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Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria
This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th 2020 and October 25th 2020 to July 25th 2021....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490894/ https://www.ncbi.nlm.nih.gov/pubmed/37682911 http://dx.doi.org/10.1371/journal.pone.0291118 |
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author | Akinseinde, Samuel A. Kosemani, Samson Osuolale, Emmanuel Cesare, Nina Pellicane, Samantha Nsoesie, Elaine O. |
author_facet | Akinseinde, Samuel A. Kosemani, Samson Osuolale, Emmanuel Cesare, Nina Pellicane, Samantha Nsoesie, Elaine O. |
author_sort | Akinseinde, Samuel A. |
collection | PubMed |
description | This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th 2020 and October 25th 2020 to July 25th 2021. Data sources include 2018 Nigeria Demographic and Health Survey and Nigeria Centre for Disease Control (NCDC) COVID-19 daily reports. It uses negative binomial models to model deaths, and stratifies results by respondent gender. It finds that overall mortality rates were concentrated within three states: Lagos, Edo and Federal Capital Territory (FCT) Abuja. Urban residence and insurance coverage are positively associated with differences in deaths for the full sample. The former, however, is significant only during the early stages of the pandemic. Associative differences in gender-stratified models suggest that wealth was a stronger protective factor for men and insurance a stronger protective factor for women. Associative strength between sociodemographic measures and deaths varies by gender and pandemic wave, suggesting that the pandemic impacted men and women in unique ways, and that the effectiveness of interventions should be evaluated for specific waves or periods. |
format | Online Article Text |
id | pubmed-10490894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104908942023-09-09 Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria Akinseinde, Samuel A. Kosemani, Samson Osuolale, Emmanuel Cesare, Nina Pellicane, Samantha Nsoesie, Elaine O. PLoS One Research Article This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th 2020 and October 25th 2020 to July 25th 2021. Data sources include 2018 Nigeria Demographic and Health Survey and Nigeria Centre for Disease Control (NCDC) COVID-19 daily reports. It uses negative binomial models to model deaths, and stratifies results by respondent gender. It finds that overall mortality rates were concentrated within three states: Lagos, Edo and Federal Capital Territory (FCT) Abuja. Urban residence and insurance coverage are positively associated with differences in deaths for the full sample. The former, however, is significant only during the early stages of the pandemic. Associative differences in gender-stratified models suggest that wealth was a stronger protective factor for men and insurance a stronger protective factor for women. Associative strength between sociodemographic measures and deaths varies by gender and pandemic wave, suggesting that the pandemic impacted men and women in unique ways, and that the effectiveness of interventions should be evaluated for specific waves or periods. Public Library of Science 2023-09-08 /pmc/articles/PMC10490894/ /pubmed/37682911 http://dx.doi.org/10.1371/journal.pone.0291118 Text en © 2023 Akinseinde et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Akinseinde, Samuel A. Kosemani, Samson Osuolale, Emmanuel Cesare, Nina Pellicane, Samantha Nsoesie, Elaine O. Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title | Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title_full | Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title_fullStr | Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title_full_unstemmed | Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title_short | Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria |
title_sort | association between wealth, insurance coverage, urban residence, median age and covid-19 deaths across states in nigeria |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490894/ https://www.ncbi.nlm.nih.gov/pubmed/37682911 http://dx.doi.org/10.1371/journal.pone.0291118 |
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