China's Revitalized Primary Care and Its Impact on Triple Aims for Chronic Diseases Patients: A Retrospective Cohort Study

China's Revitalized Primary Care and Its Impact on Triple Aims for Chronic Diseases Patients: A Retrospective Cohort Study | 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 China's Revitalized Primary Care and Its Impact on Triple Aims for Chronic Diseases Patients: A Retrospective Cohort Study Yang Wang, Hongling Chu, Hui Yang, Hua Jin, Chuan Zou, Hai Fang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4280609/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To evaluate the effectiveness, patient experience, and cost-efficiency of primary care versus hospital care for middle-aged and elderly patients with chronic diseases in China, in the context of achieving the triple aim of healthcare: improving population health, reducing per capita costs, and enhancing patient satisfaction. Methods A longitudinal cohort analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) spanning the years 2011, 2013, 2015, and 2018.The study included participants aged 45 and older from 450 communities across mainland China, specifically targeting those with chronic diseases. Individuals without chronic conditions or with incomplete data were excluded. Results The analysis encompassed 50,800 subjects. Those who visited hospitals for outpatient treatment—mainly urban residents with higher education and income levels, and with comprehensive insurance coverage—demonstrated poorer health outcomes (OR = 1.06, 95%CI 1.02–1.10, p = 0.002) and higher medical expenses (OR = 1.99, 95% CI 1.93–2.06, p < 0.001) compared to those who utilized primary care facilities. No significant difference was observed in satisfaction levels between the two groups (OR = 0.99, 95% CI 0.92–1.07, p = 0.85). Conclusions This study indicates that for patients over 45 with chronic diseases, China's primary care can achieve health outcomes comparable to or better than large hospitals, at significantly lower costs. Despite some data limitations, it highlights the effectiveness of primary care in improving health for socioeconomically disadvantaged groups, advocating for more government investment and policy support to enhance primary care's affordability and functionality. Primary Care China Health Outcomes Chronic Disease Healthcare Costs Patient Satisfaction Figures Figure 1 Figure 2 Figure 3 Introduction China's primary care system emerged between the 1950s and 1970s amid widespread poverty and scarce medical resources, with over 80% of the population residing in rural areas 1 , 2 . During this time, the Chinese government complimented nearly 5 million short trained health workers which were financially supported through rural collective economy. 50,000 township health centers were established in the two decades, that formed three-tiered (village-township-county) basic medical care system. Rural Cooperative Medical System functioned as original form of community health insurance 1 . It was celebrated as a successful model for primary care development in low- and middle-income countries 3 . Since the 1980s, China have been walking on the way of swing transformation between planning economy and market economy. In the context of national economy reform, a profit-driven approach was mixed with the public entitled health system. The mixed health system bolstered the resources (financial investment, human resources, hi-tech equipment, information technology) of hospitals under power of invisible hand, while severely undermining primary care system which was recognized as low productive efficiency. The early reform (1980s-2000s) also reduced equity in healthcare, leading to a substantial increase in residents' medical expenditures 4 , 5 . Throughout the first two decades of the 21st century, China experienced accelerated population aging and an increasing burden of chronic diseases 6 , 7 . In response, China launched an updated health system reform in 2009. Key strategies of the new reform were structure-focused, included increasing financial and human resource investments in primary care facilities, reducing reliance on profit-driven financing, and strengthening preventive medicine services for specific population 8 . However, China's healthcare system remained in a complex and mixed state of transition, which exhibited characteristics from various healthcare models 9 , 10 , such as the Beveridge model (e.g., healthcare institutions primarily managed by the government 11 ), the Bismarck model (e.g., residents and workers required to contribute to public health insurance 12 ), the U.S. model (e.g., different populations covered by distinct health insurance reimbursement schemes 13 ), and the uninsured model (e.g., residents still paying an average of about 30% of out-of-pocket medical expenses even with insurance 14 ). A hallmark of this system is its open market dynamic, granting patients the freedom to access medical care from any facility nationwide, assuming they can manage to book an appointment and bear the financial cost 15 . In this system, China's approach to "primary care" significantly diverges from Western practices, distinguished primarily by its structural organization and hierarchy rather than the specific medical services it offers 16 , 17 . Chinese primary care practitioners’ function within an integrated 'unit' system rather than as independent practices. This comprehensive network boasts roughly 900,000 state-administered primary care facilities, including about 35,000 community health centers and an equal number of township health centers, which stand as central pillars of healthcare nationwide 5 . With a workforce of approximately 3 million clinical doctors, including a small percentage of trained or certified general practitioners (GPs) (less than 10%),, along with a larger number of rural doctors and traditional Chinese medicine practitioners 18 . Their key responsibility is to deliver essential healthcare services to local communities, work in tandem with nurses and public health officials to establish family doctor groups, engage with specific segments like chronic disease sufferers and the elderly, and implement certain preventive medical services 17 , 19 . However, despite the theoretically universal access to primary care facilities within China's liberalized healthcare market, a considerable segment of the population—nearly half—prefers to bypass these facilities in favor of immediate treatment at general hospitals 20 . This preference reflects a nuanced decision-making process, influenced by the intricate dynamics of individual health statuses, economic capabilities, and specific medical requirements, resulting in a spectrum of healthcare-seeking behaviors 20 . This includes selective engagement with various types of facilities or, in certain instances, a complete abstention from seeking healthcare. Evidence from North American, European, and British Commonwealth contexts suggests that primary care can deliver patient functional health outcomes comparable to specialty care, while also achieving better or equal results in terms of population health, per capita cost, and patient experience 21 , 22 . However, China's strategic approach to revitalizing primary care, featuring a unique design, primarily depends on a visionary policy approach at the top level, incorporating insights from the evidence and policy experiences of various countries with diverse healthcare systems and primary care designs. Hence, this study aims to examine the disparities in triple aim outcomes—health of the population, cost per capita, and patient experience—among middle-aged and elderly patients with chronic diseases who sought care at either primary care facilities or general hospitals. This endeavor aims to provide direct insights into the performance of China's primary care for a specific population segment within its unique societal and healthcare system context over the seven years following the launch of the healthcare reform initiated in 2010. Methods Study Design: In this study, the researchers analyzed data from four waves (2011, 2013, 2015, and 2018) of the China Health and Retirement Longitudinal Study (CHARLS). This nationally representative cohort comprises Chinese individuals aged 45 or older, with self-reported data collected through face-to-face interviews. It selected participants from 450 residential communities of China mainland using a multi-stage probability-proportional-to-size technique. Peking University's Biomedical Ethics Review Committee approved the study (IRB00001052-11015). Further information about CHARLS can be found in other sources 23 . Focusing on residents with chronic diseases, we excluded 5,675, 6246, 7775, and 6725 residents without chronic conditions or with missing data from 2011 to 2018 CHARLS waves (Fig. 1 ). In the CHARLS survey, participants were asked to report clinician-diagnosed chronic diseases, including hypertension, diabetes, dyslipidemia, cancer, stroke, heart disease, liver disease, kidney disease, chronic lung disease, asthma, digestive disease, arthritis, psychiatric disease, and memory-related diseases. Those reporting any of these conditions were considered chronic disease patients. Independent Variable, Outcomes, and Covariates: In each of the four CHARLS waves, participants reported the type of facilities they visited for outpatient treatment within the past four weeks. Following the classification method of healthcare facilities in China 24 , we categorized them into four groups to represent their visit sites: those visiting only primary care facilities (indicating a preference for primary care), only hospitals (indicating a preference for general hospitals), not visiting any facilities (indicating infrequent healthcare utilization), and visiting both types of facilities. We selected three key outcome variables based on the Agency for Healthcare Research and Quality recommendations 25 within the Triple Aim framework to measure healthcare performance. Population health was assessed using residents' self-reported five-level Likert scale. Per capita cost refers to out-of-pocket expense for the visits in the last month, including direct expenses of treatment fees, medication costs, and prescription drugs. We divided medical spending into four levels based on China's average monthly salary in 2011 (approximately 1,200 CNY or 185 USD) 26 : no spending (0 CNY), low spending (1-119 CNY), moderate spending (120–599 CNY), and high spending (≥ 600 CNY). Patient experience was gauged through the patients' satisfaction with the quality, cost, and convenience of local healthcare services and was included as an outcome in the 2015 and 2018 CHARLS waves. The range of satisfaction responses extended from very satisfied to very dissatisfied. In accordance with the existing literature on Triple Aim outcomes in China 27 – 29 , the researchers incorporated the following covariates: gender, age, region (distinguished between the economically developed eastern region and the non-eastern regions), residential area (urban or rural), family wealth (broken down into quartiles: lowest 25%, 26%-50%, 51%-75%, and the highest 25%), level of education, health insurance scheme (classified into high-coverage, moderate-coverage, low-coverage insurance schemes, and no insurance 30 ), presence of multimorbidity, adherence to the WHO-recommended levels of physical activity 31 , smoking status, alcohol consumption, presence of Activities of Daily Living (ADL) disability and Instrumental Activities of Daily Living (IADL) disability 31 . Statistical Analysis The researchers analyzed the sociodemographic characteristics of patients from 2011 to 2018 using descriptive statistics and compared differences in characteristics of patients visiting different healthcare facilities using a Chi-square test. The researchers then reported on the health status and monthly out-of-pocket doctor visit expenditure for patients visiting either primary care facilities or hospitals exclusively from 2011 to 2018, while patient satisfaction from 2015 to 2018. A multilevel model was constructed using a random intercepts model, with patients at the first level and survey time at the second level. The independent variable was the healthcare facilities type (primarily sought care at primary care facilities or at general hospitals), and the outcomes were health status, monthly out-of-pocket doctor visit expenditure, and patient satisfaction. Based on previous literature 27 – 29 , all covariates were used for the health status model, related covariates and health status variables for the medical expenditure model, and related covariates and medical expenditure variables for the patient satisfaction model. The researchers began with a null model, calculated level 1 and 2 variances, and the variance partition coefficient (VPC). We sequentially tested potentially related level 1 covariates with dependent variables (P ≤ 0.2) and included significant covariates in the multilevel model. We used backward stepwise elimination until only significant associations remained. Statistical analysis was conducted using Stata 17.0 SE, with a significance level of p ≤ 0.05. Three sensitivity analyses were conducted. The first addressed endogeneity by using two instrumental variables—marital status and family size—a study based on another renowned database in China, the China Family Panel Studies, on residents' propensity to seek primary healthcare has confirmed that these variables are related to healthcare facility preferences but not directly associated with health status, medical expenses, or patient satisfaction. 20 , 32 . In the second analysis, we employed imputed data in accordance with guidelines for longitudinal datasets 33 and used the Last Observation Carried Forward method to re-run similar models, verifying whether the relationships between independent and dependent variables remained significant. In the third sensitivity analysis, the researchers exclusively analyzed data from patients who had only been diagnosed with hypertension, in order to eliminate the confounding effects of other chronic diseases and ascertain whether the results remained statistically significant. Results Table 1 reveals the sociodemographic backgrounds, health insurance coverage, lifestyle habits, and health conditions of chronic disease patients in 2011, as observed by us. Compared to patients who chose hospital care, we found that those who exclusively turned to primary care facilities were predominantly from specific demographics, including at least 15% more rural residents (70.6% vs. 46.5%, p < 0.001), individuals with primary school education or less (78.6% vs. 58.8%, p < 0.001), households in the bottom 50% wealth bracket (60.1% vs. 43.4%, p < 0.001), those currently employed (66.9% vs. 49.8%, p < 0.001), and participants covered by health insurance plans offering minimal coverage (83.6% vs. 59.2%, p < 0.001). This trend persisted across the data for 2013, 2015, and 2018, as shown in our Supplementary Tables 1–3. In 2011, we noted a marginally higher ADL disability rate among patients who only visited primary care facilities compared to those who went to hospitals (33.7% vs. 30.0%, p = 0.051). While the differences in 2013 and 2015 were not statistically significant, by 2018, a significant increase in ADL disability rate was evident among patients opting for primary care (40.64% vs. 34.28%, p = 0.032), as detailed in our eTables 1–3. Table 1 Sociodemographic characteristics of patients seeking care at different healthcare facilities in 2011 Visited primary care facilities Visited hospitals Did not visit any healthcare facilities Visited both healthcare facilities Total P value No. % No. % No. % No. % No. % Gender <0.001 Male 683 39.71 410 44.71 4482 48.20 34 36.17 5609 46.63 Female 1037 60.29 507 55.29 4817 51.80 60 63.83 6421 53.37 Age 0.004 45–54 years 501 29.13 332 36.21 3114 33.49 34 36.17 3981 33.09 55–64 years 656 38.14 332 36.21 3439 36.98 38 40.43 4465 37.12 65–74 years 388 22.56 157 17.12 1830 19.68 16 17.02 2391 19.88 > 74 years 175 10.17 96 10.47 916 9.85 6 6.38 1193 9.92 Region(total = 11604) 0.531 Eastern region 481 28.73 273 31.16 2672 29.80 29 33.33 3455 29.77 Non-eastern region 1193 71.27 603 68.84 6295 70.20 58 66.67 8149 70.23 Living area <0.001 Urban Community 506 29.42 491 53.54 3893 41.86 42 44.68 4932 41.00 c 1214 70.58 426 46.46 5406 58.14 52 55.32 7098 59.00 Education(total = 12018) <0.001 No formal education 617 35.89 188 20.50 2564 27.61 28 29.79 3397 28.27 Primary school 734 42.70 351 38.28 3706 39.90 34 36.17 4825 40.15 Middle school 249 14.49 210 22.90 1877 20.21 21 22.34 2357 19.61 High school and above 119 6.92 168 18.32 1141 12.28 11 11.70 1439 11.97 Wealth <0.001 Lowest 25% 560 32.56 209 22.79 2381 25.60 32 34.04 3182 26.45 26%-50% 474 27.56 189 20.61 2312 24.86 20 21.28 2995 24.90 51%-75% 387 22.50 227 24.75 2283 24.55 14 14.89 2911 24.20 Highest 25% 299 17.38 292 31.84 2323 24.98 28 29.79 2942 24.46 Health insurance scheme(total = 11984) <0.001 No insurance 96 5.58 39 4.25 681 7.36 6 6.38 822 6.86 High-coverage 124 7.21 254 27.70 1462 15.80 18 19.15 1858 15.50 Moderate-coverage 63 3.66 81 8.83 601 6.50 9 9.57 754 6.29 Low coverage 1437 83.55 543 59.21 6509 70.34 61 64.89 8550 71.35 Multimorbidity(total = 11974) <0.001 Yes 1109 64.48 627 68.45 4912 53.14 69 73.40 6717 56.10 No 611 35.52 289 31.55 4332 46.86 25 26.60 5257 43.90 Smoking(total = 11989) <0.001 Yes 438 25.57 176 19.36 2726 29.71 16 17.20 3356 28.23 No 1275 74.43 733 80.64 6448 70.29 77 82.80 8533 71.77 Alcohol consumption(total = 11984) <0.001 Yes 455 26.45 217 23.69 2938 31.75 18 19.15 3628 30.27 No 1265 73.55 699 76.31 6316 68.25 76 80.85 8356 69.73 WHO recommended level of physical activity 0.019 Yes 1112 64.65 543 59.21 5679 61.07 58 61.70 7392 61.45 No 608 35.35 374 40.79 3620 38.93 36 38.30 4638 38.55 Presence of ADL disability 0.017 Yes 580 33.72 275 29.99 2788 29.98 32 34.04 3675 30.55 No 1140 66.28 642 70.01 6511 70.02 62 65.96 8355 69.45 Presence of IADL disability <0.001 Yes 561 32.62 270 29.44 2268 24.39 37 39.36 3136 26.07 No 1159 67.38 647 70.56 7031 75.61 57 60.64 8894 73.93 Total 1720 100.00 917 100.00 9299 100.00 94 100.00 12030 100.00 From our analysis spanning 2011 to 2018, we observed that the percentages of patients reporting poor or very poor health within 1–4 weeks after an outpatient visit remained fairly consistent between those attending primary care facilities and hospitals, with minor variations of -1.2%, -0.6%, -3.1%, and 2.8% respectively, as depicted in Fig. 2 .a. Over these years, we documented a rise in the occurrence of high medical expenditures for both facility types, climbing from 6.7–18% for primary care facilities and from 43.2–49.7% for hospitals, the latter always significantly higher, as illustrated in Fig. 2 .b. Between 2015 and 2018, the percentage of patients expressing either relative or high satisfaction with local health services slightly declined from 42–38.1% for primary care facilities, and from 38.4–35.2% for hospitals, with primary care consistently achieving a bit higher satisfaction rates, as we found in Fig. 2 .c. Figure 3 presents the results of our multilevel analysis, showing that patients visiting hospitals within a month tend to have worse health outcomes (OR = 1.08, 95% CI 1.04–1.11; p = 0.002) and incur higher medical costs (OR = 1.99, 95% CI 1.93–2.06; p < 0.001) compared to those opting for primary care facilities. Conversely, there is no significant difference in patient satisfaction between the two groups (OR = 0.99, 95% CI 0.91–1.06; p = 0.85). Our endogeneity tests, employing two instrumental variables, confirm the absence of significant endogeneity in all three models (p = 0.063, 0.051, 0.058, respectively). Analyses using imputed data also highlight significant impacts on health status and medical costs (OR = 1.07, 95% CI 1.01–1.09; p = 0.007 and OR = 1.92, 95% CI 1.85–1.99; p < 0.001, respectively). In subgroups consisting solely of hypertensive patients, while health outcomes show no significance (OR = 0.99, 95% CI 0.83–1.18; p = 0.901), the findings on medical expenses remain notably significant (OR = 2.02, 95% CI 1.71–2.38; p < 0.001) (refer to eTables 4–6). Discussion This study's key finding reveals that among participants aged 45 and above with chronic diseases, those utilizing outpatient services in primary care facilities achieve similar or better health outcomes, comparable patient satisfaction, and significantly lower medical costs, despite comparable functional status (ADL disability rates) to those treated in hospitals. This research highlights the systemic and holistic contribution of primary care to healthcare performance within both the societal and health system contexts of China. Given the incentives provided by China's health authorities to encourage residents to use primary care facilities, including medical reimbursement rates approximately 10% higher than those for hospitals 34 , and the typically limited demand for complex procedures and expensive drugs and equipment at primary care facilities—due to their general unavailability 35 , 36 —it's not surprising that patients primarily seeking care at these facilities incur significantly lower medical expenses than those who primarily visit hospitals. Additionally, considering the issues widely criticized by residents at China's large general hospitals, such as infamously long wait times, confusing care pathways, and a more mechanized, speed-focused approach to diagnosis and treatment—despite their better equipment and medications—it's understandable why patient satisfaction might not significantly surpass that of primary care facilities 37 . However, one of the most striking findings of this study is that patients primarily treated at primary care facilities exhibit health outcomes one month post-treatment that are as good as, or even better than, those of patients primarily treated at hospitals. This becomes even more remarkable when considering the significant gaps in resources and clinical capacity between Chinese primary care facilities and hospitals. This result can be interpreted in two ways: First, it might be an artifact of data analysis bias. A key contextual feature of China's primary care system is its unstable and non-universal connection with the community 15 . In practice, this often translates to patients with better socioeconomic status, more severe illnesses, and a need for highly technical doctors, equipment, and medications opting to directly seek care at general hospitals, thus stepping outside the coverage of the resource-limited primary care facilities 20 , 38 . This context could lead to significant confounding in measuring population health outcomes: namely, that patients who seek care at primary care facilities are healthier might be because those who are healthier choose to go to primary care facilities, not necessarily because primary care improves health outcomes more effectively. In this study, although we employed several methods to bolster the robustness of our findings—such as comparing ADL differences between groups, using instrumental variables to test for significant causality, and conducting subgroup analyses on hypertensive patients only, which yielded positive results—looking at it neutrally, the precision of our independent and outcome variables, derived from survey data, including patients' verbal feedback on healthcare experiences and self-reported health outcomes, is not highly accurate. Given these considerations, we cannot be fully confident that China's primary care services can achieve stronger population health outcomes than general hospitals based on our findings. Despite this, evidence also exists supporting a second interpretation, where primary care may produce superior overall performance through a unique set of functional characteristics, such as accessibility, comprehensiveness, continuity, and coordination 21 , 39 . Not only in some countries in North America and Europe, but even within China's unique primary care system, several studies have confirmed the existence of these functional characteristics and their impact on population health 21 , 22 , 40 – 42 . They reflect that, despite potential limitations in the comprehensiveness of medical and health services and coordination with general hospitals, China's primary care, thanks to a network of primary care facilities built half a century ago, might have strong advantages in accessibility and continuity compared to general hospitals 40 – 44 . A large-scale, local randomized controlled trial have confirmed that primary care interventions by rural physicians, who are often perceived as lacking clinical expertise, medication, and medical equipment, can effectively control blood pressure in hypertensive patients 45 . This has significant clinical implications for preventing complications such as cardiovascular disease, stroke, and kidney disease 46 . Furthermore, the socioeconomic characteristics of the studied population are an important contextual factor to consider. In this study, we found a disproportionately high representation of patients in a disadvantaged socioeconomic status. This finding aligns with previous nationwide studies examining Chinese residents' healthcare facility preferences 20 , 38 . Despite the rise in China's per capita income from ¥18,310 (approximately 2,834 USD) to ¥28,228 (around 4,269 USD) between 2011 and 2018, rural income was half that amount 47 . Coupled with the concentration of hospitals in eastern China's urban areas and rural healthcare expenditure being less than 30% of urban costs, it becomes evident that China's primary care continues to be an essential healthcare resource for more than half of the population, especially its vulnerable populations, even after half a century 48 . Moreover, the number of patients seeking care at primary care facilities was approximately double that of those seeking care at hospitals. Past evidence shows that primary care services may have particularly significant performance impacts on this population group 21 . Therefore, although we cannot assert based on our current findings that China's primary care system has higher health performance than the general hospital system, this study indeed presents a possibility: in the current healthcare system in China, within this open market where patients freely choose, the primary care sector for some chronic disease patients—especially those in a socioeconomically disadvantaged position—could achieve health maintenance and improvement outcomes with limited costs, not inferior to those provided by large general hospitals. In our ongoing work, we are using more precise measurement tools and indicators, such as EQ-5D-5L for population health, clinical diagnostic outcomes for chronic diseases, and Person-Centered Primary Care Measure for primary care functional features, to evaluate local primary care functionality, its relationship with improved Triple Aim outcomes for residents, and its impact on enhancing specialized healthcare and clinical services for the key target population. Additionally, we plan to gain more detailed information on the existence of functional features of Chinese primary care experienced by patients, and the specific mechanisms for maintaining and improving the health status of chronic disease patients through qualitative research. Conclusion The study demonstrates that primary care in China can lead to similar or better health outcomes and significantly lower medical costs for patients aged 45 and above with chronic diseases. Although the background environment of the study and some limitations of the data may weaken our confidence in this finding, it indeed shows that China's primary care for some chronic disease patients—especially those in a socioeconomically disadvantaged position—can produce health maintenance and improvement outcomes with limited costs, not inferior to those provided by large general hospitals. The findings call for increased government investment in primary care resources, prioritizing affordability in all primary care services and features, and enhancing primary care functions within existing healthcare policies. Declarations Authorship contributions ： Conceptualization, Y.W.; Methodology, Y.W and H.C; Data curation, Y.W; Formal analysis, Y.W.; Funding acquisition, H.F; Project administration, H.F; Resources, Y.W; Supervision, H.F.; Validation, Y.W; Writing—original draft, Y.W.; Writing—review and editing, Y.W., H.Y., H.C., H.J., C.Z and H.F. All authors have read and agreed to the published version of the manuscript. Human Ethics Approval statement: Peking University's Biomedical Ethics Review Committee approved the study (IRB00001052-11015). Acknowledgments: We are deeply grateful to Prof. Kurt Stange for conducting an external review of our manuscript and offering valuable feedback and suggestions. Funding: This research was funded by the Natural Science Foundation of Beijing, China (Grant No. 9222013). Prior presentations: None. Conflict of Interest Statement: The authors declare no conflict of interest. References Weiyuan C. China's village doctors take great strides. World Health Organization. Bulletin of the World Health Organization. 2008;86(12):914. Rural population (% of total population) - China | Data - World Bank Data [Internet]. World Bank; [cited 2023 May 11]. Available from: https://data.worldbank.org/indicator/SP. RUR.TOTL.ZS?locations=CN&view=chart Cueto M. 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National Healthcare Security Administration: The annual budget for the increase in medical insurance funds is primarily allocated to grassroots medical institutions [Internet]. people.cn; 2024 [cited 2024 Jan 14]. Available from: http://health.people.com.cn/n1/2024/0112/c14739-40157935.html (Chinese) Li X, Lu J, Hu S, Cheng KK, De Maeseneer J, Meng Q, Mossialos E, Xu DR, Yip W, Zhang H, Krumholz HM. The primary health-care system in China. The Lancet. 2017;390(10112):2584–94. Wong WC, Jiang S, Ong JJ, Peng M, Wan E, Zhu S, Lam CL, Kidd MR, Roland M. Bridging the gaps between patients and primary care in China: a nationwide representative survey. The Annals of Family Medicine. 2017;15(3):237–45. Yan J, Yao J, Zhao D. Patient satisfaction with outpatient care in China: a comparison of public secondary and tertiary hospitals. International Journal for Quality in Health Care. 2021;33(1):mzab003. Zhang A, Nikoloski Z, Albala SA, Yip W, Xu J, Mossialos E. Patient choice of health care providers in China: primary care facilities versus hospitals. Health Systems & Reform. 2020;6(1):e1846844. Mold JW. From the North American Primary Care Research Group: How Primary Care Produces Better Outcomes–A Logic Model. Annals of Family Medicine. 2014;12(5):483. Wang Y, Wu Y, Chu H, et.al. Association between Health-Related Quality of Life and Access to Chronic Disease Management by Primary Care Facilities in Mainland China: A Cross-Sectional Study. International Journal of Environmental Research and Public Health. 2023;20(5):4288. Wang W, Shi L, Yin A, et.al. Contribution of primary care to health: an individual level analysis from Tibet, China. International journal for equity in health. 2015;14(1):1–6. Shi J, Jin H, Shi L, et.al. The quality of primary care in community health centers: comparison among urban, suburban and rural users in Shanghai, China. BMC Family Practice. 2020;21(1):1–0. Ding H, Chen Y, Yu M, et.al. The effects of chronic disease management in primary health care: evidence from rural China. Journal of Health Economics. 2021;80:102539. Wang HH, Wang JJ, Wong SY, et.al. Patients' experiences in community health centres under the health-care reform: research findings from a cross-sectional study using the Primary Care Assessment Tool in China. The Lancet. 2015;386:S69. Sun Y, Mu J, Wang DW, et.al. A village doctor-led multifaceted intervention for blood pressure control in rural China: an open, cluster randomised trial. The Lancet. 2022;399(10339):1964–75. Aronow WS, Fleg JL, Pepine CJ, et.al. ACCF/AHA 2011 expert consensus document on hypertension in the elderly: a report of the American College of Cardiology Foundation Task Force on Clinical Expert Consensus Documents. Circulation. 2011;123(21):2434–506. 2019 China Statistical Yearbook [Internet]. National Bureau of Statistics of the People’s Republic of China; [cited 2023 May 11]. Available from: http://www.stats.gov.cn/sj/ndsj/2019/indexch.htm 2011 Statistical Bulletin on the Development of Healthcare in China [Internet]. Statistical Information Center of the National Health Commission of the People’s Republic of China; 2012 [cited 2023 May 11]. Available from: http://www.nhc.gov.cn/mohwsbwstjxxzx/s7967/201204/54532.shtml Additional Declarations No competing interests reported. Supplementary Files Supplementalfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-4280609","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":292955517,"identity":"90775dc7-38a9-4ff2-b19d-9bfbd7d0746e","order_by":0,"name":"Yang Wang","email":"","orcid":"","institution":"Peking University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Wang","suffix":""},{"id":292955518,"identity":"99857c0e-3eef-49fb-981f-8d10a84d647b","order_by":1,"name":"Hongling Chu","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hongling","middleName":"","lastName":"Chu","suffix":""},{"id":292955519,"identity":"1dc8ca7f-5565-4d08-8989-8378a0fa0205","order_by":2,"name":"Hui Yang","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Yang","suffix":""},{"id":292955520,"identity":"c7f678a9-d216-487b-9ce4-102f9515e23b","order_by":3,"name":"Hua Jin","email":"","orcid":"","institution":"Yangpu Hospital, Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Jin","suffix":""},{"id":292955521,"identity":"07a51701-249d-4c63-b8cc-592489130016","order_by":4,"name":"Chuan Zou","email":"","orcid":"","institution":"Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chuan","middleName":"","lastName":"Zou","suffix":""},{"id":292955522,"identity":"ee8cf73a-b7a4-429d-8806-0a06eb681ce4","order_by":5,"name":"Hai Fang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACA+YDQLICRDAwgwjGBoJa2BKA5BmStTC2kaLFnI352cOv8+7Y8zfwHjbmYbCR3XCA+dkDfFos29jMjWW3PUuccYAvOZmHIc14wwE2cwO8DrvfYCYtue1wggEDj/FhHobDiRsO8LBJ4NVyjP2btOScw/ZQLf+J0cJjJvmx4TDjBqAWoMMOEKWlTJrh2OHEGYf5kg3nGCQbzzzMZkbIYdskf9Qctudv7z0s8abCTrbvePMzvFpAgJkHToKCipmQeiBg/AGmeIhQOgpGwSgYBSMSAAD1OUW0QF1DugAAAABJRU5ErkJggg==","orcid":"","institution":"Peking University","correspondingAuthor":true,"prefix":"","firstName":"Hai","middleName":"","lastName":"Fang","suffix":""}],"badges":[],"createdAt":"2024-04-17 08:50:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4280609/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4280609/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55511433,"identity":"f37ed146-91cd-4a24-bd67-ca836bf4ac06","added_by":"auto","created_at":"2024-04-29 12:36:02","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":324446,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart showing the number of CHARLES participants included in the analyses\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4280609/v1/443eb55e5d6f0ea8cb56ca62.jpeg"},{"id":55511435,"identity":"13b97da0-616f-46d5-b4ab-a3a073effc87","added_by":"auto","created_at":"2024-04-29 12:36:02","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":236956,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHealth care performance for Chronic Disease Patients Visiting Different Healthcare facilities from 2011 to 2018\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4280609/v1/0921117593f650c220db3029.jpeg"},{"id":55511432,"identity":"f0daaa96-a122-482c-b28b-b1fc54187055","added_by":"auto","created_at":"2024-04-29 12:36:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":108486,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultilevel Model: Association between Chronic Disease Patients Visiting Different Healthcare facilities from 2011 to 2018 and Healthcare performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Self-reported health status: from very good to very poor;\u003c/p\u003e\n\u003cp\u003e(b) Monthly out-of-pocket doctor visit expenditure: from no spending to high spending;\u003c/p\u003e\n\u003cp\u003e(c) Patient satisfaction: from very satisfied to very dissatisfied.\u003c/p\u003e\n\u003cp\u003eThe reference groups for the following items are: Healthcare facility type: Visiting primary care facilities; Age: 45-54 years; Education: No formal education; Medical insurance: Uninsured; Health status: Very good; Doctor visit expenditure: No spending.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4280609/v1/da34112faa23c328f25640bf.png"},{"id":56818112,"identity":"b4ed92bf-accd-4d32-a698-350fe2c9ce4c","added_by":"auto","created_at":"2024-05-20 23:08:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1463423,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4280609/v1/85461be8-de4e-408d-9a9a-016853f247f6.pdf"},{"id":55512270,"identity":"b3ec7150-1261-4c36-a7be-31c4e86ec395","added_by":"auto","created_at":"2024-04-29 12:44:02","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":80052,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4280609/v1/c50a8ec55f8e7f599bf3584a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"China's Revitalized Primary Care and Its Impact on Triple Aims for Chronic Diseases Patients: A Retrospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChina's primary care system emerged between the 1950s and 1970s amid widespread poverty and scarce medical resources, with over 80% of the population residing in rural areas\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. During this time, the Chinese government complimented nearly 5\u0026nbsp;million short trained health workers which were financially supported through rural collective economy. 50,000 township health centers were established in the two decades, that formed three-tiered (village-township-county) basic medical care system. Rural Cooperative Medical System functioned as original form of community health insurance\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. It was celebrated as a successful model for primary care development in low- and middle-income countries\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSince the 1980s, China have been walking on the way of swing transformation between planning economy and market economy. In the context of national economy reform, a profit-driven approach was mixed with the public entitled health system. The mixed health system bolstered the resources (financial investment, human resources, hi-tech equipment, information technology) of hospitals under power of invisible hand, while severely undermining primary care system which was recognized as low productive efficiency. The early reform (1980s-2000s) also reduced equity in healthcare, leading to a substantial increase in residents' medical expenditures\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThroughout the first two decades of the 21st century, China experienced accelerated population aging and an increasing burden of chronic diseases\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In response, China launched an updated health system reform in 2009. Key strategies of the new reform were structure-focused, included increasing financial and human resource investments in primary care facilities, reducing reliance on profit-driven financing, and strengthening preventive medicine services for specific population\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, China's healthcare system remained in a complex and mixed state of transition, which exhibited characteristics from various healthcare models\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, such as the Beveridge model (e.g., healthcare institutions primarily managed by the government\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e), the Bismarck model (e.g., residents and workers required to contribute to public health insurance\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e), the U.S. model (e.g., different populations covered by distinct health insurance reimbursement schemes\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e), and the uninsured model (e.g., residents still paying an average of about 30% of out-of-pocket medical expenses even with insurance\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e). A hallmark of this system is its open market dynamic, granting patients the freedom to access medical care from any facility nationwide, assuming they can manage to book an appointment and bear the financial cost\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this system, China's approach to \"primary care\" significantly diverges from Western practices, distinguished primarily by its structural organization and hierarchy rather than the specific medical services it offers \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Chinese primary care practitioners\u0026rsquo; function within an integrated 'unit' system rather than as independent practices. This comprehensive network boasts roughly 900,000 state-administered primary care facilities, including about 35,000 community health centers and an equal number of township health centers, which stand as central pillars of healthcare nationwide\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. With a workforce of approximately 3\u0026nbsp;million clinical doctors, including a small percentage of trained or certified general practitioners (GPs) (less than 10%),, along with a larger number of rural doctors and traditional Chinese medicine practitioners\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Their key responsibility is to deliver essential healthcare services to local communities, work in tandem with nurses and public health officials to establish family doctor groups, engage with specific segments like chronic disease sufferers and the elderly, and implement certain preventive medical services\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. However, despite the theoretically universal access to primary care facilities within China's liberalized healthcare market, a considerable segment of the population\u0026mdash;nearly half\u0026mdash;prefers to bypass these facilities in favor of immediate treatment at general hospitals\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This preference reflects a nuanced decision-making process, influenced by the intricate dynamics of individual health statuses, economic capabilities, and specific medical requirements, resulting in a spectrum of healthcare-seeking behaviors\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This includes selective engagement with various types of facilities or, in certain instances, a complete abstention from seeking healthcare.\u003c/p\u003e \u003cp\u003eEvidence from North American, European, and British Commonwealth contexts suggests that primary care can deliver patient functional health outcomes comparable to specialty care, while also achieving better or equal results in terms of population health, per capita cost, and patient experience\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, China's strategic approach to revitalizing primary care, featuring a unique design, primarily depends on a visionary policy approach at the top level, incorporating insights from the evidence and policy experiences of various countries with diverse healthcare systems and primary care designs. Hence, this study aims to examine the disparities in triple aim outcomes\u0026mdash;health of the population, cost per capita, and patient experience\u0026mdash;among middle-aged and elderly patients with chronic diseases who sought care at either primary care facilities or general hospitals. This endeavor aims to provide direct insights into the performance of China's primary care for a specific population segment within its unique societal and healthcare system context over the seven years following the launch of the healthcare reform initiated in 2010.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design:\u003c/h2\u003e \u003cp\u003eIn this study, the researchers analyzed data from four waves (2011, 2013, 2015, and 2018) of the China Health and Retirement Longitudinal Study (CHARLS). This nationally representative cohort comprises Chinese individuals aged 45 or older, with self-reported data collected through face-to-face interviews. It selected participants from 450 residential communities of China mainland using a multi-stage probability-proportional-to-size technique. Peking University's Biomedical Ethics Review Committee approved the study (IRB00001052-11015). Further information about CHARLS can be found in other sources\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFocusing on residents with chronic diseases, we excluded 5,675, 6246, 7775, and 6725 residents without chronic conditions or with missing data from 2011 to 2018 CHARLS waves (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the CHARLS survey, participants were asked to report clinician-diagnosed chronic diseases, including hypertension, diabetes, dyslipidemia, cancer, stroke, heart disease, liver disease, kidney disease, chronic lung disease, asthma, digestive disease, arthritis, psychiatric disease, and memory-related diseases. Those reporting any of these conditions were considered chronic disease patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIndependent Variable, Outcomes, and Covariates:\u003c/h2\u003e \u003cp\u003e In each of the four CHARLS waves, participants reported the type of facilities they visited for outpatient treatment within the past four weeks. Following the classification method of healthcare facilities in China\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, we categorized them into four groups to represent their visit sites: those visiting only primary care facilities (indicating a preference for primary care), only hospitals (indicating a preference for general hospitals), not visiting any facilities (indicating infrequent healthcare utilization), and visiting both types of facilities.\u003c/p\u003e \u003cp\u003eWe selected three key outcome variables based on the Agency for Healthcare Research and Quality recommendations\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e within the Triple Aim framework to measure healthcare performance. Population health was assessed using residents' self-reported five-level Likert scale. Per capita cost refers to out-of-pocket expense for the visits in the last month, including direct expenses of treatment fees, medication costs, and prescription drugs. We divided medical spending into four levels based on China's average monthly salary in 2011 (approximately 1,200 CNY or 185 USD) \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e: no spending (0 CNY), low spending (1-119 CNY), moderate spending (120\u0026ndash;599 CNY), and high spending (\u0026ge;\u0026thinsp;600 CNY). Patient experience was gauged through the patients' satisfaction with the quality, cost, and convenience of local healthcare services and was included as an outcome in the 2015 and 2018 CHARLS waves. The range of satisfaction responses extended from very satisfied to very dissatisfied.\u003c/p\u003e \u003cp\u003eIn accordance with the existing literature on Triple Aim outcomes in China\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, the researchers incorporated the following covariates: gender, age, region (distinguished between the economically developed eastern region and the non-eastern regions), residential area (urban or rural), family wealth (broken down into quartiles: lowest 25%, 26%-50%, 51%-75%, and the highest 25%), level of education, health insurance scheme (classified into high-coverage, moderate-coverage, low-coverage insurance schemes, and no insurance\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e), presence of multimorbidity, adherence to the WHO-recommended levels of physical activity\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, smoking status, alcohol consumption, presence of Activities of Daily Living (ADL) disability and Instrumental Activities of Daily Living (IADL) disability\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe researchers analyzed the sociodemographic characteristics of patients from 2011 to 2018 using descriptive statistics and compared differences in characteristics of patients visiting different healthcare facilities using a Chi-square test. The researchers then reported on the health status and monthly out-of-pocket doctor visit expenditure for patients visiting either primary care facilities or hospitals exclusively from 2011 to 2018, while patient satisfaction from 2015 to 2018.\u003c/p\u003e \u003cp\u003eA multilevel model was constructed using a random intercepts model, with patients at the first level and survey time at the second level. The independent variable was the healthcare facilities type (primarily sought care at primary care facilities or at general hospitals), and the outcomes were health status, monthly out-of-pocket doctor visit expenditure, and patient satisfaction. Based on previous literature\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, all covariates were used for the health status model, related covariates and health status variables for the medical expenditure model, and related covariates and medical expenditure variables for the patient satisfaction model. The researchers began with a null model, calculated level 1 and 2 variances, and the variance partition coefficient (VPC). We sequentially tested potentially related level 1 covariates with dependent variables (P\u0026thinsp;\u0026le;\u0026thinsp;0.2) and included significant covariates in the multilevel model. We used backward stepwise elimination until only significant associations remained. Statistical analysis was conducted using Stata 17.0 SE, with a significance level of p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThree sensitivity analyses were conducted. The first addressed endogeneity by using two instrumental variables\u0026mdash;marital status and family size\u0026mdash;a study based on another renowned database in China, the China Family Panel Studies, on residents' propensity to seek primary healthcare has confirmed that these variables are related to healthcare facility preferences but not directly associated with health status, medical expenses, or patient satisfaction.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. In the second analysis, we employed imputed data in accordance with guidelines for longitudinal datasets\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e and used the Last Observation Carried Forward method to re-run similar models, verifying whether the relationships between independent and dependent variables remained significant. In the third sensitivity analysis, the researchers exclusively analyzed data from patients who had only been diagnosed with hypertension, in order to eliminate the confounding effects of other chronic diseases and ascertain whether the results remained statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reveals the sociodemographic backgrounds, health insurance coverage, lifestyle habits, and health conditions of chronic disease patients in 2011, as observed by us. Compared to patients who chose hospital care, we found that those who exclusively turned to primary care facilities were predominantly from specific demographics, including at least 15% more rural residents (70.6% vs. 46.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), individuals with primary school education or less (78.6% vs. 58.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), households in the bottom 50% wealth bracket (60.1% vs. 43.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), those currently employed (66.9% vs. 49.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and participants covered by health insurance plans offering minimal coverage (83.6% vs. 59.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This trend persisted across the data for 2013, 2015, and 2018, as shown in our Supplementary Tables\u0026nbsp;1\u0026ndash;3. In 2011, we noted a marginally higher ADL disability rate among patients who only visited primary care facilities compared to those who went to hospitals (33.7% vs. 30.0%, p\u0026thinsp;=\u0026thinsp;0.051). While the differences in 2013 and 2015 were not statistically significant, by 2018, a significant increase in ADL disability rate was evident among patients opting for primary care (40.64% vs. 34.28%, p\u0026thinsp;=\u0026thinsp;0.032), as detailed in our eTables 1\u0026ndash;3.\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\u003eSociodemographic characteristics of patients seeking care at different healthcare facilities in 2011\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eVisited primary care facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eVisited hospitals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eDid not visit any healthcare facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eVisited both healthcare facilities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e46.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e63.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e53.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e37.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;74 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;74 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRegion(total\u0026thinsp;=\u0026thinsp;11604)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-eastern region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e70.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban Community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e44.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ec\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e59.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation(total\u0026thinsp;=\u0026thinsp;12018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLowest 25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e26.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26%-50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51%-75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest 25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth insurance scheme(total\u0026thinsp;=\u0026thinsp;11984)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-coverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eModerate-coverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow coverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e71.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultimorbidity(total\u0026thinsp;=\u0026thinsp;11974)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e56.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking(total\u0026thinsp;=\u0026thinsp;11989)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e71.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAlcohol consumption(total\u0026thinsp;=\u0026thinsp;11984)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e69.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWHO recommended level of physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e61.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e38.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePresence of ADL disability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e65.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e69.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePresence of IADL disability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e39.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e26.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e From our analysis spanning 2011 to 2018, we observed that the percentages of patients reporting poor or very poor health within 1\u0026ndash;4 weeks after an outpatient visit remained fairly consistent between those attending primary care facilities and hospitals, with minor variations of -1.2%, -0.6%, -3.1%, and 2.8% respectively, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.a. Over these years, we documented a rise in the occurrence of high medical expenditures for both facility types, climbing from 6.7\u0026ndash;18% for primary care facilities and from 43.2\u0026ndash;49.7% for hospitals, the latter always significantly higher, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.b. Between 2015 and 2018, the percentage of patients expressing either relative or high satisfaction with local health services slightly declined from 42\u0026ndash;38.1% for primary care facilities, and from 38.4\u0026ndash;35.2% for hospitals, with primary care consistently achieving a bit higher satisfaction rates, as we found in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.c.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of our multilevel analysis, showing that patients visiting hospitals within a month tend to have worse health outcomes (OR\u0026thinsp;=\u0026thinsp;1.08, 95% CI 1.04\u0026ndash;1.11; p\u0026thinsp;=\u0026thinsp;0.002) and incur higher medical costs (OR\u0026thinsp;=\u0026thinsp;1.99, 95% CI 1.93\u0026ndash;2.06; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those opting for primary care facilities. Conversely, there is no significant difference in patient satisfaction between the two groups (OR\u0026thinsp;=\u0026thinsp;0.99, 95% CI 0.91\u0026ndash;1.06; p\u0026thinsp;=\u0026thinsp;0.85). Our endogeneity tests, employing two instrumental variables, confirm the absence of significant endogeneity in all three models (p\u0026thinsp;=\u0026thinsp;0.063, 0.051, 0.058, respectively). Analyses using imputed data also highlight significant impacts on health status and medical costs (OR\u0026thinsp;=\u0026thinsp;1.07, 95% CI 1.01\u0026ndash;1.09; p\u0026thinsp;=\u0026thinsp;0.007 and OR\u0026thinsp;=\u0026thinsp;1.92, 95% CI 1.85\u0026ndash;1.99; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). In subgroups consisting solely of hypertensive patients, while health outcomes show no significance (OR\u0026thinsp;=\u0026thinsp;0.99, 95% CI 0.83\u0026ndash;1.18; p\u0026thinsp;=\u0026thinsp;0.901), the findings on medical expenses remain notably significant (OR\u0026thinsp;=\u0026thinsp;2.02, 95% CI 1.71\u0026ndash;2.38; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (refer to eTables 4\u0026ndash;6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This study's key finding reveals that among participants aged 45 and above with chronic diseases, those utilizing outpatient services in primary care facilities achieve similar or better health outcomes, comparable patient satisfaction, and significantly lower medical costs, despite comparable functional status (ADL disability rates) to those treated in hospitals. This research highlights the systemic and holistic contribution of primary care to healthcare performance within both the societal and health system contexts of China.\u003c/p\u003e \u003cp\u003eGiven the incentives provided by China's health authorities to encourage residents to use primary care facilities, including medical reimbursement rates approximately 10% higher than those for hospitals\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, and the typically limited demand for complex procedures and expensive drugs and equipment at primary care facilities\u0026mdash;due to their general unavailability\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e\u0026mdash;it's not surprising that patients primarily seeking care at these facilities incur significantly lower medical expenses than those who primarily visit hospitals. Additionally, considering the issues widely criticized by residents at China's large general hospitals, such as infamously long wait times, confusing care pathways, and a more mechanized, speed-focused approach to diagnosis and treatment\u0026mdash;despite their better equipment and medications\u0026mdash;it's understandable why patient satisfaction might not significantly surpass that of primary care facilities\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, one of the most striking findings of this study is that patients primarily treated at primary care facilities exhibit health outcomes one month post-treatment that are as good as, or even better than, those of patients primarily treated at hospitals. This becomes even more remarkable when considering the significant gaps in resources and clinical capacity between Chinese primary care facilities and hospitals.\u003c/p\u003e \u003cp\u003eThis result can be interpreted in two ways: First, it might be an artifact of data analysis bias. A key contextual feature of China's primary care system is its unstable and non-universal connection with the community\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In practice, this often translates to patients with better socioeconomic status, more severe illnesses, and a need for highly technical doctors, equipment, and medications opting to directly seek care at general hospitals, thus stepping outside the coverage of the resource-limited primary care facilities\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This context could lead to significant confounding in measuring population health outcomes: namely, that patients who seek care at primary care facilities are healthier might be because those who are healthier choose to go to primary care facilities, not necessarily because primary care improves health outcomes more effectively. In this study, although we employed several methods to bolster the robustness of our findings\u0026mdash;such as comparing ADL differences between groups, using instrumental variables to test for significant causality, and conducting subgroup analyses on hypertensive patients only, which yielded positive results\u0026mdash;looking at it neutrally, the precision of our independent and outcome variables, derived from survey data, including patients' verbal feedback on healthcare experiences and self-reported health outcomes, is not highly accurate. Given these considerations, we cannot be fully confident that China's primary care services can achieve stronger population health outcomes than general hospitals based on our findings.\u003c/p\u003e \u003cp\u003eDespite this, evidence also exists supporting a second interpretation, where primary care may produce superior overall performance through a unique set of functional characteristics, such as accessibility, comprehensiveness, continuity, and coordination\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Not only in some countries in North America and Europe, but even within China's unique primary care system, several studies have confirmed the existence of these functional characteristics and their impact on population health\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. They reflect that, despite potential limitations in the comprehensiveness of medical and health services and coordination with general hospitals, China's primary care, thanks to a network of primary care facilities built half a century ago, might have strong advantages in accessibility and continuity compared to general hospitals\u003csup\u003e\u003cspan additionalcitationids=\"CR41 CR42 CR43\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. A large-scale, local randomized controlled trial have confirmed that primary care interventions by rural physicians, who are often perceived as lacking clinical expertise, medication, and medical equipment, can effectively control blood pressure in hypertensive patients\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. This has significant clinical implications for preventing complications such as cardiovascular disease, stroke, and kidney disease\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, the socioeconomic characteristics of the studied population are an important contextual factor to consider. In this study, we found a disproportionately high representation of patients in a disadvantaged socioeconomic status. This finding aligns with previous nationwide studies examining Chinese residents' healthcare facility preferences\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Despite the rise in China's per capita income from \u0026yen;18,310 (approximately 2,834 USD) to \u0026yen;28,228 (around 4,269 USD) between 2011 and 2018, rural income was half that amount\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Coupled with the concentration of hospitals in eastern China's urban areas and rural healthcare expenditure being less than 30% of urban costs, it becomes evident that China's primary care continues to be an essential healthcare resource for more than half of the population, especially its vulnerable populations, even after half a century\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Moreover, the number of patients seeking care at primary care facilities was approximately double that of those seeking care at hospitals. Past evidence shows that primary care services may have particularly significant performance impacts on this population group\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, although we cannot assert based on our current findings that China's primary care system has higher health performance than the general hospital system, this study indeed presents a possibility: in the current healthcare system in China, within this open market where patients freely choose, the primary care sector for some chronic disease patients\u0026mdash;especially those in a socioeconomically disadvantaged position\u0026mdash;could achieve health maintenance and improvement outcomes with limited costs, not inferior to those provided by large general hospitals. In our ongoing work, we are using more precise measurement tools and indicators, such as EQ-5D-5L for population health, clinical diagnostic outcomes for chronic diseases, and Person-Centered Primary Care Measure for primary care functional features, to evaluate local primary care functionality, its relationship with improved Triple Aim outcomes for residents, and its impact on enhancing specialized healthcare and clinical services for the key target population. Additionally, we plan to gain more detailed information on the existence of functional features of Chinese primary care experienced by patients, and the specific mechanisms for maintaining and improving the health status of chronic disease patients through qualitative research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study demonstrates that primary care in China can lead to similar or better health outcomes and significantly lower medical costs for patients aged 45 and above with chronic diseases. Although the background environment of the study and some limitations of the data may weaken our confidence in this finding, it indeed shows that China's primary care for some chronic disease patients\u0026mdash;especially those in a socioeconomically disadvantaged position\u0026mdash;can produce health maintenance and improvement outcomes with limited costs, not inferior to those provided by large general hospitals. The findings call for increased government investment in primary care resources, prioritizing affordability in all primary care services and features, and enhancing primary care functions within existing healthcare policies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthorship contributions\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eConceptualization, Y.W.; Methodology, Y.W and H.C; Data curation, Y.W; Formal analysis, Y.W.; Funding acquisition, H.F; Project administration, H.F; Resources, Y.W; Supervision, H.F.; Validation, Y.W; Writing\u0026mdash;original draft, Y.W.; Writing\u0026mdash;review and editing, Y.W., H.Y., H.C., H.J., C.Z and H.F. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics Approval statement:\u0026nbsp;\u003c/strong\u003ePeking University\u0026apos;s Biomedical Ethics Review Committee approved the study (IRB00001052-11015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe are deeply grateful to Prof. Kurt Stange for conducting an external review of our manuscript and offering valuable feedback and suggestions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by the Natural Science Foundation of Beijing, China (Grant No. 9222013).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrior presentations:\u003c/strong\u003e None.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWeiyuan C. 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Individuals without chronic conditions or with incomplete data were excluded.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe analysis encompassed 50,800 subjects. Those who visited hospitals for outpatient treatment\u0026mdash;mainly urban residents with higher education and income levels, and with comprehensive insurance coverage\u0026mdash;demonstrated poorer health outcomes (OR\u0026thinsp;=\u0026thinsp;1.06, 95%CI 1.02\u0026ndash;1.10, p\u0026thinsp;=\u0026thinsp;0.002) and higher medical expenses (OR\u0026thinsp;=\u0026thinsp;1.99, 95% CI 1.93\u0026ndash;2.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those who utilized primary care facilities. No significant difference was observed in satisfaction levels between the two groups (OR\u0026thinsp;=\u0026thinsp;0.99, 95% CI 0.92\u0026ndash;1.07, p\u0026thinsp;=\u0026thinsp;0.85).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study indicates that for patients over 45 with chronic diseases, China's primary care can achieve health outcomes comparable to or better than large hospitals, at significantly lower costs. Despite some data limitations, it highlights the effectiveness of primary care in improving health for socioeconomically disadvantaged groups, advocating for more government investment and policy support to enhance primary care's affordability and functionality.\u003c/p\u003e","manuscriptTitle":"China's Revitalized Primary Care and Its Impact on Triple Aims for Chronic Diseases Patients: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 12:35:57","doi":"10.21203/rs.3.rs-4280609/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84a02621-f706-47d1-a657-b5f83c04e670","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-15T09:25:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 12:35:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4280609","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4280609","identity":"rs-4280609","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}