Evidence map›Paper›PMID 39794816›Full record

ArticleBMC psychology2025

Chinese burden of depressive disorders from 1990 to 2021 and prediction for 2030: analysis of data from the global burden of disease study 2021.

Na Yan, Caochen Zhang, Yihan Wang, Yuhao Wang, Yunjiao Luo, Yingxue Wang, Blen Dereje Shiferaw, Louisa Esi Mackay, Jingjing Wang, Jie Tang and 3 more

Abstract read
In one paragraph

Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Na Yan *School of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Caochen Zhang *Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
Yihan WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Yuhao WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Yunjiao LuoSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Yingxue WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Blen Dereje ShiferawSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Louisa Esi MackaySchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Jingjing WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Jie TangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Qingzhi WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China.
Xiuyin GaoSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China. 100000401004@xzhmu.edu.cn.
Wei WangSchool of Public Health, Xuzhou Medical University, 209 Tong Shan Road, Xuzhou, Jiangsu, 221004, China. weiwang90@163.com.

Funding

Education Science '14th Five-Year Plan' General Project in Jiangsu Province D/2021/01/163National Natural Science Foundation of China 82003484
6 · The paper itself

Abstract

backgroundThis study aims to examine the temporal changes in the incidence, prevalence, and disability-adjusted life years (DALYs) of depressive disorders as well as its association with age, period, and birth cohort among Chinese from 1990 to 2021, and forecast the future trends of incidence rates and numbers from 2022 to 2030.

methodsData for analysis were obtained from the Global Burden of Disease (GBD) 2021. Joinpoint analysis was used to calculate the annual percentage change (APC) and average annual percent change (AAPC) to describe the rates of depressive disorders. Age, period, and cohort model was utilized to disentangle age, period, and birth cohort effects on rates of depressive disorders. Bayesian age-period-cohort (BAPC) analysis was capitalized to forecast the incidence rates and numbers for different sexes and age groups from 2022 to 2030.

resultsThe age-standardized incidence (ASIR, AAPC: -0.35 [95%CI: -0.65, -0.04]), prevalence (ASPR, AAPC: -0.20 [95%CI: -0.24, -0.16]), and DAYLs (AAPC: -0.28 [95%CI: -0.51, -0.05]) rates of both sexes showed a downward trend from 1990 to 2021, despite a volatility growth in recent years (APC in 2019-2021 of ASPR: 0.96 [95%CI: 0.70, 1.23]). Females exhibited a higher burden of depressive disorders compared to males but experienced a more rapid rate of reduction changes. The burden of depressive disorders was most owing to the age effect and period effect in recent years. The ASIR was predicted to decrease in the whole population (males in 2030: 1,546.3 per 100,000 people; females in 2030: 2,465.8 per 100,000 people), but in children, adolescents, and the elderly demonstrate unfavorable trends in the future.

conclusionThe burden of depressive disorders decreased in China from 1990 to 2021 in terms of age-standardized rates, but increased in recent years. Children, adolescents, and the elderly are the risk groups for future depressive disorders. Considering the large population, the increasing fewer children, and the aging trend, as well as the possible long-term effects of COVID-19 on human psychological burden, more sex-age-sensitive social healthcare programs should be considered in the future to minimize the burden of depressive disorders in China.

Indexed as

Depressive DisorderDisability-Adjusted Life YearsGlobal Burden of DiseaseAdolescentAdultAgedAge FactorsBayes TheoremChildChild, PreschoolChinaEast Asian PeopleFemaleForecastingHumansIncidenceAge-period-cohort modelBayesian age-period-cohort analysisDepressive disordersDisease burdenJoinpoint regression

Identifiers

PMID39794816
PMCPMC11720356

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.