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

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

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

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.

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

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

Outcomes: other drug use and AOD use related consequences Past month # days use Drug Of Most Concern = DOMC (determined by patient) Primary Past 3 months: -Injection drug use -Use of more than one drug - Any drug dependence (ASSIST 27+) Secondary: UseSecondary: Consequences 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

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

Demographics Demographics, N=589 Age, mean (SD)41 (4) Male68 % Race/ethnicty Black or African-American63 % Hispanic or Latino11 % White20 % 1+ night on the street or in shelter (past 3 months)16 % Unemployed72 %

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 Heavy drinking days (past month), N=589 Any past month heavy drinking day48 % # HDD among heavy drinkers, mean (SD)9 (9) AUDIT-C score (past year) AUDIT-C 0 (abstinence)11 % AUDIT-C 1 – 2/3 (♀/♂) (low risk use)26 % AUDIT-C 3/4 – 9 (♀/♂) (risky use)44 % AUDIT-C 10+ (probable dependence)19 %

Other drug use Other drug use, N=589 Past month # days use Drug Of Most Concern, mean (SD) 12 (13) Marijuana as DOMC63 % Opioids as DOMC16 % Cocaine as DOMC18 % Injection Drug Use (past 3 months)11 % Use of more than one drug (past 3 months)31 % Any drug dependence ASSIST 27+ (past 3 months) 16 % DOMC = Drug Of Most Concern ASSIST = Alcohol, Smoking and Substance Involvement Screening Test

AOD use related consequences (past 3 months), N=589 Drug use related problems (SIP-D), mean (SD)13 (11) Any unsafe sex51 % # of times unsafe sex, mean (SD)16 (39) Any injury 15 % Of those, injuries with alc/drg 2 hours prior51 % Any arrest / incarceration6 % Alcohol and Other Drug use related consequences SIP-D = Short Inventory of Problems - Drugs

Primary predictor/ Primary outcome # days use DOMC Any heavy drinking day 1.00 [ ] 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.

Primary outcome Secondary predictors # Days use DOMC #HDD : 1-3 vs [ ] #HDD : 4+ vs [ ] AUDIT-C : 1-2/3 vs [ ] AUDIT-C : 3/4 -9 vs [ ] AUDIT-C : 10+ vs [ ] 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.

Secondary predictor #of heavy drinking days More than 1 drug Any drg dependce (ASSIST 27+) #HDD 1-4 vs [ ]* 1.19 [ ] #HDD >4 vs [ ]* 2.48 [ ]** Any unsafe sex # times unsafe sex Any injury w/ AlcDrg 2 hours prior Any arrest / incarceration Drug related pbs (SIP-D) #HDD 1-4 vs [ ]* 1.33 [ ] 1.16 [ ] 0.98 [ ] 1.10 [ ] #HDD >4 vs [ ]* 2.67 [ ]** 2.22 [ ]* 2.33 [ ]* 1.87 [ ]*** 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< No association found with - Injection Drug Use - Any injury

Primary predictor Secondary outcomes More than 1 drug Any drug dependence (ASSIST 27+) Any unsafe sex # times unsafe sex Drug use related pbs (SIP-D) Any heavy drinking day 1.64 [ ]* 1.74 [ ]* 1.90 [ ]** 1.87 [ ]** 1.46 [ ]** 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 No significant association with: - Injection Drug Use - Any injury - Any injury with Alcohol or Drug intake 2 hours prior - Any arrest or incarceration

Secondary predictor AUDIT-C score Any drg dependce (ASSIST 27+) # times unsafe sexDrug related pbs (SIP-D score) AUDIT-C 1-2/3 vs [ ]1.02 [ ]0.94 [ ] AUDIT-C 3/4-9 vs [ ]1.40 [ ]1.07 [ ] AUDIT-C 10+ vs [ ]**2.82 [ ]**1.94 [ ]** 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 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

Summary of findings Unhealthy alcohol 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

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

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

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

Demographics Demographics, N=589 Age, mean (SD)41 (4) Male68 % Race/ethnicty Black or African-American63 % Hispanic or Latino11 % White20 % 1+ night on the street or in shelter (past 3 months)16 % Unemployed72 % Partner57 % Children65 %

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)

Regression results: Primary predictor = Any heavy drinking day IDUMore than 1 drugASSIST 27+ Any heavy drinking day 0.99 [ ] 1.64 [ ]* 1.74 [ ]* Any unsafe sex # times unsafe sex IRR Any injury Any injury w/ AlcDrg 2 hours prior Any arrest / incarceration SIP-D score IRR Any heavy drinking day 1.90 [ ]** 1.87 [ ]** 0.91 [ ] 1.64 [ ] 1.59 [ ] 1.46 [ ]** 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

Regression results: Second. predictor = Number of heavy drinking days IDUMore than 1 drugASSIST 27+ #HDD 1-4 vs [ ] 1.65 [ ]* 1.19 [ ] #HDD >4 vs [ ] 1.62 [ ]* 2.48 [ ]** Any unsafe sex # times unsafe sex Any injuryAny injury w/ AlcDrg 2 hours prior Any arrest / incarceration SIP-D score #HDD 1-4 vs [ ]* 1.33 [ ] 0.71 [ ] 1.16 [ ] 0.98 [ ] 1.10 [ ] #HDD >4 vs [ ]* 2.67 [ ]** 1.16 [ ] 2.22 [ ]* 2.33 [ ]* 1.87 [ ]*** 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

Regression results: Second.predictor = AUDIT-C score IDUMore than 1 drugASSIST 27+ AUDIT-C < 3/4 vs [ ] 0.86 [ ] 1.43 [ ] AUDIT-C 3/4+ vs [ ] 1.35 [ ] 1.26 [ ] AUDIT-C 10+ vs [ ] 1.49 [ ] 3.79 [ ]** Any unsafe sex # times unsafe sex Any injuryAny injury w/ AlcDrg 2 hours prior Any arrest / incarceration SIP-D score AUDIT-C < 3/4 vs [ ] 1.02 [ ] 1.02 [ ] 0.60 [ ] 0.78 [ ] 0.94 [ ] AUDIT-C 3/4+ vs [ ] 1.40 [ ] 0.85 [ ] 0.57 [ ] 1.26 [ ] 1.07 [ ] AUDIT-C 10+ vs [ ] 2.82 [ ]** 1.00 [ ] 1.57 [ ] 2.54 [ ] 1.94 [ ]** 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