Dissertation/Thesis Abstract

Investigating Socioeconomic and Personal Network Factors as Predictors for Major Depressive Disorder, Especially in Women during their Reproductive Transition
by McCann, Molly K., M.S., State University of New York at Albany, 2015, 47; 1593243
Abstract (Summary)

Aim: The objective of this study was to investigate socioeconomic and personal network factors as predictors for Major Depressive Disorder (MDD) in women, especially within their reproductive transition period.

Design: Cross-sectional

Methods: Questionnaire data from the 2008 Behavioral Risk Factor Surveillance Survey (BRFSS) in combination with a DSM-IV diagnostic algorithm was used to assess the risk factors associated with female depression. A total of 19,771 women were grouped according to age based upon clinically defined reproductive status: 18-35, 36-45, >45 years. A scoring system of 0 to 24 was created to assess for severity of depressive symptoms, and female participants with outcomes ≥10 met the criteria for MDD. Logistic regression was used to determine predictive factors stratified by each age group of women.

Results: Unemployment was a significant predictor of MDD for women in their transition period (OR = 2.05, CI 90% 1.21, 3.47). Reproductive transitioning women also had higher odds of MDD when there was little to no emotional support (OR = 4.59, CI 90% 2.86, 7.38), and poor self-reported health (OR= 2.73, CI 90% 1.44, 5.17). More frequent days of poor health and inadequate rest were also significant for the women during their menopausal transition.

Conclusion: The following study provides a significant platform for improved research on female mental health, particularly across the life span. More intensive research is needed to understand possible associative relationships between female age and depression, in order to initiate appropriate intervention programs.

Indexing (document details)
Advisor: Gensburg, Lenore
Commitee: Leckman-Westin, Emily, Vasquez, Elizabeth
School: State University of New York at Albany
Department: Epidemiology
School Location: United States -- New York
Source: MAI 54/06M(E), Masters Abstracts International
Subjects: Epidemiology
Publication Number: 1593243
ISBN: 978-1-321-89654-1
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