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

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.

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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.

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“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.

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

Circulation ◽

10.1161/circ.142.suppl_3.16279 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Muhammad A Shakir ◽

Meghan E Buckley ◽

William D Surkis ◽

John M Clark

Keyword(s):

Heart Failure ◽

Socioeconomic Status ◽

Length Of Stay ◽

Low Income ◽

Household Income ◽

High Income ◽

Median Household Income ◽

Admission Rates ◽

Black Patients ◽

White Patients

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.

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Spatiotemporal patterns of urban mosquitoes are modulated by socioeconomic status and environmental traits in the United States

10.1101/2021.10.30.466623 ◽

2021 ◽

Author(s):

Senay Yitbarek ◽

Kelvin Chen ◽

Modeline Celestin ◽

Matthew McCary

Keyword(s):

United States ◽

Socioeconomic Status ◽

Low Income ◽

Household Income ◽

Meta Analysis ◽

Spatial Regression ◽

The United States ◽

Urban Environments ◽

Urban Landscapes ◽

Lower Income

The distribution of mosquitoes and associated vector diseases (e.g., West Nile, dengue, and Zika viruses) is likely a function of environmental conditions in the landscape. Urban environments are highly heterogeneous in the amount of vegetation, standing water, and concrete structures covering the land at a given time, each having the capacity to influence mosquito abundance and disease transmission. Previous research suggests that socioeconomic status is correlated with the ecology of the landscape, with lower-income neighborhoods generally having more concrete structures and standing water via residential abandonment, garbage dumps, and inadequate sewage. Whether these socio-ecological factors affect mosquito distributions across urban environments in the United States (US) remains unclear. Here, we present a meta-analysis of 22 paired observations from 15 articles testing how socioeconomic status relates to overall mosquito burden in urban landscapes in the United States. We then analyzed a comprehensive dataset from a socioeconomic gradient in Baltimore, Maryland to model spatiotemporal patterns of Aedes albopictus using a spatial regression model with socio-ecological covariates. The meta-analysis revealed that lower-income neighborhoods (regions making less than $50,000 per year on average) are exposed to 151% greater mosquito densities and mosquito-borne illnesses compared to higher-income neighborhoods (≥$50,000 per year). Two species of mosquito (Ae. albopictus and Aedes aegypti) showed the strongest relationship with socioeconomic status, with Ae. albopictus and Ae. aegypti being 62% and 22% higher in low-income neighborhoods, respectively. In the spatial regression analysis in Baltimore, we found that Ae. albopictus spatial spread of 1.2 km per year was significantly associated with median household income, vegetation cover, tree density, and abandoned buildings. Specifically, Ae. albopictus abundance was negatively correlated with median household income, vegetation cover, and tree density. Ae. albopictus abundance and the cover of abandoned buildings were positively correlated. Together, these results indicate that socio-ecological interactions can lead to disproportionate impacts of mosquitoes on humans in urban landscapes. Thus, concerted efforts to manage mosquito populations in low-income urban neighborhoods are required to reduce mosquito burden for the communities most vulnerable to human disease.

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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.

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Abstract P142: The Impact of Regional Socioeconomic Status on Stroke Center Certification in the Northeastern United States

Stroke ◽

10.1161/str.52.suppl_1.p142 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Emily Chapman ◽

Kurt Yaeger ◽

J D Mocco

Keyword(s):

United States ◽

Socioeconomic Status ◽

Household Income ◽

Stroke Care ◽

Median Household Income ◽

Northeastern United States ◽

Stroke Incidence ◽

The Impact ◽

The Relationship ◽

The U.S

Introduction: The northeastern United States has been a national leader in stroke healthcare delivery. The current roster of designated comprehensive, primary, thrombectomy-capable and acute stroke ready centers is the result of respective state initiatives. Access to certified stroke centers (SCs) varies by county as states have widely varied certification processes and typically rely on certifying organizations (COs) to identify stroke centers. Previous research has found an association at the national level between likelihood of stroke certification and local socioeconomic status. Objective: This study describes the relationship between socioeconomic status of patient populations in the Northeast U.S. and their access to quality stroke care by comparing median household income and wealth in counties with and without certified SCs. Methods: Population and median household income for 218 counties in Connecticut, Delaware, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island and Vermont were collected from the U.S. Census (2010), stroke epidemiological data were collected from the Center for Disease Control, and Area Deprivation Index (ADI) data (ranked within the U.S.) were collected from the Neighborhood Atlas, a project that quantifies disadvantage. Median household income has been used to quantify local population 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, and yielded 259 certified centers. Linear regression characterized the relationship between income and ADI with number of certified SCs, stroke incidence and stroke mortality. Results: Higher income (p<0.001) and lower ADI (p<0.001) were associated with having more certified SCs (p<0.001). Counties with a higher stroke incidence had significantly more certified SCs (p=0.01). Conclusions: Throughout the counties of the Northeastern U.S., access to quality stroke care depends on local wealth and resources. At the same time, the current analysis indicates that SC certification distribution does appear to correlate to those counties where stroke incidence is highest.

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Neighbourhood disparities in the price of the cheapest cigarettes in the USA

Journal of Epidemiology & Community Health ◽

10.1136/jech-2018-210998 ◽

2019 ◽

Vol 73 (9) ◽

pp. 894-896 ◽

Cited By ~ 1

Author(s):

Sarah D Mills ◽

Shelley D Golden ◽

Lisa Henriksen ◽

Amanda Y Kong ◽

Tara L Queen ◽

...

Keyword(s):

Low Income ◽

Household Income ◽

Median Household Income ◽

Average Price ◽

Asian Pacific Islander ◽

Cigarette Pack ◽

The Usa ◽

Asian Pacific ◽

Household Incomes ◽

The Relationship

BackgroundThere is evidence that the cheapest cigarettes cost even less in neighbourhoods with higher proportions of youth, racial/ethnic minorities and low-income residents. This study examined the relationship between the price of the cheapest cigarette pack and neighbourhood demographics in a representative sample of tobacco retailers in the USA.MethodsData collectors recorded the price of the cheapest cigarette pack (regardless of brand) in 2069 retailers in 2015. Multilevel linear modelling examined the relationship between price and store neighbourhood (census tract) characteristics, specifically median household income and percentage of youth, Black, Asian/Pacific Islander and Hispanic residents.ResultsAverage price for the cheapest pack was $5.17 (SD=1.73) and it was discounted in 19.7% of stores. The price was $0.04 less for each SD increase in the percentage of youth and $0.22 less in neighbourhoods with the lowest as compared with the highest median household incomes. Excluding excise taxes, the average price was $2.48 (SD=0.85), and associations with neighbourhood demographics were similar.ConclusionThe cheapest cigarettes cost significantly less in neighbourhoods with a greater percentage of youth and lower median household income. Non-tax mechanisms to increase price, such as minimum price laws and restrictions on discounts/coupons, may increase cheap cigarette prices.

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Abstract 90: Socioeconomic Status Is Associated With Disability Following Acute Ischemic Stroke: Findings From The Adherence eValuation After Ischemic stroke-Longitudinal (AVAIL) Registry

Stroke ◽

10.1161/str.43.suppl_1.a90 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

Janet Prvu Bettger ◽

Xin Zhao ◽

Cheryl Bushnell ◽

Louise Zimmer ◽

Ying Xian ◽

...

Keyword(s):

Socioeconomic Status ◽

Ischemic Stroke ◽

Household Income ◽

Work Status ◽

Stroke Patients ◽

Level Of Education ◽

Post Stroke ◽

Relationship Of ◽

The Relationship ◽

Education Work

Background: Socioeconomic status (SES) is widely recognized as an area of inequity that affects health outcomes. However, social determinants of health are less frequently measured in longitudinal studies of acute stroke patients. The relationship of SES on disability 3-months post-stroke is unknown. Methods: We analyzed ischemic stroke patients in the AVAIL registry who were enrolled at 98 hospitals participating in Get With The Guidelines-Stroke. Patients who died (n=64) or did not complete a modified Rankin Scale (mRS) at 3-months (n=154) were excluded. Multivariable logistic regression was used to examine the relationship of SES (defined by level of education, work status, and perceived adequacy of household income to meet needs) and disability (mRS scores 3-5). Results: Among the 2092 stroke patients who met eligibility criteria, the mean age was 65.5 ± 13.7, 44.2% were female, and 82.7% were White. Fifty seven percent had a high school or less education, 11.4% were not working post-stroke and were home not by choice, and 25.7% were without an adequate household income. A third of the sample had some level of disability at 3-months (34.6% mRS 3-5). Those with disability were more likely to be older, non-White, female, single, less educated, have inadequate income, and were home not by choice. In the multivariable analysis, lower education, inadequate income, and being home but not by choice (compared with those who returned to work) were independently associated with disability (p<0.01; Table ). Conclusion: In this national cohort of stroke survivors, socioeconomic status as measured by level of education, work status, and income were independently associated with post-stroke disability.

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Health Inequalities in the Diverse World of Self-Employment: A Swedish National Cohort Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182312301 ◽

2021 ◽

Vol 18 (23) ◽

pp. 12301

Author(s):

Karl Gauffin ◽

Andrea Dunlavy

Keyword(s):

Health Outcomes ◽

Health Inequalities ◽

Low Income ◽

Employment Status ◽

The Self ◽

Poor Health ◽

Self Employment ◽

Regular Employment ◽

National Cohort ◽

The Relationship

With labor being a central social determinant of health, there is an increasing need to investigate health inequalities within the heterogenous and growing population in self-employment. This study aimed to longitudinally investigate the relationship between income level, self-employment status and multiple work-related health indicators in a Swedish national cohort (n = 3,530,309). The study investigated the relationship between self-employment status and health outcomes later in life. All poor health outcomes, with the exception of alcohol-related disorders, were more common in the self-employed population, compared to the group in regular employment. The income gradient, however, was more pronounced in the group with regular employment than the groups in self-employment. The study found clear connections between low income and poor health in all employment groups, but the gradient was more pronounced in the group in regular employment. This suggests that income has a weaker connection to other types of health promoting resources in the self-employed population. Potentially, lacking social and public support could make it difficult for unhealthy individuals to maintain low-income self-employment over a longer time period.

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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.

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