Mechanisms of traumatic injury by demographic characteristics: an 8-year review of temporal trends from the National Trauma Data Bank.

BACKGROUND/PURPOSE: This 8-year retrospective study of the National Trauma Data Bank describes temporal trends of traumatic injury by mechanism of injury (MOI) by demographic characteristics from 2012 to 2019 for adult patients 18 years and older. METHODS: Overall, 5 630 461 records were included after excluding those with missing demographic information and International Classification of Disease codes. MOIs were calculated as proportions of total injury by year. Temporal trends of MOI were evaluated using two-sided non-parametric Mann-Kendall trend tests for (1) all patients and (2) within racial and ethnic groups (ie, Asian, 2% of total patient sample; Black, 14%; Hispanic or Latino, 10%; Multiracial, 3%; Native American, <1%; Pacific Islander, <1%; White, 69%) and stratified by age and sex. RESULTS/OUTCOMES: For all patients, falls increased over time (p=0.001), whereas burn (p<0.01), cut/pierce (p<0.01), cyclist (p=0.01), machinery (p<0.001), motor vehicle transport (MVT) motorcyclist (p<0.001), MVT occupant (p<0.001) and other blunt trauma (p=0.03) injuries decreased over time. The proportion of falls increased across all racial and ethnic groups and significantly for those aged 65 and older. There were further differences in decreasing trends of MOI by racial and ethnic categories and by age groups. CONCLUSIONS: These results suggest that falls are an important injury prevention target with an ageing US population across all racial and ethnic groups. Differing injury profiles by racial and ethnic identity indicate that injury prevention efforts be designed accordingly and targeted specifically to individuals most at risk for specific MOIs. STUDY TYPE: Level I, prognostic/epidemiological.

Context Matters: Assessing the Association Between Area Deprivation and the Severity of Injury and Types of Domestic Violence Victimization Among Women.

OBJECTIVES: To analyze the association between social determinants of health (SDOH), as measured by the Area Deprivation Index (ADI), and the severity of injury and types of domestic violence (DV) victimization among women (≥18 years of age) in Milwaukee, Wisconsin. METHODS: Neighborhood ADI data from the American Community Survey (2014-2018) were merged with Milwaukee Police Department DV data (2013-2017). ADI included multiple SDOH domains (education, employment, income/poverty, and housing quality). Types of DV were classified using an adaptation of the FBI-Uniform Crime Reporting-Hierarchy Rule, including Crimes Against Persons (homicide/negligent manslaughter, sexual assault/rape, and aggravated battery/assault). Chi-square, Anova tests, and logistic regression analyses were performed using Stata v.14.2; p-values ≤ .05 were considered statistically significant. FINDINGS: Except for aggravated battery/assault (OR: 1.003, 95% CI: 1.001-1.010), there was no statistically significant relationship between neighborhood disadvantage and DV victimization in 21,095 DV incidents between 2013 and 2017. Adjusted model results indicate that with each increase in neighborhood disadvantage (by ADI), there was a 1.003 increase in the likelihood for aggravated battery/assault (OR: 1.003, 95% CI: 1.001-1.005). Severity of DV injury was not significantly associated with ADI (OR: 1.002, 95% CI: 0.999-1.004). However, non-Hispanic Black women were 1.3 times more likely than non-Hispanic Whites to be victims of aggravated battery/assault (OR: 1.321, 95% CI: 1.189-1.469). Hispanic women were more likely than non-Hispanic Whites to sustain a more severe injury (OR: 0.841, 95% CI: 0.732-0.970]). CONCLUSION: The likelihood of DV-aggravated battery/assault increased with neighborhood deprivation, and significant associations (and highly lopsided prevalence) were found in types of DV victimization by race/ethnicity, with non-Hispanic Black women experiencing higher prevalence than others. This study adds to the body of knowledge by looking at how macro-level neighborhood-SDOH characteristics influence women's exposure to various forms of DV victimization and demonstrated the feasibility of linking law enforcement DV data to SDOH metrics, providing context for law enforcement DV victimizations.