American Community Survey Data Research Articles

The Impact of Neighborhood Characteristics on Routine and Gang-Involved Gun Violence: Are Structural Covariates Salient?

ABSTRACT An extensive body of literature has described the influence of neighborhood characteristics, including socio-economic deprivation, residential turnover, and racial/ethnic composition on gun crime. There have been limited efforts, however, to examine the extent to which these effects might vary based on the nature of gun crime – particularly in communities outside of major cities like Chicago or St. Louis. This study attempts to address this issue through application of negative binomial regression and equality of coefficients tests to data obtained from the crime logs and American Community Survey data of a medium-sized city in the Southeastern U.S. Specifically, this study examines (in)equality in the structural covariates of gun crimes when these offenses are disaggregated by gang-involved gun crime versus non-gang-involved gun crime across a sample of 153 census block groups in Chattanooga. Results indicate that the relative influence of neighborhood structural characteristics varies, to some extent, by type of gun crime, illustrating the need for disaggregated measures as a matter of exploring relationships between sub-crime types.

Model-based estimation of individual-level social determinants of health and its applications in All of Us.

We introduce a widely applicable model-based approach for estimating individual-level Social Determinants of Health (SDoH) and evaluate its effectiveness using the All of Us Research Program. Our approach utilizes aggregated SDoH datasets to estimate individual-level SDoH, demonstrated with examples of no high school diploma (NOHSDP) and no health insurance (UNINSUR) variables. Models are estimated using American Community Survey data and applied to derive individual-level estimates for All of Us participants. We assess concordance between model-based SDoH estimates and self-reported SDoHs in All of Usand examine associations with undiagnosed hypertension and diabetes. Compared to self-reported SDoHs, the area under the curve for NOHSDP is 0.727 (95% CI, 0.724-0.730) and for UNINSUR is 0.730 (95% CI, 0.727-0.733) among the 329074 All of Us participants, both significantly higher than aggregated SDoHs. The association between model-based NOHSDP and undiagnosed hypertension is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.649. Similarly, the association between model-based NOHSDP and undiagnosed diabetes is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.900. The model-based SDoH estimation method offers a scalable and easily standardized approach for estimating individual-level SDoHs. Using the All of Us dataset, we demonstrate reasonable concordance between model-based SDoH estimates and self-reported SDoHs, along with consistent associations with health outcomes. Our findings also underscore the critical role of geographic contexts in SDoH estimation and in evaluating the association between SDoHs and health outcomes.

Risk of Delayed Percutaneous Coronary Intervention for STEMI in the Southeast United States.

Emergent reperfusion by percutaneous coronary intervention (PCI) within 90 minutes of first medical contact (FMC) is indicated in patients with ST-segment elevation myocardial infarction (STEMI). However, long transport times in rural areas in the Southeast US make meeting this goal difficult. The objective of this study was to determine the number of Southeast US residents with prolonged transport times to the nearest 24/7 primary PCI (PPCI) center. A cross-sectional study of residents in the Southeastern US was conducted based on geographical and 2022 5-Year American Community Survey data. The geographic information system (GIS) ArcGIS Pro was used to estimate Emergency Medical Services (EMS) transport times for Southeast US residents to the nearest PPCI center. All 24/7 PPCI centers in North Carolina, South Carolina, Georgia, Florida, Mississippi, Alabama, and Tennessee were included in the analysis, as well as nearby PPCI centers in surrounding states. To identify those at risk of delayed FMC-to-device time, the primary outcome was defined as a >30-minute transport time, beyond which most patients would not have PCI within 90 minutes. A secondary outcome was defined as transport >60 minutes, the point at which FMC-to-device time would be >120 minutes most of the time. These cutoffs are based on national median EMS scene times and door-to-device times. Within the Southeast US, we identified 62,880,528 residents and 350 PPCI centers. Nearly 11 million people living in the Southeast US reside greater than 30 minutes from a PPCI center (17.3%, 10,866,710, +/- 58,143), with 2% (1,271,522 +/- 51,858) living greater than 60 minutes from a PPCI hospital. However, most patients reside in short transport zones; 82.7% (52,013,818 +/- 98,741). Within the Southeast region, 8.4% (52/616) of counties have more than 50% of their population in a long transport zone and 42.3% (22/52) of those have more than 90% of their population in long transport areas. Nearly 11 million people in the Southeast US do not have access to timely PCI for STEMI care. This disparity may contribute to increased morbidity and mortality.

Linguistic isolation correlates with length of stay and mortality for pediatric oncology patients in California.

To evaluate social drivers of health and how they impact pediatric oncology patients' clinical outcomes during pediatric intensive care unit (PICU) admission via correlation with patient ZIP codes. Demographic, clinical, and outcome variables from Virtual Pediatric Systems®, LLC for oncology patients (2009-2021) in California PICUs (excluding postoperative) using 3-digit ZIP Codes with social drivers of health variables linguistic isolation, poverty, race/ethnicity, and education abstracted from American Community Survey data for 3-digit ZIP Codes using the Environmental Protection Agency's EJScreen tool. Outcomes of length of stay (LOS), mortality, acuity scores, were compared with social variables. Positive correlation between mortality and minority racial groups (Hispanic/Latino) across ZIP Codes (correlation coefficients of 0.45 (95% CI: 0.22-0.64, p < 0.001) in 2017, 0.50 (95% CI: 0.27-0.68, p < 0.001) in 2018, 0.33 (95% CI: 0.07-0.54, p = 0.013) in 2020, and 0.32 (95% CI: 0.06-0.53, p = 0.018) in 2021). Median PICU length of stay significantly correlated with linguistic isolation (coefficient of 0.42 (95% CI: 0.18-0.61, p = 0.001) in 2021 versus -0.41 (95% CI: -0.61 to -0.16, p = 0.002) in 2019), which included PRISMIII (n = 7417). Mixed effects logistic regression model for other constant variables (PRISMIII, cancer type, race/ethnicity, year), random effect of patient, linguistic isolation (percentage as a continuous value) was significantly associated (95% CI: 1.01-1.06; p = 0.02) with mortality; (OR = 1.03). Linguistic isolation was correlated with LOS and mortality, however variable year to year.

Informing inclusive park planning: Neighborhood park visitation modeling based on smartphone big data in Austin, Texas

This research uses smartphone-based big data to explore how socioeconomic, built environment characteristics, and spatiotemporal factors influence neighborhood park use, with a specific focus on minority groups’ park visitation patterns. Panel data are collected through SafeGraph, and combined with GIS and American Community Survey data. We analyze 12,227 visitations from 1121 block groups to 30 neighborhood parks from September 2019 to August 2020 in Austin, Texas. Time-fixed-effect nested regression models are employed to control for unobserved time-related effects. Findings indicate a substantial increase in overall park use during the pandemic, with visiting frequencies up by 22 % and dwell time by 56 %. In contrast, minority groups, including seniors, children, blacks, unemployed, living alone, and recent movers, exhibited a decline in park visits. It also highlights visitors’ risk-averse behaviors during the pandemic, such as avoiding visiting parks during holiday weeks and avoiding using swimming pools. Before the pandemic, proximity held the utmost significance for park use; during the pandemic, park quality and facilities emerged as the primary factors influencing park utilization. This study suggests that park planning needs to improve neighborhood parks’ proximity, park facilities, and park safety to boost park use and foster inclusive park planning.

Effects of the Affordable Care Act Medicaid Expansions on the Employment and Work Hours of Nursing Assistants in Hospitals and Nursing Homes.

We examine the effects of the Affordable Care Act Medicaid expansions on the employment and work hours of nursing assistants (NAs). We use the 2011-2019 American Community Survey data to identify NAs likely to be affected by Medicaid expansions (income up to 138% of the federal poverty level) in nursing homes and hospitals. Using classical difference-in-differences regressions, we find that Medicaid expansions have little effect on employment and work hours among NAs in the full sample. However, there is a 4.4 percentage-point increase in the probability of working part-time (<30 hours/week) for nursing home NAs (p < .05). We found no employment effects of Medicaid expansions for hospital NAs. Our study adds to the literature on the heterogeneous effects of Medicaid expansions on work effort across occupations and workplaces. The rise in part-time employment for nursing home NAs following Medicaid expansions suggests the need for improved benefits to encourage full-time employment.

787 Higher County-Level Socioeconomic Status Is Associated With Increased Meningioma Survival But Does Not Impact Likelihood of Surgical Treatment: A CBTRUS Analysis

INTRODUCTION: Prior literature suggests that individual socioeconomic status (SES) may influence access to treatment and outcomes for primary brain tumors. To date, no population-level studies have assessed the correlation between meningioma treatment and outcome with county-level SES. METHODS: Incidence data were extracted from the Central Brain Tumor Registry of the United States(CBTRUS), a combined dataset including the CDC’s National Program of Cancer Registries (NPCR) and NCI’s Surveillance, Epidemiology, and End Results Program data, for diagnosis years 2006-2019, and survival data were extracted from the NPCR survival analytic dataset from 2006-2018. SES quintiles were created using American Community Survey data. Logistic regression and Cox proportional hazards models were used to assess the relationship the odds of receiving treatment and overall survival and SES and the individual SES factors. RESULTS: There were 409,681 meningioma cases available from CBTRUS. Asian/Pacific-Islander non-Hispanic individuals (odds ratio [OR] = 1.28, p &lt; 0.001) were more likely and Black non-Hispanic (BNH) individuals (OR = 0.90, p &lt; 0.001) were less likely to receive surgery than White non-Hispanic (WNH) individuals. Female sex (OR = 1.31, p &lt; 0.001), living in a metropolitan area (OR = 0.96, p &lt; 0.001), and increased age at diagnosis (OR = 0.96, p &lt; 0.001) were associated with decreased likelihood of surgery. There was no association between SES and likelihood to receive surgery. Overall median survival was 137 months and survival was higher in higher SES counties, which held true for both WNH and BNH. Age at diagnosis(hazard ratio [HR] = 1.01, p &lt; 0.001), male sex (HR = 1.51, p &lt; 0.001), BNH (HR = 1.31, p &lt; 0.001), subtotal resection (HR = 1.38, p &lt; 0.001), and malignant behavior(HR = 1.64, p &lt; 0.001) were associated with increased hazard of death. CONCLUSIONS: In the US, county-level SES did not impact treatment patterns, but higher SES was associated with increased survival. These findings provide valuable insight into socioeconomic factors influencing treatment and outcomes in meningioma patients.

Longitudinal Policy Surveillance of Private Insurance Hearing Aid Mandates in the United States: 1997-2022.

Objectives. To produce a database of private insurance hearing aid mandates in the United States and quantify the share of privately insured individuals covered by a mandate. Methods. We used health-related policy surveillance methods to create a database of private insurance hearing aid mandates through January 2023. We coded salient features of mandates and combined policy data with American Community Survey and Medicare Expenditure Panel Survey-Insurance Component data to estimate the share of privately insured US residents covered by a mandate from 2008 to 2022. Results. A total of 26 states and 1 territory had private insurance hearing aid mandates. We found variability for mandate exceptions, maximum age eligibility, allowable frequency of benefit use, and coverage amounts. Between 2008 and 2022 the proportion of privately insured youths (aged ≤ 18 years) living where there was a private insurance hearing aid mandate increased from 3.4% to 18.7% and the proportion of privately insured adults (19-64 years) increased from 0.3% to 4.6%. Conclusions. Hearing aid mandates cover a small share of US residents. Mandate exceptions in several states limit coverage, particularly for adults. Public Health Implications. A federal mandate would improve hearing aid access. States can also improve access by adopting exception-free mandates with limited utilization management and no age restrictions. (Am J Public Health. 2024;114(4):407-414. https://doi.org/10.2105/AJPH.2023.307551).

Living in high-poverty areas is associated with reduced survival in patients with thoracoabdominal aortic aneurysms

ObjectivesStudies have demonstrated that socioeconomic status, insurance, race, and distance impact clinical outcomes in patients with abdominal aortic aneurysms. The purpose of this study was to assess if these factors also impact clinical outcomes in patients with thoracoabdominal aortic aneurysms (TAAAs). MethodsWe conducted a retrospective review of patients with TAAAs confirmed by computed tomography imaging between 2009 and 2019 at a single institution. Patients’ zip codes were mapped to American Community Survey Data to obtain geographic poverty rates. We used the standard U.S. Census definition of high-poverty concentration as >20% of the population living at 100% of the poverty rate. Our primary outcome was overall survival, stratified by whether the patient underwent repair. ResultsOf 578 patients, 575 had zip code data and were analyzed. In both the nonoperative (N = 268) and operative (N = 307) groups, there were no significant differences in age, race, comorbidities, clinical urgency, surgery utilization, or surgery modality between patients living in high-poverty areas (N = 95, 16.4%) vs not. In the nonoperative group, patients from high-poverty areas were more likely to have aneurysm due to dissection (37.5% vs 17.6%, P = .03). In multivariate analyses, patients from high-poverty zip codes had significantly worse nonoperative survival (hazard ratio [HR]: 1.9, 95% confidence interval [CI]: 1.1-3.3, P = .03). In the repair group, high poverty was also a significant predictor of reduced postoperative survival (HR: 1.65, 95% CI: 1-2.63, P = .04). Adding the Gagne Index, these differences persisted in both groups (nonoperative: HR: 1.93, 95% CI: 1.01-3.70, P = .05; operative: HR: 1.62, 95% CI: 1.03-2.56, P = .04). In Kaplan-Meier analysis, the difference in postoperative survival began approximately 1.5 years after repair. Private insurance was predictive of improved postoperative survival (HR: 0.42, 95% CI: 0.18-0.95, P = .04) but reduced nonoperative survival (HR: 2.05, 95% 1.01-4.14, P = .04). Data were insufficient to determine if race impacted survival discretely from poverty status. These results were found after adjusting for age, race, sex, maximum aortic diameter, coronary artery disease, distance from the hospital, insurance, and active smoking. Interestingly, in multivariate regression, traveling greater than 100 miles was correlated with increased surgery utilization (odds ratio: 1.58, 95% CI: 1.08-2.33, P = .02) and long-term survival (HR: 0.61, 95% CI: 0.41-0.92, P = .02). ConclusionsPatients with TAAAs living in high-poverty areas had significantly more dissections and suffered a nearly doubled risk of mortality compared with patients living outside such areas. These data suggest that these disparities are attributed to the overall impacts of poverty and highlight the pressing need for research into TAAA disparities.

Associations between neighborhood characteristics and child well-being before and during the COVID-19 pandemic: A repeated cross-sectional study in the Environmental influences on Child Health Outcomes (ECHO) program

The corona virus disease (COVID-19) pandemic disrupted daily life worldwide, and its impact on child well-being remains a major concern. Neighborhood characteristics affect child well-being, but how these associations were affected by the pandemic is not well understood. We analyzed data from 1039 children enrolled in the Environmental influences on Child Health Outcomes Program whose well-being was assessed using the Patient-Reported Outcomes Measurement Information System Global Health questionnaire and linked these data to American Community Survey (ACS) data to evaluate the impacts of neighborhood characteristics on child well-being before and during the pandemic. We estimated the associations between more than 400 ACS variables and child well-being t-scores stratified by race/ethnicity (non-Hispanic white vs. all other races and ethnicities) and the timing of outcome data assessment (pre-vs. during the pandemic). Network graphs were used to visualize the associations between ACS variables and child well-being t-scores. The number of ACS variables associated with well-being t-scores decreased during the pandemic period. Comparing non-Hispanic white with other racial/ethnic groups during the pandemic, different ACS variables were associated with child well-being. Multiple ACS variables representing census tract-level housing conditions and neighborhood racial composition were associated with lower well-being t-scores among non-Hispanic white children during the pandemic, while higher percentage of Hispanic residents and higher percentage of adults working as essential workers in census tracts were associated with lower well-being t-scores among non-white children during the same study period. Our study provides insights into the associations between neighborhood characteristics and child well-being, and how the COVID-19 pandemic affected this relationship.

Racial Disparities in Socioeconomic Status Among Adoptive Parents

Parents of color are underrepresented in adoption research and as adoptive parents. Consequently, there is limited understanding of racial disparities in socioeconomic status (SES) among adoptive parents. We test two hypotheses: (1) racial disparities in the United States will be reflected in the adoption community (social stratification) and (2) adoptive parents of color may need to overcome additional barriers to adoption, thus having higher SES than White adoptive parents (overcoming barriers). Using 2019 American Community Survey data, we predict adoptive parents’ ( n = 65,556) SES by race and then compare the SES of adoptive and non-adoptive parents of the same race. Across-race results support a social stratification perspective—White adoptive parents have higher SES than adoptive parents of color. Within-race results, alternatively, show that adoptive parents have higher SES than non-adoptive parents across racial groups. Therefore, although adoptive parents experience socioeconomic advantages, parents of color navigate adoption with fewer resources.

Population-Level Associations Between Visual Impairment and Functional Difficulties in California

ABSTRACT Purpose The prevalence of visual impairment is increasing, and there is a need to understand the functional implications. Using the American Community Survey (ACS) data, this study examined the relationship between visual impairment and functional difficulties in California. Methods Using the 2010–2014 and 2015–2019 ACS 5-year estimates from the U.S. Census, data were obtained for visual impairment and functional difficulties including hearing, cognitive, ambulatory, self-care, and independent living difficulties. The prevalence of vision impairment and each functional difficulty was calculated on the Medical Service Study Area (MSSA) level in California. Unadjusted and adjusted linear regression models were performed to estimate the association between visual impairment and each functional difficulty, adjusting for age, sex, race and ethnicity, education level, English-speaking ability, poverty status, health insurance status, and urbanity of residence location. Results The prevalence of visual impairment in California was 2.3% (659,502 of 28,794,572) in 2010–2014 and 2.3% (709,353 of 30,231,767) in 2015–2019 among the population ≥ 18 years old. There were statistically significant associations between the prevalence of vision impairment and increased prevalence of all functional difficulties, with the most positive correlation observed with ambulatory difficulty (slope estimate 0.58 ± 0.072 for 2010–2014 and 0.78 ± 0.082 for 2015–2019 for ambulatory difficulty). Conclusions There may be population-level impacts of functional consequences from vision impairment, suggesting the need for neighborhood-level investigation and policy-based interventions to address the burden of vision impairment on the population level.

Labor force effects of Medicaid and Marketplace expansions: Variation by gender, parental status, and household structure

AbstractWe revisit the Affordable Care Act (ACA)'s Medicaid expansion's labor market effects and build upon it by estimating effects of subsidized Marketplace insurance. Using American Community Survey data, we jointly model the effects of Medicaid and Marketplace expansion on labor force outcomes using simulated eligibility measures. Throughout our analysis, we focus on heterogeneity by gender, parental status, and single versus two‐headed households. Consequently, this is the first paper presenting labor outcomes of the ACA among women with children, an important group, which may be particularly responsive to increased flexibility in meeting income, childcare, and insurance needs. Even among women, we find little evidence that Medicaid eligibility reduced labor force participation. Any significant reductions among women are small in magnitude and not well corroborated by placebo tests. Alternatively, women with children gaining Marketplace eligibility had statistically significant reductions in labor force participation, reductions in hours, and increases in part‐time work.

Tracking long-term services and supports rebalancing through workforce data.

To understand trends in the long-term services and supports (LTSS) workforce and assess workforce data as a measure of progress in shifting LTSS resources from institutional to community-based settings. Workforce data from the American Community Survey from 2008 to 2022. Measures of LTSS rebalancing and institutional and community workforce supply per 1000 persons with LTSS needs were constructed. After showing national trends over the study period, state fixed effects regressions were used to evaluate the within-state relationship of these measures with existing measures of LTSS utilization. Workforce supply measures were compared to the percentage of state Medicaid LTSS spending spent in the community to assess their utility for across state comparisons. Each state's progress in LTSS rebalancing over the study period was then shown using workforce data. A sample of 336,316 LTSS workers and 3,015,284 people with LTSS needs over the study period was derived from American Community Survey data. From 2008 to 2022, the percentage of the LTSS workforce employed in the community rose from 44% to 58%. Thirty states saw more than a 10 percentage point increase. From 2008 to 2013, the size of the community workforce expanded dramatically but has since stagnated. In contrast, the institutional workforce entered a long-term decline beginning in 2015 that accelerated during the COVID-19 pandemic. State fixed effects regressions showed that measures of workforce supply have a strong relationship with LTSS utilization measures for older adults, but not for younger people with disabilities. Workforce data can serve as an effective measure of changes in LTSS utilization for older adults. This offers researchers and policymakers a useful alternative to administrative claims, bypassing threats to comparability from coding changes and the shift to managed care. Additional data is needed on workforce trends in services for younger LTSS consumers.

Social Disconnectedness, Perceived Loneliness, and Cognitive Functioning: The Role of Neighborhood Environment.

Social disconnectedness and loneliness pose significant challenges for older Chinese immigrants. Yet, it remains unclear whether they are associated with an increased risk of cognitive decline in this population. This study aimed to investigate the association of social disconnectedness and loneliness with cognitive functioning and examine the moderation role of neighborhood contexts. This longitudinal analysis examined a sample of individuals aged 60 years and older from the Population Study of Chinese Elderly in Chicago (N = 2,044). Global cognition was assessed using the averaged z-scores of cognitive performance tests. Social disconnectedness was constructed using 5 indicators about structural aspects of social relationships. Loneliness was assessed with the R-UCLA loneliness scale. Neighborhood socioeconomic status (NSES) and neighborhood segregation index were constructed using 2010-2014 American Community Survey data at the census tract level. Individual perceptions about neighborhood environments were used to construct neighborhood cohesion index and neighborhood disorder index (NDI). Latent growth curve models with adjusted cluster robust standard errors were estimated. More loneliness was associated with a higher level of initial cognitive functioning (B = 0.030, p < .01), but also with a faster decline rate over time (B = -0.007, p < .01) after adjusting for covariates. High NSES and less neighborhood segregation buffered the negative effects of loneliness on cognitive decline, respectively. High NDI amplified the positive relationship between loneliness and initial functioning, but accelerated the rate of cognitive decline associated with loneliness. The study revealed that perceived loneliness, but not social disconnectedness, is a risk factor for cognitive decline among older Chinese immigrants. Living in a neighborhood with low socioeconomic status, more segregation, and high disorder elevated the detrimental effect of loneliness on long-term cognitive decline. Further research needs to investigate the complex interplay between social relationships, neighborhood environment, and cognition.

Demographic and prognostic factors in papillary transitional cell carcinoma: An analysis of the National Cancer Database.

541 Background: Transitional cell carcinomas account for the majority of bladder cancers, with the papillary subtype comprising most of these cases. The role of race in bladder cancers has been investigated in the past, but there have been no studies that collectively investigated the role of different demographic factors in survival and mortality in papillary transitional cell carcinoma (PTCC). This study analyzes the effects of demographic factors on overall mortality (OM) in patients with PTCC. Methods: A retrospective cohort analysis was conducted using National Cancer Database data from 2004-2019, including 12,300 patients with histologically confirmed PTCC (ICD-O-3=8130). Sex, race (Black, White, and Other), insurance status, and median household income quartile (based on 2016-2020 American Community Survey data) were examined. Kaplan-Meier curves were used to calculate 2, 5, and 10 year survival (2-5-10 YS). Multivariable Cox regression was used to calculate hazard ratios (HR) to identify independent prognostic factors. Statistical significance was set at α=0.05. Results: Females had higher 2-5-10 YS and decreased OM compared to males (HR=0.85, P&lt;.001). White patient survival was higher at 2 years compared to Black patients, but Black patient survival was higher at 5 and 10 years. There was no significant difference in OM between Black and White patients (HR=1.07, P=0.260). Patients of other races had higher 2-5-10 YS and decreased OM compared to White (HR=0.85, P=0.023) and Black patients (HR=0.80, P=0.011). Patients on Medicaid had lower 2-5-10 YS and increased OM compared to patients on private insurance (HR=1.19, P=0.036). Patients on Medicaid had higher 2-5-10 YS than patients on Medicare, but no significant difference in OM (HR=0.87, P=0.091). Patients on private insurance (HR=0.70, P&lt;.001) and Medicare (HR=0.73, P=0.003) had decreased OM compared to uninsured patients. Patients in the fourth income quartile had decreased OM compared to patients in the first (HR=0.82, P&lt;.001), second (HR=0.87, P&lt;.001), and third quartiles (HR=0.90, P=0.003). Conclusions: Male sex, uninsured status, and lower income were associated with increased OM. Black patients and White patients had increased OM compared to patients of other races. Future research should investigate the reasons for these disparities and how to minimize them. [Table: see text]

Socioeconomic variables in the National Cancer Database: Utilization and impact of income and education in survival models for patients with resected pancreas cancer.

607 Background: The National Cancer Database (NCDB) is commonly used for analyzing survival outcomes in pancreatic cancer and has a robust number of patient-specific socioeconomic variables. Although these aggregated variables are commonly collected, their utility and impact on survival has infrequently been assessed. We aim to assess the distribution of income and education variables on their impact on survival models for patients who underwent resection for pancreatic ductal adenocarcinoma (PDAC). Methods: Patients undergoing definitive surgery for PDAC between 2004-2020 were identified from the NCDB. Variables of interest were income and education according to the patient’s ZIP code of residence. Pearson and Spearman correlation was assessed. Overall survival (OS) was calculated using Kaplan Meier method. The effects of income and education was calculated using Cox proportional Hazard (PH) models. Results: 69,362 patients met inclusion criteria. Median age was 66 (IQR 59-73), with 48.9% female. The correlation coefficient between income and education based on the 2020 American Community Survey data was 0.48 (p&lt;0.01). Median OS from the time of diagnosis was 21 months. The 5-year OS was 19.4 and 22.7 months for groups with lowest and highest education (p&lt;0.01). Group with missing education has a 5-year OS of 22.4 month, comparable to the group with highest education (p=0.82). The 5-year OS based on income quartiles was 18.7 and 22.5 months for the Q1 and Q4 (p&lt;0.01). Group with missing income has a 5-year OS of 22.4 month, similar to the highest income group (p=0.85). When including combinations of income, education and their interaction, the concordance of Cox models was changed by less than 0.002. Conclusions: For patients who underwent definitive surgery for PDAC, the income and education variables are only mildly correlated, and their inclusion do not have significant impact on OS models. Investigators should reconsider the utility of the aggregate NCDB measures, as they many not fully elucidate income and education disparities and impact on survival. [Table: see text]

Disparities in Health Insurance Among Middle Eastern and North African American Children in the US.

To estimate and compare the proportion of foreign-born Middle Eastern/North African (MENA) children without health insurance, public, or private insurance to foreign- and US-born White and US-born MENA children. Using 2000 to 2018 National Health Interview Survey data (N = 311 961 children) and 2015 to 2019 American Community Survey data (n = 1 892 255 children), we ran multivariable logistic regression to test the association between region of birth among non-Hispanic White children (independent variable) and health insurance coverage types (dependent variables). In the NHIS and ACS, foreign-born MENA children had higher odds of being uninsured (NHIS OR = 1.50, 95%CI = 1.10-2.05; ACS OR = 2.11, 95%CI = 1.88-2.37) compared to US-born White children. In the ACS, foreign-born MENA children had 2.11 times higher odds (95%CI = 1.83-2.45) of being uninsured compared to US-born MENA children. Our findings have implications for the health status of foreign-born MENA children, who are currently more likely to be uninsured. Strategies such as interventions to increase health insurance enrollment, updating enrollment forms to capture race, ethnicity, and nativity can aid in identifying and monitoring key disparities among MENA children.

A Comparison of Three Area-Level Indices of Neighborhood Deprivation and Socioeconomic Status and their Applicability to Breast Cancer Mortality.

Neighborhood deprivation indices are widely used in research, but the performance of these indices has rarely been directly compared in the same analysis. We examined the Area Deprivation Index, Neighborhood Deprivation Index, and Yost index, and compared their associations with breast cancer mortality. Indices were constructed for Georgia census block groups using 2011-2015 American Community Survey data. Pearson correlation coefficients and percent agreement were calculated. Associations between each index and breast cancer mortality were estimated among 36,795 women diagnosed with breast cancer using Cox proportional hazards regression. The indices were strongly correlated (absolute value of correlation coefficients > 0.77), exhibited moderate (41.4%) agreement, and were similarly associated with a 36% increase in breast cancer mortality. The similar associations with breast cancer mortality suggest the indices measure the same underlying construct, despite only moderate agreement. By understanding their correlations, agreement, and associations with health outcomes, researchers can choose the most appropriate index for analysis.

Association of county-level socioeconomic status with meningioma incidence and outcomes.

Prior literature suggests that individual socioeconomic status (SES) may influence incidence, treatments, and survival of brain tumor cases. We aim to conduct the first national study to evaluate the association between US county-level SES and incidence, treatment, and survival in meningioma. The Central Brain Tumor Registry of the United States analytic dataset, which combines data from CDC's National Program of Cancer Registries (NPCR) and National Cancer Institute's Surveillance, Epidemiology, and End Results Program, was used to identify meningioma cases from 2006 to 2019. SES quintiles were created using American Community Survey data. Logistic regression models were used to evaluate associations between SES and meningioma. Cox proportional hazard models were constructed to assess the effect of SES on survival using the NPCR analytic dataset. A total of 409 681 meningioma cases were identified. Meningioma incidence increased with higher county-level SES with Q5 (highest quintile) having a 12% higher incidence than Q1 (incidence rate ratios (IRR) = 1.12, 95%CI: 1.10-1.14; P < .0001). The Hispanic group was the only racial-ethnic group that had lower SES associated with increased meningioma incidence (Q5: age-adjusted incidence ratio (AAIR) = 9.02, 95%CI: 8.87-9.17 vs. Q1: AAIR = 9.33, 95%CI: 9.08-9.59; IRR = 0.97, 95%CI: 0.94-1.00; P = .0409). Increased likelihood of surgical treatment was associated with Asian or Pacific Islander non-Hispanic individuals (compared to White non-Hispanic (WNH)) (OR = 1.28, 95%CI: 1.23-1.33, P < .001) and males (OR = 1.31, 95%CI: 1.29-1.33, P < .001). Black non-Hispanic individuals (OR = 0.90, 95%CI: 0.88-0.92, P < .001) and those residing in metropolitan areas (OR = 0.96, 95%CI: 0.96-0.96, P < .001) were less likely to receive surgical treatment compared to WNH individuals. Overall median survival was 137 months, and survival was higher in higher SES counties (Q5 median survival = 142 months). Higher county-level SES was associated with increased meningioma incidence, surgical treatment, and overall survival. Racial-ethnic stratification identified potential disparities within the meningioma population. Further work is needed to understand the underpinnings of socioeconomic and racial disparities for meningioma patients.