The Association Between Neighborhood Socioeconomic Status and Clinical Outcomes Among Patients 1 Year After Hospitalization for Cardiovascular Disease

Abstract

Residing in lower socioeconomic status neighborhoods is associated with increased risk of morbidity and mortality. Few studies have examined this association for cardiovascular disease (CVD) outcomes in a treated population in New York City (NYC). The purpose of this study was to determine the relationship between neighborhood level poverty and one-year clinical outcomes (rehospitalization and/or death) among hospitalized patients with CVD. Data on rehospitalization and/or death at one-year were collected from consecutive patients admitted at a university medical center in NYC from November 2009 to September 2010. NYC residents totaled 2,198. U.S. Census 2000 zip code data was used to quantify neighborhood SES into quintiles of poverty (Q1=lowest poverty to Q5=highest poverty). Univariate analyses were used to determine associations between neighborhood poverty and baseline characteristics and comorbidities. A logistic regression analysis was used to calculate odds ratios for the association between quintiles of poverty and rehospitalization/death at one year. Fifty-five percent of participants experienced adverse outcomes. Participants in Q5 (9%) were more likely to be female (odds ratio [OR]=0.49,95% confidence interval [CI] 0.33–0.73), younger (OR=0.50,95% CI 0.34–0.74), of minority race/ethnicity (OR=18.24,95% CI 11.12=29.23), and have no health insurance (OR=4.79,95% CI 2.92–7.50). Living in Q5 was significantly associated with increased comorbidities, including diabetes mellitus and hypertension, but was not a significant predictor of rehospitalization/death at one year. Among patients hospitalized with CVD, higher poverty neighborhood residence was significantly associated with a greater prevalence of comorbidities, but not of rehospitalization and/or death. Affordable, accessible resources targeted at reducing the risk of developing CVD and these comorbidities should be available in these communities.

Spatial social polarisation: using the Index of Concentration at the Extremes jointly for income and race/ethnicity to analyse risk of hypertension

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A novel approach for measuring residential socioeconomic factors associated with cardiovascular and metabolic health

“…Thus, we believe using block groups was superior to using census tracts. In addition, several studies examining neighborhood SES and health status used only one SES variable for their work; 25,54 we used 12 variables to define our residential clusters. Having more than one variable can provide a superior assessment of the population.…”

Symptom Distress Among Diverse Patients Referred for Community-Based Palliative Care: Sociodemographic and Medical Correlates

“…Because income level was unavailable in the electronic health record, poverty status was determined by comparing patients' zip codes to U.S. census data on the percentage of the population in this area living below the federal poverty level. 4,14,16,17 The zip codes were categorized into quintiles (Qs) (Q1 had <10% of residents living in poverty, Q2 had 10% e19.9%, Q3 had 20%e29.9%, Q4 had 30%e39.9%, and Q5 had >40%).…”