Kimberly Dalve1,2, Emma Gause3,4, Brianna Mills3,4, Anthony S Floyd5, Frederick P Rivara4, Ali Rowhani-Rahbar3,4. 1. Department of Epidemiology, School of Public Health, University of Washington, Hans Rosling Center for Population Health, 3980 15th Avenue NE, Box 351619, Seattle, WA, 98195-7230, USA. kdalve@uw.edu. 2. Firearm Injury & Policy Research Program, Harborview Injury Prevention & Research Center, University of Washington, 325 Ninth Avenue, Box 359960, Seattle, WA, 98104, USA. kdalve@uw.edu. 3. Department of Epidemiology, School of Public Health, University of Washington, Hans Rosling Center for Population Health, 3980 15th Avenue NE, Box 351619, Seattle, WA, 98195-7230, USA. 4. Firearm Injury & Policy Research Program, Harborview Injury Prevention & Research Center, University of Washington, 325 Ninth Avenue, Box 359960, Seattle, WA, 98104, USA. 5. Alcohol and Drug Abuse Institute, University of Washington, 1107 NE 45th St., Suite 120, Box 354805, Seattle, WA, 98105-4631, USA.
Abstract
BACKGROUND: Firearm violence is a public health problem that disparately impacts areas of economic and social deprivation. Despite a growing literature on neighborhood characteristics and injury, few studies have examined the association between neighborhood disadvantage and fatal and nonfatal firearm assault using data on injury location. We conducted an ecological Bayesian spatial analysis examining neighborhood disadvantage as a social determinant of firearm injury in Seattle, Washington. METHODS: Neighborhood disadvantage was measured using the National Neighborhood Data Archive disadvantage index. The index includes proportion of female-headed households with children, proportion of households with public assistance income, proportion of people with income below poverty in the past 12 months, and proportion of the civilian labor force aged 16 and older that are unemployed at the census tract level. Firearm injury counts included individuals with a documented assault-related gunshot wound identified from medical records and supplemented with the Gun Violence Archive between March 20, 2016 and December 31, 2018. Available addresses were geocoded to identify their point locations and then aggregated to the census tract level. Besag-York-Mollie (BYM2) Bayesian Poisson models were fit to the data to estimate the association between the index of neighborhood disadvantage and firearm injury count with a population offset within each census tract. RESULTS: Neighborhood disadvantage was significantly associated with the count of firearm injury in both non-spatial and spatial models. For two census tracts that differed by 1 decile of neighborhood disadvantage, the number of firearm injuries was higher by 21.0% (95% credible interval: 10.5, 32.8%) in the group with higher neighborhood disadvantage. After accounting for spatial structure, there was still considerable residual spatial dependence with 53.3% (95% credible interval: 17.0, 87.3%) of the model variance being spatial. Additionally, we observed census tracts with higher disadvantage and lower count of firearm injury in communities with proximity to employment opportunities and targeted redevelopment, suggesting other contextual protective factors. CONCLUSIONS: Even after adjusting for socioeconomic factors, firearm injury research should investigate spatial clustering as independence cannot be able to be assumed. Future research should continue to examine potential contextual and environmental neighborhood determinants that could impact firearm injuries in urban communities.
BACKGROUND: Firearm violence is a public health problem that disparately impacts areas of economic and social deprivation. Despite a growing literature on neighborhood characteristics and injury, few studies have examined the association between neighborhood disadvantage and fatal and nonfatal firearm assault using data on injury location. We conducted an ecological Bayesian spatial analysis examining neighborhood disadvantage as a social determinant of firearm injury in Seattle, Washington. METHODS: Neighborhood disadvantage was measured using the National Neighborhood Data Archive disadvantage index. The index includes proportion of female-headed households with children, proportion of households with public assistance income, proportion of people with income below poverty in the past 12 months, and proportion of the civilian labor force aged 16 and older that are unemployed at the census tract level. Firearm injury counts included individuals with a documented assault-related gunshot wound identified from medical records and supplemented with the Gun Violence Archive between March 20, 2016 and December 31, 2018. Available addresses were geocoded to identify their point locations and then aggregated to the census tract level. Besag-York-Mollie (BYM2) Bayesian Poisson models were fit to the data to estimate the association between the index of neighborhood disadvantage and firearm injury count with a population offset within each census tract. RESULTS: Neighborhood disadvantage was significantly associated with the count of firearm injury in both non-spatial and spatial models. For two census tracts that differed by 1 decile of neighborhood disadvantage, the number of firearm injuries was higher by 21.0% (95% credible interval: 10.5, 32.8%) in the group with higher neighborhood disadvantage. After accounting for spatial structure, there was still considerable residual spatial dependence with 53.3% (95% credible interval: 17.0, 87.3%) of the model variance being spatial. Additionally, we observed census tracts with higher disadvantage and lower count of firearm injury in communities with proximity to employment opportunities and targeted redevelopment, suggesting other contextual protective factors. CONCLUSIONS: Even after adjusting for socioeconomic factors, firearm injury research should investigate spatial clustering as independence cannot be able to be assumed. Future research should continue to examine potential contextual and environmental neighborhood determinants that could impact firearm injuries in urban communities.
Authors: Miriam E Van Dyke; May S Chen; Michael Sheppard; J Danielle Sharpe; Lakshmi Radhakrishnan; Linda L Dahlberg; Thomas R Simon; Marissa L Zwald Journal: MMWR Morb Mortal Wkly Rep Date: 2022-07-08 Impact factor: 35.301
Authors: Iman N Afif; Ariana N Gobaud; Christopher N Morrison; Sara F Jacoby; Zoë Maher; Elizabeth D Dauer; Elinore J Kaufman; Thomas A Santora; Jeffrey H Anderson; Abhijit Pathak; Lars Ola Sjoholm; Amy J Goldberg; Jessica H Beard Journal: Prev Med Date: 2022-03-14 Impact factor: 4.637