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Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States
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Nurjannah Nurjannah, Kathleen M. Baker, Duduzile Phindi Mashinini
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Epidemiol Health. 2021;43:e2021098. Published online November 9, 2021
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DOI: https://doi.org/10.4178/epih.e2021098
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Abstract
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.
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Summary
Key Message
Using existing secondary data with spatio-temporal analysis, the study identified diabetes-related death varies across space and time within the state of Michigan, USA at the school district level. This approach provided policy-relevant information to target high-risk school-district when having limited resources to prevent diabetes at schools.
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Citations
Citations to this article as recorded by  - Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study
Shuli Ma, Jie Ge, Lei Qin, Xiaoting Chen, Linlin Du, Yanbo Qi, Li Bai, Yunfeng Han, Zhiping Xie, Jiaxin Chen, Yuehui Jia
JMIR Public Health and Surveillance.2024; 10: e57807. CrossRef - Asthma Hot Spots in New York Before and During the COVID-19 Pandemic
Samira Skochko, Trang Nguyen, Stephanie Mack, Brooke Turcotte, Catherine Adler, Eli S. Rosenberg, Christopher Joseph, Lynley Siag, Alexandra Dubuisson, Victoria L. Wagner
Preventing Chronic Disease.2024;[Epub] CrossRef - Spatiotemporal analyses of the epidemiological characteristics of diabetes mellitus
Sang Youl Rhee
Epidemiology and Health.2021; 43: e2021102. CrossRef
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