Sex- specific clustering of metabolic syndrome components and incidence of cardiovascular disease: A latent class analysis in a population-based cohort study.

BACKGROUND

The prevalence of metabolic syndrome (MetS) is rapidly increasing in the world; also, the importance of management of MetS to decrease the risk of cardiovascular disease (CVD) has been recognized worldwide. This study aimed to explore the clusters of participants based on MetS components and its association with CVD outcomes.

METHODS

We included 2598 middle-aged participants (1545 women and 1053 men), 45-65 years old, at baseline and without prior CVD history. Participants were followed up for 10years. We conducted a latent class analysis based on MetS components. Subsequently, the relationship between latent classes and the incidence of CVD was investigated using Cox regression models adjusted for the main confounders.

RESULTS

During the study period, 393 (186 women and 207 men) new cases of CVD were identified among participants. In both genders, four distinct latent classes were identified: (1) Mets class (its prevalence rate in men: 19.6%, women: 27.7%), (2) Hypertension class (men: 12.1%, women: 13.7%), (3) Dyslipidemia class (men: 31.7%, women: 30.7%), (4) Low risk class (men: 39.3%, women: 30.5%). Compared with low-risk class, in both genders, Mets and hypertension classes were significant predictors of incident CVD. However, dyslipidemia class was a significant predictor just in women.

CONCLUSION

We found four subclasses in both genders indicating the same patterns of MetS latent classes in men and women. However, the relationship between subclasses of MetS and incident CVD varied by gender. These results suggest that the etiology of MetS involve more than one pathway and giving equal weight to each component or using the same cut-off values in both genders need to be reconsidered.