Identifying children at high risk for a child maltreatment report

Child Abuse Negl. 2011 Feb;35(2):96-104. doi: 10.1016/j.chiabu.2010.09.003. Epub 2011 Mar 4.

Abstract

Objective: To help professionals identify factors that place families at risk for future child maltreatment, to facilitate necessary services and to potentially help prevent abuse and neglect.

Method: The data are from a prospective, longitudinal study of 332 low-income families recruited from urban pediatric primary care clinics, followed for over 10 years, until the children were approximately 12 years old. Children with prior child protective services involvement (CPS) were excluded. The initial assessment included sociodemographic, child, parent and family level variables. Child maltreatment was assessed via CPS reports. Risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated using Cox regression models.

Results: Of the 224 children without a prior CPS report and with complete data who were followed for an average of 10 years, 97 (43%) later had a CPS report. In a multivariate survival analysis, 5 risk factors predicted CPS reports: child's low performance on a standardized developmental assessment (RR=1.23, 95% CI=1.01-1.49, p=.04), maternal education≤high school (RR=1.55, CI=1.01-2.38, p=.04), maternal drug use (RR=1.71, CI=1.01-2.90, p<.05), maternal depressive symptoms (RR per one standard deviation higher score=1.28, CI=1.09-1.51, p<.01), and more children in the family (RR per additional child=1.26, CI=1.07-1.47, p<.01).

Conclusions: Five risk factors were associated with an increased risk for later maltreatment. Child health care and other professionals can identify these risk factors and facilitate necessary services to strengthen families, support parents and potentially help prevent child maltreatment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Child Abuse* / prevention & control
  • Child Welfare
  • Confidence Intervals
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Poverty
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment*
  • Survival Analysis
  • Urban Population