Longitudinal trends and future projections of injury-related economic burden among middle-aged and older adults in China: analysis of CHARLS data 2011–2018

BACKGROUND: Existing studies on the economic burden of injury in China lack dynamic, national-level assessments. Using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018), this study examined trends in injury prevalence and economic burden among middle-aged and elderly adults and predicted the burden for 2021-2025. The findings aim to inform national injury prevention strategies and health policy-making. METHODS: Data were extracted from four waves of the CHARLS database (2011, 2013, 2015, and 2018). After excluding missing values, the study included 9,742, 9,586, 10,198, and 12,202 residents aged 45 and above, respectively. To address the common issues of excess zeros and skewed distributions in medical expenditure data, a two-part model was employed to estimate the per capita direct and indirect economic burdens of the injured population, and to analyze the variations in these burdens across different demographic characteristics. Furthermore, a GM(1,1) model was utilized on limited time-series data to forecast the economic burden of injuries from 2021 to 2025. RESULTS: The prevalence of injury among middle-aged and elderly individuals was 22.57% in 2011, 18.10% in 2013, 20.58% in 2015, and 19.45% in 2018, demonstrating an overall downward trend. Compared to 2011, the direct economic burden of injuries in 2018 decreased by 93.62% (from 9,689.6 CNY to 618.4 CNY), while the indirect economic burden decreased by 64.12% (from 321.1 CNY to 115.2 CNY). Stratified analysis indicated that the overall economic burden was higher for urban residents than for their rural counterparts; females bore a higher direct economic burden than males; and individuals with lower cognitive levels faced a higher economic burden than those with better cognitive function. Projections for 2021-2025 suggest that the economic burden of injuries in China will continue to decline, with the average direct and indirect economic burdens expected to drop to 191.3 CNY and 77.2 CNY, respectively, by 2025. CONCLUSION: The prevalence and economic burden of injury among middle-aged and older Chinese adults generally declined. However, urban residents, females, and populations with low cognitive levels continued to sustain comparatively higher economic burdens. Governments and society should refine policies targeting these key populations and strengthen injury prevention education in communities and public spaces to further reduce injury incidence and the associated economic losses.

Authors

Institutions

Publication Details

Journal
Health Economics Review
Published
2026-05-12
DOI
https://doi.org/10.1186/s13561-026-00785-1
Primary Topic
Injury Epidemiology and Prevention
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Longitudinal trends and future projections of injury-related economic burden among middle-aged and older adults in China: analysis of CHARLS data 2011–2018

Mingqin Cao, Shaobo Zeng, Caihong Li, Shuanglong Yuan et al.
Health Economics Review
Injury Epidemiology and Prevention
article

Longitudinal trends and future projections of injury-related economic burden among middle-aged and older adults in China: analysis of CHARLS data 2011–2018

Mingqin Cao, Shaobo Zeng, Caihong Li, Shuanglong Yuan, Abulikemu Aili, Yaying Zhang, Guliziba Kuerbanjiang, Shuang Han, Chen Liang
article en

Abstract

BACKGROUND: Existing studies on the economic burden of injury in China lack dynamic, national-level assessments. Using data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018), this study examined trends in injury prevalence and economic burden among middle-aged and elderly adults and predicted the burden for 2021-2025. The findings aim to inform national injury prevention strategies and health policy-making. METHODS: Data were extracted from four waves of the CHARLS database (2011, 2013, 2015, and 2018). After excluding missing values, the study included 9,742, 9,586, 10,198, and 12,202 residents aged 45 and above, respectively. To address the common issues of excess zeros and skewed distributions in medical expenditure data, a two-part model was employed to estimate the per capita direct and indirect economic burdens of the injured population, and to analyze the variations in these burdens across different demographic characteristics. Furthermore, a GM(1,1) model was utilized on limited time-series data to forecast the economic burden of injuries from 2021 to 2025. RESULTS: The prevalence of injury among middle-aged and elderly individuals was 22.57% in 2011, 18.10% in 2013, 20.58% in 2015, and 19.45% in 2018, demonstrating an overall downward trend. Compared to 2011, the direct economic burden of injuries in 2018 decreased by 93.62% (from 9,689.6 CNY to 618.4 CNY), while the indirect economic burden decreased by 64.12% (from 321.1 CNY to 115.2 CNY). Stratified analysis indicated that the overall economic burden was higher for urban residents than for their rural counterparts; females bore a higher direct economic burden than males; and individuals with lower cognitive levels faced a higher economic burden than those with better cognitive function. Projections for 2021-2025 suggest that the economic burden of injuries in China will continue to decline, with the average direct and indirect economic burdens expected to drop to 191.3 CNY and 77.2 CNY, respectively, by 2025. CONCLUSION: The prevalence and economic burden of injury among middle-aged and older Chinese adults generally declined. However, urban residents, females, and populations with low cognitive levels continued to sustain comparatively higher economic burdens. Governments and society should refine policies targeting these key populations and strengthen injury prevention education in communities and public spaces to further reduce injury incidence and the associated economic losses.

Health Economics Review
Xinjiang Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 5%
Injury Epidemiology and Prevention
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.