BAO Xiaolin, WEI Hongjuan, BIAN Xinxin, MA Xiumei, GAO Yin, ZHANG Yingyan, LIU Wei, MA Yuexian, ZHANG Weixin, YANG Xuewen. Analysis and Prediction of Disease Burden of Depression in Old Age in China from 1990 to 2021[J]. Medical Journal of Peking Union Medical College Hospital, 2025, 16(2): 361-369. DOI: 10.12290/xhyxzz.2024-0664
Citation: BAO Xiaolin, WEI Hongjuan, BIAN Xinxin, MA Xiumei, GAO Yin, ZHANG Yingyan, LIU Wei, MA Yuexian, ZHANG Weixin, YANG Xuewen. Analysis and Prediction of Disease Burden of Depression in Old Age in China from 1990 to 2021[J]. Medical Journal of Peking Union Medical College Hospital, 2025, 16(2): 361-369. DOI: 10.12290/xhyxzz.2024-0664

Analysis and Prediction of Disease Burden of Depression in Old Age in China from 1990 to 2021

Funds: 

Basic Scientific Research Projects of Heilongjiang Provincial Colleges and Universities in 2020 2020-KYYWF-0034

More Information
  • Corresponding author:

    WEI Hongjuan, E-mail: 627322568@qq.com

  • Received Date: August 26, 2024
  • Accepted Date: November 02, 2024
  • Available Online: November 22, 2024
  • Publish Date: November 21, 2024
  • Issue Publish Date: March 29, 2025
  • Objective 

    To analyze the trends in disease burden and risk factors of depression among the elderly population in China from 1990 to 2021, and to provide a theoretical basis for the prevention, treatment, and policy-making of geriatric depression in China.

    Methods 

    Data on the disease burden of geriatric depression in China from 1990 to 2021, including the number of incident cases, disability-adjusted life years (DALYs), incidence rate, and DALY rate, were extracted from the 2021 Global Burden of Disease (GBD) database.The Joinpoint regression model was used to analyze the trends by calculating the annual percentage change (APC) and average annual percentage change (AAPC).The autoregressive integrated moving average (ARIMA) model was employed to predict the disease burden of geriatric depression over the next five years.Population attributable fractions (PAFs) were used to describe the risk factors for geriatric depression in China in 1990 and 2021.

    Results 

    From 1990 to 2021, the number of incident cases and the incidence rate of geriatric depression in China showed an overall upward trend.The most significant increase in incidence was observed in the 60-64 age group, while the prevalence rate increased notably in the ≥ 95 age group.TheDALY rate showed the most pronounced upward trend in the 65-69 age group.The incidence, prevalence, and DALY rates of geriatric depression were higher in women than in men.Major risk factors included child hood sexual abuse and intimate partner violence, with the impact of intimate partner violence being particularly significant among women.The ARIMA model predicted that the incidence, prevalence, and DALY rates of geriatric depression in China would decline over the next five years, with a greater decline observed in women than in men.

    Conclusions 

    From 1990 to 2021, the incidence, prevalence, and DALY rates of geriatric depression in China showed an overall upward trend, with higher rates observed in women than in men.Greater attention should be paid to the elderly female population, with a focus on early prevention to reduce the disease burden of geriatric depression.

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