Background: The COVID-19 pandemic revealed large structural inequalities that led to disparities in health outcomes related to socioeconomic status. So far, most of the evidence is based on aggregated data or simulations with individual data, which point to various possible mechanisms behind the association. To date, there have been no studies regarding an income gradient in COVID-19 mortality based on individual-level data and adjusting for comorbidities or access to healthcare.
Methods: In this paper, we use linked employee-patient data for patients tested for COVID-19 at the Mexican Institute of Social Security. We estimate the association of the probability of dying with income centiles, using a probit estimation and adjusting for COVID-19 diagnosis, sociodemographic variables, and comorbidities.
Findings: After controlling for all these variables, we find that persons in the lowest income decile still had a probability of dying from COVID-19 five times greater than those at the top decile.
Interpretation: Our results imply that the association between income and COVID outcomes is not explained by the prevalence of comorbidities or by a lack of access to healthcare among the low-income population.
Funding: This study was not supported by any external funding source.
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| http://dx.doi.org/10.1016/j.lana.2021.100115 | DOI Listing |
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