Health in Whose Hands? Impacts of National Health Insurance on Social Solidarity and Individual Responsibility: Evidence from the World Values Survey of Taiwan

Health in Whose Hands? 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Impacts of National Health Insurance on Social Solidarity and Individual Responsibility: Evidence from the World Values Survey of Taiwan Meng-Ling Chang, Chih-Ching Liu, Yue-Chune Lee, Chih-Yuan Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8678924/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Purpose: The impact of state-organized welfare systems on solidarity attitudes remains uncertain due to the limited availability of longitudinal data. This study aimed to examine changes in collective solidarity and individual responsibility attitudes in Taiwan following the implementation of the National Health Insurance (NHI) scheme, using data from the World Values Survey (WVS). Methods: We conducted a repeated cross-sectional analysis using WVS data from 1995 (pre-NHI implementation) and 2005 (post-NHI implementation). Participants were Taiwanese adults aged 18 and older. Generalized Linear Mixed Models (GLMMs) were used to evaluate factors influencing solidarity attitudes. Age- and Sex-Matched 1:1 Matching was applied to balance covariates, and the Likelihood Ratio Test (LRT) was used to assess the significance of the effect of the NHI policy. Results: Our findings demonstrated stronger collective solidarity among female participants, greater perceptions of unfairness among respondents, and lower quality of life among those reporting unfairness. GLMM analysis revealed a significant reduction of 0.70 units in government responsibility scores a decade after the NHI implementation (β = -0.70, p < 0.0001), indicating increased perceptions of government responsibility. The Likelihood Ratio Test confirmed improved model fit when incorporating NHI policy effects (likelihood ratio = 4.2, p = 0.0404). Conclusion: Taiwan’s NHI system reinforces collective solidarity and concurrently promotes perceptions of individual responsibility. Notably, females, perceived fairness, and lower quality of life are significant factors associated with greater reliance on government healthcare provision. Highlight Taiwan's National Health Insurance (NHI) provides universal coverage and access within a state-organized framework. Taiwan’s NHI model significantly enhances collective solidarity by increasing perceived government responsibility. Government responsibility scores decreased by 0.70 units 10 years after NHI implementation, indicating a preference for government responsibility in healthcare provision. Females, perceived fairness, and lower quality of life are associated with greater reliance on government healthcare. 1. Introduction Solidarity has been the core principle of health insurance since its implementation [1]. European solidarity-based healthcare systems [2, 3] have implemented mandatory measures to integrate their populations into a unified healthcare framework based on contractual solidarity [4]. The concept of contractual solidarity provides the ideological rationale for individuals' transfer of financial contributions through compulsory health insurance schemes, guaranteeing equal access to healthcare for those in need [5]. National Health Insurance (NHI) serves as a cornerstone of welfare service provision in numerous countries [6-11]. It is widely accepted that NHI should build on solidarity, ensuring all citizens receive collective support and fair access to healthcare [12]. By integrating mutual aid, risk-sharing, and technical control, NHI has become a successful welfare governance tool in the twentieth century [7, 10]. Governments responsible for a robust public sector unite individuals into a common social insurance system defined as contractual solidarity [13]. With collectively financed risk-sharing arrangements of care covering all citizens with equal rights to care, some researchers have assumed that the adverse effects on voluntary solidarity may be crowded out by an increasing degree of compulsory solidarity [14]. However, the rise of chronic diseases, along with significant advancements in public health and medical technology, has led to a decrease in mortality rates and demographic shifts characterized by an aging population. These changes have substantially increased as the gap between demands and limited healthcare services widens, the shortage puts immense strain on solidarity within society and across generations [12]. The mainstream liberal tradition positions the autonomous individual as the central unit of analysis [15]. Consequently, policymakers, healthcare providers, and health economists advocate reactivating the "principle of responsibility," or "responsibilization," which holds individuals accountable for their health [15, 16]. Healthcare reforms have introduced the concept of individual responsibility to increase cost-sharing [9] and promote the belief that health is an individual responsibility rather than a government responsibility [17]. The trends analyzed in this issue reflect an increased emphasis on individual responsibility or state-aid solidarity, which remain significant topics of research and policy debate [3, 4, 18]. How does NHI implementation influence government and individual responsibility regarding healthcare coverage and provision [10, 12]? Nonetheless, the impact of state-organized, compulsory solidarity provisions on individual-level solidarity remains unclear due to limited time-series data [19, 20]. Since 1995, Taiwan's NHI program has been based on mutual assistance and risk-sharing within a state-organized compulsory health insurance system. This unique context offers an invaluable opportunity for longitudinal intervention research to explore the dynamics of contractual solidarity and individual responsibility. This study aims to (1) examine solidarity attitudes in Taiwan using World Values Survey (WVS) data and (2) investigate the impact of Taiwan’s NHI program implementation on perceptions of solidarity by comparing responses before and after the policy change. 2. Methods 2.1. R esearch design Our research design was a repeated cross-sectional study comparing the directional change of government or individual responsibility after implementing the NHI program. 2.2. Setting With a population of approximately 23 million, Taiwan is generally categorized within Esping-Andersen’s typology as a conservative welfare state regime [6]. The Taiwanese government prioritizes state intervention to foster substantial social solidarity. This intervention manifests through cohesive social security frameworks and diverse public service provisions. Social insurance schemes fundamentally underpin Taiwan’s welfare system. Based on social solidarity, Taiwan's NHI exemplifies a single-payer, mandatory social insurance model with an impressive 99.9% coverage rate and 90% enrollee satisfaction. It operates on a pay-for-service model, adhering to the principle that healthcare is a fundamental human right. This system has facilitated universal, high-quality healthcare at accessible costs, aiding socially and economically disadvantaged segments [3, 10, 21]. All insured individuals must pay an income-related premium of about 2.5% compared to 4.1% in Japan and 6.3% to 7.5% in Germany in 2005 [22]. Taiwan’s NHI promotes income solidarity by adjusting premiums based on varying income levels, supporting its universal coverage and financial sustainability goals [22]. 2.3. Data and participants The WVS encompasses 120 countries and represents 94.5% of the global population. It is the most comprehensive cross-national time-series study of human beliefs and values [23]. This extensive coverage makes it a significant research program dedicated to the academic exploration of the sociocultural values of people worldwide [23]. Taiwan participated in the 1995 and 2005 waves of the study. This study used data from the Taiwanese cohort, a nationally representative sample of citizens aged 18 and older, to reflect the adult population of Taiwan. Data collection was conducted through face-to-face interviews. The sample sizes for the respective waves were substantial, with 780 respondents in the 1995 wave and 1227 respondents in the 2005 wave. Age- and Sex-Matched 1:1 matching (Age/Sex-Matched 1:1) was utilized to balance the distribution of covariates between individuals before and after the NHI policy intervention. 2.4. Concepts and measurements Taiwan’s 1995 pre-NHI (before the NHI launch) and 2005 post-NHI (10 years after NHI program) WVS data enable a unique natural experiment examining whether NHI crowds out individual responsibility. This study uses a longitudinal analysis approach to compare the changes in healthcare responsibility before and after the implementation of the NHI. The data provides an invaluable opportunity to observe how a major policy intervention influences social and individual values over an extended period. By analyzing this data, researchers can understand how societal attitudes toward healthcare and welfare responsibilities have evolved in response to the NHI implementation. 2.5 V ariable s definition 2.5.1 Dependent variable The variable 'Government responsibility,' based on questionnaires from the 1995 and 2005 WVS waves, is the dependent variable in this study. It quantifies attitudes toward allocating responsibility for welfare provision or individual responsibility to support self-sufficiency. This is measured using a Likert scale ranging from 1 to 10. A score of 1 indicates the belief that 'the government should take more responsibility,' while a score of 10 denotes the belief that 'people should take more responsibility.' This scale effectively captures an individual’s position on the spectrum between state responsibility and individual responsibility within societal support systems [24]. By analyzing these scores, the study aims to understand how perceptions of responsibility for welfare have shifted over time, particularly in response to policy changes such as the introduction of the NHI in Taiwan." 2.5.2. Policy interventional variable The NHI as an interventional variable provides a lens to explore the relationship between health policy and solidarity notions. This variable allows researchers to examine the direct and indirect effects of the NHI on societal attitudes and behaviors. 2.5.3. Covariates To explain potential compositional effects, we control for individual-level characteristics, including sex, age, religiosity, education, marital status, employment status, income, and degree of urbanization [8, 25]. Psychocognitive framing [8, 26] and societal conditions variables, including perceived health, quality of life (QOL), trust in government, and perceptions of fairness, are also integrated into the analysis [8, 25]. 2.6. Data analysis We utilized Generalized Linear Mixed Models (GLMMs) as our data analysis methodological tool to examine the effects of various factors on the dependent variable, government responsibility as a solidarity notion, within the context of repeated cross-sectional data. The NHI program implementation was treated as an intervention dummy variable. The Likelihood Ratio Test (LRT) was employed to evaluate the impact of NHI. This test compares the -2 Log Likelihood values of both the full model (which includes the intervention variable) and the partial model (without the intervention). The LRT identifies statistically significant differences between these models, indicating the effect of the NHI intervention. 3. Results 3.1. Participants characteristics We utilized the Age/Sex-Matched 1:1 method to balance the distribution of covariates between individuals surveyed before and after the NHI policy intervention. Before matching, some covariates had absolute standardized mean differences (ASMDs) exceeding 0.2, indicating substantial imbalance (Table 1). Key variables such as age, marital status, region, education, and income showed ASMDs over 0.1, suggesting some level of imbalance. Austin (2009) states that an ASMD below 0.1 denotes negligible group differences [27]. After 1:1 matching, the matched sample included 765 respondents from the 1995 WVS wave and 765 respondents from the 2005 WVS wave. Most ASMDs were reduced below 0.2, indicating that the matching algorithm effectively balanced the covariates across the two survey waves. The matched analytic sample achieved covariate equivalence between the pre- and post-NHI intervention cohorts based on measured sociodemographic and psychocognitive characteristics, minimizing confounding influences in estimating the policy's impact in subsequent analyses. This matching process ensured a better comparison, enhancing the validity of our findings regarding the impact of the NHI policy. 3.2. Characteristics of the research samples in the 1995 and 2005 waves Despite the application of Age/Sex-Matched, several demographic differences persisted between the 1995 and 2005 survey waves (Table 1). Specifically, in 2005, a larger proportion of participants were younger (18-34 years increased from 30.9% to 35.4%), unmarried (increased from 20.0% to 29.7%), and reported having a religion (increased from 0% to 26.7%) (Table 2). Educational attainment rose in 2005, with more participants achieving college or higher education (from 40.7% to 45.4%). There were significantly fewer high-income participants in 2005 (decreased from 36.7% to 3.0%), counterbalanced by a substantial rise in middle-income respondents (from 30.3% to 69.7%). Employment rates also increased from 62.5% to 68.0%. Biopsychological characteristics also differed between the matched waves. Perceived fairness declined in 2005, from 37.6% to 23.3%. The proportion of individuals rating their happiness as high or higher decreased from 91.1% in 1995 to 85.9% in 2005. Self-rated health showed more "good" health but fewer "not good" health ratings in 2005. Similar trends were observed for QOL evaluations. There was a significant shift in the measure of solidarity between the two waves. In the 1995 wave, the government responsibility score averaged 5.535 (95% CI: 5.363-5.708). By the 2005 wave, this average dropped to 5.029 (95% CI: 4.844-5.214), a statistically significant change (p<0.0001). 3.3. Association of longitudinal predictors of solidarity before and after Taiwan’s NHI policy intervention The Generalized Linear Mixed Models (GLMMs) analysis showed baseline government responsibility scores (intercept values) of 4.79 for the 1995 wave and 5.12 for the 2005 wave (Table 3). The associations between government responsibility scores and control variables like age, marital status, education, religion, income, occupation, and urbanization were small and insignificant in 1995 and 2005. Males had slightly higher government responsibility scores compared to females. In 1995, males reported 0.34 units higher scores than females (β=0.34, p=0.3351); in 2005, this difference was 0.33 units (β=0.33, p=0.0174). Perceived unfairness was a strong predictor of government responsibility scores. In 1995, unfairness was associated with a 0.74 unit increase (β=0.74, p<0.0001), and this association remained in 2005 (β=0.74, p<0.0001). Low QOL was linked to a preference for government responsibility. In 1995, low QOL was associated with a -0.81 unit decrease (β=-0.81, p=0.0124), and in 2005, this relationship persisted (β=-0.81, p=0.0122). The LRT comparing the two models revealed that including the NHI policy in the 2005 full model resulted in a significant decrease of 0.70 units in the government responsibility score (β= -0.70, p<0.0001). The likelihood ratio 4.2 (p=0.0404) between the full and partial models indicated a significantly improved model fit when accounting for the NHI policy intervention. 4. Discussion Healthcare is universally acknowledged as a social entitlement, with governments playing a crucial role in its provision [4, 9, 12, 28]. This study, a longitudinal repeated cross-sectional analysis using data from the WVS, explores the dynamics of solidarity in the context of Taiwan’s NHI implementation. Solidarity in healthcare is organized across three distinct levels. At the interpersonal level, solidarity manifests through individual actions where people identify with others’ needs and willingly share costs, often driven by a sense of reciprocity. The second level includes group-based activities such as health information sharing and fundraising efforts. The third and most structured level involves contractual and legal frameworks that institutionalize solidarity through public healthcare systems, thus ensuring equitable access to health services [15]. The International Social Survey Program and the European Values Study adopted the concept of 'willingness to improve the living conditions of other people,' which is traditionally considered the predominant source for measuring solidarity through large-scale survey research [8, 25]. These surveys primarily focus on individual-level willingness to assist specific groups of people, reflecting a targeted approach to assessing solidarity. Our study utilizes the WVS definition of solidarity, which focuses on the government and individual responsibility to support self-sufficiency. This dual focus allows us to assess how the NHI influences solidarity perceptions across different societal demographics, including age, gender, marital status, employment status, religious beliefs, and socioeconomic status. In the methodological approach of this study, we employed GLMMs to analyze repeated cross-sectional data. Our study examined the relationship between government responsibility scores and NHI program implementation while controlling covarites. The dependent variable was the government responsibility score, and the intervention dummy variable measured whether or not an NHI program had been implemented. Control variables were included to account for potential confounding factors, such as participants' age, sex, education level, and perceptions of healthcare issues. GLMMs are more appropriate for longitudinal data with multilevel structures [29]. Given the repeated cross-sectional study design, GLMMs were utilized to analyze the impact of variables over time while accounting for individual and cluster-level variations. The models effectively partition the total variance into within-individual, between-individual, and residual error components. By examining the percentage of variance explained at each level, inferences can be made regarding the predominant source of variability in the data [30]. The LRT was conducted to assess the impact of the 1995 NHI policy intervention by comparing two nested models. The partial model represented the pre-intervention period before 1995, while the full model incorporated the potential effects of the NHI policy implemented ten years in 2005, which our study examined through LRT between pre- and post-intervention models. The findings indicate a substantial influence of the NHI policy on reducing government responsibility scores, suggesting an increased expectation for the government to assume greater responsibility in healthcare provision. Sociodemographic factors and welfare state regimes have been shown to affect people’s notions of solidarity, with previous studies indicating that females, older individuals, married individuals, those employed, religious believers, and more affluent and educated respondents generally hold a stronger solidarity notion [8, 25]. Social solidarity rationality is based on trust in institutional or state efficiency and fairness in accessing and distributing welfare provisions [13]. Our analysis reveals that sex plays a significant role in shaping solidarity perceptions, with males typically exhibiting higher government responsibility scores, suggesting a stronger inclination towards individual responsibility in healthcare. These results, along with some related studies, suggest that females have higher collective solidarity. These results and related studies suggest that females have higher collective solidarity [25]. In European welfare states, the basic understanding of solidarity is that everyone is assumed to make a fair financial contribution to a collectively organized insurance system that guarantees equal access to health and social care for all members of society. Thus, fairness forms the foundation of solidarity, which seems an essential and inherent element [7, 25]. When people believe systems and policies are fair, they may be more willing to unite behind them through acts of solidarity and support [7]. Our analysis perceived fairness as a strong predictor of government responsibility scores, highlighting the importance of fairness in fostering collective solidarity. Individuals with a lower QOL preferred more robust collective solidarity measures, indicating the social impact of perceived needs in healthcare access [21]. Taiwan’s NHI system vertically integrates citizens through a compulsory, universal health insurance system while also horizontally pooling people by health risk-sharing emphasis on mutual assistance. To ensure income solidarity, Taiwan NHI’s general premiums are jointly paid by the insured, corporate employers, and the government, and the rate is kept at approximately 5% [31]. Besides, it also provides premium subsidies for members of vulnerable groups (including low-income and near-poor households, unemployed veterans, workers, and their dependents, the physically and mentally disabled, and unemployed indigenous citizens) [31]. Approximately 4% of insured people possess valid major illness/injury certificates. For these individuals, copayments have been waived to treat their catastrophic illnesses and injuries and ensure financial relief and support. Taiwan NHI provides a comprehensive range of healthcare services, including outpatient care, inpatient care, traditional Chinese medicine, dental care, childbirth, post-acute care and rehabilitation, home health care, palliative care, and rehabilitation for chronic mental illness. The NHI covers medical payments for diagnosis, examination, laboratory tests, surgery, anesthesia, medication, materials, treatment, and nursing care [31]. The healthcare systems in Europe and Taiwan represent contrasting approaches to balancing collective solidarity and individual responsibility [32]. The European model emphasizes a two-tiered system [18], with a publicly funded tier for basic healthcare needs and a market-driven tier for more personalized or advanced services. This approach reflects a shift towards greater individual responsibility, where access to care is increasingly determined by one’s ability to pay rather than needs [21]. The solidarity-decline thesis suggests that healthcare reforms adversely affect solidarity [33]. Critics argue that this erosion of solidarity through cost-sharing undermines the collective ethos of healthcare systems, raising concerns about long-term implications for social cohesion and equitable access [21]. When people believe systems and policies are fair, they may be more willing to unite behind them through acts of solidarity and support. In contrast, Taiwan’s NHI system represents a model that integrates both solidarity and individual responsibility principles. This dual approach reflects an attempt to balance the values of collective welfare and personal accountability within the framework of a state-organized health insurance system. The system’s design acknowledges that while individuals should be accountable for their health, the state is also responsible for providing comprehensive healthcare services, ensuring that no one is excluded due to financial incapacity. This reflects a broader societal value that healthcare is a fundamental right, regardless of personal characteristics or social status [31]. Previous studies have acknowledged the commendable state initiatives to provide healthcare for all vulnerable groups, highlighting the unintended negative repercussions of such an approach. Some argue that excessive reliance on state-provided support measures may undermine individual initiative [13, 34]. Conversely, other research indicated that nationwide, state-controlled, and compulsory welfare schemes institutionalized through social insurance programs could partially compensate for the evident decline in individual solidarity resulting from state policies [12, 33]. While the European model prioritizes individual choice and a market-driven approach, Taiwan’s NHI attempts to maintain a sense of collective welfare while also promoting personal accountability [31]. Our ten years of time-series data suggest that the association between state-organized welfare provisions and notions of individual responsibility remains complex. While some argue that comprehensive welfare systems foster solidaristic attitudes, others contend that excessive reliance on state support may undermine individual initiative [9, 15, 19, 20, 35]. The changing nature of responsibility allocation between the state and individual citizens will undoubtedly lead to more concern between affluent groups such as lower QOL, low-income, and felt unfair groups in accessing healthcare services [12]. 4.1. Strengths This study offers several notable strengths: First, our research provides important real-world empirical evidence illuminating the relationship between policy interventions and societal attitudes toward solidarity. Second, our findings underscore the importance of considering solidarity among the potential effects when formulating large-scale healthcare and social welfare policies. Third, by applying GLMMs to the complex repeated cross-sectional data, we could simultaneously model the systematic effects of the policy intervention while accounting for variations across individuals and time points as random effects. 4.2. L imitations Several limitations of our study should be acknowledged to provide a balanced perspective on our findings. First, the concept of ‘solidarity notions’ lacks a standardized operational definition, posing challenges to the consistency and clarity of our findings. While we aimed to capture societal attitudes towards collective responsibility and individual responsibility, the multidimensional nature of solidarity may not be fully represented by the measures used in our analysis. Second, the Taiwanese WVS cohort data might be influenced by social desirability bias, where respondents provide socially desirable responses rather than their actual attitudes. Third, although repeated cross-sectional data support a Difference-in-Differences (DiD) framework, this study did not adopt that approach. Instead, we used Age/Sex-Matched 1:1 to improve covariate balance between the 1995 and 2005 samples. While Age/Sex-Matched enhances comparability based on observed characteristics, it does not support causal inference, as it cannot address unmeasured confounding or temporal trends. Thus, interpretations based on matched samples should remain cautious. To more robustly evaluate the causal impact of the NHI policy, a quasi-experimental design such as DiD—preferably with a comparison group from a country without universal health insurance during the same period—would offer stronger analytical validity. Four, the generalizability of our results may be limited due to the diversity of healthcare systems and welfare regimes across different countries. Lastly, our study primarily investigates solidarity at the national and individual levels. However, it does not delve into the perspectives and associated thoughts of the intermediary group of healthcare providers. This layer serves as a critical link between the individual and national policy levels, and their insights are vital for a comprehensive understanding of the multi-layered nature of social solidarity. Future research should consider including the perspectives of healthcare providers to provide a more holistic view of how health policies impact solidarity across all healthcare system levels [36]. 5. Conclusion This study significantly enhances the understanding of how national health policies impact social solidarity and individual responsibility. The findings suggest that state-organized systems can foster collective solidarity, demonstrating that comprehensive and inclusive health policies can promote a sense of shared responsibility and support within a society. However, continuous monitoring of the evolving dynamics between the state and individuals is essential to ensure the sustainability and equity of these systems. > Declarations Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work, the author(s) utilized ChatGPT 4.5 to check grammar. After using this tool, the author(s) reviewed and edited the content as needed and assume(s) full responsibility for the final content of the publication. Ethics approval and consent to participate This study was approved by the Institutional Review Board of National Yang-Ming University-YM107035E on May 5, 2018. In accordance with regulations of the National Health Research Institutes, patient identification information was anonymized, such that informed consent was not required. Consent for publication Not applicable. Declaration of generative AI in scientific writing During the preparation of this manuscript, the authors used AI language models, specifically ChatGPT and Claude, for grammar and spelling checks and for debugging SAS code. After using these tools, the authors meticulously reviewed and revised the content as needed. The authors assume full responsibility for the content of this publication. Availability of data and materials The data used in this study are sourced from the World Values Survey (C00173) [Data file]. They can also be accessed through the Survey Research Data Archive at the Center for Survey Research, Research Center for Humanities and Social Sciences, Academia Sinica. For more information, visit the website at https://srda.sinica.edu.tw, DOI: 10.6141/TW-SRDA-C00173-1. Competing Interest declaration The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributors C-Y.L. and C-C.L. studied concept and design, data analysis and interpretation, and manuscript preparation. Y-C.L. and M-L.C. supervise the development of the study concept and design, data analysis and interpretation, and manuscript preparation. All authors have read and approved the manuscript. 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From solidarity to selectivity: the reconstruction of the Dutch social security system 1980–2000. Social Policy Rev. 1998;10:183–202. Prainsack B, Buyx A. Solidarity in contemporary bioethics–towards a new approach. Bioethics. 2012;26(7):343–50. Tables Table 1 Participants’ Characteristics Before and After Age- and Sex-Matched 1:1 Matching in the Taiwan World Value Survey for the 1995 and 2005 Waves. Before matching After matching WVS 1995 wave (N=780) WVS 2005 wave (N=1 2 27) ASMD a WVS 1995 wave (N=765) WVS 2005 wave (N=765) ASMD Sex Female 399 (51.15%) 606 (49.39%) 0.035 393 (51.37%) 393 (51.37%) 0.000 Male 381 (48.85%) 621 (50.61%) 372 (48.63%) 372 (48.63%) Age 18~34 236 (30.26%) 405 (33.01%) 0.162 236 (30.85%) 271 (35.42%) 0.012 35~49 358 (45.90%) 360 (29.34%) 349 (45.62%) 283 (36.99%) 50~64 127 (16.28%) 316 (25.75%) 112 (15.82%) 139 (18.17%) ≥ 65 59 (07.56%) 146 (11.90%) 59 (07.71%) 72 ( 9.41%) M arriage No 155 (19.87%) 367 (29.91%) 0.234 153 (20.00%) 227 (29.67%) 0.225 Yes 625 (80.13%) 860 (70.09%) 612 (80.00%) 538 (70.33%) R egion No 0 (00.00%) 342 (27.87%) 0.879 0 (00.00%) 204 (26.67%) 0.852 Yes 780 (100.00%) 885 (72.13%) 765 (100.00%) 561 (73.33%) Education Primary school 260 (33.42%) 261 (21.27%) 0.145 247 (32.29%) 181 (23.66%) 0.161 High school 207 (26.61%) 481 (39.20%) 207 (27.06%) 237 (30.98%) College & above 311 (39.97%) 485 (39.53%) 311 (40.65%) 347 (45.36%) Income Low 244 (33.84%) 363 (29.71%) 0.415 234 (33.00%) 208 (27.33%) 0.408 Middle 217 (30.10%) 820 (67.10%) 215 (30.32%) 530 (69.65%) High 260 (36.06%) 39 (03.19%) 260 (36.67%) 23 (03.02%) Occupation Unemployment 294 (37.69%) 492 (40.10%) 0.049 287 (37.52%) 245 (32.03%) 0.115 Employment 486 (62.31%) 735 (59.90%) 478 (62.48%) 520 (67.97%) Urbanization Rural 343 (43.97%) 487 (39.69%) 0.087 334 (43.66%) 310 (40.52%) 0.064 Urban 437 (56.03%) 740 (60.31%) 431 (56.34%) 455 (59.48%) ASMD: absolute standardized mean differences; WVS: World Value Survey Table 2 The comparison of participant characteristics in the Taiwan World Value Survey for the 1995 and 2005 waves after Age- and Sex-Matched 1:1 Matching. WVS 1995 wave (N=765) WVS 2005 wave (N=765) p-value Sex Female 393 (51.37%) 393 (51.37%) 1.000 Male 372 (48.63%) 372 (48.63%) Age 18~34 236 (30.85%) 271 (35.42%) 0.0079 35~49 349 (45.62%) 283 (36.99%) 50~64 112 (15.82%) 139 (18.17%) ≥ 65 59 (07.71%) 72 ( 9.41%) Marriage No 153 (20.00%) 227 (29.67%) <.0001 Yes 612 (80.00%) 538 (70.33%) R egion No 0 (00.00%) 204 (26.67%) <.0001 Yes 765 (100.00%) 561 (73.33%) Education Primary school 247 (32.29%) 181 (23.66%) 0.0008 High school 207 (27.06%) 237 (30.98%) College and above 311 (40.65%) 347 (45.36%) Income Low 234 (33.00%) 208 (27.33%) <.0001 Middle 215 (30.32%) 530 (69.65%) High 260 (36.67%) 23 (03.02%) Occupation Unemployment 287 (37.52%) 245 (32.03%) 0.0242 Employment 478 (62.48%) 520 (67.97%) Urbanization Rural 334 (43.66%) 310 (40.52%) 0.2139 Urban 431 (56.34%) 455 (59.48%) Fairness No 468 (62.40%) 585 (76.67%) <.0001 Yes 282 (37.60%) 178 (23.33%) Happiness No 68 (08.94%) 108 (14.12%) 0.0015 Yes 693 (91.06%) 657 (85.88%) Health Good 163 (21.31%) 194 (25.36%) <.0001 Fair 523 (68.37%) 537 (70.20%) Not good 79 (10.33%) 34 (04.44%) Quality of life Good 257 (33.68%) 281 (36.73%) <.0001 Fair 458 (60.03%) 435 (56.86%) Not good 48 (06.29%) 310 (06.41%) Trust No 257 (33.68%) 281 (36.73%) <.0001 Yes 458 (60.03%) 435 (56.86%) 5.535±2.411 (5.363-5.708) 5.029±2.601(4.844-5.214) <.0001 Table 3 Generalized linear mixed models to analyze the impact of variables over time while accounting for individual and cluster-level. WVS 1995 wave WVS 2005 wave b β SE [95% CI] p-value β SE [95% CI] p-value Intercept 4.79 0.59 . 5.12 0.47 . Control Sex Male (ref=female) 0.34 0.14 (0.06-0.61) 0.3351 0.34 0.14 (0.06--0.61) 0.3351 Age 18-34 (ref=65+) 0.07 0.32 (-0.57-0.70) 0.8349 0.06 0.32 (-0.57-0.69) 0.858 35-49 0.30 0.29 (-0.27-0.87) 0.3067 0.29 0.29 (-0.28-0.86) 0.3237 50-64 0.54 0.29 (-0.03-1.11) 0.065 0.53 0.29 (-0.04-1.10) 0.0662 Marriage No (ref=yes) 0.24 0.18 (-0.12-0.60) 0.1853 0.25 0.18 (-0.11-0.60) 0.18 Education Elementary (ref=college) 0.13 0.22 (-0.29-0.55) 0.5435 0.12 0.22 (-0.30-0.55) 0.5631 High school 0.14 0.17 (-0.19-0.47) 0.4037 0.14 0.17 (-0.19-0.47) 0.4029 Religion No (ref=yes) 0.09 0.21 (-0.32-0.49) 0.6671 0.11 0.21 (-0.30-0.51) 0.612 Income Low (ref=high) -0.25 0.22 (-0.68-0.18) 0.2478 -0.24 0.22 (-0.67-0.19) 0.2778 Middle 0.10 0.20 (-0.30-0.50) 0.6171 0.12 0.20 (-0.28-0.52) 0.547 Occupation Unemployment (ref=yes) 0.07 0.16 (-0.24-0.37) 0.6791 0.06 0.16 (-0.25-0.37) 0.6914 Urbanization Urban (ref=rural) -0.20 0.14 (-0.46-0.07) 0.1403 -0.20 0.14 (-0.46-0.07) 0.1401 Fairness Unfairness (ref=fairness) 0.74 0.15 (0.45-1.02) <.0001 0.74 0.15 (0.45-1.03) <.0001 Happiness No (ref=yes) -0.31 0.23 (-0.75-0.14) 0.1828 -0.30 0.23 (-0.75-0.15) 0.1923 Health Poor (ref=good) 0.08 0.31 (-0.54-0.69) 0.8048 0.09 0.31 (-0.53-0.70) 0.7838 Fair -0.09 0.28 (-0.64-0.47) 0.7517 -0.08 0.28 (-0.64-0.47) 0.7726 Quality of life Low (ref=high) -0.81 0.32 (-1.45--0.18) 0.0124 -0.81 0.32 (-1.45--0.18) 0.0122 Middle -0.39 0.15 (-0.68--0.10) 0.008 -0.39 0.15 (-0.68--0.10) 0.0076 Trust Untrust (ref=trust) -0.19 0.15 (-0.48-0.10) 0.2025 -0.18 0.15 (-0.47-0.11) 0.2137 Policy Intervention NHI policy implementation Partial model (without policy effect) Full model (with policy effect) Predictor Government Responsibility -0.70 0.17 (-1.03--0.37) <.0001 -2 Log Likelihood -13361.2 -13357 Likelihood Ratio Test 4.2 0.0404 * * Likelihood Ratio Test; WVS: World Value Survey; NHI: National Health Insurance; CI: confidence interval Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8678924","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589015100,"identity":"6e16225b-10ed-4f38-88af-84f01d7aa703","order_by":0,"name":"Meng-Ling Chang","email":"","orcid":"","institution":"Taipei City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meng-Ling","middleName":"","lastName":"Chang","suffix":""},{"id":589015101,"identity":"5ab60e9e-abba-4408-a3e5-3020af52e64d","order_by":1,"name":"Chih-Ching Liu","email":"","orcid":"","institution":"National Taipei University of Nursing and Health Science","correspondingAuthor":false,"prefix":"","firstName":"Chih-Ching","middleName":"","lastName":"Liu","suffix":""},{"id":589015102,"identity":"99cd5fbc-f834-42f8-be50-3fcdde049d8e","order_by":2,"name":"Yue-Chune Lee","email":"","orcid":"","institution":"National Yang Ming Chiao Tung University","correspondingAuthor":false,"prefix":"","firstName":"Yue-Chune","middleName":"","lastName":"Lee","suffix":""},{"id":589015103,"identity":"08e89237-d59f-4711-b723-0c33d4cba507","order_by":3,"name":"Chih-Yuan Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACe2b25z8/VICYPERqMWzvMZCWOGOA0EJQp8GZMwwSvG0kabmRw2AgOe9PHj/72QOMXyoOM9hLJBDSkv4goXCbQbFkT14Cs8yZwww8hLUkGByQ3GaQuOEGjwGzZFsaA480IS33Hxg28M4xSNxPvJYbCcYMvA1AWyR4DBg/ttkQ1mI4I8eMWeKYcbHEmRyDwwxnbHh47j/Ar8VeIv0Z44cauTz+9jOGD39USMix9xzArwUGwI45zEN8GoBqYfxBtPpRMApGwSgYSQAAPJJBcs1dkv8AAAAASUVORK5CYII=","orcid":"","institution":"Taipei City Hospital","correspondingAuthor":true,"prefix":"","firstName":"Chih-Yuan","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2026-01-23 11:53:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8678924/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8678924/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102379145,"identity":"4b33a8a9-0a59-4cdd-87e4-f6fe13327e37","added_by":"auto","created_at":"2026-02-11 06:23:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1419901,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8678924/v1/4495795c-852e-4af3-ba05-5b37dc122762.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health in Whose Hands? Impacts of National Health Insurance on Social Solidarity and Individual Responsibility: Evidence from the World Values Survey of Taiwan","fulltext":[{"header":"Highlight","content":"\u003cul\u003e\n \u003cli\u003eTaiwan\u0026apos;s National Health Insurance (NHI) provides universal coverage and access within a state-organized framework.\u003c/li\u003e\n \u003cli\u003eTaiwan\u0026rsquo;s NHI model significantly enhances collective solidarity by increasing perceived government responsibility.\u003c/li\u003e\n \u003cli\u003eGovernment responsibility scores decreased by 0.70 units 10 years after NHI implementation, indicating a preference for government responsibility in healthcare provision.\u003c/li\u003e\n \u003cli\u003eFemales, perceived fairness, and lower quality of life are associated with greater reliance on government healthcare.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eSolidarity has been the core principle of health insurance since its implementation [1].\u0026nbsp;European solidarity-based healthcare systems\u0026nbsp;[2, 3]\u0026nbsp;have implemented mandatory measures to integrate their populations into a unified healthcare framework based on contractual solidarity\u0026nbsp;[4]. The concept of contractual solidarity provides the ideological rationale for individuals\u0026apos; transfer of financial contributions through compulsory health insurance schemes, guaranteeing equal access to healthcare for those in need [5].\u003c/p\u003e\n\u003cp\u003eNational Health Insurance (NHI) serves as a cornerstone of welfare service provision in numerous countries [6-11]. It is widely accepted that NHI should build on solidarity, ensuring all citizens receive collective support and fair access to healthcare [12]. By integrating mutual aid, risk-sharing, and technical control, NHI has become a successful welfare governance tool in the twentieth century [7, 10]. Governments responsible for a robust public sector unite individuals into a common social insurance system defined as contractual solidarity [13]. With collectively financed risk-sharing arrangements of care covering all citizens with equal rights to care, some researchers have assumed that the adverse effects on voluntary solidarity may be crowded out by an increasing degree of compulsory solidarity [14]. However, the rise of chronic diseases, along with significant advancements in public health and medical technology, has led to a decrease in mortality rates and demographic shifts characterized by an aging population. These changes have substantially increased as the gap between demands and limited healthcare services widens, the shortage puts immense strain on solidarity within society and across generations [12].\u003c/p\u003e\n\u003cp\u003eThe mainstream liberal tradition positions the autonomous individual as the central unit of analysis [15]. Consequently, policymakers, healthcare providers, and health economists advocate reactivating the \u0026quot;principle of responsibility,\u0026quot; or \u0026quot;responsibilization,\u0026quot; which holds individuals accountable for their health [15, 16]. Healthcare reforms have introduced the concept of individual responsibility to increase cost-sharing [9] and promote the belief that health is an individual responsibility rather than a government responsibility [17]. The trends analyzed in this issue reflect an increased emphasis on individual responsibility or state-aid solidarity, which remain significant topics of research and policy debate [3, 4, 18]. How does NHI implementation influence government and individual responsibility regarding healthcare coverage and provision [10, 12]? Nonetheless, the impact of state-organized, compulsory solidarity provisions on individual-level solidarity remains unclear due to limited time-series data [19, 20]. Since 1995, Taiwan\u0026apos;s NHI program has been based on mutual assistance and risk-sharing within a state-organized compulsory health insurance system. This unique context offers an invaluable opportunity for longitudinal intervention research to explore the dynamics of contractual solidarity and individual responsibility. This study aims to (1) examine solidarity attitudes in Taiwan using World Values Survey (WVS) data and (2) investigate the impact of Taiwan\u0026rsquo;s NHI program implementation on perceptions of solidarity by comparing responses before and after the policy change.\u003c/p\u003e"},{"header":"2.\tMethods","content":"\u003ch2\u003e\u003cem\u003e2.1. R\u003c/em\u003e\u003cem\u003eesearch design\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eOur research design was a repeated cross-sectional study comparing the directional change of government or individual responsibility after implementing the NHI program.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e2.2. Setting\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWith a population of approximately 23 million, Taiwan is generally categorized within Esping-Andersen\u0026rsquo;s typology as a conservative welfare state regime\u0026nbsp;[6]. The Taiwanese government prioritizes state intervention to foster substantial social solidarity.\u0026nbsp;This intervention manifests through cohesive social security frameworks and diverse public service provisions. Social insurance schemes fundamentally underpin Taiwan\u0026rsquo;s welfare system. Based on social solidarity, Taiwan\u0026apos;s NHI exemplifies a single-payer, mandatory social insurance model with an impressive 99.9% coverage rate and 90% enrollee satisfaction. It operates on a pay-for-service model, adhering to the principle that healthcare is a fundamental human right. This system has facilitated universal, high-quality healthcare at accessible costs, aiding socially and economically disadvantaged segments\u0026nbsp;[3, 10, 21]. All insured\u0026nbsp;individuals\u0026nbsp;must pay an income-related premium of about\u0026nbsp;2.5% compared to 4.1% in Japan and 6.3% to 7.5% in Germany in 2005\u0026nbsp;[22].\u0026nbsp;Taiwan\u0026rsquo;s NHI promotes income solidarity by adjusting premiums based on varying income levels, supporting its universal coverage and financial sustainability goals\u0026nbsp;[22].\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e2.3.\u0026nbsp;\u003c/em\u003e\u003cem\u003eData and\u0026nbsp;\u003c/em\u003e\u003cem\u003eparticipants\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe WVS encompasses 120 countries and represents 94.5% of the global population. It is the most comprehensive cross-national time-series study of human beliefs and values [23]. This extensive coverage makes it a significant research program dedicated to the academic exploration of the sociocultural values of people worldwide [23]. Taiwan participated in the 1995 and 2005 waves of the study. This study used data from the Taiwanese cohort, a nationally representative sample of citizens aged 18 and older, to reflect the adult population of Taiwan. Data collection was conducted through face-to-face interviews. The sample sizes for the respective waves were substantial, with 780 respondents in the 1995 wave and 1227 respondents in the 2005 wave. Age- and Sex-Matched 1:1 matching (Age/Sex-Matched 1:1) was utilized to balance the distribution of covariates between individuals before and after the NHI policy intervention.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e2.4. \u0026nbsp;Concepts and measurements\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTaiwan\u0026rsquo;s 1995 pre-NHI (before the NHI launch) and 2005 post-NHI (10 years after NHI program) WVS data enable a unique natural experiment examining whether NHI crowds out individual responsibility. This study uses a longitudinal analysis approach to compare the changes in healthcare responsibility before and after the implementation of the NHI. The data provides an invaluable opportunity to observe how a major policy intervention influences social and individual values over an extended period. By analyzing this data, researchers can understand how societal attitudes toward healthcare and welfare responsibilities have evolved in response to the NHI implementation.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e2.5 V\u003c/em\u003e\u003cem\u003eariable\u003c/em\u003e\u003cem\u003es\u003c/em\u003e\u003cem\u003e\u0026nbsp;definition\u003c/em\u003e\u003c/h2\u003e\n\u003ch3\u003e\u003cem\u003e2.5.1 Dependent variable\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eThe variable \u0026apos;Government responsibility,\u0026apos; based on questionnaires from the 1995 and 2005 WVS waves, is the dependent variable in this study. It quantifies attitudes toward allocating responsibility for welfare provision or individual responsibility to support self-sufficiency. This is measured using a Likert scale ranging from 1 to 10. A score of 1 indicates the belief that \u0026apos;the government should take more responsibility,\u0026apos; while a score of 10 denotes the belief that \u0026apos;people should take more responsibility.\u0026apos; This scale effectively captures an individual\u0026rsquo;s position on the spectrum between state responsibility and individual responsibility within societal support systems [24]. By analyzing these scores, the study aims to understand how perceptions of responsibility for welfare have shifted over time, particularly in response to policy changes such as the introduction of the NHI in Taiwan.\u0026quot;\u003c/p\u003e\n\u003ch3\u003e\u003cem\u003e2.5.2. \u0026nbsp;Policy interventional variable\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eThe NHI as an interventional variable provides a lens to explore the relationship between health policy and solidarity notions. This variable allows researchers to examine the direct and indirect effects of the NHI on societal attitudes and behaviors.\u003c/p\u003e\n\u003ch3\u003e\u003cem\u003e2.5.3. \u0026nbsp;Covariates\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eTo explain potential compositional effects, we control for individual-level characteristics, including sex, age, religiosity, education, marital status, employment status, income, and degree of urbanization [8, 25]. Psychocognitive framing [8, 26] and societal conditions variables, including perceived health, quality of life (QOL), trust in government, and perceptions of fairness, are also integrated into the analysis [8, 25].\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e2.6. Data analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWe utilized Generalized Linear Mixed Models (GLMMs) as our data analysis methodological tool to examine the effects of various factors on the dependent variable, government responsibility as a solidarity notion, within the context of repeated cross-sectional data. The NHI program implementation was treated as an intervention dummy variable. The Likelihood Ratio Test (LRT) was employed to evaluate the impact of NHI. This test compares the -2 Log Likelihood values of both the full model (which includes the intervention variable) and the partial model (without the intervention). The LRT identifies statistically significant differences between these models, indicating the effect of the NHI intervention.\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003cp\u003e\u003cem\u003e3.1.\u0026nbsp;\u003c/em\u003e\u003cem\u003eParticipants characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe utilized the Age/Sex-Matched 1:1 method to balance the distribution of covariates between individuals surveyed before and after the NHI policy intervention. Before matching, some covariates had absolute standardized mean differences (ASMDs) exceeding 0.2, indicating substantial imbalance (Table 1). Key variables such as age, marital status, region, education, and income showed ASMDs over 0.1, suggesting some level of imbalance. Austin (2009) states that an ASMD below 0.1 denotes negligible group differences [27]. After 1:1 matching, the\u0026nbsp;matched sample included 765 respondents from the 1995 WVS wave and 765 respondents from the 2005 WVS wave. Most ASMDs were reduced below 0.2, indicating that the matching algorithm effectively balanced the covariates across the two survey waves. The matched analytic sample achieved covariate equivalence between the pre- and post-NHI intervention cohorts based on measured sociodemographic and psychocognitive characteristics, minimizing confounding influences in estimating the policy\u0026apos;s impact in subsequent analyses. This matching process ensured a better comparison, enhancing the validity of our findings regarding the impact of the NHI policy.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2.\u0026nbsp;\u003c/em\u003e\u003cem\u003eCharacteristics of the research samples in the 1995 and 2005 waves\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDespite the application of Age/Sex-Matched, several demographic differences persisted between the 1995 and 2005 survey waves (Table 1). Specifically, in 2005, a larger proportion of participants were younger (18-34 years increased from 30.9% to 35.4%), unmarried (increased from 20.0% to 29.7%), and reported having a religion (increased from 0% to 26.7%) (Table 2). Educational attainment rose in 2005, with more participants achieving college or higher education (from 40.7% to 45.4%). There were significantly fewer high-income participants in 2005 (decreased from 36.7% to 3.0%), counterbalanced by a substantial rise in middle-income respondents (from 30.3% to 69.7%). Employment rates also increased from 62.5% to 68.0%. Biopsychological characteristics also differed between the matched waves. Perceived fairness declined in 2005, from 37.6% to 23.3%. The proportion of individuals rating their happiness as high or higher decreased from 91.1% in 1995 to 85.9% in 2005. Self-rated health showed more \u0026quot;good\u0026quot; health but fewer \u0026quot;not good\u0026quot; health ratings in 2005. Similar trends were observed for QOL evaluations. There was a significant shift in the measure of solidarity between the two waves. In the 1995 wave, the government responsibility score averaged 5.535 (95% CI: 5.363-5.708). By the 2005 wave, this average dropped to 5.029 (95% CI: 4.844-5.214), a statistically significant change (p\u0026lt;0.0001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.3.\u0026nbsp;\u003c/em\u003e\u003cem\u003eAssociation of longitudinal predictors of solidarity before and after Taiwan\u0026rsquo;s\u003c/em\u003e NHI\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cem\u003epolicy intervention\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Generalized Linear Mixed Models (GLMMs) analysis showed baseline government responsibility scores (intercept values) of 4.79 for the 1995 wave and 5.12 for the 2005 wave (Table 3). The associations between government responsibility scores and control variables like age, marital status, education, religion, income, occupation, and urbanization were small and insignificant in 1995 and 2005. Males had slightly higher government responsibility scores compared to females. In 1995, males reported 0.34 units higher scores than females (\u0026beta;=0.34, p=0.3351); in 2005, this difference was 0.33 units (\u0026beta;=0.33, p=0.0174). Perceived unfairness was a strong predictor of government responsibility scores. In 1995, unfairness was associated with a 0.74 unit increase (\u0026beta;=0.74, p\u0026lt;0.0001), and this association remained in 2005 (\u0026beta;=0.74, p\u0026lt;0.0001). Low QOL was linked to a preference for government responsibility. In 1995, low QOL was associated with a -0.81 unit decrease (\u0026beta;=-0.81, p=0.0124), and in 2005, this relationship persisted (\u0026beta;=-0.81, p=0.0122). The LRT comparing the two models revealed that including the NHI policy in the 2005 full model resulted in a significant decrease of 0.70 units in the government responsibility score (\u0026beta;= -0.70, p\u0026lt;0.0001). The likelihood ratio 4.2 (p=0.0404) between the full and partial models indicated a significantly improved model fit when accounting for the NHI policy intervention.\u003c/p\u003e"},{"header":"4.\tDiscussion","content":"\u003cp\u003eHealthcare is universally acknowledged as a social entitlement, with governments playing a crucial role in its provision [4, 9, 12, 28]. This study, a longitudinal repeated\u0026nbsp;cross-sectional analysis using data from the WVS, explores the dynamics of solidarity in the context of Taiwan\u0026rsquo;s NHI implementation.\u003c/p\u003e\n\u003cp\u003eSolidarity in healthcare is organized across three distinct levels. At the interpersonal level, solidarity manifests through individual actions where people identify with others\u0026rsquo; needs and willingly share costs, often driven by a sense of reciprocity. The second level includes group-based activities such as health information sharing and fundraising efforts. The third and most structured level involves contractual and legal frameworks that institutionalize solidarity through public healthcare systems, thus ensuring equitable access to health services [15].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The International Social Survey Program and the European Values Study adopted the concept of \u0026apos;willingness to improve the living conditions of other people,\u0026apos; which is traditionally considered the predominant source for measuring solidarity through large-scale survey research [8, 25]. These surveys primarily focus on individual-level willingness to assist specific groups of people, reflecting a targeted approach to assessing solidarity. Our study utilizes the WVS definition of solidarity, which focuses on the government and individual responsibility to support self-sufficiency. This dual focus allows us to assess how the NHI influences solidarity perceptions across different societal demographics, including age, gender, marital status, employment status, religious beliefs, and socioeconomic status.\u003c/p\u003e\n\u003cp\u003eIn the methodological approach of this study, we employed GLMMs to analyze repeated cross-sectional data. Our study examined the relationship between government responsibility scores and NHI program implementation while controlling covarites. The dependent variable was the government responsibility score, and the intervention dummy variable measured whether or not an NHI program had been implemented. Control variables were included to account for potential confounding factors, such as participants\u0026apos; age, sex, education level, and perceptions of healthcare issues. GLMMs are more appropriate for longitudinal data with multilevel structures [29].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Given the repeated cross-sectional study design, GLMMs were utilized to analyze the impact of variables over time while accounting for individual and cluster-level variations. The models effectively partition the total variance into within-individual, between-individual, and residual error components. By examining the percentage of variance explained at each level, inferences can be made regarding the predominant source of variability in the data [30]. The LRT was conducted to assess the impact of the 1995 NHI policy intervention by comparing two nested models. The partial model represented the pre-intervention period before 1995, while the full model incorporated the potential effects of the NHI policy implemented ten years in 2005, which our study examined through LRT between pre- and post-intervention models. The findings indicate a substantial influence of the NHI policy on reducing government responsibility scores, suggesting an increased expectation for the government to assume greater responsibility in healthcare provision.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Sociodemographic factors and welfare state regimes have been shown to affect people\u0026rsquo;s notions of solidarity, with previous studies indicating that females, older individuals, married individuals, those employed, religious believers, and more affluent and educated respondents generally hold a stronger solidarity notion [8, 25]. Social solidarity rationality is based on trust in institutional or state efficiency and fairness in accessing and distributing welfare provisions [13]. Our analysis reveals that sex plays a significant role in shaping solidarity perceptions, with males typically exhibiting higher government responsibility scores, suggesting a stronger inclination towards individual responsibility in healthcare. These results, along with some related studies, suggest that females have higher collective solidarity. These results and related studies suggest that females have higher collective solidarity [25]. In European welfare states, the basic understanding of solidarity is that everyone is assumed to make a fair financial contribution to a collectively organized insurance system that guarantees equal access to health and social care for all members of society. Thus, fairness forms the foundation of solidarity, which seems an essential and inherent element [7, 25]. When people believe systems and policies are fair, they may be more willing to unite behind them through acts of solidarity and support [7]. Our analysis perceived fairness as a strong predictor of government responsibility scores, highlighting the importance of fairness in fostering collective solidarity. Individuals with a lower QOL preferred more robust collective solidarity measures, indicating the social impact of perceived needs in healthcare access [21].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Taiwan\u0026rsquo;s NHI system vertically integrates citizens through a compulsory, universal health insurance system while also horizontally pooling people by health risk-sharing emphasis on mutual assistance. To ensure income solidarity, Taiwan NHI\u0026rsquo;s general premiums are jointly paid by the insured, corporate employers, and the government, and the rate is kept at approximately 5% [31]. Besides, it also provides premium subsidies for members of vulnerable groups (including low-income and near-poor households, unemployed veterans, workers, and their dependents, the physically and mentally disabled, and unemployed indigenous citizens) [31]. Approximately 4% of insured people possess valid major illness/injury certificates. For these individuals, copayments have been waived to treat their catastrophic illnesses and injuries and ensure financial relief and support. Taiwan NHI provides a comprehensive range of healthcare services, including outpatient care, inpatient care, traditional Chinese medicine, dental care, childbirth, post-acute care and rehabilitation, home health care, palliative care, and rehabilitation for chronic mental illness. The NHI covers medical payments for diagnosis, examination, laboratory tests, surgery, anesthesia, medication, materials, treatment, and nursing care [31]. The healthcare systems in Europe and Taiwan represent contrasting approaches to balancing collective solidarity and individual responsibility [32]. The European model emphasizes a two-tiered system [18], with a publicly funded tier for basic healthcare needs and a market-driven tier for more personalized or advanced services. This approach reflects a shift towards greater individual responsibility, where access to care is increasingly determined by one\u0026rsquo;s ability to pay rather than needs [21]. The solidarity-decline thesis suggests that healthcare reforms adversely affect solidarity [33]. Critics argue that this erosion of solidarity through cost-sharing undermines the collective ethos of healthcare systems, raising concerns about long-term implications for social cohesion and equitable access [21]. When people believe systems and policies are fair, they may be more willing to unite behind them through acts of solidarity and support. In contrast, Taiwan\u0026rsquo;s NHI system represents a model that integrates both solidarity and individual responsibility principles. This dual approach reflects an attempt to balance the values of collective welfare and personal accountability within the framework of a state-organized health insurance system. The system\u0026rsquo;s design acknowledges that while individuals should be accountable for their health, the state is also responsible for providing comprehensive healthcare services, ensuring that no one is excluded due to financial incapacity. This reflects a broader societal value that healthcare is a fundamental right, regardless of personal characteristics or social status [31].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Previous studies have acknowledged the commendable state initiatives to provide healthcare for all vulnerable groups, highlighting the unintended negative repercussions of such an approach. Some argue that excessive reliance on state-provided support measures may undermine individual initiative [13, 34]. Conversely, other research indicated that nationwide, state-controlled, and compulsory welfare schemes institutionalized through social insurance programs could partially compensate for the evident decline in individual solidarity resulting from state policies [12, 33]. While the European model prioritizes individual choice and a market-driven approach, Taiwan\u0026rsquo;s NHI attempts to maintain a sense of collective welfare while also promoting personal accountability [31]. Our ten years of time-series data suggest that the association between state-organized welfare provisions and notions of individual responsibility remains complex. While some argue that comprehensive welfare systems foster solidaristic attitudes, others contend that excessive reliance on state support may undermine individual initiative [9, 15, 19, 20, 35]. The changing nature of responsibility allocation between the state and individual citizens will undoubtedly lead to more concern between affluent groups such as lower QOL, low-income, and felt unfair groups in accessing healthcare services [12].\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e4.1.\u0026nbsp;\u003c/em\u003e\u003cem\u003eStrengths\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThis study offers several notable strengths: First, our research provides important real-world empirical evidence illuminating the relationship between policy interventions and societal attitudes toward solidarity. Second, our findings underscore the importance of considering solidarity among the potential effects when formulating large-scale healthcare and social welfare policies. Third, by applying GLMMs to the complex repeated cross-sectional data, we could simultaneously model the systematic effects of the policy intervention while accounting for variations across individuals and time points as random effects.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e4.2. L\u003c/em\u003e\u003cem\u003eimitations\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eSeveral limitations of our study should be acknowledged to provide a balanced perspective on our findings. First, the concept of \u0026lsquo;solidarity notions\u0026rsquo; lacks a standardized operational definition, posing challenges to the consistency and clarity of our findings. While we aimed to capture societal attitudes towards collective responsibility and individual responsibility, the multidimensional nature of solidarity may not be fully represented by the measures used in our analysis. Second, the Taiwanese WVS cohort data might be influenced by social desirability bias, where respondents provide socially desirable responses rather than their actual attitudes. Third, although repeated cross-sectional data support a Difference-in-Differences (DiD) framework, this study did not adopt that approach. Instead, we used Age/Sex-Matched 1:1 to improve covariate balance between the 1995 and 2005 samples. While Age/Sex-Matched enhances comparability based on observed characteristics, it does not support causal inference, as it cannot address unmeasured confounding or temporal trends. Thus, interpretations based on matched samples should remain cautious. To more robustly evaluate the causal impact of the NHI policy, a quasi-experimental design such as DiD\u0026mdash;preferably with a comparison group from a country without universal health insurance during the same period\u0026mdash;would offer stronger analytical validity. Four, the generalizability of our results may be limited due to the diversity of healthcare systems and welfare regimes across different countries. Lastly, our study primarily investigates solidarity at the national and individual levels. However, it does not delve into the perspectives and associated thoughts of the intermediary group of healthcare providers. This layer serves as a critical link between the individual and national policy levels, and their insights are vital for a comprehensive understanding of the multi-layered nature of social solidarity. Future research should consider including the perspectives of healthcare providers to provide a more holistic view of how health policies impact solidarity across all healthcare system levels [36].\u003c/p\u003e"},{"header":"5.\tConclusion","content":"\u003cp\u003eThis study significantly enhances the understanding of how national health policies impact social solidarity and individual responsibility. The findings suggest that state-organized systems can foster collective solidarity, demonstrating that comprehensive and inclusive health policies can promote a sense of shared responsibility and support within a society. However, continuous monitoring of the evolving dynamics between the state and individuals is essential to ensure the sustainability and equity of these systems.\u003c/p\u003e\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the author(s) utilized ChatGPT 4.5 to check grammar. After using this tool, the author(s) reviewed and edited the content as needed and assume(s) full responsibility for the final content of the publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of National Yang-Ming University-YM107035E on May 5, 2018. In accordance with regulations of the National Health Research Institutes, patient identification information was anonymized, such that informed consent was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI in scientific writing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this manuscript, the authors used AI language models, specifically ChatGPT and Claude, for grammar and spelling checks and for debugging SAS code. After using these tools, the authors meticulously reviewed and revised the content as needed. The authors assume full responsibility for the content of this publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study are sourced from the World Values Survey (C00173) [Data file]. They can also be accessed through the Survey Research Data Archive at the Center for Survey Research, Research Center for Humanities and Social Sciences, Academia Sinica. For more information, visit the website at https://srda.sinica.edu.tw, DOI: 10.6141/TW-SRDA-C00173-1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributors\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC-Y.L. and C-C.L. studied concept and design, data analysis and interpretation, and manuscript preparation. Y-C.L. and M-L.C. supervise the development of the study concept and design, data analysis and interpretation, and manuscript preparation. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe want to acknowledge the World Values Survey and the Survey Research Data Archive at the Center for Survey Research, Research Center for Humanities and Social Sciences, Academia Sinica, for providing the data files and granting permission to analyze the data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStock SAK, Redaelli M, Lauterbach KW. Disease management and health care reforms in Germany\u0026mdash;does more competition lead to less solidarity? Health Policy. 2007;80(1):86\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAltenstetter C, Busse R. Health care reform in Germany: patchwork change within established governance structures. 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Social solidarity and personal responsibility in health reform. Conn Ins LJ. 2007;14:199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrampusch C. Industrial relations as a source of solidarity in times of welfare state retrenchment. J Soc Policy. 2007;36(2):197\u0026ndash;215.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Oorschot W, Arts W. The social capital of European welfare states: The crowding out hypothesis revisited. J Eur social policy. 2005;15(1):5\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Oorschot W. From solidarity to selectivity: the reconstruction of the Dutch social security system 1980\u0026ndash;2000. Social Policy Rev. 1998;10:183\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrainsack B, Buyx A. Solidarity in contemporary bioethics\u0026ndash;towards a new approach. Bioethics. 2012;26(7):343\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants\u0026rsquo; Characteristics Before and After Age- and Sex-Matched 1:1 Matching in the Taiwan World Value Survey for the 1995 and 2005 Waves.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"101%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 1995 wave\u003cbr\u003e\u0026nbsp;(N=780)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 2005 wave\u003cbr\u003e\u0026nbsp;(N=1\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASMD\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 1995 wave\u003cbr\u003e\u0026nbsp;(N=765)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 2005 wave\u003cbr\u003e\u0026nbsp;(N=765)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASMD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e399 (51.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e606 (49.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e393 (51.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e393 (51.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e381 (48.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e621 (50.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e372 (48.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e372 (48.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e18~34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e236 (30.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e405 (33.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e236 (30.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e271 (35.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e35~49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e358 (45.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e360 (29.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e349 (45.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e283 (36.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e50~64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e127 (16.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e316 (25.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e112 (15.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e139 (18.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;59 (07.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e146 (11.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;59 (07.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;72 ( 9.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003earriage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e155 (19.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e367\u0026nbsp;(29.91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e153 (20.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e227\u0026nbsp;(29.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e625 (80.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e860\u0026nbsp;(70.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e612\u0026nbsp;(80.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e538\u0026nbsp;(70.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003cstrong\u003eegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0 \u0026nbsp;(00.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e342 (27.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;0 (00.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e204 (26.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e780 (100.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e885 (72.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e765 (100.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e561 (73.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e260 (33.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e261 (21.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e247 (32.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e181 (23.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e207 (26.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e481 (39.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e207 (27.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e237 (30.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eCollege \u0026amp; above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e311 (39.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e485 (39.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e311 (40.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e347 (45.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e244 (33.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e363 (29.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e234 (33.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e208 (27.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e217 (30.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e820 (67.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e215 (30.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e530 (69.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e260 (36.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;39 (03.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e260 (36.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;23 (03.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eUnemployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e294 (37.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e492 (40.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e287 (37.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e245 (32.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eEmployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e486 (62.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e735 (59.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e478 (62.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e520 (67.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrbanization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e343 (43.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e487 (39.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e334 (43.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e310 (40.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e437 (56.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e740 (60.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e431 (56.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e455 (59.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eASMD: absolute standardized mean differences; WVS: World Value Survey\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe comparison of participant characteristics in the Taiwan World Value Survey for the 1995 and 2005 waves after Age- and Sex-Matched 1:1 Matching.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 1995 wave\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;(N=765)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 2005 wave\u003cbr\u003e\u0026nbsp;(N=765)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e393 (51.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e393 (51.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e372 (48.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e372 (48.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e18~34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e236 (30.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e271 (35.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e35~49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e349 (45.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e283 (36.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e50~64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e112 (15.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e139 (18.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026ge; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;59 (07.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;72 ( 9.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarriage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e153 (20.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e227 (29.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e612 (80.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e538 (70.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003cstrong\u003eegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;0 (00.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e204 (26.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e765 (100.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e561 (73.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e247 (32.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e181 (23.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e207 (27.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e237 (30.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e311 (40.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e347 (45.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e234 (33.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e208 (27.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e215 (30.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e530 (69.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e260 (36.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;23 (03.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eUnemployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e287 (37.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e245 (32.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eEmployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e478 (62.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e520 (67.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrbanization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e334 (43.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e310 (40.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e431 (56.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e455 (59.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFairness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e468 (62.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e585 (76.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e282 (37.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e178 (23.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHappiness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;68 (08.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e108 (14.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e693 (91.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e657 (85.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e163 (21.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e194 (25.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e523 (68.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e537 (70.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNot good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;79 (10.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;34 (04.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuality of life\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e257 (33.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e281 (36.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e458 (60.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e435 (56.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNot good\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;48 (06.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e310 (06.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e257 (33.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e281 (36.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e458 (60.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e435 (56.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e5.535\u0026plusmn;2.411 (5.363-5.708)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e5.029\u0026plusmn;2.601(4.844-5.214)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeneralized linear mixed models to analyze the impact of variables over time while accounting for individual and cluster-level.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"102%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 1995 wave\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWVS 2005 wave \u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e[95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e[95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntercept\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e5.12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.47\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eMale (ref=female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.34\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.06-0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.3351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.34\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.06--0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.3351\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e18-34 (ref=65+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.57-0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.8349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.32\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.57-0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e35-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.27-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.3067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.28-0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.3237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e50-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.03-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.53\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.29\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.04-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarriage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eNo (ref=yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.18\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.12-0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.1853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.18\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.11-0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eElementary (ref=college)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.13\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.29-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.5435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.30-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.5631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.19-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.4037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.19-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.4029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eNo (ref=yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.32-0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.6671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.30-0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eLow (ref=high)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.68-0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.2478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.67-0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.30-0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.6171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.28-0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eUnemployment (ref=yes)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.24-0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.6791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.06\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.25-0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.6914\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrbanization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eUrban (ref=rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.46-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.1403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.20\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.46-0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1401\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFairness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eUnfairness (ref=fairness)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.45-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.74\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(0.45-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHappiness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eNo (ref=yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.75-0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.1828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.75-0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.1923\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003ePoor (ref=good)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.54-0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.8048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.53-0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.7838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eFair\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.28\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.64-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.7517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.28\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.64-0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.7726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuality of life\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eLow (ref=high)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.81\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.32\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-1.45--0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.0124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.81\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.32\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-1.45--0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.68--0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.68--0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eUntrust (ref=trust)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.48-0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e0.2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-0.47-0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolicy Intervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 36px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 38px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNHI policy implementation\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 36px;\"\u003e\n \u003cp\u003ePartial model (without policy effect)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 38px;\"\u003e\n \u003cp\u003eFull model (with policy effect)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment Responsibility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e(-1.03--0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003e-2 Log Likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 26px;\"\u003e\n \u003cp\u003e-13361.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 26px;\"\u003e\n \u003cp\u003e-13357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25px;\"\u003e\n \u003cp\u003eLikelihood Ratio Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 26px;\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.0404\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eLikelihood Ratio Test; WVS: World Value Survey; NHI: National Health Insurance; CI: confidence interval\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8678924/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8678924/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eThe impact of state-organized welfare systems on solidarity attitudes remains uncertain due to the limited availability of longitudinal data. This study aimed to examine changes in collective solidarity and individual responsibility attitudes in Taiwan following the implementation of the National Health Insurance (NHI) scheme, using data from the World Values Survey (WVS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a repeated cross-sectional analysis using WVS data from 1995 (pre-NHI implementation) and 2005 (post-NHI implementation). Participants were Taiwanese adults aged 18 and older. Generalized Linear Mixed Models (GLMMs) were used to evaluate factors influencing solidarity attitudes. Age- and Sex-Matched 1:1 Matching was applied to balance covariates, and the Likelihood Ratio Test (LRT) was used to assess the significance of the effect of the NHI policy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOur findings demonstrated stronger collective solidarity among female participants, greater perceptions of unfairness among respondents, and lower quality of life among those reporting unfairness. GLMM analysis revealed a significant reduction of 0.70 units in government responsibility scores a decade after the NHI implementation (β = -0.70, p \u0026lt; 0.0001), indicating increased perceptions of government responsibility. The Likelihood Ratio Test confirmed improved model fit when incorporating NHI policy effects (likelihood ratio = 4.2, p = 0.0404).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eTaiwan’s NHI system reinforces collective solidarity and concurrently promotes perceptions of individual responsibility. Notably, females, perceived fairness, and lower quality of life are significant factors associated with greater reliance on government healthcare provision.\u003c/p\u003e","manuscriptTitle":"Health in Whose Hands? Impacts of National Health Insurance on Social Solidarity and Individual Responsibility: Evidence from the World Values Survey of Taiwan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 06:22:51","doi":"10.21203/rs.3.rs-8678924/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-31T06:19:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T03:42:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25100882407642974230772858590357908700","date":"2026-03-03T02:40:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-22T12:07:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322187866665686467559980540112395208321","date":"2026-02-16T17:06:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-06T12:36:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-29T06:15:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-28T10:42:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-28T10:40:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-01-23T11:36:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"487faab8-4322-46ac-bc41-d22bb5671949","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T14:10:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 06:22:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8678924","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8678924","identity":"rs-8678924","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}