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April 17, 2026Medicina0 citationsOpen Access

Demographic and Clinical Correlates of Body Mass Index in Older Age Bipolar Disorder: Results from the GAGE-BD Project

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CCCarol K. ChanKRKasia G. RothenbergFBFarren Briggs

Key Points

  • This study aims to explore the relationship between body mass index (BMI) and clinical factors in older adults with bipolar disorder (OABD).
  • Secondary analysis of data from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) project.
  • Used multivariable linear regression and multinomial logistic regression for analysis.
  • BMI was treated as both a continuous and an ordinal variable.
  • Examined associations with demographic and clinical characteristics such as psychiatric history and medication use.
  • 33.0% of participants were classified as overweight and 37.7% as obese.
  • Higher BMI was linked to younger age and increased somatic comorbidities.
  • Anticonvulsant use was associated with higher BMI, while lithium use correlated with lower BMI.
  • Obesity was related to cardiovascular, musculoskeletal, and endocrine comorbidities.

Abstract

Background and Objectives: There are known associations between bipolar disorder and obesity, but it has not been well characterized in older adults with bipolar disorder (OABD). This study aims to examine body mass index (BMI) and its clinical correlations in OABD. Materials and Methods: A secondary analysis was conducted using data from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) project, an international harmonized dataset of OABD cohorts. To examine the relationship between BMI and clinical characteristics (e.g., sex, psychiatric history, symptom severity, medication use, comorbidities), multivariable linear regression and multinomial logistic regression models with random effect for study cohort were used, with BMI as a continuous and as an ordinal (underweight vs. healthy weight vs. overweight vs. obese) dependent variable, respectively. Results: Of 1,226 OABD participants with BMI data, 405 (33.0%) were classified as overweight (BMI 25–29.99) and 462 (37.7%) as obese (BMI > 30). In linear regression models, higher BMI was associated with younger age, higher number of somatic comorbidities, and anticonvulsant use, while lower BMI was associated with lithium use. In logistic regression models, obesity was associated with cardiovascular comorbidity, musculoskeletal comorbidity and endocrine comorbidity. Conclusions: A high proportion of individuals with OABD are overweight or obese. Several demographic and clinical correlations of higher BMI were found, including younger age, higher number of medical comorbidities and anticonvulsant use. Clinicians should monitor and manage weight changes and associated comorbidities, and promote lifestyle and health interventions to minimize the risk of negative health outcomes associated with high BMI.

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Cite This Study

Chan et al. (2026) studied this question.

synapsesocial.com/papers/69e1cefb5cdc762e9d857de5https://doi.org/10.3390/medicina62040761
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