Opioid prescription rates and risk for substantiated child abuse and neglect: A Bayesian spatiotemporal analysis.
Where this comes from
- Record sourced from PubMed, PMID 31698321.
- Also identified by DOI 10.1016/j.drugalcdep.2019.107623 and PMC identifier 6893092.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
To determine the association between opioid prescribing rates and substantiated abuse and neglect across Tennessee counties during an 11-year period. We adopted a Bayesian spatiotemporal approach to determine the association between opioid prescribing and rates of substantiated child abuse and neglect over and above environmental and population-level covariates. Annual county-level data for Tennessee (2006-2016) included rates of substantiated child abuse and neglect, rates of drug and non-drug crime incidents, racial and Hispanic composition, per capita income, child poverty and teen birth rates, and vacant housing. Higher opioid prescribing rates were associated with greater risk for substantiated child abuse and neglect across Tennessee counties. Risk for substantiated child abuse and neglect was positively associated with vacant housing, child poverty, teen birth rates, and rates of both drug and non-drug criminal incidents - including stimulant arrests. Risk for substantiated child abuse and neglect was negatively associated with percentages of African Americans. Results underscore the importance of opioid prescribing and crime rates as independent determinants of spatial and temporal variation in risk for substantiated child abuse and neglect. Policies that regulate and reduce opioid prescribing have the potential to reduce risk for child abuse and neglect.
Medical subject headings
- Analgesics, Opioid
- Bayes Theorem
- Child Abuse
- Practice Patterns, Physicians'
- Spatio-Temporal Analysis