A Prospective Comparison of How the Level of Response to Alcohol and Impulsivity Relate to Future DSM-IV Alcohol Problems in the COGA Youth Panel.
- Authors
- Schuckit, Marc A; Smith, Tom L; Danko, George; Anthenelli, Robert; Schoen, Lara; Kawamura, Mari; Kramer, John; Dick, Danielle M; Neale, Zoe; Kuperman, Samuel; McCutcheon, Vivia; Anokhin, Andrey P; Hesselbrock, Victor; Hesselbrock, Michie; Bucholz, Kathleen
- Year
- 2017
- Journal
- Alcoholism, clinical and experimental research
- PMID
- 28440866
- DOI
- 10.1111/acer.13407
- PMCID
- PMC5512427
BACKGROUND: Alcohol problems reflect both environmental and genetic characteristics that often operate through endophenotypes like low levels of response (low LRs) to alcohol and higher impulsivity. Relationships of these preexisting characteristics to alcohol problems have been studied, but few analyses have included both low LR and impulsivity in the same model. METHODS: We extracted prospective data from 1,028 participants in the Prospective Youth Sample of the Collaborative Study on the Genetics of Alcoholism (COGA). At Time 1 (age 18), these drinking but non-alcohol-dependent males and females completed the Barratt Impulsivity Scale and the Self-Report of the Effects of Alcohol questionnaire regarding drinks required for effects the first 5 times of drinking (SRE5-LR). Two years later, they reported perceived drinking patterns of peers (PEER), their own alcohol expectancies (EXPECT), and their drinking to cope with stress (COPE). Subsequently, at Time 3, participants reported numbers of up to 11 DSM-IV alcohol criterion items experienced in the 2 years since Time 2 (ALC PROBS). Data were analyzed using structural equation modeling (SEM). RESULTS: In the SEM, Baseline SRE5-LR and impulsivity were weakly related and did not interact in predicting later ALC PROBS. LR was directly linked to Time 3 ALC PROBS and to PEER, but had no direct path to EXPECT, with partial mediation to ALC PROBS through PEER to EXPECT and via COPE. Impulsivity did not relate directly to ALC PROBS or PEER, but was directly related to EXPECT and COPE, with effects on ALC PROBS also operating through EXPECT and COPE. CONCLUSIONS: Low LRs and impulsivity related to Time 3 ALC PROBS through somewhat different paths. Education- and counseling-based approaches to mitigate future alcohol problems may benefit from emphasizing different potential mediators of adverse alcohol outcomes for youth with low LRs versus those with high impulsivity or both characteristics.
The major hypothesized pathways regarding how Time 1 SRE5-LR and impulsivity (IMPLUSE) relate directly and via partial mediation by Time 2 perceived peer drinking (PEER), alcohol expectancies (EXPECT), and drinking to cope (COPE) to Time 3 alcohol problems (AlC PROBS) are indicated in bold; the remaining Time 1 variables (Female Sex, Age, European American [EA] background and a history of an alcohol disorder in a biological parent [Fam Hx]) are baseline covariates in the model. More detailed information regarding variables is presented in Tables 1 and 2.
The measurement model for the structural equation model (SEM) demonstrates how the 4 latent variables were created and how they relate to each other. Only significant correlations and factor loadings are shown. PEER was created from 3 indicators of perceived drinking status, frequency, and maximum drinks of 4 closest peers; EXPECT was created from the adolescent and adult Alcohol Expectancy Questionnaire values for Global, Social Behavior, and Relaxation subscale scores; indicators for COPE used 3 parcels generated from the 6 Drinking to Cope items; indicators for ALC PROBS used 3 parcels generated from the 11 DSM-IV alcohol use disorder items. Model fit was good with CFI = .98; NNFI = .97; RMSEA = .058 [.050–.066]; Standardized RMR = .033
The full SEM model is based on testing the Hypothesized Model (Figure 1) with the measurement model from Figure 2 incorporated (measurement model details are not repeated here). Only significant paths (beta weights) and correlations are shown in Figure 3. The definitions of manifest variables shown in squares and the latent variables shown as circles are described in Figure 1. SEM model fit was good with CFI = .94; NNFI = .92; RMSEA = .063 [.058–.068]; Standardized RMR = .039.
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