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Epidemiol Health > Volume 44; 2022 > Article
Epidemiology and Health 2022;44: e2022009-0.
DOI: https://doi.org/10.4178/epih.e2022009    Published online Jan 3, 2022.
The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
Dong-Hyuk Park1  , Wonhee Cho1  , Yong-Ho Lee2  , Sun Ha Jee3,4  , Justin Y. Jeon1,3 
1Department of Sports Industry, Yonsei University, Seoul, Korea
2Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
3Exercise Medicine Center for Diabetes and Cancer Patients, Institute of Convergence of Science (ICONS), Yousei university, 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
The purpose of this study was (1) to examine whether the addition of resting heart rate (RHR) to the existing undiagnosed diabetes mellitus (UnDM) prediction model would improve predictability, and (2) to develop and validate UnDM prediction models by using only easily assessable variables such as gender, RHR, age, and waist circumference (WC).
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), while the 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 ≥126 mg/dL or glycated hemoglobin ≥6.5%; however, doctors have not diagnosed it. Statistical package for the social sciences logistic regression analysis was used to determine the predictors of UnDM.
RHR, age, and WC were associated with UnDM. When RHR was added to the existing model, sensitivity was reduced (86 vs. 73%), specificity was increased (49 vs. 65%), and a higher Youden index (35 vs. 38) was expressed. When only gender, RHR, age, and WC were used in the model, a sensitivity, specificity, and Youden index of 70%, 67%, and 37, respectively, were observed.
Adding RHR to the existing UnDM prediction model improved specificity and the Youden index. Furthermore, when the prediction model only used gender, RHR, age, and WC, the outcomes were not inferior to those of the existing prediction model.
Keywords: Resting heart rate, Undiagnosed diabetes, Risk score model, Korean National Health and Nutrition Examination Survey


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