Correlations between Hotspots of Child Maltreatment and Neighborhood-Level Interventions

Seonga Cho, Sewon Kim () and Bong Joo Lee
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Seonga Cho: University of California
Sewon Kim: Catholic Kwandong University
Bong Joo Lee: Seoul National University

Child Indicators Research, 2024, vol. 17, issue 5, No 10, 2099-2121

Abstract: Abstract Child maltreatment, which seriously impacts children’s well-being, is influenced by characteristics of neighborhood. Notably, previous studies have neglected the role of neighborhood spatial features in child maltreatment. Hence, we aimed to determine the distribution of child maltreatment occurrence by city, county, and district in South Korea; whether high child maltreatment incidence rates are clustered spatially; and the neighborhood factors that affect child maltreatment incidence. We analyzed 26,354 child maltreatment cases from 225 regions for 2020 using data from the National Child Abuse Database System. Data analysis procedures followed a three-tiered approach: ordinary least squares regression, Jarque–Bera and Breusch–Pagan tests, and geographically weighted regression. We identified concentrated hotspots and found that child maltreatment incidences were spatially autocorrelated. Key neighborhood characteristics that increased child maltreatment were the number of child community centers, the number of vacant houses, the number of multicultural households, and the number of single-parent households. Financial independence of local governments, the size of the older-adult population, and population density are the key neighborhood characteristics that decrease child maltreatment. Our findings reveal that prioritizing socioeconomically vulnerable regions is critical to alleviating child maltreatment. This study provides a valuable reference for identifying areas at high risk of child maltreatment and for implementing cost-effective, neighborhood-level interventions to reduce child maltreatment.

Keywords: Child maltreatment; South Korea; Hotspot; Local characteristics; Neighborhood (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12187-024-10161-2

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