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Factors associated with preterm birth: from logistic regression to structural equation modeling

This study proposed the application of structural equation modeling (SEM) to investigate variables associated with preterm birth based on a theoretical model analyzed previously by hierarchical logistic regression. The data came from a population-based case-control observational study of hospital births to mothers residing in Londrina, Paraná State, Brazil (June 2006 to March 2007). For the SEM, the study considered the association between socioeconomic characteristics and psychosocial aspects pertaining to reproductive history, work and physical activity, complications during the pregnancy, and fetal characteristics. It also considered the relationship between these associations and the outcome preterm birth mediated by adequacy of prenatal care. The weighted least square mean and variance adjusted estimator (WLSMV) was used for categorical data and robust maximum likelihood (MLR) for odds ratios. Three latent variables were created: socioeconomic vulnerability, family vulnerability, and unwanted pregnancy. The effect of socioeconomic and family vulnerability and unwanted pregnancy on prematurity occurred indirectly through inadequacy of prenatal care. The proposed methodology allowed using constructs, verifying the role of mediation by inadequacy of prenatal care, and identifying the variables’ direct and indirect effects on the outcome preterm birth.

Keywords:
Statistical Models; Logistic Models; Risk Factors; Premature Birth


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