BACKGROUND: Integrating and advancing health equity are a core tenant of the Centers for Disease Control and Prevention's mission. Comprehensive frameworks that clearly conceptualise equity are needed to prioritise and inform the advancement of health equity within public health. METHODS: To help meet this need, the investigative team developed The Continuum of Health Equity Practice & Science (The Continuum). The Continuum was developed in two phases: (1) an initial survey distributed to internal CDC Division of Injury Prevention investigators, and (2) a review of public health frameworks and the current health equity evidence base. RESULTS: The Continuum is a framework that includes seven key components of health equity and ultimately aims to guide public health practice and research towards the advancement of health equity. To illustrate its usefulness, we provide an example using adolescent suicide for each component of The Continuum and demonstrate how this may inform efforts to advance health equity. CONCLUSION: With a specific focus on conceptualising health equity and addressing systemic inequities, The Continuum may be used to inform efforts to advance equity in injury prevention and beyond.

Background: Differences in social and environmental factors contribute to disparities in fatal injury rates. This study assessed the relationship between social vulnerability and homicide and suicide rates across United States counties. Methods: County-level age-adjusted homicide and suicide rates for 2016–2020 were linked with data from the Centers for Disease Control and Prevention's 2020 Social Vulnerability Index (SVI), a dataset identifying socially vulnerable communities. We conducted negative binomial regressions to examine the association between SVI and homicide and suicide rates, overall and by Census region/division. We mapped county-level data for SVI and homicide and suicide rates in bivariate choropleth maps. Results: Overall SVI was associated with homicide rates across U.S. counties. While no association was found for overall SVI and suicide rates, Socioeconomic Status and Racial & Ethnic Minority Status domains were associated. The geographic distribution of SVI and homicide and suicide rates varied spatially; notably, counties in the South had the greatest levels of social vulnerability and greatest homicide rates. Conclusions: Our findings demonstrate county-level social vulnerability is associated with homicide rates but may be more nuanced for suicide rates. A modified SVI for injury should include additional social and structural determinants and exclude variables not applicable to injuries. Practical Applications: This study combines the SVI with homicide and suicide data, enabling researchers to examine related social and environmental factors. Modifying the SVI to include relevant predictors could improve injury prevention strategies by prioritizing efforts in areas with high social vulnerability. © 2024

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

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

During 2010-2019, U.S. correctional authorities held 1.4-1.6 million persons in state and federal prisons annually, and 10.3-12.9 million persons were admitted to local jails each year (1,2). Incarcerated persons experience a disproportionate burden of negative health outcomes, including unintentional and violence-related injuries (3,4). No national studies on injury-related emergency department (ED) visits by incarcerated persons have been conducted, but a previous study demonstrated a high rate of such visits among a Seattle, Washington jail population (5). To examine nonfatal injury-related ED visits among incarcerated adults, CDC analyzed 2010-2019 National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) data. During 2010-2019, an estimated 733,547 ED visits by incarcerated adults occurred in the United States. The proportion of ED visits resulting from assault* and self-harm among incarcerated adults was five times as high as those among nonincarcerated adults. Among incarcerated adults, men and adult persons aged <65 years had the highest proportion of assault-related ED visits. Falls accounted for the most ED visits among incarcerated adults aged ≥65 years. A higher proportion of ED visits by incarcerated women than incarcerated men were for overdose or poisoning. These findings suggest that injuries among incarcerated adults differ from those among nonincarcerated adults and might require development and implementation of age- and sex-specific prevention strategies for this population.

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.

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.

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.