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

Adelaide Alves De Oliveira,Paula Lisiane De Assunção,Marcia Furquim De Almeida,Hellen Geremias Dos Santos,Zilda Pereira Da Silva,Gizelton Pereira Alencar,Ana Maria Rigo Silva

doi:10.1590/0102-311x00211917

Abstract

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.

Highlights

Theoretical models for studying preterm birth have demonstrated the importance of multiple variables associated with preterm birth
This study proposes to analyze the relations between variables and the outcome preterm birth via structural equation modeling (SEM), using a model tested with logistic regression and hierarchical selection of variables
Two factors were selected whose percentage of explained variance totaled 71.5%, with adequate fits in the model (RMSEA = 0.053; comparative fit index (CFI) = 0.988; Tucker-Lewis index (TLI) = 0.977) (Table 1)

Summary

Introduction

Theoretical models for studying preterm birth have demonstrated the importance of multiple variables associated with preterm birth. Some studies identify the impact of socioeconomic variables, complications, and reproductive history on inadequate prenatal care and highlight the role of prenatal care as a determinant of maternal and perinatal indicators, citing such factors as low socioeconomic status, low schooling, and alcohol use in pregnancy [8,9,10,11], low maternal age, marital status, planning of the pregnancy, public healthcare services, high parity, previous premature childbirth [9,10,12], and unwanted pregnancy 13 These determinants are part of the chain of factors associated with both inadequate prenatal care and negative outcomes such as preterm birth. We include the mediating role of prenatal care in the modeling

Methods

Results

Discussion

Conclusion