Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102311
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dc.contributorDepartment of Applied Mathematics-
dc.creatorYao, XIen_US
dc.creatorHan, Len_US
dc.creatorSun, Yen_US
dc.creatorHe, Den_US
dc.creatorZhao, Sen_US
dc.creatorRan, Jen_US
dc.date.accessioned2023-10-18T07:51:04Z-
dc.date.available2023-10-18T07:51:04Z-
dc.identifier.issn1876-0341en_US
dc.identifier.urihttp://hdl.handle.net/10397/102311-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2023 The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Yao, X. I., Han, L., Sun, Y., He, D., Zhao, S., & Ran, J. (2023). Temporal variation of excess deaths from diabetes during the COVID-19 pandemic in the United States. Journal of Infection and Public Health, 16(4), 483-489 is availale at https://doi.org/10.1016/j.jiph.2023.01.018.en_US
dc.subjectCOVID-19en_US
dc.subjectDemographic analysesen_US
dc.subjectExcess deathsen_US
dc.subjectPandemic wavesen_US
dc.subjectTemporal patternen_US
dc.titleTemporal variation of excess deaths from diabetes during the COVID-19 pandemic in the United Statesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage483en_US
dc.identifier.epage489en_US
dc.identifier.volume16en_US
dc.identifier.issue4en_US
dc.identifier.doi10.1016/j.jiph.2023.01.018en_US
dcterms.abstractBackground: Although the COVID-19 pandemic has persisted for more than two years with the evident excess mortality from diabetes, few studies have investigated its temporal patterns. This study aims to estimate the excess deaths from diabetes in the United States (US) during the COVID-19 pandemic and evaluate the excess deaths by spatiotemporal pattern, age groups, sex, and race/ethnicity.-
dcterms.abstractMethods: Diabetes as one of multiple causes of death or an underlying cause of death were both considered into analyses. The Poisson log-linear regression model was used to estimate weekly expected counts of deaths during the pandemic with adjustments for long-term trend and seasonality. Excess deaths were measured by the difference between observed and expected death counts, including weekly average excess deaths, excess death rate, and excess risk. We calculated the excess estimates by pandemic wave, US state, and demographic characteristic.-
dcterms.abstractResults: From March 2020 to March 2022, deaths that diabetes as one of multiple causes of death and an underlying cause of death were about 47.6 % and 18.4 % higher than the expected. The excess deaths of diabetes had evident temporal patterns with two large percentage increases observed during March 2020, to June 2020, and June 2021 to November 2021. The regional heterogeneity and underlying age and racial/ethnic disparities of the excess deaths were also clearly observed.-
dcterms.abstractConclusions: This study highlighted the increased risks of diabetes mortality, heterogeneous spatiotemporal patterns, and associated demographic disparities during the pandemic. Practical actions are warranted to monitor disease progression, and lessen health disparities in patients with diabetes during the COVID-19 pandemic.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of infection and public health, Apr. 2023, v. 16, no. 4, p. 483-489en_US
dcterms.isPartOfJournal of infection and public healthen_US
dcterms.issued2023-04-
dc.identifier.scopus2-s2.0-85148053486-
dc.identifier.eissn1876-035Xen_US
dc.description.validate202310 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextSci-Tech Innovation Programme 2022 at School of Global Health; Shanghai Science and Technology Development Foundation; National Natural Science Foundation of China; Natural Science Foundation of Guangdong Province; Science, Technology and Innovation Commission of Shenzhen Municipalityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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