Suchergebnisse

AbstractThis study provides causal evidence on the impact of retirement on internal migration in a developing country. Using a fuzzy regression discontinuity design, combined with a nationally representative sample of 228,855 older Chinese adults, we find that retirement leads to an increase in the probability of being a migrant by 12.9 percentage points (an 80% increase in migration). Approximately 38% of the total migration effects can be attributed to intertemporal shifts. The impact is more pronounced for the lower‐educated, those who have restricted access to health insurance and pension and those who come from origins with high accommodation costs. Relying on old age support from adult children in migration is a likely mechanism. Lifting migration restrictions and improving government‐provided benefits for retirees could be helpful to cope with population aging in a developing country.

Background China's long-term care insurance (LTCI) policy has been minimally evaluated. This systematic review aimed to assess the impact of China's LTCI pilot on beneficiaries and their caregivers. Methods This review is based on a search of peer-reviewed studies in English (Embase, MEDLINE, Web of Science) and Chinese (China National Knowledge Infrastructure [CNKI], VIP, Wanfang) databases from January 2016 through July 2020, with all studies published in English or Chinese included. We included quantitative analyses of beneficiary-level data that assessed the impact of LTCI on beneficiaries and their caregivers, with no restriction placed on the outcomes studied. Results Nine studies met our inclusion criteria. One study was a randomised trial and two used quasi-experimental approaches. Four studies examined LTCI's effect on beneficiaries' quality of life, physical pain, and health service utilisation; one study reported the effect on beneficiaries' healthcare expenditures; and one study evaluated the impact on caregivers' care tasks. These studies generally found LTCI to be associated with an improvement in patients' quality of life (including decreased physical pain), a reduction in the number of outpatient visits and hospitalisations, decreased patient-level health expenditures (e.g. one study reported a reduction in the length of stay, inpatient expenditures, and health insurance expenditures in tertiary hospitals by 41.0%, 17.7%, and 11.4%, respectively), and reduced informal care tasks for caregivers. In addition, four out of four studies that evaluated this outcome found that beneficiaries' overall satisfaction with LTCI was high. Conclusion The current evidence base for the effects of LTCI in China on beneficiaries and their caregivers is sparse. Nonetheless, the existing studies suggest that LTCI has positive effects on beneficiaries and their caregivers. Further rigorous research on the impacts of LTCI in China is needed to inform the future expansion of the program.

In this article, we describe the dataset used in our study entitled "The interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India: A cross-sectional study of 2.4 million adults", recently published in Social Science & Medicine, and present supplementary analyses. We used data from three different household surveys in India, which are representative at the district level. Specifically, we analyzed pooled data from the District-Level Household Survey 4 (DLHS-4) and the second update of the Annual Health Survey (AHS), and separately analyzed data from the National Family Health Survey (NFHS-4). The DLHS-4 and AHS sampled adults aged 18 years or older between 2012 and 2014, while the NFHS-4 sampled women aged 15–49 years and - in a subsample of 15% of households - men aged 15–54 years in 2015 and 2016. The measures of individual-level socio-economic status that we used in both datasets were educational attainment and household wealth quintiles. The measures of district-level development, which we calculated from these data, were i) the percentage of participants living in an urban area, ii) female literacy rate, and iii) the district-level median of the continuous household wealth index. An additional measure of district-level development that we used was Gross Domestic Product per capita, which we obtained from the Planning Commission of the Government of India for 2004/2005. Our outcome variables were diabetes, hypertension, obesity, and current smoking. The data were analyzed using both district-level regressions and multilevel modelling.

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020.