{"paper_id":"3b84708d-0b5e-4bb6-bc85-67b0e7da5ead","body_text":"A Health Ecological Model Study of Subjective Cognitive Decline Among Hypertensive Patients in Rural Shanxi, China | 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 A Health Ecological Model Study of Subjective Cognitive Decline Among Hypertensive Patients in Rural Shanxi, China Ruifeng Liang, Jiawei Liu, Wenhua Sun, Siyi Li, Jue Wang, Qiao Niu, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9110247/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 26 You are reading this latest preprint version Abstract Hypertension and subjective cognitive decline (SCD) frequently co-occur, challenging healthy aging. This study aimed to identify multi-level determinants of SCD among hypertensive patients in rural China using the Health Ecological Model (HEM). We conducted a cross-sectional study with 860 hypertensive patients selected from three rural counties in Shanxi Province via multi-stage cluster random sampling. Participants were categorized into non-SCD (SCD-Q9 score < 5) and SCD (≥ 5) groups. Variables were classified into five HEM layers, and logistic regression was employed to identify associated factors. The prevalence of SCD was 80.58%. Multi-level factors were significantly associated with SCD. In the Individual Characteristics Layer, advanced age, family history of hypertension, and hypertensive complications increased risk. Within the Behavior and Lifestyle Layer, lack of physical exercise and poor sleep quality were risk factors, while alcohol abstinence was protective. In the Working and Living Conditions Layer, lower household income, utilization of county-level hospitals, and mild depression emerged as risk factors. Notably, out-of-pocket payment in the Policy Environment Layer was protective. These findings translate into actionable targets for rural primary care, advocating for integrated strategies addressing hypertension management, mental health, sleep hygiene, physical activity, and socioeconomic barriers to preserve cognitive health in this vulnerable population. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Primary Hypertension Subjective Cognitive Decline Health Ecological Model Rural Health Risk Factors Protective Factors Figures Figure 1 Introduction Hypertension, a major modifiable risk factor for cardiovascular disease and cognitive decline, represents a converging challenge for aging populations worldwide 1 . This challenge is acutely felt in resource-limited settings like rural China, where health systems face the dual burden of a high hypertension prevalence and an accelerating aging demographic. In China, the number of hypertensive patients reached 245 million in 2019, accounting for one-fifth of the global total 2 . Among the spectrum of cognitive concerns, Subjective Cognitive Decline (SCD)—a self-perceived worsening of cognitive capacity with normal objective performance—is highly prevalent (e.g., 42% among Chinese adults aged ≥ 40 years) and is increasingly recognized as a critical early window for preventive intervention 3 , 4 . Hypertension is a well-established driver of SCD 5 . While biological mechanisms provide a partial explanation 6 – 8 , a full understanding requires examining its interaction with behavioral, psychological, crucially environmental and socioeconomic determinants. The Health Ecological Model (HEM) is well-suited to address this complexity. It posits that health outcomes arise from multi-level interactions between individuals and their environment, with factors categorized into five nested layers: individual characteristics, behavioral characteristics, interpersonal networks, living and working conditions, and the policy environment. This framework provides a theoretical basis for comprehensive interventions in public health practice 9 . This model is particularly valuable for developing integrated public health strategies in real-world, resource-constrained settings. We applied the HEM to investigate SCD in a high-risk,understudied population: hypertensive patients in rural Shanxi Province,China.This region epitomizes a critical public health scenario where a high burden of hypertension is compounded by suboptimal management. Local studies reveal that hypertension-related knowledge among rural residents is notably poor, which likely contributes to inadequate control 10 . The severe consequence of this is evident in the substantially elevated prevalence of stroke—a major hypertensive complication—observed in these areas, significantly exceeding national averages 11 . Given that hypertension is also a pivotal risk factor for cognitive decline, this context of high prevalence and poor control signals a population at heightened risk for SCD. Our study aimed to identify the prevalence and the multi-level, modifiable determinants of SCD within this population. The findings are intended to generate practical evidence for tailoring community-based, multi-component interventions that can preserve cognitive health and inform chronic disease management strategies in similar under-resourced settings. Materials and Methods Study Participants This investigation was based on the cohort established by the China-Gates Foundation Rural Primary Health Care Project—Shanxi Provincial Sub-project in Yangqu County (Taiyuan City), Daning County and Yonghe County (Linfen City), Shanxi Province. A total of 860 hypertensive patients aged ≥35 years who were permanent residents were selected from these three counties as survey participants.This study was approved by the Ethics Committee of Shanxi Medical University (Approval No. 2020SLL201). Study Participants and Inclusion/Exclusion Criteria The study participants were adult patients with essential hypertension from three rural counties in Shanxi Province. Inclusion Criteria: Patients were included if they (a) were aged ≥ 35 years; (b) had a diagnosis of essential hypertension; (c) were usual residents of one of the three counties; (d) were conscious, possessed independent capacity for thinking and communication, and had basic literacy; (e) provided voluntary written informed consent. Exclusion Criteria: Patients were excluded if they (a) were aged < 35 years； (b)secondary hypertension; (c) had a history of severe non-hypertensive comorbidities that could independently cause cognitive impairment; (d) had severe neurological or psychiatric disorders, or had frailty, mobility issues, communication barriers, or poor compliance that would hinder participation; or (e) were deemed by the investigators to be unable to complete the study. Eligibility was determined through a structured screening interview conducted by trained researchers, which verbally verified all inclusion and exclusion criteria prior to obtaining written informed consent and commencing formal data collection. Sample Size Calculation The sample size was estimated using the formula for cross-sectional studies: Grouping of Study Participants Participants were divided into two groups based on their SCD-Q9 scores: those with scores<5 were classified as the non-SCD group, and those with scores≥5 were classified as the SCD group. Sampling Method Participants were recruited using a multi-stage cluster random sampling method across Daning, Yonghe, and Yangqu counties. The detailed process, from the target population to participant enrollment, is illustrated in Figure 1. Variable Selection Guided by the HEM and existing literature 9,16 , we selected variables potentially associated with SCD across five layers: Individual characteristics: gender, age, family history, complications, duration of hypertension, etc; Behavior and lifestyle: smoking, alcohol use, sleep, physical activity, etc; Interpersonal networks:marital status,Number of household members. Working and living conditions: occupation (pre-retirement), annual household income, designated healthcare institutions, education level,anxiety, depression,etc; Policy environment: health insurance, method of medical payment, etc. Definitions of Key Variables Smoking: Having smoked continuously or cumulatively for≥6 months 17 . Smoking Cessation: Having met the smoking criteria above but having abstained from smoking for ≥6 months prior to the survey 17 . Non-smoker: Never having met the smoking criteria 17 . Alcohol Drinking: Consuming alcohol at least twice per month, with each intake being at least 100 mL of liquor, 100 mL of wine, or 500 mL of beer, for a duration of ≥6 months up to the time of the survey 18 . Alcohol Abstinence: Having met the alcohol drinking criteria above but having abstained from alcohol for ≥ 6 months prior to the survey 18 . Non-drinker: Never having met the alcohol drinking criteria 18 . Physical Exercise: Engaging in at least 150 min of moderate-intensity or 75 min of vigorous-intensity physical activity per week. Those not meeting this criterion were defined as having insufficient physical activity 19 . Body Mass Index (BMI): Weight (kg) divided by height squared (m²). Categories were underweight (BMI < 18.5 kg/m²), normal weight (18.5kg/m²≤BMI< 24 kg/m²), overweight (24kg/m²≤BMI < 28 kg/m²), and obese (BMI≥28 kg/m²) 20 . Designated Healthcare Institution: Refers to various medical institutions reviewed and certified by the medical security department and other relevant authorities, which have signed service agreements with medical insurance agencies to provide healthcare services for insured individuals and are subject to the supervision and management of the medical insurance department 21 . Resident Population: Refers to all persons for whom a given area serves as their habitual place of residence, having lived there for at least six months 22 . Data Collection Survey Instruments General Information Questionnaire Data were collected using a self-designed questionnaire and included the following aspects: personal characteristics (gender, age, educational attainment, family medical history, etc.), behavior and lifestyle (smoking, alcohol use, physical activity, etc.), interpersonal networks (marital status, number of family members, etc.), work and living conditions (occupation, annual household income, living arrangements and designated healthcare institutions, etc.), and policy environment (medical insurance, payment methods for medical expenses, etc.). The 7-item Generalized Anxiety Disorder Scale (GAD-7) The GAD-7, developed by Spitzer et al. 23 in 2007, is a self-assessment tool for evaluating anxiety symptom severity. It contains seven items, each rated on a 0–3 scale, resulting in a total score ranging from 0 to 21, with higher scores indicating greater severity. In this study, the scale demonstrated excellent internal consistency, with a Cronbach's α of 0.903. Patient Health Questionnaire-9 (PHQ-9) The PHQ-9 24 is a brief, efficient self-assessment depression scale based on the DSM-IV criteria. It consists of nine items rated on a 4-point scale (0 = not at all, 1 = several days, 2 = more than half the days, 3 = nearly every day). Total scores range from 0 to 27, with higher scores indicating a greater likelihood of depression. The Cronbach's α is 0.781. Pittsburgh Sleep Quality Index (PSQI) Sleep quality was assessed using the Chinese PSQI 25 , an 18-item scale across seven domains. Total scores range from 0 to 21, with higher scores indicating poorer sleep quality. The scale demonstrated good internal consistency in this study ( Cronbach's α of 0.760). Subjective Cognitive Decline Questionnaire (SCD-Q9) The Chinese version of the SCD-Q9, developed by Gifford et al. 26 and translated by Hao Lixiao et al. 27 , was used to assess persistent memory decline. The questionnaire has nine items across two dimensions: overall memory capacity and temporal comparison (four items), and activities of daily living (five items). Total scores range from 0 to 9, with higher scores indicating more severe SCD. The Cronbach's α is 0.845. Physical Examination Physical examinations were conducted by clinic doctors from each village who had received unified training, using calibrated equipment and standardized protocols.Key measurements included height, body weight, blood pressure. BMI was calculated from height and weight. Quality Control Rigorous quality control was implemented to ensure data reliability. All personnel underwent uniform training prior to data collection. Standardized face-to-face interviews and physical examinations were conducted using uniform questionnaires and protocols. Questionnaires were checked on-site for completeness immediately after each interview, with missing items addressed promptly. Data were entered using a double-entry procedure with consistency checks; questionnaires missing >10% of key variables were excluded. Statistical Analysis Data were collated and analyzed using SPSS Statistics version 27.0. Continuous variables are presented as mean ± standard deviation, while categorical and ordinal data are presented as N (%) to describe the basic characteristics and distribution of variables. Chi-square tests and t -tests were used to compare demographic characteristics between groups. To systematically explore the factors influencing SCD and examine the independent contributions of factors at different levels based on the HEM theoretical framework, hierarchical binary logistic regression analysis was performed. Specifically, five nested models were constructed sequentially: Model 1: Included only individual characteristics layer factors (baseline model). Model 2: Added behavior and lifestyle layer factors to Model 1, to examine their contribution after controlling for individual characteristics. Model 3: Added factors in the interpersonal networks layer to Model 2. Model 4: Added working and living conditions layer factors to Model 3. Model 5: The full model, including all factors from all five layers, aiming to assess the net effect of all factors. Within each layer, variable selection was performed using the forward stepwise method, with an entry criterion of P <0.05. To assess the robustness of the findings to the modeling approach, a parallel hierarchical multiple linear regression was performed using the continuous SCD-Q9 score as the dependent variable, following the same variable selection and hierarchical structure as described for the primary analysis. Results Comparison of General Characteristics Between Hypertensive Patients Pearson correlation analysis and univariate analysis of factors associated with SCD scores in hypertensive patients revealed statistically significant findings ( P < 0.05) in relation to the following variables. Within the individual characteristics layer, age and duration of hypertension were significantly positively correlated with SCD scores (Table 1 ). Additionally, sex, family history of hypertension, and presence of hypertensive complications showed statistically significant differences in SCD scores (Table 2 ). Within the behavior and lifestyle layer, statistically significant differences in SCD scores were observed regarding alcohol drinking, physical exercise, sleep quality and regular blood pressure monitoring. In the interpersonal networks layer, number of household members showed a statistically significant difference in SCD scores. For the working and living conditions layer, significant differences were identified in annual household income,education level, depression,self-rated health status and access to designated healthcare institutions. Finally, in the policy environment layer, medical payment method showed a significant difference in SCD scores. The detailed results are presented in Table 1 and Table 2 . Table 1 Pearson Correlations of Age and Hypertension Duration with SCD Variable r P Age(years) 0.160 <0.001 Duration of Hypertension (years) 0.076 0.025 Table 2 Univariate Analysis of Factors Associated with SCD in Hypertensive Patients HEM Variable and Category SCD score t / F P Individual Characteristics Layer Sex -3.142 0.002 Male 6.14 ± 2.35 Female 6.62 ± 2.05 Family History of Hypertension -2.071 0.039 No 6.22 ± 2.41 Yes 6.55 ± 2.03 Hypertensive Complications -4.924 <0.001 No 6.24 ± 2.25 Yes 7.00 ± 1.85 Hypertension Risk Level 2.117 0.121 Low risk 6.32 ± 2.22 Moderate risk 6.67 ± 2.05 High risk 6.38 ± 2.38 BMI Category (kg/m²) 0.073 0.975 Underweight 6.07 ± 2.52 Normal Weight 6.42 ± 2.22 Overweight 6.42 ± 2.11 Obese 6.45 ± 2.30 Behavior and Lifestyle Layer Smoking Status 1.414 0.244 Never Smoker 6.51 ± 2.14 Former Smoker 6.21 ± 2.33 Current Smoker 6.25 ± 2.26 Alcohol Drinking 3.560 0.029 Never Drinker 6.50 ± 2.14 Former Drinker 5.60 ± 2.87 Current Drinker 6.15 ± 2.20 Physical Exercise 2.414 0.016 No 6.58 ± 2.13 Yes 6.21 ± 2.25 Sleep Quality (PSQI) 9.899 <0.001 Very Good 6.07 ± 2.49 Fairly Good 6.40 ± 1.89 Fairly Poor 7.15 ± 1.93 Very Poor 7.18 ± 1.73 Number of Antihypertensive Medications 0.691 0.598 1 6.39 ± 2.20 2 6.65 ± 2.14 3 6.00 ± 2.18 4 6.80 ± 2.02 None 6.27 ± 2.19 Regular BP Monitoring -3.321 <0.001 Yes 6.12 ± 2.35 No 6.63 ± 2.04 Interpersonal Networks Layer Marital Status 0.853 0.465 Divorced 6.50 ± 1.84 Widowed 6.66 ± 2.14 Unmarried 5.72 ± 2.67 Married 6.41 ± 2.18 Number of household members 2.183 0.029 ≤ 2 6.50 ± 2.18 >2 6.09 ± 2.19 Working and Living Conditions Layer Occupation 1.259 0.280 Agriculture/Forestry/Fishery/Water Conservancy 6.44 ± 2.19 Commerce/Services 6.33 ± 1.51 Production/Transportation Operators 6.75 ± 1.50 Other Unclassifiable Occupations 5.54 ± 2.27 Others 4.86 ± 2.79 No Occupation 6.53 ± 2.16 Annual Household Income (CNY) 4.560 0.001 <1000 6.90 ± 2.15 1000 ~ 5000 6.32 ± 2.12 5000 ~ 10000 6.24 ± 2.21 10000 ~ 15000 6.57 ± 2.11 ≥ 15000 6.00 ± 2.26 Designated Healthcare Institution 6.252 <0.001 Village Clinic 5.96 ± 2.47 Township Health Center 6.63 ± 2.09 County-level or Above Hospital 6.70 ± 1.93 Private Clinic 6.67 ± 2.02 Others 5.19 ± 2.95 Education Level 3.991 0.008 Illiterate/Semi-illiterate 6.86 ± 2.21 Primary School 6.44 ± 2.17 Junior High School 6.36 ± 2.10 Senior High School or above 5.91 ± 2.37 Anxiety (GAD-7) 1.507 0.211 Normal 6.35 ± 2.25 Mild 6.70 ± 1.88 Moderate 6.18 ± 2.17 Severe 6.82 ± 2.82 Depression (PHQ-9) 3.686 0.012 Normal 6.23 ± 2.35 Mild 6.72 ± 1.78 Moderate 6.81 ± 2.05 Moderately Severe and Above 6.35 ± 2.81 Self-Rated Health Status 12.063 <0.001 Very Good 3.56 ± 3.92 Good 5.55 ± 2.26 Fair 6.25 ± 2.27 Poor 6.79 ± 1.94 Very Poor 7.01 ± 1.85 Policy Environment Layer Health Insurance 1.429 0.240 Urban and Rural Resident Basic Medical Insurance 6.44 ± 2.17 Urban Employee Basic Medical Insurance 5.30 ± 3.08 Others 6.00 ± 3.48 Medical Payment Method 3.819 0.010 New Rural Cooperative Medical Scheme 6.36 ± 2.14 Urban Resident Basic Medical Insurance 6.81 ± 2.17 Out-of-Pocket 5.48 ± 2.81 Others 5.92 ± 2.56 Multivariate Logistic Regression Analysis of Factors Influencing SCD in Hypertensive Patients Using the presence or absence of SCD as the dependent variable, a multivariate logistic regression analysis based on hierarchical modeling was performed to analyze the influencing factors for SCD by sequentially entering different sets of independent variables. The assignment methods for the independent variables are detailed in Table 3 . Model 1, Model 2, Model 3, Model 4, and Model 5 sequentially incorporated variables that were significant in the univariate analysis from the Individual Characteristics Layer, Behavior and Lifestyle Layer, Interpersonal Networks Layer, Working and Living Conditions Layer, and Policy Environment Layer, respectively. Model evaluation indicators showed that the overall explanatory power of the models continuously increased with the sequential inclusion of variables (Cox & Snell R ² values were 0.058, 0.098, 0.098, 0.138, and 0.144, respectively), and the goodness-of-fit for all models was satisfactory (Hosmer and Lemeshow test P > 0.05 for all), indicating that the model construction was stable and reliable. The Individual Characteristics Layer (Model 1) showed that age, sex, family history of hypertension, and hypertensive complications were all significant influencing factors. However, their effects exhibited different patterns after controlling for subsequent layers of variables. Increased age remained an independent risk factor for SCD across all models (Model 4 OR = 1.037, 95% CI: 1.008–1.067; Model 5 OR = 1.036, 95% CI :1.006 ~ 1.067). In contrast, the effects of family history of hypertension (Model 5 OR = 2.168,95% CI :1.461 ~ 3.218) and hypertensive complications (Model 5 OR = 3.118, 95% CI :1.744 ~ 5.577) remained stable across models, confirming them as strong risk factors for SCD. The effect of sex, however, weakened significantly and lost statistical significance after incorporating behavior and lifestyle factors (from Model 1 OR = 1.465, P = 0.033 to Model 2 OR = 1.338, P = 0.143). Duration of hypertension was not significant in any model. The Behavior and Lifestyle Layer (Model 2) showed that, after controlling for Individual Characteristics Layer variables, the introduction of factors from this layer substantially improved the model's explanatory power (Δ R ²=0.040). Among these factors, former drinker (vs. current drinker) demonstrated a stable protective effect (Model 5 OR = 0.289, 95% CI :0.109 ~ 0.763), while lack of physical exercise (Model 5 OR = 1.556, 95% CI :1.056 ~ 2.293) and poor sleep quality (fairly good and fairly poor vs. very good) were significant risk factors for SCD. Regular blood pressure monitoring was not significant in any model. The Interpersonal Networks Layer (Model 3) showed that, after controlling for Individual Characteristics and Behavior and Lifestyle factors, number of household members was not significantly associated with SCD in any model (Model 5 P = 0.631), consistent with the univariate analysis results. The Working and Living Conditions Layer (Model 4) indicated that, after simultaneously controlling for Individual Characteristics, Behavior and Lifestyle, and Interpersonal Networks factors, annual household income, access to designated healthcare institutions, and depression were significant predictors of SCD. Self-rated health status was not significantly associated with SCD in any model. Compared to the high-income group (≥ 15000 CNY), the low-income groups (< 1000 CNY: OR = 3.056, 95% CI :1.592 ~ 5.863; 1000 ~ 5000 CNY: OR = 2.383, 95% CI :1.062 ~ 5.344) had a significantly higher risk of SCD, demonstrating the independent influence of socioeconomic factors. Regarding designated healthcare institutions, compared to those whose designated institution was a village clinic, participants using county-level or above hospitals had a significantly higher risk of SCD ( OR = 1.696, 95% CI :1.092 ~ 2.634, P = 0.019). Mild depression (vs. normal) was a significant risk factor ( OR = 2.116, 95% CI :1.322 ~ 3.387). Education level was not significant in any model. The Policy Environment Layer (Model 5) showed that, after controlling for all variables from the previous layers, out-of-pocket payment for medical expenses (vs. New Rural Cooperative Medical Scheme) was significantly associated with lower risk of SCD ( OR = 0.360, 95% CI :0.139 ~ 0.931, P = 0.035). The final Model 5 showed that after including all variables from all layers, in the Individual Characteristics Layer, older age, family history of hypertension, and hypertensive complications remained significant risk factors (all P < 0.05). In the Behavior and Lifestyle Layer, former drinker, lack of physical exercise, and poor sleep quality (fairly good and fairly poor) showed statistically significant differences (all P < 0.05). In the Working and Living Conditions Layer, lower annual household income (< 1000 CNY, 1000 ~ 5000 CNY, and 10000 ~ 15000 CNY), county-level or above hospital (vs. village clinic), and mild depression remained significant predictors (all P < 0.05). Self-rated health status was not significant. In the Policy Environment Layer, out-of-pocket payment for medical expenses (vs. New Rural Cooperative Medical Scheme) was significantly associated with lower risk of SCD ( OR = 0.360, 95% CI: 0.139 ~ 0.931, P = 0.035). Detailed results are presented in Table 4 a,b,c. Table 3 Variable Assignments Variable Assignment / Definition Sex Male = 1 Female = 2 Family History of Hypertension No = 0 Yes = 1 Hypertensive Complications No = 0 Yes = 1 Alcohol Drinking Never Drinker = 0 Former Drinker = 1 Current Drinker = 2 Depression (PHQ-9) Normal = 1 Mild = 2 Moderate = 3 Moderately Severe and Above = 4 Severe = 5 Sleep Quality (PSQI) Very Good = 1 Fairly Good = 2 Fairly Poor = 3 Very Poor = 4 Regular Blood Pressure Monitoring Yes = 1 No = 2 Correct Use of Home Blood Pressure Monitor Yes = 1 No = 2 Self-rated Health Status Excellent = 1 Very Good = 2 Good = 3 Fair = 4 Poor = 5 Annual Household Income (CNY) <1000 = 1 1000–5000 = 2 5000–10000 = 3 10000–15000 = 4 ≥ 15000 = 5 Designated Healthcare Institution Village Clinic = 1 Township Health Center = 2 County-level or Above Hospital = 3 Private Clinic = 4 Other = 5 Number of household members ≤ 2 = 1 >2 = 2 Physical Exercise No = 1 Yes = 2 Medical Payment Method New Rural Cooperative Medical Scheme = 1 Urban Resident Basic Medical Insurance = 2 Out-of-Pocket = 3 Others = 4 Table 4 a. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Models 1–2) Variable Model 1 Model 2 β waldχ 2 OR( 95% CI) P β waldχ 2 OR( 95% CI) P Individual Characteristics Layer Age 0.046 12.987 1.047(1.021,1.073) <0.001 0.048 12.992 1.049(1.022,1.076) <0.001 Sex (Ref: Male) Female 0.382 4.540 1.465(1.031,2.083) 0.033 0.291 2.147 1.338(0.906,1.976) 0.143 Family History of Hypertension (Ref: No) Yes 0.670 13.526 1.953(1.367,2.791) <0.001 0.723 14.631 2.061(1.423,2.986) <0.001 Hypertensive Complications (Ref: No) Yes 1.027 14.947 2.791(1.659,4.697) <0.001 1.149 16.709 3.156(1.819,5.476) <0.001 Duration of Hypertension (years) 0.008 0.408 1.008(0.983,1.035) 0.523 0.012 0.756 1.012(0.985,1.039) 0.385 Behavior and Lifestyle Layer Alcohol Drinking (Ref: Current Drinker) 8.971 0.011 Never Drinker -0.031 0.012 0.969(0.548,1.714) 0.914 Former Drinker -1.287 7.204 0.276(0.108,0.707) 0.007 Physical Exercise(Ref: Yes) No 0.465 6.151 1.592(1.102,2.298) 0.013 Sleep Quality - PSQI (Ref: Very Good) 17.982 <0.001 Fairly Good 0.633 9.952 1.883(1.271,2.790) 0.002 Fairly Poor 1.005 11.664 2.733(1.535,4.866) <0.001 Very Poor 1.451 1.916 4.266(0.547,33.273) 0.166 Regular BP Monitoring (Ref: Yes) No 0.241 1.656 1.272(0.882,1.836) 0.198 Table 4 b. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Models 3–4) Variable Model 3 Model 4 β waldχ 2 OR( 95% CI) P β waldχ 2 OR( 95% CI) P Individual Characteristics Layer Age 0.046 11.620 1.047(1.020,1.075) <0.001 0.037 6.094 1.037(1.008,1.068) 0.014 Sex (Ref: Male) Female 0.296 2.216 1.345(0.910,1.987) 0.137 0.256 1.492 1.292(0.856,1.95) 0.222 Family History of Hypertension (Ref: No) Yes 0.724 14.640 2.063(1.424,2.989) <0.001 0.786 15.432 2.195(1.483,3.250) <0.001 Hypertensive Complications (Ref: No) Yes 1.168 17.051 3.216(1.847,5.599) <0.001 1.111 14.194 3.038(1.704,5.415) <0.001 Duration of Hypertension (years) 0.012 0.743 1.012(0.985,1.039) 0.389 0.010 0.508 1.010(0.982,1.039) 0.476 Behavior and Lifestyle Layer Alcohol Drinking (Ref: Current Drinker) 8.783 0.012 8.011 0.018 Never Drinker -0.029 0.010 0.972(0.549,1.721) 0.921 0.017 0.003 1.018(0.565,1.833) 0.954 Former Drinker -1.272 7.026 0.28(0.109,0.718) 0.008 -1.216 6.051 0.296(0.112,0.781) 0.014 Physical Exercise(Ref: Yes) No 0.461 6.053 1.586(1.098,2.291) 0.014 0.449 5.190 1.567(1.065,2.306) 0.023 Sleep Quality - PSQI (Ref: Very Good) 17.853 <0.001 8.718 0.033 Fairly Good 0.635 9.996 1.886(1.273,2.795) 0.002 0.471 4.895 1.602(1.055,2.432) 0.027 Fairly Poor 0.995 11.411 2.706(1.519,4.821) <0.001 0.708 4.902 2.031(1.085,3.801) 0.027 Very Poor 1.464 1.950 4.324(0.554,33.761) 0.163 1.620 2.202 5.052(0.595,42.924) 0.138 Regular BP Monitoring (Ref: Yes) No 0.228 1.464 1.256(0.868,1.816) 0.226 0.251 1.532 1.286(0.864,1.915) 0.216 Interpersonal Networks Layer Number of household members (Ref: >2) ≤ 2 0.156 0.474 1.169(0.749,1.824) 0.491 0.109 0.195 1.115(0.687,1.810) 0.659 >2 Working and Living Conditions Layer Annual Household Income, CNY (Ref: ≥15000) 13.504 0.009 <1000 1.117 11.284 3.056(1.592,5.863) 0.001 1000 ~ 5000 0.868 4.439 2.383(1.062,5.344) 0.035 5000 ~ 10000 0.421 1.776 1.523(0.820,2.828) 0.183 1000 ~ 15000 0.572 5.081 1.772(1.077,2.913) 0.024 Education Level(Ref: Senior High School or above) 3.479 0.323 Illiterate/Semi-illiterate -0.046 0.017 0.955(0.477,1.913) 0.897 Primary School 0.161 0.279 1.174(0.647,2.129) 0.597 Junior High School 0.414 1.961 1.513(0.848,2.699) 0.161 Depression - PHQ-9 (Ref: Normal) 10.077 0.018 Mild 0.750 9.747 2.116(1.322,3.387) 0.002 Moderate 0.073 0.026 1.076(0.441,2.627) 0.872 Severe 0.601 0.455 1.825(0.318,10.476) 0.500 Self-Rated Health Status (Ref: Very Poor) 6.324 0.176 Very Good -1.171 1.862 0.31(0.058,1.667) 0.172 Good -0.083 0.038 0.921(0.401,2.115) 0.845 Fair 0.299 0.712 1.348(0.673,2.701) 0.399 Poor 0.427 1.401 1.533(0.756,3.109) 0.237 Designated Healthcare Institution (Ref: Other) 7.991 0.092 Village Clinic 0.282 0.813 1.325(0.719,2.444) 0.367 Township Health Center 0.480 4.669 1.616(1.046,2.497) 0.031 County-level or Above Hospital -0.319 0.057 0.727(0.053,9.959) 0.811 Private Clinic -1.141 2.018 0.32(0.066,1.542) 0.155 Table 4 c. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Model 5) Variable Model 5 β waldχ 2 OR( 95% CI) P Individual Characteristics Layer Age 0.036 5.712 1.036(1.006,1.067) 0.017 Sex (Ref: Male) Female 0.275 1.691 1.317(0.870,1.995) 0.193 Family History of Hypertension (Ref: No) Yes 0.774 14.741 2.168(1.461,3.218) <0.001 Hypertensive Complications (Ref: No) Yes 1.137 14.705 3.118(1.744,5.577) <0.001 Duration of Hypertension (years) 0.010 0.463 1.010(0.982,1.039) 0.496 Behavior and Lifestyle Layer Alcohol Drinking (Ref: Current Drinker) 7.820 0.020 Never Drinker -0.031 0.010 0.969(0.532,1.764) 0.918 Former Drinker -1.242 6.280 0.289(0.109,0.763) 0.012 Physical Exercise(Ref: Yes) No 0.442 4.987 1.556(1.056,2.293) 0.026 Sleep Quality - PSQI (Ref: Very Good) 8.600 0.035 Fairly Good 0.462 4.604 1.587(1.041,2.420) 0.032 Fairly Poor 0.721 5.032 2.056(1.095,3.861) 0.025 Very Poor 1.601 2.132 4.956(0.578,42.476) 0.144 Regular BP Monitoring (Ref: Yes) No 0.217 1.126 1.242(0.832,1.855) 0.289 Interpersonal Networks Layer Number of household members (Ref: >2) ≤ 2 0.120 0.231 1.128(0.691,1.841) 0.631 >2 Working and Living Conditions Layer Annual Household Income, CNY (Ref: ≥15000) 14.354 0.006 <1000 1.181 12.355 3.256(1.686,6.290) <0.001 1000 ~ 5000 0.908 4.712 2.479(1.092,5.626) 0.030 5000 ~ 10000 0.444 1.960 1.559(0.837,2.902) 0.161 1000 ~ 15000 0.555 4.727 1.742(1.056,2.872) 0.030 Education Level(Ref: Senior High School or above) 3.886 0.274 Illiterate/Semi-illiterate -0.053 0.022 0.948(0.472,1.905) 0.881 Primary School 0.186 0.367 1.205(0.660,2.199) 0.544 Junior High School 0.441 2.189 1.554(0.867,2.786) 0.139 Depression - PHQ-9 (Ref: Normal) 9.929 0.019 Mild 0.749 9.578 2.114(1.316,3.397) 0.002 Moderate 0.047 0.011 1.049(0.428,2.568) 0.917 Severe 0.599 0.433 1.821(0.305,10.855) 0.511 Self-Rated Health Status (Ref: Very Poor) 6.290 0.179 Very Good 2.326 0.262(0.047,1.465) 0.127 Good 0.013 0.952(0.413,2.194) 0.908 Fair 0.619 1.322(0.659,2.652) 0.432 Poor 1.180 1.483(0.728,3.022) 0.277 Designated Healthcare Institution (Ref: Village Clinic) 8.227 0.084 Township Health Center 0.333 1.111 1.395(0.751,2.592) 0.292 County-level or Above Hospital 0.528 5.530 1.696(1.092,2.634) 0.019 Private Clinic -0.393 0.084 0.675(0.047,9.661) 0.772 Others -0.947 1.331 0.388(0.078,1.938) 0.249 Policy Environment Layer Medical Payment Method (Ref: New Rural Cooperative Medical Scheme) 5.666 0.129 Urban Resident Basic Medical Insurance 0.233 0.769 1.263(0.75,2.128) 0.381 Out-of-Pocket -1.021 4.441 0.360(0.139,0.931) 0.035 Others -0.064 0.005 0.938(0.171,5.140) 0.941 Sensitivity Analysis: Linear Regression with the Continuous SCD Score To verify the robustness of the above findings, a linear regression analysis was conducted using the continuous SCD score as the outcome (complete results are presented in Supplementary Table S1 ). In the final adjusted model (Model 5), consistent with the logistic regression results, older age ( β = 0.030,95% CI : 0.008 ~ 0.052, P = 0.007), family history of hypertension ( β = 0.472,95% CI :0.181 ~ 0.764, P = 0.002), presence of hypertensive complications ( β = 0.490,95% CI :0.148 ~ 0.831, P = 0.005), poorer sleep quality ( β = 0.230,95% CI :0.043 ~ 0.416, P = 0.016), and utilization of county-level or above hospitals ( β = 0.497,95% CI :0.148 ~ 0.831, P = 0.005) were significantly associated with higher SCD scores. Additionally, physical exercise ( β = -0.363,95% CI :-0.649~-0.077, P = 0.013) and higher annual household income ( β = -0.171,95% CI : -0.278~-0.064, P = 0.002) were significantly associated with lower SCD scores. Self-rated health status ( β = 0.293,95% CI :0.119 ~ 0.467, P < 0.001) and regular blood pressure monitoring ( β = 0.437,95% CI :0.147 ~ 0.727, P = 0.003) were also significant in the linear model, though they did not reach significance in the logistic regression. Discussion This study applied the HEM and identified distinct risk and protective factors for SCD. Notably, the observed SCD prevalence of 80.58% substantially exceeded our pre-study estimate of 68% 12 , underscoring the pronounced burden of subjective cognitive concerns in this rural hypertensive population.This study identified multi-level risk and protective factors for SCD spanning individual characteristics, behaviors, living conditions, and policy environment. These findings confirm that SCD arises from multi-level synergies 9 , supporting the need for interventions that address individual, behavioral, and environmental determinants. Below, we interpret these findings within their respective HEM layers and, critically, explore their synergistic implications for designing integrated public health strategies. In the HEM framework, the individual characteristics layer is central and includes fixed traits such as age, sex, and genetics, forming a health determinant baseline 9 . Our findings corroborate that advanced age is a significant risk factor for subjective cognitive decline in hypertensive patients ( OR = 1.036, 95% CI :1.006 ~ 1.067). The decline in vascular elasticity and impaired cerebral perfusion autoregulation associated with aging may act synergistically with the vascular damage induced by hypertension, collectively exacerbating cerebral small vessel disease and injuring cognition-related brain regions such as the hippocampus 7 , 28 . Furthermore, another study identified three primary trajectories of cognitive function in the middle-aged and elderly population: \"high-stability,\" \"moderate-decline,\" and \"rapid-decline,\" with the \"moderate-decline\" pattern being the most prevalent 29 . This study revealed that the presence of a family history of hypertension was a risk factor for SCD ( OR = 2.168,95% CI :1.461 ~ 3.218), corresponding to an approximately 2.17-fold higher risk compared to those without such a family history. Hypertension exhibits familial aggregation 30 . Relevant studies have shown that offspring with a family history of hypertension have an elevated probability of developing the condition 31 . After the onset of hypertension, the rate of cognitive decline is approximately twice as fast as in those without hypertension, equivalent to an additional 83% annual deterioration compared to individuals with normal blood pressure. This effect is more pronounced in hypertensive patients after the age of 65 years 32 . Hypertension can lead to various cardiovascular and cerebrovascular diseases 33 . This study found that the presence of hypertensive complications was a risk factor for SCD ( OR = 3.118, 95% CI :1.744 ~ 5.577), indicating that the risk of SCD in patients with complications was approximately 3.12 times that of those without complications. Relevant research demonstrated that the brain is an early target organ for hypertension-induced damage, and that following a diagnosis, the rates of overall cognitive and memory decline accelerate to approximately twice that of normal aging 6 . One study confirmed that volume reduction and altered connectivity in specific hypertension-vulnerable brain regions, including the putamen, anterior thalamic radiation, anterior corona radiata, and anterior limb of the internal capsule, are associated with cognitive decline 34 . This layer functions as a crucial link between individual characteristics and broader environmental influences within the HEM. It encompasses modifiable behavioral and lifestyle factors, such as physical activity, alcohol consumption, and sleep quality, representing a promising target for public health interventions 9 . Our analysis identified alcohol abstinence as a significant protective factor against SCD in hypertensive patients( OR = 0.289,95% CI :0.109 ~ 0.763). Longitudinal evidence indicates that although heavy alcohol consumption in midlife accelerates cognitive deterioration, individuals who adopt abstinence can experience a favorable reversal in their cognitive trajectory, ultimately reaching rates of decline comparable to those seen in never-drinkers 35 . A Mendelian randomization study provided compelling evidence that reducing alcohol consumption constitutes a causal protective behavior that significantly diminishes dementia risk 36 . This study identified lack of physical exercise as a significant risk factor for SCD in hypertensive patients ( OR = 1.556, 95% CI :1.056 ~ 2.293). Regular physical activity is an important behavioral factor for protecting cognitive function. It improves cerebral blood flow 37 , promotes the release of neurotrophic factors 38 , and reduces vascular inflammation and insulin resistance 39 . In contrast, hypertensive patients who are physically inactive experience fewer vascular health benefits, leading to a relatively higher cognitive risk 40 . Sleep serves not only as a crucial mechanism for physical rest and recovery but also helps regulate metabolism, support immune function, facilitate brain waste clearance, and consolidate memory and cognitive processes 41 . This study identified poor sleep quality as a significant influencing factor for SCD in hypertensive patients. Compared to those with very good sleep quality, patients with fairly good sleep quality ( OR = 1.587, 95% CI :1.041 ~ 2.420) and those with fairly poor sleep quality ( OR = 2.056, 95% CI :1.095 ~ 3.861) had significantly higher risk of SCD. A growing body of research indicates that the glymphatic system, which is responsible for clearing metabolic waste products such as β-amyloid and tau proteins from the brain, exhibits peak activity during slow-wave sleep 42 . Consequently, disrupted sleep patterns—reflected in the poor sleep quality observed in our cohort—may impair this vital clearance mechanism. Such impairment can lead to the accumulation of neurotoxic proteins and subsequent neuronal injury, processes that are increasingly linked to the emergence of subjective cognitive complaints 43 .Research indicates that hypertensive patients with insufficient sleep (< 6 h per night) exhibit poorer executive function and more pronounced signs of brain injury, such as white matter hyperintensities 44 . The working and living conditions layer encompasses the immediate physical and socioeconomic environments in which individuals reside, including occupational settings, income levels, housing conditions, educational resources, and healthcare accessibility, and the HEM posits that individual health behaviors are constrained by these external living conditions 9 . This study confirmed that lower annual household income (< 1000 CNY) is a significant risk factor for SCD in hypertensive patients, with its effect remaining statistically significant even after adjusting for individual characteristics and behaviors. A nationally representative health survey in the United Kingdom revealed a significant socioeconomic gradient in both hypertension prevalence and underdiagnosis, specifically, lower-income groups demonstrated not only higher hypertension prevalence rates but also greater proportions of undiagnosed hypertension 45 . Furthermore, a study comprising 76 low- and middle-income countries found that while disparities in hypertension prevalence across socioeconomic groups were generally modest, the lowest socioeconomic groups exhibited higher hypertension rates in countries with higher GDP per capita 46 . Given that hypertension is an established risk factor for SCD 5 , 12 , 32 , 47 , these income-related disparities in hypertension may consequently exert an indirect influence on SCD occurrence. This study identified depressive symptoms as a significant risk factor for SCD in hypertensive patients. Specifically, patients with mild depression had a significantly higher risk of SCD compared to those with normal status ( OR = 2.114,95% CI :1.316 ~ 3.397). Using the Behavioral Risk Factor Surveillance System, the U.S. Centers for Disease Control and Prevention determined that hypertension is an independent risk factor for SCD, and that depressive symptoms further amplify this risk 12 . Another study confirmed that depressive symptoms indirectly increase the risk of SCD by reducing self-efficacy 48 . This study identified utilization of county-level or above hospitals as a significant risk factor for SCD in hypertensive patients ( OR = 1.696, 95% CI :1.092 ~ 2.634). The decision to seek care at county-level or above hospitals often conceals underlying complex health drivers 49 . These patients may have longer disease duration, suboptimal blood pressure control, or self-perceived significant neurological symptoms such as memory decline 50 . It is precisely these more severe health conditions and more urgent healthcare needs that motivate them to overcome barriers such as distance and cost, seeking what they perceive as more authoritative and technically superior medical resources 51 . The Policy Environment Layer, as the outermost layer of the Health Ecological Model, encompasses macro-level factors such as healthcare policies, economic conditions, and cultural values that shape individual health outcomes 9 . This study identified out-of-pocket payment for medical expenses as a significant protective factor for SCD in hypertensive patients ( OR = 0.360, 95% CI :0.139 ~ 0.931).Out-of-pocket payment refers to a payment method in which patients bear the full cost of medical expenses personally, without using any form of medical insurance reimbursement 52 .Patients who choose out-of-pocket payment may have greater financial capacity and typically enjoy better living conditions, access to higher quality healthcare services, and richer health information resource—all of which may protect cognitive function through multiple pathways 53 . To assess the robustness of our primary findings, we conducted a supplementary linear regression analysis using the continuous SCD score. The results confirmed that the direction of associations for the key risk factors identified above remained consistent. This methodological convergence strengthens confidence in our conclusions. The subtle differences observed for variables such as alcohol abstinence, mild depression, and out-of-pocket payment highlight the potential for distinct factors to influence disease probability versus symptom severity, a nuance that could inform more stratified screening approaches. This study has several limitations. Its cross-sectional design precludes causal inference, and the self-reported nature of some variables may introduce recall bias. Although the number of household members from the interpersonal networks layer was included in the multivariate analysis, it was not significantly associated with SCD in the final model. Future research should employ longitudinal cohorts and incorporate objective cognitive assessments, such as neuropsychological tests, to further validate factors associated with SCD. Conclusion In summary, applying the HEM reveals that SCD risk among hypertensive patients is shaped by factors across individual, behavioral, living conditions, and policy environment layers. This multi-level perspective moves beyond a purely biomedical view and provides actionable targets for integrated intervention. Advanced age, family history of hypertension, and hypertensive complications were significant risk factors. Physical inactivity and poor sleep quality increased risk, whereas alcohol abstinence was protective. Socioeconomic factors—particularly lower income—along with utilization of county-level hospitals and mild depressive symptoms, independently contributed to increased risk. Out-of-pocket payment emerged as a protective factor, possibly reflecting greater financial capacity. Collectively, these findings advocate for comprehensive strategies that synergistically span clinical risk stratification, behavioral modification, and mitigation of socioeconomic and healthcare access barriers within strengthening primary care systems to preserve cognitive health in this vulnerable aging population. Declarations Acknowledgements The authors would like to thank all participants who participated in the study. Author contributions R.L. contributed to conceptualization, data curation, formal analysis, project administration, resources, and writing—review and editing. J.L. wrote the original draft and contributed to conceptualization, formal analysis, methodology, and data curation. W.S., S.L., and J.W. performed investigation and data curation. Q.N., S.L., and S.Z. provided supervision. H.Y., X.Q., H.Z., J.N., Z.Z., and J.B. contributed to conceptualization and methodology. All authors reviewed and approved the final manuscript. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Data Availability Statement The datasets generated and/or analysed during the current study are not publicly available due to privacy or ethical restrictions but are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Shanxi Medical University (Approval no. 2020SLL201), informed consent was obtained from all participants. Funding China-Gates Foundation Rural Basic Healthcare Project (Shanxi Sub-Project, No. PHC-I04); Shanxi Provincial Traditional Chinese Medicine (TCM) Research Project (No. 2024ZYY2D022); Open Fund from Key Laboratory of Cellular Physiology (Shanxi Medical University), Ministry of Education, China(No. CELLPHYSIOL/SXMU-2021-16); Provincial Application Basis Research Plan of Shanxi under Grant (No. 201801D121314); Shanxi Province Higher Education “Billion Project” Science and Technology Guidance Project. Additional Information Correspondence and requests for materials should be addressed to Ruifeng Liang. Reprints and permissions information is available at www.nature.com/reprints. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References World Health Organization. Global report on hypertension: the race against a silent killer (World Health Organization, 2023). Center for Cardiovascular Diseases & The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Report on Cardiovascular Health and Diseases in China 2023: An Updated Summary. Biomed. Environ. Sci. 37 , 949-992, doi:10.3967/bes2024.162 (2024). Jessen, F. et al. The characterisation of subjective cognitive decline. Lancet Neurol. 19 , 271-278, doi:10.1016/s1474-4422(19)30368-0 (2020). Wen, C. et al. Risk factors for subjective cognitive decline: the CABLE study. Transl. Psychiatry 11 , 576, doi:10.1038/s41398-021-01711-1 (2021). Cheng, G. R. et al. Prevalence and risk factors for subjective cognitive decline and the correlation with objective cognition among community-dwelling older adults in China: Results from the Hubei memory and aging cohort study. Alzheimers Dement. 19 , 5074-5085, doi:10.1002/alz.13047 (2023). Di Chiara, T. et al. Pathogenetic Mechanisms of Hypertension-Brain-Induced Complications: Focus on Molecular Mediators. Int. J. Mol. Sci. 23 , doi:10.3390/ijms23052445 (2022). Iadecola, C. et al. Impact of Hypertension on Cognitive Function: A Scientific Statement From the American Heart Association. Hypertension 68 , e67-e94, doi:10.1161/hyp.0000000000000053 (2016). Shih, Y. H. et al. Hypertension Accelerates Alzheimer's Disease-Related Pathologies in Pigs and 3xTg Mice. Front. Aging Neurosci. 10 , 73, doi:10.3389/fnagi.2018.00073 (2018). Sallis, J. F., Owen, N. & Fisher, E. B. in Health behavior and health education: Theory, research, and practice, 4th ed. 465-485 (Jossey-Bass/Wiley, 2008). Wang, M. Q., Chai, H. L., Guo, Y. Y., Ren, J. J. & Liang, R. F. Knowledge, attitude, and practice of hypertension prevention and control among rural residents in Shanxi Province. China Prev. Med. J. 35 , 563-569, doi:10.19485/j.cnki.issn2096-5087.2023.07.003 (2023). Cheng, X. Y., Wang, R., Guo, Y. Y., Wang, M. Q., Chai, H. L. & Liang, R. F. Risk factors for stroke and its correlation with H-type hypertension among the middle-aged and elderly in a rural area of Shanxi Province. Pract. Prev. Med. 31 , 1153-1158 (2024). Schliep, K. C. et al. Overall and sex-specific risk factors for subjective cognitive decline: findings from the 2015-2018 Behavioral Risk Factor Surveillance System Survey. Biol Sex Differ. 13 , 16, doi:10.1186/s13293-022-00425-3 (2022). Hongheiku Statistical Bulletin Database. Yangqu County Seventh National Population Census Bulletin , <https://tjgb.hongheiku.com/15692.html>(accessed December 18, 2025). Hongheiku Statistical Bulletin Database. Daning County Seventh National Population Census Bulletin , <https://tjgb.hongheiku.com/rkpcgb/19977.html> (accessed December 18, 2025). Hongheiku Statistical Bulletin Database. Yonghe County Seventh National Population Census Bulletin , <https://tjgb.hongheiku.com/rkpcgb/19979.html>(accessed December 18, 2025). Chang, H. et al. Factors Associated With the Prevalence of Hypertension Among Residents in Fujian Province: Based on the Health Ecological Model. Am. J. Hypertens. 37 , 1009-1009, doi:10.1093/ajh/hpae111 (2024). World Health Organization. Guidelines for controlling and monitoring the tobacco epidemic (World Health Organization, Geneva, 1998). Jang, C. C. et al . Interaction of family history of hypertension and overweight/obesity on hypertension in Han and Manchu adults in Hebei province. Basic Clin. Med. 43 , 1053-1059, doi:10.16352/j.issn.1001-6325.2023.07.1053 (2023). World Health Organization. WHO guidelines on physical activity and sedentary behaviour . (World Health Organization, 2020). Clinical practice guideline for the management of hypertension in China. Chin. Med. J. 137 , 2907-2952, doi:10.1097/cm9.0000000000003431 (2024). National Healthcare Security Administration. Interim Measures for the Administration of Designated Medical Institutions Providing Medical Insurance Services , <https://www.gov.cn/zhengce/zhengceku/2021-01/12/content_5579285.htm>(accessed December 18, 2025). National Bureau of Statistics.National Bureau of Statistics website. <https://www.stats.gov.cn/hd/lyzx/zxgk/202302/t20230215_1905399.html>(accessed December 18, 2025). Spitzer, R. L., Kroenke, K., Williams, J. B. & Löwe, B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166 , 1092-1097, doi:10.1001/archinte.166.10.1092 (2006). American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, DSM-5-TR . (2022). Liu, X. C. et al. Reliability and validity of the Pittsburgh Sleep Quality Index. Chin. J. Psychiatry. 29 , 103-107 (1996). Gifford, K. A., Liu, D., Romano, R., 3rd, Jones, R. N. & Jefferson, A. L. Development of a subjective cognitive decline questionnaire using item response theory: a pilot study. Alzheimers Dement. 1 , 429-439, doi:10.1016/j.dadm.2015.09.004 (2015). Hao, L. X., Hu, X. C., Han, Y. & Jia, J. G. Localization of Subjective Cognitive Decline Questionnaire and Its Reliability and Validity Test . Chin. Gen. Pract. 22 , 3238-3245, doi:10.12114/j.issn.1007-9572.2019.00.045 (2019). Xia, X., Jiang, Q., McDermott, J. & Han, J. J. Aging and Alzheimer's disease: Comparison and associations from molecular to system level. Aging Cell 17 , e12802, doi:10.1111/acel.12802 (2018). Zhang, H. et al. Group-based trajectory modelling for cognitive changes in middle-aged and older adults: A systematic review. Ageing Res. Rev. 112 , 102855, doi:10.1016/j.arr.2025.102855 (2025). Zappa, M., Golino, M., Verdecchia, P. & Angeli, F. Genetics of Hypertension: From Monogenic Analysis to GETomics. J. Cardiovasc. Dev. Dis. 11 , doi:10.3390/jcdd11050154 (2024). Takase, M. et al. Associations of family history of hypertension, genetic, and lifestyle risks with incident hypertension. Hypertens. Res. , doi:10.1038/s41440-025-02314-9 (2025). Chen, Q. et al. Trajectories of Cognitive Decline Before and After New-Onset Hypertension. J. Am. Heart Assoc. 14 , e039849, doi:10.1161/jaha.124.039849 (2025). Clinical practice guidelines for the management of hypertension in China. Zhonghua Xin Xue Guan Bing Za Zhi 52 , 985-1032, doi:10.3760/cma.j.cn112148-20240709-00377 (2024). Siedlinski, M. et al. Genetic analyses identify brain structures related to cognitive impairment associated with elevated blood pressure. Eur. Heart J. 44 , 2114-2125, doi:10.1093/eurheartj/ehad101 (2023). Sabia, S. et al. Alcohol consumption and cognitive decline in early old age. Neurology 82 , 332-339, doi:10.1212/wnl.0000000000000063 (2014). Zheng, L. et al. Association between alcohol consumption and incidence of dementia in current drinkers: linear and non-linear mendelian randomization analysis. EClinicalMedicine 76 , 102810, doi:10.1016/j.eclinm.2024.102810 (2024). Gkotzamanis, V., Magriplis, E. & Panagiotakos, D. The effect of physical activity interventions on cognitive function of older adults: A systematic review of clinical trials. Psychiatriki 33 , 291-300, doi:10.22365/jpsych.2022.060 (2022). Zong, B., Yu, F., Li, F., Sun, P. & Li, L. Beyond Fuel: Exercise-Induced Lactate as a Metabolic-Epigenetic Regulator in Central Nervous System Health and Disease. Biomolecules 16 , doi:10.3390/biom16010043 (2025). Tari, A. R., Walker, T. L., Huuha, A. M., Sando, S. B. & Wisloff, U. Neuroprotective mechanisms of exercise and the importance of fitness for healthy brain ageing. Lancet 405 , 1093-1118, doi:10.1016/s0140-6736(25)00184-9 (2025). Kazibwe, R. et al. Effect of vigorous-intensity physical activity on incident cognitive impairment in high-risk hypertension. Alzheimers Dement. 20 , 4602-4612, doi:10.1002/alz.13887 (2024). Miao, Y. et al. Poor sleep health is associated with older brain age: the role of systemic inflammation. eBioMedicine 120 , 105941, doi:https://doi.org/10.1016/j.ebiom.2025.105941 (2025). Dagum, P. et al. The glymphatic system clears amyloid beta and tau from brain to plasma in humans. Nat. Commun. 17 , 715, doi:10.1038/s41467-026-68374-8 (2026). Liu, X. et al. Surrogates of glymphatic metrics decline and coupled sleep rhythms disruption in Alzheimer's disease. Alzheimers Res. Ther. , doi:10.1186/s13195-026-01962-4 (2026). Yiallourou, S. et al. Short Sleep Duration and Hypertension: A Double Hit for the Brain. J. Am. Heart Assoc. 13 , e035132, doi:10.1161/jaha.124.035132 (2024). Scholes, S., Conolly, A. & Mindell, J. S. Income-based inequalities in hypertension and in undiagnosed hypertension: analysis of Health Survey for England data. J. Hypertens. 38 , 912-924, doi:10.1097/hjh.0000000000002350 (2020). Kirschbaum, T. K. et al. The Association of Socioeconomic Status With Hypertension in 76 Low- and Middle-Income Countries. J. Am. Coll. Cardiol. 80 , 804-817, doi:10.1016/j.jacc.2022.05.044 (2022). Piña-Escudero, S. D. et al. Subjective cognitive decline and elder mistreatment in Mexican community-dwelling older adults. Arch. Gerontol. Geriatr. 92 , 104242, doi:10.1016/j.archger.2020.104242 (2021). Su, H., Zhou, Y., Sun, Y. & Cai, Y. The relationship between depression and subjective cognitive decline in older adults of China: the mediating role of general self-efficacy. Psychol. Health Med. 28 , 1057-1067, doi:10.1080/13548506.2022.2125165 (2023). Guo, L. et al. Factors associated with patients' healthcare-seeking behavior and related clinical outcomes under China's hierarchical healthcare delivery system. Front. Public Health 12 , 1326272, doi:10.3389/fpubh.2024.1326272 (2024). Hasan, M. J. et al. Health-care-seeking behaviour in patients with hypertension: experience from a dedicated hypertension centre in Bangladesh. Blood Press. 33 , 2339434, doi:10.1080/08037051.2024.2339434 (2024). Li, X., Zhang, L., Li, Z. & Tang, W. Patient Choice and Willingness Toward Gatekeepers as First-Contact Medical Institutions in Chinese Tiered Healthcare Delivery System: A Cross-Sectional Study. Front. Public Health 9 , 665282, doi:10.3389/fpubh.2021.665282 (2021). Aniebo, C. L., Lawani, L. O. & Eze, P. The Burden and Socioeconomic Inequality in Catastrophic Out-of-pocket Health Expenditure in Post-Pandemic Nigeria. Glob. Soc. Welf. , doi:10.1007/s40609-025-00423-4 (2025). Zheng, Y. et al. The Impact of Socioeconomic Factors on Cognitive Ability in Community-Dwelling Older Adults: Mediating Effect of Social Participation and Social Support. Healthcare 13 , doi:10.3390/healthcare13050551 (2025). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-9110247\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":610807911,\"identity\":\"8b491b68-e3dd-4f02-9335-e3c41e159c37\",\"order_by\":0,\"name\":\"Ruifeng 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Province\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shuhong\",\"middleName\":\"\",\"lastName\":\"Zhao\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-03-13 04:54:22\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9110247/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9110247/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":105319183,\"identity\":\"9431f86e-bfd4-42ee-b0d0-63cf154c177e\",\"added_by\":\"auto\",\"created_at\":\"2026-03-24 16:59:33\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":122876,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eFlowchart illustrating the multi-stage cluster random sampling procedure and the eligibility screening process for participant enrollment\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9110247/v1/81d4e7205f5e845b1f0c3817.png\"},{\"id\":105565185,\"identity\":\"3c4914b7-f2f8-438d-bed6-0f2e71306df1\",\"added_by\":\"auto\",\"created_at\":\"2026-03-27 12:52:18\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2315651,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9110247/v1/52cce93e-b546-42a1-a0f8-7ff8918003cc.pdf\"},{\"id\":105319184,\"identity\":\"a270b046-bb61-4f89-af5b-4534d16b1a48\",\"added_by\":\"auto\",\"created_at\":\"2026-03-24 16:59:33\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":98652,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryInformation.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9110247/v1/8f0a281347fddc679a579076.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"A Health Ecological Model Study of Subjective Cognitive Decline Among Hypertensive Patients in Rural Shanxi, China\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eHypertension, a major modifiable risk factor for cardiovascular disease and cognitive decline, represents a converging challenge for aging populations worldwide\\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003e. This challenge is acutely felt in resource-limited settings like rural China, where health systems face the dual burden of a high hypertension prevalence and an accelerating aging demographic. In China, the number of hypertensive patients reached 245\\u0026nbsp;million in 2019, accounting for one-fifth of the global total\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e. Among the spectrum of cognitive concerns, Subjective Cognitive Decline (SCD)\\u0026mdash;a self-perceived worsening of cognitive capacity with normal objective performance\\u0026mdash;is highly prevalent (e.g., 42% among Chinese adults aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;40 years) and is increasingly recognized as a critical early window for preventive intervention\\u003csup\\u003e\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eHypertension is a well-established driver of SCD\\u003csup\\u003e\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e. While biological mechanisms provide a partial explanation \\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR7\\\" citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e\\u003c/sup\\u003e, a full understanding requires examining its interaction with behavioral, psychological, crucially environmental and socioeconomic determinants. The Health Ecological Model (HEM) is well-suited to address this complexity. It posits that health outcomes arise from multi-level interactions between individuals and their environment, with factors categorized into five nested layers: individual characteristics, behavioral characteristics, interpersonal networks, living and working conditions, and the policy environment. This framework provides a theoretical basis for comprehensive interventions in public health practice\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e. This model is particularly valuable for developing integrated public health strategies in real-world, resource-constrained settings.\\u003c/p\\u003e \\u003cp\\u003eWe applied the HEM to investigate SCD in a high-risk,understudied population: hypertensive patients in rural Shanxi Province,China.This region epitomizes a critical public health scenario where a high burden of hypertension is compounded by suboptimal management. Local studies reveal that hypertension-related knowledge among rural residents is notably poor, which likely contributes to inadequate control\\u003csup\\u003e\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u003c/sup\\u003e. The severe consequence of this is evident in the substantially elevated prevalence of stroke\\u0026mdash;a major hypertensive complication\\u0026mdash;observed in these areas, significantly exceeding national averages\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e. Given that hypertension is also a pivotal risk factor for cognitive decline, this context of high prevalence and poor control signals a population at heightened risk for SCD. Our study aimed to identify the prevalence and the multi-level, modifiable determinants of SCD within this population. The findings are intended to generate practical evidence for tailoring community-based, multi-component interventions that can preserve cognitive health and inform chronic disease management strategies in similar under-resourced settings.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eStudy Participants\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis investigation was based on the cohort established by the China-Gates Foundation Rural Primary Health Care Project\\u0026mdash;Shanxi Provincial Sub-project in Yangqu County (Taiyuan City), Daning County and Yonghe County (Linfen City), Shanxi Province. A total of 860 hypertensive patients aged \\u0026ge;35 years who were permanent residents were selected from these three counties as survey participants.This study was approved by the Ethics Committee of Shanxi Medical University (Approval No. 2020SLL201).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStudy Participants and Inclusion/Exclusion Criteria\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study participants were adult patients with essential hypertension from three rural counties in Shanxi Province.\\u003c/p\\u003e\\n\\u003cp\\u003eInclusion Criteria: Patients were included if they (a) were aged \\u0026ge; 35 years; (b) had a diagnosis of essential hypertension; (c) were usual residents of one of the three counties; (d) were conscious, possessed independent capacity for thinking and communication, and had basic literacy; (e) provided voluntary written informed consent.\\u003c/p\\u003e\\n\\u003cp\\u003eExclusion Criteria: Patients were excluded if they (a) were aged \\u0026lt; 35 years；\\u0026nbsp;(b)secondary hypertension; (c) had a history of severe non-hypertensive comorbidities that could independently cause cognitive impairment; (d) had severe neurological or psychiatric disorders, or had frailty, mobility issues, communication barriers, or poor compliance that would hinder participation; or (e) were deemed by the investigators to be unable to complete the study.\\u003c/p\\u003e\\n\\u003cp\\u003eEligibility was determined through a structured screening interview conducted by trained researchers, which verbally verified all inclusion and exclusion criteria prior to obtaining written informed consent and commencing formal data collection.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSample Size Calculation\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe sample size was estimated using the formula for cross-sectional studies:\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg 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\\\"\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eGrouping of Study Participants\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eParticipants were divided into two groups based on their SCD-Q9 scores: those with scores\\u0026lt;5 were classified as the non-SCD group, and those with scores\\u0026ge;5 were classified as the SCD group.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSampling Method\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eParticipants were recruited using a multi-stage cluster random sampling method across Daning, Yonghe, and Yangqu counties. The detailed process, from the target population to participant enrollment, is illustrated in Figure 1.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eVariable Selection\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eGuided by the HEM and existing literature\\u003csup\\u003e9,16\\u003c/sup\\u003e, we selected variables potentially associated with SCD across five layers:\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIndividual characteristics: gender, age, family history, complications, duration of hypertension, etc;\\u003c/p\\u003e\\n\\u003cp\\u003eBehavior and lifestyle: smoking, alcohol use, sleep, physical activity, etc;\\u003c/p\\u003e\\n\\u003cp\\u003eInterpersonal networks:marital status,Number of household members.\\u003c/p\\u003e\\n\\u003cp\\u003eWorking and living conditions: occupation (pre-retirement), annual household income, designated healthcare institutions, education level,anxiety, depression,etc;\\u003c/p\\u003e\\n\\u003cp\\u003ePolicy environment: health insurance, method of medical payment, etc.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDefinitions of Key Variables\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSmoking: Having smoked continuously or cumulatively for\\u0026ge;6 months\\u003csup\\u003e17\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eSmoking Cessation: Having met the smoking criteria above but having abstained from smoking for \\u0026ge;6 months prior to the survey\\u003csup\\u003e17\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eNon-smoker: Never having met the smoking criteria\\u003csup\\u003e17\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eAlcohol Drinking: Consuming alcohol at least twice per month, with each intake being at least 100 mL of liquor, 100 mL of wine, or 500 mL of beer, for a duration of \\u0026ge;6 months up to the time of the survey\\u003csup\\u003e18\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eAlcohol Abstinence: Having met the alcohol drinking criteria above but having abstained from alcohol for \\u0026ge; 6 months prior to the survey\\u003csup\\u003e18\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eNon-drinker: Never having met the alcohol drinking criteria\\u003csup\\u003e18\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003ePhysical Exercise: Engaging in at least 150 min of moderate-intensity or 75 min of vigorous-intensity physical activity per week. Those not meeting this criterion were defined as having insufficient physical activity\\u003csup\\u003e19\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eBody Mass Index (BMI): Weight (kg) divided by height squared (m\\u0026sup2;). Categories were underweight (BMI \\u0026lt; 18.5 kg/m\\u0026sup2;), normal weight (18.5kg/m\\u0026sup2;\\u0026le;BMI\\u0026lt; 24 kg/m\\u0026sup2;), overweight (24kg/m\\u0026sup2;\\u0026le;BMI \\u0026lt; 28 kg/m\\u0026sup2;), and obese (BMI\\u0026ge;28 kg/m\\u0026sup2;)\\u003csup\\u003e20\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eDesignated Healthcare Institution: Refers to various medical institutions reviewed and certified by the medical security department and other relevant authorities, which have signed service agreements with medical insurance agencies to provide healthcare services for insured individuals and are subject to the supervision and management of the medical insurance department\\u003csup\\u003e21\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eResident Population: Refers to all persons for whom a given area serves as their habitual place of residence, having lived there for at least six months\\u003csup\\u003e22\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData Collection\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSurvey Instruments\\u003c/p\\u003e\\n\\u003cp\\u003eGeneral Information Questionnaire\\u003c/p\\u003e\\n\\u003cp\\u003eData were collected using a self-designed questionnaire and included the following aspects: personal characteristics (gender, age, educational attainment, family medical history, etc.), behavior and lifestyle (smoking, alcohol use, physical activity, etc.), interpersonal networks (marital status, number of family members, etc.), work and living conditions (occupation, annual household income, living arrangements and designated healthcare institutions, etc.), and policy environment (medical insurance, payment methods for medical expenses, etc.).\\u003c/p\\u003e\\n\\u003cp\\u003eThe 7-item Generalized Anxiety Disorder Scale (GAD-7)\\u003c/p\\u003e\\n\\u003cp\\u003eThe GAD-7, developed by Spitzer et al.\\u003csup\\u003e23\\u003c/sup\\u003e in 2007, is a self-assessment tool for evaluating anxiety symptom severity. It contains seven items, each rated on a 0\\u0026ndash;3 scale, resulting in a total score ranging from 0 to 21, with higher scores indicating greater severity. In this study, the scale demonstrated excellent internal consistency, with a Cronbach\\u0026apos;s \\u0026alpha; of 0.903.\\u003c/p\\u003e\\n\\u003cp\\u003ePatient Health Questionnaire-9 (PHQ-9)\\u003c/p\\u003e\\n\\u003cp\\u003eThe PHQ-9\\u003csup\\u003e24\\u003c/sup\\u003e is a brief, efficient self-assessment depression scale based on the DSM-IV criteria. It consists of nine items rated on a 4-point scale (0 = not at all, 1 = several days, 2 = more than half the days, 3 = nearly every day). Total scores range from 0 to 27, with higher scores indicating a greater likelihood of depression. The Cronbach\\u0026apos;s \\u0026alpha; is 0.781.\\u003c/p\\u003e\\n\\u003cp\\u003ePittsburgh Sleep Quality Index (PSQI)\\u003c/p\\u003e\\n\\u003cp\\u003eSleep quality was assessed using the Chinese PSQI\\u003csup\\u003e25\\u003c/sup\\u003e, an 18-item scale across seven domains. Total scores range from 0 to 21, with higher scores indicating poorer sleep quality. The scale demonstrated good internal consistency in this study ( Cronbach\\u0026apos;s \\u0026alpha; of 0.760).\\u003c/p\\u003e\\n\\u003cp\\u003eSubjective Cognitive Decline Questionnaire (SCD-Q9)\\u003c/p\\u003e\\n\\u003cp\\u003eThe Chinese version of the SCD-Q9, developed by Gifford et al.\\u003csup\\u003e26\\u003c/sup\\u003e and translated by Hao Lixiao et al.\\u003csup\\u003e27\\u003c/sup\\u003e, was used to assess persistent memory decline. The questionnaire has nine items across two dimensions: overall memory capacity and temporal comparison (four items), and activities of daily living (five items). Total scores range from 0 to 9, with higher scores indicating more severe SCD. The Cronbach\\u0026apos;s \\u0026alpha; is 0.845.\\u003c/p\\u003e\\n\\u003cp\\u003ePhysical Examination\\u003c/p\\u003e\\n\\u003cp\\u003ePhysical examinations were conducted by clinic doctors from each village who had received unified training, using calibrated equipment and standardized protocols.Key measurements included height, body weight, blood pressure. BMI was calculated from height and weight.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eQuality Control\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eRigorous quality control was implemented to ensure data reliability. All personnel underwent uniform training prior to data collection. Standardized face-to-face interviews and physical examinations were conducted using uniform questionnaires and protocols. Questionnaires were checked on-site for completeness immediately after each interview, with missing items addressed promptly. Data were entered using a double-entry procedure with consistency checks; questionnaires missing \\u0026gt;10% of key variables were excluded.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStatistical Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData were collated and analyzed using SPSS Statistics version 27.0. Continuous variables are presented as mean \\u0026plusmn; standard deviation, while categorical and ordinal data are presented as \\u003cem\\u003eN\\u003c/em\\u003e (%) to describe the basic characteristics and distribution of variables. Chi-square tests and \\u003cem\\u003et\\u003c/em\\u003e-tests were used to compare demographic characteristics between groups. To systematically explore the factors influencing SCD and examine the independent contributions of factors at different levels based on the HEM theoretical framework, hierarchical binary logistic regression analysis was performed. Specifically, five nested models were constructed sequentially:\\u003c/p\\u003e\\n\\u003cp\\u003eModel 1: Included only individual characteristics layer factors (baseline model).\\u003c/p\\u003e\\n\\u003cp\\u003eModel 2: Added behavior and lifestyle layer factors to Model 1, to examine their contribution after controlling for individual characteristics.\\u003c/p\\u003e\\n\\u003cp\\u003eModel 3: Added factors in the interpersonal networks layer to Model 2.\\u003c/p\\u003e\\n\\u003cp\\u003eModel 4: Added working and living conditions layer factors to Model 3.\\u003c/p\\u003e\\n\\u003cp\\u003eModel 5: The full model, including all factors from all five layers, aiming to assess the net effect of all factors. Within each layer, variable selection was performed using the forward stepwise method, with an entry criterion of \\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;0.05.\\u003c/p\\u003e\\n\\u003cp\\u003eTo assess the robustness of the findings to the modeling approach, a parallel hierarchical multiple linear regression was performed using the continuous SCD-Q9 score as the dependent variable, following the same variable selection and hierarchical structure as described for the primary analysis.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eComparison of General Characteristics Between Hypertensive Patients\\u003c/h2\\u003e\\n \\u003cp\\u003ePearson correlation analysis and univariate analysis of factors associated with SCD scores in hypertensive patients revealed statistically significant findings (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) in relation to the following variables. Within the individual characteristics layer, age and duration of hypertension were significantly positively correlated with SCD scores (Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Additionally, sex, family history of hypertension, and presence of hypertensive complications showed statistically significant differences in SCD scores (Table \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Within the behavior and lifestyle layer, statistically significant differences in SCD scores were observed regarding alcohol drinking, physical exercise, sleep quality and regular blood pressure monitoring. In the interpersonal networks layer, number of household members showed a statistically significant difference in SCD scores. For the working and living conditions layer, significant differences were identified in annual household income,education level, depression,self-rated health status and access to designated healthcare institutions. Finally, in the policy environment layer, medical payment method showed a significant difference in SCD scores. The detailed results are presented in Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and Table \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003ePearson Correlations of Age and Hypertension Duration with SCD\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003er\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAge(years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.160\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDuration of Hypertension (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.076\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.025\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eUnivariate Analysis of Factors Associated with SCD in Hypertensive Patients\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHEM\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVariable and Category\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003eSCD score\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003et\\u003c/em\\u003e/\\u003cem\\u003eF\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"17\\\" rowspan=\\\"18\\\"\\u003e\\n \\u003cp\\u003eIndividual Characteristics Layer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSex\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e-3.142\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.14\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.62\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFamily History of Hypertension\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e-2.071\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.22\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.55\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eHypertensive Complications\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e-4.924\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.24\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.85\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eHypertension Risk Level\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.117\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.121\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eLow risk\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.32\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerate risk\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eHigh risk\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.38\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eBMI Category (kg/m\\u0026sup2;)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.073\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.975\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUnderweight\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.07\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.52\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNormal Weight\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOverweight\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eObese\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.30\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"24\\\" rowspan=\\\"25\\\"\\u003e\\n \\u003cp\\u003eBehavior and Lifestyle Layer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSmoking Status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.414\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.244\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNever Smoker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.51\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFormer Smoker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.21\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCurrent Smoker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAlcohol Drinking\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.560\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.029\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNever Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.50\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFormer Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.60\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCurrent Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePhysical Exercise\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.414\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.58\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.21\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSleep Quality (PSQI)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e9.899\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.07\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFairly Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.40\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.89\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFairly Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.18\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.73\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNumber of Antihypertensive Medications\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.691\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.598\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.39\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.80\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNone\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.27\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eRegular BP Monitoring\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e-3.321\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.12\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.63\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"7\\\" rowspan=\\\"8\\\"\\u003e\\n \\u003cp\\u003eInterpersonal Networks Layer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMarital Status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.853\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.465\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eDivorced\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.50\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eWidowed\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.66\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUnmarried\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMarried\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.41\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNumber of household members\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.183\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.029\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026le;\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.50\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026gt;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.09\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"18\\\" rowspan=\\\"19\\\"\\u003e\\n \\u003cp\\u003eWorking and Living Conditions Layer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.259\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.280\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAgriculture/Forestry/Fishery/Water Conservancy\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.44\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCommerce/Services\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eProduction/Transportation Operators\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.75\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOther Unclassifiable Occupations\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.54\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.86\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.79\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo Occupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.53\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAnnual Household Income (CNY)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e4.560\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;1000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.90\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026thinsp;~\\u0026thinsp;5000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.32\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e5000\\u0026thinsp;~\\u0026thinsp;10000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.24\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e10000\\u0026thinsp;~\\u0026thinsp;15000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.57\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026ge;\\u0026thinsp;15000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eDesignated Healthcare Institution\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e6.252\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVillage Clinic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eTownship Health Center\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.63\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCounty-level or Above Hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.70\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePrivate Clinic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eEducation Level\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.991\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eIlliterate/Semi-illiterate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.86\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePrimary School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.44\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eJunior High School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSenior High School or above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.91\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.37\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAnxiety (GAD-7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.507\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.211\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNormal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.35\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMild\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.70\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.18\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSevere\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.82\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eDepression (PHQ-9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.686\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNormal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.23\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMild\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.78\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.81\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerately Severe and Above\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.35\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSelf-Rated Health Status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e12.063\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e3.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.92\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eGood\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.55\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFair\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePoor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.79\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.94\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.01\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.85\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e\\n \\u003cp\\u003ePolicy Environment Layer\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eHealth Insurance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.429\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.240\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUrban and Rural Resident Basic Medical Insurance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.44\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUrban Employee Basic Medical Insurance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.30\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.48\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMedical Payment Method\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.819\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNew Rural Cooperative Medical Scheme\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUrban Resident Basic Medical Insurance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.81\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOut-of-Pocket\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.48\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\"±\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.92\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eMultivariate Logistic Regression Analysis of Factors Influencing SCD in Hypertensive Patients\\u003c/h2\\u003e\\n \\u003cp\\u003eUsing the presence or absence of SCD as the dependent variable, a multivariate logistic regression analysis based on hierarchical modeling was performed to analyze the influencing factors for SCD by sequentially entering different sets of independent variables. The assignment methods for the independent variables are detailed in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e.\\u003c/p\\u003e\\n \\u003cp\\u003eModel 1, Model 2, Model 3, Model 4, and Model 5 sequentially incorporated variables that were significant in the univariate analysis from the Individual Characteristics Layer, Behavior and Lifestyle Layer, Interpersonal Networks Layer, Working and Living Conditions Layer, and Policy Environment Layer, respectively. Model evaluation indicators showed that the overall explanatory power of the models continuously increased with the sequential inclusion of variables (Cox \\u0026amp; Snell \\u003cem\\u003eR\\u003c/em\\u003e\\u0026sup2; values were 0.058, 0.098, 0.098, 0.138, and 0.144, respectively), and the goodness-of-fit for all models was satisfactory (Hosmer and Lemeshow test \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05 for all), indicating that the model construction was stable and reliable.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Individual Characteristics Layer (Model 1) showed that age, sex, family history of hypertension, and hypertensive complications were all significant influencing factors. However, their effects exhibited different patterns after controlling for subsequent layers of variables. Increased age remained an independent risk factor for SCD across all models (Model 4 OR\\u0026thinsp;=\\u0026thinsp;1.037, 95% CI: 1.008\\u0026ndash;1.067; Model 5 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.036, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.006\\u0026thinsp;~\\u0026thinsp;1.067). In contrast, the effects of family history of hypertension (Model 5 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.168,95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.461\\u0026thinsp;~\\u0026thinsp;3.218) and hypertensive complications (Model 5 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3.118, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.744\\u0026thinsp;~\\u0026thinsp;5.577) remained stable across models, confirming them as strong risk factors for SCD. The effect of sex, however, weakened significantly and lost statistical significance after incorporating behavior and lifestyle factors (from Model 1 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.465, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.033 to Model 2 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.338, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.143). Duration of hypertension was not significant in any model.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Behavior and Lifestyle Layer (Model 2) showed that, after controlling for Individual Characteristics Layer variables, the introduction of factors from this layer substantially improved the model\\u0026apos;s explanatory power (\\u0026Delta;\\u003cem\\u003eR\\u003c/em\\u003e\\u0026sup2;=0.040). Among these factors, former drinker (vs. current drinker) demonstrated a stable protective effect (Model 5 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.289, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.109\\u0026thinsp;~\\u0026thinsp;0.763), while lack of physical exercise (Model 5 \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.556, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.056\\u0026thinsp;~\\u0026thinsp;2.293) and poor sleep quality (fairly good and fairly poor vs. very good) were significant risk factors for SCD. Regular blood pressure monitoring was not significant in any model.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Interpersonal Networks Layer (Model 3) showed that, after controlling for Individual Characteristics and Behavior and Lifestyle factors, number of household members was not significantly associated with SCD in any model (Model 5 \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.631), consistent with the univariate analysis results.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Working and Living Conditions Layer (Model 4) indicated that, after simultaneously controlling for Individual Characteristics, Behavior and Lifestyle, and Interpersonal Networks factors, annual household income, access to designated healthcare institutions, and depression were significant predictors of SCD. Self-rated health status was not significantly associated with SCD in any model. Compared to the high-income group (\\u0026ge;\\u0026thinsp;15000 CNY), the low-income groups (\\u0026lt;\\u0026thinsp;1000 CNY: \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3.056, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.592\\u0026thinsp;~\\u0026thinsp;5.863; 1000\\u0026thinsp;~\\u0026thinsp;5000 CNY: \\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.383, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.062\\u0026thinsp;~\\u0026thinsp;5.344) had a significantly higher risk of SCD, demonstrating the independent influence of socioeconomic factors. Regarding designated healthcare institutions, compared to those whose designated institution was a village clinic, participants using county-level or above hospitals had a significantly higher risk of SCD (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.696, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.092\\u0026thinsp;~\\u0026thinsp;2.634, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.019). Mild depression (vs. normal) was a significant risk factor (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.116, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.322\\u0026thinsp;~\\u0026thinsp;3.387). Education level was not significant in any model.\\u003c/p\\u003e\\n \\u003cp\\u003eThe Policy Environment Layer (Model 5) showed that, after controlling for all variables from the previous layers, out-of-pocket payment for medical expenses (vs. New Rural Cooperative Medical Scheme) was significantly associated with lower risk of SCD (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.360, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.139\\u0026thinsp;~\\u0026thinsp;0.931,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.035).\\u003c/p\\u003e\\n \\u003cp\\u003eThe final Model 5 showed that after including all variables from all layers, in the Individual Characteristics Layer, older age, family history of hypertension, and hypertensive complications remained significant risk factors (all \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). In the Behavior and Lifestyle Layer, former drinker, lack of physical exercise, and poor sleep quality (fairly good and fairly poor) showed statistically significant differences (all \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). In the Working and Living Conditions Layer, lower annual household income (\\u0026lt;\\u0026thinsp;1000 CNY, 1000\\u0026thinsp;~\\u0026thinsp;5000 CNY, and 10000\\u0026thinsp;~\\u0026thinsp;15000 CNY), county-level or above hospital (vs. village clinic), and mild depression remained significant predictors (all \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Self-rated health status was not significant. In the Policy Environment Layer, out-of-pocket payment for medical expenses (vs. New Rural Cooperative Medical Scheme) was significantly associated with lower risk of SCD (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.360, 95% CI: 0.139\\u0026thinsp;~\\u0026thinsp;0.931, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.035). Detailed results are presented in Table \\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea,b,c.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eVariable Assignments\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eAssignment / Definition\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eSex\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMale\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFemale\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eFamily History of Hypertension\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u0026thinsp;=\\u0026thinsp;0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHypertensive Complications\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u0026thinsp;=\\u0026thinsp;0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\n \\u003cp\\u003eAlcohol Drinking\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNever Drinker\\u0026thinsp;=\\u0026thinsp;0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFormer Drinker\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCurrent Drinker\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003eDepression (PHQ-9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNormal\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eMild\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerate\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModerately Severe and Above =\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eSevere\\u0026thinsp;=\\u0026thinsp;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\n \\u003cp\\u003eSleep Quality (PSQI)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFairly Good\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFairly Poor\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u0026thinsp;=\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRegular Blood Pressure Monitoring\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eCorrect Use of Home Blood Pressure Monitor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSelf-rated Health Status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eExcellent\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eGood\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eFair\\u0026thinsp;=\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePoor\\u0026thinsp;=\\u0026thinsp;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAnnual Household Income (CNY)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;1000\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026ndash;5000\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e5000\\u0026ndash;10000\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e10000\\u0026ndash;15000\\u0026thinsp;=\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026ge;\\u0026thinsp;15000\\u0026thinsp;=\\u0026thinsp;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDesignated Healthcare Institution\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eVillage Clinic\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eTownship Health Center\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eCounty-level or Above Hospital\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003ePrivate Clinic\\u0026thinsp;=\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOther\\u0026thinsp;=\\u0026thinsp;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003cp\\u003eNumber of household members\\u003c/p\\u003e\\n \\u003ctable float=\\\"No\\\" id=\\\"Taba\\\" border=\\\"1\\\"\\u003e\\n \\u003ctbody\\u003e\\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026le;\\u0026thinsp;2\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u0026gt;2\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003cp\\u003ePhysical Exercise\\u003c/p\\u003e\\n \\u003ctable float=\\\"No\\\" id=\\\"Tabb\\\" border=\\\"1\\\"\\u003e\\n \\u003ctbody\\u003e\\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNo\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eYes\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003cp\\u003eMedical Payment Method\\u003c/p\\u003e\\n \\u003ctable float=\\\"No\\\" id=\\\"Tabc\\\" border=\\\"1\\\"\\u003e\\n \\u003ctbody\\u003e\\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eNew Rural Cooperative Medical Scheme\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eUrban Resident Basic Medical Insurance\\u0026thinsp;=\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOut-of-Pocket\\u0026thinsp;=\\u0026thinsp;3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eOthers\\u0026thinsp;=\\u0026thinsp;4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\n \\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003ea. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Models 1\\u0026ndash;2)\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c5\\\" namest=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c10\\\" namest=\\\"c7\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003ewald\\u0026chi;\\u003c/em\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOR(\\u003c/em\\u003e95%\\u003cem\\u003eCI)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003ewald\\u0026chi;\\u003c/em\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOR(\\u003c/em\\u003e95%\\u003cem\\u003eCI)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIndividual Characteristics Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.046\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e12.987\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.047(1.021,1.073)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.048\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e12.992\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.049(1.022,1.076)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSex (Ref: Male)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.382\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.540\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.465(1.031,2.083)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.033\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.291\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e2.147\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.338(0.906,1.976)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFamily History of Hypertension (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.670\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e13.526\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.953(1.367,2.791)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.723\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e14.631\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.061(1.423,2.986)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHypertensive Complications (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.027\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e14.947\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.791(1.659,4.697)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.149\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e16.709\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e3.156(1.819,5.476)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDuration of Hypertension (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.408\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.008(0.983,1.035)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.523\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.756\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.012(0.985,1.039)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.385\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eBehavior and Lifestyle Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAlcohol Drinking (Ref: Current Drinker)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e8.971\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNever Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.969(0.548,1.714)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.914\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFormer Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-1.287\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e7.204\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.276(0.108,0.707)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.007\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePhysical Exercise(Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.465\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e6.151\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.592(1.102,2.298)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSleep Quality - PSQI (Ref: Very Good)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e17.982\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.633\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e9.952\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.883(1.271,2.790)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e11.664\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.733(1.535,4.866)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.451\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.916\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e4.266(0.547,33.273)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.166\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRegular BP Monitoring (Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.241\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.656\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.272(0.882,1.836)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.198\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eb. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Models 3\\u0026ndash;4)\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c5\\\" namest=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c10\\\" namest=\\\"c7\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003ewald\\u0026chi;\\u003c/em\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOR(\\u003c/em\\u003e95%\\u003cem\\u003eCI)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003ewald\\u0026chi;\\u003c/em\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOR(\\u003c/em\\u003e95%\\u003cem\\u003eCI)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIndividual Characteristics Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.046\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e11.620\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.047(1.020,1.075)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.037\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e6.094\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.037(1.008,1.068)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSex (Ref: Male)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.296\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e2.216\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.345(0.910,1.987)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.137\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.256\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.492\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.292(0.856,1.95)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.222\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFamily History of Hypertension (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.724\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e14.640\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.063(1.424,2.989)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.786\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e15.432\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.195(1.483,3.250)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHypertensive Complications (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.168\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e17.051\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.216(1.847,5.599)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.111\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e14.194\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e3.038(1.704,5.415)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDuration of Hypertension (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.743\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.012(0.985,1.039)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.389\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.508\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.010(0.982,1.039)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.476\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eBehavior and Lifestyle Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAlcohol Drinking (Ref: Current Drinker)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e8.783\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e8.011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNever Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.029\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.972(0.549,1.721)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.921\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.018(0.565,1.833)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.954\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFormer Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-1.272\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.026\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.28(0.109,0.718)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-1.216\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e6.051\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.296(0.112,0.781)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePhysical Exercise(Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.461\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.053\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.586(1.098,2.291)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.449\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e5.190\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.567(1.065,2.306)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSleep Quality - PSQI (Ref: Very Good)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e17.853\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e8.718\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.033\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.635\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e9.996\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.886(1.273,2.795)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.471\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e4.895\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.602(1.055,2.432)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.027\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.995\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e11.411\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.706(1.519,4.821)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.708\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e4.902\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.031(1.085,3.801)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.027\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.464\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.950\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e4.324(0.554,33.761)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.163\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.620\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e2.202\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e5.052(0.595,42.924)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.138\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRegular BP Monitoring (Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.228\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.464\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.256(0.868,1.816)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.226\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.251\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.532\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.286(0.864,1.915)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.216\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eInterpersonal Networks Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNumber of household members (Ref: \\u0026gt;2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026le;\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.156\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.474\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.169(0.749,1.824)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.491\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.109\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.195\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.115(0.687,1.810)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.659\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026gt;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWorking and Living Conditions Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAnnual Household Income, CNY (Ref: \\u0026ge;15000)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e13.504\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;1000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e1.117\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e11.284\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e3.056(1.592,5.863)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026thinsp;~\\u0026thinsp;5000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.868\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e4.439\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.383(1.062,5.344)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.035\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e5000\\u0026thinsp;~\\u0026thinsp;10000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.421\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.776\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.523(0.820,2.828)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.183\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026thinsp;~\\u0026thinsp;15000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.572\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e5.081\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.772(1.077,2.913)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.024\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eEducation Level(Ref: Senior High School or above)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e3.479\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.323\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eIlliterate/Semi-illiterate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-0.046\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.955(0.477,1.913)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.897\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrimary School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.161\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.279\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.174(0.647,2.129)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.597\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eJunior High School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.414\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.961\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.513(0.848,2.699)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.161\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDepression - PHQ-9 (Ref: Normal)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e10.077\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMild\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.750\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e9.747\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e2.116(1.322,3.387)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eModerate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.073\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.026\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.076(0.441,2.627)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.872\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSevere\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.601\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.455\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.825(0.318,10.476)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.500\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSelf-Rated Health Status (Ref: Very Poor)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e6.324\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.176\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-1.171\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.862\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.31(0.058,1.667)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.172\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eGood\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-0.083\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.038\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.921(0.401,2.115)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.845\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFair\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.299\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.712\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.348(0.673,2.701)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.399\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePoor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.427\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e1.401\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.533(0.756,3.109)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.237\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDesignated Healthcare Institution (Ref: Other)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e7.991\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.092\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVillage Clinic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.282\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.813\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.325(0.719,2.444)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.367\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eTownship Health Center\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e0.480\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e4.669\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e1.616(1.046,2.497)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eCounty-level or Above Hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-0.319\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e0.057\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.727(0.053,9.959)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.811\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrivate Clinic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\n \\u003cp\\u003e-1.141\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\n \\u003cp\\u003e2.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\n \\u003cp\\u003e0.32(0.066,1.542)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e\\n \\u003cp\\u003e0.155\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\u0026nbsp;\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003ec. Multivariate Logistic Regression Analysis of Factors Associated with SCD (Model 5)\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c5\\\" namest=\\\"c2\\\"\\u003e\\n \\u003cp\\u003eModel 5\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003ewald\\u0026chi;\\u003c/em\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOR(\\u003c/em\\u003e95%\\u003cem\\u003eCI)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIndividual Characteristics Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.036\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.712\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.036(1.006,1.067)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSex (Ref: Male)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.275\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.691\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.317(0.870,1.995)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.193\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFamily History of Hypertension (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.774\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e14.741\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.168(1.461,3.218)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eHypertensive Complications (Ref: No)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eYes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.137\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e14.705\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.118(1.744,5.577)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDuration of Hypertension (years)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.463\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.010(0.982,1.039)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.496\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eBehavior and Lifestyle Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAlcohol Drinking (Ref: Current Drinker)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e7.820\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNever Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.969(0.532,1.764)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.918\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFormer Drinker\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-1.242\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.280\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.289(0.109,0.763)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePhysical Exercise(Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.442\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.987\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.556(1.056,2.293)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.026\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSleep Quality - PSQI (Ref: Very Good)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e8.600\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.035\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.462\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.604\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.587(1.041,2.420)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.032\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFairly Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.721\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.032\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.056(1.095,3.861)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.025\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVery Poor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.601\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e2.132\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e4.956(0.578,42.476)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.144\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eRegular BP Monitoring (Ref: Yes)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.217\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.126\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.242(0.832,1.855)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.289\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eInterpersonal Networks Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eNumber of household members (Ref: \\u0026gt;2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026le;\\u0026thinsp;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.120\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.231\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.128(0.691,1.841)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.631\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026gt;2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eWorking and Living Conditions Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eAnnual Household Income, CNY (Ref: \\u0026ge;15000)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e14.354\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.006\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;1000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e1.181\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e12.355\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e3.256(1.686,6.290)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;0.001\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026thinsp;~\\u0026thinsp;5000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.908\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.712\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.479(1.092,5.626)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e5000\\u0026thinsp;~\\u0026thinsp;10000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.444\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.960\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.559(0.837,2.902)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.161\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e1000\\u0026thinsp;~\\u0026thinsp;15000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.555\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.727\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.742(1.056,2.872)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eEducation Level(Ref: Senior High School or above)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e3.886\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.274\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eIlliterate/Semi-illiterate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.053\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.022\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.948(0.472,1.905)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.881\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrimary School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.186\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.367\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.205(0.660,2.199)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.544\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eJunior High School\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.441\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e2.189\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.554(0.867,2.786)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.139\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDepression - PHQ-9 (Ref: Normal)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e9.929\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMild\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.749\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e9.578\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e2.114(1.316,3.397)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eModerate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.047\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.049(0.428,2.568)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.917\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSevere\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.599\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.433\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.821(0.305,10.855)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.511\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eSelf-Rated Health Status (Ref: Very Poor)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e6.290\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.179\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eVery Good\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e2.326\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.262(0.047,1.465)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.127\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eGood\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.952(0.413,2.194)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.908\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eFair\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.619\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.322(0.659,2.652)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.432\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePoor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.180\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.483(0.728,3.022)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.277\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eDesignated Healthcare Institution (Ref: Village Clinic)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e8.227\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.084\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eTownship Health Center\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.333\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.111\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.395(0.751,2.592)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.292\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eCounty-level or Above Hospital\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.528\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.530\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.696(1.092,2.634)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003ePrivate Clinic\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.393\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.084\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.675(0.047,9.661)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.772\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.947\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e1.331\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.388(0.078,1.938)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.249\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePolicy Environment Layer\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eMedical Payment Method (Ref: New Rural Cooperative Medical Scheme)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e5.666\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.129\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eUrban Resident Basic Medical Insurance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e0.233\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.769\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e1.263(0.75,2.128)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.381\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOut-of-Pocket\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-1.021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e4.441\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.360(0.139,0.931)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.035\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\n \\u003cp\\u003eOthers\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\n \\u003cp\\u003e-0.064\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\n \\u003cp\\u003e0.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\n \\u003cp\\u003e0.938(0.171,5.140)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\n \\u003cp\\u003e0.941\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eSensitivity Analysis: Linear Regression with the Continuous SCD Score\\u003c/h2\\u003e\\n \\u003cp\\u003eTo verify the robustness of the above findings, a linear regression analysis was conducted using the continuous SCD score as the outcome (complete results are presented in Supplementary Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). In the final adjusted model (Model 5), consistent with the logistic regression results, older age (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.030,95%\\u003cem\\u003eCI\\u003c/em\\u003e: 0.008\\u0026thinsp;~\\u0026thinsp;0.052, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.007), family history of hypertension (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.472,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.181\\u0026thinsp;~\\u0026thinsp;0.764, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.002), presence of hypertensive complications (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.490,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.148\\u0026thinsp;~\\u0026thinsp;0.831,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.005), poorer sleep quality (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.230,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.043\\u0026thinsp;~\\u0026thinsp;0.416,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.016), and utilization of county-level or above hospitals (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.497,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.148\\u0026thinsp;~\\u0026thinsp;0.831,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.005) were significantly associated with higher SCD scores. Additionally, physical exercise (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e= -0.363,95%\\u003cem\\u003eCI\\u003c/em\\u003e:-0.649~-0.077,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.013) and higher annual household income (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e= -0.171,95%\\u003cem\\u003eCI\\u003c/em\\u003e: -0.278~-0.064,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.002) were significantly associated with lower SCD scores. Self-rated health status (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.293,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.119\\u0026thinsp;~\\u0026thinsp;0.467,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and regular blood pressure monitoring (\\u003cem\\u003e\\u0026beta;\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.437,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.147\\u0026thinsp;~\\u0026thinsp;0.727,\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.003) were also significant in the linear model, though they did not reach significance in the logistic regression.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study applied the HEM and identified distinct risk and protective factors for SCD. Notably, the observed SCD prevalence of 80.58% substantially exceeded our pre-study estimate of 68%\\u003csup\\u003e12\\u003c/sup\\u003e, underscoring the pronounced burden of subjective cognitive concerns in this rural hypertensive population.This study identified multi-level risk and protective factors for SCD spanning individual characteristics, behaviors, living conditions, and policy environment. These findings confirm that SCD arises from multi-level synergies\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e, supporting the need for interventions that address individual, behavioral, and environmental determinants. Below, we interpret these findings within their respective HEM layers and, critically, explore their synergistic implications for designing integrated public health strategies.\\u003c/p\\u003e \\u003cp\\u003eIn the HEM framework, the individual characteristics layer is central and includes fixed traits such as age, sex, and genetics, forming a health determinant baseline \\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eOur findings corroborate that advanced age is a significant risk factor for subjective cognitive decline in hypertensive patients (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.036, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.006\\u0026thinsp;~\\u0026thinsp;1.067). The decline in vascular elasticity and impaired cerebral perfusion autoregulation associated with aging may act synergistically with the vascular damage induced by hypertension, collectively exacerbating cerebral small vessel disease and injuring cognition-related brain regions such as the hippocampus\\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u003c/sup\\u003e. Furthermore, another study identified three primary trajectories of cognitive function in the middle-aged and elderly population: \\\"high-stability,\\\" \\\"moderate-decline,\\\" and \\\"rapid-decline,\\\" with the \\\"moderate-decline\\\" pattern being the most prevalent\\u003csup\\u003e\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis study revealed that the presence of a family history of hypertension was a risk factor for SCD (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.168,95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.461\\u0026thinsp;~\\u0026thinsp;3.218), corresponding to an approximately 2.17-fold higher risk compared to those without such a family history. Hypertension exhibits familial aggregation\\u003csup\\u003e\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u003c/sup\\u003e. Relevant studies have shown that offspring with a family history of hypertension have an elevated probability of developing the condition\\u003csup\\u003e\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u003c/sup\\u003e. After the onset of hypertension, the rate of cognitive decline is approximately twice as fast as in those without hypertension, equivalent to an additional 83% annual deterioration compared to individuals with normal blood pressure. This effect is more pronounced in hypertensive patients after the age of 65 years\\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eHypertension can lead to various cardiovascular and cerebrovascular diseases\\u003csup\\u003e\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e. This study found that the presence of hypertensive complications was a risk factor for SCD (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3.118, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.744\\u0026thinsp;~\\u0026thinsp;5.577), indicating that the risk of SCD in patients with complications was approximately 3.12 times that of those without complications. Relevant research demonstrated that the brain is an early target organ for hypertension-induced damage, and that following a diagnosis, the rates of overall cognitive and memory decline accelerate to approximately twice that of normal aging\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e. One study confirmed that volume reduction and altered connectivity in specific hypertension-vulnerable brain regions, including the putamen, anterior thalamic radiation, anterior corona radiata, and anterior limb of the internal capsule, are associated with cognitive decline\\u003csup\\u003e\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis layer functions as a crucial link between individual characteristics and broader environmental influences within the HEM. It encompasses modifiable behavioral and lifestyle factors, such as physical activity, alcohol consumption, and sleep quality, representing a promising target for public health interventions\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eOur analysis identified alcohol abstinence as a significant protective factor against SCD in hypertensive patients(\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.289,95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.109\\u0026thinsp;~\\u0026thinsp;0.763). Longitudinal evidence indicates that although heavy alcohol consumption in midlife accelerates cognitive deterioration, individuals who adopt abstinence can experience a favorable reversal in their cognitive trajectory, ultimately reaching rates of decline comparable to those seen in never-drinkers\\u003csup\\u003e\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e\\u003c/sup\\u003e. A Mendelian randomization study provided compelling evidence that reducing alcohol consumption constitutes a causal protective behavior that significantly diminishes dementia risk\\u003csup\\u003e\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis study identified lack of physical exercise as a significant risk factor for SCD in hypertensive patients (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.556, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.056\\u0026thinsp;~\\u0026thinsp;2.293). Regular physical activity is an important behavioral factor for protecting cognitive function. It improves cerebral blood flow\\u003csup\\u003e\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e\\u003c/sup\\u003e, promotes the release of neurotrophic factors\\u003csup\\u003e\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u003c/sup\\u003e, and reduces vascular inflammation and insulin resistance\\u003csup\\u003e\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u003c/sup\\u003e. In contrast, hypertensive patients who are physically inactive experience fewer vascular health benefits, leading to a relatively higher cognitive risk\\u003csup\\u003e\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eSleep serves not only as a crucial mechanism for physical rest and recovery but also helps regulate metabolism, support immune function, facilitate brain waste clearance, and consolidate memory and cognitive processes\\u003csup\\u003e\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e\\u003c/sup\\u003e. This study identified poor sleep quality as a significant influencing factor for SCD in hypertensive patients. Compared to those with very good sleep quality, patients with fairly good sleep quality (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.587, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.041\\u0026thinsp;~\\u0026thinsp;2.420) and those with fairly poor sleep quality (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.056, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.095\\u0026thinsp;~\\u0026thinsp;3.861) had significantly higher risk of SCD. A growing body of research indicates that the glymphatic system, which is responsible for clearing metabolic waste products such as β-amyloid and tau proteins from the brain, exhibits peak activity during slow-wave sleep\\u003csup\\u003e\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e\\u003c/sup\\u003e. Consequently, disrupted sleep patterns\\u0026mdash;reflected in the poor sleep quality observed in our cohort\\u0026mdash;may impair this vital clearance mechanism. Such impairment can lead to the accumulation of neurotoxic proteins and subsequent neuronal injury, processes that are increasingly linked to the emergence of subjective cognitive complaints\\u003csup\\u003e\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e\\u003c/sup\\u003e.Research indicates that hypertensive patients with insufficient sleep (\\u0026lt;\\u0026thinsp;6 h per night) exhibit poorer executive function and more pronounced signs of brain injury, such as white matter hyperintensities\\u003csup\\u003e\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThe working and living conditions layer encompasses the immediate physical and socioeconomic environments in which individuals reside, including occupational settings, income levels, housing conditions, educational resources, and healthcare accessibility, and the HEM posits that individual health behaviors are constrained by these external living conditions\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis study confirmed that lower annual household income (\\u0026lt;\\u0026thinsp;1000 CNY) is a significant risk factor for SCD in hypertensive patients, with its effect remaining statistically significant even after adjusting for individual characteristics and behaviors. A nationally representative health survey in the United Kingdom revealed a significant socioeconomic gradient in both hypertension prevalence and underdiagnosis, specifically, lower-income groups demonstrated not only higher hypertension prevalence rates but also greater proportions of undiagnosed hypertension\\u003csup\\u003e\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e\\u003c/sup\\u003e. Furthermore, a study comprising 76 low- and middle-income countries found that while disparities in hypertension prevalence across socioeconomic groups were generally modest, the lowest socioeconomic groups exhibited higher hypertension rates in countries with higher GDP per capita\\u003csup\\u003e\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u003c/sup\\u003e. Given that hypertension is an established risk factor for SCD\\u003csup\\u003e\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e\\u003c/sup\\u003e, these income-related disparities in hypertension may consequently exert an indirect influence on SCD occurrence.\\u003c/p\\u003e \\u003cp\\u003eThis study identified depressive symptoms as a significant risk factor for SCD in hypertensive patients. Specifically, patients with mild depression had a significantly higher risk of SCD compared to those with normal status (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2.114,95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.316\\u0026thinsp;~\\u0026thinsp;3.397). Using the Behavioral Risk Factor Surveillance System, the U.S. Centers for Disease Control and Prevention determined that hypertension is an independent risk factor for SCD, and that depressive symptoms further amplify this risk\\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u003c/sup\\u003e. Another study confirmed that depressive symptoms indirectly increase the risk of SCD by reducing self-efficacy\\u003csup\\u003e\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis study identified utilization of county-level or above hospitals as a significant risk factor for SCD in hypertensive patients (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.696, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:1.092\\u0026thinsp;~\\u0026thinsp;2.634). The decision to seek care at county-level or above hospitals often conceals underlying complex health drivers\\u003csup\\u003e\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e\\u003c/sup\\u003e. These patients may have longer disease duration, suboptimal blood pressure control, or self-perceived significant neurological symptoms such as memory decline\\u003csup\\u003e\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u003c/sup\\u003e. It is precisely these more severe health conditions and more urgent healthcare needs that motivate them to overcome barriers such as distance and cost, seeking what they perceive as more authoritative and technically superior medical resources\\u003csup\\u003e\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThe Policy Environment Layer, as the outermost layer of the Health Ecological Model, encompasses macro-level factors such as healthcare policies, economic conditions, and cultural values that shape individual health outcomes\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThis study identified out-of-pocket payment for medical expenses as a significant protective factor for SCD in hypertensive patients (\\u003cem\\u003eOR\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.360, 95%\\u003cem\\u003eCI\\u003c/em\\u003e:0.139\\u0026thinsp;~\\u0026thinsp;0.931).Out-of-pocket payment refers to a payment method in which patients bear the full cost of medical expenses personally, without using any form of medical insurance reimbursement\\u003csup\\u003e\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e\\u003c/sup\\u003e.Patients who choose out-of-pocket payment may have greater financial capacity and typically enjoy better living conditions, access to higher quality healthcare services, and richer health information resource\\u0026mdash;all of which may protect cognitive function through multiple pathways\\u003csup\\u003e\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eTo assess the robustness of our primary findings, we conducted a supplementary linear regression analysis using the continuous SCD score. The results confirmed that the direction of associations for the key risk factors identified above remained consistent. This methodological convergence strengthens confidence in our conclusions. The subtle differences observed for variables such as alcohol abstinence, mild depression, and out-of-pocket payment highlight the potential for distinct factors to influence disease probability versus symptom severity, a nuance that could inform more stratified screening approaches.\\u003c/p\\u003e \\u003cp\\u003eThis study has several limitations. Its cross-sectional design precludes causal inference, and the self-reported nature of some variables may introduce recall bias. Although the number of household members from the interpersonal networks layer was included in the multivariate analysis, it was not significantly associated with SCD in the final model. Future research should employ longitudinal cohorts and incorporate objective cognitive assessments, such as neuropsychological tests, to further validate factors associated with SCD.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eIn summary, applying the HEM reveals that SCD risk among hypertensive patients is shaped by factors across individual, behavioral, living conditions, and policy environment layers. This multi-level perspective moves beyond a purely biomedical view and provides actionable targets for integrated intervention. Advanced age, family history of hypertension, and hypertensive complications were significant risk factors. Physical inactivity and poor sleep quality increased risk, whereas alcohol abstinence was protective. Socioeconomic factors\\u0026mdash;particularly lower income\\u0026mdash;along with utilization of county-level hospitals and mild depressive symptoms, independently contributed to increased risk. Out-of-pocket payment emerged as a protective factor, possibly reflecting greater financial capacity. Collectively, these findings advocate for comprehensive strategies that synergistically span clinical risk stratification, behavioral modification, and mitigation of socioeconomic and healthcare access barriers within strengthening primary care systems to preserve cognitive health in this vulnerable aging population.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors would like to thank all participants who participated in the study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eR.L. contributed to conceptualization, data curation, formal analysis, project administration, resources, and writing—review and editing. J.L. wrote the original draft and contributed to conceptualization, formal analysis, methodology, and data curation. W.S., S.L., and J.W. performed investigation and data curation. Q.N., S.L., and S.Z. provided supervision. H.Y., X.Q., H.Z., J.N., Z.Z., and J.B. contributed to conceptualization and methodology. All authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData Availability Statement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated and/or analysed during the current study are not publicly available due to privacy or ethical restrictions but are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Shanxi Medical University (Approval no. 2020SLL201), informed consent was obtained from all participants.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eChina-Gates Foundation Rural Basic Healthcare Project (Shanxi Sub-Project, No. PHC-I04);\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eShanxi Provincial Traditional Chinese Medicine (TCM) Research Project (No. 2024ZYY2D022);\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eOpen Fund from Key Laboratory of Cellular Physiology (Shanxi Medical University), Ministry of Education, China(No. CELLPHYSIOL/SXMU-2021-16);\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eProvincial Application Basis Research Plan of Shanxi under Grant (No. 201801D121314);\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eShanxi Province Higher Education “Billion Project” Science and Technology Guidance Project.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAdditional Information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eCorrespondence and requests for materials should be addressed to Ruifeng Liang.\\u003c/p\\u003e\\n\\u003cp\\u003eReprints and permissions information is available at www.nature.com/reprints.\\u003c/p\\u003e\\n\\u003cp\\u003ePublisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eWorld Health Organization. \\u003cem\\u003eGlobal report on hypertension: the race against a silent killer\\u003c/em\\u003e(World Health Organization, 2023).\\u003c/li\\u003e\\n \\u003cli\\u003eCenter for Cardiovascular Diseases \\u0026amp; The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Report on Cardiovascular Health and Diseases in China 2023: An Updated Summary. \\u003cem\\u003eBiomed. Environ. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e37\\u003c/strong\\u003e, 949-992, doi:10.3967/bes2024.162 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eJessen, F.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e The characterisation of subjective cognitive decline. \\u003cem\\u003eLancet Neurol.\\u003c/em\\u003e \\u003cstrong\\u003e19\\u003c/strong\\u003e, 271-278, doi:10.1016/s1474-4422(19)30368-0 (2020).\\u003c/li\\u003e\\n \\u003cli\\u003eWen, C.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Risk factors for subjective cognitive decline: the CABLE study. \\u003cem\\u003eTransl. Psychiatry\\u003c/em\\u003e \\u003cstrong\\u003e11\\u003c/strong\\u003e, 576, doi:10.1038/s41398-021-01711-1 (2021).\\u003c/li\\u003e\\n \\u003cli\\u003eCheng, G. R.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Prevalence and risk factors for subjective cognitive decline and the correlation with objective cognition among community-dwelling older adults in China: Results from the Hubei memory and aging cohort study. \\u003cem\\u003eAlzheimers Dement.\\u003c/em\\u003e \\u003cstrong\\u003e19\\u003c/strong\\u003e, 5074-5085, doi:10.1002/alz.13047 (2023).\\u003c/li\\u003e\\n \\u003cli\\u003eDi Chiara, T.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Pathogenetic Mechanisms of Hypertension-Brain-Induced Complications: Focus on Molecular Mediators. \\u003cem\\u003eInt. J. Mol. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e23\\u003c/strong\\u003e, doi:10.3390/ijms23052445 (2022).\\u003c/li\\u003e\\n \\u003cli\\u003eIadecola, C.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Impact of Hypertension on Cognitive Function: A Scientific Statement From the American Heart Association. \\u003cem\\u003eHypertension\\u003c/em\\u003e \\u003cstrong\\u003e68\\u003c/strong\\u003e, e67-e94, doi:10.1161/hyp.0000000000000053 (2016).\\u003c/li\\u003e\\n \\u003cli\\u003eShih, Y. H.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Hypertension Accelerates Alzheimer\\u0026apos;s Disease-Related Pathologies in Pigs and 3xTg Mice. \\u003cem\\u003eFront. Aging Neurosci.\\u003c/em\\u003e \\u003cstrong\\u003e10\\u003c/strong\\u003e, 73, doi:10.3389/fnagi.2018.00073 (2018).\\u003c/li\\u003e\\n \\u003cli\\u003eSallis, J. F., Owen, N. \\u0026amp; Fisher, E. B. in \\u003cem\\u003eHealth behavior and health education: Theory, research, and practice, 4th ed.\\u003c/em\\u003e 465-485 (Jossey-Bass/Wiley, 2008).\\u003c/li\\u003e\\n \\u003cli\\u003eWang, M. Q., Chai, H. L., Guo, Y. Y., Ren, J. J. \\u0026amp; Liang, R. F. Knowledge, attitude, and practice of hypertension prevention and control among rural residents in Shanxi Province. \\u003cem\\u003eChina Prev. Med. J.\\u003c/em\\u003e \\u003cstrong\\u003e35\\u003c/strong\\u003e, 563-569, doi:10.19485/j.cnki.issn2096-5087.2023.07.003 (2023).\\u003c/li\\u003e\\n \\u003cli\\u003eCheng, X. Y., Wang, R., Guo, Y. Y., Wang, M. Q., Chai, H. L. \\u0026amp; Liang, R. F. Risk factors for stroke and its correlation with H-type hypertension among the middle-aged and elderly in a rural area of Shanxi Province. \\u003cem\\u003ePract. Prev. Med.\\u003c/em\\u003e \\u003cstrong\\u003e31\\u003c/strong\\u003e, 1153-1158 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eSchliep, K. C.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Overall and sex-specific risk factors for subjective cognitive decline: findings from the 2015-2018 Behavioral Risk Factor Surveillance System Survey. \\u003cem\\u003eBiol Sex Differ.\\u003c/em\\u003e \\u003cstrong\\u003e13\\u003c/strong\\u003e, 16, doi:10.1186/s13293-022-00425-3 (2022).\\u003c/li\\u003e\\n \\u003cli\\u003eHongheiku Statistical Bulletin Database. \\u003cem\\u003eYangqu County Seventh National Population Census Bulletin\\u003c/em\\u003e, \\u0026lt;https://tjgb.hongheiku.com/15692.html\\u0026gt;(accessed December 18, 2025).\\u003c/li\\u003e\\n \\u003cli\\u003eHongheiku Statistical Bulletin Database. \\u003cem\\u003eDaning County Seventh National Population Census Bulletin\\u003c/em\\u003e, \\u0026lt;https://tjgb.hongheiku.com/rkpcgb/19977.html\\u0026gt; (accessed December 18, 2025).\\u003c/li\\u003e\\n \\u003cli\\u003eHongheiku Statistical Bulletin Database. \\u003cem\\u003eYonghe County Seventh National Population Census Bulletin\\u003c/em\\u003e, \\u0026lt;https://tjgb.hongheiku.com/rkpcgb/19979.html\\u0026gt;(accessed December 18, 2025).\\u003c/li\\u003e\\n \\u003cli\\u003eChang, H.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Factors Associated With the Prevalence of Hypertension Among Residents in Fujian Province: Based on the Health Ecological Model. \\u003cem\\u003eAm. J. Hypertens.\\u003c/em\\u003e \\u003cstrong\\u003e37\\u003c/strong\\u003e, 1009-1009, doi:10.1093/ajh/hpae111 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eWorld Health Organization. \\u003cem\\u003eGuidelines for controlling and monitoring the tobacco epidemic\\u003c/em\\u003e (World Health Organization, Geneva, 1998).\\u003c/li\\u003e\\n \\u003cli\\u003eJang, C. C. \\u003cem\\u003eet al\\u003c/em\\u003e\\u003cem\\u003e.\\u003c/em\\u003e Interaction of family history of hypertension and overweight/obesity on hypertension in Han and Manchu adults in Hebei province. \\u003cem\\u003eBasic Clin. Med.\\u003c/em\\u003e \\u003cstrong\\u003e43\\u003c/strong\\u003e, 1053-1059, doi:10.16352/j.issn.1001-6325.2023.07.1053 (2023).\\u003c/li\\u003e\\n \\u003cli\\u003eWorld Health Organization. \\u003cem\\u003eWHO guidelines on physical activity and sedentary behaviour\\u003c/em\\u003e. (World Health Organization, 2020).\\u003c/li\\u003e\\n \\u003cli\\u003eClinical practice guideline for the management of hypertension in China. \\u003cem\\u003eChin. Med. J.\\u003c/em\\u003e \\u003cstrong\\u003e137\\u003c/strong\\u003e, 2907-2952, doi:10.1097/cm9.0000000000003431 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eNational Healthcare Security Administration. \\u003cem\\u003eInterim Measures for the Administration of Designated Medical Institutions Providing Medical Insurance Services\\u003c/em\\u003e, \\u0026lt;https://www.gov.cn/zhengce/zhengceku/2021-01/12/content_5579285.htm\\u0026gt;(accessed December 18, 2025).\\u003c/li\\u003e\\n \\u003cli\\u003eNational Bureau of Statistics.National Bureau of Statistics website. \\u0026lt;https://www.stats.gov.cn/hd/lyzx/zxgk/202302/t20230215_1905399.html\\u0026gt;(accessed December 18, 2025).\\u003c/li\\u003e\\n \\u003cli\\u003eSpitzer, R. L., Kroenke, K., Williams, J. B. \\u0026amp; L\\u0026ouml;we, B. A brief measure for assessing generalized anxiety disorder: the GAD-7. \\u003cem\\u003eArch. Intern. Med.\\u003c/em\\u003e \\u003cstrong\\u003e166\\u003c/strong\\u003e, 1092-1097, doi:10.1001/archinte.166.10.1092 (2006).\\u003c/li\\u003e\\n \\u003cli\\u003eAmerican Psychiatric Association. \\u003cem\\u003eDiagnostic and Statistical Manual of Mental Disorders, DSM-5-TR\\u003c/em\\u003e. (2022).\\u003c/li\\u003e\\n \\u003cli\\u003eLiu, X. C.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Reliability and validity of the Pittsburgh Sleep Quality Index. \\u003cem\\u003eChin. J. Psychiatry.\\u0026nbsp;\\u003c/em\\u003e \\u003cstrong\\u003e29\\u003c/strong\\u003e, 103-107 (1996).\\u003c/li\\u003e\\n \\u003cli\\u003eGifford, K. A., Liu, D., Romano, R., 3rd, Jones, R. N. \\u0026amp; Jefferson, A. L. Development of a subjective cognitive decline questionnaire using item response theory: a pilot study. \\u003cem\\u003eAlzheimers Dement.\\u003c/em\\u003e \\u003cstrong\\u003e1\\u003c/strong\\u003e, 429-439, doi:10.1016/j.dadm.2015.09.004 (2015).\\u003c/li\\u003e\\n \\u003cli\\u003eHao, L. X., Hu, X. C., Han, Y. \\u0026amp; Jia, J. G. Localization of Subjective Cognitive Decline Questionnaire and Its Reliability and Validity Test . \\u003cem\\u003eChin. Gen. Pract.\\u003c/em\\u003e \\u003cstrong\\u003e22\\u003c/strong\\u003e, 3238-3245, doi:10.12114/j.issn.1007-9572.2019.00.045 (2019).\\u003c/li\\u003e\\n \\u003cli\\u003eXia, X., Jiang, Q., McDermott, J. \\u0026amp; Han, J. J. Aging and Alzheimer\\u0026apos;s disease: Comparison and associations from molecular to system level. \\u003cem\\u003eAging Cell\\u003c/em\\u003e \\u003cstrong\\u003e17\\u003c/strong\\u003e, e12802, doi:10.1111/acel.12802 (2018).\\u003c/li\\u003e\\n \\u003cli\\u003eZhang, H.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Group-based trajectory modelling for cognitive changes in middle-aged and older adults: A systematic review. \\u003cem\\u003eAgeing Res. Rev.\\u003c/em\\u003e \\u003cstrong\\u003e112\\u003c/strong\\u003e, 102855, doi:10.1016/j.arr.2025.102855 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eZappa, M., Golino, M., Verdecchia, P. \\u0026amp; Angeli, F. Genetics of Hypertension: From Monogenic Analysis to GETomics. \\u003cem\\u003eJ. Cardiovasc. Dev. Dis.\\u003c/em\\u003e \\u003cstrong\\u003e11\\u003c/strong\\u003e, doi:10.3390/jcdd11050154 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eTakase, M.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Associations of family history of hypertension, genetic, and lifestyle risks with incident hypertension. \\u003cem\\u003eHypertens. Res.\\u003c/em\\u003e, doi:10.1038/s41440-025-02314-9 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eChen, Q.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Trajectories of Cognitive Decline Before and After New-Onset Hypertension. \\u003cem\\u003eJ. Am. Heart Assoc.\\u003c/em\\u003e \\u003cstrong\\u003e14\\u003c/strong\\u003e, e039849, doi:10.1161/jaha.124.039849 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eClinical practice guidelines for the management of hypertension in China. \\u003cem\\u003eZhonghua Xin Xue Guan Bing Za Zhi\\u003c/em\\u003e \\u003cstrong\\u003e52\\u003c/strong\\u003e, 985-1032, doi:10.3760/cma.j.cn112148-20240709-00377 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eSiedlinski, M.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Genetic analyses identify brain structures related to cognitive impairment associated with elevated blood pressure. \\u003cem\\u003eEur. Heart J.\\u003c/em\\u003e \\u003cstrong\\u003e44\\u003c/strong\\u003e, 2114-2125, doi:10.1093/eurheartj/ehad101 (2023).\\u003c/li\\u003e\\n \\u003cli\\u003eSabia, S.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Alcohol consumption and cognitive decline in early old age. \\u003cem\\u003eNeurology\\u003c/em\\u003e \\u003cstrong\\u003e82\\u003c/strong\\u003e, 332-339, doi:10.1212/wnl.0000000000000063 (2014).\\u003c/li\\u003e\\n \\u003cli\\u003eZheng, L.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Association between alcohol consumption and incidence of dementia in current drinkers: linear and non-linear mendelian randomization analysis. \\u003cem\\u003eEClinicalMedicine\\u003c/em\\u003e \\u003cstrong\\u003e76\\u003c/strong\\u003e, 102810, doi:10.1016/j.eclinm.2024.102810 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eGkotzamanis, V., Magriplis, E. \\u0026amp; Panagiotakos, D. The effect of physical activity interventions on cognitive function of older adults: A systematic review of clinical trials. \\u003cem\\u003ePsychiatriki\\u003c/em\\u003e \\u003cstrong\\u003e33\\u003c/strong\\u003e, 291-300, doi:10.22365/jpsych.2022.060 (2022).\\u003c/li\\u003e\\n \\u003cli\\u003eZong, B., Yu, F., Li, F., Sun, P. \\u0026amp; Li, L. Beyond Fuel: Exercise-Induced Lactate as a Metabolic-Epigenetic Regulator in Central Nervous System Health and Disease. \\u003cem\\u003eBiomolecules\\u003c/em\\u003e \\u003cstrong\\u003e16\\u003c/strong\\u003e, doi:10.3390/biom16010043 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eTari, A. R., Walker, T. L., Huuha, A. M., Sando, S. B. \\u0026amp; Wisloff, U. Neuroprotective mechanisms of exercise and the importance of fitness for healthy brain ageing. \\u003cem\\u003eLancet\\u003c/em\\u003e \\u003cstrong\\u003e405\\u003c/strong\\u003e, 1093-1118, doi:10.1016/s0140-6736(25)00184-9 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eKazibwe, R.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Effect of vigorous-intensity physical activity on incident cognitive impairment in high-risk hypertension. \\u003cem\\u003eAlzheimers Dement.\\u003c/em\\u003e \\u003cstrong\\u003e20\\u003c/strong\\u003e, 4602-4612, doi:10.1002/alz.13887 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eMiao, Y.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Poor sleep health is associated with older brain age: the role of systemic inflammation. \\u003cem\\u003eeBioMedicine\\u003c/em\\u003e \\u003cstrong\\u003e120\\u003c/strong\\u003e, 105941, doi:https://doi.org/10.1016/j.ebiom.2025.105941 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eDagum, P.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e The glymphatic system clears amyloid beta and tau from brain to plasma in humans. \\u003cem\\u003eNat. Commun.\\u003c/em\\u003e \\u003cstrong\\u003e17\\u003c/strong\\u003e, 715, doi:10.1038/s41467-026-68374-8 (2026).\\u003c/li\\u003e\\n \\u003cli\\u003eLiu, X.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Surrogates of glymphatic metrics decline and coupled sleep rhythms disruption in Alzheimer\\u0026apos;s disease. \\u003cem\\u003eAlzheimers Res. Ther.\\u003c/em\\u003e, doi:10.1186/s13195-026-01962-4 (2026).\\u003c/li\\u003e\\n \\u003cli\\u003eYiallourou, S.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Short Sleep Duration and Hypertension: A Double Hit for the Brain. \\u003cem\\u003eJ. Am. Heart Assoc.\\u003c/em\\u003e \\u003cstrong\\u003e13\\u003c/strong\\u003e, e035132, doi:10.1161/jaha.124.035132 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eScholes, S., Conolly, A. \\u0026amp; Mindell, J. S. Income-based inequalities in hypertension and in undiagnosed hypertension: analysis of Health Survey for England data. \\u003cem\\u003eJ. Hypertens.\\u003c/em\\u003e \\u003cstrong\\u003e38\\u003c/strong\\u003e, 912-924, doi:10.1097/hjh.0000000000002350 (2020).\\u003c/li\\u003e\\n \\u003cli\\u003eKirschbaum, T. K.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e The Association of Socioeconomic Status With Hypertension in 76 Low- and Middle-Income Countries. \\u003cem\\u003eJ. Am. Coll. Cardiol.\\u003c/em\\u003e \\u003cstrong\\u003e80\\u003c/strong\\u003e, 804-817, doi:10.1016/j.jacc.2022.05.044 (2022).\\u003c/li\\u003e\\n \\u003cli\\u003ePi\\u0026ntilde;a-Escudero, S. D.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Subjective cognitive decline and elder mistreatment in Mexican community-dwelling older adults. \\u003cem\\u003eArch. Gerontol. Geriatr.\\u003c/em\\u003e \\u003cstrong\\u003e92\\u003c/strong\\u003e, 104242, doi:10.1016/j.archger.2020.104242 (2021).\\u003c/li\\u003e\\n \\u003cli\\u003eSu, H., Zhou, Y., Sun, Y. \\u0026amp; Cai, Y. The relationship between depression and subjective cognitive decline in older adults of China: the mediating role of general self-efficacy. \\u003cem\\u003ePsychol. Health Med.\\u003c/em\\u003e \\u003cstrong\\u003e28\\u003c/strong\\u003e, 1057-1067, doi:10.1080/13548506.2022.2125165 (2023).\\u003c/li\\u003e\\n \\u003cli\\u003eGuo, L.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Factors associated with patients\\u0026apos; healthcare-seeking behavior and related clinical outcomes under China\\u0026apos;s hierarchical healthcare delivery system. \\u003cem\\u003eFront. Public Health\\u003c/em\\u003e \\u003cstrong\\u003e12\\u003c/strong\\u003e, 1326272, doi:10.3389/fpubh.2024.1326272 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eHasan, M. J.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e Health-care-seeking behaviour in patients with hypertension: experience from a dedicated hypertension centre in Bangladesh. \\u003cem\\u003eBlood Press.\\u003c/em\\u003e \\u003cstrong\\u003e33\\u003c/strong\\u003e, 2339434, doi:10.1080/08037051.2024.2339434 (2024).\\u003c/li\\u003e\\n \\u003cli\\u003eLi, X., Zhang, L., Li, Z. \\u0026amp; Tang, W. Patient Choice and Willingness Toward Gatekeepers as First-Contact Medical Institutions in Chinese Tiered Healthcare Delivery System: A Cross-Sectional Study. \\u003cem\\u003eFront. Public Health\\u003c/em\\u003e \\u003cstrong\\u003e9\\u003c/strong\\u003e, 665282, doi:10.3389/fpubh.2021.665282 (2021).\\u003c/li\\u003e\\n \\u003cli\\u003eAniebo, C. L., Lawani, L. O. \\u0026amp; Eze, P. The Burden and Socioeconomic Inequality in Catastrophic Out-of-pocket Health Expenditure in Post-Pandemic Nigeria. \\u003cem\\u003eGlob. Soc. Welf.\\u003c/em\\u003e, doi:10.1007/s40609-025-00423-4 (2025).\\u003c/li\\u003e\\n \\u003cli\\u003eZheng, Y.\\u003cem\\u003e\\u0026nbsp;et al.\\u003c/em\\u003e The Impact of Socioeconomic Factors on Cognitive Ability in Community-Dwelling Older Adults: Mediating Effect of Social Participation and Social Support. \\u003cem\\u003eHealthcare\\u003c/em\\u003e \\u003cstrong\\u003e13\\u003c/strong\\u003e, doi:10.3390/healthcare13050551 (2025).\\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\":\"info@researchsquare.com\",\"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\":\"Primary Hypertension, Subjective Cognitive Decline, Health Ecological Model, Rural Health, Risk Factors, Protective Factors\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9110247/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9110247/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eHypertension and subjective cognitive decline (SCD) frequently co-occur, challenging healthy aging. This study aimed to identify multi-level determinants of SCD among hypertensive patients in rural China using the Health Ecological Model (HEM). We conducted a cross-sectional study with 860 hypertensive patients selected from three rural counties in Shanxi Province via multi-stage cluster random sampling. Participants were categorized into non-SCD (SCD-Q9 score\\u0026thinsp;\\u0026lt;\\u0026thinsp;5) and SCD (\\u0026ge;\\u0026thinsp;5) groups. Variables were classified into five HEM layers, and logistic regression was employed to identify associated factors. The prevalence of SCD was 80.58%. Multi-level factors were significantly associated with SCD. In the Individual Characteristics Layer, advanced age, family history of hypertension, and hypertensive complications increased risk. Within the Behavior and Lifestyle Layer, lack of physical exercise and poor sleep quality were risk factors, while alcohol abstinence was protective. In the Working and Living Conditions Layer, lower household income, utilization of county-level hospitals, and mild depression emerged as risk factors. Notably, out-of-pocket payment in the Policy Environment Layer was protective. These findings translate into actionable targets for rural primary care, advocating for integrated strategies addressing hypertension management, mental health, sleep hygiene, physical activity, and socioeconomic barriers to preserve cognitive health in this vulnerable population.\\u003c/p\\u003e\",\"manuscriptTitle\":\"A Health Ecological Model Study of Subjective Cognitive Decline Among Hypertensive Patients in Rural Shanxi, China\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-03-24 16:59:28\",\"doi\":\"10.21203/rs.3.rs-9110247/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision 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