Estudios originales
Medwave 2020;20(8):e8032 doi: 10.5867/medwave.2020.08.8032
Exceso de mortalidad en Lima Metropolitana durante la pandemia de COVID-19: comparación a nivel distrital
Excess mortality in Metropolitan Lima during the COVID-19 pandemic: A district level comparison
Akram Hernández-Vásquez, Jesús Eduardo Gamboa-Unsihuay, Rodrigo Vargas-Fernández, Diego Azañedo
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Palabras clave: COVID-19, mortality, social determinants of health, Peru

Resumen

Objetivo
Comparar el exceso de muertes según quintiles distritales del Índice de Desarrollo Humano (IDH) en Lima Metropolitana, capital de Perú, y analizar los factores socioeconómicos asociados con el exceso de muertes en el contexto de la COVID-19.

Métodos
Estudio transversal retrospectivo de los registros de mortalidad por causas no violentas registrados en el Sistema Informático Nacional de Defunciones de los 50 distritos de Lima Metropolitana durante las primeras 24 semanas de los años 2019 y 2020. Se realizó un análisis descriptivo mediante tablas de contingencia y gráficos de series de tiempo por sexo, grupo de edad y quintil del distrito de residencia según el IDH. Se realizó un análisis de regresión binomial negativa para identificar posibles factores asociados con el exceso de muertes.

Resultados
Un exceso de 20 093 muertes no violentas y 2.979 muertes confirmadas por COVID-19 se registraron en Lima Metropolitana durante el período de estudio. El exceso de mortalidad se observó especialmente en hombres y adultos de 60 años o más. Los distritos pertenecientes al quintil 5 según el IDH presentan, en la mayoría de los casos, las tasas más bajas de exceso de muertes. El análisis multivariado halló que el IDH (p = 0.009) y el porcentaje de habitantes en pobreza extrema (p = 0.014) disminuyen la tasa de exceso de muertes en Lima Metropolitana.

Conclusiones
El exceso de muertes no violentas en Lima Metropolitana es mayor en los quintiles con el IDH más bajo, en los hombres y en el grupo de edad de 60 a más años. El estudio de los determinantes sociales y económicos de la salud en Perú es fundamental para el diseño de las medidas que debe tomar el gobierno contra la pandemia de COVID-19.


 

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Objective
To compare excess mortality by district quintiles according to the Human Development Index (HDI) in Metropolitan Lima, the capital of Peru, and analyze the socioeconomic factors associated with excess mortality within the context of COVID-19.

Methods
Retrospective cross-sectional analysis of the mortality records from non-violent causes registered in the National Death Information System in the 50 districts of Metropolitan Lima of the first 24 weeks of the years 2019 and 2020. Descriptive analysis was performed using contingency tables and time series graphs by sex, age group, and quintile of the district of residence according to the HDI. Negative binomial regression analysis was performed to identify possible explanatory factors for excess mortality.

Results
An excess of 20 093 non-violent deaths and 2,979 confirmed deaths from COVID-19 were registered in Metropolitan Lima during the study period. The increase was observed primarily in men and adults aged 60 and over. Residents in the districts belonging to the fifth quintile, according to HDI, presented, in most cases, the lowest rates. Multivariate analysis revealed that a higher HDI level (p = 0.009) and a higher proportion of inhabitants living in extreme poverty (p = 0.014) decreased the excess mortality.

Conclusion
Excess of non-violent deaths in Metropolitan Lima is higher in the quintiles with the lowest HDI, in men, and the age group from 60 to more years of age. The study of social and economic health determinants in Peru is crucial for the design of measures to be taken by the government against the COVID-19 pandemic.

Autores: Akram Hernández-Vásquez[1], Jesús Eduardo Gamboa-Unsihuay[2], Rodrigo Vargas-Fernández[3], Diego Azañedo[4]

Filiación:
[1] Centro de Excelencia en Investigaciones Económicas y Sociales en Salud, Vicerrectorado de Investigación, Universidad San Ignacio de Loyola, Lima, Perú
[2] Facultad de Economía y Planificación, Universidad Nacional Agraria La Molina, Lima, Perú
[3] Facultad de Ciencias de la Salud, Universidad Científica del Sur, Lima, Perú
[4] Instituto de Investigación, Universidad Católica los Ángeles de Chimbote, Chimbote, Perú

E-mail: ahernandez@usil.edu.pe

Correspondencia a:
[1] Universidad San Ignacio de Loyola
550 La Fontana Av., La Molina 00012
Lima, Perú

Citación: Hernández-Vásquez A, Gamboa-Unsihuay JE, Vargas-Fernández R, Azañedo D. Excess mortality in Metropolitan Lima during the COVID-19 pandemic: A district level comparison. Medwave 2020;20(8):e8032 doi: 10.5867/medwave.2020.08.8032

Fecha de envío: 16/7/2020

Fecha de aceptación: 25/8/2020

Fecha de publicación: 25/9/2020

Origen: No solicitado

Tipo de revisión: Con revisión por pares externa, por cuatro árbitros a doble ciego

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  1. COVID-19 Map. Johns Hopkins Coronavirus Resource Center. 2020. [On line] | Link |
  2. Burn-Murdoch J, Giles C. UK suffers second-highest death rate from coronavirus | Free to read. Financial Times. 2020. [On line] | Link |
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  13. The impact of COVID-19 (Coronavirus) on global poverty: Why Sub-Saharan Africa might be the region hardest hit. World Bank Blogs. 2020. [On line] | Link |
  14. Michelozzi P, de'Donato F, Scortichini M, De Sario M, Noccioli F, Rossi P, et al. Mortality impacts of the coronavirus disease (COVID-19) outbreak by sex and age: rapid mortality surveillance system, Italy, 1 February to 18 April 2020. Euro Surveill. 2020 May;25(19):2000620. | CrossRef | PubMed |
  15. Piccininni M, Rohmann JL, Foresti L, Lurani C, Kurth T. Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: descriptive study. BMJ. 2020 May 14;369:m1835. | CrossRef | PubMed |
  16. Ochoa Sangrador C, Garmendia Leiza JR, Pérez Boillos MJ, Pastrana Ara F, Lorenzo Lobato MDP, Andrés de Llano JM. Impacto de la COVID-19 en la mortalidad de la comunidad autónoma de Castilla y León [Impact of COVID-19 on mortality in the autonomous community of Castilla y León (Spain)]. Gac Sanit. 2020 May 4:S0213-9111(20)30092-3. Spanish. | CrossRef | PubMed |
  17. Cagnacci A, Xholli A. Age-related difference in the rate of coronavirus disease 2019 mortality in women versus men. Am J Obstet Gynecol. 2020 Sep;223(3):453-454. | CrossRef | PubMed |
  18. Dudley JP, Lee NT. Disparities in Age-specific Morbidity and Mortality From SARS-CoV-2 in China and the Republic of Korea. Clin Infect Dis. 2020 Jul 28;71(15):863-865. | CrossRef | PubMed |
  19. Freitas ARR, Medeiros NM, Frutuoso L, Beckedorff OA, Martin LMA, Coelho MMM, et al. Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals. medRxiv. 2020. | CrossRef |
  20. Bottai M. A regression method for modelling geometric rates. Stat Methods Med Res. 2017 Dec;26(6):2700-2707. | CrossRef | PubMed |
COVID-19 Map. Johns Hopkins Coronavirus Resource Center. 2020. [On line] | Link |

Burn-Murdoch J, Giles C. UK suffers second-highest death rate from coronavirus | Free to read. Financial Times. 2020. [On line] | Link |

Chung RY, Dong D, Li MM. Socioeconomic gradient in health and the covid-19 outbreak. BMJ. 2020 Apr 1;369:m1329. | CrossRef | PubMed |

Niedzwiedz CL, O'Donnell CA, Jani BD, Demou E, Ho FK, Celis-Morales C, et al. Ethnic and socioeconomic differences in SARS-CoV-2 infection: prospective cohort study using UK Biobank. BMC Med. 2020 May 29;18(1):160. | CrossRef | PubMed |

Khalatbari-Soltani S, Cumming RC, Delpierre C, Kelly-Irving M. Importance of collecting data on socioeconomic determinants from the early stage of the COVID-19 outbreak onwards. J Epidemiol Community Health. 2020 Aug;74(8):620-623. | CrossRef | PubMed |

Vargas-Herrera J, Ruiz KP, Nuñez GG, Ohno JM, Pérez-Lu JE, Huarcaya WV, et al. Resultados preliminares del fortalecimiento del sistema informático nacional de defunciones [Preliminary results of the strengthening of the national death registry information system]. Rev Peru Med Exp Salud Publica. 2018 Jul-Sep;35(3):505-514. Spanish. | CrossRef | PubMed |

Magnani C, Azzolina D, Gallo E, Ferrante D, Gregori D. How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy. Int J Environ Res Public Health. 2020 May 15;17(10):3452. | CrossRef | PubMed |

Roberton T, Carter ED, Chou VB, Stegmuller AR, Jackson BD, Tam Y, et al. Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study. Lancet Glob Health. 2020 Jul;8(7):e901-e908. | CrossRef | PubMed |

Roser M. Human Development Index (HDI). Our World in Data. 2014. [On line] | Link |

Wadhera RK, Wadhera P, Gaba P, Figueroa JF, Joynt Maddox KE, Yeh RW, et al. Variation in COVID-19 Hospitalizations and Deaths Across New York City Boroughs. JAMA. 2020 Jun 2;323(21):2192-2195. | CrossRef | PubMed |

Royal Society for Public Health. Guest Blog: Tracking the total mortality impact of the Covid-19 pandemic. RSPH. 2020. [On line] | Link |

Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, Iosifidis C, et al. The socio-economic implications of the coronavirus pandemic (COVID-19): A review. Int J Surg. 2020 Jun;78:185-193. | CrossRef | PubMed |

The impact of COVID-19 (Coronavirus) on global poverty: Why Sub-Saharan Africa might be the region hardest hit. World Bank Blogs. 2020. [On line] | Link |

Michelozzi P, de'Donato F, Scortichini M, De Sario M, Noccioli F, Rossi P, et al. Mortality impacts of the coronavirus disease (COVID-19) outbreak by sex and age: rapid mortality surveillance system, Italy, 1 February to 18 April 2020. Euro Surveill. 2020 May;25(19):2000620. | CrossRef | PubMed |

Piccininni M, Rohmann JL, Foresti L, Lurani C, Kurth T. Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: descriptive study. BMJ. 2020 May 14;369:m1835. | CrossRef | PubMed |

Ochoa Sangrador C, Garmendia Leiza JR, Pérez Boillos MJ, Pastrana Ara F, Lorenzo Lobato MDP, Andrés de Llano JM. Impacto de la COVID-19 en la mortalidad de la comunidad autónoma de Castilla y León [Impact of COVID-19 on mortality in the autonomous community of Castilla y León (Spain)]. Gac Sanit. 2020 May 4:S0213-9111(20)30092-3. Spanish. | CrossRef | PubMed |

Cagnacci A, Xholli A. Age-related difference in the rate of coronavirus disease 2019 mortality in women versus men. Am J Obstet Gynecol. 2020 Sep;223(3):453-454. | CrossRef | PubMed |

Dudley JP, Lee NT. Disparities in Age-specific Morbidity and Mortality From SARS-CoV-2 in China and the Republic of Korea. Clin Infect Dis. 2020 Jul 28;71(15):863-865. | CrossRef | PubMed |

Freitas ARR, Medeiros NM, Frutuoso L, Beckedorff OA, Martin LMA, Coelho MMM, et al. Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals. medRxiv. 2020. | CrossRef |

Bottai M. A regression method for modelling geometric rates. Stat Methods Med Res. 2017 Dec;26(6):2700-2707. | CrossRef | PubMed |