Census Tract Data Research Articles

Abstract WP269: Food Desert Residence as a Contributing Risk Factor for Acute Ischemic Stroke Patients

Background: Research suggests that residing in a food desert (FD) area may negatively impact health by increasing cardiovascular risk factors. The USDA defines FD as an area of low income in addition to low access to grocery stores at a 1 (urban) or 10-mile (rural) radius and/or low vehicle access. This study aims to assess sociodemographic profile and stroke risk factors among individuals residing in FDs within the predominantly rural state of South Carolina (SC). Methods: Deidentified administrative discharge data included all individuals admitted to SC hospitals between 2010 and 2019 with ICD-9/10 codes for ischemic stroke. Public USDA census tract data were used to define FDs based on patients’ residential addresses at time of admission, with encrypted linkages provided by SC’s clinical data warehouse. Stroke risk factors were compared between those residing in a FD vs. not via chi-square analyses. Results: Out of the identified 63,330 patients with an index ischemic stroke event, 36.8% were classified as residing within a USDA defined FD. Acute stroke patients residing within a FD were significantly more likely to be younger (age <65), of black race, and without health insurance (all p<.0001). FD residents were significantly more likely to have comorbid hypertension (OR 1.14, 95%CI 1.09, 1.19), type 2 diabetes (OR 1.21, 95%CI 1.17, 1.25), heart failure (OR 1.14, 95%CI 1.09, 1.19), and chronic kidney disease (OR 1.24, 95%CI 1.18, 1.30) associated with acute stroke hospital admission. Also, those residing in FDs were significantly more likely to have a history of obesity (OR 1.17, 95%CI 1.11, 1.23), mental health (OR 1.14, 95%CI 1.10, 1.18), tobacco use (OR 1.28, 95%CI 1.23, 1.33), and substance abuse (OR 1.40, 95%CI 1.35, 1.45). There were no significant differences noted in terms of sex/gender, dyslipidemia, discharge disposition, or case fatality. Conclusion: Stroke patients living within FDs are at heightened risks of comorbidities associated with ischemic stroke. Limitations in access to high quality food and suboptimal nutrition may be a contributing risk factor. Future studies focusing on shopping and eating behaviors among those living within FDs are needed to further reduce health disparities within rural and urban geographic locations nationwide.

Abstract TP227: Correlation of Social Vulnerability Index and Stroke Patient Social Needs

Introduction: Social determinants of health (SDOH) have a significant role in stroke patients’ health outcomes. To assess the environments patients are discharged to, the AHA's GWTG tool collects data on ten social needs of hospitalized stroke patients. The CDC’s Social Vulnerability Index (SVI) evaluates the vulnerability of a community to hazards by considering sixteen components across four themes: Socioeconomic Status, Household Characteristics, Racial and Ethnic Minority Status, and Housing Type/Transportation. This study aims to assess the correlation between the GWTG social needs assessment and the SVI at the census tract level. Methods: Georgia Coverdell Acute Stroke Registry (GCASR) data from 2021 was matched with the Georgia Discharge Data System to obtain patients' residence coordinates. The data was then linked with 2020 SVI census tract data. Each SVI component was classified into deciles and assessed for correlation with the proportion of patients with a specific social need using Spearman correlation. Results: Among the 22,930 patients treated at GCASR participating hospitals, 10,019 had social needs data. No major sociodemographic or disease-related differences were noted between patients with and without social need data. 15 SVI components have a statistically significant correlation at the 0.05 alpha level with at least one social need. Correlation strength ranged from mild to strong. Conclusion: Most elements of the SVI at the census tract level are moderately or strongly correlated with one or more social needs, suggesting they may serve as proxy measures. SVI data, regularly updated by the CDC and freely available, could be incorporated into electronic medical records to assist with stroke patients' discharge process and transition of care.

Establishing a working definition for veterinary care desert.

To develop a formal definition of veterinary care deserts as guidance for veterinary and animal welfare professionals to easily identify areas with limited access to veterinary care that can be targeted with expansion or implementation of programs and services. 52 sources relating to veterinary care and 55 sources relating to human resource deserts were reviewed for themes and parameters relating to resource desert definitions and barriers to care. Of these, 37 veterinary and 42 human sources were included to inform the themes and parameters for our definition. We performed a scoping literature review with a focus on veterinary care barriers and definitions of human resource deserts. The review identified 3 common themes of accessibility (transportation; distance to resource), affordability (owner income or poverty level; cost of care), and availability (density of professionals) that were incorporated into the definition of a veterinary care desert and parameterized at the level of census tracts. A working definition for veterinary care deserts was established as a geographic area where accessible, affordable, and available veterinary care is limited. By consulting publicly available census tract data on accessibility, affordability, and availability, veterinary care providers and organizations can use this definition to identify areas most likely to be experiencing reduced access to veterinary care and target interventions accordingly.

Rural cardiac arrest care and outcomes in Texas

IntroductionOut-of-hospital cardiac arrest (OHCA) victims in rural communities have worse outcomes despite higher rates of bystander cardiopulmonary resuscitation (CPR) than urban communities. In this retrospective cohort study we attempt to evaluate selected aspects of the continuum of care, including post-arrest care, for rural OHCA victims, and we investigated factors that could contribute to rural areas having higher rates of bystander CPR. MethodsWe analyzed 2014–2020 Texas Cardiac Arrest Registry to Enhance Survival (TX-CARES) data for adult OHCAs. We linked TX-CARES data to census tract data and stratified OHCAs into urban and rural events. We created a mixed-model logistic regression to compare cardiac arrest characteristics, pre-hospital care, and post-arrest care between rural and urban settings. We adjusted for confounders and modeled census tract as a random intercept. We then compared different regression models evaluating the association between response time and bystander CPR. ResultsWe included 1202 rural and 28,288 urban cardiac arrests. Comparing rural to urban OHCAs, rates of bystander CPR were significantly higher in rural communities (49.6% v 40.6%, aOR 1.3 95% CI 1.1–1.5). The median response time for rural (11.5 min) was longer than urban (7.3 min). The occurrence of an ambulance response time of <10 min was notably less common in rural communities when compared to urban areas (aOR 0.2, 95% CI 0.2–0.2). For post-arrest care the rates of percutaneous coronary intervention (PCI) were higher in rural than urban communities (aOR 1.7, 95% CI 1.01–2.8). The rates of AED and TTM were similar between urban and rural communities. Survival to hospital discharge was significantly lower in rural communities than urban communities (aOR 0.6, 95% CI 0.4–0.7). Although not significant, rural communities had lower rate of survival with a cognitive performance score (CPC) of 1 or 2 (aOR 0.7, 05% CI 0.6–1.003). We identified no association between response time and bystander CPR. ConclusionPatients in rural areas of Texas have lower survival after OHCA compared to patients in urban areas, despite having significantly greater rates of bystander CPR and PCI. We did not find a link between response time and bystander CPR rates.

Neighborhood disadvantage and adolescent behavior problems: how do inferences differ across definitions of disadvantage?

Various definitions of neighborhood disadvantage (ND) exist, yet evidence is lacking on how ND operationalization may impact scientific inference. We used data from wave 6 of the Fragile Families study, excluding those without census tract or behavior problem data (n = 2363). Outcomes included five scales from the caregiver-reported Child Behavior Checklist (CBCL) and a self-reported delinquency scale. ND was defined in four ways: (1) a modified Sampson definition which included four neighborhood poverty variables; (2) a poverty-only definition which only included percent households below poverty; (3) an overextended definition which added a mediator between the ND-behavior relationship, and (4) an expanded definition which added six additional ND variables to the modified Sampson definition. Using effect estimates from generalized linear models, differences were calculated using percent change-in-estimate, with the modified Sampson as the referent. Effect estimates were similar for the modified Sampson and expanded definitions (< 5% difference). The poverty-only definition differed from the modified Sampson unsystematically. Estimates for the overextended definition were consistently larger compared to modified Sampson (10-37% greater). The expanded and modified Sampson definitions produced similar results. Poverty-only and overextended ND definitions should be interpreted with caution.

Impact of Social Determinants of Health and Novel Therapies on the Outcomes of Relapsed and Refractory Diffuse Large B Cell Lymphoma

Introduction: Outcomes for patients with relapsed and refractory diffuse large B cell lymphoma (R/R DLBCL) have improved dramatically with the recent approvals of chimeric antigen receptor (CAR) T cell therapies and novel immunotherapies. Unfortunately, studies show persistent disparities in DLBCL that impact survival, including patient race, income, and rural residence. The U.S. Veterans Health Administration (VA) is a single-payer healthcare system that provides coverage for cancer therapies and travel support, which could address barriers to treatment. This national VA study examines the influence of social determinants of health (SDoH) and treatment patterns on the outcomes of veterans with R/R DLBCL in the era of novel therapies. Methods: Patients who received frontline anthracycline at any time and any systemic therapy for R/R DLBCL between 2019-2022 were identified through the VA Corporate Data Warehouse and retrospective chart review. The Social Deprivation Index (SDI) was estimated at the zip code level using the 2019 American Community Survey (Butler et al, 2013). Median household income was estimated from federal census tract data. Logistic regression was used to evaluate binary outcomes, and Cox regression for survival analyses. Results: 225 patients across 70 VA medical centers met eligibility (Table 1). The median age was 69, and most (96%) were male, reflecting the VA population. The median follow-up was 32.7 months (range, 2.3-217.5). Patients received a median of 3 lines of therapy (range, 2-8). Novel immunotherapies were administered to 98 patients (44%): 10 (4%) received loncastuximab, 23 (10%) tafasitamab, and 83 (37%) polatuzumab. 52 (23%) and 26 (12%) patients received CAR T and autologous stem cell transplant (auto-SCT), respectively. The estimated 2-year overall survival (OS) was 65.8% (95% CI, 59.1-71.7). In univariate analyses, age &amp;lt; 70 (HR 0.58, 95% CI 0.41-0.82), use of CAR T (HR 0.64, 95% CI 0.40-0.99), and auto-SCT (HR 0.39, 95% CI 0.19-0.73) were associated with improved OS. Interestingly, the use of novel immunotherapies was associated with worse OS (HR 1.43, 95% CI 1.01-2.01), but among those who received it, using it in earlier lines had better survival (HR 0.71, 95% CI 0.54-0.94). Notably, Hispanic white had worse survival than non-Hispanic white patients (HR 1.97, 95% CI 1.13-3.23), while African Americans had similar survival to non-Hispanic white patients. Higher stage showed worse survival, but this did not reach significance (HR 1.12, 95% CI 0.93-1.40). Other SDoH (sex, income, rural residence, SDI), disease traits (transformed, LDH, cell of origin, double-hit), and medical comorbidities did not impact survival. In multivariate analysis, the impacts of CAR T, auto-SCT, and Hispanic ethnicity persisted (Figure 1). Among patients receiving at least 3 lines of therapy ( n = 143), the only significant covariate in multivariate regression for OS was CAR T (HR 0.57, 95% CI 0.32-0.96). Referrals for SCT and CAR T were sent for 65 (29%) and 81 (36%) patients, respectively. The most advantaged SDI quartile had higher odds of getting an SCT referral than the least advantaged quartile (OR 5.00, p = 0.0015). Similarly, household income ≥ $75,000 had higher odds of SCT referral vs. lower incomes (OR 2.88, p = 0.004). Race did not affect SCT referral rates, and SDoH in general did not impact CAR T referrals. SDoH was not associated with whether patients actually received novel immunotherapies, CAR T, or SCT (only affecting referral rates in the latter). The most common reasons for not pursuing auto-SCT after referral were comorbidities ( n = 23, 33%), pursuance of other cell therapies ( n = 17, 25%), and patient decision ( n = 12, 17%). The most common reasons for deferring CAR T were comorbidities ( n = 15, 28%), death ( n = 15, 28%), and patient decision ( n = 6, 11%). At last follow-up, of the 47 patients in remission for &amp;gt; 1 year, 27 (57%) had CAR T or SCT as their last therapy. Conclusion: Cellular approaches were the most impactful factors in improving OS. Hispanic ethnicity remained an independent poor prognostic factor, but other SDoH did not impact survival in this cohort. Broad drug coverage by a single-payer system, front-line anthracycline, and equal receipt of cell therapies may have mitigated some of the impact of SDoH on DLBCL survival. Nonetheless, cell therapies had a high referral but low administration rate, highlighting the challenge of getting patients to definitive treatment.

Abstract 13999: The Relationship Between Neighborhood Deprivation, Diabetes, and Extracellular Vesicles in African American Women at Risk for CVD: Data From a Pilot Study of the Step It Up Physical Activity Intervention

Background: African American women (AA) are at disproportionally high risk for diabetes and cardiovascular disease (CVD) which is accelerated when residing in resource-limited neighborhoods. Extracellular vesicles (EV) are emerging to be of importance in CVD development and progression, but little is known about a potential impact of neighborhood socioeconomic deprivation (NSD). In this study we examined associations between NSD, plasma EV, and markers of diabetes risk in a community-based cohort of AA women at risk for CVD from resource-limited neighborhoods in Washington, DC. Methods: Participants were enrolled in pilot testing of Step It Up, a community engaged physical activity intervention. Blood samples were drawn to measure clinical labs during participants’ baseline visit to the NIH Clinical Center. EV were isolated from heparinized plasma using size exclusion chromatography with size and numbers determined by nanoparticle tracking analysis. NSD was calculated using 2018 US Census tract data as a measure of neighborhood deprivation. Associations between NSD, EV, and diabetes-related clinical measures were analyzed using multivariable regressions adjusted for BMI and ASCVD 10-year risk score. Results: The study cohort was a convenience sample of AA women at risk for CVD (N=24, Age: 57±12, BMI: 35±6, ASCVD: 9±5). NSD associated with fasting glucose (β=0.54, p=0.007) and Hemoglobin A1c (HA1c) (β=0.51, p=0.007). Additionally, NSD associated with lower EV size (β=-0.42, p=0.03), with no association with EV concentration. Fasting glucose and HA1c associated negatively with EV size (β=-0.48, p=0.03 and β=-0.50, p=0.02, respectively) but no association was found with EV concentration. Conclusions: Thus, our data show that higher neighborhood deprivation is associated with lower EV size which, in turn, is associated with higher diabetes risk markers. More research is needed to understand the role of EV in diabetes and CVD development and progression. While larger studies further evaluating these observations are needed, our data highlight the importance of increased diabetes screening and multi-level interventions in patients residing in under-resourced communities to reduce existing health disparities.

Abstract 264: Impact of Receiving Hospital on Disparities in Out-of-Hospital Cardiac Arrest

Background: Minority out-of-hospital cardiac arrest (OHCA) victims suffer from worse outcomes. The factors contributing to these disparities are not completely understood, and little is known about the impact of receiving hospital on OHCA. Hypothesis: Receiving hospital plays an important role in OHCA outcome disparities. Methods: We performed a retrospective, cohort study of the national Cardiac Arrest Registry to Enhance Survival (CARES). We included OHCAs from 2014- 2021 that survived to hospital admission. Based on census tract data, we stratified OHCAs based on majority race/ethnicity: &gt;50% White, &gt;50% Black, and &gt;50% Hispanic/Latino. We stratified hospitals into quartiles based on hospital rate of the outcome, survival with favorable neurologic outcome, cerebral performance category of 1 of 2. We evaluated the association between race/ethnicity and care at increasing hospital performance quartile. We compared four models evaluating the association between race/ethnicity and outcome: 1) omitting receiving hospital and bystander CPR (B-CPR), 2) adjusting for B-CPR, 2) additionally adjusting for receiving hospital as a random intercept, and 3) adjusting for hospital performance quartile. We adjusted all models for possible confounders. Results: We include 124,908 OHCAs that survived to hospital admission; 90,034 majority White, 20,600 majority Black, and 14,338 majority Hispanic. Compared to White, Black (OR 0.1, 95% CI 0.1-0.1) and Hispanic OHCAs were less likely to be cared for at high performing hospitals. Ignoring receiving hospital, outcomes were worse for Black (19.7%, aOR 0.43, 95% CI 0.40-0.46) and Hispanic (22.1%, aOR 0.49, 95% CI 0.45-0.54) than White (33.5%). While adjusting for B-CPR did not change survival odds, adjusting for receiving hospital as a random intercept improved outcome odds for Black (aOR 0.60, 95% CI 0.54-0.67) and Hispanic (aOR 0.61, 95% CI 0.53-0.69). Adjusting for hospital performance quartile also improved outcome odds for Black (aOR 0.79, 95% CI 0.73-0.85) and Hispanic/Latino (aOR 0.78, 95% CI 0.70-0.86). Conclusion: OHCAs from minority communities were less likely to be cared for at higher performing hospitals, and adjusting for receiving hospital significantly diminished OHCA outcome disparities.

Abstract 12346: Atherosclerotic Cardiovascular Disease Risk Associated With Social Determinants of Health at Individual and Area Levels

Introduction: Adverse social determinants of health (SDOH) are associated with an increased risk for atherosclerotic cardiovascular disease (ASCVD). However, it is unclear if the ASCVD risks associated with area-level SDOH are similar to those with individual-level measures. Further, SDOH are not included in the Pooled Cohort Equations (PCEs) when estimating 10-year ASCVD risk. Studies have shown that PCEs systematically underestimate risk for socially deprived individuals. Aims To examine the association of individual- and area-level SDOH including education, income, and employment with incident ASCVD. Also, we assessed if adding SDOH to the PCEs improves risk prediction accuracy. Methods: We pooled data from four cohorts: Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, Framingham Heart Study Offspring Cohort, and Reasons for Geographic and Racial Differences in Stroke Study. We excluded participants with a history of ASCVD. Individual-level SDOH were based on participants’ self-report and area-level SDOH were derived by linking participants’ addresses to US Census tract data. We used Cox proportional hazards models to assess the associations between SDOH and ASCVD. We also assessed the changes in discrimination (Harrell’s C-index) and calibration (Integrated Brier Score) after adding SDOH to risk prediction models. Results: We analyzed data from 27,603 participants (mean age 61.4 years, 59% women, and 49% White). During a median follow-up of 13 years, 2,839 incident ASCVD events occurred. Both individual- and area-level SDOH were associated with ASCVD ( Figure, Panel A ). Adding both individual- and area-level SDOH to risk prediction modestly improved model discrimination and calibration in Black men and women ( Figure, Panels B &amp; C ), and also improved calibration in non-Black women. Conclusions: The findings suggest that SDOH may be considered in the development of future ASCVD risk assessment tools, particularly among Black individuals.

Abstract 262: Mediating Factors Between Community Race/Ethnicity and Initial Shockable Rhythm

Background: Initial shockable rhythm is an important predictor of favorable out-of-hospital cardiac arrest (OHCA) outcomes. While patients from minoritized communities suffer from lower rates of initial shockable rhythm, the reason for this disparity is not known. Hypothesis: OHCA characteristics contribute to disparities in initial shockable rhythm. Methods: We performed a retrospective study of the 2014-2021 Texas Cardiac Arrest Registry to Enhance Survival, including adult, non-traumatic OHCAs. Linked to census tract data, we stratified OHCAs based on having a majority of a race/ethnicity: &gt;50% White, &gt;50% Black, and &gt;50% Hispanic/Latino. To evaluate if initial shockable rhythm impacts outcome disparities, we compared logistic regression models between race and OHCA outcomes: 1) unadjusted, 2) adjusted for bystander CPR (bCPR), and 3) adjusted for initial rhythm. Using structural equation modeling, we then performed a mediation analysis between race/ethnicity, OHCA characteristics, and shockable rhythm, reporting the mediations proportions. Results: We included 39,596 OHCAs, 16,702 White, 5,461 Black, and 17,433 Hispanic. The rate of shockable rhythm was 19.0% for White, 14.3% for Black, and 14.6% for Hispanic. Odds of favorable neurologic outcome were lower for Black (OR 0.5, 95% CI 0.4-0.6) and Hispanic (OR 0.6, 95% CI 0.6-0.7). While adjusting for bCPR did not change these odds, adjusting for shockable rhythm increased odds for Black (OR 0.6, 95% CI 0.5-0.7) and Hispanic (OR 0.7, 95% CI 0.6-0.8). On mediation analysis, the proportion of initial shockable rhythm mediated for Black census tract were: age&gt;65 (-7.3%), male gender (6.8%), public location (6.9%), healthcare facility location (-17.2%), bystander witnessed (19.2%), bCPR (4.3%), and bystander AED (6.4%). The proportion mediated for Hispanic census tract were: age&gt;65 (-4.8%), male gender (0.5%), public location (-4.0%), healthcare location (-13.5%), bystander witnessed (20.8%), bCPR (8.7%), and bystander AED (6.2%). Conclusion: Bystander witnessed arrest was the most significant mediator of shockable rhythm for OHCA in Black and Hispanic communities, while bCPR was a modest mediator of shockable rhythm for Hispanic OHCA victims.

The Impact of Air Pollutants on a Chicagoland Cohort of Patients with Acute Myeloid Leukemia

Background Outcomes in acute myeloid leukemia (AML) can be impacted by cytogenetic/molecular features along with environmental factors such as previous exposure to cytotoxic therapy and county-level income. Our group previously identified structural racism, defined as systemic disadvantage experienced by certain groups of people, as a mediator of disparities within a cohort of 822 patients (pts) diagnosed with AML in the Chicagoland area even when accounting for genetic features of disease (Abraham et al, Blood 2022). Air pollution disproportionately impacts racial-ethnic minorities and has been demonstrated to impact DNA methylation patterns in pts which in turn influence disease biology (Tessum et al, Sci Advances 2021; Rider et al, Clin Epigenetics 2019). With that in mind we aimed to investigate the impact of air pollutant exposures that have been associated with both leukemia development/mortality and with air pollution disparities in historically redlined cities. Methods Adult AML (non-APL) pts diagnosed between 2012 and 2018 at six academic cancer centers in the Chicago area were included. Pts' census tracts were joined with measures of pollution obtained from the Center for Disease Control National Environmental Public Health Tracking Network and the 2014 National Air Toxics Assessment: 1,3-butadiene, benzene, diesel particulate matter (PM), polycyclic aromatic hydrocarbons and polycyclic organic matter (PAHPOM), and PM 2.5 µm (2014 averaged daily census tract measures). Pollutant exposures by racial/ethnic groups were determined using a Kruskall-Wallis rank sum test and pairwise Wilcoxon rank sum tests. Univariate logistic regressions for each pollutant were performed for 2010 European Leukemia Net (ELN) AML criteria and TP53 mutation status. Survival among pts in the most and least polluted census block quartiles for each pollutant was compared using Kaplan-Meier survival analysis. Results Our multi-center database contained 789 pts with AML with census tract data, allowing for air pollutant data collection. Median age of diagnosis was 62 years old. In addition, 59.9% of pts were non-Hispanic White (NHW), 15.3% were non-Hispanic Black (NHB), and 15% of pts were Hispanic. Additional characteristics are summarized in Table 1. There was significantly higher median exposure to 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 in NHB and Hispanic pts when compared to NHW pts. Hispanic pts had significantly median higher exposure to 1,3-butadiene and benzene when compared to NHB pts while NHB pts had significantly higher median exposure to PM2.5 ( Table 2). With univariate analysis, no pollutant exposure was found to be significantly associated with ELN 2010 risk category or with TP53 mutation status. We also compared median OS (mOS) from AML diagnosis between the quartile with the lowest exposure (Q1) and quartile with the highest exposure (Q4). For 1,3-butadiene mOS was 2.52 years (Q1) vs. 2.96 years (Q4) (p=0.75), for benzene it was 2.65 years vs 3.0 years (p=0.38), for diesel PM it was 2.56 years vs 2.96 years (p=0.56), for PAHPOM it was 2.76 years vs. 2.96 years (p=0.31), and for PM2.5 it was 2.92 years vs. 2.70 years (p=0.32). Conclusions We analyzed the impact of 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 on outcomes in pts with AML in the Chicagoland area. While there were significant differences in median exposure to pollutants by race/ethnicity, there was no significant association between pollutant exposure and ELN 2010 risk category or TP53 mutation analysis. We also analyzed overall survival between Q1 and Q4 of exposure for each pollutant and found no significant difference. While pollutant exposure disproportionately impacts racial-ethnic minorities, individual pollutants did not appear to be a major driver of outcomes in AML. Limitations include the source of our air pollutant data, where misclassification of pollutants may exist and impact the ability to detect true associations.

Multi-Level Factors Underlying Racial/Ethnic Inequities in Clinical Trial Participation Among Patients with Hematologic Cancers: Lessons for the Development of Diversity Plans

Background: The US Food &amp; Drug Administration announced that drug sponsors will be required to implement plans to improve racial/ethnic diversity in clinical trials starting in 2024. While historically marginalized racial/ethnic populations are less likely to participate in cancer trials, there is limited information regarding inequities in access to hematologic cancer trials. It is also unknown whether social determinants of health (SDOH) explain racial/ethnic inequities in trial participation. Here we examined the extent to which commonly used trial inclusion criteria and SDOH factors explain racial/ethnic inequities in clinical trial participation among patients with six hematologic cancers. Methods: This retrospective study used the nationwide Flatiron Health electronic health record-derived de-identified database (2011-2022) of adult patients with multiple myeloma, non-Hodgkin's lymphoma (diffuse large B-cell, follicular, or mantle cell lymphoma) or leukemia (chronic lymphocytic or acute myeloid leukemia). Area-level SDOH ( e.g. predominant race/ethnicity - a measure of segregation) characterizing where patients lived were assessed using the American Community Survey census tract data. Patients were followed from initial diagnosis to clinical study drug receipt (a proxy for trial participation), death, or last recorded activity. Associations of race/ethnicity and SDOH factors with trial participation were assessed using cause-specific hazards models adjusted for clinical confounders (diagnosis year, age, sex, and cancer type). To determine which commonly used trial inclusion criteria ( i.e. abnormal creatinine serum [≥ 2] and performance status) and SDOH factors underlie racial/ethnic inequities, mediation analysis was performed using nonlinear multiple additive regression tree models. Results: This study included 51,382 patients (median age: 67 years, 42.2% women; 57.7% non-Latinx [NL] White, 6.9% NL Black, 6.1% Latinx, 29.4% other/unknown). Black and Latinx patients were more likely to live in marginalized areas ( e.g. segregated neighborhoods color and higher percentages of limited English proficiency and low vehicle ownership) than White patients. Overall, 5.6% of patients participated in trials. Patients who received care from community practices or lived in marginalized neighborhoods were less likely to participate in trials. Black (4.2%; hazard ratio [HR] 0.62, 95% confidence interval [CI]: 0.52- 0.73) and Latinx patients (3.7%; HR 0.53, CI: 0.44-0.65) were less likely to participate in trials than White patients (6.4%). Black-White trial inequities were mediated (77%, CI: 42%-117%) by practice type ( e.g., community vs. academic center, 19%, CI: 9%-28%) and area-level SDOH such as segregation (49%, CI: 21%-77%) and vehicle ownership (12%, CI: 1%-24%). Mediators explained 55% (CI: 23%-87%) of the Latinx-White trial participation inequity; area-level SDOH-including segregation (30%, CI: 3%-58%), limited English proficiency (21%, CI: -3% to 45%), and vehicle ownership (17%, CI: 0%-45%)-were the most important mediators. Clinical factors did not substantially mediate racial/ethnic inequities (&amp;lt; 3% proportion mediated). Conclusion: Black and Latinx patients diagnosed with hematologic cancers are 40% to 50% less likely to participate in clinical trials than their White counterparts. SDOH factors explained most of these inequities. These findings suggest that efforts to increase racial/ethnic diversity in cancer trials must address the persistent effects of segregation, along with everyday obstacles to clinical care, such as transportation and language barriers. Without concerted efforts to increase trial participation among historically marginalized racial/ethnic groups, trials may perpetuate inequities in investigational drug access and adversely impact the generalizability of pivotal cancer treatment trials.

Temporal trends in sociodemographic composition and land development within U.S. fenceline communities surrounding hazardous industrial facilities: 2001–2019

Unintended releases from industrial facilities can expose fenceline communities to hazardous substances, and distance between facilities and nearby residential development can play a role in preventing exposures. Here, we assess trends in fenceline community sociodemographic characteristics, land development, and the association between the two using sociodemographic data for census tracts (n = 34 068) surrounding 2457 petroleum refining and chemical manufacturing facilities between 2001 and 2019. We find a higher median growth in percentage of Latinx populations among fenceline communities compared to neighboring communities with no industrial facilities. The increase in the median percentage of Latinx populations within fenceline communities was six times higher than for White populations overall (+6 and +1 percentage points, respectively). Though the percentage of the Black populations did not change within fenceline communities over this period, we find a minor sustained higher percentage of Black residents within fenceline communities relative to neighboring communities (20% versus 19%, respectively). Employing a spatial autoregressive model with autoregressive disturbances, we find that an increase in community percentage Latinx population is associated with a decrease in the rate of land development. Comparing fenceline and neighboring communities, we conclude that Black and Latinx populations are disproportionately located near industrial facilities, potentially contributing to inequitable exposure to unintended chemical releases. Our work lends support to the value of considering of sociodemographic composition of fenceline communities when evaluating industrial facility hazards.

Neighborhood Socioeconomic Disadvantage and White Matter Microstructure of the Arcuate Fasciculus and Uncinate Fasciculus in Adolescents

BackgroundNeighborhood- or area-level socioeconomic disadvantage is associated with neural alterations across the life span. However, few studies have examined the effects of neighborhood disadvantage on white matter microstructure during adolescence, an important period of development that coincides with increased risk for psychopathology. MethodsIn 200 adolescents (ages 13–20 years; 54.5% female, 4% nonbinary) recruited from 2 studies enriched for early adversity and depression, we examined whether neighborhood socioeconomic disadvantage derived from census tract data was related to white matter microstructure in several major white matter tracts. We also examined whether depressive symptoms and sex moderated these associations. ResultsGreater neighborhood socioeconomic disadvantage was associated with lower fractional anisotropy (FA) in the left arcuate fasciculus (β = −0.24, false discovery rate [FDR]–corrected p = .035) and right uncinate fasciculus (β = −0.32, FDR-corrected p = .002) above and beyond the effects of family-level socioeconomic status. Depressive symptoms significantly moderated the association between left arcuate fasciculus FA and both neighborhood (β = 0.17, FDR-corrected p = .026) and unemployment (β = 0.22, FDR-corrected p = .004) disadvantage such that these associations were only significant in adolescents who reported less severe depression. Sex did not moderate the association between socioeconomic disadvantage and FA in these tracts. ConclusionsGreater neighborhood socioeconomic disadvantage, particularly poverty and educational attainment levels, was associated with lower FA in the arcuate fasciculus and uncinate fasciculus above and beyond the effects of family-level measures of socioeconomic status. These patterns were only observed in adolescents with low levels of depression, suggesting that we must be cautious about generalizing these findings to youths who struggle with mental health difficulties.

Interpersonal Discrimination, Neighborhood Inequities, and Children's Body Mass Index: A Descriptive, Cross-Sectional Analysis.

Psychosocial stressors have been implicated in childhood obesity, but the role of racism-related stressors is less clear. This study explored associations between neighborhood inequities, discrimination/harassment, and child body mass index (BMI). Parents of children aged 5-9 years from diverse racial/ethnic backgrounds (n = 1307), completed surveys of their child's exposure to discrimination/harassment. Census tract data derived from addresses were used to construct an index of concentration at the extremes, a measure of neighborhood social polarization. Child's height and weight were obtained from medical records. Multiple regression and hierarchical models examined child's BMI and racism at the individual and census tract levels. Children residing in the most Black-homogenous census tracts had 8.2 percentage units higher BMI percentile (95% confidence interval, 1.5-14.9) compared with white-homogenous tracts (P = .03). Household income and home values were lower, poverty rates higher, and single parent households more common among Black-homogeneous census tracts. Almost 30% of children experienced discrimination/harassment in the past year, which was associated with a 5.28-unit higher BMI percentile (95% confidence interval, 1.72-8.84; P = .004). Discrimination and racial/economic segregation were correlated with higher child BMI. Longitudinal studies are needed to understand whether these factors may be related to weight gain trajectories and future health.

Severity of Financial Toxicity for Patients Receiving Palliative Radiation Therapy

Patients receiving palliative radiotherapy (RT) are often at their most vulnerable state, but the impact of financial toxicity on their health and quality of life (QOL) is not well-described. We set out to determine the degree of financial toxicity in a population undergoing palliative RT. A review of patients referred for palliative RT at our site was conducted. Financial toxicity was determined with COST-FACIT, and previously suggested grading cutoffs were used. Additional patient-reported outcome (PRO) instruments included the EORTC overall health and quality of life questions and the FACIT-TS-G (treatment satisfaction). Multiple imputations by chained equations using predictive mean matching were used for incomplete responses. Spearman's rank correlation coefficient, Kruskal-Wallis testing, and linear regressions were used to measure associations. A total of 53 patients were identified who had completed PRO surveys between May 2021 and December 2022. Median COST was 25 (range 0-44), with lower scores indicating greater financial toxicity. 49% reported grade 0 financial toxicity (COST ≥26), 32% had grade 1 financial toxicity (COST 14-25), 19% had grade 2 financial toxicity (COST 1-13), and 6% had grade 3 financial toxicity (COST = 0). Overall, cancer caused financial hardship among 45%. Higher COST was moderately associated with higher overall health (rho = 0.36, p = 0.02) and weakly associated with higher QOL (rho = 0.28, p = 0.07). From a demographic standpoint, median area family income from census tract data was $98,598 (range $32,303-$190,833), and higher income was associated with higher COST (rho = 0.47, p<0.001). Having Medicare (beta = 13.8, p = 0.003) or private (beta = 13.5, p = 0.001) coverage (rather than Medicaid) were associated with less financial toxicity, whereas having an underrepresented minority background (beta = -13.2, p<0.001), or having a non-English language preference (rho = 0.40, p = 0.003) were associated with greater financial toxicity. Median time from diagnosis was 12.9 mo, and 40% of patients had ≥2 prior systemic therapies. The median RT dose was 25 Gy (range 4-45 Gy). The most common irradiated sites included spine (24%), non-spine bones (21%), brain (18%), and lung/mediastinum (18%). COST was not associated with number of prior systemic therapies (p = 0.31), RT dose (p = 0.83), RT technique (p = 0.86), or treatment satisfaction (p = 0.34). Median follow up was 8.0 months, and median 6-month survival was 83% (95% CI 73%-95%). Inferior OS was associated with more prior systemic therapies (HR 3.43, p = 0.03), but not with COST (HR 1.01, p = 0.67). Financial toxicity was seen in approximately half of patients receiving palliative RT. Patient-reported overall health, Medicaid coverage, and area income correlated well with financial toxicity, but the investigated clinical characteristics did not. This supports the hypothesis that financial toxicity is common and a unique factor that should be measured in cancer patients.

Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns. We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.S. Noise contours were modeled for 90 U.S. airports in 5-year intervals between 1995 and 2015 using the Federal Aviation Administration's Aviation Environmental Design Tool. We utilized linear fixed effects models to estimate changes in noise exposure areas for day-night average sound levels (DNL) of 45, 65, and a nighttime equivalent sound level (Lnight) of 45 A-weighted decibels (dB[A]). We used group-based trajectory modeling to identify distinct groups of airports sharing underlying characteristics. We overlaid noise contours and Census tract data from the U.S. Census Bureau and American Community Surveys for 2000 to 2015 to estimate exposure changes overall and by race/ethnicity. National-scale analyses showed non-monotonic trends in mean exposed areas that peaked in 2000, followed by a 37% decrease from 2005 to 2010 and a subsequent increase in 2015. We identified four distinct trajectory groups of airports sharing latent characteristics related to size and activity patterns. Those populations identifying as minority (e.g., Hispanic/Latino, Black/African American, Asian) experienced higher proportions of exposure relative to their subgroup populations compared to non-Hispanic or White populations across all years, indicating ethnic and racial disparities in airport noise exposure that persist over time. Overall, these data identified differential exposure trends across airports and subpopulations, helping to identify vulnerable communities for aviation noise in the U.S. We conducted a descriptive analysis of temporal trends in aviation noise exposure in the U.S. at a national level. Using data from 90 U.S. airports over a span of two decades, we characterized the noise exposure trends overall and by airport characteristics, while estimating the numbers of exposed by population demographics to help identify the impact on vulnerable communities who may bear the burden of aircraft noise exposure.

Characteristics and neighborhood-level opportunity of assault-injured children in Milwaukee

BackgroundMultiple studies have explored demographic characteristics and social determinants of health in relation to the risk of pediatric assault-related injuries and reinjury. However, few have explored protective factors. The Child Opportunity Index (COI) uses neighborhood-level indicators to measure ‘opportunity’ based on factors such as education, social environment, and economic resources. We hypothesized that higher ‘opportunity’ would be associated with less risk of reinjury in assault-injured youth.MethodsThis was a single-institution, retrospective study at a Level 1 Pediatric Trauma Center. Trauma registry and electronic medical record data were queried for children ≤ 18 years old with assault-related injuries from 1/1/2016 to 5/31/2021. Reinjured children, defined as any child who sustained more than one assault injury, were compared to non-reinjured children. Area Deprivation Index (ADI), a marker of socioeconomic status, and COI were determined through census block and tract data, respectively. A post-hoc analysis examined COI between all assault-injured children, unintentionally injured children, and a state-based normative cohort representative of non-injured children.ResultsThere were 55,862 traumatic injury encounters during the study period. Of those, 1224 (2.3%) assault injured children were identified, with 52 (4.2%) reinjured children and 1172 (95.8%) non-reinjured children. Reinjured children were significantly more likely to be older (median age 15.0 [IQR 13.8–17.0] vs. median age 14.0 [IQR 8.8–16.0], p < 0.001) and female (55.8% vs. 37.5%, p = 0.01) than non-reinjured children. COI was not associated with reinjury. There were also no significant differences in race, ethnicity, insurance status, ADI, or mechanism and severity of injury between cohorts. Post-hoc analysis revealed that assault-injured children were more likely to live in areas of lower COI than the other cohorts.ConclusionsCompared to children who sustained only one assault during the study period, children who experienced more than one assault were more likely to be older and female. Furthermore, living in an area with more or less opportunity did not influence the risk of reinjury. However, all assault-injured children were more likely to live in areas of lower COI compared to unintentionally injured and a state-based normative cohort. Identification of factors on a social or environmental level that leads to assaultive injury warrants further exploration.

Neighborhood factors and survival to old age: The Jackson Heart Study

Few studies have evaluated environmental factors that predict survival to old age. Our study included 913 African American participants in the Jackson Heart Study (JHS) who resided in the tri-county area of the Jackson, MS metropolitan area and were 65–80 years at baseline. Participants were followed from 2000 through 2019 for the outcome of survival to 85 years old. We evaluated each of the following census tract-level measures of the social/physical environment as exposures: socioeconomic status, cohesion, violence, disorder, healthy food stores, residential land use, and walkability. We assessed mediation by physical activity and chronic conditions. As a complementary ecologic analysis, we used census-tract data to examine factors associated with a greater life expectancy. A total of 501 (55%) JHS participants survived to age 85 years or older. Higher social cohesion and greater residential land use were modestly associated with survival to old age (risk difference = 25%, 95% CI: 0–49%; and 4%, 95% CI: 1–7%, respectively). These neighborhood effects were modestly mediated through leisure time physical activity; additionally, social cohesion was mediated through home and yard activity. In our ecologic analysis, a greater percentage of homeowners and a greater proportion of people living in partnered families were associated with higher census-tract level life expectancy. African American older adults living in residential neighborhoods or neighborhoods with high social cohesion were more likely to survive to old age.

Predictive factors of long-term follow-up attendance in very long-term childhood cancer survivors.

Long-term follow-up (LTFU) clinics have been developed but only some childhood cancer survivors (CCS) attend long-term follow-up (LTFU). To identify factors that influence LTFU attendance. Five-year CCS treated for a solid tumor or lymphoma in Gustave Roussy before 2000, included in the FCCSS cohort (French Childhood Cancer Survivor Study), aged >18years and alive at the date of the LTFU Clinic opening (January 2012) were invited to a LTFU visit. Factors associated with attendance at the LTFU clinic between 2012 and 2020 were estimated using logistic regression analyses. Analyses included different types of factors: clinical (tumor characteristics, cancer treatments, late effects), medical (medical expenses were used as a proxy of survivor's health status), social (deprivation index based on census-tract data relating to income, educational level, proportion of blue-collar workers, and unemployed people living in the area of residence), and spatial (distance to the LTFU clinic). Among 2341 CCS contacted (55% males, mean age at study,45years; SD±10years; mean age at diagnosis,6years; SD±5years), 779 (33%) attended at least one LTFU visit. Initial cancer-related factors associated with LTFU visit attendance were: treatment with both radiotherapy and chemotherapy (odds ratio [OR],4.02; 95% CI,2.11-7.70), bone sarcoma (OR,2.43; 95% CI,1.56-3.78), central nervous system primitive tumor (OR,1.65; 95% CI,1.02-2.67), and autologous hematopoietic cell transplant (OR,2.07; 95% CI,1.34-3.20). Late effects (OR,1.70; 95% CI,1.31-2.20), highest medical expenses (OR,1.65; 95% CI,1.22-2.22), living in the most advantaged area (OR vs. the most deprived area=1.60; 95% CI,1.15-2.22), and shorter distance from LTFU care center (<12miles) also increased attendance. Patients who are apparently healthy as well as socially disadvantaged and living far away from the center are less likely to attend LTFU care. Among 2341 adult childhood cancer survivors contacted between 2012 and 2020, 33% attended at least one long-term follow-up visit. Clinical factors related to attendance were multimodal treatment of first cancer (combining chemotherapy and radiotherapy), stem cell transplant, type of diagnosis (bone tumor and central nervous system primitive tumor), late effects (at least one disease among second malignancy, heart disease, or stroke), and highest medical expenses. In addition, the study identified social and spatial inequalities related to attendance, with independent negative effects of distance and social deprivation on attendance, even though the medical costs related to the long-term follow-up examinations are covered by the French social security system.