While much of the variation in child outcomes is due to major drinking variation by QFT, other maternal risk co-factors such as maternal age, gravidity, maternal body mass index, nutrition, and socioeconomic status also play a significant and meaningful role. But including these other maternal risk factors in these analyses is beyond the scope of this paper and have been analyzed elsewhere (May and Gossage, 2011; May et al., 2007, 2008a, 2013b). It is interesting, however, that the drinking data used in the regression model explain 60 to 65% of the variance in diagnosis, which is similar to the variance in child outcomes explained in complex structural equation models of child dysmorphology and neurobehavior (62 to 55%) that incorporate multiple measures of risk: socioeconomic status, childbearing history, and maternal physical variables (May et al., 2011, 2013b). Furthermore, genetic (Khaole et al., 2004) and epigenetic variables also influence outcome. They are also beyond the scope of these epidemiologic sample data and of this paper. In light of these findings, it seems impossible to easily determine that there is a specific threshold
