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Article: 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

TitleOptimal 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
Authors
Issue Date2016
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
PLoS One, 2016, v. 11 n. 9, p. e0163424:1-11 How to Cite?
AbstractBACKGROUND: 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. MATERIAL & 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.
Persistent Identifierhttp://hdl.handle.net/10722/240929
ISSN
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.839
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLee, CHP-
dc.contributor.authorShih, AZL-
dc.contributor.authorWoo, YC-
dc.contributor.authorFong, HY-
dc.contributor.authorLeung, OY-
dc.contributor.authorJanus, ED-
dc.contributor.authorCheung, BMY-
dc.contributor.authorLam, KSL-
dc.date.accessioned2017-05-22T09:19:38Z-
dc.date.available2017-05-22T09:19:38Z-
dc.date.issued2016-
dc.identifier.citationPLoS One, 2016, v. 11 n. 9, p. e0163424:1-11-
dc.identifier.issn1932-6203-
dc.identifier.urihttp://hdl.handle.net/10722/240929-
dc.description.abstractBACKGROUND: 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. MATERIAL & 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.-
dc.languageeng-
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action-
dc.relation.ispartofPLoS ONE-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleOptimal 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-
dc.typeArticle-
dc.identifier.emailLee, CHP: pchlee@hku.hk-
dc.identifier.emailShih, AZL: ashih@hku.hk-
dc.identifier.emailWoo, YC: wooyucho@hku.hk-
dc.identifier.emailFong, HY: kalofong@hku.hk-
dc.identifier.emailLeung, OY: yiu222@hku.hk-
dc.identifier.emailCheung, BMY: mycheung@hku.hk-
dc.identifier.emailLam, KSL: ksllam@hku.hk-
dc.identifier.authorityLee, CHP=rp02043-
dc.identifier.authorityCheung, BMY=rp01321-
dc.identifier.authorityLam, KSL=rp00343-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0163424-
dc.identifier.scopuseid_2-s2.0-84992197914-
dc.identifier.hkuros272171-
dc.identifier.volume11-
dc.identifier.issue9-
dc.identifier.spagee0163424:1-
dc.identifier.epage11-
dc.identifier.isiWOS:000383893200119-
dc.publisher.placeUnited States-
dc.identifier.issnl1932-6203-

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