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Background: Few prior studies have investigated the latent class structure of PTSD using DSM-5 symptoms., Methods: To describe latent PTSD profiles among women who resided in Deepwater Horizon Oil Spill (DHOS)-affected coastal Louisiana communities, we used data from women enrolled in The Women and Their Children's Health (WaTCH) Study. Latent profile analysis was performed on the 20-item PTSD Checklist for DSM-5 (PCL-5) and model fit statistics for 2-class through 6-class solutions were compared. The pseudo-class draws method was employed on the best class solution to compare key covariates (including demographics, mental health indicators, DHOS exposure indicators, and trauma exposures) across classes., Results: Among 1997 women (mean age 46.63 ± 12.14 years, 56.8% white, mean trauma categories 6.09 ± 2.98, 9.55% previously diagnosed with PTSD), model fit statistics supported a five-class solution: low symptoms (mean PCL-5 = 4.10), moderate without mood alterations (mean = 19.73), moderate with mood alterations (mean = 34.24), severe without risk-taking (mean = 55.75), and severe with risk-taking (mean = 53.80). Women in the low-symptom class were significantly more likely to be white, have finished high school, have an income of at least $40,001 per year, be married or living with a partner, and endorse fewer trauma categories than women in the four symptomatic classes. Women with moderate to severe symptoms often had co-morbid depressive symptoms and no prior PTSD diagnosis., Limitations: This study was limited by use of self-reported data and one-time assessment of PTSD symptoms., Discussion: Five distinct latent profiles of DSM-5 PTSD symptoms consisted of notably different individuals. Most affected women did not report prior PTSD diagnosis. Future research and practice identifying and addressing barriers to care for trauma-affected women in these communities is warranted., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: Oil spill exposures are associated with increased levels of depression, which is often measured using continuous scores or dichotomous cut points on screening tools in population-based studies. Latent profile analysis can overcome analytic limitations such as 1) masking of heterogeneity in outcomes among people within dichotomous categories and 2) loss of information about symptom patterns among those with the same continuous score. This study examined variation in depressive symptoms and assessed the associations between depressive symptomatology and oil spill exposure, socioeconomic risk factors, and social capital., Methods: Between 2012 and 2014, we interviewed 2852 women in southeastern Louisiana. We performed latent profile analysis then tested the adjusted associations between sociodemographic characteristics, oil spill exposure and latent class membership., Results: Results indicated a three-class solution in which classes varied by symptom severity as the best fit. The strongest associations were among women with the most severe depressive symptoms, who were less educated, were more economically vulnerable, and had the least social support compared to women with no depressive symptoms., Limitations: This study is limited by its cross-sectional design and the self-reported nature of exposures and depressive symptoms, but results are consistent with prior literature., Conclusions: Our results support the conventional use of screening tools to estimate depressive symptomatology. Nevertheless, the identification of subgroups within study participants highlights an important finding: the subgroups were comprised of characteristically different women with varying levels of depressive symptoms, a discovery that would have been overlooked if the CES-D was used conventionally., (Copyright © 2016 Elsevier B.V. All rights reserved.)