County Demographics Research Articles

Food Surrogates? County-Level Association Between Vegetable Production and Food Insecurity in the Rural South

ABSTRACT This study examines food insecurity in rural Georgia counties. Out of 159 counties in Georgia, 108 met the criterion of over 50% rurality. Despite their central role in U.S. food production, some counties face significant food security issues. We explored the link between food insecurity and harvested vegetable acreage, using regression analysis with county demographics. Results showed no significant correlation between vegetable acreage and food insecurity. We described these areas as possible “food surrogates” and found that factors like food access and poverty were correlated with food insecurity. Further research is needed to understand the challenges of “food surrogate” communities.

Prevalence of Depressive Symptoms in a Predominantly Hispanic/Latinx South Texas Community in the Aftermath of the COVID-19 Pandemic.

COVID-19 has a lasting impact on mental health, particularly within the Hispanic/Latinx communities. This paper empirically investigates the post-COVID-19 presence and severities of depression, one of the most common mental health disorders, among adults in a predominantly U.S.-born Hispanic/Latinx community in South Texas composed primarily of Mexican Americans. Multiple statistic regression models were applied to data from 515 adults in Nueces County who completed all questions in a survey from convenience sampling between June 2022 and May 2023. Depression was assessed using both standard PHQ-2 and PHQ-9 measurements. Of the 515 participants, 377 (64.5%) were Hispanic, and 441 (85.6%) had a high school education or higher, reflecting the county's demographics. About half of the participants (47%) reported mild/moderate to severe depression. The regression model estimation results reveal that female participants, those not in full-time employment, and individuals with disabilities were more likely to feel depressed after COVID-19. Middle-aged adults demonstrated greater resilience to depression compared to other age groups. Notably, non-Hispanic participants in the study reported higher levels of depression compared to their Hispanic counterparts. Additionally, COVID-19-related experiences, such as testing positive for the virus, being hospitalized, or having a history of depression before COVID-19, were associated with higher levels of reported depression. COVID-19 has significantly impacted the mental health of this predominantly U.S.-born Hispanic/Latinx community. These findings can assist healthcare providers and policymakers in developing targeted strategies to tailor interventions aimed at enhancing mental health well-being, reducing disparities, and fostering overall improvement within the Hispanic/Latinx community.

Tobacco retailer density and its association with birth outcomes in the USA: 2000–2016

IntroductionSignificant progress has been made in reducing maternal exposure to tobacco smoke and subsequent adverse birth outcomes, however, reductions may require strategies that reduce the availability of tobacco retailers. In...

Assessing the quality of public services: For-profits, chains, and concentration in the hospital market.

We examine variation in US hospital quality across ownership, chain membership, and market concentration. We propose a new measure of quality derived from penalties imposed on hospitals under the flagship Hospital Readmissions Reduction Program, and use regression models to risk-adjust for hospital characteristics and county demographics. While the overall association between for-profit ownership and quality is negative, there is evidence of substantial heterogeneity. The quality of for-profit relative to non-profit hospitals declines with increasing market concentration. Moreover, the quality gap is primarily driven by for-profit chains. While the competition result mirrors earlier findings in the literature, the chain result appears to be new: it suggests that any potential quality gains afforded by chains are mostly realized by not-for-profit hospitals.

An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010

Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors—counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.

Evaluation of a pilot implementation of a digital cognitive behavioral therapy platform for isolated older adults in county mental health services.

Technology-enabled services (TESs) have the potential to increase access to mental healthcare. However, little research has focused on how TESs can be integrated into publicly funded service settings. As part of the state-wide Help@Hand project, Marin County conducted a pilot implementation of myStrength, a digital cognitive behavioral therapy platform, to explore its potential to reduce loneliness among isolated older adults. We evaluated the pilot impact using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. A single-site 6-month pilot implementation recruited English (n = 15) and Spanish-speaking (n = 15) isolated older adults who received a digital literacy course followed by 8 weeks of myStrength access and human support. We evaluated factors related to reach, effectiveness, adoption, and implementation using the perspectives of users and County staff. Descriptive statistics were used to examine reach, adoption, and implementation. Nonparametric tests, including Friedman and Wilcoxon signed-rank, were used to examine effectiveness. Reach: Compared to overall county demographics, platform users were majority female (93.1% vs. 50.5%), ethnoracialized (62.1% vs. 24.2%), and of lower socioeconomic status (Mdn = $35,000 vs. $131,008). Effectiveness: Users reported a significant (z = -2.62, p < .001) decrease in loneliness. Adoption: Users logged into myStrength an average of 10 times and completed 33 activities during the 8 weeks of myStrength use. Implementation: Each pilot staff (N = 20) spent an average of 19.8 hr (SD = 16.51) supporting users' use of myStrength during the pilot. Pilot staff reported several adaptations to meet the needs of users. Successes included reaching the target population, reducing loneliness, and user adoption. However, pilot staff invested significant time to support those with lower digital literacy skills. As such, although TESs may address unmet needs, their use with underserved populations may require upfront and ongoing support provided by the settings where they are implemented. Testing a New Digital Therapy Tool for Isolated Older Adults in County Mental Health Services.

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study.

Health care data breaches are the most rapidly increasing type of cybercrime; however, the predictors of health care data breaches are uncertain. This quantitative study aims to develop a predictive model to explain the number of hospital data breaches at the county level. This study evaluated data consolidated at the county level from 1032 short-term acute care hospitals. We considered the association between data breach occurrence (a dichotomous variable), predictors based on county demographics, and socioeconomics, average hospital workload, facility type, and average performance on several hospital financial metrics using 3 model types: logistic regression, perceptron, and support vector machine. The model coefficient performance metrics indicated convergent validity across the 3 model types for all variables except bad debt and the factor level accounting for counties with >20% and up to 40% Hispanic populations, both of which had mixed coefficient directionality. The support vector machine model performed the classification task best based on all metrics (accuracy, precision, recall, F1-score). All the 3 models performed the classification task well with directional congruence of weights. From the logistic regression model, the top 5 odds ratios (indicating a higher risk of breach) included inpatient workload, medical center status, pediatric trauma center status, accounts receivable, and the number of outpatient visits, in high to low order. The bottom 5 odds ratios (indicating the lowest odds of experiencing a data breach) occurred for counties with Black populations of >20% and <40%, >80% and <100%, and >40% but <60%, as well as counties with ≤20% Asian or between 80% and 100% Hispanic individuals. Our results are in line with those of other studies that determined that patient workload, facility type, and financial outcomes were associated with the likelihood of health care data breach occurrence. The results of this study provide a predictive model for health care data breaches that may guide health care managers to reduce the risk of data breaches by raising awareness of the risk factors.

Socioeconomic Disparities Associated with Access to Oculofacial Plastic Surgeons: A Cross-Sectional Analysis of US County Demographics

To compare population demographics with the geographic distribution of oculofacial plastic surgeons (OPS) in the United States (US). A cross-sectional study design was employed to investigate demographic differences between counties with one or more OPS and counties with zero OPS. The number of OPS were identified in each US County using online public databases - American Society of Ophthalmic Plastic and Reconstructive Surgeons; American Academy of Ophthalmology. Counties were categorized into two groups: one or more OPS and zero OPS. Demographic characteristics at the county level were obtained from the 2021 US Census Bureau Population Estimates and the American Community Survey. Cost of living was collected from the 2022 Economic Policy Institute Family Budget Calculator. Socioeconomic demographics of the US population as related to geographic OPS distribution. A total of 1238 OPS were identified. States with the most OPS per million were Hawaii (6.2), D.C. (6.0), Connecticut (5.8), Utah (5.1), and Maryland (5.0). Among 3143 counties, 2725 (86.7%) had zero OPS and 418 (13.3%) had one or more OPS. Counties with one or more OPS had a higher median (SD) household income versus counties with zero OPS ($72,969 [$19,724] vs. ($56,361 [$13,857]; difference $16,608; 95% CI, $14,489 to $18,727; P < 0.001). The annual cost of living per person (SD) was higher in counties with one or more OPS versus counties with zero OPS ($39,238 [$6,992] vs. $36,227 [$3,516]; difference $3,011; 95% CI $2,328 to $3,694; P < 0.001). Counties with zero OPS versus counties with one or more OPS had higher proportions of persons with only Medicaid (15.5% vs. 13.7%; difference 1.8%; 95% CI, 1.2% to 2.4%; P < 0.001), no health insurance (9.9% vs. 8.0%; difference 1.9%; 95% CI, 1.4% to 2.3%; P < 0.001), no household internet access (17.0% vs. 9.3%; difference 7.7%; 95% CI, 7.2% to 8.2%; P < 0.001), and higher proportions of persons 65 years or older (20.0% vs. 16.6%; difference 3.4%; 95% CI, 2.9% to 3.8%; P < 0.001). This cross-sectional analysis of all US counties revealed socioeconomic disparities associated with access to OPS.

Toxicology Test Results for Public Health Surveillance of the Opioid Epidemic: Retrospective Analysis.

Addressing the opioid epidemic requires timely insights into population-level factors, such as trends in prevalence of legal and illegal substances, overdoses, and deaths. This study aimed to examine whether toxicology test results of living individuals from a variety of sources could be useful in surveilling the opioid epidemic. A retrospective analysis standardized, merged, and linked toxicology results from 24 laboratories in Marion County, Indiana, United States, from September 1, 2018, to August 31, 2019. The data set consisted of 33,787 Marion County residents and their 746,681 results. We related the data to general Marion County demographics and compared alerts generated by toxicology results to opioid overdose-related emergency department visits. Nineteen domain experts helped prototype analytical visualizations. Main outcome measures included test positivity in the county and by ZIP code; selected demographics of individuals with toxicology results; and correlation of toxicology results with opioid overdose-related emergency department visits. Four percent of Marion County residents had at least 1 toxicology result. Test positivity rates ranged from 3% to 19% across ZIP codes. Males were underrepresented in the data set. Age distribution resembled that of Marion County. Alerts for opioid toxicology results were not correlated with opioid overdose-related emergency department visits. Analyzing toxicology results at scale was impeded by varying data formats, completeness, and representativeness; changes in data feeds; and patient matching difficulties. In this study, toxicology results did not predict spikes in opioid overdoses. Larger, more rigorous and well-controlled studies are needed to assess the utility of toxicology tests in predicting opioid overdose spikes.

Time, Money, or Knowledge: What factors are associated with implementing youth cooking programs?

Research suggests participating in youth hands-on cooking programs, like those offered by Extension and 4-H, can improve nutrition behaviors and reduce the risk for obesity. We surveyed [STATE] Extension professionals (n = 127) to explore factors (e.g., employee characteristics, resources, county demographics) related to offering youth hands-on cooking programs and curricula used. Over 2/3 of participants offer programs and reported creating their own curriculum. More years of experience, having received Extension Specialist training, and increased confidence were positively related to offering these programs. Results suggest training could increase confidence and program implementation and standard curricula may be needed.

Data-driven strategies for increasing patient diversity in Bristol Myers Squibb-sponsored US oncology clinical trials.

Determining whether clinical trial findings are applicable to diverse, real-world patient populations can be challenging when the full demographic characteristics of enrolled patients are not consistently reported. Here, we present the results of a descriptive analysis of racial and ethnic demographic information for patients in Bristol Myers Squibb (BMS)-sponsored oncology trials in the United States (US) and describe factors associated with increased patient diversity. BMS-sponsored oncology trials conducted at US sites with study enrollment dates between 1 January 2013 and 31 May 2021 were analyzed. Patient race/ethnicity information was self-reported in case report forms. As principal investigators (PIs) did not report their own race/ethnicity, a deep-learning algorithm (ethnicolr) was used to predict PI race/ethnicity. Trial sites were linked to counties to understand the role of county-level demographics. The impact of working with patient advocacy and community-based organizations to increase diversity in prostate cancer trials was analyzed. The magnitude of associations between patient diversity and PI diversity, US county demographics, and recruitment interventions in prostate cancer trials were assessed by bootstrapping. A total of 108 trials for solid tumors were analyzed, including 15,763 patients with race/ethnicity information and 834 unique PIs. Of the 15,763 patients, 13,968 (89%) self-reported as White, 956 (6%) Black, 466 (3%) Asian, and 373 (2%) Hispanic. Among 834 PIs, 607 (73%) were predicted to be White, 17 (2%) Black, 161 (19%) Asian, and 49 (6%) Hispanic. A positive concordance was observed between Hispanic patients and PIs (mean = 5.9%; 95% confidence interval (CI) = 2.4, 8.9), a less positive concordance between Black patients and PIs (mean = 1.0%; 95% CI = -2.7, 5.5), and no concordance between Asian patients and PIs. Geographic analyses showed that more non-White patients enrolled in study sites in counties with higher proportions of non-White residents (e.g. a county population that was 5%-30% Black had 7%-14% more Black patients enrolled in study sites). Following purposeful recruitment efforts in prostate cancer trials, 11% (95% CI = 7.7, 15.3) more Black men enrolled in prostate cancer trials. Most patients in these clinical trials were White. PI diversity, geographic diversity, and recruitment efforts were related to greater patient diversity. This report constitutes an essential step in benchmarking patient diversity in BMS US oncology trials and enables BMS to understand which initiatives may increase patient diversity. While complete reporting of patient characteristics such as race/ethnicity is critical, identifying diversity improvement tactics with the highest impact is essential. Strategies with the greatest concordance to clinical trial patient diversity should be implemented to make meaningful improvements to the diversity of clinical trial populations.

1788. COVID-19 and Antibiotic Prescriptions in the United States: A County-level Analysis

Abstract Background Declines in outpatient antibiotic prescribing were reported during the beginning of the COVID-19 pandemic in the United States; however, the overall impact of COVID-19 cases on antibiotic prescribing remains unclear. Methods We conducted an observational, ecological study to assess the impact of COVID-19 cases and pandemic-related, non-pharmaceutical interventions (NPIs) (e.g., school closures and facemasks) on antibiotic prescribing from February to December 2020 in the US. A random effects panel regression of county-level monthly reported COVID-19 case data and corresponding systemic antibiotic prescription data from IQVIA was used. The model controlled for county demographics, NPIs, and prior years’ prescribing. Results Total antibiotic prescriptions fell 26.1% between March and December 2020 compared to this period from 2017 to 2019. Prescribing rates dropped most among children (Figure 1). A 1% increase in county-level monthly COVID-19 cases was associated with a 0.9% increase (95% CI 0.7%, 1.1%; p&amp;lt; 0.01) in monthly prescriptions dispensed to adults and a 1.2% decrease (95% CI -1.7%, -0.8%; p&amp;lt; 0.01) in prescriptions dispensed to children (Table 1). Counties with schools open for in-person instruction were associated with a 4.4% increase (95% CI 2.3%, 6.4%; p&amp;lt; 0.01) in prescriptions among children compared to counties that closed schools. Internal movement restrictions and requiring facemasks were also associated with lower prescribing among children. Figure 1A) Total prescriptions per 100,000 population by month (2017-2020). B) Mean prescriptions per 100,000 population for seven age groups (2017-2019 vs 2020).Table 1 Conclusion Though the number of antibiotic prescriptions in 2020 was lower than previous years, the positive association of COVID-19 cases with prescribing for adults and the negative association for children indicates increases in prescribing occurred primarily among adults. The rarity of bacterial co-infection in COVID-19 patients suggests a large fraction of these prescriptions may have been inappropriate. Facemasks and school closures were correlated with reductions in prescribing among children, likely due to the prevention of other upper respiratory infections (e.g., the cold and influenza). Despite reductions, the strongest predictors of prescribing were prior years’ prescribing trends, suggesting the possibility that behavioral norms are an important driver of prescribing practices. Disclosures Sara E. Cosgrove, MD, Basilea: Member of Infection Adjudication Committee Ramanan Laxminarayan, PhD, HealthCubed: Board Member|HealthCubed: Ownership Interest.

168. A comparative analysis of racial disparities in nationally derived hospital data and two prospective multicenter surgical databases of adult spinal deformity surgery

<h3>BACKGROUND CONTEXT</h3> While past research has shown racial disparities exist in the outcomes and utilization of spine surgery, those studies were often performed on nondisease-specific national databases, which may capture different patient populations and complication rates compared to prospective multicenter databases. <h3>PURPOSE</h3> Purpose: 1) Assess racial disparities for enrollment in two prospective multicenter databases (ASD-DB1 and ASD-DB2). 2) Assess racial disparities in demographics, outcomes, in three databases: ASD-DB1, ASD-DB2, and the National Surgical Quality Improvement Program (NSQIP). We hypothesize that race will not affect enrollment in prospective multicenter studies. Disparities in national databases will be different than those in prospective databases. <h3>STUDY DESIGN/SETTING</h3> Retrospective review. <h3>PATIENT SAMPLE</h3> ASD patients in ASD-DB1, ASD-DB2, and NSQIP. <h3>OUTCOME MEASURES</h3> Preoperative demographic and clinical characteristics, intraoperative surgical techniques utilized, postoperative complications, correction, and change in HRQOLs. <h3>METHODS</h3> ASD-DB1 (2-year follow-up) included ASD patients from 2008-2019. ASD-DB2 (6-week follow-up) included ASD patients from 2019-2021. NSQIP (30-day follow-up) included ASD patients from 2012-2018. Racial disparities were assessed in African Americans (AA), Asians (AN) and Hispanics (H), compared to Caucasians (CA). Enrollment racial disparities were evaluated in ASD-DB1 and ASD-DB2. <h3>RESULTS</h3> ASD-DB1: 1,356 patients. Compared to CA, AA and H were younger, AA had higher max Cobb and higher rates of diabetes, H had lower SRS Activity, Mental, and Total, and AN had higher SRS Pain (all p < 0.05). The counties that enrollment sites for ASD-DB1 were located in were overall 66% CA, 18% AA, 16% H, and 11% AN. ASD-DB1 was 91% CA, 5% AA, 0% H, 1% AN. ASD-DB2: 338 patients. Compared to CA, AAs were younger and more alone (p < 0.05 all). The counties that enrollment sites for ASD-DB2 were located in were 66% CA, 18% AA, 16% AA, and 11% AN. ASD-DB2 was 91% CA, 5% AA, 0% H, and 1% AN. On multivariable analysis (MVA), no disparity in complications, recovery in HRQOLs, surgical techniques, or correction were found in ASD-DB1 or ASD-DB2 (p GT 0.05 for all). NSQIP had 2,660 patients. AAs were younger and had higher rate of ASA Class 4, dependence and diabetes (all p< 0.05). On MVA, AAs more reoperation (OR 2.2; P=0.005), greater than 5 days length of stay (OR 1.63; P=0.010), septic shock (OR 10; P=0.000), renal failure (OR 6.5; P=0.022) and deep wound infection (OR 2.77;P=0.048) (all p<0.05). <h3>CONCLUSIONS</h3> All three databases found disparities in baseline patient presentation. Both prospective databases predominantly enrolled white patients compared to county demographics. Neither of the prospective databases found racial disparities in complications, HRQOLs, radiographic correction, or techniques utilized. The national database found racial disparities in 30-day postoperative outcomes. This suggests there exist differences in patient populations and data granularity between nationally collected and prospective databases. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

The US Coronavirus Disease 2019 (COVID-19) Surveillance Environment: An Ecological Analysis of the Relationship of Testing Adequacy in the Context of Vaccination.

BackgroundCOVID-19 testing is a critical component of public health surveillance and pandemic control, especially among the unvaccinated, as the nation resumes in-person activities.This study examined the relationships between COVID-19 testing rates, testing positivity rates and vaccination coverage across US counties.MethodsData from the Health and Human Services’ Community Profile Report and 2016-2020 American Community Survey 5-Year Estimates were used. 3,114 US counties were analyzed from January through September 2021. Associations among the testing metrics and vaccination coverage were estimated using multiple linear regression models with fixed effects for states and adjusted for county demographics. COVID-19 testing rates (PCR testing per 1,000), testing positivity (percentage of all PCR tests that were positive), and vaccination coverage (percentage county population that was fully vaccinated).ResultsNationally, median daily COVID-19 testing rates were highest in January and September (35.5 and 34.6 tests per capita, respectively) and lowest in July (13.2 tests per capita). Monthly testing positivity was between 0.03 and 0.12 percentage points (pp) lower for each pp of vaccination coverage, and monthly testing rates were between 0.08 and 0.22 tests per capita higher for each pp of vaccination coverage.ConclusionsThe quantity of COVID-19 testing was associated with vaccination coverage, implying counties having populations with relatively lower protection against the virus are conducting less testing than counties with relatively more protection. Monitoring testing practices in relation to vaccination coverage may be used to monitor the sufficiency of COVID-19 testing based on population susceptibility to the virus.

Racial Bias in Police Traffic Stops: White Residents’ County-Level Prejudice and Stereotypes Are Related to Disproportionate Stopping of Black Drivers

Racial disparities in policing are well documented, but the reasons for such disparities are often debated. In the current research, we weighed in on this debate using a regional-level bias framework: We investigated the link between racial disparities in police traffic stops and regional-level racial bias, employing data from more than 130 million police traffic stops in 1,413 U.S. counties and county-level measures of racial bias from more than 2 million online respondents. Compared with their population share in county demographics, Black drivers were stopped at disproportionate rates in the majority of counties. Crucially, disproportionate stopping of Black drivers was higher in counties with higher levels of racial prejudice by White residents (rs = .07−.36). Furthermore, county-level aggregates of White people’s threat-related stereotypes were less consistent in predicting disproportionate stopping (rs = .00−.19). These observed relationships between regional-level bias and racial disparities in policing highlight the importance of the context in which police operate.

Who donates? Patterns of blood donation and donor characteristics at a university-affiliated hospital-based donor center.

Blood donors are a crucial element of the blood supply chain. Optimal recruitment strategies built upon the robust understanding of local donor behavior and demographics-specifically, the donor characteristics of our university-affiliated hospital-based donor center-improve outreach and retention of donors. This retrospective study analyzed blood donors' genders, ethnicities, and donation frequencies at a university-affiliated hospital-based donor center from 2014-2019, stratified into seven age cohorts. Donor ethnicity demographics were compared to the reported student, employee, and LA County population. Female donors outnumbered male donors in all age cohorts. The majority of donors self-identified (SI) as White (36.7%), Hispanic/Latino (21.6%), or Asian (19.1%). Older donors (age > 25) donated more frequently (4.1 vs. 2.3 donations per donor) than younger donors (age ≤ 25). Repeat donors who donated in multiple years during the study period were more likely to donate multiple times each year than those donors who only donated during 1 year. Our donor demographics more closely reflect the university student and employee demographics than LA County demographics, demonstrating the broad local efforts of recruitment by student groups and donor center recruitment staff. However, non-White populations continue to be underrepresented. The majority of donors only donated once during the study period. Recruitment strategies to increase donor engagement among underrepresented populations and increase the proportion of repeat donors are likely to prove most beneficial.

Prevalence and Risk Factors for Intimate Partner Violence-related Brain Injury in New York

<h3>Research Objectives</h3> To identify the prevalence and risk factors for intimate partner violence (IPV)-related traumatic brain injury (TBI) in survivors in New York. <h3>Design</h3> Retrospective chart review. <h3>Setting</h3> Community Justice Center. <h3>Participants</h3> Forty IPV survivors aged 35-48 years [(M 35.1; SD 13.2); 95% female, 50% Caucasian, 42.5% African American, 7.5% refugees, and 93% with previous hypoxic injury] assessed a mean of 4.4±11 days since head trauma. Our sample showed a higher proportion of African Americans (227%) and refugees (650%) than the County's average on race. <h3>Interventions</h3> Not applicable. <h3>Main Outcome Measures</h3> The HELPS was used to identify TBI prevalence in IPV survivors at the initial Center visit. <h3>Results</h3> Forty-one percent of survivors demonstrated a positive history of IPV-related TBI. Fifty-five percent reported needing an emergency room visit; 42.5% reported loss of consciousness; 45% sustained symptoms consistent with mild TBI such as headaches or fatigue. In multivariate models, after controlling for race, female sex (p=0.003) and refugee status (p=0.002) were strongly associated with the number of previous brain injuries (PBI). No other demographic variables were significantly related to the number of PBI. <h3>Conclusions</h3> Congruent with previous findings,1,2 our data indicated a high prevalence of IPV-related TBI (about two in five survivors) in New York. Notably, our sample comprises a higher percentage of African Americans and refugees compared to the County's demographics. We found that being a female or a refugee increases the risk of sustaining IPV-related TBI. Though shown as high, IPV-related TBI prevalence varies among samples.3,4 Future research must determine better nationwide estimates of brain injury prevalence in the IPV population as recommended by the recent GAO4 report to improve resource allocation and clinical management. <h3>Author(s) Disclosures</h3> The authors declare no conflict of interest.

Exploring Race and Ethnicity Representational Inequities in Illinois Medical Schools.

Purpose: Efforts to increase U.S. medical school student diversity have lagged behind the continued growth of racial/ethnic minorities in the population. A targeted, local approach may catalyze actionable change that holds schools accountable for addressing community needs through representation. The aims of our study are to (1) analyze the student racial/ethnic profiles of allopathic and osteopathic medical schools in the diverse state of Illinois and (2) compare student race/ethnicity with that of schools' local county and primary teaching hospital patient populations.Methods: Data from the Association of American Medical Colleges and American Association of College of Osteopathic Medicine were used to gather matriculated student race/ethnicity from the eight allopathic schools and one osteopathic medical school in Illinois. Representational inequity quotients (RIQs) were calculated to determine the proportion of Hispanic/Latinx, black/African American, and total underrepresented in medicine (UIM) individuals in three reference populations (U.S., county, and primary teaching hospital patient populations) relative to each medical school's student racial/ethnic profile.Results: Across Illinois schools, mean RIQs were highest (showed greater inequity) when county demographics were used as the reference population as opposed to U.S. or hospital populations. For all schools individually, Hispanic county-student RIQs were higher than RIQs based on hospital population. For a majority of schools with primary teaching hospital in Cook County, hospital-student RIQs magnified representational inequity for the black population.Conclusions: Using county data to evaluate medical school representation inequities may better reflect UIM representation goals than the U.S. population. Examining hospital demographics may further reveal other structural inequities relevant to medical education, such as primary teaching hospitals that are not adequately serving their surrounding communities. By evaluating RIQs on a local and hospital-population level, schools can periodically assess to what degree their student body and hospital populations represent their communities and adjust recruitment, retention, and service efforts.

Influenza Vaccination in Health Centers During the Coronavirus Disease 2019 Pandemic-United States, 7-27 November 2020.

Influenza vaccination is the most effective way to prevent influenza and influenza-associated complications including those leading to hospitalization. Resources otherwise used for influenza could support caring for patients with coronavirus disease 2019 (COVID-19). The Health Resources and Services Administration (HRSA) Health Center Program serves 30 million people annually by providing comprehensive primary healthcare, including influenza vaccination, to demographically diverse and historically underserved communities. Because racial and ethnic minority groups have been disproportionately affected by COVID-19, the objective of this analysis was to assess disparities in influenza vaccination at HRSA-funded health centers during the COVID-19 pandemic. The Centers for Disease Control and Prevention and HRSA analyzed cross-sectional data on influenza vaccinations from a weekly, voluntary health center COVID-19 survey after addition of an influenza-related question covering 7-11 November 2020. During the 3-week period, 1126 of 1385 health centers (81%) responded to the survey. Most of the 811 738 influenza vaccinations took place in urban areas and in the Western US region. There were disproportionately more health center influenza vaccinations among racial and ethnic minorities in comparison with county demographics, except among non-Hispanic blacks and American Indian/Alaska Natives. HRSA-funded health centers were able to quickly vaccinate large numbers of mostly racial or ethnic minority populations, disproportionately more than county demographics. However, additional efforts might be needed to reach specific racial populations and persons in rural areas. Success in influenza vaccination efforts can support success in severe acute respiratory syndrome coronavirus 2 vaccination efforts.

Demographics, politics, and health factors predict mask wearing during the COVID-19 pandemic: a cross-sectional study

BackgroundWearing a protective face covering can reduce the spread of COVID-19, but Americans’ compliance with wearing a mask is uneven. The purpose of this study is to examine the association between health determinants (Health Behaviors, Clinical Care, Social and Economic Conditions, and the Physical Environment) and mask wearing at the county level.MethodsData were collected from publicly available sources, including the County Health Rankings and the New York Times. The dependent variable was the percent of county residents who reported frequently or always wearing a mask when in public. County demographics and voting patterns served as controls. Two-levels random effects regression models were used to examine the study hypotheses.ResultsResults indicate that, after considering the effects of the controls, Health Behaviors were positively associated with mask wearing, the Physical Environment held a negative association, and Clinical Care and Social and Behavioral Factors were unrelated.ConclusionsResults indicate that patterns of healthy behaviors can help predict compliance with public health mandates that can help reduce the spread of COVID-19. From an instutitional theory perspective, the data suggest counties develop collective values and norms around health. Thus, public health officials can seek to alter governance structures and normative behaviors to improve healthy behaviors.