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      Environmental equity and COVID-19 experiences in the United States: Results from three survey waves of a nationally representative study conducted between 2020-2022

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          Abstract

          Certain environmental exposures, such as air pollution, are associated with COVID-19 incidence and mortality. To determine whether environmental context is associated with other COVID-19 experiences, we used data from the nationally representative Tufts Equity in Health, Wealth, and Civic Engagement Study data (n=1785; three survey waves 2020-2022). Environmental context was assessed using self-reported climate stress and county-level air pollution, greenness, toxic release inventory site, and heatwave data. Self-reported COVID-19 experiences included willingness to vaccinate against COVID-19, health impacts from COVID-19, receiving assistance for COVID-19, and provisioning assistance for COVID-19. Self-reported climate stress in 2020 or 2021 was associated with increased COVID-19 vaccination willingness by 2022 (odds ratio [OR] = 2.35; 95% confidence interval [CI] = 1.47, 3.76), even after adjusting for political affiliation (OR = 1.79; 95% CI = 1.09, 2.93). Self-reported climate stress in 2020 was also associated with increased likelihood of receiving COVID-19 assistance by 2021 (OR = 1.89; 95% CI = 1.29, 2.78). County-level exposures (i.e., less greenness, more toxic release inventory sites, more heatwaves) were associated with increased vaccination willingness. Air pollution exposure in 2020 was positively associated with likelihood of provisioning COVID-19 assistance in 2020 (OR = 1.16 per μg/m 3; 95% CI = 1.02, 1.32). Associations between certain environmental exposures and certain COVID-19 outcomes were stronger among those who identify as a race/ethnicity other than non-Hispanic White and among those who reported experiencing discrimination; however, these trends were not consistent. A latent variable representing a summary construct for environmental context was associated with COVID-19 vaccination willingness. Our results add to the growing body of literature suggesting that intersectional equity issues affecting likelihood of exposure to adverse environmental conditions are also associated with health-related outcomes.

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          Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status : A Systematic-Review and Meta-analysis

          Shruti Magesh, Daniel John, Wei Li … (2021)
          Question Are race and ethnicity–based COVID-19 outcome disparities in the United States associated with socioeconomic characteristics? Findings In this systematic review and meta-analysis of 4.3 million patients from 68 studies, African American, Hispanic, and Asian American individuals had a higher risk of COVID-19 positivity and ICU admission but lower mortality rates than White individuals. Socioeconomic disparity and clinical care quality were associated with COVID-19 mortality and incidence in racial and ethnic minority groups. Meaning In this study, members of racial and ethnic minority groups had higher rates of COVID-19 positivity and disease severity than White populations; these findings are important for informing public health decisions, particularly for individuals living in socioeconomically deprived communities. This systematic review and meta-analysis examines the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants. Importance COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear. Objective To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants. Data Sources A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021. Study Selection Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria. Data Extraction and Synthesis Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model. Main Outcomes and Measures The main measures were RRs, ORs, and combined prevalence values. Results A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P  = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P  = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P  < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals ( P  < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals ( P  < .001) and African American individuals ( P  < .001). Conclusions and Relevance In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.
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            Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors.

            Aaron van Donkelaar, Randall V. Martin, Michael Brauer … (2016)
            We estimated global fine particulate matter (PM2.5) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically based satellite-derived PM2.5 estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM2.5 estimates were highly consistent (R(2) = 0.81) with out-of-sample cross-validated PM2.5 concentrations from monitors. The global population-weighted annual average PM2.5 concentrations were 3-fold higher than the 10 μg/m(3) WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM2.5 data sources can yield valuable improvements to PM2.5 characterization on a global scale.
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              Structural Racism, Social Risk Factors, and Covid-19 — A Dangerous Convergence for Black Americans

              Leonard Egede, Rebekah Walker (2020)
              Article 0 comments Cited 213 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): medRxiv
                Journal ID (publisher-id): MEDRXIV
                Title: medRxiv
                Publisher: Cold Spring Harbor Laboratory
                Publication date (Electronic): 17 May 2023
                Electronic Location Identifier: 2023.05.16.23290050
                Affiliations
                [1 ]Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, USA
                [2 ]Tufts Clinical and Translational Sciences Institute, Boston, MA, USA
                [3 ]Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA, USA
                [4 ]Division of Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
                [5 ]Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
                [6 ]Department of Community Health, Tufts University School of Arts and Sciences, Medford, MA, USA
                [7 ]Department of Infectious Disease and Global Health, Tufts University Cummings School of Veterinary Medicine, Grafton, MA, USA
                [8 ]Division of Geographic Medicine and Infectious Diseases, Department of Medicine, Tufts Medical Center, Boston, MA
                [9 ]Jonathan Tisch College of Civic Life, Tufts University, Medford, MA, USA
                Author notes
                [* ]Corresponding author: Laura Corlin, laura.corlin@ 123456tufts.edu , (617) 636-0463, 136 Harrison Avenue, Boston, MA 02111
                Article
                DOI: 10.1101/2023.05.16.23290050
                PMC ID: 10246057
                PubMed ID: 37293071
                SO-VID: ea3bbaea-5ef7-4e6d-b2df-7bb1789c6b1b
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

                History
                Funding
                Funded by: Tufts University and Tufts Medical Center COVID Rapid Response
                Award ID: K12HD092535
                Funded by: Tufts University Equity Research
                Award ID: UL1TR002544
                Funded by: Tufts University Data-Intensive Science Center
                Categories
                Subject: Article

                Keywords: environmental equity,climate stress,covid-19,vaccination willingness,covid-19 assistance
                Data availability:
                Keywords: environmental equity, climate stress, covid-19, vaccination willingness, covid-19 assistance

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