All variables followed a normal distribution although tending towards skew and platykurtosis in some cases. However, where appropriate transforms could be identified (e.g. logarithm; inverse), analyses yielded identical results and so only non-transformed analyses are reported. During the online data collection, 10 participants omitted to input their age and nine participants did not provide an answer to the item “age of first intoxication”. These participants were included in the analysis in order to maximize analytic power.
Descriptive data are shown in Table 1. The distribution of males and females was approximately the same in the FHN and FHP groups, chi-square = 0.010, df = 1, p = 0.922, phi = 0.020. Comparing the remaining variables in Table 1 across FHN and FHP individuals, only age t(130) = 2.653, p = 0.009, d = 0.465; age of first intoxication, t(131) = 2.097, p = 0.038, d = 0.366 and Hangover Symptom Scale score, t(140) = 3.601, p < 0.001, d = 0.610, differed significantly.
Table 1 Frequency of men and women and means (SDs) of age, BMI, academic performance, age first intoxicated, Hangover Symptom Scale (HSS) score and estimated blood alcohol concentration (eBAC) by family history of alcohol problems
Is hangover greater in those with a positive family history of AUD?
A series of general linear model analyses were carried out using HSS score as the outcome variable. Three sets of these analyses were run—one set including FHP status and eBAC-U, a second set including FHP status and eBAC-HV and a third set including FHP status and drinking frequency. Initially, FHP status was entered as the sole predictor. Next, either eBAC-U, eBAC-HV or drinking frequency was entered as a second predictor, and the interaction term was inspected to check for regression slope homogeneity. Where the interaction was not significant, a final model was run omitting it.
The common first step for these analyses was a general linear model in which family history status (FHP v FHN) was included as the sole predictor of HSS score. This model indicated that FHP significantly predicted HSS score, F(1, 140) = 12.964, p < 0.001, η
2 = 0.085. Next, eBAC-U was added into the model and the interaction was inspected and found to be non-significant, F(1, 138) < 1.0; therefore, a final model was run including FHP and eBAC-U. In this model, FHP was a significant predictor of HSS score, F(1, 139) = 12.170, p = 0.001, η
2 = 0.081, and eBAC-U was a significant predictor of HSS score, r = 43.635, F(1, 139) = 9.087, p = 0.003, η
2 = 0.061. Adjusted R
2 for this model was 0.129.
A similar set of findings was found when eBAC-HV was included as a predictor in addition to FHP status. The interaction was not significant, F(1, 138) < 1.0, but in a model excluding the interaction, FHP was a significant predictor of HSS score, F(1, 139) = 10.292, p = 0.002, η
2 = 0.069 and eBAC-HV was a significant predictor of HSS score, r = 33.842, F(1, 139) = 15.261, p < 0.001, η
2 = 0.099. Adjusted R
2 for this model was 0.163.
In a model containing FHP, drinking frequency and the interaction of these two predictors the interaction effect was not significant, F(1, 138) < 1.0. Excluding the interaction, FHP was a significant predictor of HSS score, F(1, 139) = 11.649, p = 0.001, η
2 = 0.077 but drinking frequency did not predict HSS score, F(1, 139) < 1.0. Adjusted R
2 for this model was 0.076.