Literature DB >> 29618016

Short-Term Repeatability of Insulin Resistance Indexes in Older Adults: The Atherosclerosis Risk in Communities Study.

Anna K Poon1, Michelle L Meyer1,2, Gerald Reaven3, Joshua W Knowles3, Elizabeth Selvin4, James S Pankow5, David Couper1, Laura Loehr1, Gerardo Heiss1.   

Abstract

Context: The homeostatic model assessment of insulin resistance (HOMA-IR) and triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) are insulin resistance indexes routinely used in clinical and population-based studies; however, their short-term repeatability is not well characterized. Objective: To quantify the short-term repeatability of insulin resistance indexes and their analytes, consisting of fasting glucose and insulin for HOMA-IR and TG and HDL-C for TG/HDL-C. Design: Prospective cohort study. Participants: A total of 102 adults 68 to 88 years old without diabetes attended an initial examination and repeated examination (mean, 46 days; range, 28 to 102 days). Blood samples were collected, processed, shipped, and assayed following a standardized protocol. Main Outcome Measures: Repeatability was quantified using the intraclass correlation coefficient (ICC) and within-person coefficient of variation (CV). Minimum detectable change (MDC95) and minimum detectable difference with 95% confidence (MDD95) were quantified.
Results: For HOMA-IR, insulin, and fasting glucose, the ICCs were 0.70, 0.68, and 0.70, respectively; their respective within-person CVs were 30.4%, 28.8%, and 5.6%. For TG/HDL-C, TG, and HDL-C, the ICCs were 0.80, 0.68, and 0.91, respectively; their respective within-person CVs were 23.0%, 20.6%, and 8.2%. The MDC95 was 2.3 for HOMA-IR and 1.4 for TG/HDL-C. The MDD95 for a sample of n = 100 was 0.8 for HOMA-IR and 0.6 for TG/HDL-C. Conclusions: Short-term repeatability was fair to good for HOMA-IR and excellent for TG/HDL-C according to suggested benchmarks, reflecting the short-term variability of their analytes. These measurement properties can inform the use of these indexes in clinical and population-based studies.

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Year:  2018        PMID: 29618016      PMCID: PMC6276677          DOI: 10.1210/jc.2017-02437

Source DB:  PubMed          Journal:  J Clin Endocrinol Metab        ISSN: 0021-972X            Impact factor:   5.958


  19 in total

1.  Short-term intraindividual variability in lipoprotein measurements: the Atherosclerosis Risk in Communities (ARIC) Study.

Authors:  L E Chambless; R P McMahon; S A Brown; W Patsch; G Heiss; Y L Shen
Journal:  Am J Epidemiol       Date:  1992-11-01       Impact factor: 4.897

Review 2.  Use and abuse of HOMA modeling.

Authors:  Tara M Wallace; Jonathan C Levy; David R Matthews
Journal:  Diabetes Care       Date:  2004-06       Impact factor: 19.112

3.  Estimate of biological variation of laboratory analytes based on the third national health and nutrition examination survey.

Authors:  David A Lacher; Jeffery P Hughes; Margaret D Carroll
Journal:  Clin Chem       Date:  2004-12-08       Impact factor: 8.327

4.  Correct homeostasis model assessment (HOMA) evaluation uses the computer program.

Authors:  J C Levy; D R Matthews; M P Hermans
Journal:  Diabetes Care       Date:  1998-12       Impact factor: 19.112

5.  Adjustment for regression dilution in epidemiological regression analyses.

Authors:  M W Knuiman; M L Divitini; J S Buzas; P E Fitzgerald
Journal:  Ann Epidemiol       Date:  1998-01       Impact factor: 3.797

6.  Statistical methodology for the concurrent assessment of interrater and intrarater reliability: using goniometric measurements as an example.

Authors:  M Eliasziw; S L Young; M G Woodbury; K Fryday-Field
Journal:  Phys Ther       Date:  1994-08

Review 7.  Overproduction of very low-density lipoproteins is the hallmark of the dyslipidemia in the metabolic syndrome.

Authors:  Martin Adiels; Sven-Olof Olofsson; Marja-Riitta Taskinen; Jan Borén
Journal:  Arterioscler Thromb Vasc Biol       Date:  2008-07       Impact factor: 8.311

8.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators.

Authors: 
Journal:  Am J Epidemiol       Date:  1989-04       Impact factor: 4.897

9.  Use of metabolic markers to identify overweight individuals who are insulin resistant.

Authors:  Tracey McLaughlin; Fahim Abbasi; Karen Cheal; James Chu; Cindy Lamendola; Gerald Reaven
Journal:  Ann Intern Med       Date:  2003-11-18       Impact factor: 25.391

10.  Insulin assay standardization: leading to measures of insulin sensitivity and secretion for practical clinical care.

Authors:  Myrlene A Staten; Michael P Stern; W Greg Miller; Michael W Steffes; Scott E Campbell
Journal:  Diabetes Care       Date:  2010-01       Impact factor: 19.112

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  2 in total

1.  Association of insulin resistance, from mid-life to late-life, with aortic stiffness in late-life: the Atherosclerosis Risk in Communities Study.

Authors:  Anna K Poon; Michelle L Meyer; Hirofumi Tanaka; Elizabeth Selvin; James Pankow; Donglin Zeng; Laura Loehr; Joshua W Knowles; Wayne Rosamond; Gerardo Heiss
Journal:  Cardiovasc Diabetol       Date:  2020-01-28       Impact factor: 9.951

2.  Insulin resistance and reduced cardiac autonomic function in older adults: the Atherosclerosis Risk in Communities study.

Authors:  Anna K Poon; Eric A Whitsel; Gerardo Heiss; Elsayed Z Soliman; Lynne E Wagenknecht; Takeki Suzuki; Laura Loehr
Journal:  BMC Cardiovasc Disord       Date:  2020-05-11       Impact factor: 2.298

  2 in total

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