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Rate of alcohol consumption in the daily life of adolescents and emerging adults

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Abstract

Rationale

Alcohol consumption in adolescents and emerging adults is a significant issue. However, our understanding of the topography of alcohol use within drinking episodes in this population is at a nascent stage.

Objectives

This study characterized rate of alcohol consumption in the daily lives of problem drinkers ages 16–24 years (N = 75). We examined whether AUD symptoms and the presence of peers, factors relevant to alcohol consumption in youth, were associated with rate of consumption.

Methods

Ecological momentary assessment (EMA) was used (Nobservations = 799). Rate of consumption was defined as change in estimated blood alcohol concentration (eBAC) relative to the start of the drinking episode. Piecewise multi-level modeling was used to test hypotheses. As a comparison, we examined whether indicators of quantity and frequency (Q-F) were associated with AUD symptoms and presence of peers.

Results

For all participants, eBAC increased sharply early in the episode, then plateaued. Participants with more AUD symptoms or who were in the presence of peers had significantly steeper increases in eBAC over the early part of the episode. Participants with more AUD symptoms were also more likely to engage in binge-like behavior. For Q-F, only peak eBAC and peak number of standard drinks were associated with AUD symptoms, and not presence of peers.

Conclusions

Findings highlight the value of rate of consumption as an indicator of use in youth, one sensitive to the influence of relevant person-level and situational factors. Intervention efforts may benefit from targeting the speed at which youth drink.

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Notes

  1. Drink reports beyond the third begin-/end-drink report pair were infrequent in the sample, with 98 such reports (12.3% of prompts). Excluding the 26 participants who could not make more than three report pairs did not affect the results, except that the interaction for presence of peers and slope-300 became nonsignificant.

  2. For the first drink of an episode, if participants reported having already started their drink, the number of min ago that participants began drinking was added to time elapsed and included in the calculation of eBAC.

  3. In addition to the piecewise MLM, we considered using a polynomial model (i.e., quadratic, cubic). However, the fit of the piecewise model (AIC − 2809.6, BIC − 2815.6) was superior in terms of fit (with smaller values [i.e., more negative] being better) to that of both the quadratic (AIC − 2787.0, BIC − 2793.0) and cubic models (AIC − 2793.0, BIC − 2793.0). We additionally favored a piecewise MLM over a polynomial model because the resulting regression splines from the piecewise MLM could be interacted with moderators (AUD symptoms and presence of peers), thus facilitating our goal of examining the effect of these moderators on rate of consumption within the drinking episode. The piecewise model, which had linear slopes, was also superior to piecewise models with quadratic (AIC − 2799.6, BIC − 2805.6) and cubic (AIC − 2794.6, BIC − 2800.6) slopes.

  4. Viewing Figure 2, there may appear to be a main effect for AUD symptoms, as, for example, individuals with severe AUD have the highest eBACs for much of the episode. However, it should be noted that the bulk of prompts occurred early in the episode, before substantial differences in eBAC emerged. Thus, taking into account the entirety of the episode, there was no main effect. This also applies below to the presence of peers.

  5. We additionally conducted these analyses without a time specifier for binge-like behavior (i.e., whether participants achieved an eBAC of .080 g% at any point in the episode). The number of binge episodes increased to 33. However, results for AUD symptoms and presence of peers did not change.

  6. While drinking fast is a risky behavior, there are situations (e.g., pre-gaming) in which it may be planned in advance. Future work should examine possible differences in planned vs. unplanned fast consumption.

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Funding

The National Institute of Alcohol Abuse and Alcoholism (AA007850, PI: Miranda; AA024808, PI: Treloar; AA007459, PI: Monti; L30AA027041: PI, Emery) and the National Institute on Drug Abuse (DA016184, PI: Rohsenow) supported this research.

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Authors and Affiliations

  1. Department of Psychiatry and Human Behavior, Center for Alcohol and Addiction Studies, Brown University, Box G-S121-5, Providence, RI, 02912, USA

    Ryan W. Carpenter, H. Treloar Padovano, Noah N. Emery & Robert Miranda Jr

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  1. Ryan W. Carpenter
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  2. H. Treloar Padovano
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  3. Noah N. Emery
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  4. Robert Miranda Jr
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Correspondence to Robert Miranda Jr.

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Carpenter, R.W., Treloar Padovano, H., Emery, N.N. et al. Rate of alcohol consumption in the daily life of adolescents and emerging adults. Psychopharmacology 236, 3111–3124 (2019). https://doi.org/10.1007/s00213-019-05262-8

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