Clustering and combining pattern of metabolic syndrome components among Iranian population with latent class analysis

  Background: Metabolic syndrome (MetS), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. The aim of this study was to identify the subgroups of participants in a study on the basis of MetS components.   Methods: The cross-sectional study took place in the districts related to Tehran University of Medical Sciences. The randomly selected sample consists of 415 subjects. All participants provided written informed consent. Latent class analysis was performed to achieve the study’s objectives. Analyses were conducted by using proc LCA in SAS 9.2 software.   Results: Except systolic and diastolic blood pressure, the prevalence of all MetS components is common in female than male. Four latent classes were identified: (a) non MetS, (b) low risk, (c) high risk, and (d) MetS. Notably, 24.2% and 1.3% of the subjects were in the high risk and MetS classes respectively.   Conclusion: Most of the study participants were identified as high risk and MetS. Design and implementation of preventive interventions for this segment of the population are necessary.