Social determinants of health and associated systems, policies and practices are important drivers of health disparities. American Indian and Alaska Native (AI/AN) populations in the United States have elevated incidence rates of stomach, liver, and colorectal cancers compared to other racial groups. This study examined incidence rates of three gastrointestinal cancers among non-Hispanic AI/AN (NH-AI/AN) and non-Hispanic White (NHW) populations by geographic region and social vulnerability index (SVI) score. Incident cases diagnosed during 2010-2019 were identified from population-based cancer registries linked with the Indian Health Service patient registration databases. Age-adjusted incidence rates (per 100,000) for stomach, liver, and colorectal cancers were compared within NH-AI/AN and between NH-AI/AN and NHW populations by SVI score. Rates were higher among NH-AI/AN populations in moderate and high SVI score counties in Alaska, the Southern Plains, and the East compared with low SVI counties. Incidence rates among NH-AI/AN were elevated when compared to NHW populations by SVI category. Results indicated that higher social vulnerability may drive elevated cancer incidence among NH-AI/AN populations. Additionally, disparities between NH-AI/AN and NHW populations persist even when accounting for SVI. Exploring social vulnerability can aid in designing more effective interventions to address root causes of cancer disparities among AI/AN populations.

INTRODUCTION: Quantifying disparities in social determinants of health between people with HIV and the total population could help address health inequities, and ensure health and well-being among people with HIV in the U.S., but estimates are lacking. METHODS: Several representative data sources were used to assess differences in social determinants of health between adults with diagnosed HIV (Centers for Disease Control and Prevention Medical Monitoring Project) and the total adult population (U.S. Census Bureau's decennial census, American Community Survey, Household Pulse Survey, the Current Population Survey Annual Social and Economic Supplements; the Department of Housing and Urban Development's point-in-time estimates of homelessness; and the Bureau of Justice Statistics). The differences were quantified using standardized prevalence differences and standardized prevalence ratios, adjusting for differences in age, race/ethnicity, and birth sex between people with HIV and the total U.S. population. RESULTS: Overall, 35.6% of people with HIV were living in a household with an income at or below the federal poverty level, and 8.1% recently experienced homelessness. Additionally, 42.9% had Medicaid and 27.6% had Medicare; 39.7% were living with a disability. Over half (52.3%) lived in large central metropolitan counties and 20.6% spoke English less than very well based on survey responses. After adjustment, poverty (standardized prevalence difference=25.1%, standardized prevalence ratio=3.5), homelessness (standardized prevalence difference=8.5%, standardized prevalence ratio=43.5), coverage through Medicaid (standardized prevalence difference=29.5%, standardized prevalence ratio=3.0) or Medicare (standardized prevalence difference=7.8%), and disability (standardized prevalence difference=30.3%, standardized prevalence ratio=3.0) were higher among people with HIV than the total U.S. population. The percentage of people with HIV living in large central metropolitan counties (standardized prevalence difference=13.4%) or who were recently incarcerated (standardized prevalence ratio=5.9) was higher than the total U.S. population. CONCLUSIONS: These findings provide a baseline for assessing national-level disparities in social determinants of health between people with HIV and the total U.S. population, and it can be used as a model to assess local disparities. Addressing social determinants of health is essential for achieving health equity, requiring a multipronged approach with interventions at the provider, facility, and policy levels.

The extent to which the 2022 mpox outbreak has affected persons without a recent history of male-to-male sexual contact (MMSC) is not well understood. During November 1-December 14, 2022, CDC partnered with six jurisdictional health departments to characterize possible exposures among mpox patients aged ≥18 years who did not report MMSC during the 3 weeks preceding symptom onset. Among 52 patients included in the analysis, 14 (27%) had a known exposure to a person with mpox, including sexual activity and other close intimate contact (eight) and household contact (six). Among 38 (73%) patients with no known exposure to a person with mpox, self-reported activities before illness onset included sexual activity and other close intimate contact (17; 45%), close face-to-face contact (14; 37%), attending large social gatherings (11; 29%), and being in occupational settings involving close skin-to-skin contact (10; 26%). These findings suggest that sexual activity remains an important route of mpox exposure among patients who do not report MMSC.

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

Monkeypox (mpox) cases in the 2022 outbreak have primarily occurred among adult gay, bisexual, and other men who have sex with men (MSM); however, other populations have also been affected (1). To date, data on mpox in cisgender women and pregnant persons have been limited. Understanding transmission in these populations is critical for mpox prevention. In addition, among pregnant persons, Monkeypox virus can be transmitted to the fetus during pregnancy or to the neonate through close contact during or after birth (2-5). Adverse pregnancy outcomes, including spontaneous abortion and stillbirth, have been reported in previous mpox outbreaks (3). During May 11-November 7, 2022, CDC and U.S. jurisdictional health departments identified mpox in 769 cisgender women aged ≥15 years, representing 2.7% of all reported mpox cases.(†) Among cases with available data, 44% occurred in cisgender women who were non-Hispanic Black or African American (Black), 25% who were non-Hispanic White (White), and 23% who were Hispanic or Latino (Hispanic). Among cisgender women with available data, 73% reported sexual activity or close intimate contact as the likely route of exposure, with mpox lesions most frequently reported on the legs, arms, and genitals. Twenty-three mpox cases were reported in persons who were pregnant or recently pregnant(§); all identified as cisgender women based on the mpox case report form.(¶) Four pregnant persons required hospitalization for mpox. Eleven pregnant persons received tecovirimat, and no adverse reactions were reported. Continued studies on mpox transmission risks in populations less commonly affected during the outbreak, including cisgender women and pregnant persons, are important to assess and understand the impact of mpox on sexual, reproductive, and overall health.

OBJECTIVE: State-issued behavioral policy interventions (BPIs) can limit community spread of COVID-19, but their effects on COVID-19 transmission may vary by level of social vulnerability in the community. We examined the association between the duration of BPIs and the incidence of COVID-19 across levels of social vulnerability in US counties. METHODS: We used COVID-19 case counts from USAFacts and policy data on BPIs (face mask mandates, stay-at-home orders, gathering bans) in place from April through December 2020 and the 2018 Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention. We conducted multilevel linear regression to estimate the associations between duration of each BPI and monthly incidence of COVID-19 (cases per 100000 population) by SVI quartiles (grouped as low, moderate low, moderate high, and high social vulnerability) for 3141 US counties. RESULTS: Having a BPI in place for longer durations (ie, 2 months) was associated with lower incidence of COVID-19 compared with having a BPI in place for <1 month. Compared with having no BPI in place or a BPI in place for <1 month, differences in marginal mean monthly incidence of COVID-19 per 100000 population for a BPI in place for 2 months ranged from -4 cases in counties with low SVI to -401 cases in counties with high SVI for face mask mandates, from -31 cases in counties with low SVI to -208 cases in counties with high SVI for stay-at-home orders, and from -227 cases in counties with low SVI to -628 cases in counties with high SVI for gathering bans. CONCLUSIONS: Establishing COVID-19 prevention measures for longer durations may help reduce COVID-19 transmission, especially in communities with high levels of social vulnerability.

In April 2010, a fatal explosion on the Deepwater Horizon drilling rig in the Gulf of Mexico resulted in the largest marine oil spill in history. This research describes the association of oil exposure with anxiety after the Deepwater Horizon Oil Spill and evaluates effect modification by self-mastery, emotional support and cleanup participation. To assess the impacts of the Deepwater Horizon Oil Spill, the Centers for Disease Control and Prevention (CDC) conducted the Gulf States Population Survey (GSPS), a random-digit-dial telephone cross-sectional survey completed between December 2010 and December 2011 with 38,361 responses in four different Gulf Coast states: Louisiana, Florida, Alabama and Mississippi. Anxiety severity was measured using the Generalised Anxiety Disorder (GAD) symptom inventory. We used Tobit regression to model underlying anxiety as a function of oil exposure and hypothesised effect modifiers, adjusting for socio-demographics. Latent anxiety was higher among those with direct contact with oil than among those who did not have direct contact with oil in confounder-adjusted models [ = 2.84, 95% confidence interval (CI): 0.78, 4.91]. Among individuals with direct contact with oil, there was no significant interaction between participating in cleanup activities and emotional support for anxiety (p = 0.20). However, among those with direct contact with oil, in confounder-adjusted models, participation in oil spill cleanup activities was associated with lower latent anxiety ( = -3.55, 95% CI: -6.15, -0.95). Oil contact was associated with greater anxiety, but this association appeared to be mitigated by cleanup participation.

At least 100,000 persons in the United States experience a fatal or nonfatal firearm injury each year.* CDC examined rates of firearm injury emergency department (ED) visits by community social vulnerability using data from CDC's Firearm Injury Surveillance Through Emergency Rooms (FASTER) program.() ED visit data, shared with CDC's National Syndromic Surveillance Program (NSSP)() during 2018-2021, were analyzed for 647 counties in 10 FASTER-funded jurisdictions.() County-level social vulnerability data were obtained from the 2018 Social Vulnerability Index (SVI).** Rates of ED visits for firearm injuries (number of firearm injury ED visits per 100,000 ED visits) were calculated across tertile levels of social vulnerability. Negative binomial regression models were used to estimate rate ratios (RRs) and associated 95% CIs comparing rates of ED visits across social vulnerability levels. During 2018-2021, compared with rates in counties with low overall social vulnerability, the firearm injury ED visit rate was 1.34 times as high in counties with medium social vulnerability and 1.80 times as high in counties with high social vulnerability. Similar patterns were observed for the SVI themes of socioeconomic status and housing type and transportation, but not for the themes of household composition and disability status or racial and ethnic minority status and language proficiency. More timely data() on firearm injury ED visits by social vulnerability can help identify communities disproportionately experiencing elevated firearm injury rates. States and communities can use the best available evidence to implement comprehensive prevention strategies that address inequities in the social and structural conditions that contribute to risk for violence, including creating protective community environments, strengthening economic supports, and intervening to reduce harms and prevent future risk (e.g., with hospital-based violence intervention programs) (1,2).

The Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) is a census-based metric that includes 15 socioeconomic and demographic factors split into four themes relevant to disaster planning, response, and recovery. Using CDC/ATSDR SVI, health outcomes, and remote sensing data, we sought to understand the differences in the occurrence of overall and cause-specific emergency department (ED) visits before and after a 2017 flood event in Texas following Hurricane Harvey, modified by different levels of social vulnerability. We used a controlled before-after study design to estimate the association between flooding and overall and cause-specific ED visits after adjusting for the baseline period, seasonal trends, and individual-level characteristics. We estimated rate ratios stratified by CDC/ATSDR SVI quartiles (overall and 4 themes separately) and tested for the presence of effect modification. Positive effect modification was found such that total ED visits from flooded census tracts with moderate, high, and very high levels of social vulnerability were less reduced compared to tracts with the least vulnerability during flooding and the month following the flood event. The CDC/ATSDR SVI socioeconomic status theme, household composition and disability theme, and housing and transportation type theme explained this result. We found predominantly negative effect modification with higher ED visits among tracts with the least vulnerability for ED visits related to insect bites, dehydration, and intestinal infectious diseases. © 2022

OBJECTIVES: The adverse effects that racial and ethnic minority groups experience before, during, and after disaster events are of public health concern. The objective of this study was to examine disparities in the epidemiologic and geographic patterns of natural disaster and extreme weather mortality by race and ethnicity. METHODS: We used mortality data from the Centers for Disease Control and Prevention from January 1, 1999, through December 31, 2018. We defined natural disaster and extreme weather mortality based on International Classification of Diseases, 10th Revision codes X30-X39. We calculated age-adjusted mortality rates by race, ethnicity, and hazard type, and we calculated age-adjusted mortality rate ratios by race, ethnicity, and state. We used geographic mapping to examine age-adjusted mortality rate ratios by race, ethnicity, and state. RESULTS: Natural disasters and extreme weather caused 27 335 deaths in the United States during 1999-2018. Although non-Hispanic White people represented 68% of total natural disaster and extreme weather mortality, the mortality rate per 100 000 population among non-Hispanic Black people was 1.87 times higher (0.71) and among non-Hispanic American Indian/Alaska Native people was 7.34 times higher (2.79) than among non-Hispanic White people (0.38). For all racial and ethnic groups, exposure to extreme heat and cold were the 2 greatest causes of natural disaster and extreme weather mortality. Racial and ethnic disparities in natural disaster and extreme weather mortality were highest in the South, Southwest, Mountain West, and Upper Midwest. CONCLUSIONS: Racial and ethnic minority populations have a greater likelihood of mortality from natural disaster or extreme weather events than non-Hispanic White people. Our study strengthens the current knowledge base on these disparities and may inform and improve disaster preparedness and response efforts.

PURPOSE: Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. METHODS: Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7 to April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index. RESULTS: Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. CONCLUSIONS: Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and responses to future outbreaks.

OBJECTIVES: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. METHODS: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. RESULTS: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. CONCLUSION: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

Disparities in vaccination coverage by social vulnerability, defined as social and structural factors associated with adverse health outcomes, were noted during the first 2.5 months of the U.S. COVID-19 vaccination campaign, which began during mid-December 2020 (1). As vaccine eligibility and availability continue to expand, assuring equitable coverage for disproportionately affected communities remains a priority. CDC examined COVID-19 vaccine administration and 2018 CDC social vulnerability index (SVI) data to ascertain whether inequities in COVID-19 vaccination coverage with respect to county-level SVI have persisted, overall and by urbanicity. Vaccination coverage was defined as the number of persons aged ≥18 years (adults) who had received ≥1 dose of any Food and Drug Administration (FDA)-authorized COVID-19 vaccine divided by the total adult population in a specified SVI category.(†) SVI was examined overall and by its four themes (socioeconomic status, household composition and disability, racial/ethnic minority status and language, and housing type and transportation). Counties were categorized into SVI quartiles, in which quartile 1 (Q1) represented the lowest level of vulnerability and quartile 4 (Q4), the highest. Trends in vaccination coverage were assessed by SVI quartile and urbanicity, which was categorized as large central metropolitan, large fringe metropolitan (areas surrounding large cities, e.g., suburban), medium and small metropolitan, and nonmetropolitan counties.(§) During December 14, 2020-May 1, 2021, disparities in vaccination coverage by SVI increased, especially in large fringe metropolitan (e.g., suburban) and nonmetropolitan counties. By May 1, 2021, vaccination coverage was lower among adults living in counties with the highest overall SVI; differences were most pronounced in large fringe metropolitan (Q4 coverage = 45.0% versus Q1 coverage = 61.7%) and nonmetropolitan (Q4 = 40.6% versus Q1 = 52.9%) counties. Vaccination coverage disparities were largest for two SVI themes: socioeconomic status (Q4 = 44.3% versus Q1 = 61.0%) and household composition and disability (Q4 = 42.0% versus Q1 = 60.1%). Outreach efforts, including expanding public health messaging tailored to local populations and increasing vaccination access, could help increase vaccination coverage in high-SVI counties.

The U.S. COVID-19 vaccination program began in December 2020, and ensuring equitable COVID-19 vaccine access remains a national priority.* COVID-19 has disproportionately affected racial/ethnic minority groups and those who are economically and socially disadvantaged (1,2). Thus, achieving not just vaccine equality (i.e., similar allocation of vaccine supply proportional to its population across jurisdictions) but equity (i.e., preferential access and administra-tion to those who have been most affected by COVID-19 disease) is an important goal. The CDC social vulnerability index (SVI) uses 15 indicators grouped into four themes that comprise an overall SVI measure, resulting in 20 metrics, each of which has national and state-specific county rankings. The 20 metric-specific rankings were each divided into lowest to highest tertiles to categorize counties as low, moderate, or high social vulnerability counties. These tertiles were combined with vaccine administration data for 49,264,338 U.S. residents in 49 states and the District of Columbia (DC) who received at least one COVID-19 vaccine dose during December 14, 2020-March 1, 2021. Nationally, for the overall SVI measure, vaccination coverage was higher (15.8%) in low social vulnerability counties than in high social vulnerability counties (13.9%), with the largest coverage disparity in the socioeconomic status theme (2.5 percentage points higher coverage in low than in high vulnerability counties). Wide state variations in equity across SVI metrics were found. Whereas in the majority of states, vaccination coverage was higher in low vulnerability counties, some states had equitable coverage at the county level. CDC, state, and local jurisdictions should continue to monitor vaccination coverage by SVI metrics to focus public health interventions to achieve equitable coverage with COVID-19 vaccine.

OBJECTIVES: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. METHODS: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. RESULTS: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. CONCLUSIONS: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.

Prior studies of oil spills have reported adverse impacts on mental health, but have not examined some potentially important moderators. In this cross-sectional analysis of n = 38,361 responses to the 2010-2011 Gulf States Population Survey, we assessed the association of direct oil contact with depression severity following the Deepwater Horizon oil spill, and modification by self-mastery, emotional support, and cleanup participation using Tobit regression models accounting for the complex survey design. Oil contact was associated with increased depression severity. Among respondents with oil contact, depression was more severe for those reporting lower self-mastery. However, respondents with oil contact had lower depression severity if they participated in cleanup efforts, compared to exposed individuals who did not participate. This potential protective effect was larger for respondents with lower self-mastery. Our results are consistent with the notion that participation in recovery efforts may reduce depressive symptoms following oil spills among impacted individuals.

BACKGROUND: On April 20, 2010, the Deepwater Horizon oil rig exploded, spilling over 4.9 million barrels of oil in the Gulf of Mexico over an 87-day period and developing into a long-term environmental disaster that affected people living in Gulf Coast states. Engagement of community members in recovery efforts is important for mitigating adverse effects of disasters and accelerating the rebuilding process for impacted communities; however, few studies have explored factors that determine participation in oil spill cleanups. METHODS: We analyzed data from the Gulf States Population Survey (GSPS) to study the determinants of participating in the Deepwater Horizon Oil Spill cleanup. The GSPS was a random-digit dialing survey conducted on 38,361 adults in counties and parishes in Alabama, Florida, Louisiana, and Mississippi impacted by the oil spill. Using survey estimation to account for the complex survey design, we estimated the probability of cleanup participation and used logistic regression to examine the association between sociodemographic factors and cleanup participation. RESULTS: Approximately 4.7% of residents in affected Gulf communities participated in the cleanup. Most participants were young, men, non-Hispanic white, and employed. Living in an affected coastal county was associated with higher odds of participation (unadjusted odds ratio [OR]: 1.69; 95% confidence interval [CI]: 1.28-2.24), as was having excellent or very good physical health (OR: 2.05; 95% CI: 1.11-3.81). Older persons were less likely to participate in the cleanup (OR for 65+ age group vs. 18-24 age group: 0.14; 95% CI: 0.05-0.36). CONCLUSIONS: Understanding the demographics of cleanup participants may help inform civilian recruitment for future oil spill responses.