Abstract
Introduction: Metabolic syndrome (MetS) is a cluster of components including abdominal obesity, hyperglycemia, hypertension, and dyslipidemia. MetS is highly prevalent in individuals with bipolar disorders (BD) with an estimated global rate of 32.6%. Longitudinal data on incident MetS in BD are scarce and based on small sample size. The objectives of this study were to estimate the incidence of MetS in a large longitudinal cohort of 1521 individuals with BD and to identify clinical and biological predictors of incident MetS.Methods: Participants were recruited from the FondaMental Advanced Center of Expertise for Bipolar Disorder (FACE-BD) cohort and followed-up for 3 years. MetS was defined according to the International Diabetes Federation criteria. Individuals without MetS at baseline but with MetS during follow-up were considered as having incident MetS. A logistic regression model was performed to estimate the adjusted odds ratio and its corresponding 95% confidence interval (CI) for an association between each factor and incident MetS during follow-up. We applied inverse probability-of-censoring weighting method to minimize selection bias due to loss during follow-up.Results: Among individuals without MetS at baseline (n = 1521), 19.3% developed MetS during follow-up. Multivariable analyses showed that incident MetS during follow-up was significantly associated with male sex (OR = 2.2, 95% CI = 1.7-3.0, p < 0.0001), older age (OR = 2.14, 95% CI = 1.40-3.25, p = 0.0004), presence of a mood recurrence during follow-up (OR = 1.91, 95% CI = 1.22-3.00, p = 0.0049), prolonged exposure to second-generation antipsychotics (OR = 1.56, 95% CI = 0.99, 2.45, p = 0.0534), smoking status at baseline (OR = 1.30, 95% CI = 1.00-1.68), lifetime alcohol use disorders (OR = 1.33, 95% CI = 0.98-1.79), and baseline sleep disturbances (OR = 1.04, 95% CI = 1.00-1.08), independently of the associations observed for baseline MetS components.Conclusion: We observed a high incidence of MetS during a 3 years follow-up (19.3%) in individuals with BD. Identification of predictive factors should help the development of early interventions to prevent or treat early MetS.