Latent class analysis of the metabolic syndrome

Boyko, Edward J.; Doheny, Rebecca A.; McNeely, Marguerite J.; Kahn, Steven E.; Leonetti, Donna L.; Fujimoto, Wilfred Y.

doi:10.1016/j.diabres.2010.02.013

« Previous Next »Diabetes Research and Clinical Practice
Volume 89, Issue 1 , Pages 88-93, July 2010

Latent class analysis of the metabolic syndrome☆

Edward J. Boyko
- VA Puget Sound Health Care System, Seattle, WA, USA
- Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, WA, USA
- Corresponding author at: 1100 Olive Way, Suite 1400, Seattle, WA 98101, USA. Tel.: +1 206 2774618; fax: +1 206 7642563.
Rebecca A. Doheny
- Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, WA, USA
Marguerite J. McNeely
- Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, WA, USA
Steven E. Kahn
- VA Puget Sound Health Care System, Seattle, WA, USA
- Department of Medicine, Division of Metabolism, Endocrinology and Nutrition, University of Washington, Seattle, WA, USA
Donna L. Leonetti
- Department of Anthropology, University of Washington, Seattle, WA, USA
Wilfred Y. Fujimoto
- Department of Medicine, Division of Metabolism, Endocrinology and Nutrition, University of Washington, Seattle, WA, USA

Received 26 December 2009; received in revised form 15 February 2010; accepted 16 February 2010. published online 08 March 2010.

Abstract

Attempts to explain the associations among metabolic syndrome (MetS) features using factor analysis to identify unobserved potential causes have resulted in inconsistent findings. We examined whether an unobserved categorical factor explains the associations among MetS features using latent class analysis. A cross-sectional analysis of 499 non-diabetic Japanese-Americans who underwent measurements of fasting blood, waist circumference (WC) and CT-measured intra-abdominal fat (IAF) area was conducted. MetS components were defined by IDF criteria. IAF and fasting serum insulin (FI) were dichotomized at the 75^th percentile. Latent two- and three-class models were fit that included hypertension, dyslipidemia, hyperglycemia, and either WC, IAF, or FI for a total of six models. A three-class latent model fit the data well, while a two-class model did not. In the three-class model, one latent class was strongly associated with all MetS components, while another was associated with hyperglycemia and hypertension only. IAF was associated with only one latent class. Latent class analysis supports the presence of an unobserved factor linked to the co-occurrence of MetS features. One class of this factor was associated with hypertension and hyperglycemia but not central adiposity or FI, suggesting another pathway for observed MetS features.

Keywords: Metabolic syndrome, Latent class analysis, Intra-abdominal fat, Waist circumference, Japanese-American