Mortality from COVID-19: educational inequalities and socio-spatial context in two provinces of Argentina
DOI:
https://doi.org/10.17843/rpmesp.2024.412.13201Keywords:
Spatial analysis, socioeconomic disparities in health, mortality, SARS-CoV-2, medical geographyAbstract
With the objective of describing the association between sociodemographic characteristics and contextual factors with mortality from COVID-19, during 2020-2021 in the provinces of Mendoza and San Juan in Argentina, an ecological study was carried out, where the sociodemographic factors were the age, sex and educational level and contextual poverty and urbanization at the departmental level, the analyzes were estimated using negative binomial Bayesian hierarchical models. Educational inequalities existed
regardless of the socioeconomic context and the level of urbanization. The exception was the age group 65 and older during 2021, which, regardless of educational level, showed a higher risk of death from COVID-19 in departments with high levels of structural poverty. In conclusion, educational inequality is an indicator of social inequality that increases vulnerability to mortality from COVID-19.
Downloads
References
Bermudi PMM, Lorenz C, de Aguiar BS, Failla MA, Barrozo LV, Chiaravalloti-Neto F. Spatiotemporal ecological study of COVID-19
mortality in the city of São Paulo, Brazil: shifting of the high mortality risk from areas with the best to those with the worst socio-economic conditions. Travel Med Infect Dis.2021;39:101945. doi: 10.1016/j.tmaid.2020.101945.
Mena G, Martinez PP, Mahmud AS, Marquet PA, Buckee CO, Santillana M. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile. Science.2021;372(6545):eabg5298. doi: 10.1101/2021.01.12.21249682.
Silva J, Ribeiro-Alves M. Social inequalities and the pandemic of COVID-19: the case of Rio de Janeiro. J Epidemiol Community Health. 2021;75(10):975-979. doi: 10.1136/jech-2020-214724.
Leveau CM, Soares Bastos L. Desigualdades socio-espaciales de la mortalidad por COVID-19 en tres olas de propagación: un análisis intra-urbano en Argentina. Cad Saúde Pública. 2022;38(5):e00163921. doi: 10.1590/0102-311XES163921.
Albuquerque MV de, Ribeiro LHL. Desigualdade, situação geográfica e sentidos da ação na pandemia da COVID-19 no Brasil. Cad Saúde Pública. 2021;36(12): e00208720. doi: 10.1590/0102-311X00208720.
Anzalone AJ, Horswell R, Hendricks BM, Chu S, Hillegass WB, Beasley WH, et al. Higher hospitalization and mortality rates among
SARS‐CoV‐2‐infected persons in rural America. J Rural Health. 2023;39:39–54. doi: 10.1111/jrh.12689.
Cuadros DF, Branscum AJ, Mukandavire Z, Miller FD, MacKinnon N. Dynamics of the COVID-19 epidemic in urban and rural areas in the United States. Ann Epidemiol. 2021;59:16–20. doi: 10.1016/j.annepidem.2021.04.007.
Petrelli A, Ventura M, Di Napoli A, Mateo-Urdiales A, Pezzotti P, Fabiani M. Geographic heterogeneity of the epidemiological impact of the COVID-19 pandemic in Italy using a socioeconomic proxy-based classification of the national territory. Front Public Health. 2023;11:1143189. doi: 10.3389/fpubh.2023.1143189.
Angelici L, Sorge C, Di Martino M, Cappai G, Stafoggia M, Agabiti N, et al. Incidence of SARS-CoV-2 Infection and Related Mortality by Education Level during Three Phases of the 2020 Pandemic: A Population-Based Cohort Study in Rome. J Clin Med. 2022;11(3):877. doi: 10.3390/jcm11030877.
Chiaravalloti Neto F, Bermudi PMM, Aguiar BS de, Failla MA, Barrozo LV, Toporcov TN. Covid-19 hospital mortality using spatial hierarchical models: cohort design with 74,994 registers. Rev Saúde Pública. 2023; (suppl 1):2s. doi: 10.11606/s1518-8787.2023057004652.
Feldman JM, Bassett MT. Variation in COVID-19 mortality in the US by race and ethnicity and educational attainment. JAMA Netw Open. 2021;4(11):e2135967. doi: 10.1001/jamanetworkopen.2021.35967.
Spijker JJA, Trias-Llimós S. Cause-specific mortality in Spain during the pandemic: educational differences and its impact on life expectancy. Eur J Public Health 2023;33(3):543–9. doi: 10.1093/eurpub/ckad036.
Li SL, Pereira RH, Prete Jr CA, Zarebski AE, Emanuel L, Alves PJ, et al. Higher risk of death from COVID-19 in low-income and non-White populations of São Paulo, Brazil. BMJ Glob Health. 2021;6(4):e004959. doi: 10.1136/bmjgh-2021-004959.
Leveau CM, Hussein M, Tapia-Granados JA, Velázquez GA. Economic fluctuations and educational inequalities in premature ischemic heart disease mortality in Argentina. Cad Saúde Pública. 2023;39(5):e00181222. doi: 10.1590/0102-311xen181222.
Boletín Oficial de la República Argentina. Boletín Oficial República Argentina - Aislamiento Social Preventivo Y Obligatorio - Decreto 297/2020. 2020 [consultado el 21 de agosto de 202]. Disponible en: https://www.boletinoficial.gob.ar/detalleAviso/primera/227042
Freitas ARR, Beckedorff OA, Cavalcanti LP de G, Siqueira AM, Castro DB de, Costa CF da, et al. The emergence of novel SARS-CoV-2 variant P.1 in Amazonas (Brazil) was temporally associated with a change in the age and sex profile of COVID-19 mortality: A population based ecological study. Lancet Reg Health Am. 2021;1:100021. doi: 10.1016/j.lana.2021.100021.
Instituto Nacional de Estadística y Censos. Datos provisionales del CENSO 2022. Censo Nac Poblac Hogares Viviendas 2023. [consultado el 31 de mayo de 2023]. Disponible en: https://censo.gob.ar/index.php/datos_provisionales/.
Ministerio de Salud de la Nación. Datos Abiertos del Ministerio de Salud - Defunciones ocurridas y registradas en la República Argentina 2023. [consultado el 16 de diciembre de 2023]. Disponible en: http://datos.salud.gob.ar/.
Scruzzi GF, Aballay LR, Carreño P, Díaz Rousseau GA, Franchini CG, Cecchetto E, et al. Vacunación contra SARS-CoV-2 y su relación con enfermedad y muerte por COVID-19 en Argentina. Rev Panam Salud Pública 2023;46:e39. doi: 10.26633/RPSP.2022.39.
Huisman M, Kunst AE, Bopp M, Borgan J-K, Borrell C, Costa G, et al. Educational inequalities in cause-specific mortality in middle-aged and older men and women in eight western European populations. Lancet. 2005;365(9458):493–500. doi: 10.1016/S0140-6736(05)17867-2.
Brønnum-Hansen H, Baadsgaard M. Increasing social inequality in life expectancy in Denmark. Eur J Public Health 2007;17:585–6. doi: 10.1093/eurpub/ckm045.
Instituto Nacional de Estadística y Censos de la República Argentina. Necesidades básicas insatisfechas 2024. [consultado el 30 de noviembre de 2023]. Disponible en: https://www.indec.gob.ar/indec/web/Nivel4-Tema-4-47-156.
Tisdale H. The Process of Urbanization. Soc Forces 1942;20:311. doi: 10.2307/3005615.
Blangiardo M, Cameletti M, Baio G, Rue H. Spatial and spatio-temporal models with R-INLA. Spat Spatiotemporal Epidemiol. 2013;4:33–49. doi: 10.1016/j.sste.2012.12.001.
Riebler A, Sørbye SH, Simpson D, Rue H. An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Stat Methods Med Res. 2016;25:1145–65. doi: 10.1177/0962280216660421.
Besag J, York J, Mollié A. Bayesian image restoration, with two applications in spatial statistics. Ann Inst Stat Math. 1991;43:1–20. doi: 10.1007/BF00116466.
La Nación. Coronavirus: murió un hombre de 74 años en Mendoza y hay 110 víctimas en el país 2020. [consultado el 21 de agosto de 2020]. Disponible en: https://www.lanacion.com.ar/sociedad/coronavirus-argentina-murio-hombre-74-anos-mendoza-nid2354467.
Data Driven Argentina. Reporte de movilidad de Google. Data Driven Argent 2022. [consultado el 1 de noviembre de 2022]. Disponible en: https://datadriven.com.ar/movilidad-google-argentina/.
Rodríguez López S, Bilal U, Ortigoza AF, Diez-Roux AV. Educational inequalities, urbanicity and levels of non-communicable diseases risk factors: evaluating trends in Argentina (2005–2013). BMC Public Health. 2021;21:1–12. doi:10.1186/s12889-021-11617-8.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Carlos M. Leveau, Guillermo A. Velázquez
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
