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Journal Article

Citation

Hou H, Yu B, He C, Li G, Pei Y, Wang J, Tang J, Chen X, Gao X, Wang W. J. Affect. Disord. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.jad.2023.02.110

PMID

36849004

Abstract

BACKGROUND: The overall suicide rate in China has dropped substantially since the 1990s, but a slowdown in the decrease and even a reversing trend was observed in specific groups in recent years. This study aims to investigate the latest suicide risk in mainland China by using the age-period-cohort (APC) analysis.

METHOD: This population-based multiyear cross-sectional study included Chinese ages 10 to 84 years using data from the China Health Statistical Yearbook (2005-2020). Data were analyzed by the APC analysis and intrinsic estimator (IE) technique.

RESULTS: The data satisfactorily fit the constructed APC models. The cohort effect indicated a high risk of suicide among people birth in 1920-1944 and a sharp decline in the 1945-1979 cohort. The lowest risk occurred in the 1980-1994 cohort before a sharp increase in generation Z (birth years in 1995-2009). The period effect showed a declining trend since 2004. The age effect indicated that the suicide risk increased over time, except for a gradual decline from age 35 to 49. The suicide risk increased greatly in adolescents and reached the highest among the elderly. LIMITATIONS: The aggregated population-level data and the non-identifiability of the APC model could result in bias in the accuracy of results in this study.

CONCLUSIONS: This study successfully updated the Chinese suicide risk from the age, period and cohort perspective using the latest available data (2004-2019). The findings enhance the understanding of suicide epidemiology and provide evidence supporting policies and strategies at the macro-level for suicide prevention and management. Immediate action is needed to focus on a national suicide prevention strategy that targets generation Z, adolescents and the elderly which will require a collaborative effort by government officials, public/community health planners and health care agencies.


Language: en

Keywords

Suicide; Age-period-cohort modeling; Historical epidemiology; Social determinants

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