Census Tracts Research Articles

Differences in Patient-Reported Outcome Measures in Patients With Cancer Six Months Before Death.

Patient-reported outcome measures (PROMs) provide a direct report of the patient's perspective, complementary to clinician assessment. Currently, understanding the real-time changes in PROM scores near the end of life remains limited. This study evaluated differences in mean PROM scores between patients with cancer within 6 months before death compared with surviving patients with cancer. This retrospective case-control study uses the National Institutes of Health's Patient-Reported Outcomes Measurement Information System computer adaptive testing instruments to assess pain interference, physical function, fatigue, and depression. Patients dying within 6 months of PROM completion were selected as cases and matched to controls 1:3 by age at PROM completion, sex, cancer disease site, and cancer stage at diagnosis. Generalized estimating equation models assessed the difference in mean PROM score in cases compared with controls. A total of 461 cases and 1,270 controls from September 2020 to January 2023 were included. After adjustment for ethnicity, Charlson Comorbidity Index, and census tract median household income, significant differences in mean scores were demonstrated. Physical function domain showed the largest difference, with cases averaging 6.52 points lower than controls (95% CI, -8.25 to -4.80). Fatigue and pain interference domains showed a rise in PROMs scores by 4.83 points (95% CI, 2.94 to 6.72) and 4.33 points (95% CI, 2.53 to 6.12), respectively. Compared with controls, patients dying within 6 months of PROM completion demonstrated worse PROM scores in the four domains assessed. These findings suggest the utility of routinely collected PROMs as a real-time indicator of the terminal stage of life among patients with cancer to allow for earlier intervention with supportive oncology services.

Wealth disparities in maternal health service utilization among women of reproductive age in Ethiopia: findings from the mini-EDHS 2019

BackgroundEthiopia has made strides in reducing maternal mortality, but significant discrepancies in maternal health service utilization exist across socioeconomic levels. According to studies, women from higher-income households are far more likely to use essential services such as antenatal care, delivery care, and postnatal care than poorer women. This wealth disparity is a primary contributor to persistently high maternal mortality, particularly among poor populations. The study’s goal was to assess wealth disparities in maternal health service uptake and identify contributing factors.Methods and materialsWe used the Ethiopian Mini Demographic Health Survey (EMDHS), conducted in 2019 on women aged 15–49 living in selected census areas, with a weighted sample size of 3,909. The Erreygers Concentration Index (ECI) was used to measure wealth inequalities in maternal health care, and the ECI decomposition was used to identify factors contributing to inequality in maternal health services.ResultsMaternal health service utilization was pro-rich among women in Ethiopia. The prevalence of antenatal care service (ANC), delivery, and postnatal care (PNC) service utilization showed a pro-rich distribution among Ethiopian women, with ECI = 0.115 (95% CI: 0.091–0.137), ECI = 0.223 (95% CI: 0.191–0.276), and ECI = 0.121 (95% CI: 0.041-0.200), respectively. The ECI indices were decomposed to examine the contributing factors to disparities in maternal service utilization in Ethiopia. Mother’s current age, household family size, region, birth order, and parity were contributors to maternal health service utilization.ConclusionThe ANC service, delivery service and PNC service utilization showed a pro-rich distribution among Ethiopian women. Mother’s current age, household family size, region, birth order, and parity are important contributors of maternal health service inequality. To improve access and usage among low-income women, policymakers can develop programs including increasing the number of free or subsidized services and providing transportation.

Neighborhood Child Opportunity and Preterm Birth Rates by Race and Ethnicity

In the US, infants born to non-Hispanic Black birthing parents are 50% more likely to be born preterm than those born to non-Hispanic White birthing parents, and individual-level factors do not fully account for this inequity. Neighborhood context, rooted in historic patterns of structural racism, may facilitate understanding patterns of inequity in preterm birth. To estimate the association between neighborhood opportunity level, measured by the Child Opportunity Index (COI), and preterm birth among infants in Massachusetts. In this cross-sectional, population-based study, Massachusetts birth certificates from 3 large metropolitan areas (Boston, Springfield, and Worcester) were linked to US Census tract-level data from the COI, and log binomial regression models and generalized estimating equations were fit to examine associations of different levels of opportunity with preterm birth. Singleton infants born in Massachusetts between February 1, 2011, and December 31, 2015, were included. Analyses were originally conducted in 2019 and updated in 2024. Level of child opportunity (measured by the COI) at the US Census tract level. Race and ethnicity were ascertained from the birth certificate, as reported by the birthing parent. Live birth before 37 completed weeks' gestation. The analytic dataset included 267 553 infants, of whom 18.9% were born to Hispanic, 10.1% to non-Hispanic Asian or Pacific Islander, 10.1% to non-Hispanic Black, and 61.0% to non-Hispanic White birthing parents. More than half of infants born to non-Hispanic Black and Hispanic birthing parents were born into very low opportunity neighborhoods, and in crude models, this was associated with greater prevalence of preterm birth relative to very high opportunity neighborhoods (prevalence ratio, 1.44; 95% CI, 1.37-1.52). After adjustment for covariates, infants born into very low opportunity neighborhoods still had a greater prevalence of preterm birth (prevalence ratio, 1.16; 95% CI, 1.10-1.23). In this cross-sectional study of neighborhood opportunity and preterm birth, elevated risk associated with exposure to a very low opportunity neighborhood, coupled with the disproportionate exposure by race and ethnicity, points to a modifiable factor that may contribute to racial and ethnic inequities in preterm birth. Future research should investigate interventions that seek to address neighborhood opportunity.

Enhancing Sustainability: Quantifying and Mapping Vulnerability to Extreme Heat Using Socioeconomic Factors at the National, Regional and Local Levels

Population-dense urban areas often concentrate high commercial and industrial activity and intricate transportation systems. In crowded cities, extreme events can be even more damaging due to the high population they affect and the social inequalities that are likely to emerge. Extreme heat is a climate hazard that has been linked to high morbidity and mortality, especially in cities with high population densities. The way extreme heat events are felt in the population varies depending on a variety of factors, such as age, employment status, living conditions, air-conditioning, housing conditions, habits, behaviors and other socio-demographic parameters. In this article, we quantify and locate vulnerabilities of populations to extreme heat in order to formulate policy and practice recommendations that will make communities resilient and will shape the transition to a more sustainable future. This work contributes towards the achievement of Sustainable Development Goal 11—Sustainable Cities and Communities—by developing the tools to make cities and settlements resilient and sustainable. To this end, we analyze socioeconomic data at the NUTS3 level for the national case study of Greece and at the census tract level for the local case study of the city of Athens. The target variable for this study is defined as the average daily mortality during heatwaves per 100,000 individuals, and a methodology is developed for constructing this variable based on socioeconomic data available in public databases. The independent variables were selected based on their contribution to socioeconomic vulnerability; they include the percentage of elderly individuals, retirees, unemployed persons, renters, those living alone, those residing in smaller houses, those living in older houses and immigrants from developing countries. An ensemble gradient boosted tree model was employed for this study to obtain feature importance metrics that was used to construct a composite index of socioeconomic heat vulnerability. The socioeconomic heat vulnerability index (SHVI) was calculated for each prefecture in Greece and for each census tract in the city of Athens, Greece. The unique feature of this SHVI is that it can be applied to any geographical resolution using the same methodology and produces a result that is not only quantifiable, but also facilitates a comparison between vulnerability scores across different regions. This application aimed to map the SHVI of both prefecture and city, to examine the significance of scale, to identify vulnerability hotspots, and rank the most vulnerable areas, which are prioritized by authorities for interventions that protect public health.

Mediators of racial and ethnic inequities in clinical trial participation among patients with cancer, 2011-2023.

Although racially and ethnically minoritized populations are less likely to participate in cancer trials, it is unknown whether social determinants of health (SDOH) explain these inequities. Here we identify SDOH factors that contribute to racial and ethnic inequities in clinical trial participation among patients with 22 common cancers. This retrospective cohort study used electronic health record data (2011-2023) linked to neighborhood (US Census tract) data from multiple sources. Patients were followed from diagnosis to clinical study drug receipt (proxy for trial participation), death, or last recorded activity. Associations were assessed using Cox proportional hazards models adjusted for clinical factors (year of diagnosis, age, sex, performance status, disease stage, cancer type). To elucidate which area-level SDOH underlie racial and ethnic inequities, mediation analysis was performed using nonlinear multiple additive regression tree models. This study included 250 105 patients (64.7% non-Latinx White, 8.9% non-Latinx Black, 5.2% Latinx). Black and Latinx patients were more likely to live in economically or socially marginalized areas (eg, disproportionately minoritized [measure of segregation], limited English proficiency, low vehicle ownership) than White patients. Black (3.7%; hazard ratio = 0.55, 95% confidence interval [CI] = 0.52 to 0.60) and Latinx patients (4.4%; hazard ratio = 0.63, 95% CI = 0.58 to 0.69) were less likely to participate in trials than White patients (6.3%). Fewer patients in economically or socially marginalized neighborhoods participated in trials. Mediators explained 62.2% (95% CI = 49.5% to 74.8%) of participation inequities between Black and White patients; area-level SDOH-including segregation (29.9%, 95% CI = 21.2% to 38.6%) and vehicle ownership (11.6%, 95% CI = 7.0% to 16.1%)-were the most important mediators. Similarly, Latinx-White participation inequities were mediated (65.1%, 95% CI = 49.8% to 80.3%) by area-level SDOH, such as segregation (39.8%, 95% CI = 28.3% to 51.3%), limited English proficiency (11.6%, 95% CI = 2.8% to 20.4%), and vehicle ownership (9.6%, 95% CI = 5.8% to 13.5%). To improve racial and ethnic diversity in cancer trials, efforts to address barriers related to adverse neighborhood SDOH factors are necessary.

Abstract P365: Prevalence of Hypertension in Minnesota Adults in 2023 Using Data from a Statewide Electronic Health Record Consortium

Background: Data on prevalence of hypertension in the United States come primarily from in-person data collected by the National Health and Nutrition Examination Survey and self-reports in the Behavioral Risk Factor Surveillance Survey. Electronic phenotypic algorithms for hypertension that include diagnosis codes, blood pressure values, and antihypertensive treatment have been proposed and tested. Objective: To describe prevalence of hypertension in Minnesota adults using data from a statewide electronic health record (EHR) consortium, the Minnesota EHR Consortium (MNEHRC). Methods: Data from 11 health systems participating in the MNEHRC were standardized to a common data model allowing for distributed querying of EHR data. Data were de-duplicated using a one-way hash algorithm. Preliminary prevalence of hypertension in 2023 was estimated in Minnesota residents with ≥ 1 encounter in the past 3 years who had ≥1 diagnosis of hypertension in the past 5 years. Medicaid insurance status was determined via linkage with state enrollment files. Residential addresses of patients were geocoded to census tracts and social vulnerability index (SVI) of census tracts was determined. Results: Among 4,369,470 Minnesotan age 18 and older in 2023, 23.6% had hypertension based on ≥1 diagnosis code. Prevalence increased with age, was higher in men (26% vs. 22% in women), and adjusted for age and sex was highest in Black (30%) and Native American (27%) compared with White (23%) and Hispanic (21%) Minnesotans. Within each race/ethnic group, those insured by Medicaid had a higher adjusted hypertension prevalence than those with other insurance types. The prevalence of hypertension in census tracts with moderate to high SVI ranged from 3% to 43%, but on average was similar to the statewide prevalence of 24% (see image 1). Prevalence of hypertension in race/ethnicity, sex, and age subgroups in higher SVI census tracts was similar to the statewide prevalence in those subgroups. Conclusions: The prevalence of hypertension in Minnesota was described in detail by demographic characteristics, geography and social vulnerability. Future work will expand the electronic hypertension phenotype and examine quality of care.

Surgical subspecialist distribution and Social Vulnerability Indices in the inland empire

BackgroundAccess to surgical specialty care differs based on geographic location, insurance status, and subspecialty type. This study uses the Inland Empire as a model to determine the relationship between Social Vulnerability Indices (SVIs), surgeon sex, and surgical subspecialty distribution. Methods823 census tracts from the Centers for Disease Control's (CDC) SVI 2018 database were compared against 992 surgeons within 30 distinct subspecialties. This data was retrieved from the American Medical Association's (AMA) 2018 Physician Masterfile. Spearman's bivariate and multiple regression were used to compare the relationship between SVI and number of surgical subspecialists within each census tract. ResultsThere were approximately 3.34 male and 0.35 female surgeons per census tract (t(267) = 7.74, p < 0.001). Significant inverse relationships existed between Cosmetic surgery, Urology and Minority status/language (ρ = −0.131 [95 % CI −1.000 to −0.028], p = 0.016; ρ = −0.142 [95 % CI −1.000 to −0.039], p = 0.010, respectively); General surgery, Socioeconomic status (ρ = −0.118 [95 % CI −1.000 to −0.014], p = 0.027), and Household composition/disability (ρ = −0.203 [95 % CI −1.000 to −0.102], p < 0.001); Hand surgery and Socioeconomic status (ρ = −0.114 [95 % CI −1.000 to −0.010], p = 0.031); Otolaryngology, Housing type/transportation (ρ = −0.102 [95 % CI −1.000 to 0.001], p = 0.047), and Overall Social Vulnerability (ρ = −0.105 [95 % CI −1.000 to −0.001], p = 0.043). Multiple regression analyses reinforced these findings. ConclusionsThis study concludes that social vulnerability is predictive of, and significantly linked to, differences in distribution of surgical subspecialty and surgeon gender. Future research should investigate recruitment of a diverse surgical workforce, infrastructural barriers to care, and differences in quality of care. Key messageOur work demonstrates complex relationships between surgical subspecialist distribution, surgeon gender, and a census tract's various Social Vulnerability Indices. Thus, this research can serve to continue educating surgeons and other healthcare providers about the importance of social determinants of health in the construction of healthcare policy and practice, as well as incentivizing equitable recruitment of a diverse population of surgeons.

Spatial Variability in Relationships between Early Childhood Lead Exposure and Standardized Test Scores in Fourth Grade North Carolina Public School Students (2013-2016).

Exposure to lead during childhood is detrimental to children's health. The extent to which the association between lead exposure and elementary school academic outcomes varies across geography is not known. Estimate associations between blood lead levels (BLLs) and fourth grade standardized test scores in reading and mathematics in North Carolina using models that allow associations between BLL and test scores to vary spatially across communities. We link geocoded, individual-level, standardized test score data for North Carolina public school students in fourth grade (2013-2016) with detailed birth records and blood lead testing data retrieved from the North Carolina childhood blood lead state registry on samples typically collected at 1-6 y of age. BLLs were categorized as: (reference), , and . We then fit spatially varying coefficient models that incorporate information sharing (smoothness), across neighboring communities via a Gaussian Markov random field to provide a global estimate of the association between BLL and test scores, as well as census tract-specific estimates (i.e., spatial coefficients). Models adjusted for maternal- and child-level covariates and were fit separately for reading and math. The average BLL across the 91,706 individuals in the analysis dataset was . Individuals were distributed across 2,002 (out of 2,195) census tracts in North Carolina. In models adjusting for child sex, birth weight percentile for gestational age, and Medicaid participation as well as maternal race/ethnicity, educational attainment, marital status, and tobacco use, BLLs of , and were associated with overall lower reading test scores of [95% confidence interval (CI): , ], (, ), and (, ), respectively. For BLLs of , , and , spatial coefficients-that is, tract-specific adjustments in reading test score relative to the "global" coefficient-ranged from to 2.52, to 3.90, to 7.85, and to 4.33, respectively. Results for mathematics were similar to those for reading. The association between lead exposure and reading and mathematics test scores exhibits considerable heterogeneity across North Carolina communities. These results emphasize the need for prevention and mitigation efforts with respect to lead exposures everywhere, with special attention to locations where the cognitive impact is elevated. https://doi.org/10.1289/EHP13898.

Federal Firearm Licensee Rates and Suicide in Maryland, 2014 to 2019

Federal firearm licensee density is associated with interpersonal firearm violence. Yet the role of Federal firearm licensees in firearm suicide remains understudied, even though firearms are the method used in more than half of suicides. This study tested associations between the spatial distribution of federal firearm licensees and firearm suicides in Maryland. Kernel density estimation measured federal firearm licensee and suicide rates at the census tract level (n=1,397), and SaTScan detected clusters of licensees and suicides. Choropleth maps compared visual associations between federal firearm licensee, firearm, and non-firearm suicide rates and clusters. Generalized estimating equations tested associations between Federal firearm licensee rates and clusters and the odds of using a firearm as the lethal means overall and after stratifying by biological sex. Data were obtained in 2020 and analyzed in 2020-2024. The federal firearm licensee rate was associated with greater odds of firearm suicide overall (aOR=1.29, 95% CI=1.21, 1.38, p<0.001), for men (aOR=1.29, 95% CI=1.20, 1.39, p<0.001), and for women (aOR=1.26, 95% CI=1.07, 1.49, p=0.007). Suicide decedents in a census tract located in a federal firearm licensee cluster (vs not) had higher odds of firearm use overall (aOR=1.70, 95% CI=1.28, 2.27, p<0.001) and for men (aOR=1.67, 95% CI=1.22, 2.27, p=0.001), but not for women (aOR=1.65, 95% CI=0.81, 3.34, p=0.168). The federal firearm licensee rate and clusters were associated with firearm suicides and unrelated to the spatial distribution of non-firearm suicides. Prevention approaches that limit the number of these federal firearm licensees or alter their sales practices, such as federal firearm licensee zoning and land use provisions, advertising restrictions, or gun shop projects, may prevent firearm suicides.

Socioeconomic disparities based on shooting intent in pediatric firearm injury.

Pediatric firearm injury is often associated with socioeconomically disadvantaged neighborhoods. Most studies only include fatal injuries and do not differentiate by shooting intent. We hypothesized that differences in neighborhood socioeconomic disadvantage would be observed among shooting intents of fatal and nonfatal cases. A linked integrated database of pediatric fatal and nonfatal firearm injuries was developed from trauma center and medical examiner records in Harris County, Texas (2018-2020). Geospatial analysis was utilized to map victim residence locations, stratified by shooting intent. Area Deprivation Index (ADI), a composite measure of neighborhood socioeconomic disadvantage at the census tract level was linked to shooting intent. Differences in high ADI (more deprived) versus low ADI among the shooting intents were assessed. Unadjusted and adjusted regression models assessed differences in ADI scores across shooting intent, adjusted models controlled for age, gender, and race/ethnicity. Of 324 pediatric firearm injuries, 28% were fatal; 77% were classified as interpersonal violence, 15% unintentional, and 8% self-harm. Differences were noted among shooting intent across the ADI quartiles; with increases in ADI score, the odds of interpersonal violence injuries compared with self-harm injuries significantly increased by 5%; however, when adjusting for individual-level variables of age, gender, and race and ethnicity, no significant differences in ADI were noted. Our results suggest that children living in disadvantaged neighborhoods are more likely to be affected by interpersonal firearm violence compared with self-harm; however, when differences in race/ethnicity are considered, the differences attributable to neighborhood-level disadvantage disappeared. Resources should be dedicated to improving structural aspects of neighborhood disadvantage, which disproportionately impact racial/ethnic minoritized populations. Furthermore, firearm self-harm injuries occurred among children living in the less disadvantaged neighborhoods. Understanding the associations among individual and neighborhood-level factors are important for developing streamlined injury prevention interventions by shooting intent. Prognostic and Epidemiological; Level IV.

Abstract MP20: Leveraging Electronic Health Records to Assess Neighborhood Advantages and Risk of Cardiovascular Outcomes Among Hypertensive Patients

Introduction: Hypertension disproportionately impacts socially disadvantaged groups in the U.S. with increasing prevalence and suboptimal control rates. Our study aims to examine the association between neighborhood-level social vulnerability and hypertension outcomes using electronic health record (EHR) data from a large regional health system. Methods: We conducted a retrospective analysis of EHR data from the Sentara Health System, covering the period from January 1st, 2010, to December 31st, 2022. We assigned a Social Vulnerability Index (SVI) based on the residential census tract of each patient and established a longitudinal cohort of patients who consistently utilized healthcare services. To be included in the study, patients were required to have a minimum of five years of observational time and to have healthcare visits in at least 50% of the observed years. The study focused on patients diagnosed with hypertension—either through a hypertension diagnosis, a blood pressure measurement exceeding 140/90, or antihypertensive medication prescriptions. We utilized multivariate Cox Proportional Hazards models to analyze the associations of SVI with cardiovascular outcomes and blood pressure control (&lt;140/90 mmHg). Results: The longitudinal cohort consisted of 55,060 patients, with an average age of 54 years (Interquartile range: 42-65), 30.0% of whom were Black adults and 60.0% were females. Compared to patients residing in the most advantaged neighborhoods (quartile 1 of SVI), those in more disadvantaged neighborhoods (quartiles 2, 3, and 4) had hazard ratios for composite cardiovascular endpoint (myocardial infarction, heart failure, and stroke) of 1.22 (95% CI, 1.19-1.25), 1.40 (95% CI, 1.37-1.44), and 1.64 (95% CI, 1.60-1.68), respectively, after adjustment for age and sex. Additionally, blood pressure control was significantly lower in higher SVI quartiles, with control rates in quartiles 1 through 4 at 78.4%, 76.5%, 75.2%, and 72.8%, respectively (P&lt;0.001). Among the SVI themes, socioeconomic status (theme 1) and housing type and transportation (theme 4) were associated with the highest hazard ratios for cardiovascular outcomes. Conclusions: Neighborhood-level social vulnerability is significantly associated with worse hypertension control and adverse cardiovascular outcomes. Health systems can employ tailored interventions targeting high-risk neighborhoods to reduce disparities and enhance health outcomes for vulnerable populations.

Geographic Variations in Urban‐Rural Particulate Matter (PM2.5) Concentrations in the United States, 2010–2019

AbstractFine particulate matter 2.5 (PM2.5) is a widely studied pollutant with substantial health impacts, yet little is known about the urban‐rural differences across the United States. Trends of PM2.5 in urban and rural census tracts between 2010 and 2019 were assessed alongside sociodemographic characteristics including race/ethnicity, poverty, and age. For 2010, we identified 13,474 rural tracts and 59,065 urban tracts. In 2019, 13,462 were rural and 59,055 urban. Urban tracts had significantly higher PM2.5 concentrations than rural tracts during this period. Levels of PM2.5 were lower in rural tracts compared to urban and fell more rapidly in rural than urban. Rural tract annual means for 2010 and 2019 were 8.51 [2.24] μg/m3 and 6.41 [1.29] μg/m3, respectively. Urban tract annual means for 2010 and 2019 were 9.56 [2.04] μg/m3 and 7.51 [1.40] μg/m3, respectively. Rural and urban majority Black communities had significantly higher PM2.5 pollution levels (10.19 [1.64] μg/m3 and 9.79 [1.10] μg/m3 respectively), in 2010. In 2019, they were: 7.75 [1.1] μg/m3 and 7.09 [0.78] μg/m3, respectively. Majority Hispanic communities had higher PM2.5 levels and were the highest urban concentration among all races/ethnicities (8.01 [1.73] μg/m3), however they were not the highest rural concentration among all races/ethnicities (6.22 [1.60] μg/m3) in 2019. Associations with higher levels of PM2.5 were found with communities in the poorest quartile and with higher proportions of residents age&lt;15 years old. These findings suggest greater protections for those disproportionately exposed to PM2.5 are needed, such as, increasing the availability of low‐cost air quality monitors.

49636 Social Determinants of Health and Hidradenitis Suppurativa Disease Severity: A Geocoded and Census Tract Level Analysis

49636 Social Determinants of Health and Hidradenitis Suppurativa Disease Severity: A Geocoded and Census Tract Level Analysis

Correlation of Patient-Reported Social Determinants of Health With Census Tract Measures of Socioeconomic Disadvantage in Patients With GI Cancers in Eastern North Carolina.

Investigating the impact of social determinants of health (SDOHs) on cancer care in large populations relies on census estimates. Routine clinic SDOH screening provides timely patient-level information which could inform best practices. This study evaluated the correlation between patient-reported SDOH needs and population-level census tract measures. This was a retrospective cross-sectional study of a cohort of adult patients with GI malignancy screened for SDOHs such as financial insecurity, transportation, and food insecurity during initial outpatient evaluation at East Carolina University (formerly Vidant) Health Medical Center in Greenville, NC (November 2020-July 2021). Primary outcomes included number and severity of identified SDOH needs and area deprivation index (ADI) and census tract measures for each patient. Spearman rank correlations were calculated among patient-level needs and between patient-level needs and similar census tract measures. Of 112 patients screened, 58.9% self-identified as White (n = 66) and 41.1% as Black (n = 46). A total of 50.5% (n = 54) resided in a rural county. The collective median state ADI rank was 7 (IQR, 5-9). The median household income was $38,125 in US dollars (USD) (IQR, $31,436-$48,934 [USD]). Only 12.5% (n = 14) reported a moderate or severe financial need. Among reported needs, financial need moderately correlated with food insecurity (coefficient, 0.46; P < .001) and transportation (coefficient, 0.45; P < .001). Overall, census tract measures and reported needs poorly correlated. Lack of transportation correlated with percentage of households without a vehicle (coefficient, 0.18; P = .03) and limited access to healthy foods (coefficient, 0.18; P = .04). Given the poor correlation between reported and census needs, population-level measures may not accurately predict patient-reported needs. These findings highlight the importance of SDOH screening in the clinical setting to reduce health disparities and identify opportunities to improve care delivery.

Estimating primary substation boundaries and the value of mapping Great Britain's electrical network infrastructure

Localised data aggregation in many countries including Great Britain (GB) is typically performed at a geographical level with polygon boundaries that have a robust and trusted governance system in place. This means there is confidence in a process to create a set of polygons that have unique identifiers coupled to geographical areas, and the ability to have these updated through a defined code of practice. Examples found across many countries are in the delivery of post, such as post codes and zip codes, and of the definition of census areas and municipal boundaries. The confidence in these boundaries allows different data to be aggregated by third parties, which itself provides greater amounts of data over comparable geographical areas to enhance wider analysis and decision making. As helpful as these polygons are for certain types of analyses, they are not specifically defined for energy systems analysis. Here we combine publicly available datasets published from the six regional electricity Distribution Network Operators of GB to produce a new geospatial dataset with 4436 unique polygons defining the areas served by electrical primary substations. An example demonstrating the value of these polygons is given to link these polygons with postcode level open government datasets on domestic energy consumption (2015–2020) from the Department of Energy Security and Net Zero (DESNZ). The resulting new data reflects energy statistics aggregated to the geographical areas served by each primary electrical substation across Great Britain. The significant value of the generated data is demonstrated by the quantification of the domestic annual heating demand presently met by natural gas across different primary substation areas which varies from an average of 5100 kWh to 28,900 kWh per property. This highlights how the rate of electrical capacity expansion will have to differ by geography under an electrified heating scenario. Therefore, we believe there is a compelling argument for all countries to set up processes to create and update polygons that have a meaningful relationship to energy systems. This would allow more accurate energy systems analysis to be performed, ultimately leading to an accelerated or potentially lower cost transition to a net zero world.

Workplace Exposures Vary Across Neighborhoods in the US: Implications on Social Vulnerability and Racial/Ethnic Health Disparities.

Ignoring workplace exposures that occur beyond the local residential context in place-based risk indices like the CDC's Social Vulnerability Index (SVI) likely misclassifies community exposure by under-counting risks and obscuring true drivers of racial/ethnic health disparities. To investigate this hypothesis, we developed several place-based indicators of occupational exposure and examined their relationships with race/ethnicity, SVI, and health inequities. We used publicly available job exposure matrices and employment estimates from the United States (US) Census to create and map six indicators of occupational hazards for every census tract in the US. We characterized census tracts with high workplace-low SVI scores. We used natural cubic splines to examine tract level associations between the percentage of racial/ethnic minorities (individuals who are not non-Hispanic White) and the occupational indicators. Lastly, we stratified each census tract into high/low occupational noise, chemical pollutant, and disease/infection exposure to examine racial/ethnic health disparities to diabetes, asthma, and high blood pressure, respectively, as a consequence of occupational exposure inequities. Our results show that racial/ethnic minority communities, particularly those that are also low-income, experience a disproportionate burden of workplace exposures that may be contributing to racial/ethnic health disparities. When composite risk measures, such as SVI, are calculated using only information from the local residential neighborhood, they may systematically under-count occupational risks experienced by the most vulnerable communities. There is a need to consider the role of occupational justice on nationwide, racial/ethnic health disparities.

Impact of social vulnerability index on patients with alcohol-related liver disease

IntroductionAlcohol related liver disease (ALD) affects diverse communities with individual and social characteristics that can impact outcomes. The social vulnerability index (SVI) assigns a score between 0 and 1, where higher scores represent an increased risk of social vulnerability. We sought to assess the impact of SVI on outcomes of patients hospitalized with ALD with access to social support services. Methods and materialsHospitalizations for ALD at our institution between March and August 2019 were reviewed. All patients were assigned an SVI score based on their residential census tract. Per our standard practice, patients were screened by care coordinators to identify needs for rehabilitation counseling, and care coordination after discharge. Demographics, hepatic decompensation, critical care needs, readmission, and mortality were compared. ResultsAmong 73 patients admitted for alcoholic hepatitis, 32 had a low SVI and 42 had a high SVI. African American patients were more likely to have a higher SVI (35% vs 0%, p=<0.001). No significant difference in outcomes based on SVI was noted.There were 393 patients admitted for alcoholic cirrhosis including 166 with a low SVI and 227 with a high SVI. Patients that were African American (23.6% vs 5.5%, p=<0.001) or disabled (41.4% vs 29.5%, p = 0.008) had a higher SVI. No significant difference in outcomes based on SVI was noted. ConclusionMost patients admitted for ALD had a high SVI; however, SVI did not impact hospitalization outcomes.

The heart of the matter: neighborhood violent crime and deprivation, cardiometabolic disease, and the racial invariance thesis

ABSTRACT Studies have observed a tight spatial coupling of elevated violent crime rates, structural deprivation, and cardiometabolic disease prevalence across geographic areas. Conceptual perspectives in the health sciences provide a framework to explain this geographic concentration of poor health and crime, which differs from perspectives derived from macro-level criminology. Drawing on these different conceptual approaches, the current study uses administrative and survey data aggregated to Census tracts to examine whether violent crime and structural deprivation are factors for cardiometabolic disease prevalence. Drawing on the racial invariance thesis, the study also tests whether these patterns are invariant across neighborhoods of different racial and ethnic compositions. Multivariate results reveal that cardiometabolic disease varies directly with levels of violent crime but not structural deprivation. Furthermore, the results do not provide consistent support for the racial and ethnic invariance hypothesis. We discuss the implications of the findings for prevention models focused on modifiable risk factors of poor health in local geographic areas.

High-resolution population maps derived from Sentinel-1 and Sentinel-2

Detailed population maps play an important role in diverse fields ranging from humanitarian action to urban planning. Generating such maps in a timely and scalable manner presents a challenge, especially in data-scarce regions. To address it we have developed Popcorn, a population mapping method whose only inputs are free, globally available satellite images from Sentinel-1 and Sentinel-2; and a small number of aggregate population counts over coarse census districts for calibration. Despite the minimal data requirements our approach surpasses the mapping accuracy of existing schemes, including several that rely on building footprints derived from high-resolution imagery. E.g., we were able to produce population maps for Rwanda with 100m GSD based on less than 400 regional census counts. In Kigali, those maps reach an R2 score of 66% w.r.t. a ground truth reference map, with an average error of only ±10 inhabitants/ha. Conveniently, Popcorn retrieves explicit maps of built-up areas and local building occupancy rates, making the mapping process interpretable and offering additional insights, for instance about the distribution of built-up, but unpopulated areas, e.g., industrial warehouses. With our work we aim to democratize access to up-to-date and high-resolution population maps, recognizing that some regions faced with particularly strong population dynamics may lack the resources for costly micro-census campaigns. Project page: https://popcorn-population.github.io/.

Developing equity-aware safety performance functions for identifying hotspots of pedestrian-involved crashes

Crashes are frequently disproportionally observed in disadvantaged areas. Despite the evident disparities in transportation safety, there has been limited exploration of quantitative approaches to incorporating equity considerations into road safety management. This study proposes a novel concept of equity-aware safety performance functions (SPFs), enabling a distinct treatment of equity-related variables such as race and income. Equity-aware SPFs introduce a fairness distance and integrate it into the log-likelihood function of the negative binomial regression as a form of partial lasso regularization. A parameter λ is used to control the importance of the regularization term. Equity-aware SPFs are developed for pedestrian-involved crashes at the census tract level in Virginia, USA, and then employed to compute the potential for safety improvement (PSI), a prevalent metric used in hotspot identification. Results show that equity-aware SPFs can diminish the effects of equity-related variables, including poverty ratio, black ratio, Asian ratio, and the ratio of households without vehicles, on the expected crash frequencies, generating higher PSIs for disadvantaged areas. Based on the results of Wilcoxon signed-rank tests, it is evident that there are significant differences in the rankings of PSIs when equity awareness is considered, especially for disadvantaged areas. This study adds to the literature a new quantitative approach to harmonize equity and effectiveness considerations, empowering more equitable decision-making in safety management, such as allocating resources for safety enhancement.