The Impacts of Internal Migration on Child Victimization in China: A Meta-Analysis

Qiqi Chen, Xiaoyue Sun, Qianwen Xie, Jia Li, Ko Ling Chan

Research output: Contribution to journalReview article

3 Citations (Scopus)

Abstract

Objective: A 100 million children in China are affected by internal migration, a result of the growing demand for human labor due to economic growth. Whether moving to urban cities with their parents or being left behind in rural areas, these children are vulnerable to victimization. The meta-analysis presented in this study is the first to synthesize the rates of victimization among children affected by internal migration. Method: Studies providing data published before May 2016 on the prevalence of child victimization among 105,415 Chinese subjects aged 0–17 years were identified through eight English and Chinese databases. Two reviewers independently extracted data to generate summary effect sizes using a random effects meta-analytic model. A priori subgroup and sensitivity analyses were performed to evaluate heterogeneity and bias in these studies. Results: Our meta-analysis of 31 studies showed that children affected by internal migration, both migrant children and left-behind children, are at a higher risk of victimization in comparison to their unaffected counterparts (odds ratio [OR] = 1.492, p <.01), especially in their vulnerability to unintentional injuries (OR = 1.683, p <.01) and neglect (OR = 1.398, p <.01). These children are at a higher risk of being unintentionally injured from the ages of 6 to 11 years (OR = 1.644, p <.01). The highest victimization rate observed in this study was found in the central districts of China (OR = 1.599, p <.01). Conclusion: This study reveals the high prevalence of victimization among both migrant children and left-behind children. The increasing number of children affected by internal migration deserves continuous academic and policy attention.

Original languageEnglish
Pages (from-to)40-50
Number of pages11
JournalTrauma, Violence, and Abuse
Volume20
Issue number1
DOIs
Publication statusPublished - 2019 Jan 1

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All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Applied Psychology
  • Public Health, Environmental and Occupational Health

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