title: Using Bayesian space-time models to understand the substance use environment and risk for being referred to child protective services.
abstract: Parental substance misuse has often been cited as a cause of children being referred for investigation of child abuse and neglect. Research on how the substance use environment might affect this relationship is still in its infancy with primarily only cross-sectional studies finding a positive relationship of alcohol outlet density at the level of neighborhoods and alcohol prices at level of states and maltreatment. A longitudinal study shows that increasing female drug-related arrests are related to increasing rates of maltreatment in rural and urban counties. The current study incorporates three aspects of the substance use environment in a panel study of 58 California counties over 4 years (n = 232) to study this relationship for referrals to child protective services (CPS) for child abuse and neglect. We use conditionally autoregressive (CAR) Bayesian models to model the spatial and temporal structure in the data. We find that use of welfare benefits, the number of outliers per population, and the number of drug-related arrests per population are positively related to referrals while unemployment and admissions to publicly funded alcohol and drug user treatment programs are negatively correlated to referrals. Significant spatial structure and space-time relationships are also found. The findings indicate that supply of alcohol and drugs (as measured by number of alcohol outlets and arrests for drug use and sales) may increase risk for being referred to CPS, but treatment for substance use does not increase the risk for referral.
authors.affiliation: UCLA Department of Social Welfare, Los Angeles, California 90095, USA. freisther@spa.ucla.edu
authors.forename: Bridget
authors.initials: B
authors.lastname: Freisthler
authors.forename: Robert E
authors.initials: RE
authors.lastname: Weiss
mesh_terms: D000434:Alcoholic Beverages / Q000600:supply & distribution; D000465:Algorithms; D001499:Bayes Theorem; D002140:California; D002669:Child Welfare / Q000706:statistics & numerical data; D016241:Child of Impaired Parents; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D005843:Geography; D006801:Humans; D013287:Illicit Drugs / Q000600:supply & distribution; D008297:Male; D012017:Referral and Consultation; D018570:Risk Assessment / Q000706:statistics & numerical data; D019966:Substance-Related Disorders
chemical_list: D013287:Illicit Drugs