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

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

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


Background
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
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
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
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


Outcomes other drug use and aod use related consequences
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


Analysis
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



Alcohol use
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


Other drug use
Other drug use

DOMC = Drug Of Most Concern

ASSIST = Alcohol, Smoking and Substance Involvement Screening Test


Alcohol and other drug use related consequences
Alcohol and Other Drug use related consequences

SIP-D = Short Inventory of Problems - Drugs


Primary predictor primary outcome
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.


Primary outcome secondary predictors
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.


Secondary predictor of heavy drinking days
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


Primary predictor secondary outcomes
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


Secondary predictor audit c score
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


Summary of findings
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


Limitations
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
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
Acknowledgements

  • CARE Unit,Boston University, Boston Medical Center

    • Mentor : Dr Richard Saitz

    • Debbie Cheng

    • Christine Lloyd-Travaglini

    • Jeffrey Samet

    • Judith Bernstein

    • Tibor Palfai



Stratification by domc
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
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


Regression results second predictor number of heavy drinking days
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


Regression results second predictor audit c score
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


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