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. (C) 2016 Elsevier B.V. All rights reserved.