Literature DB >> 32032922

Depressive costs: medical expenditures on depression and depressive symptoms among rural elderly in China.

X Sun1, M Zhou2, L Huang3, B Nuse4.   

Abstract

OBJECTIVES: To provide an evaluation of medical expenditures induced by depression and depressive symptoms among rural elderly in China. STUDY
DESIGN: The panel dataset used for this study is taken from the China Family Panel Studies (CFPS) data for the years 2012 and 2016. We examined the case of rural elderly who were 60 years old or older at the time of the 2012 survey and 64 years old or older at the time of the 2016 survey and then created a panel dataset that includes 2938 rural elderly for both years to estimate the influence of depressive symptoms/depression on medical cost.
METHODS: Both two part model and four part model were used to estimate the influence of depressive symptoms and depression on medical expenditure. Then a counter-factual method was used to calculate the cost of depressive symptoms and depression among rural elderly in China.
RESULTS: Mental health status has significant effects on individual medical expenses, and they aggregately contribute to 47.26% of total personal expected medical expenditures. Specifically, the rural group, the female group, the widowed group, and the poorly educated group have higher medical expenditures because of depressive status than the other groups.
CONCLUSIONS: Mental health status significantly increased both the chance of undergoing medical care and the degree of medical expenditure among rural elderly in China. This situation is more serious in some vulnerable groups. Therefore, the Chinese government needs to reform its mental health of rural elderly and insurance institutions to eliminate the policy-caused barriers to mental health resources, especially for vulnerable groups.
Copyright © 2019 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Counter-factual analysis; Depression; Medical expenditure; Rural elderly

Mesh:

Year:  2020        PMID: 32032922     DOI: 10.1016/j.puhe.2019.12.011

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


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