Association Between State-Level Income Inequality and COVID-19 Cases and Mortality in the USA
- PDF / 424,675 Bytes
- 3 Pages / 595.276 x 790.866 pts Page_size
- 0 Downloads / 191 Views
J Gen Intern Med DOI: 10.1007/s11606-020-05971-3 © Society of General Internal Medicine 2020
INTRODUCTION
COVID-19, caused by the novel coronavirus SARS-CoV-2, has resulted in the largest pandemic in 100 years. The USA has been particularly impacted, reporting a third of the cases and a quarter of the deaths worldwide. In recent weeks, the unequal impact of COVID-19 across communities has become glaringly apparent. Data from New York and Chicago indicate that African American and Hispanic people experience disproportionately higher rates of COVID-19 infection and mortality.1, 2 Inequality may compound these disparities further through economic segregation, decreased social mobility, and lower access to medical care.3 Given that low-income individuals are more likely to be in essential occupations with a high exposure risk and have less access to healthcare, income inequality may exacerbate the impact of the COVID-19 outbreak.
METHODS
We examined the association between income inequality and the number of COVID-19 cases and deaths. State income inequality data—as measured by the Gini index—were extracted from the 2018 American Community Survey. The number of cases and deaths was calculated using the COVID-19 Dashboard, a data set hosted by the Center for Systems Science and Engineering at Johns Hopkins University.4, 5 We limited our analysis to the 50 states from January 22, 2020, through April 13, 2020. First, we performed simple correlation analyses between the state-level Gini index and the number of cases and deaths per 100,000 population due to COVID-19 using the Spearman rank-order correlation test. To account for the right-skewed distribution, we log-transformed the data on the number of COVID-19 cases and deaths. Second, using multivariable regressions, we examined the associations between the state-level Gini index and logtransformed number of cases and deaths due to COVID-19 adjusting for potential confounders. The adjustment variables Received May 7, 2020 Accepted June 5, 2020
included the proportion of the population 65+ years, female, African American, Hispanic, and below poverty; median household income; the number of tests performed per capita; doctors per capita (2018–2019 Area Health Resource File); beds per capita (2009–2018 American Hospital Association Annual Survey); and whether a state had a stay-at-home or shelter-in-place policy (no order, order in some parts of the state, statewide order; the New York Times database).6 This study was exempted from review by the institutional review board of UCLA.
RESULTS
On April 13, 2020, there were a total of 577,414 cases and 23,424 deaths across 50 states. The number of cases ranged from 28.7 to 1,006.2 cases per 100,000 (median. 73.0; IQR, 47.7–133.6). The mortality rates ranged from 0.17 to 51.7 deaths per 100,000 (median, 2.0; IQR, 1.2–4.5). We observed positive correlations between the Gini index and the number of cases (correlation coefficient = 0.38; P = 0.006) and deaths (correlation coefficient = 0.44; P = 0.002) due to COVID-19 (Fig. 1).
Data Loading...
