Abstract
Alcohol expectancies (AEs) are associated with likelihood of alcohol initiation and subsequent alcohol use disorders. It is unclear whether genetic predisposition to alcohol use and/or related traits contributes to shaping how one expects to feel when drinking alcohol. We used the Adolescent Brain Cognitive Development study to examine associations between genetic propensities (i.e., polygenic risk for problematic alcohol use, depression, risk-taking), sociodemographic factors (i.e., parent income), and the immediate social environment (i.e., peer use and disapproval toward alcohol) and positive and negative AEs in alcohol-naïve children (max analytic N = 5,352). Mixed-effect regression models showed that age, parental education, importance of the child’s religious beliefs, adverse childhood experiences, and peer disapproval of alcohol use were associated with positive and/or negative AEs, to varying degrees. Overall, our results suggest several familial and psychosocial predictors of AEs but little evidence of contributions from polygenic liability to problematic alcohol use or related phenotypes.
Similar content being viewed by others
Data Availability
Genetic and phenotypic data in the ABCD sample are available for download by approved researchers from the NIMH Data Archive.
Code Availability
Available at https://github.com/emmacj/ABCD_alc_expectancies
References
Agrawal A et al (2008) Drinking expectancies and motives: a genetic study of young adult women. Addiction 103:194–204
Albertina EA, Barch DM, Karcher NR (2022) Internalizing symptoms & adverse childhood experiences associated with functional connectivity in a middle childhood sample. Biol Psychiatry Cogn Neurosci Neuroimaging. https://doi.org/10.1016/j.bpsc.2022.04.001
Boyd SJ, Sceeles EM, Tapert SF, Brown SA, Nagel BJ (2018) Reciprocal relations between positive alcohol expectancies and peer use on adolescent drinking: an accelerated autoregressive cross-lagged model using the NCANDA sample. Psychol Addict Behav 32:517
Brown SA, Christiansen BA, Goldman MS (1987a) The alcohol expectancy questionnaire: an instrument for the assessment of adolescent and adult alcohol expectancies. J Stud Alcohol 48:483–491
Brown SA, Creamer VA, Stetson BA (1987b) Adolescent alcohol expectancies in relation to personal and parental drinking patterns. J Abnorm Psychol 96:117
Brown SA, Tate SR, Vik PW, Haas AL, Aarons GA (1999) Modeling of alcohol use mediates the effect of family history of alcoholism on adolescent alcohol expectancies. Exp Clin Psychopharmacol 7:20–27. https://doi.org/10.1037/1064-1297.7.1.20
Chang CC et al (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4:7
Chen A-J et al (2021) Association between childhood negative life events with alcohol expectancies in early adolescence: Cumulative risk and latent class approaches. Drug Alcohol Depend 226:108853
Cooper ML (1994) Motivations for alcohol use among adolescents: development and validation of a four-factor model. Psychol Assess 6:117
Corbin WR, Waddell JT, Ladensack A, Scott C (2020) I drink alone: mechanisms of risk for alcohol problems in solitary drinkers. Addict Behav 102:106147
Dick D et al (2014) Spit for Science: launching a longitudinal study of genetic and environmental influences on substance use and emotional health at a large US university. Front Genet. https://doi.org/10.3389/fgene.2014.00047
Elder RW et al (2010) The effectiveness of tax policy interventions for reducing excessive alcohol consumption and related harms. Am J Prev Med 38:217–229
Freedman D, Thornton A, Camburn D, Alwin D, Young-DeMarco L (1988) The life history calendar: a technique for collecting retrospective data. Sociol Methodol 18:37–68
Fromme K, D’Amico EJ (2000) Measuring adolescent alcohol outcome expectancies. Psychol Addict Behav 14:206
Ge T, Chen C-Y, Ni Y, Feng Y-CA, Smoller JW (2019) Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun 10:1–10
Goldman, M. S., del Boca, F. K. & Darkes, J. (1999). Alcohol expectancy theory: The application of cognitive neuroscience
Goldstein RZ, Volkow ND (2002) Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am J Psychiatry 159:1642–1652
Ham LS, Stewart SH, Norton PJ, Hope DA (2005) Psychometric assessment of the comprehensive effects of alcohol questionnaire: comparing a brief version to the original full scale. J Psychopathol Behav Assess 27:141–158
Hasking P, Lyvers M, Carlopio C (2011) The relationship between coping strategies, alcohol expectancies, drinking motives and drinking behaviour. Addict Behav 36:479–487
Heckley G, Jarl J, Gerdtham U-G (2017) Frequency and intensity of alcohol consumption: new evidence from Sweden. Eur J Health Econ 18:495–517
Howard DM et al (2019) Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci 22:343–352
Huerta MC, Borgonovi F (2010) Education, alcohol use and abuse among young adults in Britain. Soc Sci Med 71:143–151
Jernigan TL, Brown SA, Dowling GJ (2018) The Adolescent brain cognitive development study. J Res Adolesc 28:154–156
Johnston, L. D., O’Malley, P. M., Miech, R. A., Bachman, J. G. & Schulenberg, J. E. (2014) Monitoring the Future Results on Drug Use: 1975–2013: Overview, Key Findings on Adolescent Drug Use, 2013. Ann Arbor Inst. Soc. Res. Univ. Michigan
Jones SC, Gordon CS (2017) A systematic review of children’s alcohol-related knowledge, attitudes and expectancies. Prev Med (baltim) 105:19–31
Jones BT, Corbin W, Fromme K (2001) A review of expectancy theory and alcohol consumption. Addiction 96:57–72
Kendler KS, Gardner CO, Prescott CA (1997) Religion, psychopathology, and substance use and abuse: a multimeasure, genetic-epidemiologic study. Am J Psychiatry 154:322–329
Kendler KS et al (2003) Dimensions of Religiosity and their relationship to lifetime psychiatric and substance use disorders. Am J Psychiatry 160:496–503
Kong A et al (2018) The nature of nurture: effects of parental genotypes. Science 1979(359):424–428
Kranzler HR et al (2019) Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 10:1499
LaBrie JW, Grant S, Hummer JF (2011) “This would be better drunk”: alcohol expectancies become more positive while drinking in the college social environment. Addict Behav 36:890–893
Lam M et al (2019) RICOPILI: rapid imputation for COnsortias PIpeLIne. bioRxiv 36:930–933
Lee JJ et al (2018) Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet 50:1112–1121
Leonard KE, Blane HT (1999) Psychological theories of drinking and alcoholism. Guilford Press, New York
Levey DF et al (2021) Bi-ancestral depression GWAS in the million veteran program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nat Neurosci 24:954–963
Linnér RK et al (2019) Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat Genet 51:245
Lisdahl KM et al (2018) Adolescent brain cognitive development (ABCD) study: overview of substance use assessment methods. Dev Cogn Neurosci 32:80–96
Liu M et al (2019) Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet 51:237–244
Martino SC, Collins RL, Ellickson PL, Schell TL, McCaffrey D (2006) Socio-environmental influences on adolescents’ alcohol outcome expectancies: a prospective analysis. Addiction 101:971–983
Mason MJ, Mennis J, Linker J, Bares C, Zaharakis N (2014) Peer attitudes effects on adolescent substance use: the moderating role of race and gender. Prev Sci 15:56–64
Miller L, Davies M, Greenwald S (2000) Religiosity and substance use and abuse among adolescents in the national comorbidity survey. J Am Acad Child Adolesc Psychiatry 39:1190–1197
Murphy MA, Dufour SC, Gray JC (2021) The association between child alcohol sipping and alcohol expectancies in the ABCD study. Drug Alcohol Depend 221:108624
Nicolai J, Demmel R, Moshagen M (2010) The comprehensive alcohol expectancy questionnaire: confirmatory factor analysis, scale refinement, and further validation. J Pers Assess 92:400–409
Ouellette JA, Gerrard M, Gibbons FX, Reis-Bergan M (1999) Parents, peers, and prototypes: antecedents of adolescent alcohol expectancies, alcohol consumption, and alcohol-related life problems in rural youth. Psychol Addict Behav 13:183
Palmer RHC et al (2015) Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry. Addiction 110:1922–1931
Perry A (1973) The effect of heredity on attitudes toward alcohol, cigarettes, and coffee. J Appl Psychol 58:275–277. https://doi.org/10.1037/h0035527
Polderman TJC et al (2015) Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet 47:702–709
R Core Team. (2017) R: A language and environment for statistical computing. Preprint at https://www.r-project.org/.
Read JP et al (2012) Trauma and posttraumatic stress symptoms predict alcohol and other drug consequence trajectories in the first year of college. J Consult Clin Psychol 80:426
Ruan Y et al (2022) Improving polygenic prediction in ancestrally diverse populations. Nat Genet 54:573–580
Ryan SM, Jorm AF, Lubman DI (2010) Parenting factors associated with reduced adolescent alcohol use: a systematic review of longitudinal studies. Aust N Z J Psychiatry 44:774–783
Samek DR, Keyes MA, Iacono WG, McGue M (2013) Peer deviance, alcohol expectancies, and adolescent alcohol use: explaining shared and nonshared environmental effects using an adoptive sibling pair design. Behav Genet 43:286–296
Sauer-Zavala S, Burris JL, Carlson CR (2014) Understanding the relationship between religiousness, spirituality, and underage drinking: the role of positive alcohol expectancies. J Relig Health 53:68–78
Shorey RC, McNulty JK, Moore TM, Stuart GL (2016) Being the victim of violence during a date predicts next-day cannabis use among female college students. Addiction 111:492–498
Simons-Morton B (2007) Social influences on adolescent substance use. Am J Health Behav 31:672–684
Slutske WS et al (2002) Genes, environment, and individual differences in alcohol expectancies among female adolescents and young adults. Psychol Addict Behav 16:308–317
Smit K, Voogt C, Otten R, Kleinjan M, Kuntsche E (2019) Exposure to parental alcohol use rather than parental drinking shapes offspring’s alcohol expectancies. Alcohol Clin Exp Res 43:1967–1977
Stein LAR et al (2007) Validity and reliability of the alcohol expectancy questionnaire-adolescent. Brief J Child Adolesc Subst Abuse 16:115–127
Taliun D et al (2021) Sequencing of 53,831 diverse genomes from the NHLBI TOPMed program. Nature 590:290–299
Ting T-T, Chen WJ, Liu C-Y, Lin Y-C, Chen C-Y (2015) Peer influences on alcohol expectancies in early adolescence: a study of concurrent and prospective predictors in Taiwan. Addict Behav 40:7–15
Vernon PA, Lee D, Harris JA, Jang KL (1996) Genetic and environmental contributions to individual differences in alcohol expectancies. Personal Individ Differ 21:183–187. https://doi.org/10.1016/0191-8869(96)00068-2
Viechtbauer W (2010) Conducting meta-analyses in R with the metafor package. J Stat Softw 36:1–48
Waddell JT, Blake AJ, Sternberg A, Ruof A, Chassin L (2020) Effects of observable parent alcohol consequences and parent alcohol disorder on adolescent alcohol expectancies. Alcohol Clin Exp Res 44:973–982
Walters RK et al (2018) Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci 21:1656–1669
Webb JA, Baer PE, Francis DJ, Caid CD (1993) Relationship among social and intrapersonal risk, alcohol expectancies, and alcohol usage among early adolescents. Addict Behav 18:127–134
Zamboanga BL (2006) From the eyes of the beholder: alcohol expectancies and valuations as predictors of hazardous drinking behaviors among female college students. Am J Drug Alcohol Abuse 32:599–605
Zamboanga BL, Bean JL, Pietras AC, Pabón LC (2005) Subjective evaluations of alcohol expectancies and their relevance to drinking game involvement in female college students. J Adolesc Health 37:77–80
Zamboanga BL, Schwartz SJ, Ham LS, Borsari B, van Tyne K (2010) Alcohol expectancies, pregaming, drinking games, and hazardous alcohol use in a multiethnic sample of college students. Cognit Ther Res 34:124–133
Zhou H et al (2020) Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nat Neurosci 23:809–818
Funding
ECJ was supported by K01DA051759. AA and RB receive support from R01DA054750. ASH was supported by K01AA030083. AJG was supported by DGE-213989. NRK was supported by K23MH12179201. SEP was supported by F31AA029934. National Institute on Drug Abuse, K01DA051759, R01DA054750,R01DA054750, National Institute on Alcohol Abuse and Alcoholism, F31AA029934, K01AA030083, National Science Foundation, DGE-213989, National Institute of Mental Health, K23MH12179201.
Author information
Authors and Affiliations
Contributions
All authors had input on study design, with ECJ, DAAB, and AA leading study design and conception. ECJ, SEP, SMCC, LL, and RW contributed to data analysis. SEP, ASH, IH, and NK contributed to phenotype curation. AA and RB supervised analyses. ECJ wrote the manuscript draft, and all authors contributed to editing and approved of the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
Emma C Johnson, Sarah E Paul, David AA Baranger, Alexander S Hatoum, Sarah MC Colbert, Shuyu Lin, Rachel Wolff, Aaron J Gorelik, Isabella Hansen, Nicole R Karcher, Ryan Bogdan, Arpana Agrawal have no conflicts of interest to declare.
Ethical Approval
This study was approved by the local Institutional Review Board. Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093, and U01DA041025. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/Consortium_Members.pdf. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from https://doi.org/10.15154/1523041.
Consent to Participate
All participants in ABCD provided informed consent (or assent).
Consent for Publication
NA
Additional information
Edited by Chun Chieh Fan.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Johnson, E.C., Paul, S.E., Baranger, D.A.A. et al. Characterizing Alcohol Expectancies in the ABCD Study: Associations with Sociodemographic Factors, the Immediate Social Environment, and Genetic Propensities. Behav Genet 53, 265–278 (2023). https://doi.org/10.1007/s10519-023-10133-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10519-023-10133-2