Association of COVID-19 impact with outcomes of an integrated obesity and depression intervention: Posthoc analysis of an RCT

Abstract

ObjectiveTo examine the association between COVID-19 impact and clinical outcomes of an integrated collaborative care intervention for adults with obesity and comorbid depression. MethodsLatent class analysis identified clusters of self-reported COVID-19 impact. Cluster characteristics were examined using Fishers’ least significant difference method and canonical discriminant analysis. Intervention vs. usual care effects on primary (body mass index [BMI], depressive symptoms) and secondary (anxiety symptoms and other psychosocial) outcomes stratified by cluster were examined using linear mixed models. ResultsThree clusters were identified: mental health and sleep impact (cluster 1, n = 37), economic impact (cluster 2, n = 18), and less overall impact (cluster 3, n = 20). Clusters differed in age, income, diet, and baseline coping skills. The intervention led to improvements across several health outcomes compared with usual care, with medium to large effects on functional impairments (standardized mean difference, −0.7 [95% CI: −1.3, −0.1]) in cluster 1, depressive symptoms (−1.1 [95% CI: −2.0, −0.1]) and obesity-related problems (−1.6 [95% CI: −2.8, −0.4]) in cluster 2, and anxiety (−1.1 [95% CI: −1.9, −0.3]) in cluster 3. ConclusionsPeople with obesity and comorbid depression may have varied intervention responses based on COVID-19 impact. Interventions tailored to specific COVID-19 impact clusters may restore post-pandemic health.