American Community Survey Data Research Articles

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 < 0.001) were more likely and Black non-Hispanic (BNH) individuals (OR = 0.90, p < 0.001) were less likely to receive surgery than White non-Hispanic (WNH) individuals. Female sex (OR = 1.31, p < 0.001), living in a metropolitan area (OR = 0.96, p < 0.001), and increased age at diagnosis (OR = 0.96, p < 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 < 0.001), male sex (HR = 1.51, p < 0.001), BNH (HR = 1.31, p < 0.001), subtotal resection (HR = 1.38, p < 0.001), and malignant behavior(HR = 1.64, p < 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 Aneurysm

Studies have demonstrated socioeconomic status, insurance, race, and distance impact clinical outcomes in patients with abdominal aortic aneurysms (AAA). The purpose of this study was to assess if these factors also impact clinical outcomes in patients with thoracoabdominal aortic aneurysms (TAAA). We conducted a retrospective review of patients with TAAAs confirmed by CT imaging between 2009 to 2019 at a single institution. Patients' zip codes were mapped to American Community Survey Data to obtain geographic poverty rates. We used the standard US 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. Of 578 patients, 575 had zip code data and were analyzed. In both the non-operative (N=268) and operative (N=307) groups there were no significant differences in age, race, co-morbidities, clinical urgency, surgery utilization, or surgery modality between patients living in high-poverty areas (N=95, 16.4%) versus not. In the non-operative group, patients from high-poverty areas were more likely to have aneurysm due to dissection (37.5 vs. 17.6%, P=0.03). In multivariate analyses, patients from high-poverty zip codes had significantly worse non-operative survival (HR 1.9, 95% 1.1-3.3, P=0.03). In the repair group, high-poverty was also a significant predictor of reduced post-operative survival (HR 1.65, 95% 1-2.63, P=0.04). Adding the Gagne Index, these differences persisted in both groups (non-operative: HR 1.93, 95% 1.01-3.70, P = 0.05; operative: HR 1.62, 95% 1.03-2.56, p = 0.04). In Kaplan-Meier analysis the difference in post-operative survival began approximately 1.5 years after repair. Private insurance was predictive of improved post-operative survival (HR 0.42, 95% 0.18- 0.95, P=0.04) but reduced non-operative survival (HR 2.05, 95% 1.01-4.14, P=0.04). 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 (OR 1.58, 95% 1.08-2.33, P=0.02) and long-term survival (HR 0.61, 95% 0.41-0.92, P=0.02). Patients with TAAA living in high-poverty areas had significantly more dissections and suffered a nearly doubled risk of mortality compared to 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]

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.

Preliminary Data on the Rural‐Urban Commuting Area Codes for the ALLFTD Cohort

AbstractBackgroundThe rural‐urban commuting area (RUCA) codes classify communities using measures of population density, urbanization, and daily commuting from U.S. Census Bureau information. The ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study generated RUCA codes for enrolled participants to better understand our cohort demographics. The rural‐urban distribution of participants may provide important insights for clinical trial planning.MethodsThe current RUCA codes are generated from the 2010 decennial census and the 2006‐10 American Community Survey data. The codes are numbers (1‐10) that describe metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows.ResultsRUCA codes were generated on 784 ALLFTD participants. At their most recent visit, participant median age was 60, 51.1% female, and a median education of 16 years. Participants were classified as clinically normal (39.1%), behavioral variant FTD (25%), nonfluent PPA (6.7%), semantic variant PPA (6.6%), PSP (4.7%), MBCI (4.8%), corticobasal syndrome (5.9%), and the remaining 7% of participants had other dementia‐related diagnoses. For participants with sporadic disease, 87.4% live in a metropolitan area, 6.7% a micropolitan area, 3.2% a small‐town area, and 3.2% live in a rural area. In familial FTLD, a larger percentage of participants live in micropolitan or small town/rural community (18.8% combined; p = 0.029), driven largely by MAPT family participants (n = 101). 10% of those with a familial MAPT mutation live in a rural area; with an additional 18% in micropolitan (12.9%) or small‐town areas (5%). Among those with a familial C9orf72 expansion, 83.3% live in a metropolitan area, 8.9% micropolitan area, 5.6% in a small‐town area, and 2.2% in a rural area. Participants with a familial GRN mutation show a similar distribution: 84.7% live in a metropolitan area, 5.6% micropolitan, 6.9% small‐town, 2.8% rural.ConclusionsAdditional analyses to better understand if FTD families are disproportionately living in rural communities are underway. These analyses will better characterize sporadic and familial FTD demographics to assist with clinical trial design.

Abstract B077: Understanding the relationship between neighborhood deprivation and breast cancer mortality among Black and White women

Abstract Background: Neighborhood deprivation has been associated with increased breast cancer mortality among White women, but findings are inconsistent among Black women, who are more likely to die from the disease. To improve our understanding of the relation, we investigated the joint effects of race and neighborhood racial composition, residential mobility, and rurality on the neighborhood deprivation-breast cancer mortality association among White and Black women. Methods: In 2010-2017, 31,358 non-Hispanic White and Black women diagnosed with invasive stage I-IIIA breast cancer were identified by the Georgia Cancer Registry and were followed through 2019 for breast cancer mortality. The neighborhood deprivation index (NDI) was derived through principal component analysis of 2011-2015 block group-level American Community Survey (ACS) data on poverty, income, housing, unemployment, occupation, and education. Neighborhood racial composition and residential mobility were measured using 2011-2015 ACS data. Rurality was measured using Georgia Department of Public Health data. We used Cox proportional hazards regression to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI) for the association between NDI, in quintiles, and breast cancer mortality, overall and according to joint effects of race and neighborhood characteristics (neighborhood racial composition, residential mobility, and rurality). Results: During follow-up, 2,353 (1,347 non-Hispanic White, 1,006 non-Hispanic Black) women died from breast cancer. Living in the most deprived neighborhoods was associated with a 30% increased risk of breast cancer mortality (quintile 5 vs. 1: HR=1.30, 95% CI 1.13-1.49). The association was present among non-Hispanic White (quintile 5 vs. 1: HR=1.47, 95% CI 1.20-1.79) but not non-Hispanic Black women. We observed similar race-specific patterns when assessing jointly stratified associations. For example, among non-Hispanic White women, neighborhood deprivation was associated with breast cancer mortality irrespective of the additional neighborhood characteristics considered, with the strongest association observed among non-Hispanic White women living in the most deprived rural neighborhoods compared to those living in the least deprived urban neighborhoods (HR=1.70, 95% CI 1.30-2.22). In contrast, no association was found among non-Hispanic Black women in any strata of neighborhood racial composition, residential mobility, or rurality (non-Hispanic Black women living in the most deprived rural neighborhoods vs. those living in the least deprived urban neighborhoods: HR=1.05, 95% CI 0.78-1.41). Conclusions: Consistent with previous studies, our study found that living in a deprived neighborhood may increase breast cancer mortality among non-Hispanic White but not non-Hispanic Black women. Neighborhood racial composition, residential mobility, and rurality did not explain the lack of association among non-Hispanic Black women. Other factors beyond neighborhood may contribute to the high breast cancer mortality rate among this racial group. Citation Format: Lauren E. Barber, Leah Moubadder, Maret L. Maliniak, Jasmine M. Miller-Kleinhenz, Jeffrey M. Switchenko, Lauren E. McCullough. Understanding the relationship between neighborhood deprivation and breast cancer mortality among Black and White women [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B077.

Abstract B090: Breast cancer incidence rates by neighborhood socioeconomic status and ethnic enclaves among Asian American, Native Hawaiian, and Pacific Islander females in California

Abstract Background—Among Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females in the U.S., breast cancer incidence has steadily increased1. Of note, California has the largest population of AANHPI residents in the United States2. Few studies have examined whether the incidence rates of breast cancer among AANHPI populations differ by the neighborhood social environment. Thus, we examined the incidence of invasive breast cancer by AANHPI ethnic enclave (ethnically distinct neighborhoods) and neighborhood socioeconomic status (nSES) among AANHPI females in California. Methods— With 14,738 AANHPI females diagnosed with invasive breast cancer from 2008 through 2012 from the California Cancer Registry, we calculated the incidence rates of breast cancer. The 2007 to 2011 American Community Survey (ACS) data was used to assess AANHPI ethnic enclave index and nSES at the census tract level. Incidence rate ratios (IRRs) were analyzed by statewide quintiles of AANHPI ethnic enclave index and nSES. For analyses of AANHPI ethnic enclave index and nSES combined, low and high levels were defined as quintiles 1-3 and quintiles 4-5, respectively, and IRRs were calculated for joint AANHPI and nSES as low-low, low-high, high-low, and high-high. IRR associations of ethnic enclave and nSES by stage (localized vs. advanced (regional/distant)) were also assessed. Results— Overall, neighborhoods of lower AANHPI ethnic enclave index had higher incidence rates of breast cancer for AANHPI females in California. The incidence rate of breast cancer among AANHPI living in low ethnic enclave neighborhoods were 1.16 times that of AANHPI females living high ethnic enclave neighborhoods (95% CI 1.12 to 1.20; p&amp;lt;0.001). In addition, AANHPI females living in higher SES neighborhoods had higher incidence rates of breast cancer (IRR = 1.16 comparing highest to lowest nSES quintile, 95% CI 1.12 to 1.20). The incidence rate of breast cancer among AANHPI females living in low ethnic enclave+high SES neighborhoods was 1.32 times that of AANHPI females living in high ethnic enclave+low SES neighborhoods (95% CI 1.25 to 1.39; p&amp;lt;0.001). Similar patterns of associations were observed for localized and advanced stages of the disease. Conclusion—For AANHPI females in California, incidence rates of breast cancer differed by nSES, ethnic enclave, and jointly. Impact— Future studies should examine whether the impact of these neighborhood-level factors on breast cancer incidence rates differ across specific AANHPI ethnic groups and investigate the pathways through which they contribute to breast cancer risk. Citation Format: Alya Truong, Mi-Ok Kim, Meg Mckinley, Scarlett L. Gomez, Salma Shariff-Marco, Iona Cheng. Breast cancer incidence rates by neighborhood socioeconomic status and ethnic enclaves among Asian American, Native Hawaiian, and Pacific Islander females in California [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B090.

Earnings of US Physicians With and Without Disabilities

This cross-sectional study uses American Community Survey data to assess disability earnings gaps for physicians between 2005 and 2019.

Abstract B066: Neighborhood-level factors and breast cancer survival in U.S. Black women

Abstract Background: Black women living in the United States (U.S.) are 40% more likely to die from breast cancer than White women. There are multiple contributors to this disparity. One factor that warrants further research is the neighborhood environment. The legacy of structural racism, including redlining mortgage practices, has resulted in Black Americans being more likely to live in disadvantaged and economically deprived neighborhoods, regardless of their own individual socioeconomic (SES) status. We investigated the interplay of neighborhood-level and individual-level factors with breast cancer mortality in a cohort of breast cancer cases from the prospective Black Women’s Health Study. Methods: Included were 1,781 Black women with invasive breast cancer diagnosed at stages I-III. Data on individual-level factors were obtained by questionnaire and death data were obtained from the National Death Index. Participant addresses, updated every two years, were geocoded and linked with U.S. census data and American Community Survey data to create three neighborhood variables. Neighborhood SES and Neighborhood Disadvantage were based on factor analysis of items related to income, wealth, employment, etc., and provided a numerical score at the block group level, which was then analyzed as quartiles. The Index of Concentration at the Extremes (ICE) grouped locations into three income-based groups representing concentrated privilege, middle, and concentrated deprivation in each census tract.  Participants were followed to time of breast cancer death, death from any other cause, or end of follow-up. Time to breast cancer death was calculated in months. Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI). All analyses were adjusted for age at diagnosis and stage at diagnosis. Results: During follow-up from 1997-2019, there were 464 deaths, of which 286 deaths were from breast cancer. The HR for living in the most disadvantaged neighborhood relative to the least disadvantaged was 1.71 (95% CI: 1.21, 2.42), and the HR for lowest quartile of neighborhood SES relative to highest was 1.44 (95% CI: 1.01, 2.06). Lastly, for women living in concentrated deprivation as compared to women living in concentrated privilege, the HR for breast cancer mortality was 1.64 (95% CI: 1.22, 2.20). Further control for body mass index, vigorous activity, smoking, alcohol intake, and initial treatments did not reduce the magnitude of the associations. In addition, the observed associations were similar for women with estrogen receptor positive and estrogen receptor negative breast cancer. Conclusion: In this study of U.S. Black women, those who lived in disadvantaged neighborhoods were more likely to die from their breast cancer, even after accounting for stage at diagnosis and lifestyle factors. The findings suggest that other attributes of the neighborhood environment, including chronic stress (e.g., from noise, violence, lack of green space) and distance to treatment facilities likely play a role.  Citation Format: Etienne X. Holder, Nuo N. Xu, Julie R. Palmer. Neighborhood-level factors and breast cancer survival in U.S. Black women [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B066.

Abstract IA039: Individual, cultural, and area-based factors associated with survivorship care among Asian American childhood cancer survivors

Abstract With treatment advances for childhood cancer, over 80% of patients achieve long-term survival. However, cancer treatments often lead to serious issues, including chronic health problems and early mortality. As a result, life-long cancer-focused long-term follow-up care (LTFU) is essential for childhood cancer survivors (CCS) to screen for, prevent, and treat late effects. Among Asian Americans, who represent the fastest growing ethnic group and the largest group of new immigrants in the United States, rates of LTFU and factors influencing cancer-focused care among CCS are unknown. To address this research gap, we are currently recruiting a population-based cohort of roughly 330 young adult Asian American CCS and their parents in Los Angeles and Orange Counties, California, to examine individual, cultural, and area-level factors (e.g., impacts of residence in an ethnically concentrated neighborhood or “ethnic enclave”) related to survivorship care utilization. Our preliminary data from the Project Forward cohort, a cancer registry–derived, population-based study of risk and protective factors of cancer-related follow-up care among young adult CCS Indicated lower rates of LTFU among Asian American (versus other racial and ethnic groups) and was lowest for non-US-born Asian American CCS (45.8% compared to 62% non-Latino white). To better understand the potential role of neighborhood level enclave in LTFU, we examined all cancer cases of Asian race/ethnicity ages 18-39, living in Los Angeles or Orange County, California, diagnosed while under age 21 in the years 1991-2018 (N=743). Focusing on the most common subgroups (Chinese, Korean, Vietnamese, and Filipino), we were able to identify distinct clusters of residential enclave neighborhoods for each subgroup. We then linked cases via their census tract of residence to American Community Survey data to examine factors associated with LTFU among CCS. For all Asian subgroups, the proportion of non-US born individuals was higher inside the enclave than outside, as was the proportion of individuals reporting they speak English “less than very well.” In addition, the direction of the differences varied in potential LTFU-related factors by enclave status and Asian subgroup: for example, Koreans residing inside a Korean enclave were more likely to have access to a vehicle while Filipinos living inside Filipino enclaves were more likely to not have vehicle access (in both cases, versus those residing outside enclaves). Thus, factors related to enclave residence may have unique positive and negative associations with LTFU. Overall, understanding the dynamics of individual, cultural, and enclave-related factors will help identify methods to increase culturally congruent outreach and intervention strategies to promote LTFU for Asian American CCS.  Citation Format: Kimberly A. Miller. Individual, cultural, and area-based factors associated with survivorship care among Asian American childhood cancer survivors [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr IA039.

Empirical evidence supporting the inclusion of multi-axes segregation in assessing US county health

To facilitate community action toward health equity, the County Health Rankings & Roadmaps program (CHR&R) assigns health rankings to US counties. The CHR&R conceptual model considers White-Black and White-non-White dissimilarity values to represent residential segregation as part of the family and social support subcomponent. As the US is greying and becoming more multi-racial-ethnic, the two-group White-centered segregation measures are inadequate to capture segregation among population subgroups in the US. Thus, we evaluate the relevancy of segregation measures that consider multiple racial, ethnic, and age groups in assessing US county health. Besides using the two-group dissimilarity index to measure White-centered racial segregation as conceptualized by CHR&R, the study also uses the multi-group generalized dissimilarity index to measure racial-ethnic-age segregation by counties, employing both aspatial and spatial versions of these measures. These indices are computed for counties using the 2015–2019 American Community Survey data at the census tract level. Descriptive statistics and regressions controlling for sociodemographic factors and healthcare access are used to assess the contributions of individual segregation measures to mortality (life expectancy, years of potential life lost and premature mortality) and morbidity (frequent mental distress, frequent physical distress, and low birth weight) indicators representing county health.Overall, correlations between these indicators and most segregation measures are significant but weak. Regression results show that many segregation measures are not significantly related to mortality indicators, but most are significantly associated with morbidity indicators, with the magnitudes of these associations higher for the multi-group racial-ethnic-age segregation index and its spatial version. Results provide evidence that racial-ethnic-age segregation is associated with county-level morbidity and that spatial measures capturing segregation of multiple population axes should be considered for ranking county health.