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Cited by 229Diabetes, Cardiovascular Risks, and LipoproteinsDiet, Metabolism, and DiseaseAdipokines, Inflammation, and Metabolic Diseases

The DOI matches its Crossref record, with a small difference in title or year; 37 of the 37 references it cites were found in a registry or an index.

Factor Analysis of Metabolic Syndrome Using Directly Measured Insulin Sensitivity

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Hanley, Anthony J.G., Karter, Andrew J., Festa, Andreas, D’Agostino, Ralph, Wagenknecht, Lynne E., Savage, Peter, Tracy, Russell P., Saad, Mohammed F., Haffner, Steven·2002·Diabetes
DOI 10.2337/diabetes.51.8.2642
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Abstract

Factor analysis, a multivariate correlation technique, has been used to provide insight into the underlying structure of metabolic syndrome, which is characterized by physiological complexity and strong statistical intercorrelation among its key variables. The majority of previous factor analyses, however, have used only surrogate measures of insulin sensitivity. In addition, few have included members of multiple ethnic groups, and only one has presented results separately for subjects with impaired glucose tolerance. The objective of this study was to investigate, using factor analysis, the clustering of physiologic variables using data from 1,087 nondiabetic participants in the Insulin Resistance Atherosclerosis Study (IRAS). This study includes information on the directly measured insulin sensitivity index (SI) from intravenous glucose tolerance testing among African-American, Hispanic, and non-Hispanic white subjects aged 40–69 years at various stages of glucose tolerance. Principal factor analysis identified two factors that explained 28 and 9% of the variance in the dataset, respectively. These factors were interpreted as 1) a “ metabolic” factor, with positive loadings of BMI, waist, fasting and 2-h glucose, and triglyceride and inverse loadings of log(SI+1) and HDL; and 2) a “blood pressure” factor, with positive loadings of systolic and diastolic blood pressure. The results were unchanged when surrogate measures of insulin resistance were used in place of log(SI+1). In addition, the results were similar within strata of sex, glucose tolerance status, and ethnicity. In conclusion, factor analysis identified two underlying factors among a group of metabolic syndrome variables in this dataset. Analyses using surrogate measures of insulin resistance suggested that these variables provide adequate information to explore the underlying intercorrelational structure of metabolic syndrome. Additional clarification of the physiologic characteristics of metabolic syndrome is required as individuals with this condition are increasingly being considered candidates for behavioral and pharmacologic intervention.

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Metadata

Authors
Hanley, A. J. G., Karter, A. J., Festa, A., D’Agostino, R., Wagenknecht, L. E., Savage, P., Tracy, R. P., Saad, M. F., & Haffner, S.
Affiliations
  • Mount Sinai Hospital (CA)
  • Kaiser Permanente (US)
  • The University of Texas at San Antonio Health Science Center (US)
  • Wake Forest University Health Sciences (US)
  • National Heart, Lung, and Blood Institute (US)
  • University of Vermont (US)
  • University of Southern California (US)
ORCID
Venue
Diabetes
Publisher
American Diabetes Association
Published
2002-08-01
Volume
51
Issue
8
Pages
2642-2647
ISSN
  • 0012-1797 (ISSN-L)
  • 1939-327X
DOI
10.2337/diabetes.51.8.2642
OpenAlex
W2120101762
Cited by
229
References
36
Citations by year
2025: 2 · 2024: 4 · 2023: 1 · 2022: 3 · 2021: 5 · 2020: 6 · 2018: 6 · 2017: 6 · 2016: 5 · 2015: 5 · 2014: 12 · 2013: 8 · 2012: 15
FWCI
10.90
Type
journal article
Language
en
Open access
Locations
  • Diabetes (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Bristol-Myers Squibb
  • Eli Lilly and Company
  • Pfizer
  • National Institutes of Health (5u01hl047887-09, 5u01hl047889-09)
  • Genentech
  • U.S. Public Health Service (R01-58329)
  • Canadian Institutes of Health Research
  • National Heart, Lung, and Blood Institute (U01HL047902, U01-HL 47889, U01-HL 47887, U01HL047892, DK-29867)
  • National Institute of Diabetes and Digestive and Kidney Diseases (R01DK029867, DK29867)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
Keywords
metabolic syndrome, insulin sensitivity, insulin resistance, factor structure, impaired glucose tolerance, blood pressure, body mass index, waist circumference, triglycerides, HDL cholesterol, African Americans, Hispanic Americans, Insulin Resistance Atherosclerosis Study
MeSH terms
Arteriosclerosis, Body Constitution, Cardiovascular Diseases, Creatinine, Ethnicity, Factor Analysis, Statistical, Female, Humans, Hypertension, Insulin, Insulin Resistance, Male, Middle Aged, Risk Factors, Smoking, Triglycerides, Body Mass Index

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