title: Latent class analysis of the metabolic syndrome.
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.
authors.affiliation: VA Puget Sound Health Care System, Seattle, WA, USA. eboyko@u.washington.edu
authors.forename: Edward J
authors.initials: EJ
authors.lastname: Boyko
authors.forename: Rebecca A
authors.initials: RA
authors.lastname: Doheny
authors.forename: Marguerite J
authors.initials: MJ
authors.lastname: McNeely
authors.forename: Steven E
authors.initials: SE
authors.lastname: Kahn
authors.forename: Donna L
authors.initials: DL
authors.lastname: Leonetti
authors.forename: Wilfred Y
authors.initials: WY
authors.lastname: Fujimoto
mesh_terms: D050153:Abdominal Fat / Q000033:anatomy & histology; D001213:Asian / Q000706:statistics & numerical data*; D001786:Blood Glucose / Q000378:metabolism; D003430:Cross-Sectional Studies; D050171:Dyslipidemias / Q000208:ethnology; D005260:Female; D006801:Humans; D006943:Hyperglycemia / Q000208:ethnology; D006973:Hypertension / Q000208:ethnology; D007328:Insulin / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000208:ethnology*; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D012307:Risk Factors; D055105:Waist Circumference; D014861:Washington / Q000453:epidemiology
chemical_list: D001786:Blood Glucose; D007328:Insulin