Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Trends in Disparities in Advanced Neuroimaging Utilization in Acute Stroke: A Population-Based Study.

BACKGROUND: Our primary objective was to evaluate if disparities in race, sex, age, and socioeconomic status (SES) exist in utilization of advanced neuroimaging in year 2015 in a population-based study. Our secondary objective was to identify the disparity trends and overall imaging utilization as compared with years 2005 and 2010. METHODS: This was a retrospective, population-based study that utilized the GCNKSS (Greater Cincinnati/Northern Kentucky Stroke Study) data. Patients with stroke and transient ischemic attack were identified in the years 2005, 2010, and 2015 in a metropolitan population of 1.3 million. The proportion of imaging use within 2 days of stroke/transient ischemic attack onset or hospital admission date was computed. SES determined by the percentage below the poverty level within a given respondent's US census tract of residence was dichotomized. Multivariable logistic regression was used to determine the odds of advanced neuroimaging use (computed tomography angiogram/magnetic resonance imaging/magnetic resonance angiogram) for age, race, gender, and SES. RESULTS: There was a total of 10 526 stroke/transient ischemic attack events in the combined study year periods of 2005, 2010, and 2015. The utilization of advanced imaging progressively increased (48% in 2005, 63% in 2010, and 75% in 2015 [P<0.001]). In the combined study year multivariable model, advanced imaging was associated with age and SES. Younger patients (≤55 years) were more likely to have advanced imaging compared with older patients (adjusted odds ratio, 1.85 [95% CI, 1.62-2.12]; P<0.01), and low SES patients were less likely to have advanced imaging compared with high SES (adjusted odds ratio, 0.83 [95% CI, 0.75-0.93]; P<0.01). A significant interaction was found between age and race. Stratified by age, the adjusted odds of advanced imaging were higher for Black patients compared with White patients among older patients (>55 years; adjusted odds ratio, 1.34 [95% CI, 1.15-1.57]; P<0.01), but no racial differences among the young. CONCLUSIONS: Racial, age, and SES-related disparities exist in the utilization of advanced neuroimaging for patients with acute stroke. There was no evidence of a change in trend of these disparities between the study periods.

Association of Neighborhood Recreation Centers and Poststroke Outcomes in a Population-Based Cohort.

BACKGROUND: Higher neighborhood socioeconomic status has been favorably associated with stroke outcomes. This may be due to these areas having more beneficial resources such as recreational centers. We aimed to determine if neighborhood density of recreation centers is favorably associated with stroke outcomes. METHODS: We conducted analyses of data from the Brain Attack Surveillance in Corpus Christi project, a cohort of stroke survivors ≥45 years of age residing in Nueces County, TX (2009-2020). We included non-Hispanic White and Mexican American incident stroke survivors, who were not institutionalized prestroke and completed baseline and follow-up assessments (N=1392). We calculated the density of fitness and recreational sports centers within their residential census tract during the year of their stroke. Outcomes included function (self-ratings on activities of daily living and instrumental activities of daily living), cognition (modified mini-mental state exam), depression (Patient Health Questionnaire-8), and quality of life (abbreviated Stroke-Specific Quality of Life Scale). We fit confounder-adjusted gamma-distributed mixed generalized linear models with a log link for each outcome and considered interaction with stroke severity. RESULTS: On average, participants were 65 years old, 53% male, and 63% Mexican American. Median recreational centers were 1.60 per square mile (interquartile range, 0.41-3.06). Among moderate-severe stroke survivors, greater density of recreation centers (75th versus 25th percentile) was associated with more favorable function and possibly quality of life (activities of daily living/instrumental activities of daily living, 4.8% change [95% CI, -0.11% to -9.27%]; Stroke-Specific Quality of Life Scale, 3.7% change [95% CI, -0.7% to 8.2%]). Minimal nonsignificant differences were observed among the overall stroke population and those with mild stroke. CONCLUSIONS: The availability of recreation centers may be beneficial for poststroke function and quality of life among those with moderate-severe stroke. If further research confirms recreation centers to be beneficial, this could inform rehabilitation following stroke.

Relationships Between Patient Race and Residential Race Context With Missed Human Immunodeficiency Virus Care Visits in the United States, 2010-2015.

BACKGROUND: Racial inequities exist in retention in human immunodeficiency virus (HIV) care and multilevel analyses are needed to contextualize and address these differences. Leveraging data from a multisite clinical cohort of people with HIV (PWH), we assessed the relationships between patient race and residential characteristics with missed HIV care visits. METHODS: Medical record and patient-reported outcome (PRO; including mental health and substance-use measures) data were drawn from 7 participating Center for AIDS Research Network of Integrated Clinical Systems (CNICS) sites including N = 20 807 PWH from January 2010 through December 2015. Generalized estimating equations were used to account for nesting within individuals and within census tracts in multivariable models assessing the relationship between race and missed HIV care visits, controlling for individual demographic and health characteristics and census tract characteristics. RESULTS: Black PWH resided in more disadvantaged census tracts, on average. Black PWH residing in census tracts with higher proportion of Black residents were more likely to miss an HIV care visit. Non-Black PWH were less likely to miss a visit regardless of where they lived. These relationships were attenuated when PRO data were included. CONCLUSIONS: Residential racial segregation and disadvantage may create inequities between Black PWH and non-Black PWH in retention in HIV care. Multilevel approaches are needed to retain PWH in HIV care, accounting for community, healthcare setting, and individual needs and resources.

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study.

BACKGROUND: Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE: This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS: Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS: Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS: The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

The impact of socioeconomic status on telemedicine utilization during the COVID-19 pandemic among surgical clinics at an academic tertiary care center.

BACKGROUND: The COVID-19 pandemic caused many surgical providers to conduct outpatient evaluations using remote audiovisual conferencing technology (i.e., telemedicine) for the first time in 2020. We describe our year-long institutional experience with telemedicine in several general surgery clinics at an academic tertiary care center and examine the relationship between area-based socioeconomic measures and the likelihood of telemedicine participation. METHODS: We performed a retrospective review of our outpatient telemedicine utilization among four subspecialty clinics (including two acute care and two elective surgery clinics). Geocoding was used to link patient visit data to area-based socioeconomic measures and a multivariable analysis was performed to examine the relationship between socioeconomic indicators and patient participation in telemedicine. RESULTS: While total outpatient visits per month reached a nadir in April 2020 (65% decrease in patient visits when compared to January 2020), there was a sharp increase in telemedicine utilization during the same month (38% of all visits compared to 0.8% of all visits in the month prior). Higher rates of telemedicine utilization were observed in the two elective surgery clinics (61% and 54%) compared to the two acute care surgery clinics (14% and 9%). A multivariable analysis demonstrated a borderline-significant linear trend (p = 0.07) between decreasing socioeconomic status and decreasing odds of telemedicine participation among elective surgery visits. A sensitivity analysis to examine the reliability of this trend showed similar results. CONCLUSION: Telemedicine has many patient-centered benefits, and this study demonstrates that for certain elective subspecialty clinics, telemedicine may be utilized as the preferred method for surgical consultations. However, to ensure the equitable adoption and advancement of telemedicine services, healthcare providers will need to focus on mitigating the socioeconomic barriers to telemedicine participation.

Availability of medical cannabis services by racial, social, and geographic characteristics of neighborhoods in New York: a cross-sectional study.

BACKGROUND: Within the United States (US), because racial/ethnic disparities in cannabis arrests continue, and cannabis legalization is expanding, understanding disparities in availability of legal cannabis services is important. Few studies report mixed findings regarding disparities in availability of legal cannabis services; none examined New York. We examined disparities in availability of medical cannabis services in New York. We hypothesized that New York census tracts with few Black or Hispanic residents, high incomes, high education levels, and greater urbanicity would have more medical cannabis services. METHODS: In this cross-sectional study, we used data from the 2018 US Census Bureau 5-year American Community Survey and New York Medical Marijuana Program. Main exposures were census tract characteristics, including urban-rural classification, percentage of Black and Hispanic residents, percentage of residents with bachelor's degrees or higher, and median household income. Main outcomes were presence of at least one medical cannabis certifying provider and dispensary in each census tract. To compare census tracts' characteristics with (vs. without) certifying providers and dispensaries, we used chi-square tests and t-tests. To examine characteristics independently associated with (vs. without) certifying providers, we used multivariable logistic regression. RESULTS: Of 4858 New York census tracts, 1073 (22.1%) had medical cannabis certifying providers and 37 (0.8%) had dispensaries. Compared to urban census tracts, suburban census tracts were 62% less likely to have at least one certifying provider (aOR = 0.38; 95% CI = 0.25-0.57). For every 10% increase in the proportion of Black residents, a census tract was 5% less likely to have at least one certifying provider (aOR = 0.95; 95% CI = 0.92-0.99). For every 10% increase in the proportion of residents with bachelor's degrees or higher, a census tract was 30% more likely to have at least one certifying provider (aOR = 1.30; 95% CI = 1.21-1.38). Census tracts with (vs. without) dispensaries were more likely to have a higher percentage of residents with bachelor's degrees or higher (43.7% vs. 34.1%, p < 0.005). CONCLUSIONS: In New York, medical cannabis services are least available in neighborhoods with Black residents and most available in urban neighborhoods with highly educated residents. Benefits of legal cannabis must be shared by communities disproportionately harmed by illegal cannabis.

Marked Reduction of Socioeconomic and Racial Disparities in Invasive Pneumococcal Disease Associated With Conjugate Pneumococcal Vaccines.

BACKGROUND: It is not known whether reductions in socioeconomic and racial disparities in incidence of invasive pneumococcal disease (defined as the isolation of Streptococcus pneumoniae from a normally sterile body site) noted after pneumococcal conjugate vaccine (PCV) introduction have been sustained. METHODS: Individual-level data collected from 20 Tennessee counties participating in Active Bacterial Core surveillance over 19 years were linked to neighborhood-level socioeconomic factors. Incidence rates were analyzed across 3 periods-pre-7-valent PCV (pre-PCV7; 1998-1999), pre-13-valent PCV (pre-PCV13; 2001-2009), and post-PCV13 (2011-2016)-by socioeconomic factors. RESULTS: A total of 8491 cases of invasive pneumococcal disease were identified. Incidence for invasive pneumococcal disease decreased from 22.9 (1998-1999) to 17.9 (2001-2009) to 12.7 (2011-2016) cases per 100 000 person-years. Post-PCV13 incidence (95% confidence interval [CI]) of PCV13-serotype disease in high- and low-poverty neighborhoods was 3.1 (2.7-3.5) and 1.4 (1.0-1.8), respectively, compared with pre-PCV7 incidence of 17.8 (15.7-19.9) and 6.4 (4.9-7.9). Before PCV introduction, incidence (95% CI) of PCV13-serotype disease was higher in blacks than whites (17.3 [15.1-19.5] vs 11.8 [10.6-13.0], respectively); after introduction, PCV13-type disease incidence was greatly reduced in both groups (white: 2.7 [2.4-3.0]; black: 2.2 [1.8-2.6]). CONCLUSIONS: Introduction of PCV13 was associated with substantial reductions in overall incidence and socioeconomic and racial disparities in PCV13-serotype incidence.

Improving Estimates of Neighborhood Change with Constant Tract Boundaries.

Social scientists routinely rely on methods of interpolation to adjust available data to their research needs. Spatial data from different sources often are based on different geographies that need to be reconciled, and some boundaries (e.g., administrative or political boundaries) change frequently. This study calls attention to the potential for substantial error in efforts to harmonize data to constant boundaries using standard approaches to areal and population interpolation. The case in point is census tract boundaries in the United States, which are redefined before every decennial census. Research on neighborhood effects and neighborhood change rely heavily on estimates of local area characteristics for a consistent area of time, for which they now routinely use estimates based on interpolation offered by sources such as the Neighborhood Change Data Base (NCDB) and Longitudinal Tract Data Base (LTDB). We identify a fundamental problem with how these estimates are created, and we reveal an alarming level of error in estimates of population characteristics in 2000 within 2010 boundaries. We do this by comparing estimates from one of these sources (the LTDB) to true values calculated by re-aggregating original 2000 census microdata to 2010 tract areas. We then demonstrate an alternative approach that allows the re-aggregated values to be publicly disclosed, using "differential privacy" (DP) methods to inject random noise that meets Census Bureau standards for protecting confidentiality of the raw data. We show that the DP estimates are considerably more accurate than the LTDB estimates based on interpolation, and we examine conditions under which interpolation is more susceptible to error. This study reveals cause for greater caution in the use of interpolated estimates from any source. Until and unless DP estimates can be publicly disclosed for a wide range of variables and years, research on neighborhood change should routinely examine data for signs of estimation error that may be substantial in a large share of tracts that experienced complex boundary changes.

Relationship Between Census Tract-Level Poverty and Domestically Acquired Salmonella Incidence: Analysis of Foodborne Diseases Active Surveillance Network Data, 2010-2016.

BACKGROUND: The relationships between socioeconomic status and domestically acquired salmonellosis and leading Salmonella serotypes are poorly understood. METHODS: We analyzed surveillance data from laboratory-confirmed cases of salmonellosis from 2010-2016 for all 10 Foodborne Disease Active Surveillance Network (FoodNet) sites, having a catchment population of 47.9 million. Case residential data were geocoded, linked to census tract poverty level, and then categorized into 4 groups according to census tract poverty level. After excluding those reporting international travel before illness onset, age-specific and age-adjusted salmonellosis incidence rates were calculated for each census tract poverty level, overall and for each of the 10 leading serotypes. RESULTS: Of 52 821geocodable Salmonella infections (>96%), 48 111 (91.1%) were domestically acquired. Higher age-adjusted incidence occurred with higher census tract poverty level (P < .001; relative risk for highest [≥20%] vs lowest [<5%] census tract poverty level, 1.37). Children <5 years old had the highest relative risk (2.07). Although this relationship was consistent by race/ethnicity and by serotype, it was not present in 5 FoodNet sites or among those aged 18-49 years. CONCLUSION: Children and older adults living in higher-poverty census tracts have had a higher incidence of domestically acquired salmonellosis. There is a need to understand socioeconomic status differences for risk factors for domestically acquired salmonellosis by age group and FoodNet site to help focus prevention efforts.

Mixed measures: different definitions of racially diverse neighborhoods compared.

Focusing on neighborhoods that researchers consider particularly diverse, this paper assesses the ways scholars have characterized neighborhood racial diversity in the United States. Social scientists use a variety of methods to define and measure highly racially diverse places, resulting in a single label being used to capture very different aspects of a census tract's racial demography. We examine the criteria used to classify neighborhood racial diversity to bring perspective on the logic behind various approaches. We then group the range of schemas into several broad types from which we choose a representative four. These form the basis for a series of empirical comparisons using U.S. Census data to reveal the contexts where the taxonomies produce similar outcomes and those where they do not. The analysis goes on to consider the implications stemming from the choices social scientists make when they opt for one approach over another.

Neighborhood Poverty and Control of HIV, Hypertension, and Diabetes in the Women's Interagency HIV Study.

Neighborhoods with high poverty rates have limited resources to support residents' health. Using census data, we calculated the proportion of each Women's Interagency HIV Study participant's census tract (neighborhood) living below the poverty line. We assessed associations between neighborhood poverty and (1) unsuppressed viral load [VL] in HIV-seropositive women, (2) uncontrolled blood pressure among HIV-seropositive and HIV-seronegative hypertensive women, and (3) uncontrolled diabetes among HIV-seropositive and HIV-seronegative diabetic women using modified Poisson regression models. Neighborhood poverty was associated with unsuppressed VL in HIV-seropositive women (> 40% versus ≤ 20% poverty adjusted prevalence ratio (PR), 1.42; 95% confidence interval (CI) 1.04-1.92). In HIV-seronegative diabetic women, moderate neighborhood poverty was associated with uncontrolled diabetes (20-40% versus ≤ 20% poverty adjusted PR, 1.75; 95% CI 1.02-2.98). Neighborhood poverty was associated with neither uncontrolled diabetes among HIV-seropositive diabetic women, nor uncontrolled hypertension in hypertensive women, regardless of HIV status. Women living in areas with concentrated poverty may need additional resources to control health conditions effectively.

Neighborhood Poverty and 9-1-1 Ambulance Contacts.

BACKGROUND: Neighborhood poverty is positively associated with frequency of 9-1-1 ambulance utilization, but it is unclear whether this association remains significant when accounting for variations in the severities and types of ambulance contacts. METHODS: We merged EMS ambulance contact records in a single California county (n = 88,027) with data from the American Community Survey at the census tract level (n = 300). Using tract as a proxy for neighborhood and negative binomial regression as an analytical tool, we predicted 16 outcomes: any ambulance contacts, ambulance contacts stratified by three intervention severities, and ambulance contacts varied by 12 primary impression categories. For each model, we estimated the incident rate ratios for 10 percentage point increases in tract-level poverty while controlling for geographic patterns in race, citizenship, gender, age, emergency department proximity, population density, and population size. RESULTS: Our study produced three major findings. First, tract-level poverty was positively associated with ambulance contacts (incident rate ratio [IRR] 1.45; 95% confidence interval [CI] 1.34 to 1.57). Second, poverty was positively associated with low severity contacts (IRR 1.48; 95% CI 1.35 to 1.61), medium severity contacts (IRR 1.38; 95% CI 1.28 to 1.49), and high severity contacts (IRR 1.40; 95% CI 1.30 to 1.51). Third, poverty was positively associated with 12 primary impression categories: abdominal (IRR 1.48; 95% CI 1.36 to 1.61), altered level of consciousness (IRR 1.37; 95% CI 1.25 to 1.50), cardiac (IRR 1.28; 95% CI 1.14 to 1.42), overdose/intoxication (IRR 1.59; 95% CI 1.40 to 1.81), pain (IRR 1.56; 95% CI 1.41 to 1.73), psych/behavioral (IRR 1.50; 95% CI 1.34 to 1.67), respiratory (IRR 1.42; 95% CI 1.29 to 1.56) seizure (IRR 1.52; 95% CI 1.38 to 1.68), stroke (IRR 1.14; 95% CI 1.01 to 1.28), syncope/near syncope (IRR 1.23; 95% CI 1.12 to 1.36), trauma (IRR 1.44; 95% CI 1.31 to 1.58), and general weakness (IRR 1.31; 95% CI 1.20 to 1.42). CONCLUSION: Our study suggests poverty is a positive, strong, and enduring predictor of ambulance contacts at the neighborhood level. The relationship between neighborhood poverty and ambulance utilization should be considered at multiple levels of EMS decision making.

Tract- and county-level income inequality and individual risk of obesity in the United States.

OBJECTIVES: We tested three alternative hypotheses regarding the relationship between income inequality and individual risk of obesity at two geographical scales: U.S. Census tract and county. METHODS: Income inequality was measured by Gini coefficients, created from the 2000 U.S. Census. Obesity was clinically measured in the 2003-2008 National Health and Nutrition Examination Survey (NHANES). The individual measures and area measures were geo-linked to estimate three sets of multi-level models: tract only, county only, and tract and county simultaneously. Gender was tested as a moderator. RESULTS: At both the tract and county levels, higher income inequality was associated with lower individual risk of obesity. The size of the coefficient was larger for county-level Gini than for tract-level Gini; and controlling income inequality at one level did not reduce the impact of income inequality at the other level. Gender was not a significant moderator for the obesity-income inequality association. CONCLUSIONS: Higher tract and county income inequality was associated with lower individual risk of obesity, indicating that at least at the tract and county levels and in the context of cross-sectional data, the public health goal of reducing the rate of obesity is in line with anti-poverty policies of addressing poverty through mixed-income development where neighborhood income inequality is likely higher than homogeneous neighborhoods.

Patterns and causes of uncertainty in the American Community Survey.

In 2010 the American Community Survey (ACS) replaced the long form of the United States decennial census. The ACS is now the principal source of high-resolution geographic information about the U.S. population. The margins of error on ACS census tract-level data are on average 75 percent larger than those of the corresponding 2000 long-form estimate. The practical implications of this increase is that data are sometimes so imprecise that they are difficult to use. This paper explains why the ACS tract and block group estimates have large margins of error. Statistical concepts are explained in plain English. ACS margins of error are attributed to specific methodological decisions made by the Census Bureau. These decisions are best seen as compromises that attempt to balance financial constraints against concerns about data quality, timeliness, and geographic precision. In addition, demographic and geographic patterns in ACS data quality are identified. These patterns are associated with demographic composition of census tracts. Understanding the fundamental causes of uncertainty in the survey suggests a number of geographic strategies for improving the usability and quality ACS.

Association of Hospice Agency Location and Neighborhood Socioeconomic Disadvantage in the U.S.

BACKGROUND: Despite the growing increase in the utilization of hospice in the U.S, disparities exist in the utilization of hospice. Accumulating evidence has shown that neighborhood characteristics have an impact on availability of hospice agencies. OBJECTIVE: To assess the association between neighborhood social vulnerability and hospice agency availability. METHODS: Using the Medicare Post-Acute Care and Hospice Provider Utilization and Payment Public Use Files (PAC PUF) for 2019. Hospice agency addresses were geocoded to the census tract level. Multivariable Poisson regression models were used to assess the association between socioeconomic status SVI theme and hospice agency availability adjusting for number of home health agencies, primary care health profession shortage, per cent Black, and Percent Hispanic at the census tract level and rurality. RESULTS: The socioeconomic status SVI subtheme was associated with decreased likelihood of hospice agency availability (adjusted IRR (aIRR), .56; 95% CI, .50- .63; P < .001). Predominantly Black, and predominantly Hispanic neighborhoods had lower rates of hospice agency availability (aIRR, .48; 95% CI, .39-.59; P < .001 and aIRR, .29; 95% CI, .24-.36; P < .001), respectively. CONCLUSION: Neighborhood socioeconomic disadvantage was associated with lower availability of hospice agencies. Policies aimed at increasing access to hospice should be cognizant of neighborhood socioeconomic disadvantage.

How An Academic Direct Primary Care Clinic Served Patients from Vulnerable Communities.

PURPOSE: Direct primary care (DPC) critics are concerned that the periodic fee precludes participation from vulnerable populations. The purpose is to describe the demographics and appointments of a, now closed, academic DPC clinic and determine whether there are differences in vulnerability between census tracts with and without any clinic patients. METHODS: We linked geocoded data from the DPC's electronic health record with the social vulnerability index (SVI). To characterize users, we described their age, sex, language, membership, diagnoses, and appointments. Descriptive statistics included frequencies, proportions or medians, and interquartile ranges. To determine differences in SVI, we calculated a localized SVI percentile within Harris County. A t test assuming equal variances and Mann-Whitney U Tests were used to assess differences in SVI and all other census variables, respectively, between those tracts with and without any clinic patients. RESULTS: We included 322 patients and 772 appointments. Patients were seen an average of 2.4 times and were predominantly female (58.4%). More than a third (37.3%) spoke Spanish. There was a mean of 3.68 ICD-10 codes per patient. Census tracts in which DPC patients lived had significantly higher SVI scores (ie, more vulnerable) than tracts where no DPC clinic patients resided (median, 0.60 vs 0.47, p-value < 0.05). CONCLUSION: This academic DPC clinic cared for individuals living in vulnerable census tracts relative to those tracts without any clinic patients. The clinic, unfortunately, closed due to multiple obstacles. Nevertheless, this finding counters the perception that DPC clinics primarily draw from affluent neighborhoods.

Environmental Justice Index and adverse pregnancy outcomes.

BACKGROUND: The Environmental Justice Index is a tool released by the Centers for Disease Control and Prevention that quantifies and ranks the environmental burden and social vulnerability of each census tract. Racial and ethnic disparities in adverse pregnancy outcomes are well established. The relative contributions of individual (person-level) and environmental (neighborhood-level) risk factors to disease prevalence remain poorly understood. OBJECTIVE: This study aimed to determine whether the Environmental Justice Index is associated with adverse pregnancy outcomes after adjustment for individual clinical and sociodemographic risk factors. STUDY DESIGN: This was a retrospective cross-sectional study of all patients who delivered a singleton newborn at ≥23 weeks of gestation between January 2019 and February 2022 at 7 hospitals within a large academic health system in New York. Patients were excluded if their home address was not available, if the address could not be geocoded to a census tract, or if the census tract did not have corresponding Environmental Justice Index data. Patients were also excluded if they had preexisting diabetes or hypertension. For patients who had multiple pregnancies during the study period, only the first pregnancy was included for analysis. Clinical and demographic data were obtained from the electronic medical record. Environmental Justice Index score, the primary independent variable, ranges from 0 to 1. Higher Environmental Justice Index scores indicate communities with increased cumulative environmental burden and increased social vulnerability. The primary outcome was adverse pregnancy outcome, defined as the presence of ≥1 of any of the following conditions: hypertensive disorders of pregnancy, gestational diabetes, preterm birth, fetal growth restriction, low birthweight, small for gestational age newborn, placental abruption, and stillbirth. Multivariable logistic regression was performed to investigate the relationship between Environmental Justice Index score and adverse pregnancy outcome, adjusting for potential confounding variables, including body mass index group, race and ethnicity group, advanced maternal age, nulliparity, public health insurance, and English as the preferred language. RESULTS: A total of 65,273 pregnancies were included for analysis. Overall, adverse pregnancy outcomes occurred in 37.6% of pregnancies (n=24,545); hypertensive disorders of pregnancy (13.4%) and gestational diabetes (12.2%) were the most common adverse pregnancy outcome conditions. On unadjusted analysis, the strongest associations between Environmental Justice Index score and individual adverse pregnancy outcome conditions were observed for stillbirth (odds ratio, 1.079; 95% confidence interval, 1.025-1.135) and hypertensive disorders of pregnancy (odds ratio, 1.052; 95% confidence interval, 1.042-1.061). On multivariable logistic regression, every 0.1 increase in Environmental Justice Index score was associated with 1.4% higher odds of adverse pregnancy outcome (adjusted odds ratio, 1.014; 95% confidence interval, 1.007-1.021). The strongest associations with adverse pregnancy outcomes were observed with well-established clinical and social risk factors, including class 3 obesity (adjusted odds ratio, 1.710; 95% confidence interval, 1.580-1.849; reference: body mass index <25 kg/m2) and certain race and ethnicity groups (reference: non-Hispanic White), particularly Asian and Pacific Islander (adjusted odds ratio, 1.817; 95% confidence interval, 1.729-1.910), and non-Hispanic Black (adjusted odds ratio, 1.668; 95% confidence interval, 1.581-1.760) people. CONCLUSION: Environmental Justice Index score is positively associated with adverse pregnancy outcomes, and most strongly associated with stillbirth and hypertensive disorders of pregnancy. Geospatial analysis with Environmental Justice Index may help to improve our understanding of health inequities by identifying neighborhood characteristics that increase the risk of pregnancy complications.

Neighborhood Resources and Health Outcomes Among Stroke Survivors in a Population-Based Cohort.

BACKGROUND: Stroke survivors believe neighborhood resources such as community centers are beneficial; however, little is known about the influence of these resources on stroke outcomes. We evaluated whether residing in neighborhoods with greater resource density is associated with favorable post-stroke outcomes. METHODS AND RESULTS: We included Mexican American and non-Hispanic White stroke survivors from the Brain Attack Surveillance in Corpus Christi project (2009-2019). The exposure was density of neighborhood resources (eg, community centers, restaurants, stores) within a residential census tract at stroke onset. Outcomes included time to death and recurrence, and at 3 months following stroke: disability (activities of daily living/instrumental activities of daily living), cognition (Modified Mini-Mental State Exam), depression (Patient Health Questionnaire-8), and quality of life (abbreviated Stroke-Specific Quality of Life scale). We fit multivariable Cox regression and mixed linear models. We considered interactions with stroke severity, ethnicity, and sex. Among 1786 stroke survivors, median age was 64 years (interquartile range, 56-73), 55% men, and 62% Mexican American. Resource density was not associated with death, recurrence, or depression. Greater resource density (75th versus 25th percentile) was associated with more favorable cognition (Modified Mini-Mental State Exam mean difference=0.838, 95% CI=0.092, 1.584) and among moderate-severe stroke survivors, with more favorable functioning (activities of daily living/instrumental activities of daily living=-0.156 [95% CI, -0.284 to 0.027]) and quality of life (abbreviated Stroke-Specific Quality of Life scale=0.194 [95% CI, 0.029-0.359]). CONCLUSIONS: We observed associations between greater resource density and cognition overall and with functioning and quality of life among moderate-severe stroke survivors. Further research is needed to confirm these findings and determine if neighborhood resources may be a tool for recovery.

Environmental determinants of health: Measuring multiple physical environmental exposures at the United States census tract level.

Physical environment plays a key role in determining human health risks. Exposure to toxins, weather extremes, degraded air and water quality, high levels of noise and limited accessibility to green areas can negatively affect health. Furthermore, adverse environmental exposures are often correlated with each other and with socioeconomic status, thereby compounding disadvantages in marginalized populations. Moreover, despite their importance in determining human health risks, the role of multiple environmental exposures is not well studied, and only a few resources contain aggregate environmental exposure data and only for selected areas of the contiguous US. To fill these gaps, we took a cumulative approach to measuring the environment by generating a composite Multi-Exposure Environmental Index (MEEI) as a US Census Tract-level summary of key environmental factors with known health effects. This measure quantifies multiple environmental exposures in the same area that can result in additive and synergistic effects on health outcomes. This information is crucial to better understand and possibly leverage environmental determinants of health for informed policy-making and intervention.