Praise Iyiewuare1, Kelly J Rohan2, Teodor T Postolache3. 1. Department of Psychological Science, University of Vermont, John Dewey Hall, 2 Colchester Avenue, Burlington, VT 05401, United States. Electronic address: piyiewua@uvm.edu. 2. Department of Psychological Science, University of Vermont, John Dewey Hall, 2 Colchester Avenue, Burlington, VT 05401, United States. 3. Department of Psychiatry, University of Maryland School of Medicine, United States; Rocky Mountain Mental Illness Research Education and Clinical Center for Suicide Prevention, United States.
Abstract
BACKGROUND: Efficacious treatments for winter seasonal affective disorder (SAD) include light therapy (LT) and cognitive-behavioral therapy (CBT-SAD); however, baseline characteristics may differentially predict treatment outcomes. This study investigated body mass index (BMI) and atypical balance (the proportion of atypical depression symptoms), as predictors of depression remission. METHODS: The parent study randomized 177 adults diagnosed with Major Depression, Recurrent with Seasonal Pattern to 6-weeks of CBT-SAD (n = 88) or LT (n = 89) and followed participants one and two winters later. At baseline, BMI was measured and atypical balance was derived using the Structured Interview Guide for the Hamilton Rating Scale for Depression-Seasonal Affective Disorder Version (SIGH-SAD) as 8-item atypical subscale score/total SIGH-SAD score × 100. Depression remission was defined using standard SIGH-SAD cutpoints. Hierarchical logistic regressions tested the main effects of treatment modality, BMI, and atypical balance and their interactive effects on depression remission at post-treatment and follow-ups. RESULTS: The BMI × treatment and atypical balance × treatment interactions significantly predicted depression remission at second winter follow-up. The probability of remission was higher in CBT-SAD than LT at BMI ≤ 26.1 and atypical balance ≤ 40.3%. This predictive relationship survived when adjusting atypical balance for BMI, but not vice-versa. LIMITATIONS: Participants were predominantly White and older. BMI does not account for muscle mass or fat distribution. CONCLUSIONS: BMI and atypical balance prescriptively predicted higher likelihood of depression remission two winters following CBT-SAD but not LT. This work informs clinical decision-making and precision medicine efforts.
BACKGROUND: Efficacious treatments for winter seasonal affective disorder (SAD) include light therapy (LT) and cognitive-behavioral therapy (CBT-SAD); however, baseline characteristics may differentially predict treatment outcomes. This study investigated body mass index (BMI) and atypical balance (the proportion of atypical depression symptoms), as predictors of depression remission. METHODS: The parent study randomized 177 adults diagnosed with Major Depression, Recurrent with Seasonal Pattern to 6-weeks of CBT-SAD (n = 88) or LT (n = 89) and followed participants one and two winters later. At baseline, BMI was measured and atypical balance was derived using the Structured Interview Guide for the Hamilton Rating Scale for Depression-Seasonal Affective Disorder Version (SIGH-SAD) as 8-item atypical subscale score/total SIGH-SAD score × 100. Depression remission was defined using standard SIGH-SAD cutpoints. Hierarchical logistic regressions tested the main effects of treatment modality, BMI, and atypical balance and their interactive effects on depression remission at post-treatment and follow-ups. RESULTS: The BMI × treatment and atypical balance × treatment interactions significantly predicted depression remission at second winter follow-up. The probability of remission was higher in CBT-SAD than LT at BMI ≤ 26.1 and atypical balance ≤ 40.3%. This predictive relationship survived when adjusting atypical balance for BMI, but not vice-versa. LIMITATIONS: Participants were predominantly White and older. BMI does not account for muscle mass or fat distribution. CONCLUSIONS: BMI and atypical balance prescriptively predicted higher likelihood of depression remission two winters following CBT-SAD but not LT. This work informs clinical decision-making and precision medicine efforts.
Authors: F Lamers; N Vogelzangs; K R Merikangas; P de Jonge; A T F Beekman; B W J H Penninx Journal: Mol Psychiatry Date: 2012-10-23 Impact factor: 15.992
Authors: Kelly J Rohan; Maggie Evans; Jennifer N Mahon; Lilya Sitnikov; Sheau-Yan Ho; Yael I Nillni; Teodor T Postolache; Pamela M Vacek Journal: Trials Date: 2013-03-21 Impact factor: 2.279