Predicting Accurate Perinatal Depression Diagnoses in an Obgyn Setting

Background and Purpose: Perinatal depression is a serious, but treatable mental illness.  Among women living in the United States, perinatal depression affects approximately one in every five women.  During childbearing years, women are most susceptible to depression, and have been found to be more likely to experience mental illness following childbirth than during any other time in life. One of the most prevalent forms of maternal mental illness is perinatal depression.  Perinatal depression has been shown to impact childbearing women of all backgrounds.  Despite the fact that women of diverse backgrounds experience perinatal depression, pre-existing social determinants impact the number of women who receive the appropriate care for their depressive symptoms.  Current conservative estimates indicate that less than 50% of depressed women are accurately diagnosed with perinatal depression. When unaddressed, perinatal depression can have a long-term negative effect on a woman and her family.  As a result of perinatal depression, mothers and families may struggle to maintain an infant’s physical and mental health, creating a life-long ripple effect of adverse outcomes for family units. In order to mitigate and prevent the serious negative repercussions of perinatal depression, this study examined social determinants that are believed to impact providers’ ability to accurately diagnose perinatal depression.

Methods: Cross-sectional data were collected at a Southeastern OBGYN clinic. The sample for this study includes 2,109 perinatal women.  A logistic regression was conducted to examine whether the social determinants of race, education, and socioeconomic status served as predictors for an accurate perinatal depression diagnosis. 

Results: Race was found to be a statistically significant predictor for whether or not perinatal depression was accurately diagnosed (OR=3.88, 95%CI: 2.27, 6.63, p< .001).  Here, the odds of an inaccurate diagnosis are nearly four times greater for non-White women than for White women.  While literature indicates that SES and education levels are both risk factors for developing perinatal depression, the statistical analyses do not significantly predict whether these social determinants impact a provider’s accurate assessment and diagnosis of perinatal depression (OR_EDU = 1.008, 95%CI: .88, 1.16, p=.91; OR_SES= .99, 95%CI: .61, 1.14, p=.91).  Here, analyses indicate approximately equal odds of diagnostic accuracy among women from diverse education and SES backgrounds.

Conclusions and Implications:  Given the serious, long-term repercussions of failing to accurately diagnose perinatal depression when it initially presents, it is important to develop a model that examines the risk and protective factors present in making an accurate diagnosis.  These results support previous findings regarding providers’ ability to diagnose racially diverse patient populations in general practice settings, and reflect an important diagnostic gap within the current healthcare delivery system.  The results of this study speak to the need for providers’ increased awareness of mental health issues among minority patients, and call for a greater focus on accurate screening techniques for providers with a diverse patient-base. Social workers working within interdisciplinary care settings may offer a unique solution to racially sensitive issues surrounding this diagnostic gap, and should be further explored within perinatal care environments.