Background Multimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes. MethodsIn this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status. Findings Of 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56-69) in 2015, and 5766 (48•8%) participants were male. 7320 (61•9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2•93, 95% CI 2•71-3•15), among women (2•70, 2•04-3•57), within a higher socioeconomic group (for quartile 4 [highest group] 1•50, 1•24-1•82), and higher educational level (5•17, 3•02-8•83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1•29, 95% CI 1•27-1•31), and number of days spent in hospital as an inpatient (1•38, 1•35-1•41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1•29, 95% CI 1•26-1•32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes.Interpretation Concerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection.
An Expert Working Group of the National Heart Foundation of Australia undertook a review of systematic reviews of the evidence relating to major psychosocial risk factors to assess whether there are independent associations between any of the factors and the development and progression of coronary heart disease (CHD), or the occurrence of acute cardiac events. The expert group concluded that (i) there is strong and consistent evidence of an independent causal association between depression, social isolation and lack of quality social support and the causes and prognosis of CHD; and (ii) there is no strong or consistent evidence for a causal association between chronic life events, work‐related stressors (job control, demands and strain), Type A behaviour patterns, hostility, anxiety disorders or panic disorders and CHD. The increased risk contributed by these psychosocial factors is of similar order to the more conventional CHD risk factors such as smoking, dyslipidaemia and hypertension. The identified psychosocial risk factors should be taken into account during individual CHD risk assessment and management, and have implications for public health policy and research.
objectives To investigate trends and socio-economic disparities in the catastrophic health expenditure (CHE) and health impoverishment in China after major reform of the health system and to examine the impacts of the chronic disease on CHE and impoverishment.methods We obtained data from four rounds of the China Family Panel Studies 2010-2016, with a sample size of 14 960 households. We defined CHE as the point at which annual household health payments exceeded 40% of annual capacity to pay. Impoverishment is measured by the $1.90 per day poverty line. Multivariate logistic regression models were performed to identify impacts of the family member with chronic disease on CHE and impoverishment.results Between 2010 and 2016, the incidence of CHE in China decreased from 19.37% to 15.11% and from 7.39% to 5.14% for health impoverishment; however, the decrease in level of impoverishment was less in rural areas (from 6.16% down to 3.03%) than in urban areas (from 8.46% down to 7.81%). The gap between impoverishment rates across the income quartiles is growing. Multivariable analysis showed that households with two or more members suffering chronic diseases were significantly more likely to incur CHE (aOR: 2.46, 95% CI: 1.93-3.13) and impoverishment (aOR: 2.66, 95% CI: 1.87-3.78) than households with no members suffering chronic diseases, after adjusting for sociodemographic covariates.conclusions Important advances have been made in achieving greater financial protection for Chinese citizens. Nevertheless, greater attention to the poor households with chronic disease members is needed. Policymakers in China should focus on optimising integrated rural-urban health insurance by expanding the current benefit packages and strengthening poverty alleviation efforts.keywords catastrophic health expenditure, health impoverishment, socio-economic disparity, China Sustainable Development Goals (SDGs): SDG 1 (no poverty), SDG 3 (good health and well-being), SDG 8 (decent work and economic growth), SDG 10 (reduced inequalities), SDG 11 (sustainable cities and communities), SDG 17 (partnerships for the goals)
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