Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-5 (of 5 Records) |
Query Trace: Wulz AR[original query] |
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Association between social vulnerability factors and unintentional fatal injury rates United States, 2015-2019
Wulz AR , Sharpe JD , Miller GF , Wolkin AF . J Saf Res 2023 Background: Differences in social and environmental factors can contribute to disparities in fatal injury rates. The purpose of this study was to examine the relationship between social and environmental factors and unintentional fatal injury across counties in the United States and how this relationship varies by geography. Methods: County-level vital statistics on age-adjusted unintentional fatal injury rates for 20152019 were linked with county-level data from the 2018 Social Vulnerability Index (SVI), a dataset identifying socially vulnerable communities. We conducted linear regression to examine the association between SVI and unintentional fatal injury, overall and by Census region/division. We mapped county-level data for SVI and unintentional fatal injury rates in bivariate choropleth maps using quartiles. Results: SVI was positively associated with unintentional fatal injury ( = 18.29, p < 0.001) across U.S. counties. The geographic distribution of SVI and unintentional fatal injury rates varied spatially and substantially for U.S. counties, with counties in the South and West regions having the greatest levels of SVI and rates of unintentional fatal injury. Conclusions: Our findings demonstrate that the social vulnerability of counties is associated with unintentional fatal injury rates. Modification of the SVI for injury research could include additional social determinants and exclude variables not applicable to injuries. A modified SVI could inform unintentional injury prevention strategies by prioritizing efforts in areas with high levels of social vulnerability. Practical Applications: This study is the first step in combining the SVI and injury mortality data to provide researchers with an index to investigate upstream factors related to injury. 2023 |
Association between social vulnerability factors and unintentional fatal injury rates – United States, 2015–2019
Wulz AR , Sharpe JD , Miller GF , Wolkin AF . J Safety Res 2023 86 245-252 Background: Differences in social and environmental factors can contribute to disparities in fatal injury rates. The purpose of this study was to examine the relationship between social and environmental factors and unintentional fatal injury across counties in the United States and how this relationship varies by geography. Methods: County-level vital statistics on age-adjusted unintentional fatal injury rates for 2015–2019 were linked with county-level data from the 2018 Social Vulnerability Index (SVI), a dataset identifying socially vulnerable communities. We conducted linear regression to examine the association between SVI and unintentional fatal injury, overall and by Census region/division. We mapped county-level data for SVI and unintentional fatal injury rates in bivariate choropleth maps using quartiles. Results: SVI was positively associated with unintentional fatal injury (β = 18.29, p < 0.001) across U.S. counties. The geographic distribution of SVI and unintentional fatal injury rates varied spatially and substantially for U.S. counties, with counties in the South and West regions having the greatest levels of SVI and rates of unintentional fatal injury. Conclusions: Our findings demonstrate that the social vulnerability of counties is associated with unintentional fatal injury rates. Modification of the SVI for injury research could include additional social determinants and exclude variables not applicable to injuries. A modified SVI could inform unintentional injury prevention strategies by prioritizing efforts in areas with high levels of social vulnerability. Practical Applications: This study is the first step in combining the SVI and injury mortality data to provide researchers with an index to investigate upstream factors related to injury. © 2023 |
Costs attributable to criminal justice involvement in injuries: a systematic review
Miller GF , Barnett SB , Wulz AR , Luo F , Florence C . Inj Prev 2022 CONTEXT: Costs related to criminal justice are an important component of the economic burden of injuries; such costs could include police involvement, judicial and corrections costs, among others. If the literature has sufficient information on the criminal justice costs related to injury, it could be added to existing estimates of the economic burden of injury. OBJECTIVE: To examine research on injury-related criminal justice costs, and what extent cost information is available by type of injury. DATA SOURCES: Medline, PsycINFO, Sociological Abstracts ProQuest, EconLit and National Criminal Justice Reference Service were searched from 1998 to 2021. DATA EXTRACTION: Preferred Reporting Items for Systematic reviews and Meta-Analyses was followed for data reporting. RESULTS: Overall, 29 studies reported criminal justice costs and the costs of crime vary considerably. CONCLUSIONS: This study illustrates possible touchpoints for cost inputs and outputs in the criminal justice pathway, providing a useful conceptualisation for better estimating criminal justice costs of injury in the future. However, better understanding of all criminal justice costs for injury-related crimes may provide justification for prevention efforts and potentially for groups who are disproportionately affected. Future research may focus on criminal justice cost estimates from injuries by demographics to better understand the impact these costs have on particular populations. |
Assessing female suicide from a health equity viewpoint, U.S. 2004-2018
Wulz AR , Miller GF , Kegler SR , Yard EE , Wolkin AF . Am J Prev Med 2022 63 (4) 486-495 INTRODUCTION: Geographic and urbanization differences in female suicide trends across the U.S. necessitates suicide prevention efforts on the basis of geographic variations. The purpose of this study was to assess female suicide rates by mechanism within Census divisions and by urbanicity to help inform geographically tailored approaches for suicide prevention strategies. METHODS: Data from 2004 to 2018 were obtained from the National Vital Statistics System (analyzed in 2021). Annual counts of female suicides were tabulated for firearm, suffocation, and drug poisoning and stratified by the U.S. Census division and urbanicity. Age-adjusted rates were calculated to describe female suicide incidence by geographic areas and urbanicity. Data were analyzed annually and by 5-year timeframes. Trends in annual female suicide rates by mechanism for 3 urbanization levels were identified using Joinpoint Regression. Annual percent change estimates were calculated for age-adjusted female suicide rates between 2004 and 2018. RESULTS: Female suicide rates by mechanism were not homogeneous within Census divisions or by urbanization levels. Suicide rates by mechanism across Census divisions within the same urbanization level varied (range=3.38-11.15 [per 100,000 person per year]). From 2014 to 2018 in large metropolitan areas in the northern divisions, rates for suffocation were higher than for firearms and drug poisoning. During the same period, in all urbanization levels in southern divisions, rates for firearms were higher than for suffocation and drug poisoning. CONCLUSIONS: Female suicide mechanisms vary by urbanization level, and this variation differs by region. These results could inform female suicide prevention strategies on the basis of mechanism, urbanization, and geographic region. |
Leveraging data science to enhance suicide prevention research: a literature review
Wulz AR , Law R , Wang J , Wolkin AF . Inj Prev 2021 28 (1) 74-80 OBJECTIVE: The purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science may be useful for future injury prevention research. DESIGN: We conducted a literature review of injury prevention and data science in April 2020 and January 2021 in three databases. METHODS: For the included 99 articles, we extracted the following: (1) author(s) and year; (2) title; (3) study approach (4) reason for applying data science method; (5) data science method type; (6) study description; (7) data source and (8) focus on a disproportionately affected population. RESULTS: Results showed the literature on data science and suicide more than doubled from 2019 to 2020, with articles with individual-level approaches more prevalent than population-level approaches. Most population-level articles applied data science methods to describe (n=10) outcomes, while most individual-level articles identified risk factors (n=27). Machine learning was the most common data science method applied in the studies (n=48). A wide array of data sources was used for suicide research, with most articles (n=45) using social media and web-based behaviour data. Eleven studies demonstrated the value of applying data science to suicide prevention literature for disproportionately affected groups. CONCLUSION: Data science techniques proved to be effective tools in describing suicidal thoughts or behaviour, identifying individual risk factors and predicting outcomes. Future research should focus on identifying how data science can be applied in other injury-related topics. |
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