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Characterizing Alcohol‐Related Neurodevelopmental Disorder: Prenatal Alcohol Exposure and the Spectrum of Outcomes

Abstract

Background

The effects of prenatal alcohol exposure (PAE) are conceptualized as fetal alcohol spectrum disorder, with fetal alcohol syndrome (FAS) as the most severe. Many find it more difficult to characterize behavioral and cognitive effects of exposure on the central nervous system when physical signs are not present. In the current study, an operational definition of alcohol-related neurodevelopmental disorder (ARND) was examined to determine its usefulness in discrimination of children classified as ARND based on behavior (ARND/B) and cognition (ARND/C) from children in 4 contrast groups: (i) children exposed to study-defined "risky drinking"; (ii) children with any reported PAE; (iii) children classified as "Higher Risk" for developmental problems; and (iv) children classified as "Lower Risk."

Methods

A total of 1,842 children seen as part of a surveillance study (J Am Med Assoc, 319, 2018, 474) were evaluated for alcohol exposure and physical characteristics of FAS, and completed neurodevelopmental testing. Ninety-one were identified as either ARND/B or ARND/C and contrasted with other groups to further identify distinguishing patterns. Multinomial logistic regression (MLR) was used to examine the accuracy of classification and to identify factors contributing to such classification.

Results

Children described as ARND/C were distinct from other groups based on cognition and behavior as well as demographic factors (e.g., age, race, SES), child characteristics (e.g., gestational age; sex), and other drug exposures, while those described as ARND/B differed only on behavior and other drug exposures. MLR models successfully discriminated ARND groups from children in other groups with accuracy ranging from 79% (Higher Risk) to 86.7% (Low Risk).

Conclusions

ARND has been a subject of debate. This analysis suggests the effects of alcohol on behavior and cognition even in the absence of the characteristic facial features and growth deficiency that can be identified. The results also indicate that it may be possible to distinguish such children from those in other high-risk groups.

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