본문 바로가기
KERD
논문KCI 등재

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

지선하|박동혁|조원희|Lee Yong-ho|Jeon Justin Y.
한국역학회 (Korean Society of Epidemiology)|2022.01|Epidemiology and Health|제44권 |pp. 1-8|DOI 10.4178/epih.e2022009

2

조회

0

다운로드

1

인용

0

참고문헌

키워드

Resting heart rateUndiagnosed diabetesRisk score model

초록

OBJECTIVES: 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). 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), 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. RESULTS: 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. CONCLUSIONS: 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.

Abstract

OBJECTIVES: 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). 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), 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. RESULTS: 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. CONCLUSIONS: 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.

참고문헌 (46)

  1. 정찬희, "Diabetes Fact Sheets in Korea, 2020: An Appraisal of Current Status", Diabetes and Metabolism Journal, 45(1), pp.1~10 (2021), 대한당뇨병학회[DOI]
  2. "Cause of death" (2018)[URL]
  3. Shah AD, "Type 2 diabetes and incidence of cardiovascular diseases : a cohort study in 1·9 million people", Lancet Diabetes Endocrinol, 3, pp.105~113 (2015)
  4. Ergul A, "Cerebrovascular complications of diabetes : focus on stroke", Endocr Metab Immune Disord Drug Targets, 12, pp.148~158 (2012)
  5. Thiruvoipati T, "Peripheral artery disease in patients with diabetes : epidemiology, mechanisms, and outcomes", World J Diabetes, 6, pp.961~969 (2015)
  6. Cusick M, "Associations of mortality and diabetes complications in patients with type 1 and type 2 diabetes : early treatment diabetic retinopathy study report no. 27", Diabetes Care, 28, pp.617~625 (2005)
  7. Young BA, "Diabetes complications severity index and risk of mortality, hospitalization, and healthcare utilization", Am J Manag Care, 14, pp.15~23 (2008)
  8. "National diabetes statistics report" (2020)[URL]
  9. Lee YH, "Undiagnosed diabetes is prevalent in younger adults and associated with a higher risk cardiometabolic profile compared to diagnosed diabetes", Am Heart J, 170, pp.760~769 (2015)
  10. Bang H, "Development and validation of a patient self-assessment score for diabetes risk", Ann Intern Med, 151, pp.775~783 (2009)
  11. Griffin SJ, "Diabetes risk score : towards earlier detection of type 2 diabetes in general practice", Diabetes Metab Res Rev, 16, pp.164~171 (2000)
  12. Lee YH, "A simple screening score for diabetes for the Korean population : development, validation, and comparison with other scores", Diabetes Care, 35, pp.1723~1730 (2012)
  13. Carnethon MR, "Association of 20-year changes in cardiorespiratory fitness with incident type 2 diabetes : the coronary artery risk development in young adults(CARDIA)fitness study", Diabetes Care, 32, pp.1284~1288 (2009)
  14. Zaccardi F, "Cardiorespiratory fitness and risk of type 2 diabetes mellitus : a 23-year cohort study and a meta-analysis of prospective studies", Atherosclerosis, 243, pp.131~137 (2015)
  15. Zhang SY, "Overweight, resting heart rate, and prediabetes", diabetes : a population-based prospective cohort study among Inner Mongolians in China, 2016, pp.6, 23939~
  16. Shalev AY, "A prospective study of heart rate response following trauma and the subsequent development of posttraumatic stress disorder", Arch Gen Psychiatry, 55, pp.553~559 (1998)
  17. Grassi G, "Heart rate as marker of sympathetic activity", J Hypertens, 16, pp.1635~1639 (1998)
  18. Anderson EA, "Hyperinsulinemia produces both sympathetic neural activation and vasodilation in normal humans", J Clin Invest, 87, pp.2246~2252 (1991)
  19. Gonzales TI, "Resting heart rate as a biomarker for tracking change in cardiorespiratory fitness of UK adults: the Fenland Study", medRxiv (2020)[DOI]
  20. Nauman J, "A prospective population study of resting heart rate and peak oxygen uptake(the HUNT Study, Norway)", PLoS One, 7, pp.e45021~ (2012)
  21. Silva DA, "Association between resting heart rate and health-related physical fitness in Brazilian adolescents", Biomed Res Int, 2018, pp.3812197~ (2018)
  22. Emaus A, "Does a variation in self-reported physical activity reflect variation in objectively measured physical activity, resting heart rate, and physical fitness? Results from the Tromso study", Scand J Public Health, 38(5 Suppl), pp.105~118 (2010)
  23. Yang HI, "The association of resting heart rate with diabetes, hypertension, and metabolic syndrome in the Korean adult population : the fifth Korea National Health and Nutrition Examination Survey", Clin Chim Acta, 455, pp.195~200 (2016)
  24. Kim DI, "The association between resting heart rate and type 2 diabetes and hypertension in Korean adults", Heart, 102, pp.1757~1762 (2016)
  25. 박현아, "한국 성인의 안정 시 심박수와 대사증후군 및 제2형 당뇨병 유병률의 관계: 제5기 국민건강영양조사(2012년)", Journal of Obesity & Metabolic Syndrome, 24(3), pp.166~174 (2015), 대한비만학회
  26. 조원희, "한국 성인의 안정시 심박수 및 근지구력과 제2형 당뇨 유병률의 관계", 운동과학, 26(4), pp.259~266 (2017), 한국운동생리학회[DOI]
  27. Hong JW, "The association of resting heart rate with the presence of diabetes in Korean adults : the 2010-2013 Korea National Health and Nutrition Examination Survey", PLoS One, 11, pp.e0168527~ (2016)
  28. 박동혁, "한국 노인의 안정시심박수, 상대 악력 및 당뇨병 유병률의 연관성: 2015-2018 국민건강영양조사 자료를 기반으로", 운동과학, 29(4), pp.416~426 (2020), 한국운동생리학회
  29. Lee DH, "Resting heart rate and risk of type 2 diabetes : a prospective cohort study and meta-analysis", Diabetes Metab Res Rev, 35, pp.e3095~ (2019)
  30. Kim G, "Increase in resting heart rate over 2 years predicts incidence of diabetes : a 10-year prospective study", Diabetes Metab, 43, pp.25~32 (2017)
  31. Aune D, "Resting heart rate and the risk of type 2 diabetes : a systematic review and dose--response meta-analysis of cohort studies", Nutr Metab Cardiovasc Dis, 25, pp.526~534 (2015)
  32. "Examine survey guideline" (2018)[URL]
  33. Kweon S, "Data resource profile : the Korea National Health and Nutrition Examination Survey(KNHANES)", Int J Epidemiol, 43, pp.69~77 (2014)
  34. American Diabetes Association, "2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2019", Diabetes Care, 42(Suppl 1), pp.S13~S28 (2019)
  35. Perkins NJ, "The inconsistency of"optimal"cutpoints obtained using two criteria based on the receiver operating characteristic curve", Am J Epidemiol, 163, pp.670~675 (2006)
  36. Youden WJ, "Index for rating diagnostic tests", Cancer, 3, pp.32~35 (1950)
  37. Hosmer DW, "Applied logistic regression", pp.47~54 (2013), Wiley
  38. Brenner H, "Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence", Stat Med, 16, pp.981~991 (1997)
  39. Bradley AP, "The use of the area under the ROC curve in the evaluation of machine learning algorithms", Pattern Recognit, 30, pp.1145~1159 (1997)
  40. Linneberg A, "Effect of smoking on blood pressure and resting heart rate : a mendelian randomization meta-analysis in the CARTA consortium", Circ Cardiovasc Genet, 8, pp.832~841 (2015)
  41. Conrod PJ, "Biphasic effects of alcohol on heart rate are influenced by alcoholic family history and rate of alcohol ingestion", Alcohol Clin Exp Res, 21, pp.140~149 (1997)
  42. Shi Y, "Resting heart rate and the risk of hypertension and heart failure : a dose-response meta-analysis of prospective studies", J Hypertens, 36, pp.995~1004 (2018)
  43. Li YQ, "Resting heart rate as a marker for identifying the risk of undiagnosed type 2 diabetes mellitus : a cross-sectional survey", BMC Public Health, 14, pp.1052~ (2014)
  44. "Diabetes fact sheet in Korea 2016" (2018)[URL]
  45. 김헌성, "Future and Development Direction of Digital Healthcare", Healthcare Informatics Research, 27(2), pp.95~101 (2021), 대한의료정보학회
  46. Kario K, "Digital therapeutics for essential hypertension using a smartphone application: a randomized, open-label, multicenter pilot study", J Clin Hypertens(Greenwich), 23, pp.923~934 (2021)

관련 논문AI추천

한국 성인의 안정시 심박수 및 근지구력과 제2형 당뇨 유병률의 관계김동일, 민지희, 전용관, 조원희한국운동생리학회 · 운동과학2017 · 제26권 제4호안정 시 심박수와 이상지질혈증 및 당뇨병과의 관련성김맹규, 이중철, 허안식대한임상건강증진학회 · Korean Journal of Health Promotion2021 · 제21권 제4호한국 노인의 안정시심박수, 상대 악력 및 당뇨병 유병률의 연관성: 2015-2018 국민건강영양조사 자료를 기반으로박동혁, 전용관, 조원희, 홍성현한국운동생리학회 · 운동과학2020 · 제29권 제4호한국 폐경 여성의 허리둘레/신장비 및 안정시 심박수와 심혈관-대사 위험요인과의 상관성박하늬, 변지용, 전용관한국운동생리학회 · 운동과학2019 · 제28권 제1호건강예측 요인으로서의 안정시심박수의 가치와 의미박동혁, 전용관한국운동생리학회 · 운동과학2020 · 제29권 제1호Lifestyle-related predictors affecting prediabetes and diabetes in 20-30-year-old young Korean adults박경실, 황선영한국역학회 · Epidemiology and Health2020 · 제42권

이 간행물의 다른 논문 (112건)

Socioeconomic inequality in compliance with precautions and health behavior changes during the COVID-19 outbreak: an analysis of the Korean Community Health Survey 2020양재원, Kim Hyeon Chang, Jung Sun Jae, 이가빈, YANG YIYI, Hoang Thang Manhpp. 1-8Model-based cost-effectiveness analysis of oral antivirals against SARS-CoV-2 in KoreaHuh Kyungmin, Kim Sun Bean, 유진홍, 백경란, 정재훈, Jo Youngji, Radnaabaatar Munkhzul, Park Hojunpp. 1-10Predictors of COVID-19 booster vaccine hesitancy among fully vaccinated adults in Korea: a nationwide cross-sectional surveyChoe Seung-Ah, 이상원, 신주영, 김주환, 윤동원, 최영준, Noh Yunha, Jung Jaehunpp. 1-8Obesity, hypertension, diabetes mellitus, and hypercholesterolemia in Korean adults before and during the COVID-19 pandemic: a special report of the 2020 Korea National Health and Nutrition Examination SurveyKim Yoonjung, Kim Hyeon Chang, Park Suyeon, Oh Kyungwon, 이가빈pp. 1-8The Korea National Health and Nutrition Examination Survey data linked Cause of Death dataOh Kyungwon, Yun Sunghapp. 1-7
원문 보기