Unhealthy alcohol use in other drug users identified by screening in primary care

1. Unhealthy alcohol use in other drug users identified by screening in primary care Christine Maynié-François Debbie Cheng Jeffrey Samet Christine Lloyd-Travaglini Tibor Palfai Judith Bernstein Richard Saitz Secondary analysis of ASPIRE trial data Funded by NIDA 1 R01 DA025068 with support from SAMHSA. Clinicaltrials.gov ID NCT00876941

2. Background • Alcohol use common in other drug users • Negative impact on • Other drug use • Alcohol and other drug (AOD) use consequences (unsafe sex, injury, fatal overdoses) • Most studies on patients in substance abuse treatment, community • Few data on primary care patients, identified by screening

3. Aims • Primary: Describe alcohol use in patients screening positive for other drug use in primary care • Secondary: Evaluate the association between unhealthy alcohol use and • Other drug use • AOD-use related consequences

4. Hypothesis In this primary care cohort of patients screening positive for drug use, there will be an association between unhealthy alcohol use and drug use/consequences.

5. Methods • Cross-sectional design • Secondary analysis • Cohort recruited by systematic screening in primary care for randomized controlled trial (ASPIRE study) • Main eligibility criteria : ASSIST drug-specific score ≥2 (once or twice over past 3 months) ASPIRE = Assessing Screening Plus brief Intervention’s Resulting Efficacy to stop drug use. ASSIST = Alcohol, Smoking and Substance Involvement Screening Test

6. Predictors: unhealthy alcohol use Primary Any past month heavy drinking day (HDD) (≥4♀ or ≥5♂ drinks in a day) Secondary Secondary • AUDIT-C score (past year) • 0 = abstinent • 1- 2/3 (♀/♂)= low-risk • 3/4 - 9 (♀/♂) = risky use • 10+ = probable dependence • Number of past month HDD • None / 1-4 / >4 AUDIT-C = Alcohol Use Disorder Identification Test – Consumption

7. Outcomes:other drug use and AOD use related consequences Primary Past month # days use Drug Of Most Concern = DOMC (determined by patient) Secondary: Use Secondary: Consequences • Past 3 months: • Injection drug use • -Use of more than one drug • - Any drug dependence (ASSIST 27+) • Past 3 months: • Drug use related problems • (SIP-D score) • -Unsafe sex • -Injury • -Arrest/incarceration ASSIST = Alcohol, Smoking and Substance Involvement Screening Test SIP-D = Short Inventory of Problems - Drugs

8. Analysis • Negative binomial regression models for count outcomes • Logistic regression models for binary outcomes • Adjusted for • Demographics : age, sex, race/ethnicity, employment, homelessness, partner, children • Psychiatric co morbidity: PHQ-9 (depression symptoms) PHQ-9 = Patient Health Questionnaire 9 items

9. Demographics

10. Alcohol use Heavy drinking day = ≥4♀ or ≥5♂ drinks in a day AUDIT-C = Alcohol Use Disorder Identification Test – Consumption DOMC = Drug Of Most Concern

11. Other drug use DOMC = Drug Of Most Concern ASSIST = Alcohol, Smoking and Substance Involvement Screening Test

12. Alcohol and Other Drug use related consequences SIP-D = Short Inventory of Problems - Drugs

13. Primary predictor/ Primary outcome DOMC = Drug Of Most Concern Result given in adjusted IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9.

14. Primary outcome Secondary predictors HDD = Heavy Drinking Day AUDIT-C = Alcohol Use Disorder Identification Test – Consumption Results given in adjusted IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9.

15. Secondary predictor #of heavy drinking days • No association found with • Injection Drug Use • Any injury Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01 ***p<0.0001

16. Primary predictor Secondary outcomes • No significant association with: • Injection Drug Use • Any injury • Any injury with Alcohol or Drug intake 2 hours prior • Any arrest or incarceration Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01

17. Secondary predictor AUDIT-C score • No significant association found with: • Injection Drug Use • Use of more than one drug • Any unsafe sex • Any injury (+ with Alcohol or Drug intake 2 hours prior) • Any arrest or incarceration Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01

18. Summary of findings • Unhealthyalcohol use (UAU) common in patients screening positive for drug use in primary care. • Unable to detect an association between UAU and # days use DOMC (primary) • UAU associated with more severe other drug use and consequences. • More of these associations detected when using # of heavy drinking days as the marker for UAU

19. Limitations • External validity out of urban hospital-based primary care • No reason to think that the association between unhealthy alcohol use and outcomes wouldn’t be the same in other settings • Separate role of alcohol and other drugs uncertain on AOD use related consequences • Role of alcohol on unsafe sex • No exploration of synergistic effect

20. Implications • Attention should be given to unhealthy alcohol use in people identified as other drug users in primary care (screening?) • Past month heavy drinking days appear to be a useful marker for other drug use severity and consequences

21. Acknowledgements • CARE Unit,Boston University, Boston Medical Center • Mentor : Dr Richard Saitz • Debbie Cheng • Christine Lloyd-Travaglini • Jeffrey Samet • Judith Bernstein • Tibor Palfai

23. Demographics

24. Stratification by DOMC • Bivariate analysis • A few significant results with DOMC cocaine • 1+ HDD / Any unsafe sex • AUDIT-C score / ASSIST 27+ • AUDIT-C / # days use DOMC: • Opioids: with low risk / unhealthy alcohol use (mean 10 days) • Cocaine: with alcohol dependence (mean 8 days) • MJ: with abstinence (mean 19 days)

25. Regression results: Primary predictor= Any heavy drinking day Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01

26. Regression results: Second. predictor= Number of heavy drinking days Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01 ***p<0.0001

27. Regression results: Second.predictor = AUDIT-C score Results given in adjusted OR or IRR. Model adjusted for baseline covariates: age, sex, race/ethnicity, employment, tobacco use, homelessness, partner, children and PHQ-9. *p<0.05 **p<0,01