Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis

Lee, Eun Kyung; Donley, Gwendolyn; Ciesielski, Timothy H.; Gill, India; Yamoah, Owusua; Roche, Abigail; Martínez, Roberto; Freedman, Darcy A.

doi:10.1016/j.socscimed.2021.114696

Cited by 116 publications

(43 citation statements)

References 77 publications

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“…Within the context of historical redlining, recent studies have shown associations between redlining and heat stress and higher intra-urban heat [12], less greenspace [13,14], higher incidence of brownfield sites [14], oil and gas well siting [15], and air pollution [8,16]. Poor health is a well-understood consequence of environmental exposures; redlining has also been associated with higher cardiovascular disease risk [17], asthma risk [18], preterm birth [19,20], breast cancer mortality [21], and generally poorer mental and physical health [22][23][24]. In tandem with these recent redlining studies, research over the last several decades has produced a substantial body of literature that challenges the notion that racial/ethnic minorities (in particular, Blacks) themselves are to blame for unequal racial outcomes in regard to health, socioeconomic status, and environmental pollution [25].…”

Section: Introductionmentioning

confidence: 99%

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining

Shkembi

Smith

Neitzel

2022

J Expo Sci Environ Epidemiol

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Objectives To identify the most pervasive environmental exposures driving environmental disparities today associated with historical redlining in Detroit. Methods We overlaid Detroit’s 1939 Home Owners’ Loan Corporation (HOLC) shapefile from the Mapping Inequality project onto the EPA EJScreen and the DOT National Transportation Noise maps to analyze differences in current demographic and environmental indicators between historically redlined (D-grade) and non-redlined neighborhoods using simple linear regression and a boosted classification tree algorithm. Results Historically redlined neighborhoods in Detroit experienced significantly higher environmental hazards than non-redlined neighborhoods in the form of 12.1% (95% CI: 7.2–17.1%) higher levels of diesel particulate matter (PM), 32.2% (95% CI: 3.3–69.3%) larger traffic volumes, and 65.7% (95% CI: 8.6–152.8%) higher exposure to hazardous road noise (LEQ(24h) >70 dBA). Historically redlined neighborhoods were situated near 1.7-times (95% CI: 1.4–2.1) more hazardous waste sites and twice as many (95% CI: 1.5–2.7) risk management plan (RMP) sites than non-redlined neighborhoods. The lifetime cancer risk from inhalation of air toxics was 4.4% (95% CI: 2.9–6.6%) higher in historically redlined communities, and the risk of adverse respiratory health outcomes from air toxics was 3.9% (95% CI: 2.1–5.6%) higher. All factors considered together, among the environmental hazards considered, the most pervasive hazards in historically redlined communities are proximity to RMP sites, hazardous road noise, diesel PM, and cancer risk from air pollution. Conclusions Historically redlined neighborhoods may have a disproportionately higher risk of developing cancer and adverse respiratory health outcomes from air toxics. Policies targeting air and noise pollution from transportation sources, particularly from sources of diesel exhaust, in historically redlined neighborhoods may ameliorate some of the impacts of structural environmental racism from historical redlining in Detroit.

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Section: Introductionmentioning

confidence: 99%

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining

Shkembi

Smith

Neitzel

2022

J Expo Sci Environ Epidemiol

View full text Add to dashboard Cite

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“…Crawford et al 19 conducted a scoping review of 13 articles associating racial microaggressions and perinatal health outcomes; they found inconsistencies in definitions and measures of microaggressions. Kyung Lee et al 89 examined 12 studies of redlined compared with nonredlined neighborhoods and various adverse health outcomes and found significant associations with preterm birth. Mehra et al 17 reviewed 42 studies of racial residential segregation and adverse birth outcomes where 18 measured preterm birth; authors found that segregation measures varied widely.…”

Section: Discussionmentioning

confidence: 99%

Measures of Racism and Discrimination in Preterm Birth Studies

Balascio

Moore

Gongalla

et al. 2022

Obstetrics &Amp; Gynecology

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Preterm birth (any birth at less than 37 weeks of gestation) disproportionally affects Black birthing people and is associated with adverse perinatal and fetal health outcomes. Racism increases the risk of preterm birth, but standardized measurement metrics are elusive. This narrative synthesis examines literature on measures of racial discrimination used in preterm birth research.DATA SOURCES: Six databases (CINAHL, Cochrane, EMBASE, PubMed [MEDLINE], Scopus, Web of Science) and ClinicalTrials.gov were searched. Search terms were categorized into three groups (racism terms, measurement terms, preterm birth terms) to identify original research articles that explored associations between racism and preterm birth. English-language, original research articles with U.S. populations were included.

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“…31,32 Numerous events and historical circumstances have led to extreme neighborhood-level disparities in wealth and socioeconomic status in the United States that have disproportionately affected racial and ethnic minority populations. 27 These resource-related disparities are stubbornly persistent structures that continue to create disparate patterns of health-related risks and outcomes. Examples of phenomena that produce disparate resource-level availability among neighborhoods include discrimination in housing and loan financing policies, offshoring of manufacturing jobs that previously supported small towns, gentrification of attractive neighborhoods in urbanized areas, and declining funding for public schools.…”

Section: Discussionmentioning

confidence: 99%

“…Examples of phenomena that produce disparate resource-level availability among neighborhoods include discrimination in housing and loan financing policies, offshoring of manufacturing jobs that previously supported small towns, gentrification of attractive neighborhoods in urbanized areas, and declining funding for public schools. 27 Correspondingly, access and utilization of health care services among low-income and minority populations have been affected by escalating costs, consolidation in the health care sector, changes in insurance policies, uneven quality of health services delivery, mistrust of health institutions, and widening economic inequalities. Policies that produce unequal representation of individuals in data sets are not just historical footnotes.…”

Section: Discussionmentioning

confidence: 99%

“…26 Similar analyses have been conducted for many areas of the United States. 27 Spatial autocorrelation analysis provides estimates of the degree of spatial (e.g., neighborhood-level) similarity observed among neighboring values of an outcome. A key component to such autocorrelation methods is the capture of spatial association in outcomes among neighborhoods that are closer in space as compared with neighborhoods that are more distant from one another.…”

Section: Mapping and Spatial Analysismentioning

confidence: 99%

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Evaluating and Modeling Neighborhood Diversity and Health Using Electronic Health Records

et al. 2022

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Background Electronic health records (EHRs) provide researchers with abundant sample sizes, detailed clinical data, and other advantages for performing high-quality observational health research on diverse populations. We review and demonstrate strategies for the design and analysis of cohort studies on neighborhood diversity and health, including evaluation of the effects of race, ethnicity, and neighborhood socioeconomic position on disease prevalence and health outcomes, using localized EHR data. Methods Design strategies include integrating and harmonizing EHR data across multiple local health systems and defining the population(s) of interest and cohort extraction procedures for a given analysis based on the goal(s) of the study. Analysis strategies address inferential goals, including the mechanistic study of social risks, statistical adjustment for differences in distributions of social and neighborhood-level characteristics between available EHR data and the underlying local population, and inference on individual neighborhoods. We provide analyses of local variation in mortality rates within Cuyahoga County, Ohio. Results When the goal of the analysis is to adjust EHR samples to be more representative of local populations, sampling and weighting are effective. Causal mediation analysis can inform effects of racism (through racial residential segregation) on health outcomes. Spatial analysis is appealing for large-scale EHR data as a means for studying heterogeneity among neighborhoods even at a given level of overall neighborhood disadvantage. Conclusions The methods described are a starting point for robust EHR-derived cohort analysis of diverse populations. The methods offer opportunities for researchers to pursue detailed analyses of current and historical underlying circumstances of social policy and inequality. Investigators can employ combinations of these methods to achieve greater robustness of results. Highlights EHR data are an abundant resource for studying neighborhood diversity and health. When using EHR data for these studies, careful consideration of the goals of the study should be considered in determining cohort specifications and analytic approaches. Causal mediation analysis, stratification, and spatial analysis are effective methods for characterizing social mechanisms and heterogeneity across localized populations.

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Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis

Cited by 116 publications

References 77 publications

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining

Measures of Racism and Discrimination in Preterm Birth Studies

Evaluating and Modeling Neighborhood Diversity and Health Using Electronic Health Records

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