title: Optimal Cut-Offs of Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) to Identify Dysglycemia and Type 2 Diabetes Mellitus: A 15-Year Prospective Study in Chinese.
abstract: BACKGROUND
  The optimal reference range of homeostasis model assessment of insulin resistance (HOMA-IR) in normal Chinese population has not been clearly defined. Here we address this issue using the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS), a prospective population-based cohort study with long-term follow-up.
  
  
  METHODS
  In this study, normal glucose tolerance (NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM) were defined according to the 1998 World Health Organization criteria. Dysglycemia referred to IFG, IGT or T2DM. This study comprised two parts. Part one was a cross-sectional study involving 2,649 Hong Kong Chinese subjects, aged 25-74 years, at baseline CRISPS-1 (1995-1996). The optimal HOMA-IR cut-offs for dysglycemia and T2DM were determined by the receiver-operating characteristic (ROC) curve. Part two was a prospective study involving 872 subjects who had persistent NGT at CRISPS-4 (2010-2012) after 15 years of follow-up.
  
  
  RESULTS
  At baseline, the optimal HOMA-IR cut-offs to identify dysglyceia and T2DM were 1.37 (AUC = 0.735; 95% confidence interval [CI] = 0.713-0.758; Sensitivity [Se] = 65.6%, Specificity [Sp] = 71.3%] and 1.97 (AUC = 0.807; 95% CI = 0.777-0.886; Se = 65.5%, Sp = 82.9%) respectively. These cut-offs, derived from the cross-sectional study at baseline, corresponded closely to the 75th (1.44) and 90th (2.03) percentiles, respectively, of the HOMA-IR reference range derived from the prospective study of subjects with persistent NGT.
  
  
  CONCLUSIONS
  HOMA-IR cut-offs, of 1.4 and 2.0, which discriminated dysglycemia and T2DM respectively from NGT in Southern Chinese, can be usefully employed as references in clinical research involving the assessment of insulin resistance.
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.|Research Center of Heart, Brain, Hormone and Healthy Aging, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: C H
authors.initials: CH
authors.lastname: Lee
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: A Z L
authors.initials: AZ
authors.lastname: Shih
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: Y C
authors.initials: YC
authors.lastname: Woo
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: C H Y
authors.initials: CH
authors.lastname: Fong
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: O Y
authors.initials: OY
authors.lastname: Leung
authors.affiliation: Department of Medicine, University of Melbourne and Western Health, Melbourne, Victoria, Australia.
authors.forename: E
authors.initials: E
authors.lastname: Janus
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.|Research Center of Heart, Brain, Hormone and Healthy Aging, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: B M Y
authors.initials: BM
authors.lastname: Cheung
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong S.A.R., China.|Research Center of Heart, Brain, Hormone and Healthy Aging, The University of Hong Kong, Hong Kong S.A.R., China.|State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong S.A.R., China.
authors.forename: K S L
authors.initials: KS
authors.lastname: Lam