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. 2023 Feb 1:57:101830.
doi: 10.1016/j.eclinm.2023.101830. eCollection 2023 Mar.

Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach

Kenneth J Nieser  1 , Zachary N Stowe  2 , D Jeffrey Newport  3   4 , Jessica L Coker  5   6 , Amy L Cochran  1   7
Affiliations

Detection of differential depressive symptom patterns in a cohort of perinatal women: an exploratory factor analysis using a robust statistics approach

Kenneth J Nieser et al. EClinicalMedicine. .

Abstract

Background: Postpartum depression can take many forms. Different symptom patterns could have divergent implications for how we screen, diagnose, and treat postpartum depression. We sought to utilise a recently developed robust estimation algorithm to automatically identify differential patterns in depressive symptoms and subsequently characterise the individuals who exhibit different patterns.

Methods: Depressive symptom data (N = 548) were collected from women with neuropsychiatric illnesses at two U.S. urban sites participating in a longitudinal observational study of stress across the perinatal period. Data were collected from Emory University between 1994 and 2012 and from the University of Arkansas for Medical Sciences between 2012 and 2017. We conducted an exploratory factor analysis of Beck Depression Inventory (BDI) items using a robust expectation-maximization algorithm, rather than a conventional expectation-maximization algorithm. This recently developed method enabled automatic detection of differential symptom patterns. We described differences in symptom patterns and conducted unadjusted and adjusted analyses of associations of symptom patterns with demographics and psychiatric histories.

Findings: 53 (9.7%) participants were identified by the algorithm as having a different pattern of reported symptoms compared to other participants. This group had more severe symptoms across all items-especially items related to thoughts of self-harm and self-judgement-and differed in how their symptoms related to underlying psychological constructs. History of social anxiety disorder (OR: 4.0; 95% CI [1.9, 8.1]) and history of childhood trauma (for each 5-point increase, OR: 1.2; 95% CI [1.1, 1.3]) were significantly associated with this differential pattern after adjustment for other covariates.

Interpretation: Social anxiety disorder and childhood trauma are associated with differential patterns of severe postpartum depressive symptoms, which might warrant tailored strategies for screening, diagnosis, and treatment to address these comorbid conditions.

Funding: There are no funding sources to declare.

Keywords: Adverse childhood experiences; Factor analysis; Postpartum depression; Robust statistics; Self-injurious behavior; Social phobia; Symptom heterogeneity.

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Conflict of interest statement

KJN has no conflicts of interest to declare. ALC has received research support from the National Institute of Mental Health, UW American Family Data Science Institute, UW Center for Human Genomics and Precision Medicine; has received honorarium from the University of Michigan; and served a statistical editor for the American Journal of Psychiatry. ZNS has received research support from NIH, CDC, GSK, Pfizer, Wyeth, Janssen and SAGE; has served on speaker or advisory boards for Pfizer, Eli Lilly, Wyeth, SAGE, BMS, and GSK; and has received honoraria from Eli Lilly, GSK, Pfizer, and Wyeth. DJN has received research support from Eli Lilly, Glaxo SmithKline (GSK), Janssen, the National Alliance for Research on Schizophrenia and Depression (NARSAD), the National Institutes of Health (NIH), Sage Therapeutics, Takeda Pharmaceuticals, the Texas Health & Human Services Commission, and Wyeth. He has served on speakers’ bureaus and/or received honoraria from Astra-Zeneca, Eli Lilly, GSK, Pfizer and Wyeth. He has served on advisory boards for GSK, Janssen, and Sage Therapeutics. He has served as a consultant to Sage Therapeutics. Neither he nor family members have ever held equity positions in biomedical or pharmaceutical corporations. JLC has no conflicts of interest pertaining to this project.

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