Impact Of Neighborhood Socioeconomic Status Research Articles

Abstract WP250: The Changing Impact of Neighborhood Socioeconomic Status on Stroke Incidence in the BASIC Project

Background: Poverty is associated with increased stroke risk, but it is unclear how this has changed over time. We sought to evaluate temporal trends in stroke incidence by neighborhood socioeconomic status (nSES) in a south Texas community. Methods: Within the BASIC project, we identified all first-ever ischemic and hemorrhagic strokes among Mexican American or non-Hispanic White persons, age >45, from 2010-2021, geocoded to census tract by patient home address (n=4,137). Using 5 year rolling average annual data from the American Community Survey, a composite nSES score was assigned to each census tract, reflecting aggregate neighborhood income, wealth, education, and occupation (range -1.60, 1.95; lower=poorer). For each year, the nSES percentile of each tract was determined. Incidence rates were estimated using Poisson regression, with annual population estimates as offsets, including a quadratic term for time to account for nonlinear trends. The model included annual nSES percentile, age, sex, ethnicity, and nSES-time and ethnicity-time interactions. Results: Incidence rates for high vs low nSES neighborhoods for the 45-65-year age group are shown in the Figure. Incidence rate ratios for nSES changed over time (p<0.01 for interaction) in a u-shaped fashion, with no association present in 2010, a significant association in 2015 (RR for 90th vs 10th percentile nSES=0.59, 95% CI=0.49-0.70), and no association in 2021 (Figure). Conclusions: The gap in stroke incidence between the richest and poorest neighborhoods peaked in 2015 and was no longer present in 2021, due to declining rates in low nSES neighborhoods. Future work should explore the causes underlying these trends.

The relationship between neighborhood economic deprivation and community-acquired pneumonia related admissions in Maryland.

Community-acquired pneumonia (CAP) is a major health concern in the United States (US), with its incidence, severity, and outcomes influenced by social determinants of health, including socioeconomic status. The impact of neighborhood socioeconomic status, as measured by the Distressed Communities Index (DCI), on CAP-related admissions remains understudied in the literature. To determine the independent association between DCI and CAP-related admissions in Maryland. We conducted a retrospective study using the Maryland State Inpatient Database (SID) to collate data on CAP-related admissions from January 2018 to December 2020. The study included adults aged 18-85 years. We explored the independent association between community-level economic deprivation based on DCI quintiles and CAP-related admissions, adjusting for significant covariates. In the study period, 61,467 cases of CAP-related admissions were identified. The patients were predominantly White (49.7%) and female (52.4%), with 48.6% being over 65 years old. A substantive association was found between the DCI and CAP-related admissions. Compared to prosperous neighborhoods, patients living in economically deprived communities had 43% increased odds of CAP-related admissions. Residents of the poorest neighborhoods in Maryland have the highest risk of CAP-related admissions, emphasizing the need to develop effective public health strategies beneficial to the at-risk patient population.

Impact of Neighborhood Socioeconomic Status on Outcomes Following First-Stage Palliation of Single Ventricle Heart Disease.

Background The impact of neighborhood socioeconomic status (SES) on outcomes following first-stage palliation of single ventricle heart disease remains incompletely characterized. Methods and Results This was a single-center, retrospective review of consecutive patients who underwent the Norwood procedure from January 1, 1997 to November 11, 2017. Outcomes of interest included in-hospital (early) mortality or transplant, postoperative hospital length-of-stay, inpatient cost, and postdischarge (late) mortality or transplant. The primary exposurewas neighborhood SES, assessed using a composite score derived from 6 US census-block group measures related to wealth, income, education, and occupation. Associations between SES and outcomes were assessed using logistic regression, generalized linear, or Cox proportional hazards models, adjusting for baseline patient-related risk factors. Of 478 patients, there were 62 (13.0%) early deaths or transplants. Among 416 transplant-free survivors at hospital discharge, median postoperative hospital length-of-stay and cost were 24 (interquartile range, 15-43) days and $295 000 (interquartile range, $193 000-$563 000), respectively. There were 97 (23.3%) late deaths or transplants. On multivariable analysis, patients in the lowest SES tertile had greater risk of early mortality or transplant (odds ratio [OR], 4.3 [95% CI, 2.0-9.4; P<0.001]), had longer hospitalizations (coefficient 0.4 [95% CI, 0.2-0.5; P<0.001]), incurred higher costs (coefficient 0.5 [95% CI, 0.3-0.7; P<0.001]), and had greater risk of late mortality or transplant (hazard ratio, 2.2 [95% CI, 1.3-3.7; P=0.004]), compared with those in the highest tertile. The risk of late mortality was partially attenuated with successful completion of home monitoring programs. Conclusions Lower neighborhood SES is associated with worse transplant-free survival following the Norwood operation. This risk persists throughout the first decade of life and may be mitigated with successful completion of interstage surveillance programs.

The Impact of Neighborhood Socioeconomic Status, Race and Ethnicity, and Language on Prenatal Diagnosis of CHD.

Congenital heart disease (CHD) is the most prevalent birth defect. This study aimed to assess whether prenatal diagnosis (PD) of CHD and time of the diagnosis are associated with maternal race, ethnicity, neighborhood SES, and language. In this retrospective cohort study, we analyzed data on 163 patients who underwent surgical intervention for CHD within 30days of birth between 2011 and 2020 at the University of Maryland Children's Hospital. A neighborhood SES score was calculated using the mother's address at time of discharge and 6 SES variables from the US Census block group data with a previously published method by Diez Roux et al. Neighborhood SES did not impact the likelihood of receiving a PD of CHD; however, patients of Latino ethnicity were 3.2 times and non-English-preferred language patients were 5.1 times more likely to not receive a PD. Patients whose preferred language was a non-English language received a prenatal diagnosis 5.3weeks later, resulting in the PD being made in the third trimester rather than the second. Patients from the highest quartile SES received an earlier prenatal diagnosis, although this association was less significant when controlling for insurance type and preferred language. Significant disparities in PD of CHD were seen in patients of Latino ethnicity and patients who prefer non-English language. Better understanding of the root causes of these disparities will be important to guide interventions to reduce these disparities.

Impact of neighborhood socioeconomic status, income segregation, and greenness on blood biomarkers of inflammation.

Background:Neighborhood deprivation is linked with inflammation, which may explain poorer health across populations. Behavioral risk factors are assumed to largely mediate these relationships, but few studies have examined this. We examined three neighborhood contextual factors that could exert direct effects on inflammation: (1) neighborhood socioeconomic status, (2) an index of concentration at extremes (that measures segregation), and (3) surrounding vegetation (greenness).Methods:Using blood samples and addresses collected from prospective cohorts of 7,930 male (1990–1994) and 16,183 female (1986–1990) health professionals with at least one inflammatory marker, we prospectively linked neighborhood contextual factors to inflammatory biomarkers (adiponectin, C-reactive protein, interleukin-6, soluble tumor necrosis factor receptor-2). Log-transformed, z-scaled component measures were used to calculate an inflammation score. Neighborhood socioeconomic status and index of concentration of extremes were obtained from the 1990 decennial census and linked to participant addresses. Surrounding greenness was assessed from satellite data and focal statistics were applied to generate exposures within 270 m and 1230 m of the participants’ address. We fit multiple linear regression models adjusting for demographic, clinical, and behavioral risk factors.Results:Higher neighborhood socioeconomic status was associated with lower inflammation score in women (β for interquartile range increase = –27.7%, 95% CI: –34.9%, –19.8%) and men (β = –21.2%, 95% CI: –31.0%, –10.1%). Similarly, participants in neighborhoods with higher concentrations of high-income households were associated with lower inflammation score in women (β = –27.8%, 95% CI: –35.8%, –18.7%) and men (β = −16.4%, 95% CI: –29.7%, –0.56%). Surrounding greenness within 270 m of each participant’s address was associated with lower inflammation score in women (β = −18.9%, 95% CI: –28.9%, –7.4%) but not men. Results were robust to sensitivity analyses to assess unmeasured confounding and selection bias.Discussion:Our findings support the hypothesis that adverse neighborhood environments may contribute to inflammation through pathways independent of behavioral risk factors, including psychosocial stress and toxic environments.

The impact of neighborhood socioeconomic status on retention in care and viral suppression among people living with HIV

ABSTRACT Our study combined publicly available neighborhood socioeconomic status (nSES) data from the U.S. Census and clinical data to investigate the relationships between nSES, retention in care (RIC) and viral suppression (VS). Data from 2275 patients were extracted from 2009 to 2015 from a midwestern infectious diseases clinic. RIC was defined as patients who kept ≥ 3 visits and VS as an average viral load <200 copies/mL during their index year of study. Logistic regression models provided estimates for neighborhood-level and patient-level variables. In multivariable models, patients living in zip codes with low disability rates (1.50, 1.30–1.70), who wereolder (1.02, 1.01–1.03), and receiving antiretroviral therapy (ART; 3.81, 3.56–4.05) were more likely to have RIC, while those who were unemployed (0.72, 0.45–0.98) and self-reported as BIPOC (0.79, 0.64–0.97) were less likely to have RIC. None of the nSES variables were significantly associated with VS in multivariable models, yet older age (1.05, 1.04–1.05) and self-reported as BIPOC (1.68, 1.36–2.09) were modestly associated with VS, and receiving ART (6.14, 5.86–6.42) was a strong predictor of VS. In multivariable models, nSES variables were independently predictive more than of patient-level variables, for RIC but not VS.

Socioeconomic disadvantage and human papillomavirus (HPV) vaccination uptake

ImportanceDespite availability of safe and effective human papillomavirus (HPV) vaccines, vaccination uptake remains low in the U.S. Research examining the impact of neighborhood socioeconomic status on HPV vaccination may help target interventions. ObjectiveTo examine the association between area deprivation and HPV vaccine initiation and completion. Design, setting, participantsRetrospective cohort study of individuals aged 11–18 years residing in the upper Midwest region. Receipt of HPV vaccination was examined over a three-year follow-up period (01/01/2016–12/31/2018). Main outcomes and measuresOutcomes of interest were initiation and completion of HPV vaccination. Demographic data were collected from the Rochester Epidemiology Project (REP). Area-level socioeconomic disadvantage was measured by calculating an Area Deprivation Index (ADI) score for each person, a measure of socioeconomic disadvantage derived from American Community Survey data. Multivariable mixed effect Cox proportional hazards models were used to examine the association of ADI quartiles (Q1-Q4) with HPV vaccine series initiation and completion, given initiation. ResultsIndividuals residing in census block groups with higher deprivation had significantly lower likelihood of HPV vaccine initiation (Q2: HR = 0.91, 0.84–0.99 Q3: HR = 0.83, 0.76–0.90; Q4: HR = 0.84, 0.74–0.96) relative to those in the least-deprived block groups (Q1). Similarly, those living in block groups with higher deprivation had significantly lower likelihood of completion (Q2: HR = 0.91, 0.86–0.97; Q3: HR = 0.87, 0.81–0.94; Q4: HR = 0.82, 0.74–0.92) compared to individuals in the least-deprived block groups (Q1). Conclusions and relevanceLower probability of both HPV vaccine-series initiation and completion were observed in areas with greater deprivation. Our results can inform allocation of resources to increase HPV vaccination rates in our primary care practice and provide an example of leveraging public data to inform similar efforts across diverse health systems.

From street address to survival: Neighborhood socioeconomic status and pancreatic cancer outcomes

BackgroundNeighborhood factors may influence cancer care through physical, economic, and social means. This study assesses the impact of neighborhood socioeconomic status on diagnosis, treatment, and survival in pancreatic cancer. MethodsPatients with pancreatic adenocarcinoma were identified in the 2010–2016 Surveillance Epidemiology and End Results database. Neighborhood socioeconomic status (divided into tertiles) was based on an National Cancer Institute census tract-level composite score, including income, education, housing, and employment. Multivariate models predicted metastasis at time of diagnosis and receipt of surgery for early-stage disease. Overall survival compared via Kaplan-Meier and Cox proportional hazards. ResultsFifteen thousand four hundred and thirty-six patients (29.7%) lived in low neighborhood socioeconomic status, 17,509 (33.7%) in middle neighborhood socioeconomic status, and 19,010 (36.6%) in high neighborhood socioeconomic status areas. On multivariate analysis, neighborhood socioeconomic status was not associated with metastatic disease at diagnosis (low neighborhood socioeconomic status odds ratio 1.02, 95% confidence interval 0.97–1.07; ref: high neighborhood socioeconomic status). However, low neighborhood socioeconomic status was associated with decreased likelihood of surgery for localized/regional disease (odds ratio 0.60, 95% confidence interval 0.54–0.68; ref: high neighborhood socioeconomic status) and worse overall survival (low neighborhood socioeconomic status hazard ratio 1.18, 95% confidence interval 1.15–1.21; ref: high neighborhood socioeconomic status). ConclusionPatients from resource-poor neighborhoods are less likely to receive stage-appropriate therapy for pancreatic cancer and have an 18% higher risk of death.

Rural/urban differences in the prevalence of stroke risk factors: A cross-sectional analysis from the REGARDS study.

We previously described the magnitude of rural-urban differences in the prevalence of stroke risk factors and stroke mortality. In this report, we sought to extend the understanding of rural-urban differences in the prevalence of stroke risk factors by using an enhanced definition of rural-urban status and assessing the impact of neighborhood socioeconomic status (nSES) on risk factor differences. This analysis included 28,242 participants without a history of stroke from the REasons for Geographic And Racial Differences in Stroke (REGARDS) cohort. Participants were categorized into the 6-level ordinal National Center for Health Statistics Urban-Rural Classification Scheme. The prevalence of stroke risk factors (hypertension, diabetes, smoking, atrial fibrillation, left ventricular hypertrophy, and heart disease) was assessed across the rural-urban scale with adjustment for demographic characteristics and further adjustment for nSES score. Hypertension, diabetes, and heart disease were more prevalent in rural than urban regions. Higher odds were observed for these risk factors in the most rural compared to the most urban areas (odds ratios [95% CI]: 1.25 [1.11-1.42] for hypertension, 1.15 [0.99-1.33] for diabetes, and 1.19 [1.02-1.39] for heart disease). Adjustment for nSES score partially attenuated the odds of hypertension and heart disease with rurality, completely attenuated the odds of diabetes, and unmasked an association of current smoking. Some of the higher stroke mortality in rural areas may be due to the higher burden of stroke risk factors in rural areas. Lower nSES contributed most notably to rural-urban differences for diabetes and smoking.

Abstract MP23: Neighborhood Disadvantage And Oral Anticoagulant Use In Patients With Atrial Fibrillation

Background: Atrial Fibrillation (AF) is the most common heart rhythm disorder in the US and is treated with anticoagulation to mediate patients’ increased risk of ischemic stroke and death. Direct-acting oral anticoagulants (DOACs) are associated with better patient outcomes than warfarin, but prior studies show disparities in DOAC prescription. AF patients with low socioeconomic status (SES) have an increased risk of AF incidence, adverse outcomes, and mortality. Despite SES disparities in AF outcomes and prescribed medications, the impact of neighborhood SES (ADI) on AF management is unclear. We hypothesized that in comparison to patients with high ADI (e.g. the most disadvantaged), those with low ADI will be more likely to initiate any oral anticoagulants (OACs) and will be more likely to initiate DOACs. Methods: We conducted a retrospective observational study using national data from the Veterans Health Administration (VA) of newly diagnosed AF patients. Our independent variable was ADI, a marker of SES incorporating income, education, employment etc. Our model assessed numerous baseline patient, provider, and system-level covariates. We grouped patients into ADI quintiles, with Q1 being the lowest ADI (e.g., the least disadvantaged) and Q5 being the highest ADI, and used Q5 as a reference value. We used mixed effects logistic regression models, with site as a random effect, to determine the adjusted odds of initiating any OACs and of initiating DOACs by ADI quintile. Results: In our final cohort including 111,666 patients, 10,9386 (98.0%) were male and 2280 (2.0%) were female. The overall mean age at diagnosis was 72.86 (SD 10.4). Patients had the following medical comorbidities: Congestive heart failure: 18212, (16.3%); Hypertension: 84944, (76.1%); Diabetes: 70673, (63.3%); Vascular Disease: 46599, (41.7%). The ADI quintiles included the following patients: Q1: 21570, (20.3%); Q2: 21032, (19.8%); Q3: 21439, (20.2%); Q4: 20974, (19.8%); Q5: 21215, (20.0%). There was no significant difference in the odds of initiating any OAC between ADI quintiles compared to Q5 (Q1: adjusted odds ratio [95% CI], 0.95 [ 0.9, 1.01]; p=0.11). Among patients initiating DOAC, there was a significant association between low ADI and higher odds of initiating DOAC (Q1: 1.39 [1.29, 1.50]); (Q2: 1.18 [1.10, 1.27]); (Q3: 1.13 [1.06, 1.20]); (Q4: 1.09 [1.02, 1.16]). Each ADI quintile had a significantly higher odds of initiating DOACs compared to the highest ADI quintile. Conclusions: Patients with lower ADI are significantly more likely to be prescribed DOACs compared to patients with the highest levels of ADI. We found no significant difference in initiation of any OAC between ADI quintiles, which may result from high Warfarin utilization in the VA compared to the general population. Our data suggests that differences in neighborhood deprivation contribute to disparities in the prescribing DOACs in the VA.

Neighborhood Socioeconomic Status and Stroke Incidence: A Systematic Review.

To summarize overall patterns of the impact of neighborhood socioeconomic status (nSES) on stroke incidence and uncover potential gaps in the literature, we conducted a systematic review of studies examining the association between nSES and stroke incidence, independent of individual SES. Four electronic databases and reference lists of included articles were searched, and corresponding authors were contacted to locate additional studies. A keyword search strategy included the 3 broad domains of neighborhood, SES, and stroke. Eight studies met our inclusion criteria (e.g., nSES as an exposure, individual SES as a covariate, and stroke incidence as an outcome). We coded study methodology and findings across the 8 studies. The results provide evidence for the overall nSES and stroke incidence association in Sweden and Japan, but not within the United States. Findings were inconclusive when examining the nSES-stroke incidence association stratified by race. We found evidence for the mediating role of biological factors in the nSES-stroke incidence association. Higher neighborhood disadvantage was found to be associated with higher stroke risk, but it was not significant in all the studies. The relationship between nSES and stroke risk within different racial groups in the United States was inconclusive. Inconsistencies may be driven by differences in covariate adjustment (e.g., individual-level sociodemographic characteristics and neighborhood-level racial composition). Additional research is needed to investigate potential intermediate and modifiable factors of the association between nSES and stroke incidence, which could serve as intervention points.

Abstract P881: Geospatial Analysis of Community and Patient Risk Factors for Poor Functional Outcome in Stroke

Introduction: Low neighborhood socioeconomic status has been associated with increased stroke risk, but it is not clear if this association is independent of individual socioeconomic status and clinical risk. Neighborhood racial segregation as defined by a racial isolation index (RI) has been shown to be associated with increased risk of stroke mortality. Using geospatial mapping techniques, we sought to determine the impact of neighborhood socioeconomic status and racial isolation on post-stroke functional outcome. Methods: Using our center’s prospective stroke registry, we matched charts for ischemic stroke patients seen between 1/1/2008 and 12/31/2018 with address data obtained from our hospital EMR for geospatial mapping. Racial Isolation (RI) and Neighborhood Deprivation Index (NDI) were calculated using census data. To assess the relationship between neighborhood factors and functional outcome, we used geographically weighted regression models. We fitted univariate and multivariate multinomial logistic regression models for functional outcome, and linear regression models for the percentage of poor functional outcome (defined as mRS 4-6). Significance was determined to be p &lt; 0.05. Results: We included 5204 patients across 786 county census tracts. NDI (range -1.75 to 3.79) and RI (range 0 to 1) both appear to correlate visually with stroke rates of our patients across individual census tracts (Figure 1). Hypertension, diabetes, and dyslipidemia rates at individual and census tract level were significantly associated with poor functional outcome. NDI was not (OR 1.00 95% CI 0.99 - 1.00), but RI trended significant (OR 1.04 95% CI (0.99 - 1.09). Overall explanatory power was limited, warranting further investigation. Conclusions: Patient’s individual risk factors increased likelihood of poor functional outcome, but community segregation and socioeconomic deprivation indices are not predictors of poor functional outcome.

Impact of Neighborhood Socioeconomic Status on Cardiovascular Risk Factors in a French Urban Population

Over the past decade, neighborhood deprivation suggested to play a significant role in the repartition of cardiovascular risk factors. We assessed the effect of neighborhood socioeconomic position on the main cardiovascular risk factors in a French urban population with a comprehensive and multidimensional indicator. Between 2010 and 2018, we studied cardiovascular risk factors in 7821 participants residing in Paris west suburb (CARVAR 92 cohort). Three neighborhood clusters of decreasing socioeconomic status were obtained after a hierarchical clustering analysis applied to eighteen measures of socioeconomic status. We used multivariate logistic models to estimate the association between neighborhood clusters and risk factors. Medium and low socioeconomic status were associated with higher risk of diabetes (OR = 1.63; 95%CI 1.23-2.15, OR = 3.28 95%CI 2.49-4.31, respectively) and obesity (OR = 1.42; 95%CI 1.23-1.64, OR = 2.23; 95%CI 1.92-2.58, respectively). High blood pressure and smoking intensity were also significantly associated with the most deprived neighborhoods (OR = 1.42; 95%CI 1.20-1.68, OR = 1.66; 95%CI 1.24-2.22, respectively) ( Fig. 1 ). Higher odds of diabetes and obesity were observed among the subgroup of females, especially in the lowest socioeconomic status neighborhoods (OR 3.85 95%CI 2.47-5.98, OR 2.55 95%CI 2.10-3.09, respectively), compared to those of males (OR = 2.81 95%CI 2.07-3.80, OR = 1.81 95%CI 1.43-2.30) ( Table 1 ). Even in a country owning universal welfare coverage such as France, neighborhoods socioeconomic status is still nowadays strongly associated with an uneven distribution of cardiovascular risk factors. Most affected risks factors are diabetes and obesity. Furthermore, deprivation seems to have a stronger negative effect on women.

Impact of neighborhood socioeconomic status on the association between occupational radiation exposure and circulatory disease

Background: Exposure to ionizing radiation, even at low-to-moderate doses, increases the risk of circulatory disease (CD) incidence and mortality. The risk of CD is also influenced by an individual’s social environment, and this may modify the effect of occupational exposures like ionizing radiation. Aim: We examined the effect of neighborhood socioeconomic status (nSES) on incidence and mortality from overall CD, ischemic heart disease (IHD) and cerebrovascular disease (CeVD) in the US Radiologic Technologists Study (USRT) between 1994 and 2012. Additionally, we assessed whether nSES confounds and/or modifies the association between occupational radiation exposure and CD outcomes. Methods: Cumulative radiation dose (mGy) was estimated for each participant. We created tertiles of nSES combining six items from the 1990 Census (household income, housing value, % households with interest/income, % adults who completed high school, % adults who completed college, % of persons in managerial occupations). Using discrete time hazard models, we estimated HR and 95%CI for the association between radiation, nSES and CD outcomes. Results: Compared to residents from the top nSES tertile, technologists from low-nSES areas had an elevated risk of overall CD mortality, IHD mortality and incidence, and CeVD incidence (HRs ranging from 1.18 to 1.25, 95%CIs:1.07-1.42), but not for CeVD mortality (HR: 0.92, 95%CI: 0.75-1.15) adjusting for radiation and individual education. We found no evidence of confounding by nSES on the association between radiation and any CD outcomes. There was evidence of a multiplicative interaction between nSES tertiles and radiation exposure for all mortality outcomes (p-value for interaction: &lt;0.001 for overall CD, 0.003 for IHD and 0.004 for CeVD), but not for incidence. Conclusion: nSES is independently associated with CD mortality and incidence in a group of US radiologic technologists occupationally exposed to radiation. Additionally, nSES modifies (but does not confound) the association between radiation and CD mortality outcomes.

The implications of neighborhood socioeconomic status on surgical management and mortality in malignant phyllodes patients in the Surveillance, Epidemiology, and End Results program

BackgroundNeighborhood socioeconomic status has been implicated in breast cancer incidence and mortality. However, there are no studies on the impact of neighborhood socioeconomic status on clinical outcomes or surgical management among patients with phyllodes tumors. The objective of this study is to understand the relationship between neighborhood socioeconomic status, surgical management and disease specific mortality in malignant phyllodes tumor patients in the Surveillance, Epidemiology, and End Results program. MethodsSurveillance, Epidemiology, and End Results program was queried for malignant phyllodes tumor patients diagnosed between 2000 and 2016. Using the National Cancer Institute census tract-level index for neighborhood socioeconomic status the data were stratified into low neighborhood socioeconomic status, middle neighborhood socioeconomic status, and high neighborhood socioeconomic status. Bivariate intergroup analysis was conducted. Disease specific mortality was evaluated using a Cox proportional hazards model. ResultsOf the 651 patients with malignant phyllodes tumor in the sample, the disease specific mortality was 7.6% and 7.9% at 5 and 10 years, respectively. On bivariate analysis, there were no differences between the neighborhood socioeconomic status groups and surgery type (P = .794). On multivariable analysis, older age (≥71 years; hazard ratio 9.9; 95% confidence interval, 2.84–34.57; P < .001) and larger tumor size (≥40 mm; hazard ratio 2.20; 95% confidence interval, 1.09–4.44; P = .027) were associated with a higher disease specific mortality compared with younger age (≤ 40 years) and smaller tumor size (<40 mm). There was no association between neighborhood socioeconomic status and disease specific mortality (low neighborhood socioeconomic status-ref, middle neighborhood socioeconomic status hazard ratio 0.87 (95% confidence interval, 0.71–1.78; P = .71), high hazard ratio 0.91 (95% confidence interval, 0.44–1.90, P = .81). ConclusionAmong malignant phyllodes tumor patients in the Surveillance, Epidemiology, and End Results program, disease specific mortality and surgical management are mostly driven by tumor characteristics and not social determinants of health.

Abstract C067: Impact of neighborhood socioeconomic status on survival among young patients with acute leukemia in California

Abstract Introduction: Among young patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), minority race/ethnicity and lack of health insurance have been associated with lower survival. We sought to evaluate the impact of neighborhood socioeconomic status (nSES) and neighborhood archetype on early mortality and overall survival among patients with ALL and AML in California. We hypothesized that living in low SES neighborhoods will be associated with lower survival among young patients with acute leukemia. Methods: Patients aged 0-39 years reported to the California Cancer Registry with a diagnosis of ALL or AML between 2006 and 2016 were included. Using a previously developed composite measure, nSES quintiles were evaluated as the primary exposure of interest. Latent class analysis was used to generate neighborhood archetypes based on 39 social and built environment attributes at the block group level, which were evaluated as an exploratory exposure. Patients were observed from diagnosis through last available follow up. Cox proportional hazards univariate models were used to estimate crude hazard ratios (HR) for early death (within 60 days following diagnosis) and overall survival (OS). Results: Of the 8761 patients included, 6338 were diagnosed with ALL and 2423 were diagnosed with AML. Median follow up time was 3.2 and 2.1 years, respectively. Minority race/ethnicity, older age (&amp;gt;19 years), lack of insurance, lack of chemotherapy, and treatment at an adult center were associated with lower OS in univariate models. Patients in the lowest quintile of nSES had an increased risk of early mortality for both ALL (HR 1.91, 95% CI 1.06, 3.47) and AML (HR 2.01, 95% CI 1.17, 3.45) relative to the highest quintile of nSES. Likewise, patients in the lowest quintile of nSES had lower OS for both ALL (HR 2.10, 95% CI 1.68, 2.62) and AML (HR 1.40, 95% CI 1.12, 1.76). A dose effect was observed with worse OS observed among quintiles 2-4 as well. In patients with ALL, relative to the highest status neighborhood archetype, all other neighborhood archetypes demonstrated lower OS, with the most pronounced effects in inner city (HR 2.35, 95% CI 1.79, 3.09), Hispanic small towns (HR 2.33, 95% CI 1.74, 3.11), and mixed SES class suburban neighborhoods (HR 2.27, 95% CI 1.65, 3.12). While there was a suggestion of differences by archetype among AML patients, none reached statistical significance. Conclusions: The substantial crude effect of neighborhood SES on early mortality and overall survival highlights an important disparity. Multivariable adjustment for other known predictors of survival is underway. When other aspects of the social/built environment are incorporated, the magnitude of the effect grows, suggesting that nSES interacts with other neighborhood factors such as the racial/ethnic makeup. The greater effects of neighborhood among ALL patients relative to AML patients may be linked to the prolonged, outpatient nature of the therapy and difficulties with treatment adherence among vulnerable populations. Citation Format: Lena E Winestone, Juan Yang, Daphne Y Lichtensztajn, Renata Abrahao, Theresa H Keegan, Iona Cheng, Scarlett L Gomez, Salma Shariff-Marco. Impact of neighborhood socioeconomic status on survival among young patients with acute leukemia in California [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C067.

Abstract C063: Impact of neighborhood socioeconomic status on breast cancer subtypes among Black women

Abstract Background: Compared to White women, African American/Black women are more likely to develop triple-negative breast cancer (TNBC), an aggressive breast cancer subtype. While many studies have examined individual-level socioeconomic status (SES) as a major social determinant of more aggressive breast tumor phenotypes, the impact of neighborhood-level SES (nSES) on breast cancer is not well understood, particularly among Blacks. Objective: To evaluate the impact of nSES on breast cancer subtypes among Black women with breast cancer. Methods: We evaluated the association of interest among 1,220 Black women with invasive breast cancer from 2006 to 2018 enrolled from 10 counties of New Jersey in the Women’s Circle of Health Study (WCHS). Residential address at diagnosis was geocoded to the census tract-level. Neighborhood SES was measured using the NCI’s census tract-level SES index, a time-dependent score constructed by a factor analysis of seven variables measuring different aspects of census tract SES (education index, percent unemployed, percent working class, median household income, percent below 150% of poverty line, median house value, and median rent). In a case-only analysis, we used multilevel multinomial logistic regressions to estimate nSES in relation to breast cancer subtype (TNBC, HER2-enriched, Luminal B vs. Luminal A). Models were adjusted for individual-level SES variables, body mass index and reproductive factors, and census tract-level percentage of Black residents. We tested whether the associations were modified by percentage of Black residents and participant’s education. Results: Higher nSES was found to predict a lower risk of TNBC. Compared to tertile 1 (lowest nSES score), the odds ratio (OR) was 0.91 (95% CI: 0.65, 1.29) for tertile 2 and 0.52 (95% CI: 0.34, 0.79) for tertile 3 (highest nSES score; p-trend: 0.001). Higher nSES was borderline significantly associated with a lower risk of Luminal B (OR: 0.61 comparing highest vs. lowest nSES tertile; 95% CI: 0.36, 1.03; p-trend: 0.055). The inverse association between nSES and TNBC was observed only among Black women living in census tracts with lower proportion of Black residents (p-for-interaction=0.08). Compared to the lowest nSES tertile, OR was 0.38 (95% CI: 0.21, 0.68) for the highest tertile (p-trend: &amp;lt;0.001). There was a suggestion that the inverse relationship of nSES with TNBC was also more pronounced among women who had relatively lower levels of education. Conclusion: Neighborhood socioeconomic environment may influence the development of TNBC among Black women, which might be buffered by some contextual factors in areas with more Black residents. Further investigation to elucidate these factors is needed. Citation Format: Bo Qin, Adana A.M. Llanos, Riddhi Babel, Jesse J. Plascak, Karen Pawlish, Christine B. Ambrosone, Kitaw Demissie, Chi-Chen Hong, Elisa V. Bandera. Impact of neighborhood socioeconomic status on breast cancer subtypes among Black women [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C063.

167 - Impact of neighborhood socio-economic status on bystander cardiopulmonary resuscitation in Paris

167 - Impact of neighborhood socio-economic status on bystander cardiopulmonary resuscitation in Paris

Capsule Commentary on Joynt et al., The Impact of Neighborhood Socioeconomic Status and Race on the Prescribing of Opioids in Emergency Departments Throughout the United States

This study used data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) between 2006 and 2009 to examine the prescription of opioids for moderate to severe pain in emergency departments across the United States.1 Patients from poorer neighborhoods and African-Americans and Latinos were less likely to be prescribed opioids. The effects for race and ethnicity persisted even when neighborhood factors were controlled. This study is the first to examine the effect of socio-economic status (SES) on the prescription of opioids, and is thus an important addition to the literature on inequities in health care. As the authors note, however, the study is limited in that individual patient characteristics for SES were unavailable and neighborhood characteristics were used as proxies for patient SES. Inequities in the delivery of health care for minority groups generally,2 and in the prescription of opioids specifically,3,4 has been well documented and reflect inequities in society as a whole. However, emergency department physicians typically see patients for a short period of time, and often have little personal knowledge about their patients. As a consequence, ED physicians may be more likely to make decisions about opiate prescriptions based on cultural stereotypes, specifically the perception that racial and ethnic minorities are more likely to abuse drugs of all sorts. Health care is delivered in the context of a relationship between the provider and the patient,5 and many factors may influence prescribing practices, including how patients report their symptoms, how these reports are interpreted by clinicians and whether or not pain medications are requested.3 While likely an important component, current inequities in the quality of care delivered to minorities is unlikely to be determined by cultural stereotypes alone.3 Future research needs to move beyond documenting inequities. We need to determine the sources of these disparities and test interventions to reduce disparate care.

The Impact of Neighborhood Socioeconomic Status and Race on the Prescribing of Opioids in Emergency Departments Throughout the United States

Racial and ethnic disparities in opioid prescribing in the emergency department (ED) are well described, yet the influence of socioeconomic status (SES) remains unclear. (1) To examine the effect of neighborhood SES on the prescribing of opioids for moderate to severe pain; and (2) to determine if racial disparities in opioid prescribing persist after accounting for SES. We used cross-sectional data from the National Hospital Ambulatory Medical Care Survey between 2006 and 2009 to examine the prescribing of opioids to patients presenting with moderate to severe pain (184 million visits). We used logistic regression to examine the association between the prescribing of opioids, SES, and race. Models were adjusted for age, sex, pain-level, injury-status, frequency of emergency visits, hospital type, and region. Our primary outcome measure was whether an opioid was prescribed during a visit for moderate to severe pain. SES was determined based on income, percent poverty, and educational level within a patient's zip code. Opioids were prescribed more frequently at visits from patients of the highest SES quartile compared to patients in the lowest quartile, including percent poverty (49.0 % vs. 39.4 %, P<0.001), household income (47.3 % vs. 40.7 %, P<0.001), and educational level (46.3 % vs. 42.5 %, P=0.01). Black patients were prescribed opioids less frequently than white patients across all measures of SES. In adjusted models, black patients (AOR 0.73; 95 % CI 0.66–0.81) and patients from poorer areas (AOR 0.76; 95 % CI 0.68–0.86) were less likely to receive opioids after accounting for pain-level, age, injury-status, and other covariates. Patients presenting to emergency departments from lower SES regions were less likely to receive opioids for equivalent levels of pain than those from more affluent areas. Black and Hispanic patients were also less likely to receive opioids for equivalent levels of pain than whites, independent of SES.