Use of confirmatory factor analysis for the identification of new components of the metabolic syndrome: the role of plasminogen activator inhibitor-1 and Haemoglobin A1c.
OBJECTIVE
This study was aimed to identify additional components of metabolic syndrome from a set of cardiovascular risk markers.


RESULTS
The homeostasis model assessment of insulin resistance (HOMA-IR), C-reactive protein, fibrinogen, plasminogen activator inhibitor-1 (PAI-1), von Willebrand factor, homocysteine, Haemoglobin A1c (HbA1c), and lipoprotein(a) were assessed in a population-based sample of 902 nondiabetic adult subjects. Those biomarkers that were associated with metabolic syndrome were evaluated by multiple regression analysis, along with other traditional cardiovascular risk factors. Confirmatory factor analysis (CFA) was used to test the hypothesis that both the established components of metabolic syndrome and the novel variables identified by the regression analysis were associated with a single underlying factor. HOMA-IR, PAI-1 and HbA1c were the only biomarkers independently related to metabolic syndrome. CFA validated a one-factor model that included these variables. Moreover, the indices of goodness of fit were better for this expanded model than those obtained for a previously validated one-factor model that was restricted to the conventional elements of the syndrome.


CONCLUSIONS
These findings show that PAI-1 and HbA1c are singularly linked to metabolic syndrome. Their elevation is presumably another manifestation of the same pathophysiological mechanism that underlies the recognized traits of the syndrome.
Boronat
M
M
Section of Endocrinology and Nutrition, Hospital Universitario Insular, Avda. Marítima del Sur s/n, Las Palmas de Gran Canaria, Spain. mborcor@ono.com
Saavedra
P
P
Varillas
V F
VF
Nóvoa
F J
FJ
D000328:Adult; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D002318:Cardiovascular Diseases / Q000097:blood / Q000209:etiology* / Q000503:physiopathology; D003430:Cross-Sectional Studies; D005163:Factor Analysis, Statistical; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis*; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology; D008875:Middle Aged; D017395:Plasminogen Activator Inhibitor 1 / Q000097:blood*; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D013030:Spain
D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007328:Insulin; D017395:Plasminogen Activator Inhibitor 1; C051321:SERPINE1 protein, human; C517652:hemoglobin A1c protein, human