Predictors of preterm birth and low birth weight: A person-centered approach

Objective: Profound disparities exist among Black and White families who experience adverse infant health outcomes, yet much is unclear regarding factors that predict disparate outcomes. In order to address this gap, this study applied a person-centered, intersectional analysis to determine ways that women's typological risk profiles inform risk for preterm birth and low birth weight. Materials and methods: In order to examine the role that social determinants play in predicting risk, this study implemented a latent class mixture modeling analysis of data from the Pregnancy Risk Assessment Monitoring System (PRAMS). Data were extracted from Pennsylvania and Illinois PRAMS surveys from 2012 to 2015 (n = 4336). Results: Results of the study indicate three distinct risk types among women in the sample: low-, moderate- and high-risk. Three latent classes were identified: (1) low risk for PTB/LBW (44%); (2) moderate risk (19%); and (3) high risk (36%). Compared to class one, the likelihood of experiencing PTB were significantly higher for class three (x2PTB = 9.54, p < .001; x2LBW = 35.51, p < .001). The likelihood of experiencing LBW were significantly higher for class three, compared to class two (x2PTB = 9.21, p < .05; x2LBW = 21.17, p < .001).Within the three risk groups, racial disparities are particularly notable, with 76% of the sample's African American mothers falling into the “high-risk” category. Conclusion: Public and perinatal health researchers, organizations, and funders are increasingly recognizing the need to identify methods that will best support health-promoting interventions that have the potential to close the racial disparity in PTB and LBW. Although racial disparities have long been noted, the findings from this study's analysis help to better understand how determinants of health intersect to create an overarching risk profile, which can be used to inform health interventions and services that may reduce the current Black-White gap in infant health outcomes