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Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States
OBJECTIVES: This study examined the spatiotemporal epidemiological status of diabetes-related death in relation to school district boundaries in the state of Michigan, United States. METHODS: A retrospective observational study was conducted using death records spanning the years 2007–2014 in Michig...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Epidemiology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920744/ https://www.ncbi.nlm.nih.gov/pubmed/34773935 http://dx.doi.org/10.4178/epih.e2021098 |
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author | Nurjannah, Nurjannah Baker, Kathleen M. Mashinini, Duduzile Phindi |
author_facet | Nurjannah, Nurjannah Baker, Kathleen M. Mashinini, Duduzile Phindi |
author_sort | Nurjannah, Nurjannah |
collection | PubMed |
description | OBJECTIVES: This study examined the spatiotemporal epidemiological status of diabetes-related death in relation to school district boundaries in the state of Michigan, United States. METHODS: A retrospective observational study was conducted using death records spanning the years 2007–2014 in Michigan, with school districts as the geographic unit of analysis. Geocoding was performed for each death record. Cluster analysis used spatial autocorrelation with local Moran’s I, and spatiotemporal analysis used the Space Time Pattern Mining tool in ArcGIS Pro 2.1. RESULTS: The study revealed spatial clusters of high-high locations of diabetes-related mortality rate by school district in Michigan from 2007 to 2014. Spatiotemporal analysis showed grids with intensifying, consecutive, sporadic, and persistent hotspots of diabetes-related death in the Lansing, Royal Oak, Flint City, Berkley, Detroit City, East Lansing, South Lake, and Holt public school districts. These school districts should be prioritized for school-based diabetes prevention programs CONCLUSIONS: The study demonstrated the presence of various hotspots of diabetes-related deaths within the state of Michigan across the 8-year period of analysis. Understanding spatial and temporal hotspots could further improve our ability to evaluate diabetes burden across both time and space. |
format | Online Article Text |
id | pubmed-8920744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Society of Epidemiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-89207442022-03-22 Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States Nurjannah, Nurjannah Baker, Kathleen M. Mashinini, Duduzile Phindi Epidemiol Health Original Article OBJECTIVES: This study examined the spatiotemporal epidemiological status of diabetes-related death in relation to school district boundaries in the state of Michigan, United States. METHODS: A retrospective observational study was conducted using death records spanning the years 2007–2014 in Michigan, with school districts as the geographic unit of analysis. Geocoding was performed for each death record. Cluster analysis used spatial autocorrelation with local Moran’s I, and spatiotemporal analysis used the Space Time Pattern Mining tool in ArcGIS Pro 2.1. RESULTS: The study revealed spatial clusters of high-high locations of diabetes-related mortality rate by school district in Michigan from 2007 to 2014. Spatiotemporal analysis showed grids with intensifying, consecutive, sporadic, and persistent hotspots of diabetes-related death in the Lansing, Royal Oak, Flint City, Berkley, Detroit City, East Lansing, South Lake, and Holt public school districts. These school districts should be prioritized for school-based diabetes prevention programs CONCLUSIONS: The study demonstrated the presence of various hotspots of diabetes-related deaths within the state of Michigan across the 8-year period of analysis. Understanding spatial and temporal hotspots could further improve our ability to evaluate diabetes burden across both time and space. Korean Society of Epidemiology 2021-11-09 /pmc/articles/PMC8920744/ /pubmed/34773935 http://dx.doi.org/10.4178/epih.e2021098 Text en © 2021, Korean Society of Epidemiology 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 work is properly cited. |
spellingShingle | Original Article Nurjannah, Nurjannah Baker, Kathleen M. Mashinini, Duduzile Phindi Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title | Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title_full | Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title_fullStr | Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title_full_unstemmed | Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title_short | Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States |
title_sort | spatiotemporal trends in diabetes-related mortality by school district in the state of michigan, united states |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920744/ https://www.ncbi.nlm.nih.gov/pubmed/34773935 http://dx.doi.org/10.4178/epih.e2021098 |
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