Higher Resting Heart Rate and Lower Relative Grip Strength is Associated with Increased Risk of Diabetes in Korean Elderly Population: Korean National Health and Nutrition Examination Survey 2015-2018

Park, Dong Hyuk; Hong, Sung Hwan; Cho, Wonhee; Jeon, Justin Y

doi:10.15857/ksep.2020.29.4.416

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…Medical diagnosis using physiological information is one of the oldest and most popular diagnostic methods. For example, the time-series characteristics of heart rate are closely related to the prevalence of several diseases such as metabolic syndrome, diabetes, hypertension, and myocardial infarction 11 . Li et al 12 presented a Lyme disease prediction system that measures physiological indicators, such as abnormal blood oxygen concentration, heart rate, and skin, based on physiological data sampled over 250,000 a day through smartwatches from 43 people.…”

Section: Related Workmentioning

confidence: 99%

Machine learning-based optimization of pre-symptomatic COVID-19 detection through smartwatch

Cho

Kim

Yoon

et al. 2022

Sci Rep

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Patients with weak or no symptoms accelerate the spread of COVID-19 through various mutations and require more aggressive and active means of validating the COVID-19 infection. More than 30% of patients are reported as asymptomatic infection after the delta mutation spread in Korea. It means that there is a need for a means to more actively and accurately validate the infection of the epidemic via pre-symptomatic detection, besides confirming the infection via the symptoms. Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) reported that physiological data collected from smartwatches could be an indicator to suspect COVID-19 infection. It shows that it is possible to identify an abnormal state suspected of COVID-19 by applying an anomaly detection method for the smartwatch’s physiological data and identifying the subject’s abnormal state to be observed. This paper proposes to apply the One Class-Support Vector Machine (OC-SVM) for pre-symptomatic COVID-19 detection. We show that OC-SVM can provide better performance than the Mahalanobis distance-based method used by Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) in three aspects: earlier (23.5–40% earlier) and more detection (13.2–19.1% relative better) and fewer false positives. As a result, we could conclude that OC-SVM using Resting Heart Rate (RHR) with 350 and 300 moving average size is the most recommended technique for COVID-19 pre-symptomatic detection based on physiological data from the smartwatch.

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Section: Related Workmentioning

confidence: 99%

Machine learning-based optimization of pre-symptomatic COVID-19 detection through smartwatch

Cho

Kim

Yoon

et al. 2022

Sci Rep

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“…반면에, 안정시 심박수 (Resting Heart Rate, RHR)는 누구나 특별한 장비 없이도 손쉽게 측정이 가능 하며 비만도 [14], 스트레스 [15], 교감신경 [16], 인슐린 [17], 최대산소섭취량 [18,19], 체 력 [20], 고강도 신체활동량 [21]과 높은 상관관계가 있음을 고려할 때에, 미진단 당뇨병 위 험 예측 모형에 사용할 수 있는 변인이다. 지금까지 많은 연구에서 높은 RHR은 당뇨병 유병 률 [22][23][24][25][26][27]과 발병 위험 [28][29][30]과 관련이 있다고 규명하였다 [31]. 델 타당도를 분석하였다 (Figure 1).…”

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“…Thus, RHR is a variable that could be used in risk prediction models for undiagnosed diabetes. In fact, a number of studies have demonstrated that high RHR is associated with the prevalence [ 23 - 28 ] and incidence of diabetes [ 29 - 31 ].…”

Section: Introductionmentioning

confidence: 99%

The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey

et al. 2022

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Relationship Between Handgrip Strength and the Prevalence of Diabetes Mellitus Among Korean Adults: Korean National Health and Nutrition Examination Survey, 2014-2018

Hong¹,

Byeon²,

Ji³

et al. 2021

Exerc Sci

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PURPOSE: The study aimed to examine whether handgrip strength (HGS) expressed as absolute or relative to body weight is associated with fasting glucose (FG), hemoglobin A1c (HbA1c) and the prevalence of diabetes mellitus (DM) in different age categories.METHODS:A total of 28,129 adults from the Korea National Health and Nutrition Examination Survey of 2014-2018 was analyzed. To examine the relationship between HGS and variables related to DM, participants were categorized into three groups according to their HGS (Tertile). Then, participants were further categorized into six groups according to their age. One-way ANOVA and logistic regression analyses were performed.RESULTS: Compared with participants in the upper tertile of absolute handgrip strength (AHGS), those in the lower tertile were older, shorter and heavier and also had higher FG and HbA1c. When age was adjusted, the prevalence of DM was 1.19 times (95% CI: 1.03-1.38) higher among men in the lowest tertile of AHGS. On the other hand, compared with participants in the highest tertile of relative handgrip strength (RHGS), those in the lowest tertile had 2.10 times (95% CI: 1.87-2.41) and 2.42 times (95% CI: 2.08-2.81) higher prevalence of DM in men and women, respectively. When the associations were examined according to age subcategories, significant associations between AHGS and the prevalence of DM were seen only in men in their 50s and 60s, but not seen in women in all age groups, with the exception of the 60s. However, significant associations between RHGS and the prevalence of DM were seen in all age subcategories.CONCLUSIONS:We concluded that the association between HGS and the prevalence of DM was dependent on age and RHGS is a stonger measure than AHGS.

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Higher Resting Heart Rate and Lower Relative Grip Strength is Associated with Increased Risk of Diabetes in Korean Elderly Population: Korean National Health and Nutrition Examination Survey 2015-2018

Cited by 4 publications

References 35 publications

Machine learning-based optimization of pre-symptomatic COVID-19 detection through smartwatch

Machine learning-based optimization of pre-symptomatic COVID-19 detection through smartwatch

The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey

Relationship Between Handgrip Strength and the Prevalence of Diabetes Mellitus Among Korean Adults: Korean National Health and Nutrition Examination Survey, 2014-2018

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