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.
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.
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.
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.