Marzieh Majd1, Joshua M Smyth2, Nan Lv3, Lan Xiao4, Mark B Snowden5, Elizabeth M Venditti6, Leanne M Williams7, Olusola A Ajilore8, Trisha Suppes7, Jun Ma9. 1. Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA. 2. Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA; Center for Healthy Aging, The Pennsylvania State University, University Park, PA, USA; Penn State Milton S. Hershey Medical Center, The Pennsylvania State University, PA, USA. 3. Institute of Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois, USA. 4. Department of Epidemiology and Population Health, Stanford University, Palo Alto, CA, USA. 5. Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA. 6. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 7. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA. 8. Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA. 9. Institute of Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois, USA; Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA. Electronic address: maj2015@uic.edu.
Abstract
BACKGROUND: Examining variability in the presenting symptoms of depression may be particularly important in characterizing depression in patients with comorbid conditions such as obesity. Identifying the underlying constructs of depression in such patients may produce phenotypic information to aid diagnosis and treatment decisions. OBJECTIVE: To examine the latent factors of symptoms using the depression Symptom Checklist (SCL-20) and the Patient Health Questionnaire (PHQ-9), separately, in patients with obesity and elevated depressive symptoms. METHODS: Exploratory factor analysis (EFA) was performed on baseline data from 409 patients with obesity and elevated depressive symptoms recruited in primary care. Bootstrap analysis was performed to estimate the precision and potential replicability of identified latent factors. RESULTS: Participants (70% women, mean age of 51.0 ± 12.1 years) had moderate depression. EFA of the SCL-20 suggested two reliable factors: dysphoric mood (71% of the variance) and anhedonia (15% of the variance). EFA of the PHQ-9 yielded one factor: dysphoric mood (87% of the variance). Bootstrapped results supported the replicability of these results. The top most endorsed symptoms were feeling low energy, overeating and disturbed sleep. LIMITATIONS: The generalizability of these findings to severe depression may be limited. CONCLUSIONS: Patients with elevated depressive symptoms and obesity present with heterogeneous symptoms. The SCL-20 seems more sensitive than the PHQ-9 for differentiating symptom profiles in this population. Some possible reasons include: 1) differences in number of scale items, and 2) differences in the aspects of depression they tap into; the SCL-20 measures the severity of symptoms, whereas the PHQ-9 measures the frequency of symptoms.
BACKGROUND: Examining variability in the presenting symptoms of depression may be particularly important in characterizing depression in patients with comorbid conditions such as obesity. Identifying the underlying constructs of depression in such patients may produce phenotypic information to aid diagnosis and treatment decisions. OBJECTIVE: To examine the latent factors of symptoms using the depression Symptom Checklist (SCL-20) and the Patient Health Questionnaire (PHQ-9), separately, in patients with obesity and elevated depressive symptoms. METHODS: Exploratory factor analysis (EFA) was performed on baseline data from 409 patients with obesity and elevated depressive symptoms recruited in primary care. Bootstrap analysis was performed to estimate the precision and potential replicability of identified latent factors. RESULTS: Participants (70% women, mean age of 51.0 ± 12.1 years) had moderate depression. EFA of the SCL-20 suggested two reliable factors: dysphoric mood (71% of the variance) and anhedonia (15% of the variance). EFA of the PHQ-9 yielded one factor: dysphoric mood (87% of the variance). Bootstrapped results supported the replicability of these results. The top most endorsed symptoms were feeling low energy, overeating and disturbed sleep. LIMITATIONS: The generalizability of these findings to severe depression may be limited. CONCLUSIONS: Patients with elevated depressive symptoms and obesity present with heterogeneous symptoms. The SCL-20 seems more sensitive than the PHQ-9 for differentiating symptom profiles in this population. Some possible reasons include: 1) differences in number of scale items, and 2) differences in the aspects of depression they tap into; the SCL-20 measures the severity of symptoms, whereas the PHQ-9 measures the frequency of symptoms.
Authors: Kim D Baas; Angélique O J Cramer; Maarten W J Koeter; Eloy H van de Lisdonk; Henk C van Weert; Aart H Schene Journal: J Affect Disord Date: 2011-03 Impact factor: 4.839
Authors: Jun Ma; Veronica Yank; Nan Lv; Jeremy D Goldhaber-Fiebert; Megan A Lewis; M Kaye Kramer; Mark B Snowden; Lisa G Rosas; Lan Xiao; Andrea C Blonstein Journal: Contemp Clin Trials Date: 2015-06-19 Impact factor: 2.226
Authors: Daniel J Munoz; Eunice Chen; Sarah Fischer; Megan Roehrig; Lisa Sanchez-Johnson; John Alverdy; Maureen Dymek-Valentine; Daniel le Grange Journal: Obes Surg Date: 2007-08 Impact factor: 4.129