Geographic Variation of Demographic and Socioeconomic Factors Associated with Child Abuse: A Geospatial Analysis

Introduction: Child abuse is a preventable public health issue that profoundly affects pediatric health and necessitates a multidisciplinary approach, including vigilance from pediatric neurosurgeons. Geographical variation in child abuse exists, influenced by neighborhood structural factors. However, limited research uses geospatial techniques to study this variation. This cross-sectional study examines the geospatial patterns of child abuse across Zip Code Tabulation Areas (ZCTAs).

Methods: We retrospectively reviewed ED admissions at our Level 1 trauma center, a major referral hub, over 7 years (2016–2023). Data on demographics, patients' addresses, injury characteristics—including Injury Severity Score (ISS)—and outcomes were obtained. American Community Survey 5-year estimates on ZCTA demographics and socioeconomic factors were accessed. Child abuse incidence was computed using spatial Bayesian smoothing techniques. Global Moran’s I test assessed spatial autocorrelation, and the Local Indicators of Spatial Association (LISA) test identified hotspots and coldspots of child abuse incidence. A zero-inflated negative binomial regression, adjusted for population density and urbanicity, with an offset of the population under 18 and a spatial lag variable as a zero predictor, estimated the incidence rate ratios (IRRs). Interactive choropleth maps indicating child abuse incidence were generated using the tmap Package in R.

Results: Our cohort included 628 patients with an average age of 3.05 years. We identified 39 ZCTAs as hotspots and 121 as coldspots. ZCTA factors associated with increased risk of child abuse included higher percentages of Black residents (IRR,1.015;95%CI,1.007–1.024;P <.001), unemployment (IRR,1.076;95%CI,1.041–1.112;P <.001), lack of health insurance (IRR,1.107;95%CI,1.054–1.162;P <.001), and poverty (IRR,1.086;95%CI,1.055–1.117;P <.001). Comparing patients residing in hotspots to others, we found these patients had a lower ISS (Median[IQR]:5[2–10]vs.10[5–14];P <.001) and lower proportions of traumatic brain injury (56.4%vs.70.0%;P <.001). Patients in hotspots had higher rates of direct discharge from the ED (43.3%vs.27.5%;P <.001), lower transfer rates to the ICU (21.1%vs.32.9%;P <.001), and shorter hospital stays (Median[IQR]:1[1–3]vs.2[1–4];P <.001).

Conclusion : Our findings reveal sociodemographic disparities across ZCTAs impacting child abuse incidence. Policymakers should focus on these disparities to implement targeted neighborhood-level interventions for effective prevention.