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The Latent Class Analysis of Adverse Childhood Experiences among Chinese Children and Early Adolescents in Rural Areas and Their Association with Depression and Suicidal Ideation

Author

Listed:
  • Chun Chen

    (School of Humanities and Social Sciences, Chinese University of Hong Kong-Shenzhen, Shenzhen 518172, China)

  • Yu Sun

    (Department of Education Policy Studies, Pennsylvania State University, State College, PA 16801, USA)

  • Boyuan Liu

    (Department of Sociology, Tsinghua University, Beijing 100184, China
    China Development Research Foundation, Beijing 100011, China)

  • Xiao Zhang

    (China Institute for Educational Finance Research, Peking University, Beijing 100871, China)

  • Yingquan Song

    (China Institute for Educational Finance Research, Peking University, Beijing 100871, China)

Abstract

Exposure to adverse childhood experiences (ACEs) is a global public health concern that is detrimental to the psychological outcomes of Chinese children in rural areas due to the lack of public awareness of ACEs and mental health resources. The objective of this study was to identify the patterns of ACEs and the impact of ACE patterns on depression and suicidal ideation among 4683 students (mean age = 10.08 years, SD = 0.99; 48.17% female students) from 63 elementary schools in rural areas in Guizhou Province, China. Latent class analysis was conducted to identify the best class pattern. A three-step approach was undertaken to explore the association between the class patterns and demographic covariates and depression and suicidal thoughts. An overall three-class pattern of ACEs was identified, which was: (1) high ACEs, (2) high verbal abuse and emotional neglect and low household dysfunction, and (3) low ACEs. The results also showed that children in the high ACEs class tended to show higher depression rates and more frequent suicidal ideation across the three groups. Being female and younger and having a lower socioeconomic status were risk factors. Our study identified a class pattern that was not found in previous research, which is high verbal abuse and emotional neglect and low household dysfunction.

Suggested Citation

  • Chun Chen & Yu Sun & Boyuan Liu & Xiao Zhang & Yingquan Song, 2022. "The Latent Class Analysis of Adverse Childhood Experiences among Chinese Children and Early Adolescents in Rural Areas and Their Association with Depression and Suicidal Ideation," IJERPH, MDPI, vol. 19(23), pages 1-13, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16031-:d:989444
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    References listed on IDEAS

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    1. Yang, Chenlu & Liu, Xiaoli & Yang, Yuning & Huang, Xiaona & Song, Qiying & Wang, Yan & Zhou, Hong, 2020. "Violent disciplinary behaviors towards left-behind children in 20 counties of rural China," Children and Youth Services Review, Elsevier, vol. 114(C).
    2. Vermunt, Jeroen K., 2010. "Latent Class Modeling with Covariates: Two Improved Three-Step Approaches," Political Analysis, Cambridge University Press, vol. 18(4), pages 450-469.
    3. Mi Zhou & Guangsheng Zhang & Scott Rozelle & Kaleigh Kenny & Hao Xue, 2018. "Depressive Symptoms of Chinese Children: Prevalence and Correlated Factors among Subgroups," IJERPH, MDPI, vol. 15(2), pages 1-10, February.
    4. Afifi, T.O. & Enns, M.W. & Cox, B.J. & Asmundson, G.J.G. & Stein, M.B. & Sareen, J., 2008. "Population attributable fractions of psychiatric disorders and suicide ideation and attempts associated with adverse childhood experiences," American Journal of Public Health, American Public Health Association, vol. 98(5), pages 946-952.
    5. Xuening Chang & Xueyan Jiang & Tamara Mkandarwire & Min Shen, 2019. "Associations between adverse childhood experiences and health outcomes in adults aged 18–59 years," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-11, February.
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