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Epidemiol Health > Accepted Articles
Epidemiology and Health 2022;e2022009.
DOI: https://doi.org/10.4178/epih.e2022009    [Accepted] Published online Jan 3, 2022.
The predicting value of resting heart rate to identify undiagnosed diabetes in Korean adult: Korea National Health and Nutrition Examination Survey
Dong-Hyuk Park1,2  , Wonhee Cho1  , Yong-ho Lee3  , Sun Ha Jee4  , Justin Y Jeon1,2 
1Department of Sports industry, Yonsei University, Seoul , Korea
2Exercise Medicine Center for Diabetes and Cancer Patients, ICONS, Seoul, Korea
3Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
4Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
Correspondence  Justin Y Jeon ,Email: jjeon@yonsei.ac.kr
Received: Oct 1, 2021  Accepted after revision: Dec 27, 2021
Abstract
OBJECTIVES:
The purpose of the current study is to examine 1) whether the addition of resting heart rate (RHR) to existing undiagnosed diabetes (UnDM) prediction model would improve predictability, 2) to develop and validate UnDM prediction model by only using easily assessable variables such as age, gender, RHR and waist circumference (WC).
METHODS:
Korea National Health and Nutrition Examination Survey (KNHANES) 2010, 2012, 2014, 2016 data were used to develop the model (model building set, N=19,675) and KNHANES data from 2011, 2013, 2015, 2017 were used to validate the model (validation set, N=19,917). UnDM was defined as a fasting glucose level ≥ 126mg/dL or hemoglobin A1c ≥6.5%, yet has not been diagnosed by doctors. SPSS logistic regression analysis was used to determine predictors of UnDM.
RESULTS:
Age, RHR, waist circumference (WC) were associated with UnDM. When RHR was added to the existing model, sensitivity was reduced (86% vs. 73%) while specificity was increased (49% vs. 65%), expressed as higher Youden index (35 vs. 38). When only age, sex, WC and RHR were used in the model, sensitivity of 70%, and specificity of 67% with Youden index of 37 were observed.
CONCLUSIONS:
Adding RHR to existing UnDM prediction model improved specificity and Youden index. Furthermore, prediction model only used age, sex, RHR and WC were not inferior to existing prediction model.
Keywords: Resting heart rate; Undiagnosed diabetes; Risk score model; Korea National Health and Nuturition Examination


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