For the measures of drinking frequency used in the longitudinal analysis, 4021 young people provided a complete set of three responses, with a further 3079 partial responders giving a total of 7100 cases. Figures for the measure of typical alcohol consumption were similar with 3867 and 3215 cases, respectively, giving a total of 7082. Preliminary work showed evidence of an association between degree of missing data and gender as well as housing tenure, parity and maternal education with complete responders being more likely to be female, have parents who own their own home, have a mother educated beyond high school and have fewer siblings. Table shows there are slightly lower rates of alcohol use within the complete case samples where all three repeated measures are available.
Measures of alcohol-use in restricted (complete case) and unrestricted (all available data) samples
Latent class analysis
Between one- and three-class models were compared for drinking frequency, and up to four classes were considered for typical consumption. Model fit statistics are shown in Table . Insufficient degrees of freedom did not permit the fitting of a four-class model for frequency. There is good support for a three-class model with both the alcohol measures. The incomplete data bring more uncertainty reflected in poorer entropy and higher values of bivariate fit, however, the three-class models are still deemed acceptable.
Model fit statistics for latent class analyses
Figure shows the extracted patterns for drinking frequency and typical consumption for the partially observed data sets. To simplify the figures, we present the within class probabilities of (a) drinking on a weekly basis, and (b) drinking three or more units on one occasion. Complete ordinal profiles of drinking behaviour are available on request from the first author. For both drinking frequency and typical consumption, we have named the resulting latent groups as high, medium and low.
Resulting patterns from LLCA (partially observed data).
The results were as follows: for drinking frequency, 53.2% were classified as low frequency with very little drinking from 13 to 14 years and occasional drinking by the age of 15; 32.5% were classified occasional drinking by 14 years and all are drinking by 15 years with a quarter drinking on a weekly basis. Finally, 14.2% were classified as high-frequency drinkers with the majority drinking throughout the time period and almost two-thirds drinking weekly by age 15. For typical alcohol consumption, 58.8% were in the low consumption class with 1–2 units by age 15 but little before this age; 32.3% were in the medium consumption class where about half had consumed 1–2 units by age 13 and a third had had 3+ units by age 15. Finally, the high consumption class of 8.9% consumed to a higher level throughout the time period with three quarters drinking 3+ units by age 15 and a third drinking 7+ units in one sitting. The prevalence of different classes of behaviour was very similar for the smaller complete case samples.
There was reasonable concordance in the latent grouping derived from the two models with two-thirds of the young people in the ‘same’ category for frequency and consumption. For example, of the 7082 respondents, 45% were classified as low on both frequency and consumption, 17% as medium on both and 4.2% as high. Twelve percent were classified as low consumption/medium frequency, 8.2% would be classified as medium consumption/high frequency, 7.3% as medium consumption/low frequency and 3.7% as high consumption/medium frequency class. Only 3% were classified as high/low or low/high, leaving little scope for further investigation of these highly discordant, yet potentially interesting, individuals. Prior to the assessment of risk factor associations, the resulting three-class models described above were re-estimated separately for boys and girls. There was no evidence of an improvement in fit using these models: BIC values were higher compared with the single sample model; and the patterns of response extracted by the latent class model within each gender showed good agreement between boys and girls.
Risk factors for latent class membership
Table shows the relationship between adolescent alcohol-use risk factors and the latent classes for drinking frequency and consumption. These results are based on the latent classes derived using FIML estimation and the partially observed data set, and hence any drop in sample size is due to missing data in the risk factors. Conclusions remained relatively unchanged when examining results based on the complete case latent class model (data available from first author). Results are univariable, considering each risk factor in turn. In each case, the outcome has three categories with the normative category (low drinking frequency/typical consumption) treated as the reference. Following each test of association, a post-estimation comparison was made to investigate which factors were able to further distinguish between the medium- and high -use patterns (data not shown).
Risk factors for class membership (partially observed data for latent class models)
Gender and socio-demographic measures
There was little evidence that class membership varied for boys and girls (P = 0.339 for frequency and P = 0.248 for consumption). There was weak evidence for an association between measures of social position or deprivation and drinking frequency but slightly stronger evidence for associations with typical consumption. In the majority of cases, lower social position or higher deprivation was associated with an increase in the odds of being a high frequency or consumption alcohol user, but there was little effect for medium-level alcohol users. For instance, having no maternal educational qualifications was associated with a 26% increased odds of being in the high-frequency class and 68% increased odds of being in the high-consumption class. Subsidized housing was also associated with the high-consumption class; however, there was no evidence of an association between housing tenure and drinking frequency. The strongest associations within these measures were for parity with an apparent dose–response relationship between the number of siblings and rates of high consumption.
Maternal substance use
There was strong evidence for associations between all three maternal substance use measures and drinking frequency and consumption class membership. Maternal alcohol consumption demonstrates a weak gradient effect. Associations were stronger for tobacco and cannabis, particularly the latter with double the odds of being in the high-drinking frequency and high-consumption classes for young people with cannabis, using mothers at age 9.
Young person characteristics
The cigarette/cannabis use at age 13 is strongly related to alcohol-use pattern, particularly for cannabis which was associated with being both a medium- and high-level alcohol user. Finally, higher levels of maternally reported conduct problems at age 11 are strongly related with high-frequency/-consumption with an approximate doubling of the odds, but associated with little additional risk for more moderate drinking levels.
Post-estimation differences between medium and high alcohol use
For many risk factors, associations were slightly stronger for the level of consumption compared with frequency of use. This is probably due to differences in the high-category prevalences (9 vs 14%) resulting in a more extreme group of users in the high category for the ‘level of consumption’, hence establishing a stronger dose response. Consequently, there was a greater tendency to observe differences between the medium and high use for this outcome. Socio-demographic factors conferred a mildly increased odds of being a high-level user compared with medium-level user, particularly parity (both outcomes) and subsidized housing/no education (consumption outcome only). In addition, maternal smoking and cannabis were associated with being a high-consumption user compared with medium-consumption user [smoking: odds ratio (OR) = 1.65 (1.20, 2.27), and cannabis: OR = 1.71 (1.05, 2.79)]. Finally, the young person's own characteristics were most able to distinguish between all three levels of the outcome, conferring between three and four times greater odds of being a high user for the smoking and cannabis predictors.
Relationship with harmful/hazardous alcohol use at 16
These analyses are based on the subsample of ~4100 with an estimated latent class membership and also a 16-year AUDIT outcome. At age 16, 29% of the young people were drinking hazardously and a further 5.6% were assessed as harmful drinkers. There was moderate evidence (P = 0.017) of an association between the gender and AUDIT score: 29.7% of girls scored 8–15 on the AUDIT scale (hazardous use) compared with 28.2% of boys, and 6.4% of girls scored 16 or higher (harmful use), compared with 4.6% of the boys. Table shows evidence of a strong association between patterns of alcohol use across ages 13 and 15 and AUDIT scores at age 16. Being in the high use class for either drinking frequency or typical consumption is associated with an 8- to 10-fold increase in odds of harmful alcohol use at 16. Adjustment for gender, demographics and maternal substance use led to very minor attenuation (<5%) of the estimates displayed in Table .
Predicting harmful/hazardous alcohol use at age 16 using patterns of alcohol frequency and consumption