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Explaining the ethnic gaps in COVID-19 outcomes in Mexico

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  • Salas-Ortiz, A.

Abstract

Indigenous groups are one of the most socially vulnerable groups across societies. Concerns have been raised about the possibility of greater health disparities when the Covid-19 pandemic interacts with non-communicable diseases in contexts of high socioeconomic inequalities (Horton, 2020). Using national and administrative public data on Covid-19, this study investigates this hypothesis by explaining differences in Covid-19 health outcomes (hospitalisations, admissions to intensive care unit, and mortality) between indigenous and non-indigenous groups in Mexico. The analysis uses an adaptation of the Oaxaca decomposition method to account for nonlinear responses. This allows to identify and characterise the factors behind ethnic disparities. Results indicate that indigenous people have worse Covid-19 health outcomes. These differences are mainly attributable to differences in people’s characteristics. Disentangling the contribution of each individual and contextual circumstances to the observable differences, we found that underlying health conditions, household and municipal socioeconomic characteristics are the main drivers of observable inequalities in hospitalisations and deaths due to Covid-19. These findings highlight that this pandemic is exacerbating the pre-existing and longstanding health inequalities between indigenous and non-indigenous people in Mexico.

Suggested Citation

  • Salas-Ortiz, A., 2021. "Explaining the ethnic gaps in COVID-19 outcomes in Mexico," Health, Econometrics and Data Group (HEDG) Working Papers 21/20, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:21/20
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    References listed on IDEAS

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    1. Rene Leyva-Flores & Edson Servan-Mori & Cesar Infante-Xibille & Blanca Estela Pelcastre-Villafuerte & Tonatiuh Gonzalez, 2014. "Primary Health Care Utilization by the Mexican Indigenous Population: The Role of the Seguro Popular in Socially Inequitable Contexts," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-6, August.
    2. Powers, Daniel A. & Yun, Myeong-Su, 2009. "Multivariate Decomposition for Hazard Rate Models," IZA Discussion Papers 3971, Institute of Labor Economics (IZA).
    3. Daniel A. Powers & Hirotoshi Yoshioka & Myeong-Su Yun, 2011. "mvdcmp: Multivariate decomposition for nonlinear response models," Stata Journal, StataCorp LP, vol. 11(4), pages 556-576, December.
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