The roles of health literacy and social support in self-management among older adults with chronic obstructive pulmonary disease in China

The roles of health literacy and social support in self-management among older adults with chronic obstructive pulmonary disease in 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 Research Article The roles of health literacy and social support in self-management among older adults with chronic obstructive pulmonary disease in China Miaoqing Zhuang, Intan Idiana Hassan, Wan Muhamad Amir W Ahmad, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8746286/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Chronic obstructive pulmonary disease (COPD) is a major chronic condition among older adults in China, associated with high morbidity and healthcare burden. Effective self-management is crucial for disease control and improved outcomes, yet many older patients struggle to maintain it due to socioeconomic, cognitive, and physical challenges. Social support and health literacy—the ability to access, understand, and use health information—are recognized as key factors influencing health behaviors, but their interplay in self-management remains unclear in this population. Objective This study aimed to examine the prevalence and associated factors of self-management among older adults with COPD in China. Furthermore, it sought to investigate the mediating role of health literacy in the relationship between social support and self-management, providing insights into the psychological mechanisms through which social resources influence health behaviors in this population. Methods and results In this cross-sectional study, a total of 219 older adults with COPD were recruited from a tertiary hospital in China. The results of the survey showed that the current state of self-management among patients with COPD generally indicates a moderate level, with a mean score of (130.62 ± 20.70). After adjusting for potential confounders, participants residing in rural areas had significantly lower self-management scores compared to those in urban areas ( β = -6.531, p < 0.05). In contrast, patients receiving home oxygen therapy demonstrated a higher self-management score ( β = 7.748, p < 0.05). Additionally, each one-unit increase in health literacy was associated with a 4.473 point increase in self-management ( β = 4.473, p < 0.001), and a one-unit increase in social support corresponded to a 1.052 point increase ( β = 1.052, p < 0.001). Pearson correlation analysis revealed that both health literacy ( r = 0.501, p < 0.01) and social support ( r = 0.500, p < 0.01) were significantly positively correlated with self-management. Furthermore, mediation analysis showed that health literacy partially mediated the association between social support and self-management, accounting for 61.08% of the total effect. Conclusion Self-management was suboptimal among older adults with COPD in China. Factors such as residence, home oxygen therapy, health literacy, and social support were significantly associated with self-management. Notably, health literacy partially mediated the association between social support and self-management, highlighting its role as both a direct contributor and a psychological mechanism linking social resources to health behaviors. older adults chronic obstructive pulmonary disease self-management health literacy social support associated factors mediation effect Figures Figure 1 Introduction Chronic obstructive pulmonary disease (COPD), the third leading cause of global mortality, disproportionately affects low- and middle-income countries, where over 90% of the estimated 384 million cases reside (GBD 2019 Diseases and Injuries Collaborators, 2019; Zhuang et al., 2025 ). Numerous studies have identified a range of modifiable and non-modifiable risk factors for COPD. Notably, in China, prevalence rates exceed 27% among individuals aged 60 and above, rising to 35.5% in those aged 70 and older (Agusti et al., 2023). Given this substantial burden, Boers (2023) emphasized that preventing COPD in older adults should be a key objective for mitigating the disease’s future global impact. Patients with COPD face a high risk of recurrence, significantly exacerbating the global health burden (Qi et al., 2023). As recurrent events are associated with higher mortality and more severe health impairments (Richie et al., 2023), enhancing patient self-management capabilities is widely recognized as a crucial strategy for reducing exacerbation frequency (Cannon et al., 2016 ). Effective self-management programs—encompassing smoking cessation, regular exercise, nutritional guidance, and proper medication use—play a vital role in lowering recurrence risk (Russell et al., 2018 ). For example, improved awareness and adherence to maintenance therapy have been shown to significantly reduce acute exacerbations and enhance quality of life (Religioni et al., 2015). Furthermore, a review by Schrijver (2022) suggests that strengthening self-management skills, such as recognizing and responding to early symptoms and effectively managing daily activities, is essential for preventing recurrence. There is also a consensus that non-pharmacological interventions, particularly lifestyle modifications, are important modifiable factors for controlling COPD progression and alleviating its future global burden (ur Rehman et al., 2020 ). Consequently, promoting self-management among COPD patients is considered a critical objective for mitigating the condition's long-term impact. However, patient engagement in self-management is a major determinant of the effectiveness of medical management in preventing COPD exacerbations and other adverse outcomes (Shnaigat et al., 2021). Self-management generally refers to the active role patients play in managing their condition, encompassing symptom monitoring, adherence to treatment plans, lifestyle modifications, and seeking appropriate medical care (Dineen-Griffin et al., 2019 ). A substantial and growing body of literature indicates that self-management behaviors and persistence after diagnosis are often inadequate among COPD patients (Chapple et al., 2019; Wiratmo et al., 2025; van et al., 2019). These findings highlight the need for clinicians, healthcare systems, and other stakeholders (e.g., payers) to prioritize improving self-management in this population. Undoubtedly, a crucial step in developing effective self-management strategies is first understanding the current status, associated factors, and the mediating role of health literacy in the relationship between social support and self-management among older adults with COPD. Although several studies have explored self-management behaviors and persistence in COPD patients (Wang et al., 2016 ; Yadav et al., 2020 ; Lan et al., 2022 ), they have not specifically focused on older adults. Furthermore, self-management is of particular importance in this older population. A recent systematic review identified negative factors affecting self-management in older COPD patients, including lack of disease knowledge and misunderstanding of symptoms, low self-efficacy (confidence in performing self-management tasks such as pulmonary rehabilitation exercises and inhaler techniques), inadequate social support, emotional distress (e.g., anxiety and depression), and financial hardship (Disler et al., 2012 ). Meanwhile, inadequate self-management behaviors have been found to be alarmingly prevalent among older adults with other chronic conditions, such as diabetes mellitus and hypertension (Sadeghi et al., 2024 ). Additionally, older COPD patients are more likely to have comorbid chronic conditions (e.g., hypertension, history of cardiac comorbidities, diabetes) (Dos Santos et al., 2022 ; Chen et al., 2015 ), meaning they must manage multiple health needs simultaneously. This places a greater burden on their self-management capacity, further challenging their ability to adhere to complex regimens and increasing the risk of adverse health outcomes when self-management fails. However, little is known about the prevalence and associated sociodemographic and clinical factors of self-management among older adults with COPD. Moreover, the underlying mechanisms through which social support influences self-management remain poorly understood, particularly the potential mediating role of health literacy. Therefore, this study aims to examine the current level of self-management, identify associated sociodemographic and clinical factors, and explore the mediating role of health literacy in the relationship between social support and self-management among older adults with COPD in Xi’an, Shaanxi Province, China. Methods Study design We conducted a cross-sectional study from May 2025 to July 2025. The study was approved by the ethics committee of a tertiary hospitals (Shaanxi Provincial Hospital of Traditional Chinese Medicine) before the initiation of this study. Participants Participants were recruited using a systematic sampling method from a tertiary hospital in Xi'an, Shaanxi Province, China. They were eligible for inclusion based on the following criteria: being aged 60 years or older; diagnosed with COPD based on post-bronchodilator spirometry showing an FEV 1 / FVC ratio < 0.7, in accordance with the clinical and functional criteria outlined in the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2025 guidelines; having a stable condition defined as no acute exacerbation within the past 4 weeks and ≤ 1 acute exacerbation in the past 6 months; having a medical history of more than 1 year; and being able to read Chinese and communicate in Mandarin Chinese or the local Xi'an dialect. We excluded the following patients who: had psychiatric illness or deafness, aphasia, or other language barriers; had cognitive impairment (Mini-Mental State Examination score ≤ 17 [for illiterate] or ≤ 20 [individuals with 1–6 years of education] or ≤ 24 [for individuals with 7 or more years of education]). Sample size calculation Sample size estimation was conducted using G*Power software (version 3.1.9.7; Faul, Erdfelder, Lang, & Buchner, 2007 ) to determine the required sample for detecting a small effect size in the primary outcome. A two-tailed independent t-test was assumed, with an effect size (Cohen’s d) of 0.2 (Lee, D. K., 2016), a significance level (α) of 0.05, and a desired statistical power (1-β) of 0.80. Based on these parameters, the estimated minimum sample size was 199 participants. To account for a potential dropout rate of 15%, the final target sample size was increased to 235. Survey instrument The study protocol included one set of demographic questions and three validated instruments—the Self-Management Scale (CSMS) (Zhou et al., 2022), Chronic Obstructive Pulmonary Disease Knowledge Questionnaire (COPD-Q) (Maples et al., 2010 ), and Social Support Rating Scale (SSRS) (Xiao et al., 2010 ). Demographic data were self-reported by the participants and included gender, age, marital status, educational level, duration of disease, living conditions, payment method for medical expenses, per-capita monthly household income, occupation status, family history, complications, home oxygen therapy, use inhaled medications, residence, and smoke. The Self-Management Scale (CSMS) is a validated instrument designed to assess the self-management capabilities of patients with COPD during the stable phase in community settings (Zhou et al., 2022). The scale, developed in Chinese (Mandarin), comprises 39 items rated on a 5-point Likert scale (1 = “Never” to 5 = “Always”), yielding a total score range of 39–195, with higher scores reflecting better self-management performance. It is structured across three domains: disease symptom management (15 items: e.g., symptom recognition, medication adherence, lung function monitoring), daily life management (14 items: e.g., smoking cessation, dietary control, breathing exercises), and psychosocial management (10 items: e.g., emotional regulation, utilization of social support, goal setting). Total scores are categorized into three levels: low (39–84), moderate (85–139), and high (140–195). The CSMS has demonstrated strong psychometric properties. Content validity was high, with item-level content validity indices (I-CVI) ranging from 0.941 to 1.000 and a scale-level content validity index (S-CVI) of 0.985. Exploratory factor analysis identified three underlying factors, accounting for 71.534% of the total variance. Confirmatory factor analysis indicated a good model fit (χ²/df = 2.36, RMSEA = 0.032, CFI = 0.956). The scale also exhibited excellent internal consistency (Cronbach’s α = 0.979) and split-half reliability (0.985), supporting its reliability and construct validity for use in community-based COPD populations. The Chronic Obstructive Pulmonary Disease Questionnaire (COPD-Q), developed by the University of Tennessee in 2009, is a 13-item instrument designed to assess disease-specific knowledge and health literacy in patients with COPD (Maples et al., 2010 ). Derived from a literature review and refined by 23 experts from an initial pool of 21 items, it covers prevention, symptoms, treatment, and risk factors, with 8 positively and 5 negatively worded questions. Responses include “Yes”, “No”, and “Don't know”, and scoring is adjusted so that correct answers receive 1 point, yielding a total score of 0–13, with higher scores indicating better knowledge. The scale demonstrates acceptable psychometric properties (Cronbach’s α = 0.72, test-retest = 0.90). It has been translated into Spanish and Chinese, with the Spanish version showing good internal consistency (α = 0.85), strong item agreement (kappa > 0.6), and excellent retest reliability (ICC = 0.84) in 59 patients (Puente-Maestu et al., 2016). Studies in Chinese populations (Cao, 2014 ; Wang et al., 2014 ) have applied the COPD-Q to evaluate the impact of health literacy on self-management. Due to its brevity and clarity, it is a practical tool for assessing patient understanding, particularly among older adults with limited endurance. The Social Support Rating Scale (SSRS), developed by Yuan Xiaoshui in 1986, is a comprehensive instrument designed to assess individuals’ levels of social support (Xiao et al., 2010 ). The scale consists of 10 items measuring three dimensions: Subjective Support (items 1, 3, 4, 5), reflecting perceived emotional care; Objective Support (items 2, 6, 7), assessing tangible assistance; and Utilization of Support (items 8, 9, 10), evaluating how individuals access available resources. Scoring varies: items 1–4 and 8–10 are rated 1–4 points; item 5 (with sub-items A–E) is scored 1–4 per item, with the scores summed; items 6 and 7 receive 0 for “no sources” or 1 point for each source endorsed. Total scores are interpreted as follows: below 20 indicates low support, 20–30 moderate support, and above 30 satisfactory support. The Chinese version demonstrates strong psychometric properties (Cronbach’s α = 0.890–0.940, test-retest reliability = 0.920), supporting its reliability and applicability across diverse populations. Data collection procedure Data were collected through a structured, questionnaire-guided interview approach. Written informed consent was obtained from all participants before they completed the questionnaire. The study was carried out in full compliance with the ethical principles outlined in the Declaration of Helsinki. Participants were clearly informed that their involvement was voluntary and that they could withdraw at any stage without facing any pressure, coercion, or negative consequences. The questionnaires were administered to individuals receiving care in the respiratory ward or outpatient clinic during the study period, with each participant taking approximately 20 minutes to complete the survey. A total of 235 hospitalized patients with COPD were approached for participation. To ensure impartiality and effective communication, 5 trained health professionals fluent in the local language and unaffiliated with the study hospital were recruited to distribute and collect the questionnaires. Prior to data collection, these personnel received comprehensive training to ensure familiarity with the survey instrument and standardized administration procedures. For participants who were illiterate or had visual impairments, the research team read each question aloud verbatim from the questionnaire, and responses were recorded directly by the interviewer. Upon completion, all questionnaires were collected immediately and reviewed for completeness; any missing or unclear responses were followed up with the participant as necessary. Statistical analysis All statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS), version 27. Data were first checked for accuracy, explored for distribution patterns, and cleaned to address missing or inconsistent entries. Descriptive statistics were used to summarize categorical variables as frequencies and percentages, and continuous variables as means with standard deviations (Mean ± SD). The prevalence of self-management levels (high, moderate, low) was determined using the previously defined cutoff scores and reported as proportions within the sample. The 95% confidence intervals (CIs) for these proportions were calculated using exact binomial methods. Self-management ability as the dependent variable. For univariate analyses, independent samples t -tests or one-way analysis of variance (ANOVA) were employed as appropriate, depending on the number of groups being compared. To identify factors independently associated with moderate self-management, multivariate linear regression analyses were performed. Results are presented as standardized or unstandardized regression coefficients ( β ), along with corresponding variance inflation factors (VIF) to assess multicollinearity. Pearson correlation analysis was conducted to examine the interrelationships among variables. The mediating effect of health literacy in the relationship between social support and self-management was assessed using the PROCESS macro. Furthermore, structural equation modeling (SEM) was performed using Amos 28.0, and the goodness-of-fit and significance of the mediation model were evaluated through the Bootstrap method. A p -value of less than 0.05 was considered statistically significant for all tests. Results Characteristics of participants A total of 235 older adults with COPD were approached, of whom 219 agreed to participate and were enrolled in the study, yielding a response rate of 93.2%. The majority of participants were male (141 [64.4%]), resided in urban areas (154 [70.3%]), married (204 [93.2%]), lived with their spouse (158 [72.1%]), and had no family history of COPD (194 [88.6%]). Among the 219 participants, nearly half were public servants in enterprises or institutions (119 [54.3%]), had a monthly per-capita household income of ¥3,001–4,999 (122 [55.7%]), used resident medical insurance (118 [53.9%]), and reported comorbidities (112 [51.1%]). Approximately one-third had a disease duration of 3–6 years (71 [32.4%]) and had quit smoking due to COPD (81 [37.0%]), while nearly 30% had attained a senior secondary or junior college education (63 [28.8%]). The mean age of the participants was (68.26 ± 6.84) years. Additionally, 53.0% received home oxygen therapy, and 69.4% used inhaled medications. The baseline characteristics of the study participants are summarized in Table 1 . Table 1 Demographic characteristics of total participants (N = 219). Variable n (%) or (Mean ± SD) Gender Male 141 64.4 Female 78 35.6 Age, y 68.26 ± 6.84 Residence City 154 70.3 Rural areas 65 29.7 Marital status Married 204 93.2 Unmarried 2 0.9 Divorced 2 0.9 widowed 11 5.0 Educational level Illiteracy 32 14.6 Primary school 36 16.4 Junior school 60 27.4 Senior secondary and junior college 63 28.8 Bachelor degree or above 28 12.8 Occupation Worker 27 12.3 peasant 53 24.2 Public servants of enterprises and institutions 119 54.3 Individual 20 9.1 Living conditions Living with children 33 15.1 Living with spouse 158 72.1 Living alone 28 12.8 Monthly household income per capita, ¥ a ≤1,500 47 21.5 1,500–3,000 11 5.0 3,001–4999 122 55.7 ≥5000 39 17.8 Payment methods Self-pay 2 0.9 Urban medical insurance 96 43.8 Resident medical insurance 118 53.9 Commercial insurance 3 1.4 Duration of disease Less than 2 years 61 27.9 3–6 years 71 32.4 7–9 years 42 19.2 10 years or more 45 20.5 Family history Yes 19 8.7 No 194 88.6 Unclear 6 2.7 Complications Yes 112 51.1 No 107 48.9 Home oxygen therapy Yes 116 53.0 No 103 47.0 Use inhaled medications Yes 152 69.4 No 67 30.6 Smoke Currently smoking 35 16.0 Quit smoking 81 37.0 Never smoked 103 47.0 a As of 14 August 2025, 1¥ = 0.1387 US $ . Participants’ self-management Of the 219 responding participants, the current state of self-management among patients with COPD generally indicates a moderate level, with a mean score of (130.62 ± 20.70). Specifically, 32.3% of participants demonstrated high self-management skills, while the majority, 143 participants (62.4%), reported moderate self-management. Additionally, a small percentage (0.9%) exhibited low self-management. Detailed self-management characteristics of the participants are presented in Table 2 . Table 2 Self-management among patients. CSMS score Mean ± SD Low self-management no.(%) Moderate self-management no.(%) High self-management no.(%) Disease symptom management 44.57 ± 11.54 22 (10.0) 153 (69.9) 44 (20.1) Daily life management 50.86 ± 7.99 1 (0.5) 115 (52.5) 103 (47.0) Psychosocial management 35.19 ± 8.52 5 (2.3) 100 (45.7) 114 (52.1) Overall Self-management 130.62 ± 20.70 2 (0.9) 143 (62.4) 74 (32.3) Relationship of moderate self-management with related factors Table 3 shows the univariate analysis of the factors associated with moderate self-management, which are as follows: gender ( p = 0.043), residence ( p = 0.022), marital status ( p = 0.016), educational level ( p < 0.001), home oxygen therapy ( p < 0.001), use inhaled medications ( p = 0.002), smoke ( p = 0.037), health literacy score ( p < 0.001), and social support score ( p < 0.001). Table 3 Relationship of moderate self-management with related factors. Variable n Mean ± SD t / F p Gender -2.034 0.043 Male 141 128.52 ± 19.602 Female 78 134.41 ± 22.123 Age, y 0.131 0.877 ≤70 141 130.84 ± 20.370 71–79 62 130.76 ± 21.358 ≥80 16 128.06 ± 21.898 Residence 2.312 0.022 City 154 132.69 ± 19.835 Rural areas 65 125.69 ± 21.932 Marital status 3.529 0.016 Married 204 129.78 ± 20.519 Unmarried 2 126.50 ± 16.263 Divorced 2 117.00 ± 4.243 Widowed 11 149.27 ± 17.596 Educational level 7.734 0.000 Illiteracy 32 147.13 ± 18.556 Primary school 36 123.92 ± 22.319 Junior school 60 127.33 ± 18.905 Senior secondary and junior college 63 131.48 ± 15.684 Bachelor degree or above 28 135.46 ± 25.093 Occupation 0.836 0.475 Worker 27 128.70 ± 22.047 Peasant 53 128.06 ± 24.092 Public servants of enterprises and institutions 119 132.64 ± 18.626 Individual 20 127.95 ± 21.017 Living conditions 0.424 0.655 Living with children 33 149.42 ± 29.650 Living with spouse 158 130.28 ± 18.562 Living alone 28 133.89 ± 19.843 Monthly household income per capita, ¥ a 1.926 0.126 ≤1,500 47 131.74 ± 24.026 1,500–3,000 11 120.18 ± 14.804 3,001–4999 121 132.52 ± 20.182 ≥5000 39 126.26 ± 18.320 Payment methods 2.202 0.089 Self-pay 2 112.00 ± 2.824 Urban medical insurance 96 132.80 ± 21.403 Resident medical insurance 118 129.73 ± 20.017 Commercial insurance 3 108.00 ± 4.359 Duration of disease 1.840 0.141 Less than 2 years 61 132.38 ± 20.080 3–6 years 71 133.89 ± 20.814 7–9 years 42 125.86 ± 23.290 10 years or more 45 127.51 ± 17.921 Family history 2.693 0.070 Yes 19 125.42 ± 28.457 No 194 131.62 ± 19.782 Unclear 6 114.50 ± 13.065 Complications -1.907 0.058 Yes 112 128.03 ± 19.588 No 107 133.32 ± 21.521 Home oxygen therapy -4.572 0.000 Yes 116 124.85 ± 20.076 No 103 137.11 ± 19.473 Use inhaled medications -3.217 0.002 Yes 152 127.36 ± 17.975 No 67 138.01 ± 24.356 Smoke 3.359 0.037 Currently smoking 35 125.14 ± 22.247 Quit smoking 81 128.37 ± 17.363 Never smoked 103 134.24 ± 22.022 Health literacy score 219 7.10 ± 1.501 8.526 0.000 Social support score 219 42.18 ± 5.235 9.701 0.000 Correlation among health literacy, social support, and self-management in older adults with COPD In older adults with COPD, health literacy was positively correlated with social support ( p < 0.01, r = 0.557); health literacy was positively correlated with self-management ( p < 0.01, r = 0.501); self-management was positively correlated with social support ( p < 0.01, r = 0.550). See Table 4 . Table 4 Relationship among health literacy, social support and self-management of patients with COPD. Variable Health literacy Social support Self-management Health literacy 1 Social support 0.557** 1 Self-management 0.501** 0.550** 1 **. p < 0.01. Risk factors for moderate self-management All variables demonstrating statistical significance ( p < 0.05) in the univariate analysis were included in the subsequent multiple linear regression model (independent variable coding is detailed in Table 5). The results of the multivariable analysis are presented in Table 6. The regression analysis revealed that residence, home oxygen therapy, health literacy score, and social support score were significantly associated with self-management levels. Together, these four independent variables account for 44.9% of the variance in self-management. The overall model was statistically significant, as indicated by the F -test ( F = 18.887, p < 0.05). After adjusting for other factors, individuals residing in rural areas exhibited a mean decrease of 6.531 points in self-management score compared to their urban counterparts ( β = -6.531). Conversely, patients receiving home oxygen therapy showed a mean increase of 7.748 points in self-management relative to those not receiving such therapy ( β = 7.748). Furthermore, each one-unit increase in health literacy score was associated with a 4.473 point rise in self-management ( β = 4.473), while a one-unit increase in social support score corresponded to a 1.052 point increase in self-management ( β = 1.052). Table 5 Multiple linear regression of self-management of patients with COPD Code Variable Scoring Y Self-management Continuous variable X 1 Gender Male: 1 point, Female: 2 points X 2 Residence City: 1 point, Rural areas: 2 points X 3 Marital status Married: 1 point, Unmarried: 2 points, Divorced: 3 points, Widowed: 4 points X 4 Educational level Illiterate: 1 point, Primary school: 2 points, Junior school: 3 points, Senior secondary and junior college: 4 points, Bachelor degree or above: 5 points X 5 Home oxygen therapy Yes: 1 point, No: 2 points X 6 Use inhaled medications Yes: 1 point, No: 2 points X 7 Smoke Currently smoking: 1 point, Quit smoking: 2 points, Never smoked: 3 points Table 6 Factors associated with moderate self-management using multiple linear regression. Item B S.E. Beta t p VIF Constant 46.152 12.361 3.734 0.000 Gender -0.657 3.048 -0.015 -0.216 0.830 1.897 Residence -6.531 2.628 -0.145 -2.485 0.014 1.283 Marital status 1.317 1.707 0.044 0.771 0.441 1.209 Educational level -1.861 0.966 -0.112 -1.926 0.055 1.280 Home oxygen therapy 7.748 2.457 0.187 3.154 0.002 1.338 Use inhaled medications 3.790 2.716 0.085 1.395 0.164 1.395 Smoke 2.402 1.845 0.085 1.302 0.194 1.617 Health literacy score 4.473 0.884 0.325 5.059 0.000 1.561 Social support score 1.052 0.262 0.266 4.011 0.000 1.671 B, unstandardized coefficient B; SE, standard error; Beta, standardized coefficient Beta; t , t-statistic ; p , p -value; VIF, Collinearity Statistics VIF. Significance taken at p < 0.05. Mediating effect analysis of health literacy between social support and self-management in COPD patients Mediation structural equation model A mediation model was constructed based on multiple regression analysis (Fig. 1), comprising two latent variables: social support (measured by three observed variables: subjective support, objective support, and utilization of support) and self-management (measured by three observed variables: disease symptom management, daily life management, and psychosocial management), with health literacy serving as the mediating variable. Model fit indices indicated an acceptable fit: χ²/df = 1.841, p < 0.05; GFI = 0.950; AGFI = 0.909; CFI = 0.931; and RMSEA = 0.062 (< 0.08). These results suggest that the model is well-fitted and provides a solid basis for further analysis. Analysis of mediation effect results The model was further tested using the Bootstrap method, and the 95% confidence intervals (CIs) for the direct effect, indirect effect, and total effect of social support on quality of life did not include 0, indicating that both the direct and indirect effects are statistically significant. The results demonstrate that coping styles partially mediate the relationship between social support and quality of life, with the mediation effect accounting for 61.08% of the total effect, as shown in Table 7. Table 7 Multiple mediation effects and their effect sizes Path β S.E. 95% CI Direct effect 1.507 0.257 [1.001, 2.012] Indirect effect 0.628 0.171 [0.305, 0.985] Total effect 2.135 0.226 [1.689, 2.581] β, Standardized Path Coefficient; SE, standard error. Discussion Analysis of the current status and influencing factors of self-management in older adults with COPD To the best of our knowledge, this cross-sectional study is the first to comprehensively assess self-management levels among older adults with COPD in Xi’an, Shaanxi Province, China. The overall self-management level was moderate (130.62 ± 20.70), with only 32.3% of the 219 participants exhibiting high self-management skills, while the majority (62.4%) demonstrated moderate levels and a small but notable proportion (0.9%) showed low capacity. Compared to previous studies reporting higher self-management in more general COPD populations—often including younger individuals—our findings suggest relatively lower performance, likely due to our focus on adults aged 60 years and older. Age has been identified as an independent factor influencing self-management, with older patients facing greater challenges in adhering to complex regimens and maintaining health behaviors, even after adjusting for comorbidities and socioeconomic factors (Schulman-Green et al., 2016 ). Beyond multimorbidity and polypharmacy, multiple age-related barriers may contribute to suboptimal self-management, including cognitive decline, limited health literacy, physical and sensory impairments, social isolation, reduced access to digital health tools, and diminished self-efficacy (Doyle et al., 2019; Lorig & Holman, 2003 ). These findings highlight the need for targeted, age-sensitive interventions to strengthen self-management capacity and improve long-term outcomes in this vulnerable population. Meanwhile, residence was found to be a significant predictor of self-management among older adults with COPD. Individuals residing in rural areas exhibited lower self-management scores compared to their urban counterparts. This disparity is consistent with previous study indicating that rural residents with chronic conditions often face greater barriers to effective disease management (Golembiewski et al., 2022). Factors such as limited access to healthcare services, scarcity of health education resources, and inadequate availability of pulmonary rehabilitation and follow-up care may contribute to poorer self-management in rural settings. Moreover, reduced exposure to reliable health information may lead to misconceptions about medications or inhaler use, further impairing adherence and proactive symptom monitoring (Hew et al., 2019). Therefore, when developing interventions to enhance self-management in COPD, the urban-rural divide must be explicitly considered. Notably, older adults in rural areas often lack access to digital health tools, transportation, and specialist pulmonary care-challenges that are compounded by age-related physical and cognitive limitations (Rony et al., 2024 ). These findings highlight residence as a key social determinant of health and underscore the need for geographically targeted, context-sensitive strategies to support self-management among underserved rural populations with COPD. Among the factors examined, home oxygen therapy emerged as a significant correlate of self-management in older adults with COPD. Our findings indicate that patients receiving home oxygen therapy demonstrated higher levels of self-management compared to those not receiving such therapy. This may be attributed to the structured support and regular clinical follow-up that often accompany oxygen therapy prescriptions, which can enhance patients’ disease understanding, symptom monitoring, and confidence in managing their condition. These results align with previous studies suggesting that patients on more comprehensive treatment regimens tend to engage more actively in self-care behaviors, particularly when these are integrated with educational and monitoring components (Riegel et al., 2021). A possible explanation is that the routine use of medical devices at home increases health awareness and reinforces daily self-management practices (Grönvall et al., 2013). In contrast, Liddy et al. ( 2014 ) reported that complex treatment regimens were associated with reduced self-management in patients with multiple chronic conditions. This discrepancy may reflect differences in patient populations-our study focused specifically on older adults with COPD who may benefit from the routine and support associated with oxygen therapy, whereas broader chronic disease cohorts may experience treatment burden as a barrier. Another important finding was that higher levels of social support were positively associated with better self-management among patients with COPD. This finding is consistent with previous study on self-management in elderly individuals with chronic conditions (Chen et al., 2017 ), which have shown that patients who perceive strong social support from family, friends, or healthcare providers tend to engage more actively in disease management compared to those with limited support. Our results align with the work of Dilworth (2014), who emphasized that patients’ perceptions and psychosocial context—such as trust in care networks and perceived support—can significantly influence health behaviors. Furthermore, COPD patients have reported that lack of emotional or practical support, as well as feelings of isolation, are key barriers to maintaining consistent self-management practices (Ahola et al., 2013). Therefore, it is essential for healthcare professionals to recognize social support not merely as a background factor, but as an integral component of care. Interventions should aim to strengthen patients’ support systems by involving family members, promoting peer support groups, and ensuring continuity of care, thereby enhancing patients’ confidence and motivation to manage their condition effectively. Overall, the most important clinically relevant finding was that health literacy is significantly associated with self-management in patients with COPD. In this context, health literacy refers to the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make informed decisions about their health (Ratzan et al., 2001). According to this finding, lower levels of health literacy are strongly associated with poorer self-management behaviors. This result is consistent with previous studies in chronic disease populations (Papadakos et al., 2018; Geboers et al., 2016 ), which suggest that individuals with limited health literacy may struggle to understand treatment plans, interpret medication instructions, or navigate healthcare systems (Sudore et al., 2009), and may also face barriers in accessing preventive services (Stormacq et al., 2019 ). Given that health literacy is considered a key modifiable determinant of health disparities across socioeconomic groups (Svendsen et al., 2020), future interventions should prioritize tailored strategies that account for varying levels of health literacy to effectively support self-management among older adults with COPD. Analysis of the relationship among health literacy, social support, and self-management in older adults with COPD This study reveals a significant positive correlation among health literacy, social support, and self-management in elderly patients with COPD, forming a dynamically reinforcing “golden triangle” that plays a crucial role in chronic disease management. Health literacy serves as the cognitive foundation, promoting self-management by enhancing individuals’ ability to understand health information and make informed decisions, which supports the core role of the “knowledge-attitude-practice” (KAP) model in chronic illness care (Zhou et al., 2025 ). Meanwhile, social support not only directly strengthens self-management through emotional, instrumental, and informational assistance, but also indirectly improves health literacy by lowering barriers to accessing and comprehending health-related information, aligning with the “resource empowerment” framework (Kirkman et al., 1999). The findings further highlight a bidirectional interaction: individuals with higher health literacy are more likely to actively seek and utilize social resources, while underutilization of available support suggests the need to enhance health empowerment to promote patient engagement. This triadic synergy is consistent with previous research, which has consistently reported significant positive associations among health literacy, social support, and self-management in various chronic disease populations, underscoring the generalizability of their interdependent roles in long-term management (Dinh et al., 2023). However, excessive support may lead to functional dependency, emphasizing the importance of fostering “supportive autonomy” (Benita et al., 2014 ). In conclusion, clinical interventions should integrate family involvement, community resources, and educational initiatives to build a stratified and coordinated support system, transforming these interrelationships into tangible improvements in quality of life for elderly COPD patients. This study, using structural equation modeling, reveals a dual-path mechanism through which health literacy operates between social support and self-management: it partially mediates the relationship (accounting for 61.08%) by enabling social support to enhance patients’ understanding and application of health information, thus serving as a “cognitive bridge” that transforms external resources into internal self-management capacity; meanwhile, social support also exerts a significant direct effect (38.92%) by promoting self-management behaviors through instrumental assistance and emotional encouragement, forming a dual model of “indirect transformation” and “direct facilitation”. This pattern of partial mediation contrasts with findings from Mak et al., who observed full mediation by health beliefs in the pathway from social support to self-care capacity, a difference likely attributable to population characteristics - our sample may include more individuals with higher educational attainment (e.g., junior high school or above), who are better able to directly translate social support into action, whereas Mak et al.’s study focused on rural patients with limited educational resources, for whom health beliefs may represent the primary cognitive pathway (Mak et al., 2009 ). This suggests that the mediation mechanism is moderated by sociocultural and socioeconomic factors, highlighting the need for stratified interventions tailored to patients’ health literacy levels. Future research should employ longitudinal or experimental designs to verify causality and explore how digital health technologies might extend and strengthen these pathways. Strengths and limitation A key strength of this study lies in its provision of valuable insights, to the best of our knowledge, into the current status and associated factors of self-management among older adults with COPD in Xi'an, Shaanxi Province, China, by utilizing standardized assessment scales. More importantly, our findings reveal a significant mediating role of health literacy in the relationship between social support and self-management, shedding light on the psychological mechanism through which social resources translate into improved health behaviors. It is noteworthy that older adults with COPD are frequently excluded from research; this study, therefore, focuses on a population that has long been overlooked, laying a crucial foundation for the future development and implementation of targeted interventions aimed at enhancing their self-management capabilities. However, this study has limitations that are worth considering. First, information on self-management was collected for the previous months prior to the survey, so some degree of recall bias cannot be ruled out. This could lead to inaccurate estimations of the prevalence of inadequate self-management among COPD patients. Additionally, the data relied on self-reported practices of self-management, which might have been over- or under-reported by participants. Second, the study was limited in scope. Participants were from a tertiary hospital in Xi'an, Shaanxi Province, China, which limits its generalizability to broader regions in China. Third, this was a cross-sectional study. Therefore, associations between inadequate self-management and risk factors among COPD patients cannot necessarily be considered causal relationships. Furthermore, although we identified health literacy as a partial mediator in the relationship between social support and self-management, the cross-sectional design also restricts our ability to infer directional or causal pathways in this mediation process. Longitudinal or interventional studies are needed to confirm the temporal sequence and stability of this mediating effect. Abbreviations ANOVA Analysis of variance CI Confidence intervals COPD Chronic Obstructive Pulmonary Disease COPD-Q Chronic Obstructive Pulmonary Disease Knowledge Questionnaire CSMS Self-Management Scale GOLD Chronic Obstructive Lung Disease KAP Knowledge-attitude-practice SEM Structural equation modeling SPSS Statistical Package for the Social Sciences SSRS Social Support Rating Scale VIF Variance inflation factors Declarations Ethics approval and consent to participate This study was reviewed and approved by the Ethics Committee of the Shaanxi Provincial Hospital of Traditional Chinese Medicine (Approval No.: AF/SC-04/01.2). Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Youth Talent Support Program of the Xi’an Association for Science and Technology (Grant No. 0959202513139) and the Regular Project of the Shaanxi Provincial Sports Bureau (Grant No. 20250368). Authors' contributions IIH and AAK conceived and proposed the idea. WMAWA and MZ designed the work. MZ, YG, FL, YT and JY contributed to the data collection. MZ and XL contributed to data analysis and the interpretation of data for the work. MZ wrote the first draft of the manuscript. IIH, AAK, and WMAWA helped revise the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the physicians and nurses of the departments of respiratory at the a hospital visited for this study for their valuable support and cooperation in conducting this study. The authors are also particularly grateful to the contributions of the patients who participated in this research. Finally, the authors would like to thank Scribendi for their professional proofreading of this manuscript. Authors' information School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia College of Nursing and Rehabilitation, Xi'an Jiaotong University City College, Xi'an, China School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia Shaanxi Provincial Hospital of Traditional Chinese Medicine, Xi'an, China The Second Affiliated Hospital of Xi'an Medical University, Xi'an, China Corresponding author: Intan Idiana Hassan, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. Email: [email protected] References GBD 2019 Chronic Respiratory Diseases Collaborators. Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019. EClinicalMedicine. 2023;59:101936. 10.1016/j.eclinm.2023.101936 . 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Patient and health professional's perceived barriers to the delivery of psychosocial care to adults with cancer: a systematic review. Psycho-oncology. 2014;23(6):601–12. Ahola AJ, Groop PH. Barriers to self-management of diabetes. Diabet Med. 2013;30(4):413–20. Ratzan SC. Health literacy: communication for the public good. Health Promot Int. 2001;16(2):207–14. Papadakos, J. K., Hasan, S. M., Barnsley, J., Berta, W., Fazelzad, R., Papadakos,C. J., … Howell, D. (2018). Health literacy and cancer self-management behaviors:a scoping review. Cancer, 124(21), 4202–4210. Geboers B, de Winter AF, Spoorenberg SL, Wynia K, Reijneveld SA. The association between health literacy and self-management abilities in adults aged 75 and older, and its moderators. Qual Life Res. 2016;25(11):2869–77. Sudore RL, Schillinger D. Interventions to improve care for patients with limited health literacy. J Clin outcomes management: JCOM. 2009;16(1):20. Stormacq C, Van den Broucke S, Wosinski J. 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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-8746286","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616670856,"identity":"3e621baa-479d-408a-962c-e8a79483bc0d","order_by":0,"name":"Miaoqing Zhuang","email":"","orcid":"","institution":"Universiti Sains Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Miaoqing","middleName":"","lastName":"Zhuang","suffix":""},{"id":616670857,"identity":"3f06ac43-40d1-48ed-bfec-52af1db37fe8","order_by":1,"name":"Intan Idiana 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social support and self-management\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8746286/v1/7a9531c1d4e4751bb826a431.png"},{"id":106414908,"identity":"3609fee2-0e0e-410c-99c8-c0819fa3a79a","added_by":"auto","created_at":"2026-04-08 10:30:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1628782,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8746286/v1/fc5c894a-0b0f-440d-85d2-95a0682b9e7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The roles of health literacy and social support in self-management among older adults with chronic obstructive pulmonary disease in China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic obstructive pulmonary disease (COPD), the third leading cause of global mortality, disproportionately affects low- and middle-income countries, where over 90% of the estimated 384\u0026nbsp;million cases reside (GBD 2019 Diseases and Injuries Collaborators, 2019; Zhuang et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Numerous studies have identified a range of modifiable and non-modifiable risk factors for COPD. Notably, in China, prevalence rates exceed 27% among individuals aged 60 and above, rising to 35.5% in those aged 70 and older (Agusti et al., 2023). Given this substantial burden, Boers (2023) emphasized that preventing COPD in older adults should be a key objective for mitigating the disease\u0026rsquo;s future global impact.\u003c/p\u003e \u003cp\u003ePatients with COPD face a high risk of recurrence, significantly exacerbating the global health burden (Qi et al., 2023). As recurrent events are associated with higher mortality and more severe health impairments (Richie et al., 2023), enhancing patient self-management capabilities is widely recognized as a crucial strategy for reducing exacerbation frequency (Cannon et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Effective self-management programs\u0026mdash;encompassing smoking cessation, regular exercise, nutritional guidance, and proper medication use\u0026mdash;play a vital role in lowering recurrence risk (Russell et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For example, improved awareness and adherence to maintenance therapy have been shown to significantly reduce acute exacerbations and enhance quality of life (Religioni et al., 2015). Furthermore, a review by Schrijver (2022) suggests that strengthening self-management skills, such as recognizing and responding to early symptoms and effectively managing daily activities, is essential for preventing recurrence. There is also a consensus that non-pharmacological interventions, particularly lifestyle modifications, are important modifiable factors for controlling COPD progression and alleviating its future global burden (ur Rehman et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Consequently, promoting self-management among COPD patients is considered a critical objective for mitigating the condition's long-term impact.\u003c/p\u003e \u003cp\u003eHowever, patient engagement in self-management is a major determinant of the effectiveness of medical management in preventing COPD exacerbations and other adverse outcomes (Shnaigat et al., 2021). Self-management generally refers to the active role patients play in managing their condition, encompassing symptom monitoring, adherence to treatment plans, lifestyle modifications, and seeking appropriate medical care (Dineen-Griffin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A substantial and growing body of literature indicates that self-management behaviors and persistence after diagnosis are often inadequate among COPD patients (Chapple et al., 2019; Wiratmo et al., 2025; van et al., 2019). These findings highlight the need for clinicians, healthcare systems, and other stakeholders (e.g., payers) to prioritize improving self-management in this population.\u003c/p\u003e \u003cp\u003eUndoubtedly, a crucial step in developing effective self-management strategies is first understanding the current status, associated factors, and the mediating role of health literacy in the relationship between social support and self-management among older adults with COPD. Although several studies have explored self-management behaviors and persistence in COPD patients (Wang et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yadav et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), they have not specifically focused on older adults. Furthermore, self-management is of particular importance in this older population. A recent systematic review identified negative factors affecting self-management in older COPD patients, including lack of disease knowledge and misunderstanding of symptoms, low self-efficacy (confidence in performing self-management tasks such as pulmonary rehabilitation exercises and inhaler techniques), inadequate social support, emotional distress (e.g., anxiety and depression), and financial hardship (Disler et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Meanwhile, inadequate self-management behaviors have been found to be alarmingly prevalent among older adults with other chronic conditions, such as diabetes mellitus and hypertension (Sadeghi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, older COPD patients are more likely to have comorbid chronic conditions (e.g., hypertension, history of cardiac comorbidities, diabetes) (Dos Santos et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), meaning they must manage multiple health needs simultaneously. This places a greater burden on their self-management capacity, further challenging their ability to adhere to complex regimens and increasing the risk of adverse health outcomes when self-management fails. However, little is known about the prevalence and associated sociodemographic and clinical factors of self-management among older adults with COPD. Moreover, the underlying mechanisms through which social support influences self-management remain poorly understood, particularly the potential mediating role of health literacy. Therefore, this study aims to examine the current level of self-management, identify associated sociodemographic and clinical factors, and explore the mediating role of health literacy in the relationship between social support and self-management among older adults with COPD in Xi\u0026rsquo;an, Shaanxi Province, China.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study from May 2025 to July 2025. The study was approved by the ethics committee of a tertiary hospitals (Shaanxi Provincial Hospital of Traditional Chinese Medicine) before the initiation of this study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited using a systematic sampling method from a tertiary hospital in Xi'an, Shaanxi Province, China. They were eligible for inclusion based on the following criteria: being aged 60 years or older; diagnosed with COPD based on post-bronchodilator spirometry showing an FEV\u003csub\u003e1\u003c/sub\u003e / FVC ratio\u0026thinsp;\u0026lt;\u0026thinsp;0.7, in accordance with the clinical and functional criteria outlined in the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2025 guidelines; having a stable condition defined as no acute exacerbation within the past 4 weeks and \u0026le;\u0026thinsp;1 acute exacerbation in the past 6 months; having a medical history of more than 1 year; and being able to read Chinese and communicate in Mandarin Chinese or the local Xi'an dialect. We excluded the following patients who: had psychiatric illness or deafness, aphasia, or other language barriers; had cognitive impairment (Mini-Mental State Examination score\u0026thinsp;\u0026le;\u0026thinsp;17 [for illiterate] or \u0026le;\u0026thinsp;20 [individuals with 1\u0026ndash;6 years of education] or \u0026le;\u0026thinsp;24 [for individuals with 7 or more years of education]).\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eSample size estimation was conducted using G*Power software (version 3.1.9.7; Faul, Erdfelder, Lang, \u0026amp; Buchner, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) to determine the required sample for detecting a small effect size in the primary outcome. A two-tailed independent t-test was assumed, with an effect size (Cohen\u0026rsquo;s d) of 0.2 (Lee, D. K., 2016), a significance level (α) of 0.05, and a desired statistical power (1-β) of 0.80. Based on these parameters, the estimated minimum sample size was 199 participants. To account for a potential dropout rate of 15%, the final target sample size was increased to 235.\u003c/p\u003e\n\u003ch3\u003eSurvey instrument\u003c/h3\u003e\n\u003cp\u003eThe study protocol included one set of demographic questions and three validated instruments\u0026mdash;the Self-Management Scale (CSMS) (Zhou et al., 2022), Chronic Obstructive Pulmonary Disease Knowledge Questionnaire (COPD-Q) (Maples et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and Social Support Rating Scale (SSRS) (Xiao et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDemographic data were self-reported by the participants and included gender, age, marital status, educational level, duration of disease, living conditions, payment method for medical expenses, per-capita monthly household income, occupation status, family history, complications, home oxygen therapy, use inhaled medications, residence, and smoke.\u003c/p\u003e \u003cp\u003eThe Self-Management Scale (CSMS) is a validated instrument designed to assess the self-management capabilities of patients with COPD during the stable phase in community settings (Zhou et al., 2022). The scale, developed in Chinese (Mandarin), comprises 39 items rated on a 5-point Likert scale (1 = \u0026ldquo;Never\u0026rdquo; to 5 = \u0026ldquo;Always\u0026rdquo;), yielding a total score range of 39\u0026ndash;195, with higher scores reflecting better self-management performance. It is structured across three domains: disease symptom management (15 items: e.g., symptom recognition, medication adherence, lung function monitoring), daily life management (14 items: e.g., smoking cessation, dietary control, breathing exercises), and psychosocial management (10 items: e.g., emotional regulation, utilization of social support, goal setting). Total scores are categorized into three levels: low (39\u0026ndash;84), moderate (85\u0026ndash;139), and high (140\u0026ndash;195).\u003c/p\u003e \u003cp\u003eThe CSMS has demonstrated strong psychometric properties. Content validity was high, with item-level content validity indices (I-CVI) ranging from 0.941 to 1.000 and a scale-level content validity index (S-CVI) of 0.985. Exploratory factor analysis identified three underlying factors, accounting for 71.534% of the total variance. Confirmatory factor analysis indicated a good model fit (χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;2.36, RMSEA\u0026thinsp;=\u0026thinsp;0.032, CFI\u0026thinsp;=\u0026thinsp;0.956). The scale also exhibited excellent internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.979) and split-half reliability (0.985), supporting its reliability and construct validity for use in community-based COPD populations.\u003c/p\u003e \u003cp\u003eThe Chronic Obstructive Pulmonary Disease Questionnaire (COPD-Q), developed by the University of Tennessee in 2009, is a 13-item instrument designed to assess disease-specific knowledge and health literacy in patients with COPD (Maples et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Derived from a literature review and refined by 23 experts from an initial pool of 21 items, it covers prevention, symptoms, treatment, and risk factors, with 8 positively and 5 negatively worded questions. Responses include \u0026ldquo;Yes\u0026rdquo;, \u0026ldquo;No\u0026rdquo;, and \u0026ldquo;Don't know\u0026rdquo;, and scoring is adjusted so that correct answers receive 1 point, yielding a total score of 0\u0026ndash;13, with higher scores indicating better knowledge. The scale demonstrates acceptable psychometric properties (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.72, test-retest\u0026thinsp;=\u0026thinsp;0.90). It has been translated into Spanish and Chinese, with the Spanish version showing good internal consistency (α\u0026thinsp;=\u0026thinsp;0.85), strong item agreement (kappa\u0026thinsp;\u0026gt;\u0026thinsp;0.6), and excellent retest reliability (ICC\u0026thinsp;=\u0026thinsp;0.84) in 59 patients (Puente-Maestu et al., 2016). Studies in Chinese populations (Cao, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) have applied the COPD-Q to evaluate the impact of health literacy on self-management. Due to its brevity and clarity, it is a practical tool for assessing patient understanding, particularly among older adults with limited endurance.\u003c/p\u003e \u003cp\u003eThe Social Support Rating Scale (SSRS), developed by Yuan Xiaoshui in 1986, is a comprehensive instrument designed to assess individuals\u0026rsquo; levels of social support (Xiao et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The scale consists of 10 items measuring three dimensions: Subjective Support (items 1, 3, 4, 5), reflecting perceived emotional care; Objective Support (items 2, 6, 7), assessing tangible assistance; and Utilization of Support (items 8, 9, 10), evaluating how individuals access available resources. Scoring varies: items 1\u0026ndash;4 and 8\u0026ndash;10 are rated 1\u0026ndash;4 points; item 5 (with sub-items A\u0026ndash;E) is scored 1\u0026ndash;4 per item, with the scores summed; items 6 and 7 receive 0 for \u0026ldquo;no sources\u0026rdquo; or 1 point for each source endorsed. Total scores are interpreted as follows: below 20 indicates low support, 20\u0026ndash;30 moderate support, and above 30 satisfactory support. The Chinese version demonstrates strong psychometric properties (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.890\u0026ndash;0.940, test-retest reliability\u0026thinsp;=\u0026thinsp;0.920), supporting its reliability and applicability across diverse populations.\u003c/p\u003e\n\u003ch3\u003eData collection procedure\u003c/h3\u003e\n\u003cp\u003eData were collected through a structured, questionnaire-guided interview approach. Written informed consent was obtained from all participants before they completed the questionnaire. The study was carried out in full compliance with the ethical principles outlined in the Declaration of Helsinki. Participants were clearly informed that their involvement was voluntary and that they could withdraw at any stage without facing any pressure, coercion, or negative consequences. The questionnaires were administered to individuals receiving care in the respiratory ward or outpatient clinic during the study period, with each participant taking approximately 20 minutes to complete the survey. A total of 235 hospitalized patients with COPD were approached for participation. To ensure impartiality and effective communication, 5 trained health professionals fluent in the local language and unaffiliated with the study hospital were recruited to distribute and collect the questionnaires. Prior to data collection, these personnel received comprehensive training to ensure familiarity with the survey instrument and standardized administration procedures. For participants who were illiterate or had visual impairments, the research team read each question aloud verbatim from the questionnaire, and responses were recorded directly by the interviewer. Upon completion, all questionnaires were collected immediately and reviewed for completeness; any missing or unclear responses were followed up with the participant as necessary.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS), version 27. Data were first checked for accuracy, explored for distribution patterns, and cleaned to address missing or inconsistent entries. Descriptive statistics were used to summarize categorical variables as frequencies and percentages, and continuous variables as means with standard deviations (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). The prevalence of self-management levels (high, moderate, low) was determined using the previously defined cutoff scores and reported as proportions within the sample. The 95% confidence intervals (CIs) for these proportions were calculated using exact binomial methods. Self-management ability as the dependent variable. For univariate analyses, independent samples \u003cem\u003et\u003c/em\u003e-tests or one-way analysis of variance (ANOVA) were employed as appropriate, depending on the number of groups being compared. To identify factors independently associated with moderate self-management, multivariate linear regression analyses were performed. Results are presented as standardized or unstandardized regression coefficients (\u003cem\u003eβ\u003c/em\u003e), along with corresponding variance inflation factors (VIF) to assess multicollinearity. Pearson correlation analysis was conducted to examine the interrelationships among variables. The mediating effect of health literacy in the relationship between social support and self-management was assessed using the PROCESS macro. Furthermore, structural equation modeling (SEM) was performed using Amos 28.0, and the goodness-of-fit and significance of the mediation model were evaluated through the Bootstrap method. A \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 was considered statistically significant for all tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of participants\u003c/h2\u003e \u003cp\u003eA total of 235 older adults with COPD were approached, of whom 219 agreed to participate and were enrolled in the study, yielding a response rate of 93.2%. The majority of participants were male (141 [64.4%]), resided in urban areas (154 [70.3%]), married (204 [93.2%]), lived with their spouse (158 [72.1%]), and had no family history of COPD (194 [88.6%]). Among the 219 participants, nearly half were public servants in enterprises or institutions (119 [54.3%]), had a monthly per-capita household income of \u0026yen;3,001\u0026ndash;4,999 (122 [55.7%]), used resident medical insurance (118 [53.9%]), and reported comorbidities (112 [51.1%]). Approximately one-third had a disease duration of 3\u0026ndash;6 years (71 [32.4%]) and had quit smoking due to COPD (81 [37.0%]), while nearly 30% had attained a senior secondary or junior college education (63 [28.8%]). The mean age of the participants was (68.26\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84) years. Additionally, 53.0% received home oxygen therapy, and 69.4% used inhaled medications. The baseline characteristics of the study participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Demographic characteristics of total participants (N\u0026thinsp;=\u0026thinsp;219).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(%) or (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.26\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliteracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior secondary and junior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epeasant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic servants of enterprises and institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly household income per capita, \u0026yen;\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;1,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1,500\u0026ndash;3,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3,001\u0026ndash;4999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePayment methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-pay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban medical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResident medical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommercial insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome oxygen therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse inhaled medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuit smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e As of 14 August 2025, 1\u0026yen; = 0.1387 US\u003cspan\u003e$\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u0026rsquo; self-management\u003c/h2\u003e \u003cp\u003eOf the 219 responding participants, the current state of self-management among patients with COPD generally indicates a moderate level, with a mean score of (130.62\u0026thinsp;\u0026plusmn;\u0026thinsp;20.70). Specifically, 32.3% of participants demonstrated high self-management skills, while the majority, 143 participants (62.4%), reported moderate self-management. Additionally, a small percentage (0.9%) exhibited low self-management. Detailed self-management characteristics of the participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Self-management among patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSMS score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003eself-management\u003c/p\u003e \u003cp\u003eno.(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003eself-management\u003c/p\u003e \u003cp\u003eno.(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eself-management\u003c/p\u003e \u003cp\u003eno.(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease symptom management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e44.57\u0026thinsp;\u0026plusmn;\u0026thinsp;11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153 (69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44 (20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily life management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e50.86\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103 (47.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychosocial management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e35.19\u0026thinsp;\u0026plusmn;\u0026thinsp;8.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e114 (52.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Self-management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e130.62\u0026thinsp;\u0026plusmn;\u0026thinsp;20.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e143 (62.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRelationship of moderate self-management with related factors\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the univariate analysis of the factors associated with moderate self-management, which are as follows: gender (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043), residence (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022), marital status (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), educational level (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), home oxygen therapy (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), use inhaled medications (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), smoke (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), health literacy score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and social support score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Relationship of moderate self-management with related factors.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e/\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.52\u0026thinsp;\u0026plusmn;\u0026thinsp;19.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e134.41\u0026thinsp;\u0026plusmn;\u0026thinsp;22.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.877\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e130.84\u0026thinsp;\u0026plusmn;\u0026thinsp;20.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e71\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e130.76\u0026thinsp;\u0026plusmn;\u0026thinsp;21.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.06\u0026thinsp;\u0026plusmn;\u0026thinsp;21.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e132.69\u0026thinsp;\u0026plusmn;\u0026thinsp;19.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e125.69\u0026thinsp;\u0026plusmn;\u0026thinsp;21.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e129.78\u0026thinsp;\u0026plusmn;\u0026thinsp;20.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e126.50\u0026thinsp;\u0026plusmn;\u0026thinsp;16.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e117.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e149.27\u0026thinsp;\u0026plusmn;\u0026thinsp;17.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliteracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e147.13\u0026thinsp;\u0026plusmn;\u0026thinsp;18.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e123.92\u0026thinsp;\u0026plusmn;\u0026thinsp;22.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e127.33\u0026thinsp;\u0026plusmn;\u0026thinsp;18.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior secondary and junior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e131.48\u0026thinsp;\u0026plusmn;\u0026thinsp;15.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e135.46\u0026thinsp;\u0026plusmn;\u0026thinsp;25.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.70\u0026thinsp;\u0026plusmn;\u0026thinsp;22.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeasant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.06\u0026thinsp;\u0026plusmn;\u0026thinsp;24.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic servants of enterprises and institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e132.64\u0026thinsp;\u0026plusmn;\u0026thinsp;18.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e127.95\u0026thinsp;\u0026plusmn;\u0026thinsp;21.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e149.42\u0026thinsp;\u0026plusmn;\u0026thinsp;29.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e130.28\u0026thinsp;\u0026plusmn;\u0026thinsp;18.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e133.89\u0026thinsp;\u0026plusmn;\u0026thinsp;19.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly household income per capita, \u0026yen;\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;1,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e131.74\u0026thinsp;\u0026plusmn;\u0026thinsp;24.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1,500\u0026ndash;3,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e120.18\u0026thinsp;\u0026plusmn;\u0026thinsp;14.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3,001\u0026ndash;4999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e132.52\u0026thinsp;\u0026plusmn;\u0026thinsp;20.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e126.26\u0026thinsp;\u0026plusmn;\u0026thinsp;18.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePayment methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-pay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e112.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban medical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e132.80\u0026thinsp;\u0026plusmn;\u0026thinsp;21.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResident medical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e129.73\u0026thinsp;\u0026plusmn;\u0026thinsp;20.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommercial insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e108.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e132.38\u0026thinsp;\u0026plusmn;\u0026thinsp;20.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;6 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e133.89\u0026thinsp;\u0026plusmn;\u0026thinsp;20.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e125.86\u0026thinsp;\u0026plusmn;\u0026thinsp;23.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 years or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e127.51\u0026thinsp;\u0026plusmn;\u0026thinsp;17.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e125.42\u0026thinsp;\u0026plusmn;\u0026thinsp;28.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e131.62\u0026thinsp;\u0026plusmn;\u0026thinsp;19.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e114.50\u0026thinsp;\u0026plusmn;\u0026thinsp;13.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.03\u0026thinsp;\u0026plusmn;\u0026thinsp;19.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e133.32\u0026thinsp;\u0026plusmn;\u0026thinsp;21.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome oxygen therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e124.85\u0026thinsp;\u0026plusmn;\u0026thinsp;20.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e137.11\u0026thinsp;\u0026plusmn;\u0026thinsp;19.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse inhaled medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e127.36\u0026thinsp;\u0026plusmn;\u0026thinsp;17.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e138.01\u0026thinsp;\u0026plusmn;\u0026thinsp;24.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e125.14\u0026thinsp;\u0026plusmn;\u0026thinsp;22.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuit smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.37\u0026thinsp;\u0026plusmn;\u0026thinsp;17.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e134.24\u0026thinsp;\u0026plusmn;\u0026thinsp;22.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth literacy score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e42.18\u0026thinsp;\u0026plusmn;\u0026thinsp;5.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation among health literacy, social support, and self-management in older adults with COPD\u003c/h2\u003e \u003cp\u003eIn older adults with COPD, health literacy was positively correlated with social support (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.557); health literacy was positively correlated with self-management (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.501); self-management was positively correlated with social support (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.550). See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cdiv\u003e\n \u003cdiv align=\"left\" colname=\"c1\" colnum=\"1\"\u003e\u0026nbsp;\u003c/div\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eRelationship among health literacy, social support and self-management of patients with COPD.\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\u003eHealth literacy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eSelf-management\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\u003eHealth literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.557**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSelf-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.501**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.550**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e**. \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eRisk factors for moderate self-management\u003c/h2\u003e\n \u003cp\u003eAll variables demonstrating statistical significance (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) in the univariate analysis were included in the subsequent multiple linear regression model (independent variable coding is detailed in Table 5). The results of the multivariable analysis are presented in Table 6. The regression analysis revealed that residence, home oxygen therapy, health literacy score, and social support score were significantly associated with self-management levels. Together, these four independent variables account for 44.9% of the variance in self-management. The overall model was statistically significant, as indicated by the \u003cem\u003eF\u003c/em\u003e-test (\u003cem\u003eF\u003c/em\u003e = 18.887, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n \u003cp\u003eAfter adjusting for other factors, individuals residing in rural areas exhibited a mean decrease of 6.531 points in self-management score compared to their urban counterparts (\u003cem\u003eβ\u003c/em\u003e = -6.531). Conversely, patients receiving home oxygen therapy showed a mean increase of 7.748 points in self-management relative to those not receiving such therapy (\u003cem\u003eβ\u003c/em\u003e = 7.748). Furthermore, each one-unit increase in health literacy score was associated with a 4.473 point rise in self-management (\u003cem\u003eβ\u003c/em\u003e = 4.473), while a one-unit increase in social support score corresponded to a 1.052 point increase in self-management (\u003cem\u003eβ\u003c/em\u003e = 1.052).\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMultiple linear regression of self-management of patients with COPD\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\u003eCode\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eScoring\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\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSelf-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eContinuous variable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eMale: 1 point, Female: 2 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCity: 1 point, Rural areas: 2 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e3\u003c/sub\u003e\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\n \u003cp\u003eMarried: 1 point, Unmarried: 2 points, Divorced: 3 points, Widowed: 4 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eEducational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIlliterate: 1 point, Primary school: 2 points, Junior school: 3 points, Senior secondary and junior college: 4 points, Bachelor degree or above: 5 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHome oxygen therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eYes: 1 point, No: 2 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUse inhaled medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eYes: 1 point, No: 2 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eX\u003csub\u003e7\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCurrently smoking: 1 point, Quit smoking: 2 points, Never smoked: 3 points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"char\" char=\".\" colname=\"c2\" colnum=\"2\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFactors associated with moderate self-management using multiple linear regression.\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\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eVIF\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\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e46.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e12.361\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\u003e3.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e-0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-6.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e-2.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEducational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e-1.861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e-1.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHome oxygen therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e7.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e3.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.338\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUse inhaled medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth literacy score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e5.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial support score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e4.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eB, unstandardized coefficient B; SE, standard error; Beta, standardized coefficient Beta; \u003cem\u003et\u003c/em\u003e, \u003cem\u003et-statistic\u003c/em\u003e; \u003cem\u003ep\u003c/em\u003e, \u003cem\u003ep\u003c/em\u003e-value; VIF, Collinearity Statistics VIF. Significance taken at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eMediating effect analysis of health literacy between social support and self-management in COPD patients\u003c/h2\u003e\n \u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eMediation structural equation model\u003c/h2\u003e\n \u003cp\u003eA mediation model was constructed based on multiple regression analysis (Fig. 1), comprising two latent variables: social support (measured by three observed variables: subjective support, objective support, and utilization of support) and self-management (measured by three observed variables: disease symptom management, daily life management, and psychosocial management), with health literacy serving as the mediating variable. Model fit indices indicated an acceptable fit: χ²/df = 1.841, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; GFI = 0.950; AGFI = 0.909; CFI = 0.931; and RMSEA = 0.062 (\u0026lt; 0.08). These results suggest that the model is well-fitted and provides a solid basis for further analysis.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eAnalysis of mediation effect results\u003c/h2\u003e\n \u003cp\u003eThe model was further tested using the Bootstrap method, and the 95% confidence intervals (CIs) for the direct effect, indirect effect, and total effect of social support on quality of life did not include 0, indicating that both the direct and indirect effects are statistically significant. The results demonstrate that coping styles partially mediate the relationship between social support and quality of life, with the mediation effect accounting for 61.08% of the total effect, as shown in Table 7.\u003c/p\u003e\n \u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMultiple mediation effects and their effect sizes\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\u003ePath\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e95% CI\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\u003eDirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e[1.001, 2.012]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e[0.305, 0.985]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e[1.689, 2.581]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026beta;, Standardized Path Coefficient; SE, standard error. \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the current status and influencing factors of self-management in older adults with COPD\u003c/h2\u003e \u003cp\u003eTo the best of our knowledge, this cross-sectional study is the first to comprehensively assess self-management levels among older adults with COPD in Xi\u0026rsquo;an, Shaanxi Province, China. The overall self-management level was moderate (130.62\u0026thinsp;\u0026plusmn;\u0026thinsp;20.70), with only 32.3% of the 219 participants exhibiting high self-management skills, while the majority (62.4%) demonstrated moderate levels and a small but notable proportion (0.9%) showed low capacity. Compared to previous studies reporting higher self-management in more general COPD populations\u0026mdash;often including younger individuals\u0026mdash;our findings suggest relatively lower performance, likely due to our focus on adults aged 60 years and older. Age has been identified as an independent factor influencing self-management, with older patients facing greater challenges in adhering to complex regimens and maintaining health behaviors, even after adjusting for comorbidities and socioeconomic factors (Schulman-Green et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Beyond multimorbidity and polypharmacy, multiple age-related barriers may contribute to suboptimal self-management, including cognitive decline, limited health literacy, physical and sensory impairments, social isolation, reduced access to digital health tools, and diminished self-efficacy (Doyle et al., 2019; Lorig \u0026amp; Holman, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). These findings highlight the need for targeted, age-sensitive interventions to strengthen self-management capacity and improve long-term outcomes in this vulnerable population.\u003c/p\u003e \u003cp\u003eMeanwhile, residence was found to be a significant predictor of self-management among older adults with COPD. Individuals residing in rural areas exhibited lower self-management scores compared to their urban counterparts. This disparity is consistent with previous study indicating that rural residents with chronic conditions often face greater barriers to effective disease management (Golembiewski et al., 2022). Factors such as limited access to healthcare services, scarcity of health education resources, and inadequate availability of pulmonary rehabilitation and follow-up care may contribute to poorer self-management in rural settings. Moreover, reduced exposure to reliable health information may lead to misconceptions about medications or inhaler use, further impairing adherence and proactive symptom monitoring (Hew et al., 2019). Therefore, when developing interventions to enhance self-management in COPD, the urban-rural divide must be explicitly considered. Notably, older adults in rural areas often lack access to digital health tools, transportation, and specialist pulmonary care-challenges that are compounded by age-related physical and cognitive limitations (Rony et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings highlight residence as a key social determinant of health and underscore the need for geographically targeted, context-sensitive strategies to support self-management among underserved rural populations with COPD.\u003c/p\u003e \u003cp\u003eAmong the factors examined, home oxygen therapy emerged as a significant correlate of self-management in older adults with COPD. Our findings indicate that patients receiving home oxygen therapy demonstrated higher levels of self-management compared to those not receiving such therapy. This may be attributed to the structured support and regular clinical follow-up that often accompany oxygen therapy prescriptions, which can enhance patients\u0026rsquo; disease understanding, symptom monitoring, and confidence in managing their condition. These results align with previous studies suggesting that patients on more comprehensive treatment regimens tend to engage more actively in self-care behaviors, particularly when these are integrated with educational and monitoring components (Riegel et al., 2021). A possible explanation is that the routine use of medical devices at home increases health awareness and reinforces daily self-management practices (Gr\u0026ouml;nvall et al., 2013). In contrast, Liddy et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported that complex treatment regimens were associated with reduced self-management in patients with multiple chronic conditions. This discrepancy may reflect differences in patient populations-our study focused specifically on older adults with COPD who may benefit from the routine and support associated with oxygen therapy, whereas broader chronic disease cohorts may experience treatment burden as a barrier.\u003c/p\u003e \u003cp\u003eAnother important finding was that higher levels of social support were positively associated with better self-management among patients with COPD. This finding is consistent with previous study on self-management in elderly individuals with chronic conditions (Chen et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which have shown that patients who perceive strong social support from family, friends, or healthcare providers tend to engage more actively in disease management compared to those with limited support. Our results align with the work of Dilworth (2014), who emphasized that patients\u0026rsquo; perceptions and psychosocial context\u0026mdash;such as trust in care networks and perceived support\u0026mdash;can significantly influence health behaviors. Furthermore, COPD patients have reported that lack of emotional or practical support, as well as feelings of isolation, are key barriers to maintaining consistent self-management practices (Ahola et al., 2013). Therefore, it is essential for healthcare professionals to recognize social support not merely as a background factor, but as an integral component of care. Interventions should aim to strengthen patients\u0026rsquo; support systems by involving family members, promoting peer support groups, and ensuring continuity of care, thereby enhancing patients\u0026rsquo; confidence and motivation to manage their condition effectively.\u003c/p\u003e \u003cp\u003eOverall, the most important clinically relevant finding was that health literacy is significantly associated with self-management in patients with COPD. In this context, health literacy refers to the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make informed decisions about their health (Ratzan et al., 2001). According to this finding, lower levels of health literacy are strongly associated with poorer self-management behaviors. This result is consistent with previous studies in chronic disease populations (Papadakos et al., 2018; Geboers et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which suggest that individuals with limited health literacy may struggle to understand treatment plans, interpret medication instructions, or navigate healthcare systems (Sudore et al., 2009), and may also face barriers in accessing preventive services (Stormacq et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Given that health literacy is considered a key modifiable determinant of health disparities across socioeconomic groups (Svendsen et al., 2020), future interventions should prioritize tailored strategies that account for varying levels of health literacy to effectively support self-management among older adults with COPD.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnalysis of the relationship among health literacy, social support, and self-management in older adults with COPD\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study reveals a significant positive correlation among health literacy, social support, and self-management in elderly patients with COPD, forming a dynamically reinforcing \u0026ldquo;golden triangle\u0026rdquo; that plays a crucial role in chronic disease management. Health literacy serves as the cognitive foundation, promoting self-management by enhancing individuals\u0026rsquo; ability to understand health information and make informed decisions, which supports the core role of the \u0026ldquo;knowledge-attitude-practice\u0026rdquo; (KAP) model in chronic illness care (Zhou et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Meanwhile, social support not only directly strengthens self-management through emotional, instrumental, and informational assistance, but also indirectly improves health literacy by lowering barriers to accessing and comprehending health-related information, aligning with the \u0026ldquo;resource empowerment\u0026rdquo; framework (Kirkman et al., 1999). The findings further highlight a bidirectional interaction: individuals with higher health literacy are more likely to actively seek and utilize social resources, while underutilization of available support suggests the need to enhance health empowerment to promote patient engagement. This triadic synergy is consistent with previous research, which has consistently reported significant positive associations among health literacy, social support, and self-management in various chronic disease populations, underscoring the generalizability of their interdependent roles in long-term management (Dinh et al., 2023). However, excessive support may lead to functional dependency, emphasizing the importance of fostering \u0026ldquo;supportive autonomy\u0026rdquo; (Benita et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In conclusion, clinical interventions should integrate family involvement, community resources, and educational initiatives to build a stratified and coordinated support system, transforming these interrelationships into tangible improvements in quality of life for elderly COPD patients.\u003c/p\u003e \u003cp\u003eThis study, using structural equation modeling, reveals a dual-path mechanism through which health literacy operates between social support and self-management: it partially mediates the relationship (accounting for 61.08%) by enabling social support to enhance patients\u0026rsquo; understanding and application of health information, thus serving as a \u0026ldquo;cognitive bridge\u0026rdquo; that transforms external resources into internal self-management capacity; meanwhile, social support also exerts a significant direct effect (38.92%) by promoting self-management behaviors through instrumental assistance and emotional encouragement, forming a dual model of \u0026ldquo;indirect transformation\u0026rdquo; and \u0026ldquo;direct facilitation\u0026rdquo;. This pattern of partial mediation contrasts with findings from Mak et al., who observed full mediation by health beliefs in the pathway from social support to self-care capacity, a difference likely attributable to population characteristics - our sample may include more individuals with higher educational attainment (e.g., junior high school or above), who are better able to directly translate social support into action, whereas Mak et al.\u0026rsquo;s study focused on rural patients with limited educational resources, for whom health beliefs may represent the primary cognitive pathway (Mak et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This suggests that the mediation mechanism is moderated by sociocultural and socioeconomic factors, highlighting the need for stratified interventions tailored to patients\u0026rsquo; health literacy levels. Future research should employ longitudinal or experimental designs to verify causality and explore how digital health technologies might extend and strengthen these pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitation\u003c/h2\u003e \u003cp\u003eA key strength of this study lies in its provision of valuable insights, to the best of our knowledge, into the current status and associated factors of self-management among older adults with COPD in Xi'an, Shaanxi Province, China, by utilizing standardized assessment scales. More importantly, our findings reveal a significant mediating role of health literacy in the relationship between social support and self-management, shedding light on the psychological mechanism through which social resources translate into improved health behaviors. It is noteworthy that older adults with COPD are frequently excluded from research; this study, therefore, focuses on a population that has long been overlooked, laying a crucial foundation for the future development and implementation of targeted interventions aimed at enhancing their self-management capabilities.\u003c/p\u003e \u003cp\u003eHowever, this study has limitations that are worth considering. First, information on self-management was collected for the previous months prior to the survey, so some degree of recall bias cannot be ruled out. This could lead to inaccurate estimations of the prevalence of inadequate self-management among COPD patients. Additionally, the data relied on self-reported practices of self-management, which might have been over- or under-reported by participants. Second, the study was limited in scope. Participants were from a tertiary hospital in Xi'an, Shaanxi Province, China, which limits its generalizability to broader regions in China. Third, this was a cross-sectional study. Therefore, associations between inadequate self-management and risk factors among COPD patients cannot necessarily be considered causal relationships. Furthermore, although we identified health literacy as a partial mediator in the relationship between social support and self-management, the cross-sectional design also restricts our ability to infer directional or causal pathways in this mediation process. Longitudinal or interventional studies are needed to confirm the temporal sequence and stability of this mediating effect.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD-Q\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Obstructive Pulmonary Disease Knowledge Questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSelf-Management Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGOLD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Obstructive Lung Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKnowledge-attitude-practice\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStructural equation modeling\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSSRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocial Support Rating Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVariance inflation factors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis study was reviewed and approved by the Ethics Committee of the Shaanxi Provincial Hospital of Traditional Chinese Medicine (Approval No.: AF/SC-04/01.2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e The datasets used and/or analysed during the current study are available from the author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e This work was supported by the Youth Talent Support Program of the Xi\u0026rsquo;an Association for Science and Technology (Grant No. 0959202513139) and the Regular Project of the Shaanxi Provincial Sports Bureau (Grant No. 20250368).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e IIH and AAK conceived and proposed the idea. WMAWA and MZ designed the work. MZ, YG, FL, YT and JY contributed to the data collection. MZ and XL contributed to data analysis and the interpretation of data for the work. MZ wrote the first draft of the manuscript. IIH, AAK, and WMAWA helped revise the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe authors would like to thank the physicians and nurses of the departments of respiratory at the a hospital visited for this study for their valuable support and cooperation in conducting this study. The authors are also particularly grateful to the contributions of the patients who participated in this research. Finally, the authors would like to thank Scribendi for their professional proofreading of this manuscript.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; information\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eSchool of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia\u003c/li\u003e\n \u003cli\u003eCollege of Nursing and Rehabilitation, Xi\u0026apos;an Jiaotong University City College, Xi\u0026apos;an, China\u003c/li\u003e\n \u003cli\u003eSchool of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia\u003c/li\u003e\n \u003cli\u003eShaanxi Provincial Hospital of Traditional Chinese Medicine, Xi\u0026apos;an, China\u003c/li\u003e\n \u003cli\u003eThe Second Affiliated Hospital of Xi\u0026apos;an Medical University, Xi\u0026apos;an, China\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eCorresponding author: Intan Idiana Hassan, School of Health Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia.\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD 2019 Chronic Respiratory Diseases Collaborators. 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The effect of knowledge, attitude, and practice model-based health education on psychological well-being and self-efficacy of patients with concurrent cerebrovascular stenosis and coronary heart disease: a quasi-experimental study. Front Public Health. 2025;12:1484210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKirkman BL, Rosen B. Beyond self-management: Antecedents and consequences of team empowerment. Acad Manag J. 1999;42(1):58\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDinh TTH, Bonner A. Exploring the relationships between health literacy, social support, self-efficacy and self-management in adults with multiple chronic diseases. BMC Health Serv Res. 2023;23(1):923.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenita M, Roth G, Deci EL. When are mastery goals more adaptive? It depends on experiences of autonomy support and autonomy. J Educ Psychol. 2014;106(1):258.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMak WW, Law RW, Woo J, Cheung FM, Lee D. Social support and psychological adjustment to SARS: The mediating role of self-care self-efficacy. Psychol Health. 2009;24(2):161\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"older adults, chronic obstructive pulmonary disease, self-management, health literacy, social support, associated factors, mediation effect","lastPublishedDoi":"10.21203/rs.3.rs-8746286/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8746286/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eChronic obstructive pulmonary disease (COPD) is a major chronic condition among older adults in China, associated with high morbidity and healthcare burden. Effective self-management is crucial for disease control and improved outcomes, yet many older patients struggle to maintain it due to socioeconomic, cognitive, and physical challenges. Social support and health literacy\u0026mdash;the ability to access, understand, and use health information\u0026mdash;are recognized as key factors influencing health behaviors, but their interplay in self-management remains unclear in this population.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to examine the prevalence and associated factors of self-management among older adults with COPD in China. Furthermore, it sought to investigate the mediating role of health literacy in the relationship between social support and self-management, providing insights into the psychological mechanisms through which social resources influence health behaviors in this population.\u003c/p\u003e\u003ch2\u003eMethods and results\u003c/h2\u003e \u003cp\u003eIn this cross-sectional study, a total of 219 older adults with COPD were recruited from a tertiary hospital in China. The results of the survey showed that the current state of self-management among patients with COPD generally indicates a moderate level, with a mean score of (130.62\u0026thinsp;\u0026plusmn;\u0026thinsp;20.70). After adjusting for potential confounders, participants residing in rural areas had significantly lower self-management scores compared to those in urban areas (\u003cem\u003eβ\u003c/em\u003e = -6.531, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In contrast, patients receiving home oxygen therapy demonstrated a higher self-management score (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.748, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, each one-unit increase in health literacy was associated with a 4.473 point increase in self-management (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.473, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a one-unit increase in social support corresponded to a 1.052 point increase (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.052, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Pearson correlation analysis revealed that both health literacy (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.501, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and social support (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.500, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were significantly positively correlated with self-management. Furthermore, mediation analysis showed that health literacy partially mediated the association between social support and self-management, accounting for 61.08% of the total effect.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSelf-management was suboptimal among older adults with COPD in China. Factors such as residence, home oxygen therapy, health literacy, and social support were significantly associated with self-management. Notably, health literacy partially mediated the association between social support and self-management, highlighting its role as both a direct contributor and a psychological mechanism linking social resources to health behaviors.\u003c/p\u003e","manuscriptTitle":"The roles of health literacy and social support in self-management among older adults with chronic obstructive pulmonary disease in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 10:30:27","doi":"10.21203/rs.3.rs-8746286/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-12T10:15:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203543758008625101966852711215889391501","date":"2026-04-10T09:07:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70600750358822385666601240083985112888","date":"2026-04-10T08:40:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T16:12:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-19T10:46:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-10T08:48:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-10T04:31:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2026-02-10T04:18:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"372d1b94-ee2a-41d1-86aa-b6cbf7d5c937","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T10:30:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 10:30:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8746286","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8746286","identity":"rs-8746286","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}