Abstract

Geographical variations and influential factors of disease prevalence are crucial information enabling optimal allocation of limited medical resources and prioritization of appropriate treatments for each regional unit. The purpose of this study was to explore the geographical variations and influential factors of cardiometabolic disease prevalence with respect to 230 administrative districts in South Korea. Global Moran’s I was calculated to determine whether the standardized prevalences of cardiometabolic diseases (hypertension, stroke, and diabetes mellitus) were spatially clustered. The CART algorithm was then applied to generate decision tree models that could extract the diseases’ regional influential factors from among 101 demographic, economic, and public health data variables. Finally, the accuracies of the resulting model–hypertension (67.4%), stroke (62.2%), and diabetes mellitus (56.5%)–were assessed by ten-fold cross-validation. Marriage rate was the main determinant of geographic variation in hypertension and stroke prevalence, which has the possibility that married life could have positive effects in lowering disease risks. Additionally, stress-related variables were extracted as factors positively associated with hypertension and stroke. In the opposite way, the wealth status of a region was found to have an influence on the prevalences of stroke and diabetes mellitus. This study suggested a framework for provision of novel insights into the regional characteristics of diseases and the corresponding influential factors. The results of the study are anticipated to provide valuable information for public health practitioners’ cost-effective disease management and to facilitate primary intervention and mitigation efforts in response to regional disease outbreaks.

Highlights

  • The geographical variations and influential factors of diseases have been intensively studied in recent years [1,2,3,4,5,6,7,8,9,10,11,12]

  • The target area of this study comprises 230 administrative districts in South Korea that cover a total area of 99,720 km2 (Fig 1)

  • Low prevalence is clustered in Seoul capital area and in southeastern coastal area, while high prevalence is clustered across central area

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Summary

Introduction

The geographical variations and influential factors of diseases have been intensively studied in recent years [1,2,3,4,5,6,7,8,9,10,11,12]. MOLIT (The Ministry of Land, Infrastructure and Transport), Korea, under the national spatial information research program supervised by the KAIA (Korea Agency for Infrastructure Technology Advancement)"(18NSIP-B081011-05).

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