Adverse Birth Outcomes as Indicators of Poor Fetal Growth Conditions in a French Newborn Population-A Stratified Analysis by Neighborhood Deprivation Level

Abstract

Background: Adverse birth outcomes are related to unfavorable fetal growth conditions. A latent variable, named Favorable Fetal Growth Condition (FFGC), has been defined by Bollen et al., in 2013; he showed that this FFGC latent variable mediates the effects of maternal characteristics on several birth outcomes. Objectives: The objectives of the present study were to replicate Bollen's approach in a population of newborns in Paris and to investigate the potential differential effect of the FFGC latent variable according to the neighborhood socioeconomic level. Methods: Newborn health data were available from the first birth certificate registered by the Maternal and Child Care department of the City of Paris. All newborns (2008-2011) were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level. Several mothers' characteristics were collected from the birth certificates: age, parity, education and occupational status and the occupational status of the father. Three birth outcomes were considered: birth weight (BW), birth length (BL) and gestational age (GA). Results: Using a series of structural equation models, we confirm that the undirected model (that includes the FFGC latent variable) provided a better fit for the data compared with the model where parental characteristics directly affected BW, BL, and/or GA. However, the strength, the direction and statistical significance of the associations between the exogenous variables and the FFGC were different according to the neighborhood deprivation level. Conclusion: Future research should be designed to assess the how robust the FFGC latent variable is across populations and should take into account neighborhood characteristics to identify the most vulnerable group and create better design prevention policies.

Keywords: adverse birth outcomes; fetal growth conditions; neighborhood deprivation; social inequalities; structural equation models (sem).

Figure 1

Structural equation model relating parents’ characteristics to those of an infant’s birth (BW, BL, GA) (Model 1). Legend: BW = birth weight; BL = birth length, GA = gestational age; GIRL = newborn is a girl; FirstP = newborn was firstborn; Younger = mother was <20 years old when pregnant; Older = mother was >35 years old when pregnant; primary = women with a low education level; secondary = women with a middle education level; bac = women with a high education level; unemployedM = unemployed mother; unemployedF = unemployed father.

Figure 2

Structural equation model relating parents’ characteristics to those of an infant’s birth (BW, BL, GA) with a mediating latent variable Favorable Fetal Growth Condition (FFGC) (Model 2). Legend: BW= birth weight; BL = birth length, GA = gestational age; GIRL = newborn is a girl; FirstP = newborn was firstborn; Younger = mother was <20 years old when pregnant; Older = mother was >35 years old when pregnant; primary = women with a low education level; secondary = women with a middle education level; bac = women with a high education level; unemployedM = unemployed mother; unemployedF = unemployed father.

Figure 3

Structural equation model relating parents’ characteristics to those of an infant’s birth (BW, BL, GA) with a mediating latent variable FFGC and additional paths (Model 3). Legend: BW= birth weight; BL = birth length, GA = gestational age; GIRL = newborn is a girl; FirstP = newborn was firstborn; Younger = mother was <20 years old when pregnant; Older = mother was >35 years old when pregnant; primary =women with a low education level; secondary = women with a middle education level; bac = women with a high education level; unemployedM = unemployed mother; unemployedF = unemployed father.