The World Health Organization has proposed a model of healthy aging built around the concept of functional ability, comprising an individual’s intrinsic capacity, the physical and social environment they occupy, and interactions between the two. However, these constructs have been poorly defined. We examined the structure of intrinsic capacity in a representative sample of the Chinese population aged 60 years and older and assessed its value in predicting declining performance in instrumental activities of daily living (IADLs) and activities of daily living (ADLs) using similar methods to a construct validation previously undertaken in an English cohort. Deidentified data were accessed on 7 643 participants of the China Health and Retirement Longitudinal Study 2011 and 2013 waves. Incrementally related structural equation modeling was applied, including exploratory and confirmatory factor analysis, and path analysis. Multiple linear regression tested construct validity, and simple and serial mediation models assessed predictive validity. Factor loadings for the models showed a clear structure for intrinsic capacity: 1 general factor with 5 subfactors—locomotor, cognitive, psychological and sensory capacities, and vitality (reflecting underlying physiologic changes). Intrinsic capacity predicted declining performance in both IADLs (standardized coefficient (SE) −0.324 (0.02), p < .001) and ADLs (−0.227 (0.03), p < .001), after accounting for age, sex, education, wealth, and number of chronic diseases. Each characteristic was associated with intrinsic capacity, providing strong construct validity. Assessment of intrinsic capacity provides valuable information on an individual’s subsequent functioning beyond that afforded by age, other personal factors, and multimorbidity.

China has three basic health insurance schemes: Urban Employee Basic Medical Insurance (UEBMI), Urban Resident Basic Medical Insurance (URBMI) and New Rural Cooperative Medical Scheme (NRCMS). This study aimed to compare the equity of health-related quality of life (HRQoL) of residents under any two of the schemes. Using data from the 5th National Health Services Survey of Shaanxi Province, China, coarsened exact matching method was employed to control confounding factors. We included a matched sample of 6802 respondents between UEBMI and URBMI, 34,169 respondents between UEBMI and NRCMS, and 36,928 respondents between URBMI and NRCMS. HRQoL was measured by EQ-5D-3L based on the Chinese-specific value set. Concentration index was adopted to assess health inequality and was decomposed into its contributing factors to explain health inequality. After matching, the horizontal inequity indexes were 0.0036 and 0.0045 in UEBMI and URBMI, 0.0035 and 0.0058 in UEBMI and NRCMS, and 0.0053 and 0.0052 in URBMI and NRCMS respectively, which were mainly explained by age, educational and economic statuses. The findings demonstrated the pro-rich health inequity was much higher for the rural scheme than that for the urban ones. This study highlights the need to consolidate all three schemes by administrating uniformly, merging funds pooling and benefit packages. Based on the contributing factors, strategies aim to facilitate health conditions of the elderly, narrow economic gap, and reduce educational inequity, are essential. This study will provide evidence-based strategies on consolidating the fragmented health schemes towards reducing health inequity in both China and other developing countries.

The inequality of health human resource is a worldwide problem, and solving it also is one of the major goals of China’s recent health system reform. Yet there is a huge disparity among cities in mainland China. The aim of this study is to analyze the distribution inequality of the health human resource in 322 prefecture-level cities of mainland China in 2014, and to reveal the facets and causes of the inequalities. The data for this study were acquired from the provincial and municipal Health Statistics Yearbook (2014) and Statistical Yearbook (2014), the municipal National Economic Bulletin (2014), and the official websites of municipal governments, involving 322 prefecture-level cities. Meanwhile, Concentration Index was used to measure the magnitude of the unequal distribution of health human resource. A decomposition analysis was employed to quantify the contribution of each determinant to the total inequality. The overall concentration index of doctors and nurses in mainland China in 2014 was 0.1038 (95% CI = 0.0208, 0.1865) and 0.0785 (95% CI =0.0018, 0.1561). Decomposition of the concentration index revealed that economic status was the primary contributor (58.5% and 57%) to the inequality of doctors and nurses, followed by the Southwest China (19.1% and 18.6%), urbanization level (− 13.1% and − 12.8%), and revenue (8.0% and 7.8%). Party secretaries with Master degree (7.0%, 6.8%), mayors who were 60 years old or above (6.3%, 6.1%) also were proved to be a major contributor to the inequality of health human resource. There was inequality of health human resource distribution which was pro-rich in mainland China in 2014. Economic status of the cities accounted for most of the existing inequality, followed by the Southwest China, urbanization level, revenue, party secretaries with Master degree, and mayors who were 60 years old or above in respective importance. Besides, the party secretaries and mayors also had certain influence on the allocation of health human resource. The tough issue of HHR inequality should be addressed by comprehensive measures from a multidisciplinary perspective.

China has been undergoing tremendous demographic and epidemiological transitions during the past three decades and increasing burden from non-communicable diseases and an ageing population have presented great health-care challenges for the country. Numerous studies examine catastrophic healthcare expenditures (CHE) worldwide on whole populations rather than specific vulnerable groups. As hypertension and other chronic conditions impose a growing share of the disease burden in China, they will become an increasingly important component of CHE. This study aims to estimate households with hypertension incurring CHE and its income-related inequality in the rural areas of Shaanxi Province. Data were obtained from the National Household Health Service Surveys of Shaanxi Province conducted in 2013 and 13104 households were identified for analysis. The households were classified into three types: households with non-chronic diseases, households with hypertension only and households with hypertension plus other chronic diseases. CHE was measured according to the proportion of out-of-pocket health payments to non-food household expenditures and the concentration index was employed to measure the extent of income-related inequality in CHE. A decomposition method based on a probit model was used to decompose the concentration index into its determining components. The incurring of CHE of households with hypertension is at a disconcerting level compared to households with non-chronic diseases. Households with hypertension only and households with hypertension plus other chronic diseases incurred CHE in 23.48% and 34.01% of cases respectively whereas households with non-chronic diseases incurred CHE in only 13.33%. The concentration index of households with non-chronic diseases is -0.4871. However, the concentration index of households with hypertension only and households with hypertension plus other chronic diseases is -0.4645 and -0.3410 respectively. The majority of observed inequalities in CHE were explained by household economic status and having elder members. The proportion of households incurring CHE in the rural areas of Shaanxi Province was considerably high in all three types of households and households with hypertension were at a higher risk of incurring CHE. Furthermore, there existed a strong pro-poor inequality of CHE in all three types of households and the results implied more inequality in households with non-chronic diseases compared with two other groups. Our study suggests that more concern needs to be directed toward households with hypertension plus other chronic diseases and households having elder members.

Background: China has the largest number of aging people in need of long-term care, among whom 70% have chronic diseases. For policy planners, it is necessary to understand the different levels of needs of long-term care and provide long-term care insurance to ensure the long-term care needs of all people can be met. Methods: This study combines the 2013 wave of CHARLS survey and the Life Course Survey of 2014. The combination allows us to factor in both childhood and adulthood data to provide life-course analysis. We identified 7,734 older adults with chronic diseases for analysis. The need for long-term care is defined by the presence of functional limitations based on the performance of basic activities of daily living (ADLs) and of instrumental activities of daily living (IADLs). Two dummy variables, ADLs disability and IADLs disability, and two count variables, ADLs score and IADLs score, were defined to measure incidence and severity of long-term care need, respectively. The concentration index was used to capture the inequality in long-term care need, and a decomposition method based on Probit Regression and Negative Binomial Regression was exploited to identify the contribution of each determination. Results: At least a little difficulty was reported in ADLs and IADLs in 20.44% and 19.25% of respondents, respectively. The concentration index of ADLs disability, ADLs score, IADLs disability, IADLs score were −0.085, −0.109, −0.095 and −0.120, respectively, all of which were statistically significant, indicating the pro-poor inequality in the incidence and severity of long-term care need. Decomposition analyses revealed that family income, education attainment, aging, and childhood experience played a significant role in explaining the inequalities. Conclusions: The long-term care need among older adults with chronic disease is high in China and low socioeconomic groups had a higher probability of needing long-term care or need more long-term care. It is urgent to implement long-term care insurance, especially for the individuals from lower socioeconomic groups.

Hypertension has become a global health challenge given its high prevalence and but low awareness and detection. Whether the actual prevalence of hypertension has been estimated is important, especially for the poor. This study aimed to measure tested prevalence and self-reported prevalence of hypertension and compare the inequity between them in China. Data were derived from China Health and Nutrition Survey (CHNS) conducted in 2011. By using the multistage, stratified, random sampling method, 12,168 respondents aged 18 or older were identified for analysis. Both tested prevalence (systolic blood pressure ≥ 140 mmHg or/and diastolic blood pressure ≥ 90 mmHg or /and current use any of antihypertensive medication) and self-reported prevalence (ever diagnosed with hypertension by a doctor) were used to measure the prevalence of hypertension. The concentration index was employed to measure the extent of inequality in tested prevalence and self-reported prevalence. A decomposition method, based on a Probit model, was used to analyze income-related horizontal inequity of tested prevalence and self-reported prevalence. The tested prevalence and self-reported prevalence of total respondents were 28.8% [95% CI (28.0%, 29.6%)] and 15.7% [95% CI (15.0%, 16.3%)], and 26.4% [95% CI (25.1%, 27.6%)] and 19.0% [95% CI (17.9%, 20.1%)] in urban areas, and 30.3% [95% CI (29.3%, 31.4%)] and 13.5% [95% CI (12.7%, 14.3%)] in rural areas. The horizontal inequity indexes of mean tested prevalence and self-reported prevalence were − 0.0494 and 0.1203 of total respondents, − 0.0736 and 0.0748 in urban area, and − 0.0177 and 0.0466 in rural area respectively, indicating pro-poor inequity in tested prevalence and pro-rich inequity in self-reported prevalence of hypertension. Economic status, education attainment and age were key factors of the pro-poor inequity in tested prevalence. Economic status, area and age were key factors to explain the poor-rich inequity in self-reported prevalence. This study revealed self-reported prevalence of hypertension was much lower than tested prevalence in China, while a larger gap between self-reported and tested prevalence was found in rural areas. Our study suggested social strategies aiming at narrowing economic gap and regional disparities, reducing educational inequity, and facilitating health conditions of the elderly should be implemented. Finally, awareness raising campaigns to test hypertension in rural area need be strengthened by health education programs and improving the access to public health service, especially for those who do not engage with regular health checkups.