Diagnosing Insulin Resistance in the General Population
Diagnosing Insulin Resistance in the General Population Kirsten A. McAuley , MBCHB 1 , Sheila M. Williams , BSC(HONS) 2 , Jim I. Mann , DM, PHD, FRACP 1 , Robert J. Walker , MD, FRACP 3 , Nick J. Lewis-Barned , FRACP 4 , Lara A. Temple , BSC 1 and Ashley W. Duncan , BSC, NZCS 1 1 Department of Human...
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Published in | Diabetes care Vol. 24; no. 3; pp. 460 - 464 |
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Main Authors | , , , , , , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Alexandria, VA
American Diabetes Association
01.03.2001
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Subjects | |
Online Access | Get full text |
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Abstract | Diagnosing Insulin Resistance in the General Population
Kirsten A. McAuley , MBCHB 1 ,
Sheila M. Williams , BSC(HONS) 2 ,
Jim I. Mann , DM, PHD, FRACP 1 ,
Robert J. Walker , MD, FRACP 3 ,
Nick J. Lewis-Barned , FRACP 4 ,
Lara A. Temple , BSC 1 and
Ashley W. Duncan , BSC, NZCS 1
1 Department of Human Nutrition
2 Department of Preventive and Social Medicine, and
3 Department of Medicine, Otago University, Dunedin, New Zealand
4 Department of Diabetes and Endocrinology, Gloucestershire Royal Hospital, Gloucester, U.K.
Abstract
OBJECTIVE —Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general
population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett
index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin
clamp to determine the most appropriate method for assessing insulin resistance in the general population.
RESEARCH DESIGN AND METHODS —Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes,
and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged
25–68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements
of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for
individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI.
RESULTS —Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar
in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use
of a score based on
rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting
insulin sensitivity.
CONCLUSIONS —A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple
means of screening for insulin resistance in the general population.
AST, aspartate aminotransferase
BP, blood pressure
HOMA, homeostasis model assessment
IGT, impaired glucose tolerance
ISI, insulin sensitivity index
IVGTT, intravenous glucose tolerance test
M, glucose disposal rate
Mbw/I, ISI corrected for total body weight divided by average insulin
Mffm/I, ISI corrected for fat-free mass divided by average insulin
PSEP, prognostic separation index
TAG, triglycerides
WHR, waist-to-hip ratio
Footnotes
Address correspondence and reprint requests to Dr. Kirsten McAuley, Department of Human Nutrition, Otago University, P.O.
Box 56, Dunedin, New Zealand. E-mail: kirsten.mcauley{at}stonebow.otago.ac.nz .
Received for publication 25 July 2000 and accepted in revised form 9 November 2000.
N.J.L.-B. has received grants from the National Heart Foundation of New Zealand and the Laurensen Trust (Otago Medical Foundation).
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. |
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AbstractList | Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population. Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25-68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI. Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on Mffm/I = exp[2.63 - 0.28ln(insulin) - 0.31ln(TAG)] rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity. A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population. Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population. Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25-68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI. Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on Mffm/I = exp[2.63 - 0.28ln(insulin) - 0.31ln(TAG)] rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity. A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population. Diagnosing Insulin Resistance in the General Population Kirsten A. McAuley , MBCHB 1 , Sheila M. Williams , BSC(HONS) 2 , Jim I. Mann , DM, PHD, FRACP 1 , Robert J. Walker , MD, FRACP 3 , Nick J. Lewis-Barned , FRACP 4 , Lara A. Temple , BSC 1 and Ashley W. Duncan , BSC, NZCS 1 1 Department of Human Nutrition 2 Department of Preventive and Social Medicine, and 3 Department of Medicine, Otago University, Dunedin, New Zealand 4 Department of Diabetes and Endocrinology, Gloucestershire Royal Hospital, Gloucester, U.K. Abstract OBJECTIVE —Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population. RESEARCH DESIGN AND METHODS —Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25–68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI. RESULTS —Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity. CONCLUSIONS —A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population. AST, aspartate aminotransferase BP, blood pressure HOMA, homeostasis model assessment IGT, impaired glucose tolerance ISI, insulin sensitivity index IVGTT, intravenous glucose tolerance test M, glucose disposal rate Mbw/I, ISI corrected for total body weight divided by average insulin Mffm/I, ISI corrected for fat-free mass divided by average insulin PSEP, prognostic separation index TAG, triglycerides WHR, waist-to-hip ratio Footnotes Address correspondence and reprint requests to Dr. Kirsten McAuley, Department of Human Nutrition, Otago University, P.O. Box 56, Dunedin, New Zealand. E-mail: kirsten.mcauley{at}stonebow.otago.ac.nz . Received for publication 25 July 2000 and accepted in revised form 9 November 2000. N.J.L.-B. has received grants from the National Heart Foundation of New Zealand and the Laurensen Trust (Otago Medical Foundation). A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population.OBJECTIVEDifficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population.Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25-68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI.RESEARCH DESIGN AND METHODSFamily history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25-68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI.Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on Mffm/I = exp[2.63 - 0.28ln(insulin) - 0.31ln(TAG)] rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity.RESULTSCorrelation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on Mffm/I = exp[2.63 - 0.28ln(insulin) - 0.31ln(TAG)] rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity.A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population.CONCLUSIONSA weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population. OBJECTIVE—Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared fasting insulin, homeostasis model assessment (HOMA), insulin-to-glucose ratio, Bennett index, and a score based on weighted combinations of fasting insulin, BMI, and fasting triglycerides with the euglycemic insulin clamp to determine the most appropriate method for assessing insulin resistance in the general population. RESEARCH DESIGN AND METHODS—Family history of diabetes, BMI, blood pressure, waist and hip circumference, fasting lipids, glucose, insulin, liver enzymes, and insulin sensitivity index (ISI) using the euglycemic insulin clamp were obtained for 178 normoglycemic individuals aged 25–68 years. Product-moment correlations were used to examine the association between ISI and various surrogate measurements of insulin sensitivity. Regression models were used to devise weights for each variable and to identify cutoff points for individual components of the score. A bootstrap procedure was used to identify the most useful predictors of ISI. RESULTS—Correlation coefficients between ISI and fasting insulin, HOMA, insulin-to-glucose ratio, and the Bennett index were similar in magnitude. The variables that best predicted insulin sensitivity were fasting insulin and fasting triglycerides. The use of a score based on \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \[Mffm{/}I{\,}{\,}{=}{\,}{\,}exp{[}2.63{\,}{\,}{-}{\,}{\,}0.28ln(insulin){\,}{\,}{-}{\,}{\,}0.31ln(TAG){]}\] \end{document}rather than the use of fasting insulin alone resulted in a higher sensitivity and a maintained specificity when predicting insulin sensitivity. CONCLUSIONS—A weighted combination of two routine laboratory measurements, i.e., fasting insulin and triglycerides, provides a simple means of screening for insulin resistance in the general population. |
Audience | Professional |
Author | Robert J. Walker Lara A. Temple Ashley W. Duncan Kirsten A. McAuley Nick J. Lewis-Barned Sheila M. Williams Jim I. Mann |
Author_xml | – sequence: 1 givenname: Kirsten A. surname: McAuley fullname: McAuley, Kirsten A. organization: Department of Human Nutrition – sequence: 2 givenname: Sheila M. surname: Williams fullname: Williams, Sheila M. organization: Department of Preventive and Social Medicine, and – sequence: 3 givenname: Jim I. surname: Mann fullname: Mann, Jim I. organization: Department of Human Nutrition – sequence: 4 givenname: Robert J. surname: Walker fullname: Walker, Robert J. organization: Department of Medicine, Otago University, Dunedin, New Zealand – sequence: 5 givenname: Nick J. surname: Lewis-Barned fullname: Lewis-Barned, Nick J. organization: Department of Diabetes and Endocrinology, Gloucestershire Royal Hospital, Gloucester, U.K – sequence: 6 givenname: Lara A. surname: Temple fullname: Temple, Lara A. organization: Department of Human Nutrition – sequence: 7 givenname: Ashley W. surname: Duncan fullname: Duncan, Ashley W. organization: Department of Human Nutrition |
BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=951975$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/11289468$$D View this record in MEDLINE/PubMed |
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Keywords | Endocrinopathy Human Protein hormone Body mass index Target tissue resistance Pancreatic hormone Glucose clamp technique Clinical biology Diagnosis Non insulin dependent diabetes Insulin Glycemia |
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Snippet | Diagnosing Insulin Resistance in the General Population
Kirsten A. McAuley , MBCHB 1 ,
Sheila M. Williams , BSC(HONS) 2 ,
Jim I. Mann , DM, PHD, FRACP 1 ,... OBJECTIVE—Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we... Difficulties in measuring insulin sensitivity prevent the identification of insulin-resistant individuals in the general population. Therefore, we compared... |
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SubjectTerms | Adult Aged Biological and medical sciences Blood Glucose - metabolism Blood pressure Body Constitution Body Mass Index Clinical medicine Diabetes Diabetes. Impaired glucose tolerance Diagnosis Endocrine pancreas. Apud cells (diseases) Endocrinopathies Enzymes Female Glucose Glucose Clamp Technique Homeostasis Humans Infusions, Intravenous Insulin - administration & dosage Insulin - blood Insulin - pharmacology Insulin Resistance Male Management. Various non-drug treatments. Langerhans islet grafts Medical sciences Middle Aged Plasma Research design Risk Factors Triglycerides Triglycerides - blood Variables |
Title | Diagnosing Insulin Resistance in the General Population |
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