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Estimating the disease burden of Korean type 2 diabetes mellitus patients considering its complications

Authors
Kim, JuyoungYoon, Seok-JunJo, Min-Woo
Issue Date
8-2월-2021
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, v.16, no.2
Indexed
SCIE
SCOPUS
Journal Title
PLOS ONE
Volume
16
Number
2
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/49596
DOI
10.1371/journal.pone.0246635
ISSN
1932-6203
Abstract
Background The burden of diabetes is considerable not only globally but also nationally within Korea. The Global Burden of Disease study derived the disability-adjusted life years (DALYs) of diabetes depending on its complications as individual severity using prevalence-based approach from 2017. Conversely, the Korean National Burden of Disease study based on an incidence-based approach does not incorporate the severity of diseases. This study aimed to simulate incidence-based DALYs of type 2 diabetes mellitus (T2DM), given diabetic complications as disease severity using a Markov model. Methods We developed a model with six Markov states, including incident and existing prevalent cases of diabetes and its complications and death. We assumed that diabetes and its complications would not be cured. The cycle length was one year, and the endpoint of the simulation was 100 years. A 5% discount rate was adopted in the analysis. Transition cases were counted by 5-year age groups above 30 years of age. Age- and sex-specific transition probabilities were calculated based on the incident rate. Results The total DALY estimates of T2DM were 5,417 and 3,934 per 100,000 population in men and women, respectively. The years of life lost in men were relatively higher than those in women in most age groups except the 80-84 age group. The distribution of years lived with disability by gender and age group showed a bell shape, peaking in the 55-59 age group in men and 65-69 age group in women. Conclusions The burden of T2DM considering its complications was larger compared to the outcomes from previous studies, with more precise morbid duration using the Markov model.
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