Abstract 16279: Impact of Race and Socioeconomic Status on Rates of Congestive Heart Failure Admissions, Readmissions, and Length of Stay

Introduction: Health disparities due to race and socioeconomic status persist among congestive heart failure (CHF) patients. Our hospital in the Philadelphia area is uniquely situated to study disparities as it sits on the border of a diverse inner city and suburban population. The area west of our hospital is known to have a drastically higher median income than the area to the east. We aimed to evaluate differences in rates of CHF admissions, readmissions, and length of stay (LOS) for patients based on race and socioeconomic status. Methods: From 3/1/2018 to 3/31/2020, 6,785 total patients were admitted to our hospital due to acute decompensated CHF. To compare rates of admission, readmission and a LOS > 5 days based on race and socioeconomic status, we used the SlicerDicer function of the EPIC electronic record platform. For race, we compared data for white and black patients. For socioeconomic status, we included a 10-mile radius around our hospital and used public records to collect median household income for 11 zip codes to the east and 11 to the west. The average yearly median household income for the east and west zip codes were USD $27,171 and $134,390, respectively. Outcomes are expressed as percentages and compared using a Chi-square test of independence and 95% confidence interval (CI) for differences. Significance was assessed at the 0.05 level. Results: Admission rates were significantly higher among Black patients at 67% compared to White patients at 58% (95% CI 7-11%, p<0.05). There was no significant difference between rates of readmission (60% for Black vs. 58% for White patients, 95% CI 0-4%, p=0.11) or LOS > 5 days (56% for Black vs. 55% for White patients, 95% CI 0-3%, p=0.42). Admission rates were significantly higher among patients from low income areas at 70% compared to high income areas at 56% (95% CI 11-17%, p<0.05). Readmission rates were not significantly different, 57% for low income and 56% for high income areas (95% CI 0-4%, p=0.82). Patients from low income areas were significantly more likely to have a LOS > 5 days at 57% compared to patients from high income areas at 53% (95% CI 0.8-8%, p<0.05). Conclusions: Race and socioeconomic status continue to impact CHF patients’ health outcomes including rates of admissions, readmissions, and length of stay.

Download Full-text

Neighbourhood characteristics and health outcomes: evaluating the association between socioeconomic status, tobacco store density and health outcomes in Baltimore City

Tobacco Control ◽

10.1136/tobaccocontrol-2017-053945 ◽

2017 ◽

Vol 27 (e1) ◽

pp. e19-e24 ◽

Cited By ~ 6

Author(s):

Panagis Galiatsatos ◽

Cynthia Kineza ◽

Seungyoun Hwang ◽

Juliana Pietri ◽

Emily Brigham ◽

...

Keyword(s):

Socioeconomic Status ◽

Life Expectancy ◽

Health Outcomes ◽

Low Income ◽

Household Income ◽

Spatial Regression ◽

Median Household Income ◽

Baltimore City ◽

Education Status ◽

The Relationship

IntroductionSeveral studies suggest that the health of an individual is influenced by the socioeconomic status (SES) of the community in which he or she lives. This analysis seeks to understand the relationship between SES, tobacco store density and health outcomes at the neighbourhood level in a large urban community.MethodsData from the 55 neighbourhoods of Baltimore City were reviewed and parametric tests compared demographics and health outcomes for low-income and high-income neighbourhoods, defined by the 50th percentile in median household income. Summary statistics are expressed as median. Tobacco store density was evaluated as both an outcome and a predictor. Association between tobacco store densities and health outcomes was determined using Moran’s I and spatial regression analyses to account for autocorrelation.ResultsCompared with higher-income neighbourhoods, lower-income neighbourhoods had higher tobacco store densities (30.5 vs 16.5 stores per 10 000 persons, P=0.01), lower life expectancy (68.5 vs 74.9 years, P<0.001) and higher age-adjusted mortality (130.8 vs 102.1 deaths per 10 000 persons, P<0.001), even when controlling for other store densities, median household income, race, education status and age of residents.ConclusionIn Baltimore City, median household income is inversely associated with tobacco store density, indicating poorer neighbourhoods in Baltimore City have greater accessibility to tobacco. Additionally, tobacco store density was linked to lower life expectancy, which underscores the necessity for interventions to reduce tobacco store densities.

Download Full-text

Socioeconomic Status and Outcomes in Heart Failure With Reduced Ejection Fraction From Asia

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.120.006962 ◽

2021 ◽

Vol 14 (4) ◽

Author(s):

Tiew-Hwa K. Teng ◽

Wan Ting Tay ◽

Arthur Mark Richards ◽

Timothy Shi Ming Chew ◽

Inder Anand ◽

...

Keyword(s):

Heart Failure ◽

Ejection Fraction ◽

Low Income ◽

Household Income ◽

High Income ◽

Socioeconomic Indicators ◽

Regional Income ◽

Reduced Ejection Fraction ◽

Patients With Heart Failure ◽

Education Status

Background: Little is known regarding the impact of socioeconomic factors on the use of evidence-based therapies and outcomes in patients with heart failure with reduced ejection fraction across Asia. Methods: We investigated the association of both patient-level (household income, education levels) and country-level (regional income level by World Bank classification, income disparity by Gini index) socioeconomic indicators on use of guideline-directed therapy and clinical outcomes (composite of 1-year mortality or HF hospitalization, quality of life) in the prospective multinational ASIAN-HF study (Asian Sudden Cardiac Death in Heart Failure). Results: Among 4540 patients (mean age: 60±13 years, 23% women) with heart failure with reduced ejection fraction, 39% lived in low-income regions; 34% in regions with high-income disparity (Gini ≥42.8%); 64.4% had low monthly household income (<US$1000); and 29.5% had no/only primary education. The largest disparity in treatment across regional income levels pertained to β-blocker and device therapies, with patients from low-income regions being less likely to receive these treatments compared with those from high-income regions and even greater disparity among patients with lower education status and lower household income within each regional income strata. Higher country- and patient-level socioeconomic indicators related to higher quality of life scores and lower risk of the primary composite outcome. Notably, we found a significant interaction between regional income level and both household income and education status ( P interaction <0.001 for both), where the association of low household income and low education status with poor outcomes was more pronounced in high-income compared with lower income regions. Conclusions: These findings highlight the importance of socioeconomic determinants among patients with heart failure in Asia and suggest that attention should be paid to address disparities in access to care among the poor and less educated, including those from wealthy regions. Registration: URL: https://clinicaltrials.gov ; Unique Identifier: NCT01633398.

Download Full-text

The Relationship Between Estimated Median Household Income and Critical Care Length of Stay in Children With Diabetic Ketoacidosis

Global Pediatric Health ◽

10.1177/2333794x20956770 ◽

2020 ◽

Vol 7 ◽

pp. 2333794X2095677

Author(s):

Meredith C. G. Broberg ◽

Jerri A. Rose ◽

Katherine N. Slain

Keyword(s):

Length Of Stay ◽

Diabetic Ketoacidosis ◽

Low Income ◽

Household Income ◽

Severity Of Illness ◽

Pediatric Intensive Care ◽

Median Household Income ◽

Poverty Threshold ◽

The Relationship ◽

Zip Code

Diabetic ketoacidosis (DKA) is an important diagnosis in the pediatric intensive care unit (PICU) and is associated with significant morbidity. We hypothesized children with DKA living in poorer communities would have unfavorable outcomes while critically ill. This single-center retrospective study included children with DKA admitted to a PICU over a 27-month period. Patients were classified as low-income if they lived in a ZIP code where the median household income was estimated to be less than 200% of the federal poverty threshold, or $48 016 for a family of 4. In this study, living in a low-income ZIP code was not associated with increased severity of illness, longer PICU length of stay (LOS), or readmission.

Download Full-text

Abstract 20: Patterns of Stroke Center Certification and the Impact on Stroke Mortality in Counties of New York State

Stroke ◽

10.1161/str.52.suppl_1.20 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Emily Chapman ◽

Kurt A Yaeger ◽

J D Mocco

Keyword(s):

New York ◽

Socioeconomic Status ◽

Household Income ◽

New York State ◽

Stroke Care ◽

Stroke Mortality ◽

Median Household Income ◽

Stroke Incidence ◽

York State ◽

The Relationship

Introduction: To establish a statewide stroke system in March 2019, New York State (NYS) created the Stroke Designation Program. Stroke centers (SCs) must be certified by a state-approved certifying organization (CO), which is tasked with initial designation and ongoing re-certification. Previous research has found an association at the national level between socioeconomic status and access to higher levels of acute stroke care. Objective: This study characterizes the relationship between socioeconomic status of NYS populations and stroke care level access by comparing median household income and wealth in counties with and without certified SCs. Methods: Population and median household income from the U.S. Census (2010), stroke epidemiological data from the Center for Disease Control, and Area Deprivation Index (ADI) data (ranked within NYS) from the Neighborhood Atlas, a project that quantifies disadvantage by census tract, were collected and averaged for each county. Income has been used to assess local wealth and ADI to analyze community health risks. Certification data were mined from quality check databases for The Joint Commission and Det Norske Veritas, the most commonly used COs. Student’s t-tests compared income and ADI in counties with at least one certified SC to those without. Linear regression characterized the relationship between income and ADI with number of certified SCs, stroke incidence and stroke mortality. Results: All 62 counties in NYS were investigated to yield 40 certified SCs. Counties with at least one certified SC had a significantly higher income ($68,183.63 vs. $57,155.12; p=0.03) and lower ADI (5.90 vs. 7.37; p=0.004) compared to counties with no certified SC. Higher income (p<0.001) and lower ADI (p<0.001) were also associated with more certified SCs. Counties with fewer certified SCs had significantly higher stroke mortality (p<0.001) despite having similar stroke incidence. Conclusion: Socioeconomic heterogeneity in NYS counties is correlated to differential access to certified SCs and quality stroke care, as fewer centers are found in lower-income and disadvantaged communities. Although populations with less access experience stroke at similar rates, this study finds higher death rates in these counties.

Download Full-text

Forecasting of Households Consumption Expenditure with Nonparametric Regression: The Case of Turkey

Zagreb International Review of Economics and Business ◽

10.1515/zireb-2016-0006 ◽

2016 ◽

Vol 19 (2) ◽

pp. 19-32

Author(s):

Noyan Aydin ◽

Taner Akmercan

Keyword(s):

Low Income ◽

Household Income ◽

Household Size ◽

High Income ◽

Consumption Expenditure ◽

Income Levels ◽

Parametric Regression ◽

Household Disposable Income ◽

R Programming ◽

The Relationship

Abstract The relationship between household income and expenditure is important for understanding how the shape of the economic dynamics of the households. In this study, the relationship between household consumption expenditure and household disposable income were analyzed by Locally Weighted Scatterplot Smoothing Regression which is a nonparametric method using R programming. This study aimed to determine relationship between variables directly, unlike making any assumptions are commonly used as in the conventional parametric regression. According to the findings, effect on expenditure with increasing of income and household size together increased rapidly at first, and then speed of increase decreased. This increase can be explained by having greater compulsory consumption expenditure relatively in small households. Besides, expenditure is relatively higher in middle and high income levels according to low income level. However, the change in expenditure is limited in middle and is the most limited in high income levels when household size changes.

Download Full-text

Socioeconomic Differences in Access to Neighborhood and Network Social Capital and Associations With Body Mass Index Among Black Americans

American Journal of Health Promotion ◽

10.1177/0890117119883583 ◽

2019 ◽

Vol 34 (2) ◽

pp. 150-160 ◽

Cited By ~ 1

Author(s):

Stephanie T. Child ◽

Andrew T. Kaczynski ◽

Katrina M. Walsemann ◽

Nancy Fleischer ◽

Alexander McLain ◽

...

Keyword(s):

Body Mass Index ◽

Social Capital ◽

Socioeconomic Status ◽

South Carolina ◽

Body Mass ◽

Social Cohesion ◽

Low Income ◽

Household Income ◽

Black Americans ◽

Neighborhood Environment

Purpose: To examine associations between socioeconomic status and two forms of social capital, namely, neighborhood and network measures, and how these distinct forms of capital are associated with body mass index (BMI) among Black residents of low-income communities. Design: Respondent-driven sampling was used to engage residents in a household survey to collect data on the respondents’ personal network, perceptions about their neighborhood environment, and health. Setting: Eight special emphasis neighborhoods in Greenville, South Carolina. Participants: N = 337 black/African American older adults, nearly half of whom have a household income of less than $15 000 and a high school education, were included. Measures: Neighborhood capital was assessed via three scales on social cohesion, collective efficacy, and social support from neighbors. Network capital was calculated via a position generator, common in egocentric network surveys. Body mass index was calculated with self-reported height and weight. Analysis: Multilevel linear regression models were used to examine the association between neighborhood and network capital and obesity among respondents within sampling chains. Results: Higher household income was associated with greater neighborhood capital, whereas higher educational attainment was associated with greater network capital. Social cohesion was negatively associated with BMI ( b = −1.25, 95% confidence interval [CI]: −2.39 to −0.11); network diversity was positively associated with BMI ( b = 0.31, 95% CI: 0.08 to 0.55). Conclusion: The findings shed light on how social capital may be patterned by socioeconomic status and, further, how distinct forms of capital may be differentially associated with health among black Americans.

Download Full-text

Medicare D Subsidies and Racial Disparities in Persistence and Adherence With Hormonal Therapy

Journal of Clinical Oncology ◽

10.1200/jco.2016.67.3350 ◽

2016 ◽

Vol 34 (36) ◽

pp. 4398-4404 ◽

Cited By ~ 18

Author(s):

Alana Biggers ◽

Yushu Shi ◽

John Charlson ◽

Elizabeth C. Smith ◽

Alicia J. Smallwood ◽

...

Keyword(s):

Breast Cancer ◽

Black Women ◽

Hormonal Therapy ◽

Low Income ◽

White Women ◽

Hispanic Women ◽

Ethnic Disparities ◽

Black Patients ◽

Hispanic Patients ◽

White Patients

Purpose To investigate the role of out-of-pocket cost supports through the Medicare Part D Low-Income Subsidy on disparities in breast cancer hormonal therapy persistence and adherence by race or ethnicity. Methods A nationwide cohort of women age ≥ 65 years with a breast cancer operation between 2006 and 2007 and at least one prescription filled for oral breast cancer hormonal therapy was identified from all Medicare D enrollees. The association of race or ethnicity with nonpersistence (90 consecutive days with no claims for a hormonal therapy prescription) and nonadherence (medication possession rate < 80%) was examined. Survival analyses were used to account for potential differences in age, comorbidity, or intensity of other treatments. Results Among the 25,111 women in the study sample, 77% of the Hispanic and 70% of the black women received a subsidy compared with 21% of the white women. By 2 years, 69% of black and 70% of Hispanic patients were persistent compared with 61% of white patients. In adjusted analyses, patients in all three unsubsidized race or ethnicity groups had greater discontinuation than subsidized groups (white patients: hazard ratio [HR], 1.83; 95% CI, 1.70 to 1.95; black patients: HR, 2.09; 95% CI, 1.73 to 2.51; Hispanic patients: HR, 3.00; 95% CI, 2.37 to 3.89). Racial or ethnic persistence disparities that were present for unsubsidized patients were not present or reversed among subsidized patients. All three subsidized race or ethnicity groups also had higher adherence than all three unsubsidized groups, although with the smallest difference occurring in black women. Conclusion Receipt of a prescription subsidy was associated with substantially improved persistence to breast cancer hormonal therapy among white, black, and Hispanic women and lack of racial or ethnic disparities in persistence. Given high subsidy enrollment among black and Hispanic women, policies targeted at low-income patients have the potential to also substantially reduce racial and ethnic disparities.

Download Full-text

Analysis of COVID-19 Case Demographics in Gary, Indiana

Proceedings of IMPRS ◽

10.18060/25841 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Yazan Al-Tarshan ◽

Maryam Sabir ◽

Cameron Snapp ◽

Martin Brown ◽

Roland Walker ◽

...

Keyword(s):

Low Income ◽

Household Income ◽

Black Population ◽

Health Department ◽

Poverty Line ◽

Median Household Income ◽

Predominantly Black ◽

Chi Square ◽

Gary Indiana ◽

Zip Code

Background and Hypothesis It has been reported in several recent studies that health disparities associated with COVID-19 infection r are prevalent in Black and impoverished populations. The contribution of multiple causes to these disparities is still not completely elucidated. Gary, Indiana has a large Black population (80%), high number of residents living below the poverty line (34%), and high unemployment rate (20%). We hypothesized that Black individuals in Gary have a higher rate of positive cases, hospitalizations, and deaths than non-Black individuals. Also, we hypothesized that (median household income measured by the zip code) is negatively correlated with COVID-19 positive cases, hospitalizations, and deaths. Methods In collaboration with the Gary Health Department, we analyzed data on all positive cases in the city from 06/16/2020 through 06/07/2021(totally 5149 cases). We compared this data to the data from 03/16/2020 through 06/16/2020 (totally 724 cases) that we analyzed previously. Data was de-identified and included age, race, ethnicity, and zip code. The data was analyzed using Pearson's chi-square test and regression analysis. Results When compared to the non-Black population in Gary age and population-adjusted rates of hospitalizations and deaths in the Black population are 3-fold (p<9.385E-11) and 2-fold (p<0.0171) higher, respectively. Surprisingly, the non-Black population had a higher infection rate than the Black population (p<2.69E-09). Median household income of a zip code is negatively correlated with COVID-19 hospitalizations in that zip code (R2=0.6345, p=0.03), but is does not affect the .rates of infections and deaths. Conclusion Our data show that in Gary, there is a clear health disparity of both income and race, specifically in the context of COVID-19. IUSMNW and Gary health officials can collaborate and utilize this data to reallocate resources to the highly populated, low income, and predominantly Black neighborhoods.

Download Full-text

“Association between Median Household Income, State Medicaid Expansion Status, and COVID-19 Outcomes Across US Counties”

10.1101/2021.02.03.21251075 ◽

2021 ◽

Author(s):

Tsikata Apenyo ◽

Antonio Vera-Urbina ◽

Khansa Ahmad ◽

Tracey H. Taveira ◽

Wen-Chih Wu

Keyword(s):

Mortality Risk ◽

Low Income ◽

Household Income ◽

Medicaid Expansion ◽

Median Household Income ◽

Incidence And Mortality ◽

Significant Difference ◽

Us Counties ◽

The Relationship ◽

Income Quartile

AbstractObjectiveThe relationship between socioeconomic status and its interaction with State’s Medicaid-expansion policies on COVID-19 outcomes across United States (US) counties are uncertain. To determine the association between median-household-income and its interaction with State Medicaid-expansion status on COVID-19 incidence and mortality in US countiesMethodsLongitudinal, retrospective analysis of 3142 US counties (including District of Columbia) to study the relationship between County-level median-household-income (defined by US Census Bureau’s Small-Area-Income-and-Poverty-Estimates) and COVID-19 incidence and mortality per 100000 of the population in US counties from January 20, 2020 through December 6, 2020. County median-household-income was log-transformed and stratified by quartiles. Medicaid-expansion status was defined by US State’s Medicaid-expansion adoption as of first reported US COVID-19 infection, January 20, 2020. Multilevel mixed-effects generalized-linear-model with negative binomial distribution and log link function compared quartiles of median-household-income and COVID-19 incidence and mortality, reported as incidence-risk-ratio (IRR) and mortality-risk-ratio (MRR), respectively. Models adjusted for county socio-demographic and comorbidity conditions, population density, and hospitals, with a random intercept for states. Multiplicative interaction tested for Medicaid-expansion*income quartiles on COVID-19 incidence and mortality.ResultsThere was no significant difference in COVID-19 incidence across counties by income quartiles or by Medicaid expansion status. Conversely, significant differences exist between COVID-19 mortality by income quartiles and by Medicaid expansion status. The association between income quartiles and COVID-19 mortality was significant only in counties from non-Medicaid-expansion states but not significant in counties from Medicaid-expansion states (P<0.01 for interaction). For non-Medicaid-expansion states, counties in the lowest income quartile had a 41% increase in COVID-19 mortality compared to counties in the highest income quartile (MRR 1.41, 95% CI: 1.25-1.59).Conclusions and RelevanceMedian-household-income was not related to COVID-19 incidence but negatively related to COVID-19 mortality in US counties of states without Medicaid-expansion. It was unrelated to COVID-19 mortality in counties of states that adopted Medicaid-expansion. These findings suggest that expanded healthcare coverage should be investigated further to attenuate the excessive COVID-19 mortality risk associated with low-income communities.Key FindingsQuestionIs there a relationship between COVID-19 outcomes (incidence and mortality) and household income and status of Medicaid expansion of US counties?FindingsIn this longitudinal, retrospective analysis of 3142 US counties, we found no significant difference in COVID-19 incidence across US counties by quartiles of household income. However, counties with lower median household income had a higher risk of COVID-19 mortality, but only in non-Medicaid expansion states. This relationship was not significant in Medicaid expansion states.MeaningExpanded healthcare coverage through Medicaid expansion should be investigated as an avenue to attenuate the excessive COVID-19 mortality risk associated with low-income communities.

Download Full-text

Contemporary Reevaluation of Race and Ethnicity With Outcomes in Heart Failure

Journal of the American Heart Association ◽

10.1161/jaha.120.016601 ◽

2021 ◽

Vol 10 (3) ◽

Author(s):

Samuel T. Savitz ◽

Thomas Leong ◽

Sue Hee Sung ◽

Keane Lee ◽

Jamal S. Rana ◽

...

Keyword(s):

Heart Failure ◽

Ejection Fraction ◽

Pacific Islander ◽

Left Ventricular Ejection ◽

Asian Pacific Islander ◽

Black Patients ◽

Hispanic Patients ◽

Race Ethnicity ◽

Asian Pacific ◽

White Patients

Background Variation in outcomes by race/ethnicity in adults with heart failure (HF) has been previously observed. Identifying factors contributing to these variations could help target interventions. We evaluated the association of race/ethnicity with HF outcomes and potentially contributing factors within a contemporary HF cohort. Methods and Results We identified members of Kaiser Permanente Northern California, a large integrated healthcare delivery system, who were diagnosed with HF between 2012 and 2016 and had at least 1 year of prior continuous membership and left ventricular ejection fraction data. We used Cox regression with time‐dependent covariates to evaluate the association of self‐identified race/ethnicity with HF or all‐cause hospitalization and all‐cause death, with backward selection for potential explanatory variables. Among 34 621 patients with HF, compared with White patients, Black patients had a higher rate of HF hospitalization (adjusted hazard ratio [HR], 1.28; 95% CI, 1.18–1.38) but a lower rate of death (adjusted HR, 0.78; 95% CI, 0.72–0.85). In contrast, Asian/Pacific Islander patients had similar rates of HF hospitalization, but lower rates of all‐cause hospitalization (adjusted HR, 0.89; 95% CI, 0.85–0.93) and death (adjusted HR, 0.75; 95% CI, 0.69–0.80). Hispanic patients also had a lower rate of death (adjusted HR, 0.85; 95% CI, 0.80–0.91). Sensitivity analyses showed that effect sizes for Black patients were larger among patients with reduced ejection fraction. Conclusions In a contemporary and diverse population with HF, Black patients experienced a higher rate of HF hospitalization and a lower rate of death compared with White patients. In contrast, selected outcomes for Asian/Pacific Islander and Hispanic patients were more favorable compared with White patients. The observed differences were not explained by measured potentially modifiable factors, including pharmacological treatment. Future research is needed to identify explanatory mechanisms underlying ongoing racial/ethnic variation to target potential interventions.

Download Full-text