Assessing the Influence of Food Insecurity and Retail Environments as a Proxy for Structural Racism on the COVID-19 Pandemic in an Urban Setting
Abstract
:1. Introduction
Socially and Structurally Determined Outcomes: COVID-19, Food Insecurity, and Obesity
2. Materials and Methods
3. Analysis
4. Results
4.1. Regressions
4.1.1. Regression 1: Predicting Food Insecurity
4.1.2. Regression 2: Predicting Death Rates from COVID-19
4.1.3. Spatial Analysis: Local Clustering with Empirical Bayes Rates
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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ZIP Code | Race (%Black/African American; %White) [67] | Quality (Range 0–6) | Availability (Range 0–27) | Price (Range −8–16) | Total (Range −8–49) |
---|---|---|---|---|---|
48201 | 70%; 20% | 6.00 | 22.00 | 0.00 | 28.00 |
48202 | 82%; 12% | 6.00 | 23.00 | −2.00 | 27.00 |
48203 | 92%; 5% | 6.00 | 27.00 | −3.00 | 30.00 |
48204 | 97%; 1% | 6.00 | 23.00 | −2.00 | 27.00 |
48205 | 92%; 5% | 5.00 | 19.33 | 1.00 | 25.33 |
48206 | 95%; 2% | 6.00 | 19.00 | 4.50 | 29.50 |
48207 | 89%; 7% | 5.14 | 22.29 | 3.00 | 30.00 |
48209 | 10%; 50% | 5.25 | 17.00 | 3.25 | 25.50 |
48210 | 28%; 42% | 6.00 | 16.50 | 3.50 | 26.00 |
48212 | 37%; 37% | 6.00 | 18.00 | 1.00 | 25.00 |
48213 | 96%; 2% | 6.00 | 25.00 | 3.00 | 34.00 |
48214 | 91%; 6% | 6.00 | 26.00 | 2.50 | 34.50 |
48215 | 92%; 5% | 4.50 | 22.00 | 2.00 | 28.50 |
48216 | 42%; 38% | 6.00 | 18.00 | −3.00 | 21.00 |
48219 | 91%; 7% | 3.75 | 22.25 | 0.50 | 26.50 |
48221 | 93%; 4% | 5.00 | 23.00 | 0.67 | 28.67 |
48223 | 89%; 8% | 6.00 | 0.00 | 0.00 | 6.00 |
48224 | 90%; 8% | 6.00 | 17.50 | 3.00 | 26.50 |
48227 | 96%; 2% | 4.50 | 20.17 | 2.00 | 26.67 |
48228 | 79%; 17% | 6.00 | 19.20 | 2.75 | 27.00 |
48234 | 94%; 4% | 6.00 | 17.33 | 0.00 | 23.30 |
48235 | 97%; 1% | 4.50 | 9.50 | 3.00 | 17.00 |
48238 | 97%; 1% | 4.00 | 10.00 | 0.33 | 14.33 |
Regression | B | 95% CI | β | p |
---|---|---|---|---|
Analysis 1 | ||||
Constant | 136.97 | −178.49, 452.40 | - | 0.37 |
Case Counts | 0.047 | 0.008, 0.086 | 0.47 | 0.02 |
Death Counts | 1.89 | 0.34, 3.43 | 0.47 | 0.02 |
NEMS | −0.36 | −10.77, 10.06 | −0.008 | 0.94 |
Analysis 2 | ||||
Constant | 218.74 | −159.85, 597.33 | - | 0.24 |
Case Rates | −0.002 | −0.02, 0.02 | −0.06 | 0.83 |
NEMS | 3.05 | −5.35, 11.44 | 0.17 | 0.45 |
Calls to 2-1-1 | 0.19 | −0.03, 0.40 | 0.45 | 0.08 |
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Dombrowski, R.D.; Hill, A.B.; Bode, B.; Knoff, K.A.G.; Dastgerdizad, H.; Kulik, N.; Mallare, J.; Blount-Dorn, K.; Bynum, W. Assessing the Influence of Food Insecurity and Retail Environments as a Proxy for Structural Racism on the COVID-19 Pandemic in an Urban Setting. Nutrients 2022, 14, 2130. https://doi.org/10.3390/nu14102130
Dombrowski RD, Hill AB, Bode B, Knoff KAG, Dastgerdizad H, Kulik N, Mallare J, Blount-Dorn K, Bynum W. Assessing the Influence of Food Insecurity and Retail Environments as a Proxy for Structural Racism on the COVID-19 Pandemic in an Urban Setting. Nutrients. 2022; 14(10):2130. https://doi.org/10.3390/nu14102130
Chicago/Turabian StyleDombrowski, Rachael D., Alex B. Hill, Bree Bode, Kathryn A. G. Knoff, Hadis Dastgerdizad, Noel Kulik, James Mallare, Kibibi Blount-Dorn, and Winona Bynum. 2022. "Assessing the Influence of Food Insecurity and Retail Environments as a Proxy for Structural Racism on the COVID-19 Pandemic in an Urban Setting" Nutrients 14, no. 10: 2130. https://doi.org/10.3390/nu14102130