Spatial and Temporal Patterns of Chronic Disease Burden in the U.S., 2018-2021

Jocelyn V Hunyadi1, Kehe Zhang1, Qian Xiao2

  • 1Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas; Center for Spatial-Temporal Modeling for Applications in Population Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.

Insights

A new Chronic Disease Burden Index (CDBI) reveals high disease burdens in southern US counties, particularly in rural areas. This index helps identify vulnerable populations for targeted public health interventions and equitable healthcare access.

Area of Science:

  • Public Health
  • Epidemiology
  • Geographic Information Systems (GIS)

Background:

  • Chronic diseases are leading causes of death and disability in the U.S.
  • Existing individual-level indices do not capture population-level chronic disease burden.
  • A quantitative tool is needed to understand geographic patterns and impacts of chronic diseases for public health strategies.

Purpose of the Study:

  • To construct a county-level Chronic Disease Burden Index (CDBI).
  • To identify geographic and temporal patterns of chronic disease burden.
  • To investigate the association between CDBI and social vulnerability.

Main Methods:

  • Utilized 20 health measures from CDC's PLACES database (2018-2021).
  • Constructed annual county-level CDBIs using principal component analysis.
  • Identified geographic hotspots with Getis-Ord Gi* and assessed associations with social vulnerability using logistic regression.

Main Results:

  • High chronic disease burden clusters in the southern U.S., with persistent burden in KY and WV.
  • Increased burden observed in OH and TX.
  • Significant association between CDBI and social vulnerability index (OR=7.6); nonmetro-urban counties showed elevated CDBI (OR=14.6).

Conclusions:

  • The CDBI is an effective population-level tool for assessing chronic disease burden.
  • Identifying high-burden, vulnerable communities is essential for resource allocation.
  • This approach aids in enhancing equitable healthcare access and understanding health disparities.
Abstract

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