Applying behavioral economics to understand changes in alcohol outcomes during the transition to adulthood: Longitudinal relations and differences by sex and race

Abstract

Objective: Population drinking trends show clear developmental periodicity, with steep increases in harmful alcohol use from ages 18 to 22 followed by a gradual decline across the 20s, albeit with persistent problematic use in a subgroup of individuals. Cross-sectional studies implicate behavioral economic indicators of alcohol overvaluation (high alcohol demand) and lack of alternative substance-free reinforcers (high proportionate alcohol-related reinforcement) as potential predictors of change during this developmental window, but longitudinal evidence is sparse.

Method: Using a sample of emerging adults (N = 497, M_age = 22.61 years, 62% female, 48.69% White, 40.44% Black), this study examined prospective, bidirectional relations between both past-week heavy drinking days (HDD) and alcohol problems and proportionate alcohol-related reinforcement (reinforcement ratio), alcohol demand intensity (consumption at zero price), alcohol demand O_max (maximum expenditure), and change in demand elasticity (rate of change in consumption across escalating price) over five assessments (every 4 months) using random intercept cross-lagged panel models.

Results: Alcohol problems and HDD decreased across assessments. Significant between-person effects indicated that each behavioral economic variable was associated with increased drinking risk. Change in reinforcement ratio was positively associated with decreases in alcohol problems. Multigroup invariance modeling revealed distinct risk pathways in that change in demand intensity and O_max predicted change in alcohol problems for male participants and change in intensity predicted change in alcohol problems for non-White participants.

Conclusion: The study provides consistent support for proportionate alcohol-related reinforcement and mixed support for demand as within-person predictors of reductions in drinking. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Figure 1.. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Participant Inclusion Flowchart

Note. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) participant inclusion flowchart outlining recruitment and reasons for exclusion over the course of the study.

Figure 2.. Mean number of alcohol problems across time.

Note. The x-axis denotes each assessment, while the number of alcohol problems reported in the past month are quantified along the y-axis.

Figure 3.. Mean number of heavy drinking days per week across time overall and by sex.

Note. Heavy drinking days per week (HDD) over time in the full sample (left panel), and split by sex assigned at birth (right panel). The x-axis denotes each assessment, while the number of HDD reported in the past month are quantified along the y-axis.