Comorbidity of metabolic syndrome components in a population-based screening program: A latent class analysis

Background: The prevalence of metabolic syndrome (MS) is rapidly increasing in the world. Thus, the aim of the present study was to identify the latent subgroups of Iranian male adults based on MS components and investigate the effect of abnormal alanine aminotransferase (ALT) and aspartate aminotransferase (AST), high total cholesterol (TC), and low-density lipoprotein (LDL) on the odds of membership in each class. Methods: In the present study, we used the data of a population-based screening program conducted on 823 urban adult men aged 25 years and older in city of Qom in 2014. Abdominal obesity, fasting blood sugar (FBS), blood pressure, and serum lipid profile were measured in participants after for at least 8 hours. MS was defined according to the Adults Treatment Panel III criteria. Latent class analysis was used to achieve the aims of study. Analyses were conducted using PROC LCA in SAS 9.2 software. In all analysis, p value < 0.05 was considered statistically significant. Results: There were 3 different latent classes among participants. Latent class 1, non-MS, 55.1%; latent lass 2, at risk, 21.3%; and finally latent class 3, MS, with 23.6% of the participants. Age (OR=0.98, 95% CI: 0.98-0.99, high LDL (OR=0.27, 95% CI: 0.13-0.56), high TC (OR=8.12, 95% CI: 4.40-15.00), and abnormal ALT (OR=2.25, 95% CI 1.49-3.41) were associated with at risk class. Also, only age (OR=1.02, 95% CI: 1.01-1.04) was associated with MS class. The most prevalent components among the participants were having low HDL (34.0%) and high WC (33.9%). Conclusion: Notable percent of samples fell in “at risk” and “MS” classes, which stress the necessity of designing preventive interventions for these specific stratums of population.