Socioeconomic deprivation, medical services accessibility, and income-related health inequality among older Chinese adults: evidence from a national longitudinal survey from 2011 to 2018.

BACKGROUND: Health inequality poses a challenge to improving the quality of life of older adults as well as the service system. The literature rarely explores the moderating role of medical services accessibility in the association between socioeconomic deprivation and health inequality. OBJECTIVE: This study examines the socioeconomic deprivation and medical services accessibility associated with health inequality among older Chinese adults, which will contribute to the medical policy reform. METHODS: Using data from the 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we analyse 14,232 older adults. This paper uses a concentration index (CI) to measure the income-related health inequality among the target population and employs a recentered influence function-concentration index-ordinary least squares (RIF-CI-OLS) model to empirically analyse the correlation between socioeconomic deprivation and health inequality among older Chinese adults. Based on the correlation analysis, we discuss the moderating effect of medical services accessibility. RESULTS: We find that health inequality exists among older Chinese adults and that the relative deprivation in socioeconomic status (SES) is significantly associated with health inequality (ß∈  [0.1109,  0.1909], P < 0.01). The correlation between socioeconomic deprivation and health inequality is moderated by medical services accessibility, which means that an increase in medical services accessibility can weaken the correlation between socioeconomic deprivation and health inequality. CONCLUSION: China needs an in-depth reform of its medical services accessibility system to promote the equitable distribution of medical services resources, strengthen medical costs and quality management, and ultimately mitigate the SES reason for health inequality among older Chinese adults.

High-cost users: drivers of inpatient healthcare expenditure concentration in urban China.

BACKGROUND: Total healthcare expenditures are concentrated among a small number of patients. To date, studies on the concentration of health care expenditures in developing countries are limited, mainly focusing on concentration measures and the demographic, clinical and socioeconomic characteristics of high-cost users (HCU). The drivers of the skewed overall distribution of health care expenditures are opaque. Using inpatient administrative claims data, this study provides new evidence on the concentration of healthcare expenditures in China; the demographic and clinical characteristics of high-cost users; and the drivers of the overall distribution of healthcare expenditures. METHODS: Utilizing administrative claims data for hospitalization in a prefecture-level city in China, we investigated the concentration of healthcare expenditure. We used recentered influence function (RIF) regression to examine the drivers of healthcare expenditure concentration, decomposing and estimating the effects of demographic and disease characteristics on the overall distribution of health care expenditures. RESULTS: Using a sample of 87,841 adults, we found extreme skewness in the distribution of inpatient medical expenditures in China, with approximately 49% of annual medical expenditures generated by the top 10% of inpatient groups. HCUs tend to be elderly and male, with high-frequency hospitalizations and long lengths of stay. In addition, healthcare expenditure concentration was related to diseases of the circulatory system, malignant neoplasms, diseases of the musculoskeletal system and connective tissue, diseases of the digestive system, injury and poisoning, and diseases of the respiratory system. Malignant and major diseases reinforced the concentration of healthcare spending, and a 10% increase in the prevalence of malignancy would result in a predicted Gini coefficient increase of 7.2%, heart disease of 0.92% and cerebrovascular disease of 1.5%. The above significant positive effects were not observed for hypertension and diabetes mellitus. CONCLUSIONS: Our study provides new insights into the concentration of inpatient medical expenditures in China, including the precise picture of HCU expenditure concentration, the drivers of HCU expenditure concentration and the magnitude of their impact. With the aging of China's population and the profound shift in the disease spectrum, policymakers need to strengthen the early detection and intervention management of specific chronic diseases and high-risk populations, especially the early diagnosis and treatment of key cancers.

Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations.

BACKGROUND: In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease's rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. OBJECTIVE: The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. METHODS: We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China's new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China's response to the epidemic and to provide lessons for other countries' prevention and control of COVID-19. RESULTS: In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus's sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. CONCLUSIONS: China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.

The "long arm" of adverse childhood experiences on adult health depreciation in China.

BACKGROUND: The effects of childhood adversity on health may persist into the middle and old-aged. The assessment of the long-term effect of adverse childhood experiences (ACE) on adult health depreciation promotes a paradigm shift from current factors in health to early causation shaping health life course trajectories. OBJECTIVE: Determine whether the direct and significant dose-response effect between childhood adversity and health depreciation holds true, and to examine whether socioeconomic status (SES) in adulthood can diminish the negative effects of ACE. METHODS: A sample of 6344 nationally representative respondents (48 % were male; Mage = 64.48 years old, SD = 9.6 years old) was obtained. Adverse childhood experiences were collected from a Life History survey in China. Health depreciation was assessed by years lived with disabilities (YLDs) based on the Global Burden of Disease (GBD) disability weights. Ordinary least squares and matching methods (propensity score matching and coarsened exact matching) were used to test the relationship and treatment effect between ACEs and health depreciation. Mediating effect coefficients test and the Karlson-Holm-Breen (KHB) examined the mediating effect of socioeconomic status in adulthood. RESULTS: Compared to respondents without ACE, respondents who experienced 1 ACE increased YLD 15.9 % (p < 0.01); 2 ACEs by 32.8 % (p < 0.01); 3 ACEs by 47.4 % (p < 0.01), and 4+ ACEs by 71.5 % (p < 0.01) higher YLDs. The mediating effect of SES in adulthood was only between 3.9 % and 8.2 %. The interaction effect between ACE and adult socioeconomic status was not significant. CONCLUSION: The "long arm" of ACE on health depreciation exhibited a significant dose-response relationship. Policies and measures aimed at reducing family dysfunction and strengthening early childhood health interventions can facilitate the reduction of health depreciation in middle and old age.

The long arm of childhood: The prolonged influence of adverse childhood experiences on depression during middle and old age in China.

Utilizing data from the nationally representative China Health and Retirement Longitudinal Study, this study analyzed the effect of intensity and duration of adverse childhood experiences on depression in middle aged and older aged adults in China. The mediating effect of cumulative health risk and personal factors were validated through the Karlson-Holm-Breen method. The results showed a significant dose-response relationship between adverse childhood experiences and adult depression. The elevated health risks of chronic diseases, disabilities, and physical pain, as well as the disadvantages in education, employment, and economic status caused by the adverse childhood experiences indirectly worsen adult depression.

Health Inequality Among the Elderly in Rural China and Influencing Factors: Evidence from the Chinese Longitudinal Healthy Longevity Survey.

Based on data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), this paper calculates the health distribution of the elderly using the Quality of Well-Being Scale (QWB) score, and then estimates health inequality among the elderly in rural China using the Wagstaff index (WI) and Erreygers index (EI). Following this, it compares health inequalities among the elderly in different age groups, and finally, uses the Shapley and recentered influence function-index-ordinary least squares (RIF-I-OLS) model to decompose the effect of four factors on health inequality among the elderly in rural China. The QWB score distribution shows that the health of the elderly in rural China improved with social economic development and medical reform from 2002 to 2014. However, at the same time, we were surprised to find that the health level of the 65-74 years old group has been declining steadily since 2008. This phenomenon implies that the incidence of chronic diseases is moving towards the younger elderly. The WI and EI show that there is indeed pro-rich health inequality among the rural elderly, the health inequality of the younger age groups is more serious than that of the older age groups, and the former incidence of health inequality is higher. Health inequality in the age group of 65-74 years old is higher than that in other groups, and the trend of change fluctuated downward from 2002 to 2014. Health inequality in the age group of 75-84 years old is lower than that in the group of 65-74 years old, but higher than that in the other age groups. The results of Shapley decomposition show that demographic characteristics, socioeconomic status (SES), health care access, and quality of later life contributed 0.0054, 0.0130, 0.0442, and 0.0218 to the health inequality index of the elderly, which accounted for 6.40%, 15.39%, 52.41%, and 25.80% of health inequality index. From the results of RIF-I-OLS decomposition, this paper has analyzed detailed factors' marginal effects on health inequality from four dimensions, which indicates that the health inequality among the elderly in rural China was mainly caused by the disparity of income, medical expenses, and living arrangement.