Journal Articles

Maternal Risk Factors Predicting Child Physical Characteristics and Dysmorphology in Fetal Alcohol Syndrome and Partial Fetal Alcohol Syndrome

March 18, 2011

Philip A. May, Barbara G. Tabachnick, Luther K. Robinson, H. Eugene Hoyme, and J. Phillip Gossage (2011)Maternal Risk Factors Predicting Child Physical Characteristics and Dysmorphology in Fetal Alcohol Syndrome and Partial Fetal Alcohol SyndromeDrug and Alcohol Dependencedoi:10,1016/j.drugaldep.2011.05.009

Abstract

BACKGROUND:

Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS).

METHOD:

Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics.

RESULTS:

Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child’s physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies.

CONCLUSIONS:

Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables.

Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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