BMIgap: A New Tool for Understanding Weight Gain and Mental Health
Author Information
Author(s): Koutsouleris Nikolaos, Khuntia Adyasha Tejaswi, Popovic David, Sarisik Elif, Buciuman Madalina O., Pedersen Mads L., Westlye Lars T., Andreassen Ole, Meyer-Lindenberg Andreas, Kambeitz Joseph, Salokangas Raimo, Hietala Jarmo, Bertolino Alessandro, Borgwardt Stefan, Brambilla Paolo, Upthegrove Rachel, Wood Stephen, Lencer Rebekka, Meisenzahl Eva, Falkai Peter, Schwarz Emanuel, Wiegand Ariane
Hypothesis
Can BMIgap predict future weight gain in individuals with psychiatric disorders?
Conclusion
BMIgap can help identify individuals at risk of weight gain, especially in younger patients with recent-onset depression.
Supporting Evidence
- BMIgap was higher in individuals with schizophrenia and clinical high-risk states.
- Higher BMIgap predicted future weight gain, especially in younger individuals with recent-onset depression.
- The study involved a large sample size of 2063 participants.
Takeaway
The study created a new way to measure weight gain risk using brain data, which could help doctors give better care to people with mental health issues.
Methodology
Used support-vector machines and whole-brain voxel-wise grey matter volume to generate and validate a BMI predictor.
Participant Demographics
Healthy individuals and those with schizophrenia, clinical high-risk states for psychosis, and recent-onset depression.
Digital Object Identifier (DOI)
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