title: The Geography of Child Maltreatment: A Spatiotemporal Analysis Using Bayesian Hierarchical Analysis With Integrated Nested Laplace Approximation.
abstract: This study quantifies the spatiotemporal risk of child abuse and neglect in Los Angeles at the census tract level over a recent 4-year period, identifies areas of increased risk, and evaluates the role of structural disadvantage in substantiated child maltreatment referrals. Child maltreatment data on 83,379 child maltreatment cases in 1,678 census tracts spanning 2006-2009 were obtained from the Los Angeles County Department of Children and Family Services. Substantiated referral counts were analyzed across census tracts with Bayesian hierarchical spatial models using integrated nested Laplace approximations. Results showed that the unadjusted yearly rate of child abuse and neglect held fairly steady over the study period decreasing by only 2.57%. However, the temporal term in the spatiotemporal model reflected a downward trend beginning in 2007. High rates of abuse and neglect were predicted by several neighborhood-level measures of structural burden. Every 1-unit decrease in the social vulnerability index reduced the risk of child abuse and neglect by 98.3% (95% CrI = 1.869-2.1042) while every 1-unit increase in the Black-White dissimilarity index decreased child abuse and neglect risk by 70.6%. The interaction of these variables demonstrated the protective effect of racial heterogeneity in socially vulnerable neighborhoods. No such effect was found in neighborhoods characterized by low levels of vulnerability. Population-based child abuse and neglect prevention and intervention efforts should be aided by the characteristics of neighborhoods that demonstrate strong spatial patterns even after accounting for the role of race and place.
authors.affiliation: 1 Northeastern University, Boston, MA, USA.
authors.forename: Gia Elise
authors.initials: GE
authors.lastname: Barboza
mesh_terms: D001499:Bayes Theorem; D002391:Catchment Area, Health / Q000706:statistics & numerical data*; D002648:Child; D002649:Child Abuse / Q000517:prevention & control / Q000706:statistics & numerical data*; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D015141:Los Angeles; D008297:Male; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D062211:Spatio-Temporal Analysis; D014754:Violence / Q000706:statistics & numerical data
keywords: Bayesian hierarchical spatial modeling; INLA; child abuse and neglect substantiations; child maltreatment; racial heterogeneity; social disorganization