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Caicedo-Velásquez B, Cifuentes-Ríos AM. Distribuição espacial da mortalidade por COVID-19 e sua associação com as condições sociodemográficas em Antioquia-Colômbia. Hacia Promoc. Salud [Internet]. 1º de julho de 2023 [citado 23º de novembro de 2024];28(2):64-81. Disponível em: https://revistasojs.ucaldas.edu.co/index.php/hacialapromociondelasalud/article/view/8623
Fomatos de Citação
Autores
Beatriz Caicedo-Velásquez
Universidad de Antioquia
Ana María Cifuentes-Ríos
Universidad de AntioquiaResumo
Antioquia tem mostrado amplas variações sub-regionais e municipais no risco de mortalidade por COVID-19. Entretanto, fatores relevantes para explicar o padrão geográfico de mortalidade, além das condições individuais, são desconhecidos. Objetivo: explorar a possível influência das características municipais no risco de mortalidade por COVID-19 em Antioquia, ajustando para condições individuais. Metodologia: foi utilizado um estudo analítico de dados secundários, transversal, usando dados de todos os casos positivos de COVID-19 identificados entre 9 de março de 2020 e 29 de outubro de 2021 em Antioquia, Colômbia. Um modelo logístico multinível foi ajustado para analisar a associação entre a mortalidade por COVID-19 e preditores socioeconômicos e demográficos nos municípios, independentemente de idade, sexo e etnia. Resultados: após o controle de variáveis individuais, 12 das 16 variáveis em nível municipal se mostraram independentemente associadas à mortalidade por COVID-1. Os resultados sugerem ainda um gradiente negativo de mortalidade por COVID-19, em que os municípios com condições precárias apresentaram riscos mais elevados. Conclusões: esses resultados sugerem a necessidade de levar em conta não apenas o ambiente imediato, mas também o ambiente mais amplo ao qual as pessoas pertencem, a fim de evitar a propagação do vírus e suas graves consequências.
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Referências
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20. Whittle RS, Diaz-Artiles A. An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City. BMC Med [Internet]. 2020; 18(1):1-17. Disponible en: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-020-01731-6
21. Cifuentes MP, Rodriguez-Villamizar LA, Rojas-Botero ML, Alvarez-Moreno CA, Fernández-Niño JA. Socioeconomic inequalities associated with mortality for COVID-19 in Colombia: a cohort nationwide study. J Epidemiol Community Health [Internet]. 2021; 75(7):610-615. Disponible en: https://jech.bmj.com/content/75/7/610
22. Chadeau-Hyam M, Bodinier B, Elliott J, Whitaker MD, Tzoulaki I, Vermeulen R, et al. Risk factors for positive and negative COVID-19 tests: A cautious and in-depth analysis of UK biobank data. Int J Epidemiol. 2020; 49(5):1454-1467.
23. Lyu T, Hair N, Yell N, Li Z, Qiao S, Liang C, et al. Temporal geospatial analysis of covid-19 pre-infection determinants of risk in South Carolina. Int J Environ Res Public Health. 2021; 18(18):9673.
24. Mascarello KC, Vieira ACBC, Souza ASS de, Marcarini WD, Barauna VG, Maciel ELN. Hospitalização e morte por COVID-19 e sua relação com determinantes sociais da saúde e morbidades no Espírito Santo: um estudo transversal. Epidemiol Serv Saude. 2021; 30(3):e2020919.
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27. Rosa MFP, Silva WNT da, Faria CPG, Rende VF, Oliveira SV de, Raimondi GA. Inequity in access to health and racism in: epidemiological analysis during the COVID-19 pandemic. J Heal NPEPS [Internet]. 2021; 6(2). Disponible en: https://periodicos.unemat.br/index.php/jhnpeps/article/view/5594
28. Yancy CW. COVID-19 and African Americans. JAMA [Internet]. 2020; 323(19):1891-1892. Disponible en: https://jamanetwork.com/journals/jama/fullarticle/2764789
29. Kamis C, Stolte A, West JS, Fishman SH, Brown T, Brown T, et al. Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time? SSM - Popul Heal [Internet]. 2021; 15:100845. Disponible en: https://www.sciencedirect.com/science/article/pii/S2352827321001208
30. Fuenzalida M. COVID-19 y las desigualdades territoriales al interior de Áreas Metropolitanas de Valparaíso, Santiago y Concepción, Chile. Espiral, revista de geografías y ciencias sociales [Internet]. 2020; 2(4):79-89. Disponible en: https://revistasinvestigacion.unmsm.edu.pe/index.php/espiral/article/view/19535
31. Chan JFW, Yuan S, Kok KH, To KKW, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet [Internet]. 2020; 395(10223):514-523. Disponible en: http://www.thelancet.com/article/S0140673620301549/fulltext
32. Zhu M, Kleepbua J, Guan Z, Chew SP, Tan JW, Shen J, et al. Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia. Healthc [Internet]. 2021; 9(9):1220. Disponible en: https://www.mdpi.com/2227-9032/9/9/1220/htm
33. Fotheringham AS, Wong DWS. The Modifiable Areal Unit Problem in Multivariate Statistical Analysis. Environment and planning A: Economy and Space [Internet]. 2016; 23(7):1025-1044. Disponible en: https://journals.sagepub.com/doi/10.1068/a231025
2. WHO Coronavirus (COVID-19) Dashboard | WHO Coronavirus (COVID-19) Dashboard With Vaccination Data [Internet]. [citado 11 de noviembre de 2021]. Disponible en: https://covid19.who.int/
3. Diaz H, España G, Castañeda N, Rodriguez L, de la Hoz-Restrepo F. Dynamical characteristics of the COVID-19 epidemic: Estimation from cases in Colombia. Int J Infect Dis [Internet]. 2021; 105:26-31. Disponible en: https://pubmed.ncbi.nlm.nih.gov/33529705/
4. Instituto Nacional de Salud, Observatorio Nacional de Salud. Informe 12: COVID-19 en Colombia, consecuencias de una pandemia en desarrollo [Internet]. Bogotá DC; 2020 [citado 10 de noviembre de 2021]. Disponible en: https://www.ins.gov.co/Direcciones/ONS/Informes/12COVID-19 en Colombia, pandemia en desarrollo.pdf
5. Moreno-Montoya J, Ballesteros SM, Idrovo AJ. COVID-19 distribution in Bogotá, Colombia: effect of poverty during the first 2 months of pandemic. J Epidemiol Community Health [Internet]. 2021; 76(2): 116-120. Disponible en: https://pubmed.ncbi.nlm.nih.gov/34193568/
6. Rodriguez-Villamizar LA, Belalcázar-Ceron LC, Fernández-Niño JA, Marín-Pineda DM, Rojas-Sánchez OA, AcuñaMerchán LA, et al. Air pollution, sociodemographic and health conditions effects on COVID-19 mortality in Colombia: An ecological study. Sci Total Environ. 2021; 756:144020.
7. Millán-Guerrero RO, Caballero-Hoyos R, Monárrez-Espino J. Poverty and survival from COVID-19 in Mexico. J Public Health (Bangkok) [Internet]. 2021; 43(3):437-444. Disponible en: https://academic.oup.com/jpubhealth/article/43/3/437/6046291
8. Bray I, Gibson A, White J. Coronavirus disease 2019 mortality: a multivariate ecological analysis in relation to ethnicity, population density, obesity, deprivation and pollution. Public Health [Internet]. 2020; 185:261-263. Disponible en: https://pubmed.ncbi.nlm.nih.gov/32693249/
9. Consolazio D, Murtas R, Tunesi S, Gervasi F, Benassi D, Russo AG. Assessing the Impact of Individual Characteristics and Neighborhood Socioeconomic Status During the COVID-19 Pandemic in the Provinces of Milan and Lodi. Int J Heal Serv [Internet]. 2021; 51(3):311-324. Disponible en: https://acortar.link/PppA1n
10. Casos positivos de COVID-19 en Colombia | Datos Abiertos Colombia [Internet]. [citado 31 de enero de 2022]. Disponible en: https://acortar.link/ViJpZp
11. Departamento Administrativo Nacional de Estadística DANE. Censo Nacional de Población y Vivienda 2018 [Internet]; 2018 [citado 31 de enero de 2022]. Disponible en: https://acortar.link/2c6
12. Departamento Administrativo Nacional de Estadística (DANE). Medida de pobreza multidimensional de fuente censal [Internet]. 2018 [citado 31 de enero de 2022]. Disponible en: https://acortar.link/dtlOmf
13. Departamento Administrativo Nacional de Estadística (DANE). Justificación de actualización de los datos del NBI [Internet]. Bogotá citado 31 de enero de 2022]. Disponible en: https://acortar.link/2t9Ubh
14. Departamento Administrativo Nacional de Estadística (DANE). Población censada por grupo étnico en los municipios de Antioquia. Censo 2018 [Internet]. [citado 2022 Jan 31]. Disponible en: http://www.antioquiadatos.gov.co/index.php/poblacion-319
15. Duncan C, Jones K, Moon G. Context, composition and heterogeneity: Using multilevel models in health research. Soc Sci Med. 1998; 46(1):97-117.
16. Merlo J, Chaix B, Yang M, Lynch J, Råstam L. A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon. J Epidemiol Community Health [Internet]. 2005; 59(6):443-449. Disponible en: https://jech.bmj.com/content/59/6/443
17. C C, J R, WJ B, M H, B C. MLwiN | Centre for Multilevel Modelling | University of Bristol [Internet]. 2020 [citado 2022 Jan 31]. Disponible en: http://www.bristol.ac.uk/cmm/software/mlwin/
18. Surendra H, Salama N, Lestari KD, Adrian V, Widyastuti, Oktavia D, et al. Pandemic inequity in a megacity: a multilevel analysis of individual, community and health care vulnerability risks for COVID-19 mortality in Jakarta, Indonesia. medRxiv [Internet]. 2021. Disponible en: https://www.medrxiv.org/content/10.1101/2021.11.24.21266809v1
19. Cavalini LT, De Lon ACMP. Morbidity and mortality in Brazilian municipalities: a multilevel study of the association between socioeconomic and healthcare indicators. Int J Epidemiol [Internet]. 2008; 37(4):775-783. Disponible en: https://academic.oup.com/ije/article/37/4/775/735301
20. Whittle RS, Diaz-Artiles A. An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City. BMC Med [Internet]. 2020; 18(1):1-17. Disponible en: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-020-01731-6
21. Cifuentes MP, Rodriguez-Villamizar LA, Rojas-Botero ML, Alvarez-Moreno CA, Fernández-Niño JA. Socioeconomic inequalities associated with mortality for COVID-19 in Colombia: a cohort nationwide study. J Epidemiol Community Health [Internet]. 2021; 75(7):610-615. Disponible en: https://jech.bmj.com/content/75/7/610
22. Chadeau-Hyam M, Bodinier B, Elliott J, Whitaker MD, Tzoulaki I, Vermeulen R, et al. Risk factors for positive and negative COVID-19 tests: A cautious and in-depth analysis of UK biobank data. Int J Epidemiol. 2020; 49(5):1454-1467.
23. Lyu T, Hair N, Yell N, Li Z, Qiao S, Liang C, et al. Temporal geospatial analysis of covid-19 pre-infection determinants of risk in South Carolina. Int J Environ Res Public Health. 2021; 18(18):9673.
24. Mascarello KC, Vieira ACBC, Souza ASS de, Marcarini WD, Barauna VG, Maciel ELN. Hospitalização e morte por COVID-19 e sua relação com determinantes sociais da saúde e morbidades no Espírito Santo: um estudo transversal. Epidemiol Serv Saude. 2021; 30(3):e2020919.
25. Liao TF, De Maio F. Association of Social and Economic Inequality With Coronavirus Disease 2019 Incidence and Mortality Across US Counties. JAMA Netw Open [Internet]. 2021; 4(1):e2034578-e2034578. Disponible en: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2775303
26. Porto EF, Domingues AL, Souza AC de, Miranda MKV, Froes MB da C, Pasqualinoto SRV. Mortalidade por Covid-19 no Brasil: perfil sociodemográfico das primeiras semanas. Res Soc Dev. 2021; 10(1):e34210111588.
27. Rosa MFP, Silva WNT da, Faria CPG, Rende VF, Oliveira SV de, Raimondi GA. Inequity in access to health and racism in: epidemiological analysis during the COVID-19 pandemic. J Heal NPEPS [Internet]. 2021; 6(2). Disponible en: https://periodicos.unemat.br/index.php/jhnpeps/article/view/5594
28. Yancy CW. COVID-19 and African Americans. JAMA [Internet]. 2020; 323(19):1891-1892. Disponible en: https://jamanetwork.com/journals/jama/fullarticle/2764789
29. Kamis C, Stolte A, West JS, Fishman SH, Brown T, Brown T, et al. Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time? SSM - Popul Heal [Internet]. 2021; 15:100845. Disponible en: https://www.sciencedirect.com/science/article/pii/S2352827321001208
30. Fuenzalida M. COVID-19 y las desigualdades territoriales al interior de Áreas Metropolitanas de Valparaíso, Santiago y Concepción, Chile. Espiral, revista de geografías y ciencias sociales [Internet]. 2020; 2(4):79-89. Disponible en: https://revistasinvestigacion.unmsm.edu.pe/index.php/espiral/article/view/19535
31. Chan JFW, Yuan S, Kok KH, To KKW, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet [Internet]. 2020; 395(10223):514-523. Disponible en: http://www.thelancet.com/article/S0140673620301549/fulltext
32. Zhu M, Kleepbua J, Guan Z, Chew SP, Tan JW, Shen J, et al. Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia. Healthc [Internet]. 2021; 9(9):1220. Disponible en: https://www.mdpi.com/2227-9032/9/9/1220/htm
33. Fotheringham AS, Wong DWS. The Modifiable Areal Unit Problem in Multivariate Statistical Analysis. Environment and planning A: Economy and Space [Internet]. 2016; 23(7):1025-1044. Disponible en: https://journals.sagepub.com/doi/10.1068/a231025
