Social Psychiatry and Psychiatric Epidemiology

, Volume 54, Issue 1, pp 99–110 | Cite as

Historical trends in suicide risk for the residents of mainland China: APC modeling of the archived national suicide mortality rates during 1987–2012

  • Xinguang Chen
  • Yang SunEmail author
  • Zhi Li
  • Bin Yu
  • Ge Gao
  • Peigang Wang
Original Paper



Distinctive and dramatic changes in the history of China with a rapid suicide decline in recent years present an opportunity to investigate the risk of suicide. In this study, we investigated suicide risk with a historical perspective with archived data to inform suicide research and prevention policies and strategies.


Documented age-specific suicide mortality rates in 1987–2012 were decomposed into age, period, and cohort effect using APC-modeling method and intrinsic estimator (IE) technique. The estimated effects were further analyzed by numerical differentiation.


The data satisfactorily fit the constructed APC models. Cohort effect indicated that suicide risk in China fluctuated at very high levels during 1903–1967, followed by a sharp decline during 1968–1977, and reached the lowest level in 1983–1987 before increased again. Period effect confirmed the declining trend since 1987. Three sunny cohorts with reduced suicide risk and four cloudy cohorts with increased risk were, respectively, associated with significant cultural, social, political, and economic events in China since the 1900s.


The mega trends in the suicide risk at the population level are closely related to significant historical events in China. Suicide is anticipated to increase because of the growing risk for the young cohorts (particularly young females) as the country further develops. Study findings suggest the significance of national strategies for suicide prevention and control, including maintenance of social harmony and stability, provision of more opportunities for development, enhancement of social integration, and restriction of suicide facilitating factors.


Suicide research Social determinants Historical epidemiology China Age–period–cohort modeling 



The study was supported in part by the four participation schools, including Wuhan University, University of Florida, The Pennsylvania State University, and University of Maryland.

Author contributions

XC initiated the idea and worked with the team to establish the framework, guided data analysis, write most of the manuscript. YS participated in framing the research, collected data and participated in data analysis, results interpretation and manuscript development. ZL participated in later-stage in reframing the research topic, collected part of the data, and conducted most of the analysis, contributed much for manuscript preparation. BY and GG assisted in literature search, data analysis, results tabulation and graphing, manuscript writing and reviewing. PW participated in results interpretation and manuscript development.


The study was supported by the Humanities and Social Sciences Project of China Ministry of Education (17YJCZH155) and National Natural Science Foundation of China (71573192, 71303012). In addition, author Chen X was supported in part by the Clinical and Translational Science Institute (CTSI) at the University of Florida.

Compliance with ethical standards

Conflict of interest

None of the authors has a conflict of interest associated with the reported research.

Availability of data and material

The data sets generated and/or analyzed during the current study are available in the NHFPC (National Health and Family Planning Commission of the People’s Republic of China) repository,, and published on Annual China Health Statistical Yearbook, which renamed as China Health and Family Planning Statistics Yearbook from year 2014.

Supplementary material

127_2018_1593_MOESM1_ESM.tif (969 kb)
Supplementary material 1 (TIF 968 KB)
127_2018_1593_MOESM2_ESM.docx (29 kb)
Supplementary material 2 (DOCX 28 KB)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xinguang Chen
    • 1
    • 2
  • Yang Sun
    • 1
    • 3
    Email author
  • Zhi Li
    • 4
  • Bin Yu
    • 2
  • Ge Gao
    • 5
  • Peigang Wang
    • 1
  1. 1.Global Health InstituteWuhan UniversityWuhanChina
  2. 2.Department of EpidemiologyUniversity of FloridaGainesvilleUSA
  3. 3.Department of Public Affairs and Management, School of Political Science and Public AdministrationWuhan UniversityWuhanChina
  4. 4.Department of Sociology and CriminologyThe Pennsylvania State University, University ParkPennsylvaniaUSA
  5. 5.Department of SociologyUniversity of MarylandCollege ParkUSA

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