93-9f67-513b20207cee.pdf"},{"id":104168740,"identity":"457fcdc6-e2d2-4d0f-992e-d22885197f82","added_by":"auto","created_at":"2026-03-08 14:35:25","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":12595,"visible":true,"origin":"","legend":"","description":"","filename":"BADL.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8899879/v1/d597821bc026ef7093481667.xlsx"},{"id":104168741,"identity":"360670d0-508d-49fd-b132-07668da74502","added_by":"auto","created_at":"2026-03-08 14:35:26","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":12553,"visible":true,"origin":"","legend":"","description":"","filename":"IADL.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8899879/v1/bd84dfdfec27baf042e78168.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Association between Sarcopenic Obesity and Impaired Activities of Daily Living among Middle-aged and Elderly Chinese: A Study Based on CHARLS","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWith the acceleration of population aging, the burden of functional limitations and disability in later life has surged rapidly, becoming one of the core challenges facing China's public health and long-term care systems. Impairments in activities of daily living (ADL) not only directly undermine older adults' self-care abilities but are also associated with higher healthcare utilization and mortality risks. Therefore, identifying intervenable upstream risk factors is of significant importance.Sarcopenia and obesity represent two major key phenotypes influencing physical function and health outcomes in the elderly population. Sarcopenia is characterized by a decline in skeletal muscle mass, muscle strength, and physical performance.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], It is widely associated with adverse outcomes such as falls[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]、functional decline[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]、cardiovascular diseases[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]、depression[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]、 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], cognitive impairment, hospitalization, and death[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e];其Diagnostic criteria have been continuously refined under the promotion of guidelines such as AWGS and EWGSOP. When sarcopenia and obesity coexist in the same individual, known as \"sarcopenic obesity\" (SO), the two can be linked through inflammation[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]、insulin resistance[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]、Endocrinology and muscle fat infiltration[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]Pathways such as these can produce overlapping or synergistic adverse effects, thereby amplifying the risks of cardiac metabolism and functional decline. These mechanistic clues provide biological rationality for the potential link between SO and functional disorders, including ADL.\u003c/p\u003e \u003cp\u003eObesity is often associated with fractures.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e],cardiovascular disease[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e],Respiratory function impairment[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]Abdominal obesity is associated with the onset of diseases leading to hospitalisation and disability risks, thereby increasing the incidence of ADL impairment. Korean literature has documented that abdominal obesity affects future activities of daily living.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]Sarcopenia is also a significant contributor to ADL impairment, with muscle loss and reduced strength serving as key predictors of ADL decline.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]Previous studies indicate a high degree of overlap between the trajectories of sarcopenia and obesity-related sarcopenia in middle-aged and elderly Chinese individuals and their activities of daily living (ADL).[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]Obesity with sarcopenia is also quite common.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Individuals with osteoarthritis experience impaired musculoskeletal integrity, abnormal gait patterns and functional limitations, which not only substantially increase their risk of falls but also render them more susceptible to frailty and disability.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]It manifests as frailty and functional decline, and is associated with a significantly increased mortality rate among patients.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHowever, despite the recognition that sarcopenia may compound the dual risks of muscle loss and obesity, longitudinal studies examining the association between sarcopenia and activities of daily living (ADL) impairment among middle-aged and elderly Chinese populations using nationally representative samples remain insufficient. Consequently, this study utilises baseline and 2018 follow-up data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS) cohort to analyse the relationship between sarcopenia, obesity, sarcopenic obesity, and the occurrence of ADL disability. This provides a reference basis for the prevention and intervention of ADL disability.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Study Design and Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data for this cohort study were obtained from the China Health and Retirement Longitudinal Study (CHARLS), an ongoing nationally representative cohort study. Detailed information regarding the study design and sampling methods of CHARLS has been described elsewhere [19, 20]. Briefly, at baseline (2011), 17,705 respondents from CHARLS were surveyed across 150 counties in 28 provinces in China, followed by follow-up visits every 2-3 years (2013, 2015, 2018, 2020). All respondents were interviewed by systematically trained interviewers using standardized questionnaires.\u003c/p\u003e\n\u003cp\u003eWe conducted a longitudinal study spanning seven years (2011-2018), using the population data from 2011 as the baseline. After excluding subjects who were diagnosed with ADL disability at baseline or lacked information during follow-up, we longitudinally monitored and observed eligible subjects until 2018.\u003c/p\u003e\n\u003cp\u003eOf the initially screened 17,705 participants, those who were under 45 years old (n = 404), had missing obesity data (n = 4679), incomplete ADL disability information in 2018 (n = 2626), missing neck pain data and confirmed ADL disability in 2011 (n = 3582), and individuals with missing covariates (n = 250) were excluded. Finally, this longitudinal analysis included 6740 participants (Figure 1). This included 4514 individuals without ADL disability and 1956 individuals with new-onset ADL disability. Figure 1 illustrates the flowchart describing our study designFigure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. \u0026nbsp;Assessment of sarcopenic obesity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObesity status was evaluated based on Body Mass Index (BMI) and waist circumference measurements. Specifically, obesity was diagnosed when BMI reached or exceeded 28 kg/m² [22] or when waist circumference was ≥85 cm for males and ≥80 cm for females[23]，Waist circumference was measured with a flexible tape measure, while height and weight were determined in an upright posture using a Seca™ 213 stadiometer (Seca Hangzhou Co., Ltd., China) and an Omron™ HN-286 scale (Kerui Technology Yangzhou Co., Ltd.), respectively\u003c/p\u003e\n\u003cp\u003eThe assessment of sarcopenia status was based on the 2019 consensus recommendations issued by the Asian Working Group for Sarcopenia (AWGS) [24]，which are more suitable for the Chinese population. Specifically, sarcopenia was defined as a reduction in skeletal muscle mass accompanied by either decreased physical function or reduced muscle strength. Given the absence of data on Dual-energy X-ray Absorptiometry (DXA) or Bioelectrical Impedance Analysis (BIA) in the CHARLS dataset, we employed a muscle mass equation that has demonstrated satisfactory agreement with DXA measurements in the Chinese population to calculate participants' appendicular skeletal muscle mass (ASM) [25] The skeletal muscle mass index (SMI) was calculated as follows: SMI = ASM / height². The cut-off value for low SMI was defined as the lowest 20% of SMI values stratified by gender within the study population: 7 kg/m² for males and 5.28 kg/m² for females. Muscle strength was evaluated using grip strength measured with a Yuejian™ WL-1000 dynamometer (Nantong Yuejian Physical Examination Equipment Co., Ltd.), with participants performing two measurements of grip strength for each hand in turn. According to the AWGS 2019 recommendations, low muscle strength was defined as a maximum grip strength of \u0026lt;28 kg for males or \u0026lt;18 kg for females across the four measurements. Physical function was assessed through the 5-time chair stand test and the 5-meter gait speed test, with low physical function defined as a time of ≥12 seconds on the 5-time chair stand test or a gait speed of \u0026lt;1.0 m/s. Diagnostic criteria for sarcopenic obesityThe diagnostic criteria for sarcopenic obesity are based on the latest expert consensus issued by the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) in 2022: sarcopenic obesity is defined as the coexistence of obesity and sarcopenia[26, 27].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. ADL Disability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eActivities of Daily Living (ADL) refer to the fundamental self-care abilities required for individuals to maintain basic independent living, including functional activities such as dressing, eating, bathing, toileting, mobility, and transfers. ADL disability typically indicates an individual's difficulty or reliance on assistance in one or more fundamental daily activities, serving as a key indicator for assessing functional independence and self-care capacity. ADL is often combined with higher-level instrumental activities of daily living (IADL, such as shopping, transportation, and financial management) to comprehensively reflect an individual's overall functional status[28].\u003c/p\u003e\n\u003cp\u003eADL impairment directly reflects diminished functional independence, typically accompanied by a marked increase in the requirement for home care or professional nursing resources. Among community-dwelling and institutionalised elderly populations, limitations in ADL demonstrate a significant positive correlation with long-term care needs, serving as a crucial functional indicator for predicting chronic care requirements[29].Moreover, ADL disability has been extensively demonstrated to correlate with adverse health outcomes. A study of individuals aged ≥65 years revealed that ADL dependency was significantly associated with increased healthcare utilisation, heightened comorbidity burden, and elevated mortality risk, suggesting that ADL disability holds substantial prognostic predictive value.[29, 30]。Among elderly residents in care homes, diminished ADL capabilities are similarly closely associated with increased mortality risk, further underscoring the link between disability severity and life prognosis.[30]。\u003c/p\u003e\n\u003cp\u003eBeyond physical functional impairments, ADL limitations are also closely associated with psychological and cognitive health. Research indicates that ADL disability increases the risk of developing depressive symptoms and may mediate the relationship between depression and cognitive decline, suggesting that functional impairment significantly influences psychological and cognitive states.[31].Concurrently, limitations in Activities of Daily Living (ADL) frequently coincide with a marked decline in health-related quality of life (QoL). Studies involving critically ill patients and ICU survivors indicate that individuals with ADL impairment exhibit significantly lower quality of life across both physical and psychological dimensions compared to those who retain functional capacity.[32]。The systematic review further indicates that chronic pain and multimorbidity may accelerate declines in activities of daily living (ADL) function, whilst impaired ADL in turn heightens the risk of falls, fall-related injuries and long-term disability, thereby establishing a detrimental cycle of functional deterioration.[33]。\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Determination of Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on prior research, this study controlled for potential confounding factors\u003cstrong\u003e.\u003c/strong\u003e[34, 35].Socio-economic demographic characteristics include age, gender (male and female), educational attainment (illiterate, primary school, secondary school, senior secondary school and above), place of residence (rural and urban), and marital status (married/cohabiting and other).\u003c/p\u003e\n\u003cp\u003eHealth-related factors include smoking (current/former/never smoker), alcohol consumption (frequency of drinking in the past year [none, less than once a month, more than once a month]), body mass index (BMI, continuous variable), and night-time sleep duration (continuous variable). Chronic diseases include hypertension and diabetes. Chronic disease data were derived from the questionnaire: \"Have you been diagnosed by a doctor with a chronic disease? Including stroke, heart disease, and arthritis.\u003c/p\u003e\n\u003cp\u003eBMI was calculated as weight (kg) divided by height (m) squared. BMI categories were defined as follows: BMI \u0026lt; 18.5 kg/m², 18.5 kg/m² ≤ BMI \u0026lt; 24 kg/m², and BMI ≥ 24 kg/m². Participants were classified as having hypertension if they self-reported a doctor-diagnosed condition, or if their systolic blood pressure (BP) was ≥140 mmHg or diastolic BP was ≥90 mmHg. Diabetes was defined as participants reporting a doctor-diagnosed condition, or having fasting blood glucose ≥126 mg/dl, non-fasting blood glucose ≥200 mg/dl, or glycated haemoglobin ≥6.5%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the dataset, categorical variables were described by frequency (percentage). Normally distributed continuous variables were described by mean (standard deviation), while non-normally distributed continuous variables were described by median (interquartile range). Comparisons were performed using χ² tests and analysis of variance (where applicable).\u003c/p\u003e\n\u003cp\u003eLogistic regression analysis examined the prospective association between sarcopenic obesity and ADL disability, expressed as odds ratios (OR) with 95% confidence intervals (CI). To account for potential confounding factors, we employed multivariate-adjusted models. Specifically, the baseline model was an unadjusted single regression model. Model 1 adjusted for gender, age, marital status, place of residence, BMI, night-time sleep duration, smoking status, and alcohol consumption status; Model 2 further adjusted for alcohol consumption status, smoking status, sleep duration, and BMI on top of Model 1; Model 3 further adjusted for chronic disease history, including hypertension, diabetes, and stroke, on top of Model 2.\u003c/p\u003e\n\u003cp\u003eAdditionally, we conducted stratified analyses to assess potential interactions among various variables. Specifically, we examined interactions based on the following factors: gender, age, marital status, place of residence, BMI, nocturnal sleep duration, smoking status, alcohol consumption status, and hypertension and diabetes mellitus. Statistical analyses were performed using R version 4.5.0, with P \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Baseline characteristics of study participants\u003c/strong\u003eTable 1\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003evariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003cbr\u003e\u0026nbsp;(n=4477)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003enormal\u003cbr\u003e\u0026nbsp;(n=1504)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e\u003cstrong\u003epossible sarcopenia\u003cbr\u003e\u0026nbsp;(n=841)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eobesity\u003cbr\u003e\u0026nbsp;(n=1870)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esarcopenic obesity\u003cbr\u003e\u0026nbsp;(n=262)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003estatistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep.value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e59.63 \u0026plusmn; 8.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e56.69 \u0026plusmn; 7.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e66.15 \u0026plusmn; 8.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e58.27 \u0026plusmn; 8.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e65.33 \u0026plusmn; 8.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e310.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e23.87 \u0026plusmn; 4.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e22.07 \u0026plusmn; 2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e19.85 \u0026plusmn; 2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e26.87 \u0026plusmn; 3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e25.66 \u0026plusmn; 4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e1348.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e85.10 \u0026plusmn; 12.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e77.64 \u0026plusmn; 10.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e75.30 \u0026plusmn; 9.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e94.36 \u0026plusmn; 8.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e93.26 \u0026plusmn; 8.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e1254.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esleep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e6.21 \u0026plusmn; 1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e6.24 \u0026plusmn; 1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e5.93 \u0026plusmn; 2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e6.32 \u0026plusmn; 1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e6.07 \u0026plusmn; 2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e8.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e204.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2795(62.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e768(51.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e470(55.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1350(72.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e207(79.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1682(37.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e736(48.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e371(44.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e520(27.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e55(20.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eresidence_place\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e127.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3017(67.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1082(71.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e666(79.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1109(59.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e160(61.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1460(32.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e422(28.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e175(20.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e761(40.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e102(38.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emarry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e39.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; married with spouse present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3697(82.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1255(83.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e658(78.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1594(85.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e190(72.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e780(17.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e249(16.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e183(21.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e276(14.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e72(27.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eedu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e133.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; High school or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e330( 7.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e132( 8.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e27( 3.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e158( 8.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e13( 4.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Illiteracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2275(50.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e684(45.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e540(64.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e885(47.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e166(63.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Middle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e803(17.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e311(20.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e83( 9.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e382(20.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e27(10.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1069(23.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e377(25.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e191(22.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e445(23.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e56(21.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eage2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e595.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2295(51.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1010(67.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e155(18.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1058(56.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e72(27.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2182(48.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e494(32.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e686(81.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e812(43.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e190(72.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esleeptime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e7.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2455(54.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e815(54.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e495(58.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e997(53.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e148(56.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2022(45.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e689(45.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e346(41.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e873(46.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e114(43.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esmoke\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e151.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; current smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1163(25.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e514(34.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e273(32.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e332(17.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e44(16.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e336( 7.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e111( 7.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e60( 7.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e147( 7.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e18( 6.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; never smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2978(66.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e879(58.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e508(60.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1391(74.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e200(76.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003edrink_freqency_last_year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e48.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e314( 7.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e124( 8.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e49( 5.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e129( 6.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e12( 4.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026gt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e920(20.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e373(24.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e187(22.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e323(17.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e37(14.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3243(72.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1007(66.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e605(71.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1418(75.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e213(81.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ehypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e214.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2582(57.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1052(69.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e534(63.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e890(47.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e106(40.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1895(42.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e452(30.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e307(36.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e980(52.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e156(59.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e82.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3903(87.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1376(91.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e769(91.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1547(82.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e211(80.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e574(12.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e128( 8.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e72( 8.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e323(17.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e51(19.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eobesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e2619.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; low weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e309( 6.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e69( 4.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e235(27.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e5( 1.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2178(48.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1178(78.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e561(66.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e344(18.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e95(36.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e651(14.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e257(17.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e45( 5.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e947(50.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e90(34.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; over weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1339(29.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e579(30.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e72(27.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eheart\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e42.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3889(86.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1355(90.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e755(89.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1556(83.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e223(85.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e588(13.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e149( 9.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e86(10.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e314(16.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e39(14.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003estroke\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e13.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e4394(98.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1490(99.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e827(98.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1822(97.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e255(97.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e83( 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e14( 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e14( 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e48( 2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e7( 2.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003earthritis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e2526(56.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e846(56.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e477(56.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1060(56.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e143(54.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1951(43.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e658(43.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e364(43.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e810(43.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e119(45.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBADL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e49.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e4051(90.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1405(93.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e733(87.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1699(90.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e214(81.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e426( 9.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e99( 6.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e108(12.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e171( 9.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e48(18.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIADL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e126.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3237(72.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1181(78.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e517(61.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1397(74.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e142(54.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1240(27.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e323(21.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e324(38.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e473(25.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e120(45.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e5565.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3374(75.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1504(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1870(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; possible\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e399( 8.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e193(22.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e206(78.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e704(15.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e648(77.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e56(21.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esarcopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e4477.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e3374(75.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1504(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e1870(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.9586%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e1103(24.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.8402%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e841(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6976%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.699%;\"\u003e\n \u003cp\u003e262(100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.13267%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Longitudinal Associations Between Obesity, Sarcopenia, Sarcopenic Obesity, and Risk of ADL Impairment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression analyses using \u0026quot;non-sarcopenic, non-obese\u0026quot; as the reference group revealed that in the fully adjusted model (Model 3), sarcopenic obesity was independently associated with IADL impairment, OR 1.90 (95% CI 1.42\u0026ndash;2.55); Possible sarcopenia was also associated with IADL impairment, OR 1.35 (95% CI 1.10\u0026ndash;1.66), whereas simple obesity showed no significant association (OR 1.11, 95% CI 0.93\u0026ndash;1.32).\u003c/p\u003e\n\u003cp\u003eRegarding BADL impairment, sarcopenic obesity remained significantly associated (OR 1.73, 95% CI 1.15\u0026ndash;2.58), whereas possible sarcopenia and simple obesity did not reach statistical significance (OR 1.16, 95% CI 0.85\u0026ndash;1.59; OR 1.19, 95% CI 0.90\u0026ndash;1.56 respectively)\u0026nbsp;（Table 2）.\u003c/p\u003e\n\u003cp\u003eTable 2 presents the odds ratios (OR) and 95% confidence intervals (CI) for obesity, sarcopenia, sarcopenic obesity, and ADL disability. Data are presented as OR (95% CI).\u003c/p\u003e\n\u003cp\u003eUnadjusted model: No adjustment for confounders\u003c/p\u003e\n\u003cp\u003eModel 1: Adjusted for age, place of residence, educational attainment, marital status\u003c/p\u003e\n\u003cp\u003eModel 2: Further adjusted for alcohol consumption, smoking status, and sleep duration based on Model 1\u003c/p\u003e\n\u003cp\u003eModel 3: Further adjusted for various chronic conditions (hypertension, diabetes) on top of Model 2.\u003c/p\u003e\n\u003cp\u003eModel 4: Further adjusted for depressive symptoms on top of Model 3.\u003c/p\u003e\n\u003cp\u003eTable 2\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003echaracter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecrude model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eg~~IADL~group4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; possible sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e2.29(1.90,2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.34(1.09,1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.34(1.09,1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.35(1.10,1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.24(1.05,1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.17(0.99,1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.16(0.98,1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.11(0.93,1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; sarcopenic obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e3.09(2.35,4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.98(1.48,2.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.96(1.47,2.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.9(1.42,2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ep for trend(character2integer)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eg~~BADL~group4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; possible sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e2.09(1.57,2.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.13(0.82,1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.14(0.83,1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.16(0.85,1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.43(1.10,1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.29(1.00,1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.28(0.98,1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.19(0.90,1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; sarcopenic obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e3.18(2.19,4.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.83(1.23,2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.82(1.22,2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.73(1.15,2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ep for trend(character2integer)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Subgroup Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe explored interactions in the association between obesity, sarcopenia, and sarcopenic obesity with ADL disability through subgroup analysis.（subgroups Table 3）。We found no interaction between the subgroups.\u003c/p\u003e\n\u003cp\u003eBADL subgroup Table 3\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003echaracter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003enormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003epossible sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eobesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003esarcopenic obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003ep for trend(character2integer)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003ep for interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.01(0.64,1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.13(0.74,1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.35(0.58,2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.30(0.82, 2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.29(0.89, 1.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.04(1.22, 3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eage2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.13(0.77,1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.23(0.86,1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.68(1.03,2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.40(0.67,2.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.17(0.76,1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.17(0.89,4.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esleeptime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.80(0.49,1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.89(0.59,1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.29(0.69,2.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.66(1.07,2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.60(1.10,2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.43(1.38,4.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eresidence_place\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.11(0.77,1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.36(0.98,1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.73(1.02,2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.46(0.77,2.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.99(0.60,1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.86(0.92,3.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eedu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Illiteracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.40(0.91,2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.43(0.97,2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.62(0.93,2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Middle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.02(0.37, 2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.91(0.46, 1.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.44(0.69, 7.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.03(0.52,2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.41(0.80,2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.51(1.06,5.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; High school or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.31(0.04, 1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.50(0.15, 1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.53(0.21,18.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003emarry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; married with spouse present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.18(0.82,1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.18(0.87,1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.13(1.33,3.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.14(0.56, 2.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.38(0.72, 2.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.07(0.44, 2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; current smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.93(0.51, 1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.30(0.74, 2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.72(0.58, 4.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; never smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.35(0.89,2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.28(0.90,1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.13(1.30,3.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.77(0.27,2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.81(0.34,1.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e0.66(0.12,2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003edrink_freqency_last_year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.35(0.92,2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.35(0.96,1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.07(1.28,3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026gt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e0.88(0.47,1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.03(0.59,1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.16(0.38,3.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.69(0.14, 2.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.89(0.26, 3.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;1.39(0.10,11.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003ehypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.53(0.93,2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.34(0.88,2.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e2.43(1.40,4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.00(0.65,1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.22(0.85,1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.09(0.51,2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.13(0.80,1.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.09(0.81,1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.76(1.11,2.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e1.19(0.45,3.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.90(0.95,4.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.52(0.51,4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIADL subgroup\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003echaracter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003enormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003epossible sarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003eobesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003esarcopenic obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ep for trend(character2integer)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003ep for interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.22(0.89,1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.16(0.87,1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.00(1.10,3.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.40(1.06,1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.04(0.83,1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.79(1.26,2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eage2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.45(1.11,1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.34(1.02,1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.68(1.16,2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.19(0.79,1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.89(0.70,1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.69(1.59,4.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esleeptime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.24(0.91,1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.85(0.66,1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.57(0.99,2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.40(1.06,1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.31(1.04,1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.07(1.39,3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eresidence_place\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.34(1.06,1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.09(0.88,1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.67(1.16,2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.29(0.83,2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.05(0.76,1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.12(1.27,3.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eedu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Illiteracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.45(1.11,1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.12(0.88,1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.69(1.16,2.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Middle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.44(0.73,2.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.36(0.85,2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e3.85(1.51,9.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.01(0.65,1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.93(0.64,1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e2.02(1.07,3.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; High school or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0.59(0.14,2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.75(0.35,1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.71(0.09,3.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003emarry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; married with spouse present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.36(1.08,1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.02(0.84,1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.83(1.30,2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.27(0.78, 2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.39(0.90, 2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.80(0.96, 3.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003esmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; current smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.17(0.81, 1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.31(0.91, 1.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.46(0.71, 2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; never smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.39(1.06,1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.04(0.84,1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.83(1.29,2.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.33(0.62, 2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.87(0.46, 1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e3.31(1.01,11.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003edrink_freqency_last_year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.24(0.97,1.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e0.99(0.81,1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.68(1.20,2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026gt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.34(0.86,2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.50(1.01,2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.80(0.82,3.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt;1m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.20(0.99, \u0026nbsp; \u0026nbsp; 4.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.92(0.46, \u0026nbsp; \u0026nbsp; 1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.85(0.70, 12.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003ehypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.55(1.10,2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.24(0.94,1.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.88(1.24,2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.25(0.96,1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.00(0.80,1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.94(1.24,3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.30(1.05,1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.01(0.84,1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.62(1.17,2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e1.60(0.79,3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e1.84(1.08,3.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e3.76(1.77,8.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study analysed follow-up data from a national cohort between 2011 and 2018, revealing that:\u003c/p\u003e \u003cp\u003e① Compared with \"normal\" status, sarcopenic obesity (SO) significantly increased the subsequent risk of IADL and BADL functional limitations (IADL: adjusted effect 1.90, 95% CI 1.42\u0026ndash;2.55; BADL: 1.73, 1.15\u0026ndash;2.58), with an increasing trend from \"normal \u0026rarr; obese \u0026rarr; possible sarcopenia \u0026rarr; SO\" (trend test for IADL P\u0026thinsp;=\u0026thinsp;0.01; BADL P\u0026thinsp;=\u0026thinsp;0.03). ② After full adjustment, simple obesity no longer showed significant associations with IADL/BADL; ③ Probable sarcopenia correlated with IADL (but not BADL) (1.35, 1.10\u0026ndash;1.66), suggesting diminished muscle strength/physical capacity earlier impacts instrumental activities. ④ Age interacted with IADL outcomes, with SO exerting greater influence among \u0026ge;\u0026thinsp;60-year-olds. Overall, findings underscore the central role of \"sarcopenic components\" rather than mere fat excess in functional decline.\u003c/p\u003e \u003cp\u003eOur findings broadly align with prevailing trends in prior domestic and international research. A seminal cohort study reported as early as 2004 that sarcopenic obesity substantially elevates the risk of impaired daily living abilities in older adults: compared with those with sarcopenia alone, obesity alone, or normal body composition, sarcopenic obese older adults exhibited a two- to threefold increased risk of IADL disability during follow-up.[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]Recent nationwide studies in China have similarly confirmed the adverse impact of sarcopenic obesity on functional capacity in older adults: compared with non-sarcopenic obese individuals, sarcopenic obese older adults exhibit a significantly elevated risk of ADL impairment, with an OR of approximately 3.99 (95% CI: 2.50\u0026ndash;6.09).[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]这Evidence supports the conclusion of this study that the coexistence of sarcopenia and obesity significantly impairs the ability of older adults to live independently.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]However, findings from certain research studies do not entirely align with those of the present investigation. For instance, Cavdar et al. observed in their study of elderly outpatients in Turkey that the occurrence of sarcopenic obesity, as diagnosed according to the ESPEN/EASO criteria, did not significantly increase the risk of developing ADL or IADL impairment.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]The discrepancy may stem from differences in study population characteristics and diagnostic criteria: Cavdar et al.'s relatively small sample size (n\u0026thinsp;=\u0026thinsp;408) yielded a sarcopenic obesity prevalence of only 6.9%, and their definition of SO required stricter conditions such as BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;, potentially underestimating the functional impact on moderately overweight individuals with reduced muscle mass. Concurrently, the study population comprised hospitalised elderly patients, whose overall health status and functional capacity may differ significantly from community-dwelling older adults. The higher baseline prevalence of functional limitations may have diminished the statistical power for detecting the impact of SO. Furthermore, some scholars have proposed the existence of an \"obesity paradox\" among frail elderly individuals, suggesting that higher BMI may offer some degree of protection against declines in certain functional indicators.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]This phenomenon is primarily observed in individuals with mild to moderate overweight, potentially reflecting compensatory mechanisms during disease progression. However, it does not apply to those with severe obesity or concomitant sarcopenia, and its conclusions remain controversial. Overall, given the large population base and extended follow-up period of this study, the findings more accurately reflect the hazards of sarcopenic obesity among community-dwelling older adults. Our findings align with the majority of existing evidence, further underscoring the detrimental role of sarcopenic obesity in functional decline among the elderly. This warrants heightened attention within clinical and public health spheres.\u003c/p\u003e \u003cp\u003eThe mechanisms through which sarcopenic obesity increases the risk of ADL impairment in older adults may be multifaceted. Firstly, mechanical loading factors: sarcopenic obesity combines reduced skeletal muscle mass with excessive fat accumulation, readily causing biomechanical imbalance. Insufficient muscular strength impairs the elderly's ability to maintain stability and balance during daily activities such as standing, walking, and stair climbing. Concurrently, excessive body weight increases stress loads on weight-bearing structures like joints and the spine, rendering movements more laborious and heightening susceptibility to overuse injuries and pain. Under this dual burden, individuals with sarcopenic obesity experience premature fatigue and reduced exercise tolerance. Long-term, this accelerates degenerative changes in bones and joints alongside muscle function decline, ultimately heightening the risk of activity limitations and disability. Secondly, inflammatory responses and metabolic disorders: Chronic low-grade inflammation is considered a key pathway linking sarcopenic obesity to functional impairment. In an obese state, adipose tissue secretes markedly elevated levels of pro-inflammatory cytokines (such as IL-6, TNF-α, and C-reactive protein). Research indicates that inflammatory markers (e.g., high-sensitivity C-reactive protein) are consistently higher in frail obese elderly individuals compared to the general population. Persistent inflammation promotes muscle protein breakdown and inhibits myofibrillar regeneration, while simultaneously triggering metabolic abnormalities like insulin resistance. This leads to further muscle atrophy and diminished physical function.[\u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]In the long term, inflammation-mediated muscle wasting and metabolic dysfunction will markedly increase the likelihood of functional decline in older adults. Furthermore, cognitive and psychological factors: both sarcopenia and obesity may indirectly exacerbate ADL impairment by affecting mental and psychological health.[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]Research indicates that sarcopenia is closely associated with depressive mood and cognitive decline in older adults.[\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e];Obesity may also be associated with cardiovascular disease.[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]Chronic inflammation increases the risk of cognitive impairment and dementia.[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]Furthermore, individuals with sarcopenic obesity often reduce physical activity and social engagement due to physical limitations. Prolonged difficulties with activities of daily living may lead to psychological issues such as diminished self-esteem, depression, and loneliness. These psychological factors, in turn, reduce their willingness and ability to participate in daily activities, accelerating further functional decline and creating a vicious cycle.\u003c/p\u003e \u003cp\u003eThe \"double blow\" of SO exerts a more potent impact on function through multiple pathways:\u003c/p\u003e \u003cp\u003eIntramuscular fat infiltration and diminished muscle fibre quality weaken muscle strength and power;\u003c/p\u003e \u003cp\u003eThe chronic low-grade inflammation-insulin resistance axis (involving hypertrophic adipose tissue and dysregulated myogenic/adipogenic factors) further inhibits myoglobin synthesis and repair;\u003c/p\u003e \u003cp\u003eIncreased weight-bearing demands coupled with reduced physical activity create a vicious cycle, accelerating declines in performing complex instrumental activities (e.g., shopping, managing finances, household chores);\u003c/p\u003e \u003cp\u003eIntertwined with comorbidities (metabolic syndrome, musculoskeletal disorders, depression), amplifying the \"temporal\" disparity between early impairment in IADLs and late impairment in BADLs. Related CHARLS research also indicates that functional limitations and psychological states mutually influence each other, thereby exacerbating adverse trajectories.\u003c/p\u003e \u003cp\u003eThis study holds significant implications for public health and clinical practice. Firstly, the findings suggest that individuals with sarcopenic obesity should be prioritised as key targets for preventing functional decline in older adults. Within community and clinical settings, regular assessment mechanisms for body composition in middle-aged and elderly individuals should be established to identify high-risk individuals concurrently exhibiting sarcopenia and overweight/obesity at an early stage. For this population, comprehensive interventions should be implemented promptly, including tailored resistance exercise programmes to enhance muscle strength, alongside nutritional guidance (such as optimised protein intake and vitamin D supplementation) to improve muscle quality.[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], and implementing weight management and dietary interventions to reduce excess fat[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]Existing research indicates that early identification and intervention for sarcopenia and sarcopenic obesity may help slow the progression of activities of daily living (ADL) impairment. Consequently, healthcare practice should strengthen health management for elderly individuals with sarcopenic obesity, incorporating screening and intervention for sarcopenic obesity into routine elderly health examinations and community care programmes. From a clinical perspective, healthcare professionals should heighten vigilance regarding sarcopenic obesity. While managing chronic conditions, attention must be paid to patients' muscular and weight status, employing multidisciplinary interventions (including exercise rehabilitation, nutritional guidance, and psychological support) to enhance physical function. Such measures hold significant importance for prolonging healthy independent living in older adults and reducing care burdens.\u003c/p\u003e \u003cp\u003eThis study also has certain limitations that warrant mention. Firstly, muscle mass indicators were not measured directly via dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA), but estimated using predictive formulas based on height and weight. This may introduce errors, potentially leading to inaccurate assessments of sarcopenia. Secondly, ADL impairment outcomes were assessed via self-reported questionnaires. The absence of objective, quantitative measurements of daily functional capacity may introduce recall bias and information bias influenced by respondent subjectivity. Thirdly, due to data limitations, we were unable to incorporate several potential confounding factors, such as dietary nutrient intake, daily physical activity levels, prior history of muscle training, and cognitive function and social support. These factors may simultaneously influence both body composition and ADL capacity; their uncontrolled presence may impact the results. Fourthly, the exposure factors in this study (sarcopenia, obesity, and their combination) were assessed only at baseline, with no consideration given to changes in individual body composition or muscle strength during follow-up. Consequently, we were unable to analyse the impact of phenotypic shifts over time on ADL function. These limitations should be considered when generalising the study's conclusions. Future research could improve upon this design through more rigorous methodologies, such as employing direct measurement techniques for muscle mass and function, refining outcome measures, and incorporating additional relevant confounding variables to further validate our findings.\u003c/p\u003e \u003cp\u003eFuture research directions: Firstly, it is recommended to incorporate time-varying exposure variables into longitudinal studies to dynamically monitor the trajectories of changes in muscle mass, muscle strength, and body fat among older adults. For instance, methods such as latent class trajectory models could be employed to characterise the evolution of sarcopenic obesity status over time and its impact on declining activities of daily living (ADL) function. Such longitudinal analysis would more precisely capture the developmental process of sarcopenic obesity, thereby identifying critical intervention windows. Secondly, deeper exploration of biological mechanisms is required. Future studies should collect biological data such as inflammatory markers, muscle metabolic indicators, and hormone levels to elucidate the role of chronic inflammation and endocrine alterations in SO-induced functional impairment. This will clarify the causal chain linking sarcopenic obesity to changes in muscle mass, neuromuscular function, and the central nervous system. Finally, interventional studies or randomised controlled trials should be conducted to evaluate the efficacy of comprehensive interventions targeting populations with sarcopenic obesity. For instance, through exercise training (combining resistance training with aerobic exercise)[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]、Nutritional supplementation (increasing intake of protein, vitamin D, and omega-3 fatty acids, etc.)[\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]as well as weight-loss treatments and other multi-pronged approaches[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], To observe its effects on enhancing muscle strength, improving physical function, and preventing activities of daily living (ADL) impairment in older adults. The aforementioned research will provide direct evidence for formulating effective clinical and public health strategies, thereby advancing early intervention and prevention of age-related functional decline associated with sarcopenic obesity and promoting the attainment of healthy ageing objectives.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBaseline sarcopenic obesity significantly increases the future risk of ADL disability in middle-aged and elderly individuals, with this association remaining robust after full adjustment. The independent effect of obesity is weaker and partially influenced by comorbidities, suggesting sarcopenia may not yet present a pronounced risk. Enhanced early identification and comprehensive intervention targeting sarcopenic obese populations are warranted, balancing muscle gain with fat reduction to reduce the incidence of ADL disability and disease burden.Author Contributions\u003c/p\u003e\n\u003cp\u003eYZ organized and processed the data, and completed the writing of the manuscript. JJ reviewed and revised the manuscript\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study were from the China Health and Retirement Longitudinal Study (CHARLS). CHARLS was approved by the Ethical Review Committee of Peking University (IRB approval number: IRB00001052-11015). All participants provided written informed consent at the time of enrollment. As this study is a secondary analysis of de-identified, publicly available data, no additional ethical approval was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study is based on de-identified, publicly available data from the CHARLS study. Written informed consent was obtained from all original CHARLS participants by the Peking University research team.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Health Commission of Hongkou District, Shanghai. （Project Number：HKGYQYXM-2026-13）The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study are from the China Health and Retirement Longitudinal Study (CHARLS), which is publicly available. The datasets can be accessed at the CHARLS official website (http://charls.pku.edu.cn) upon reasonable request and registration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePapadopoulou, S.K., \u003cem\u003eSarcopenia: A Contemporary Health Problem among Older Adult Populations.\u003c/em\u003e Nutrients, 2020. \u003cstrong\u003e12\u003c/strong\u003e(5).\u003c/li\u003e\n\u003cli\u003eLarsson, L., et al., \u003cem\u003eSarcopenia: Aging-Related Loss of Muscle Mass and Function.\u003c/em\u003e Physiol Rev, 2019. \u003cstrong\u003e99\u003c/strong\u003e(1): p. 427-511.\u003c/li\u003e\n\u003cli\u003eCruz-Jentoft, A.J. and A.A. 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Nilsson, and M.A. Tarnopolsky, \u003cem\u003eMulti-ingredient supplementation for combating sarcopenia and polymorbidity.\u003c/em\u003e Curr Opin Clin Nutr Metab Care, 2025. \u003cstrong\u003e28\u003c/strong\u003e(6): p. 452-462.\u003c/li\u003e\n\u003cli\u003eBatsis, J.A. and D.T. Villareal, \u003cem\u003eSarcopenic obesity in older adults: aetiology, epidemiology and treatment strategies.\u003c/em\u003e Nat Rev Endocrinol, 2018. \u003cstrong\u003e14\u003c/strong\u003e(9): p. 513-537.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8899879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8899879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the association between sarcopenic obesity (SO) and impairments in basic activities of daily living (BADL) and instrumental activities of daily living (IADL) among middle-aged and elderly individuals.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData were derived from the China Health and Retirement Longitudinal Study (CHARLS), with a final sample of 4,477 participants. Participants were categorized into four exposure groups: normal (no sarcopenia or obesity, n\u0026thinsp;=\u0026thinsp;1,504), possible sarcopenia \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:n=841\\)\u003c/span\u003e\u003c/span\u003e, obesity alone \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:n=\\text{1,870}\\)\u003c/span\u003e\u003c/span\u003e, and sarcopenic obesity \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:SO,n=262\\)\u003c/span\u003e\u003c/span\u003e. Using BADL/IADL impairment as the outcome, multivariable logistic regression with stepwise adjustment across multiple models was employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBaseline prevalence of BADL/IADL impairment showed a gradient increase across the four groups, with the highest rates observed in the SO group (18.32% for BADL, 45.80% for IADL). In the fully adjusted model, SO was significantly associated with both IADL impairment (OR\u0026thinsp;=\u0026thinsp;1.90, 95% CI: 1.42\u0026ndash;2.55) and BADL impairment (OR\u0026thinsp;=\u0026thinsp;1.73, 95% CI: 1.15\u0026ndash;2.58). No significant associations were found between obesity alone and IADL/BADL impairment. Possible sarcopenia was positively associated with IADL impairment (OR\u0026thinsp;=\u0026thinsp;1.35, 95% CI: 1.10\u0026ndash;1.66).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSarcopenia-related exposures, particularly sarcopenic obesity, are significantly associated with ADL impairment. These findings suggest that both muscle mass/strength and body fat management should be prioritized in the prevention and control of functional decline among the elderly.\u003c/p\u003e","manuscriptTitle":"The Association between Sarcopenic Obesity and Impaired Activities of Daily Living among Middle-aged and Elderly Chinese: A Study Based on CHARLS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:35:20","doi":"10.21203/rs.3.rs-8899879/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-21T18:27:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T21:28:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173492595415049216038303298960647322332","date":"2026-04-01T19:19:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-01T00:29:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172327432184911310173463792391876869787","date":"2026-03-27T12:42:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-25T22:28:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-25T10:00:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-18T04:27:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-18T04:24:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-17T09:51:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b621ad36-87d3-4388-aced-c88ede067361","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":63549016,"name":"Health sciences/Diseases"},{"id":63549017,"name":"Health sciences/Health care"},{"id":63549018,"name":"Health sciences/Medical research"},{"id":63549019,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-21T18:39:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:35:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8899879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8899879","identity":"rs-8899879","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}