Abstract
A complex interplay of social, economic, and environmental factors drove the COVID-19 epidemic. Understanding these factors is crucial in explaining the racial disparities observed in COVID-19 deaths. This research investigated various hypotheses, including ecological, racial, demographic, economic, and political party factors, to determine their impact on COVID-19 deaths. The study utilized data from the National Center for Health Statistics (NCHS), specifically focusing on COVID-19 deaths categorized by race and Hispanic origin in US counties, with over 100 recorded deaths as of July 11, 2022.
Method
To analyze the data, the study employed partial least squares (PLS) as the statistical approach, considering the presence of multicollinearity in the county-level socioeconomic data. SmartPLS4 software was utilized to illustrate paths depicting variance and covariance and to conduct significance tests. The analysis encompassed overall COVID-19 deaths and deaths among White, Black, and Hispanic Americans, utilizing the same latent variables and paths.
Results
The results revealed that the number of residents aged 65 years or older in a county was the most influential predictor of COVID-19 deaths, irrespective of race. Economic factors emerged as the second strongest predictors. However, when considering each racial group separately, distinct factors aligned with the five hypotheses emerged as significant contributors to COVID-19 deaths. Furthermore, the diagrams illustrating the relationships between these factors (covariates) varied among racial groups, indicating that the underlying social influences differed across races.
Discussion
In light of these findings, it becomes evident that a “one-size-fits-all” approach to prevention strategies is suboptimal. Instead, targeted prevention efforts tailored to specific racial and social classes at high risk of COVID-19 death could have provided more precise messaging and necessitate direct engagement.
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Notes
The sociological racial descriptors of African American, Latinx Americans, and White Americans are used in this paper interchangeably with Black, Hispanic, and White as used in the research literature and in CDC data sets.
Percentages of Blacks in county populations were divided by standard deviations into an ordinal index that served as measures of Black racial segregation. The higher the percentage of Black residents, the more likely there is racial segregation. Percentages of Hispanics in county populations were divided in the same way producing a second ordinal index to measure Hispanic racial segregation.
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Acknowledgement
Many thanks for the statistical consultation of the late Bruce Trumbo and Carl O. Word, and for financial support from the California State University Emeritus and Retired Faculty and Staff Association in planning this research.
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Appendices
Appendix 1
Table 1
Appendix 2
Table 2
Appendix 3
Latent variable bootstrip tests of significance for path coefficients
White COVID-19 Deaths
Original | Sample | Standard | T Statistics | ||
|---|---|---|---|---|---|
sample (O) | mean (M) | deviation | |O/STDEV|) | P values | |
Demograph -> COVID-19 Deaths | 0.823 | 0.809 | 0.116 | 7.12 | 0.001 |
Ecology -> COVID-19 Deaths | -0.089 | -0.083 | 0.024 | 3.76 | 0.001 |
Economy -> COVID-19 Deaths | -0.377 | -0.351 | 0.094 | 3.99 | 0.001 |
Economy -> Ecology | -0.374 | -0.384 | 0.036 | 10.43 | 0.001 |
Economy -> Political | 0.828 | 0.835 | 0.023 | 36.78 | 0.001 |
Political -> COVID-19 Deaths | 0.366 | 0.363 | 0.125 | 2.94 | 0.003 |
Race -> COVID-19 Deaths | -0.042 | -0.044 | 0.017 | 2.44 | 0.015 |
Race -> Demographic | 0.32 | 0.324 | 0.027 | 11.86 | 0.001 |
Black COVID-19 Deaths
Original | Sample | Standard | T Statistic | ||
|---|---|---|---|---|---|
sample (O) | mean (M) | deviation | (|O/STDEV|) | P values | |
Demographic -> COVID Deaths | 1.065 | 1.07 | 0.064 | 16.66 | 0.001 |
Demographic -> Political | 0.731 | 0.732 | 0.045 | 16.08 | 0.001 |
Ecological -> Demographic | 0.434 | 0.457 | 0.081 | 5.38 | 0.001 |
Economic -> COVID Deaths | -0.052 | -0.053 | 0.017 | 3.09 | 0.002 |
Economic -> Political | 0.25 | 0.261 | 0.05 | 5.00 | 0.001 |
Political -> COVID Deaths | -0.106 | -0.111 | 0.067 | 1.59 | 0.112 |
Race -> COVID Deaths | -0.135 | -0.141 | 0.031 | 4.36 | 0.001 |
Race -> Demographic | 0.291 | 0.287 | 0.04 | 7.30 | 0.001 |
Race -> Ecological | 0.184 | 0.195 | 0.031 | 5.98 | 0.001 |
Hispanic COVID-19 Deaths
Original sample (O) | Sample mean (M) | Standard deviation | T Statistics (|O/STDEV|) | P values | |
|---|---|---|---|---|---|
Demographic -> COVID Deaths | 0.915 | 0.957 | 0.122 | 7.48 | 0.001 |
Demographic -> Political | 0.247 | 0.233 | 0.138 | 1.79 | 0.073 |
Demographic -> Race | 0.38 | 0.403 | 0.053 | 7.12 | 0.001 |
Ecological -> COVID Deaths | -0.042 | -0.043 | 0.014 | 3.05 | 0.002 |
Economic -> COVID Deaths | 0.236 | 0.218 | 0.089 | 2.64 | 0.008 |
Economic -> Ecological | 0.107 | 0.111 | 0.022 | 4.95 | 0.001 |
Economic -> Political | 0.66 | 0.656 | 0.111 | 5.92 | 0.001 |
Political -> COVID Deaths | -0.155 | -0.19 | 0.073 | 2.12 | 0.034 |
Race -> COVID Deaths | -0.066 | -0.077 | 0.036 | 1.84 | 0.067 |
Race -> Ecological | 0.559 | 0.556 | 0.031 | 18.10 | 0.001 |
Race -> Political | -0.033 | -0.028 | 0.029 | 1.15 | 0.251 |
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Bowser, B.P. Social-Economic Backgrounds to US County-Based COVID-19 Deaths: PLS-SEM Analysis. J. Racial and Ethnic Health Disparities 11, 2304–2317 (2024). https://doi.org/10.1007/s40615-023-01698-z
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DOI: https://doi.org/10.1007/s40615-023-01698-z