1. Social Network Drinking Outweighs Family History in the Development of Alcohol Dependence in Adults Vivia V. McCutcheon, PhD, Christina Lessov-Schlaggar, PhD, Douglas Steinley, PhD., Kathleen K. Bucholz, PhD. Association for Medical Education and Research in Substance Abuse Bethesda, MD November 7-9, 2013

2. Background Genetic influences on risk for alcohol use disorder account for 40-60% of variance Alcohol use and peers – Homophily – Influence Heath et al., 1997; Prescott et al., 1999; Knopik et al., 1999

3. Peer Influence on Alcohol Use Additional heavy drinkers/abstainers in close network increases likelihood heavy drinking/abstention in principal (Rosenquist et al., 2010) Affiliation with substance use promoting peers predicted increase in AUD symptoms at subsequent ages from age 17 to 40 (Chassin et al., 2012) Peer network substance use predicted changes in drinking from adolescence into young adulthood after controlling for genetic and shared environmental influences on peer selection (Cruz et al., 2012)

4. Objective 1.Characterize group of adults with high familial risk for AD – Parental alcohol problems – Drinking behavior in network 2.Examine associations of network drinking and familial risk with first-onset AD

5. Sample 11-year follow-up of subset of ECA sample selected for high risk of developing alcohol dependence (N=753) – Previous reports heavy drinking in self or 1 st - degree relatives – Risk score including conduct disorder, illicit drug use, depression – Age 18-49 at baseline ECA interview 29-62 at 11-year follow-up Regier et al., 1984; Bucholz et al., 1996

6. Assessments DSM-III AD – Current (6.8%) – Remitted (7.7%) Family history alcohol problems in one or both parents – “I’d like to ask you some questions about the drinking of some of your relatives. Have any of the following relatives drunk heavily or had ANY drinking problems, like problems with health, family, job, or police?”

7. Assessments Network drinking – “Now I’d like to know about the current drinking habits of the people you may be close to. Which of the patterns on the card best describes the drinking pattern of (closest friend outside family, closest sibling, current spouse/partner)?” Lifelong abstainer/Non-drinker/Light drinker Moderate/Heavy/Problem drinker or Alcoholic Recovering problem drinker or alcoholic who doesn’t drink now

8. Demographic Characteristics No AD (N=644) Remitted AD (N=51) Current AD (N=58) Age, M(SD)43.4 (8.3)40.4 (6.3)39.7 (7.3) Female, %63.551.051.7 Black, Hispanic, %41.847.153.4 Years educ., M(SD)12.9 (2.3)13.2 (2.1)12.5 (2.2) Marital status, % Married55.952.941.4 SepDiv26.913.724.1 Never Married13.023.519.0 Living as married4.29.815.5

9. Drinking Characteristics No AD (N=644) Remitted AD (N=51) Current AD (N=58) Age regular drinking, M(SD) 22.5 (6.6)19.8 (4.0)22.0 (4.9) Abstinent last year, %57.641.20.0 Typical drinks/week last year, M(SD) 5.4 (6.4)9.4 (10.6)11.9 (10.7) Ever thought you drank too much, % 10.264.731.0

10. AD Incidence by Parental Alcohol Problems 65%30%5% *

11. AD Incidence by Spousal Drinking 5%57%38% *

12. AD Incidence by Friend, Sib Drinking Closest FriendClosest Sibling 41%57%2%52%44%4% * * * *

13. Multinomial Regression Predicting Remitted and Current Incident AD Remitted ADCurrent AD RRR (95% CI) Network drinking Moderate/Heavy1.5 (0.8-2.8)2.6 (1.4-5.1) Recovering5.8 (2.3-14.3)2.7 (0.9-8.3) Parental alcohol problems One parent0.9 (0.4-1.8)0.8 (0.4-1.5) Both parents4.6 (1.8-11.7)1.7 (0.5-5.5) Adjusted for gender, age, marital status

14. Logistic Regression Predicting Incident AD First-Onset AD OR (95% CI) Network drinking Moderate/Heavy2.0 (1.2-3.1) Recovering4.2 (1.9-8.9) Parental alcohol problems One parent0.89 (0.5-1.4) Both parents3.0 (1.3-6.6) Adjusted for gender, age, marital status

15. Conclusions Network heavy drinking and recovery had effects equal to that of alcohol problems in both parents in predicting first-onset AD, and outweighed the influence of AD in one parent. Future: Does association of recovery in network with remitted AD reflect network selection or network influence? Does recovery spread within network?

16. Acknowledgements K01 AA018146 (McCutcheon, PI) K01 DA027046 (Lessov-Schlaggar, PI) K25 AA017456, R21 AA022074 (Steinley, PI) R01 AA008752, P50 AA 011998, R01 AA012640, R01 DA 014363 (Bucholz, PI)

17. Thank You! Questions? Contact info: Vivia V. McCutcheon, Ph.D. Research Assistant Professor of Psychiatry Washington University School of Medicine, St. Louis, MO vmccutcheon@wustl.edu 314-286-2297