Disease burden of ageing, sex and regional disparities and health resources allocation: a longitudinal analysis of 31 provinces in Mainland China

Shu Chen; Yafei Si; Katja Hanewald; Bingqin Li; Hazel Bateman; Xiaochen Dai; Chenkai Wu; Shenglan Tang

doi:10.1136/bmjopen-2022-064641

Disease burden of ageing, sex and regional disparities and health resources allocation: a longitudinal analysis of 31 provinces in Mainland China

BMJ Open. 2022 Nov 16;12(11):e064641. doi: 10.1136/bmjopen-2022-064641.

Authors

Shu Chen^{1

2}, Yafei Si^{1

2}, Katja Hanewald^{1

2}, Bingqin Li³, Hazel Bateman^{1

2}, Xiaochen Dai^{4

5}, Chenkai Wu⁶, Shenglan Tang^{7

8}

Affiliations

¹ School of Risk and Actuarial Studies, UNSW, Sydney, New South Wales, Australia.
² ARC Centre of Excellence in Population Ageing Research (CEPAR), UNSW, Sydney, New South Wales, Australia.
³ Social Policy Research Center, University of New South Wales, Sydney, New South Wales, Australia.
⁴ Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, Washington, USA.
⁵ Institute for Health Metrics and Evaluation, Seattle, Washington, USA.
⁶ Global Health Research Center, Duke Kunshan University, Kunshan, China.
⁷ Global Health Research Center, Duke Kunshan University, Kunshan, China [email protected].
⁸ Duke Global Health Institute, Duke University, Durham, North Carolina, USA.

Abstract

Objectives: To measure the disease burden of ageing based on age-related diseases (ARDs), the sex and regional disparities and the impact of health resources allocation on the burden in China.

Design: A national comparative study based on Global Burden of Diseases Study estimates and China's routine official statistics.

Setting and participants: Thirty-one provinces of Mainland China were included for analysis in the study. No individuals were involved.

Methods: We first identified the ARDs and calculated the disability-adjusted life years (DALYs) of ARDs in 2016. We assessed the ARD burden disparities by province and sex and calculated the provincial ARD burden-adjusted age. We assessed historical changes between 1990 and 2016. Fixed effects regression models were adopted to evaluate the impact of health expenditures and health workforce indicators on the ARD burden in 2010-2016.

Results: In 2016, China's total burden of ARDs was 15 703.7 DALYs (95% uncertainty intervals: 12 628.5, 18 406.2) per 100 000 population. Non-communicable diseases accounted for 91.9% of the burden. There were significant regional disparities. The leading five youngest provinces were Beijing, Guangdong, Shanghai, Zhejiang and Fujian, located on the east coast of China with an ARD burden-adjusted age below 40 years. After standardising the age structure, western provinces, including Tibet, Qinghai, Guizhou and Xinjiang, had the highest burden of ARDs. Males were disproportionately affected by ARDs. China's overall age-standardised ARD burden has decreased since 1990, and females and eastern provinces experienced the largest decline. Regression results showed that the urban-rural gap in health workforce density was positively associated with the ARD burdens.

Conclusion: Chronological age alone does not provide a strong enough basis for appropriate ageing resource planning or policymaking. In China, concerted efforts should be made to reduce the ARDs burden and its disparities. Health resources should be deliberately allocated to western provinces facing the greatest health challenges due to future ageing.

Keywords: epidemiology; health economics; health policy; public health.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Aging
China / epidemiology
Cost of Illness
Female
Health Resources*
Humans
Male
Respiratory Distress Syndrome*