Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study
Background: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed t...
Published in: | Journal of Infection and Public Health |
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2-s2.0-85176264682 Shakor A.S.A.; Samsudin E.Z.; Chen X.W.; Ghazali M.H. Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study 2023 Journal of Infection and Public Health 16 12 10.1016/j.jiph.2023.10.016 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176264682&doi=10.1016%2fj.jiph.2023.10.016&partnerID=40&md5=1ce3d7cf9275df1d56a379831c23370a Background: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed to examine the factors associated with COVID-19 BID by integrating new variables from multiple databases. Methods: This multi-database comparative cross-sectional study examined COVID-19 in-patient deaths (IPD) and COVID-19 BID (n = 244 in each group) in Selangor, Malaysia. BID cases, IPD cases, and their sociodemographic, clinical, and health behaviour factors were identified from the COVID-19 mortality investigation reports submitted to the Selangor State Health Department between 14 February 2022 and 31 March 2023. Data linkage was used to connect three open-source databases—GitHub-MOH, Socioeconomic Data and Applications Center, and OpenStreetMap—and identify health infrastructure and geospatial factors. The groups were compared using chi-square tests, independent t-tests, and logistic regression analyses to identify factors associated with COVID-19 BID. Results: The COVID-19 IPD and BID cases were comparable. After adjusting for confounders, non-Malaysian nationality (AOR: 3.765, 95% CI: 1.163, 12.190), obesity (AOR: 5.272, 95% CI: 1.131, 24.567), not seeking treatment while unwell (AOR: 5.385, 95% CI: 3.157, 9.186), and a higher percentage of COVID-19-dedicated beds occupied on the date of death (AOR: 1.165, 95% CI: 1.078, 1.259) were associated with increased odds of COVID-19 BID. On the other hand, being married (AOR: 0.396, 95% CI: 0.158, 0.997) and the interaction between the percentage of COVID-19-dedicated beds occupied and the percentage of ventilators in use (AOR: 0.996, 95% CI: 0.994, 0.999) emerged as protective factors. Conclusion: These findings indicated that certain groups have higher odds of COVID-19 BID and thus, require closer monitoring. Considering that COVID-19 BID is influenced by various elements beyond clinical factors, intensifying public health initiatives and multi-organisational collaboration is necessary to address this issue. © 2023 The Author(s) Elsevier Ltd 18760341 English Article All Open Access; Gold Open Access |
author |
Shakor A.S.A.; Samsudin E.Z.; Chen X.W.; Ghazali M.H. |
spellingShingle |
Shakor A.S.A.; Samsudin E.Z.; Chen X.W.; Ghazali M.H. Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
author_facet |
Shakor A.S.A.; Samsudin E.Z.; Chen X.W.; Ghazali M.H. |
author_sort |
Shakor A.S.A.; Samsudin E.Z.; Chen X.W.; Ghazali M.H. |
title |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
title_short |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
title_full |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
title_fullStr |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
title_full_unstemmed |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
title_sort |
Factors associated with COVID-19 brought-in deaths: A data-linkage comparative cross-sectional study |
publishDate |
2023 |
container_title |
Journal of Infection and Public Health |
container_volume |
16 |
container_issue |
12 |
doi_str_mv |
10.1016/j.jiph.2023.10.016 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176264682&doi=10.1016%2fj.jiph.2023.10.016&partnerID=40&md5=1ce3d7cf9275df1d56a379831c23370a |
description |
Background: The phenomenon of Coronavirus disease 2019 (COVID-19) brought-in-dead (BID), i.e., COVID-19 deaths occurring outside hospital settings, suggests missed opportunities for life-saving care. However, much is still unknown with regards to its potential determinants. The present study aimed to examine the factors associated with COVID-19 BID by integrating new variables from multiple databases. Methods: This multi-database comparative cross-sectional study examined COVID-19 in-patient deaths (IPD) and COVID-19 BID (n = 244 in each group) in Selangor, Malaysia. BID cases, IPD cases, and their sociodemographic, clinical, and health behaviour factors were identified from the COVID-19 mortality investigation reports submitted to the Selangor State Health Department between 14 February 2022 and 31 March 2023. Data linkage was used to connect three open-source databases—GitHub-MOH, Socioeconomic Data and Applications Center, and OpenStreetMap—and identify health infrastructure and geospatial factors. The groups were compared using chi-square tests, independent t-tests, and logistic regression analyses to identify factors associated with COVID-19 BID. Results: The COVID-19 IPD and BID cases were comparable. After adjusting for confounders, non-Malaysian nationality (AOR: 3.765, 95% CI: 1.163, 12.190), obesity (AOR: 5.272, 95% CI: 1.131, 24.567), not seeking treatment while unwell (AOR: 5.385, 95% CI: 3.157, 9.186), and a higher percentage of COVID-19-dedicated beds occupied on the date of death (AOR: 1.165, 95% CI: 1.078, 1.259) were associated with increased odds of COVID-19 BID. On the other hand, being married (AOR: 0.396, 95% CI: 0.158, 0.997) and the interaction between the percentage of COVID-19-dedicated beds occupied and the percentage of ventilators in use (AOR: 0.996, 95% CI: 0.994, 0.999) emerged as protective factors. Conclusion: These findings indicated that certain groups have higher odds of COVID-19 BID and thus, require closer monitoring. Considering that COVID-19 BID is influenced by various elements beyond clinical factors, intensifying public health initiatives and multi-organisational collaboration is necessary to address this issue. © 2023 The Author(s) |
publisher |
Elsevier Ltd |
issn |
18760341 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677578300030976 |