Concentrated Disadvantage

Jargowsky, Paul A.; Tursi, Natasha O.

doi:10.1016/b978-0-08-097086-8.32192-4

Cited by 16 publications

(13 citation statements)

References 36 publications

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“…Socioeconomic and racial disparities in access to health care services, health status, and health outcomes are welldocumented in the literature [4][5][6][7][8][9]. Aside from the individuallevel characteristics that impact outcomes, populations residing in neighborhoods with higher concentrations of socioeconomic disadvantages and racial/ethnic minorities are at greater risk of experiencing different forms of health disparities [10][11][12][13][14]. For example, those living in areas of concentrated economic hardship or higher racial/ethnic minority concentration are more likely to experience adverse health outcomes such as reduced prostate cancer survival rates, increased infant mortality, and higher incidence of premature deaths [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

Khanijahani

Tomassoni

2021

J. Racial and Ethnic Health Disparities

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Introduction This study's objective was to examine the association of the percentage of county population residing in concentrated disadvantage and Black-concentrated census tracts with county-level confirmed COVID-19 deaths in the USA, concentrated disadvantage and Black concentration at census tract-level measure socioeconomic segregation and racial segregation, respectively. Methods We performed secondary data analysis using tract (N = 73,056) and county (N = 3142) level data from the US Census Bureau and other sources for the USA. Confirmed COVID-19 deaths per 100,000 population was our outcome measure. We performed mixed-effect negative binomial regression to examine the association of county population's percentage residing in concentrated disadvantage and Black-concentrated tracts with COVID-19 deaths while controlling for several other characteristics. Results For every 10% increase in the percentage of county population residing in concentrated disadvantage and Black-concentrated tracts, the rate for confirmed COVID-19 deaths per 100,000 population increases by a factor of 1.14 (mortality rate ratio [MMR] = 1.14; 95% confidence interval [CI]:1.11, 1.18) and 1.11 (MMR = 1.11; 95% CI:1.08, 1.14), respectively. These relations stayed significant in all models in further sensitivity analyses. Moreover, a joint increase in the percentage of county population residing in racial and socioeconomic segregation was associated with a much greater increase in COVID-19 deaths. Conclusions It appears that people living in socioeconomically and racially segregated neighborhoods may be disproportionately impacted by COVID-19 deaths. Future multilevel and longitudinal studies with data at both individual and aggregated tract level can help isolate the potential impacts of the individual-level characteristics and neighborhood-level socioeconomic and racial segregation with more precision and confidence.

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Section: Introductionmentioning

confidence: 99%

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

Khanijahani

Tomassoni

2021

J. Racial and Ethnic Health Disparities

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“…Disparities in health status, health outcomes, and access to health services have been shown in different contexts and populations (Williams and Collins 2001; Manuel 2018; Kawachi, Daniels, and Robinson 2005; McQuillan et al 2004; Lara-Cinisomo, Xue, and Brooks-Gunn 2013). It is well known that concentrated disadvantage plays a significant role in widening the health gap between poor and rich (Browning and Cagney 2002; Jargowsky and Tursi 2015; Braveman et al 2010). Given the highly contagious nature of COVID-19, the current pandemic demands a population-level understanding of the issue and the consequences.…”

Section: Introductionmentioning

confidence: 99%

County-Level Proportions of Black and Hispanic populations, and Socioeconomic Characteristics in Association with Confirmed COVID-19 Cases and Deaths in the United States

Khanijahani

2020

Preprint

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Objectives. The objective of this study was to investigate potential county-level disparities among racial/ethnic and economic groups in COVID-19 burden which was measured using confirmed cases and deaths in 100,000 population. Design. Secondary data analysis Using county-level data for 3,142 US counties was conducted in 2020. Hierarchical linear regression and concentration curve analyses were performed. The combined association of COVID-19 cases and deaths was examined separately by sociodemographic and economic characteristics of the county population. Data from the American Community Survey (ACS) 5-year estimates (2014-2018), Area Health Resources File (AHRF) 2018-2019, and 2020 COVID-19 data from Johns Hopkins University were used in this study. Results. After adjusting for covariates, US counties with a higher proportion of the black population, and a higher proportion of adults with less than high school diploma had disproportionately higher COVID-19 cases and deaths (β>0, p<0.05). A higher proportion of the Hispanic population was associated with higher confirmed cases (β= 1.03, 95% CI= 0.57-1.5), and higher housing cost to household income ratio was associated with higher deaths (β= 3.74, 95% CI= 2.14-5.37). This can potentially aggravate the existing health disparities among these population groups. Conclusions. Identification of disproportionately impacted population groups can pave the way towards narrowing the disparity gaps and guide policymakers and stakeholders in designing and implementing population group-specific interventions to mitigate the negative consequences of COVID-19 pandemic.

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“…Given the relevance of place and space, the conceptual framework of this study builds on the notions of concentrated disadvantage (Elijah, 1990 ; Jargowsky & Tursi, 2015 ) and geography of opportunity (Pastor, 2001 ; Tate, 2008 ) or disadvantage (Pacione, 1997 ).…”

Section: Conceptual Lenses: Neighborhood or Place-based Effectsmentioning

confidence: 99%

“…As depicted in Fig. 4 , income diversity within ZIP codes prevails across the continental United States, accordingly, access to data distribution of income variation within ZIP codes opens the possibility of modeling how this spatial heterogeneity impacts SLID disbursements, while accounting for place-based cultural , ethnic, and socioeconomic factors typically depicted in the neighborhood effects literature (Chetty et al, 2014 ) and the concentrated advantage and disadvantaged frameworks (Elijah, 1990 ; Jargowsky & Tursi, 2015 ; Pastor, 2001 ; Tate, 2008 ; Weicher, 1979 ). The possibility of modeling this place-based income heterogeneity as a systematic source of variation of SLID disbursements is considered an important contribution to the existing literature.…”

Section: Conceptual Lenses: Neighborhood or Place-based Effectsmentioning

confidence: 99%

Post-purchase Federal Financial Aid: How (in)Effective is the IRS’s Student Loan Interest Deduction (SLID) in Reaching Lower-Income Taxpayers and Students?

Canché

2022

Res High Educ

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Federal financial aid policies for higher education may be classified based on their “for-purchase” and “post-purchase” natures. The former include grants, loans, and workstudy and intend to help students finance or afford college attendance, persistence, and graduation. Post-purchase policies are designed to minimize financial burdens associated with having invested in college attendance and are granted as tax incentives/expenditures. One of these expenditures is the IRS’s Student Loan Interest Deduction (SLID)—which offers up to $2500 as an adjustment for taxable income based on having paid interest on student loans and has an annual cost of $12.81 billion—about 45.7% of the Pell grant cost. Despite this high cost, SLID has remained virtually unstudied. Accordingly, the study’s purpose is to assess how (in)effective SLID may be in reaching lower-income taxpayers. To address this purpose, we relied on an innovative analytic framework “multilevel modelling with spatial interaction effects” that allowed controlling for contextual and systemic observed and unobserved factors that may both affect college participation and may be related with SLID disbursements over and above income prospects. Data sources included the IRS, ACS, FBI, IPEDS, and the NPSAS:2015–2016. Findings revealed that SLID is regressive at the top, wealthier taxpayers and students attending more expensive colleges realize higher tax benefits than lower income taxpayers and students. Indeed, 75% of community college students were found to not be eligible to receive SLID—data and replication code ( https://cutt.ly/COyfdKC ) are provided. Is this the best use of this multibillion tax incentive? Is SLID designed to exclude the poorest, neediest students? A policy similar to Education Credits, focused on outstanding debt rather than on interest, that targets below-poverty line students with up to $5000 in debt, would represent a true commitment, and better use of public funds, to close socioeconomic gaps, by helping those more prone to default.

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Concentrated Disadvantage

Cited by 16 publications

References 36 publications

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

County-Level Proportions of Black and Hispanic populations, and Socioeconomic Characteristics in Association with Confirmed COVID-19 Cases and Deaths in the United States

Post-purchase Federal Financial Aid: How (in)Effective is the IRS’s Student Loan Interest Deduction (SLID) in Reaching Lower-Income Taxpayers and Students?

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