title: Resting heart rate as a marker for identifying the risk of undiagnosed type 2 diabetes mellitus: a cross-sectional survey.
abstract: BACKGROUND
  Fast resting heart rate might increase the risk of developing type 2 diabetes mellitus (T2DM). However, it is unclear whether resting heart rate could be used to predict the risk of undiagnosed T2DM. Therefore, the purposes of this study were to examine the association between resting heart rate and undiagnosed T2DM, and evaluate the feasibility of using resting heart rate as a marker for identifying the risk of undiagnosed T2DM.
  
  
  METHODS
  A cross-sectional survey was conducted. Resting heart rate and relevant covariates were collected and measured. Fasting blood samples were obtained to measure blood glucose using the modified hexokinase enzymatic method. Predictive performance was analyzed by Receiver Operating Characteristic (ROC) curve.
  
  
  RESULTS
  This study included 16, 636 subjects from rural communities aged 35-78 years. Resting heart rate was significantly associated with undiagnosed T2DM in both genders. For resting heart rate categories of <60, 60-69, 70-79, and ≥80 beats/min, adjusted odds ratios for undiagnosed T2DM were 1.04, 2.32, 3.66 and 1.05, 1.57, 2.98 in male and female subjects, respectively. For male subjects, resting heart rate ≥70 beats/min could predict undiagnosed T2DM with 76.56% sensitivity and 48.64% specificity. For female subjects, the optimum cut-off point was ≥79 beats/min with 49.72% sensitivity and 67.53% specificity. The area under the ROC curve for predicting undiagnosed T2DM was 0.65 (95% CI: 0.64-0.66) and 0.61(95% CI: 0.60-0.62) in male and female subjects, respectively.
  
  
  CONCLUSIONS
  Fast resting heart rate is associated with an increased risk of undiagnosed T2DM in male and female subjects. However, resting heart rate as a marker has limited potential for screening those at high risk of undiagnosed T2DM in adults living in rural areas.
authors.forename: Yu-qian
authors.initials: YQ
authors.lastname: Li
authors.forename: Chang-qing
authors.initials: CQ
authors.lastname: Sun
authors.forename: Lin-lin
authors.initials: LL
authors.lastname: Li
authors.forename: Ling
authors.initials: L
authors.lastname: Wang
authors.forename: Yi-rui
authors.initials: YR
authors.lastname: Guo
authors.forename: Ai-guo
authors.initials: AG
authors.lastname: You
authors.forename: Yuan-lin
authors.initials: YL
authors.lastname: Xi
authors.affiliation: Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, PR China. tjwcj2005@126.com.
authors.forename: Chong-jian
authors.initials: CJ
authors.lastname: Wang
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015415:Biomarkers; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000503:physiopathology; D005215:Fasting; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D016017:Odds Ratio; D012372:ROC Curve; D012016:Reference Values; D012306:Risk; D012424:Rural Population; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers; D001786:Blood Glucose