Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic
Descripción del Articulo
Background In this study, we estimated excess all-cause deaths and excess death rates during the COVID-19 pandemic in 25 Peruvian regions, stratified by sex and age group. Design Cross-sectional study. Setting Twenty-five Peruvian regions with complete mortality data. Participants Annual all-cause o...
Autores: | , , |
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Formato: | artículo |
Fecha de Publicación: | 2022 |
Institución: | Universidad Tecnológica del Perú |
Repositorio: | UTP-Institucional |
Lenguaje: | español |
OAI Identifier: | oai:repositorio.utp.edu.pe:20.500.12867/5784 |
Enlace del recurso: | https://hdl.handle.net/20.500.12867/5784 http://dx.doi.org/10.1136/bmjopen-2021-057056 |
Nivel de acceso: | acceso abierto |
Materia: | Mortality COVID-19 https://purl.org/pe-repo/ocde/ford#3.00.00 |
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dc.title.es_PE.fl_str_mv |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
title |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
spellingShingle |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic Ramírez Soto, Max Carlos Mortality COVID-19 https://purl.org/pe-repo/ocde/ford#3.00.00 |
title_short |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
title_full |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
title_fullStr |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
title_full_unstemmed |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
title_sort |
Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemic |
author |
Ramírez Soto, Max Carlos |
author_facet |
Ramírez Soto, Max Carlos Ortega-Cáceres, Gutia Arroyo-Hernández, Hugo |
author_role |
author |
author2 |
Ortega-Cáceres, Gutia Arroyo-Hernández, Hugo |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ramírez Soto, Max Carlos Ortega-Cáceres, Gutia Arroyo-Hernández, Hugo |
dc.subject.es_PE.fl_str_mv |
Mortality COVID-19 |
topic |
Mortality COVID-19 https://purl.org/pe-repo/ocde/ford#3.00.00 |
dc.subject.ocde.es_PE.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#3.00.00 |
description |
Background In this study, we estimated excess all-cause deaths and excess death rates during the COVID-19 pandemic in 25 Peruvian regions, stratified by sex and age group. Design Cross-sectional study. Setting Twenty-five Peruvian regions with complete mortality data. Participants Annual all-cause official mortality data set from SINADEF (Sistema Informático Nacional de Defunciones) at the Ministry of Health of Peru for 2017– 2020, disaggregated by age and sex. Main outcome measures Excess deaths and excess death rates (observed deaths vs expected deaths) in 2020 by sex and age (0–29, 30–39, 40 49, 50–59, 60–69, 70–79 and ≥80 years) were estimated using P-score. The ORs for excess mortality were summarised with a randomeffects meta-analysis. Results In the period between January and December 2020, we estimated an excess of 68 608 (117%) deaths in men and 34 742 (69%) deaths in women, corresponding to an excess death rate of 424 per 100 000 men and 211 per 100 000women compared with the expected mortality rate. The number of excess deaths increased with age and was higher in men aged 60–69 years (217%) compared with women (121%). Men between the ages of 40 and 79 years experienced twice the rate of excess deaths compared with the expected rate. In eight regions, excess deaths were higher than 100% in men, and in seven regions excess deaths were higher than 70% in women. Men in eight regions and women in one region had two times increased odds of excess death than the expected mortality. There were differences in excess mortality according to temporal distribution by epidemiological week. Conclusion Approximately 100 000 excess all-cause deaths occurred in 2020 in Peru. Age-stratified excess death rates were higher in men than in women. There was strong excess in geographical and temporal mortality patterns according to region. |
publishDate |
2022 |
dc.date.accessioned.none.fl_str_mv |
2022-07-27T07:57:12Z |
dc.date.available.none.fl_str_mv |
2022-07-27T07:57:12Z |
dc.date.issued.fl_str_mv |
2022 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
dc.identifier.issn.none.fl_str_mv |
2044-605 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12867/5784 |
dc.identifier.journal.es_PE.fl_str_mv |
BMJ Open |
dc.identifier.doi.none.fl_str_mv |
http://dx.doi.org/10.1136/bmjopen-2021-057056 |
identifier_str_mv |
2044-605 BMJ Open |
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https://hdl.handle.net/20.500.12867/5784 http://dx.doi.org/10.1136/bmjopen-2021-057056 |
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spa |
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spa |
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BMJ Open;12:e057056 |
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info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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BMJ Publishing Group |
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GB |
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Repositorio Institucional - UTP Universidad Tecnológica del Perú |
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reponame:UTP-Institucional instname:Universidad Tecnológica del Perú instacron:UTP |
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Universidad Tecnológica del Perú |
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spelling |
Ramírez Soto, Max CarlosOrtega-Cáceres, GutiaArroyo-Hernández, Hugo2022-07-27T07:57:12Z2022-07-27T07:57:12Z20222044-605https://hdl.handle.net/20.500.12867/5784BMJ Openhttp://dx.doi.org/10.1136/bmjopen-2021-057056Background In this study, we estimated excess all-cause deaths and excess death rates during the COVID-19 pandemic in 25 Peruvian regions, stratified by sex and age group. Design Cross-sectional study. Setting Twenty-five Peruvian regions with complete mortality data. Participants Annual all-cause official mortality data set from SINADEF (Sistema Informático Nacional de Defunciones) at the Ministry of Health of Peru for 2017– 2020, disaggregated by age and sex. Main outcome measures Excess deaths and excess death rates (observed deaths vs expected deaths) in 2020 by sex and age (0–29, 30–39, 40 49, 50–59, 60–69, 70–79 and ≥80 years) were estimated using P-score. The ORs for excess mortality were summarised with a randomeffects meta-analysis. Results In the period between January and December 2020, we estimated an excess of 68 608 (117%) deaths in men and 34 742 (69%) deaths in women, corresponding to an excess death rate of 424 per 100 000 men and 211 per 100 000women compared with the expected mortality rate. The number of excess deaths increased with age and was higher in men aged 60–69 years (217%) compared with women (121%). Men between the ages of 40 and 79 years experienced twice the rate of excess deaths compared with the expected rate. In eight regions, excess deaths were higher than 100% in men, and in seven regions excess deaths were higher than 70% in women. Men in eight regions and women in one region had two times increased odds of excess death than the expected mortality. There were differences in excess mortality according to temporal distribution by epidemiological week. Conclusion Approximately 100 000 excess all-cause deaths occurred in 2020 in Peru. Age-stratified excess death rates were higher in men than in women. There was strong excess in geographical and temporal mortality patterns according to region.Campus Lima Centroapplication/pdfspaBMJ Publishing GroupGBBMJ Open;12:e057056info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Repositorio Institucional - UTPUniversidad Tecnológica del Perúreponame:UTP-Institucionalinstname:Universidad Tecnológica del Perúinstacron:UTPMortalityCOVID-19https://purl.org/pe-repo/ocde/ford#3.00.00Excess all-cause deaths stratified by sex and age in Peru: a time series analysis during the COVID-19 pandemicinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.utp.edu.pe/bitstream/20.500.12867/5784/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALM.Ramirez_Articulo.pdfM.Ramirez_Articulo.pdfapplication/pdf4364700http://repositorio.utp.edu.pe/bitstream/20.500.12867/5784/1/M.Ramirez_Articulo.pdf6cbdcd1d6c6befa9ac5d200d1d14d3d2MD51TEXTM.Ramirez_Articulo.pdf.txtM.Ramirez_Articulo.pdf.txtExtracted texttext/plain37456http://repositorio.utp.edu.pe/bitstream/20.500.12867/5784/3/M.Ramirez_Articulo.pdf.txt299f1037613f39ff04a2fba1995e9fd3MD53THUMBNAILM.Ramirez_Articulo.pdf.jpgM.Ramirez_Articulo.pdf.jpgGenerated Thumbnailimage/jpeg25602http://repositorio.utp.edu.pe/bitstream/20.500.12867/5784/4/M.Ramirez_Articulo.pdf.jpg5315b050935fab8dea00716a6d9ec3ecMD5420.500.12867/5784oai:repositorio.utp.edu.pe:20.500.12867/57842023-05-22 12:36:32.536Repositorio Institucional de la Universidad Tecnológica del Perúrepositorio@utp.edu.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 |
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