Regional Variation in the Incidence of Diabetes-Related Lower Limb Amputations and Its Relationship with the Regional Factors

Sung Hun Won; Jahyung Kim; Dong-Il Chun; Young Yi; Suyeon Park; Kwang-Young Jung; Gun-Hyun Park; Jaeho Cho

doi:10.14193/jkfas.2019.23.3.121

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Won, Kim, Chun, Yi, Park, Jung, Park, and Cho: Regional Variation in the Incidence of Diabetes-Related Lower Limb Amputations and Its Relationship with the Regional Factors

Original Article

Journal of Korean Foot and Ankle Society 2019; 23(3): 121-130.

Published online: 17 September 2019

DOI: https://doi.org/10.14193/jkfas.2019.23.3.121

Regional Variation in the Incidence of Diabetes-Related Lower Limb Amputations and Its Relationship with the Regional Factors

Sung Hun Won, Jahyung Kim, Dong-Il Chun, Young Yi^*, Suyeon Park^†, Kwang-Young Jung^‡, Gun-Hyun Park^§, Jaeho Cho^§

Department of Orthopedic Surgery, Soon Chun Hyang University Seoul Hospital, Korea.

^*Department of Orthopedic Surgery, Seoul Paik Hospital, Inje University College of Medicine, Korea.

^†Department of Biostatistics, Soon Chun Hyang University Seoul Hospital, Seoul, Korea.

^‡Division of Genome Research, Center for Genome Science, Korea National Institute of Health, Cheongju, Korea.

^§Department of Orthopedic Surgery, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon, Korea.

Corresponding Author: Jaeho Cho. Department of Orthopaedic Surgery, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, 77 Sakju-ro, Chuncheon 24253, Korea. Tel: 82-33-240-5198, Fax: 82-33-252-0177, hohotoy@nate.com

Received 2 August 2019 Revised 21 August 2019 Accepted 26 August 2019

Korean Foot and Ankle Society

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

To investigate the spatial distribution of diabetes-related lower limb amputations and analyze the relationship between the spatial distribution of diabetes-related lower limb amputations and regional factors.

Materials and Methods

This study was performed based on the data from the Korean Health Insurance Review and Assessment Service, in 2016. The unit of analysis was the administrative districts of city·gun·gu. The dependent variable was the age- and sex-adjusted incidence of diabetes-related lower limb amputations and the regional variables were selected to represent two aspects: socioeconomic factors, and health and medical factors. Along with traditional ordinary least square (OLS) regression analysis, geographically weighted regression (GWR) was applied for spatial analysis.

Results

The age- and sex-adjusted incidence of diabetes-related lower limb amputation varied according to region. OLS regression showed that the incidence of diabetes-related lower limb amputation had significant relationships with the health and medical factors (number of healthcare institution and doctors per 100,000 population). In GWR, the effects of regional factors were not consistent.

Conclusion

The spatial distribution of the incidence of diabetes-related lower limb amputations and the effects of regional factors varied according to the regions. The regional characteristics should be considered when establishing health policy related to diabetic foot care.

Keywords: Diabetes mellitus, Diabetic foot, Amputation, Spatial analysis

Figures and Tables

Figure 1

Summary of research model.

Figure 2

Spatial distribution in the incidence of diabetes-related lower limb amputation. (A) Standardized Incidence rate of diabetes-related lower limb amputation per 100,000 population based on city, province (n=16). (B) Standardized Incidence rate of diabetes-related lower limb amputation per 100,000 population based on city, gun, gu (n=228).

Figure 3

Distribution of regression coefficients variables based on city, gun, gu (n=228). (A) National Health Insurance premium per capita. (B) Financial independence. (C) Number of registered car per capita. (D) Number of healthcare institution per 100,000 population. (E) Number of doctors per 100,000 population.

Table 1

Amputation Rate by Age, Sex, Region

Table 2

Descriptive Statistics of Independent Variables (n=228)

SD: standard deviation.

Table 3

Results of Pearson's Correlation and Multicollinearity Analysis

NHI: National Health Insurance.

Table 4

Results of Ordinary Least Square

NHI: National Health Insurance.

Table 5

Results of Geographically Weighted Regression

Values are presented as mean±SD (range) or mean only.

SD: standard deviation, NHI: National Health Insurance.

Notes

^{Financial support} This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. M20181113437).

^{Conflict of interest} None.

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ORCID iDs: Jaeho Cho
https://orcid.org/0000-0001-8680-4680
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