Health Insurance and Long-Term Care Services for the Disabled Elderly in China: Based on CHARLS Data

Abstract

Purpose

This paper aimed to explore the relationship between the different factors, especially health insurance, and the availability of long-term care (LTC) services, among the disabled elderly.

Methods

Based on the data of China Health and Retirement Longitudinal Study (CHARLS), the logistic regression model was utilized to evaluate the influence of the different factors, especially health insurance, on the availability of long-term care services.

Results

Our findings show some interesting results. Firstly, the findings suggest that informal long-term care (LTC) services for elderly persons with disabilities heavily depend on a family member from different health insurance groups. About 80.733% of the disabled elderly depend on a family member as their primary caregivers. Secondly, other influence factors such as income and area of residence were also significantly related to the availability of long-term rental services. Thirdly, Health insurance is a very important factor influencing the availability of Long-term care services both in urban and rural areas (p<0.001) but Income is the most interesting variable.

Conclusion

Based on our results, the growth and integration of formal long-term care (LTC) services should be facilitated. Firstly, policymakers can encourage formal long-term care (LTC) services from a variety of sources to work together to increase overall supply capability. Secondly, the long-term living security needs of people who do not have health insurance should be regulated through subsidies according to the economic status.

Keywords:

• long-term care
• LTC
• the disabled elderly
• health insurance
• CHARLS data
• informal care
• formal care

Acknowledgments

We thank the support by China Chongqing Education Commission Humanities and Social Sciences Research Project, grant number No: 19SKGH089; the MOE Project of Key Research Institute of Humanities and Social Sciences of Research Center for Economy of Upper Reaches of the Yangtse River “Research on agricultural modernization and industrial innovation and development”, grant number CJSYTD201710; Open subject of Collaborative Innovation Center for Urban Industries Development in Chengdu-Chongqing Economic Zone ”Study on spatiotemporal differences and influencing factors of low carbon agricultural productivity in China”, grant number KFJJ2019029; and thank Professor Timothy Kyng and Professor Fei Guo at Macquarie university, Feng Wei at University of Electronic Science and Technology of China for their thoughtful guidance.

Disclosure

The authors report no conflicts of interest in this work.