title: Metabolic syndrome in older subjects: coincidence or clustering?
abstract: The prevalence of the metabolic syndrome (MS) increases with advancing age. However, aging per se is associated with increased prevalence of most of the abnormalities contributing to the MS. Whether MS in older people consistently identifies a true pathophysiological entity or a casual aggregation of aging-associated metabolic abnormalities, remains to be fully elucidated. In the present study, we aimed to evaluate whether in older subjects the aggregation of metabolic components of the MS, as defined by the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III), is consistent with a single latent variable. Age, waist circumference, systolic and diastolic blood pressure, metabolic variables were determined in 152 older (>70 years), non-diabetic, healthy men. Cronbach alpha was used to assess the internal consistency of the components contributing to the MS. Structural equation modeling, using the Normed Fit Index (NFI), the Root Mean Square Error of Approximation (RMSEA), the Comparative Fit Index (CFI), and the Tucker-Lewis Index (TLI) was used to assess the fit to a model with a single latent variable. The Cronbach alpha test showed low internal consistency among the metabolic variables (alpha=0.31). The calculated chi(2) values were 28.31 and 32.52 for model entering hypertension as dichotomous variable and for model entering blood pressure values, respectively, both expressing low fit to a model with a single latent variable. In both models, CFI (0.41 and 0.55), NFI (0.59 and 0.55), RMSEA (0.25 and 0.22) and TLI (-0.31 and -0.12) scores showed a low fit of the metabolic alterations to a single latent variable. These findings suggest caution in making diagnosis of MS at older ages, since metabolic and cardiovascular abnormalities being per se extremely common in elderly people, do not appear to cluster together under a single common factor.
authors.affiliation: Department of Medical and Surgical Disciplines, University of Turin, Azienda Ospedaliera San Giovanni Battista, Molinette, Torino, Italy. mario.bo@unito.it
authors.forename: Mario
authors.initials: M
authors.lastname: Bo
authors.forename: Alessandro
authors.initials: A
authors.lastname: Sona
authors.forename: Marco
authors.initials: M
authors.lastname: Astengo
authors.forename: Umberto
authors.initials: U
authors.lastname: Fiandra
authors.forename: Eleonora
authors.initials: E
authors.lastname: Quagliotti
authors.forename: Alessia
authors.initials: A
authors.lastname: Brescianini
authors.forename: Gianfranco
authors.initials: G
authors.lastname: Fonte
mesh_terms: D000368:Aged; D000375:Aging / Q000378:metabolism*; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D005163:Factor Analysis, Statistical; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D007558:Italy / Q000453:epidemiology; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis* / Q000453:epidemiology*; D015995:Prevalence; D055105:Waist Circumference