Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search
Advanced Search
mobile menu button

Search

Page Path
HOME > Search
1 "Geographic information systems"
Filter
Filter
Article category
Keywords
Publication year
Authors
Original Article
Spatiotemporal trends in diabetes-related mortality by school district in the state of Michigan, United States
Nurjannah Nurjannah, Kathleen M. Baker, Duduzile Phindi Mashinini
Epidemiol Health. 2021;43:e2021098.   Published online November 9, 2021
DOI: https://doi.org/10.4178/epih.e2021098
  • 22,490 View
  • 152 Download
  • 3 Web of Science
  • 4 Crossref
AbstractAbstract AbstractSummary PDF
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.
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.

Citations

Citations to this article as recorded by  
  • Age-specific life expectancies across school districts in the United States: Applying a population weighted geographic crosswalk to aggregate census tract indicators
    Logan Beyer, Jeff Blossom, Junyi Chen, Rockli Kim, S.V. Subramanian
    SSM - Population Health.2026; 33: 101896.     CrossRef
  • 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
Epidemiol Health : Epidemiology and Health
© Korean Society of Epidemiology.
TOP