title: Clustering of hemodynamic and metabolic abnormalities and of anthropometric characteristics in men and women, aged 21-60 years.
abstract: The associations between fat pattern and metabolic profile were evaluated, using cluster analysis, in 214 males and 244 females (aged 21-60 years). The subjects were randomly selected from the patients of one general practice in Castel D'Azzano (Italy). The metabolic status was indexed by blood pressure, blood glucose, uric acid, serum triglycerides, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol (both total and percentage). Fat pattern was evaluated using six skinfolds and three circumferences. The analyses were performed separately on anthropometric and metabolic variables for each sex. The analyses were repeated five times to evaluate the stability of the cluster solution. Anthropometric rather than metabolic variables provided a more stable solution for cluster analysis. Anthropometric clusters showed significantly different metabolic patterns. Most of the differences disappeared when a body mass index (BMI) effect was taken into account but not when an adjustment for waist to hip ratio (WHR) was made. On the other hand, neither BMI nor WHR was able to fully account for the differences in metabolic profiles of metabolic clusters. Cross-classification results of anthropometric and metabolic cluster membership showed a significant, although moderate, degree of association between the two classification sets. These results indicate that in both sexes anthropometric characteristics contribute to a limited degree to the metabolic profile and that the associations probably reflect a complex mechanism.
authors.affiliation: Istituto di Statistica e Ricerca Operativa, Trento, Italy.
authors.forename: R
authors.initials: R
authors.lastname: Micciolo
mesh_terms: D000273:Adipose Tissue / Q000737:chemistry*; D000328:Adult; D000886:Anthropometry; D001823:Body Composition; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000209:etiology / Q000378:metabolism; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000150:complications* / Q000175:diagnosis; D012307:Risk Factors