Skip to main content

Advertisement

Log in

Differentiating Types of Self-Reported Alcohol Abstinence

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

We contrast three types of abstinence: quit after alcohol associated problems (Q-AP), quit for other reasons (Q-OR), and lifetime abstainer (LTA). We summarized the characteristics of people living with HIV (PLWH), and matched uninfected individuals, by levels of alcohol use and types of abstinence. We then identified factors that differentiate abstinence and determined whether the association with an alcohol biomarker or a genetic polymorphism is improved by differentiating abstinence. Among abstainers, 34% of PLWH and 38% of uninfected were Q-AP; 53% and 53% were Q-OR; and 12% and 10% were LTA. Logistic regression models found smoking, alcohol, cocaine, and hepatitis C increased odds of Q-AP, whereas smoking and marijuana decreased odds of LTA. Differentiating types of abstinence improved association. Q-APs and LTAs can be readily differentiated by an alcohol biomarker and genetic polymorphism. Differentiating type of abstinence may enhance understanding of alcohol health effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Crane HM, Nance RM, Merrill JO, Hutton H, Chander G, McCaul ME, et al. Not all non-drinkers with HIV are equal: demographic and clinical comparisons among current non-drinkers with and without a history of prior alcohol use disorders. AIDS Care. 2017;29(2):177–84.

    PubMed  Google Scholar 

  2. Udo T, Vasquez E, Shaw BA. A lifetime history of alcohol use disorder increases risk for chronic medical conditions after stable remission. Drug Alcohol Depend. 2015;157:68–74.

    PubMed  Google Scholar 

  3. Marees AT, Hammerschlag AR, Bastarache L, de Kluiver H, Vorspan F, van den Brink W, et al. Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use. Drug Alcohol Depend. 2018;188:94–101.

    PubMed  Google Scholar 

  4. Denny JC, Bastarache L, Roden DM. Phenome-wide association studies as a tool to advance precision medicine. Annu Rev Genom Hum Genet. 2016;17:353–73.

    CAS  Google Scholar 

  5. Kirby JC, Speltz P, Rasmussen LV, Basford M, Gottesman O, Peissig PL, et al. PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability. J Am Med Inform Assoc. 2016;23(6):1046–52.

    PubMed  PubMed Central  Google Scholar 

  6. Wei WQ, Denny JC. Extracting research-quality phenotypes from electronic health records to support precision medicine. Genome Med. 2015;7(1):41.

    PubMed  PubMed Central  Google Scholar 

  7. Sanchez-Roige S, Fontanillas P, Elson SL, Gray JC, de Wit H, Davis LK, et al. Genome-wide association study of alcohol use disorder identification test (AUDIT) scores in 20 328 research participants of European ancestry. Addict Biol. 2019;24(1):121–31.

    PubMed  Google Scholar 

  8. Sanchez-Roige S, Palmer AA, Fontanillas P, Elson SL, Adams MJ, Howard DM, et al. Genome-wide association study meta-analysis of the alcohol use disorders identification test (AUDIT) in two population-based cohorts. Am J Psychiatry. 2018;176(2):107–18.

    PubMed  Google Scholar 

  9. Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, et al. AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations. Addiction. 2018;113(12):2214–24.

    PubMed  PubMed Central  Google Scholar 

  10. Saunders JB, Aasland OG, Babor TF, DeLaFuente JR, Grant M. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction. 1993;88:791–804.

    CAS  Google Scholar 

  11. Bradley KA, Bush KR, Epler AJ, Dobie DJ, Davis TM, Sporleder JL, et al. Two brief alcohol-screening tests from the alcohol use disorders identification test (AUDIT): validation in a female Veterans Affairs patient population. Arch Intern Med. 2003;163(7):821–9.

    PubMed  Google Scholar 

  12. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol use disorders identification test. Arch Intern Med. 1998;158(16):1789–95.

    CAS  PubMed  Google Scholar 

  13. Bajunirwe F, Haberer JE, Boum Y 2nd, Hunt P, Mocello R, Martin JN, et al. Comparison of self-reported alcohol consumption to phosphatidylethanol measurement among HIV-infected patients initiating antiretroviral treatment in Southwestern Uganda. PLoS ONE. 2014;9(12):e113152.

    PubMed  PubMed Central  Google Scholar 

  14. Eyawo O, McGinnis KA, Justice AC, Fiellin DA, Hahn JA, Williams EC, et al. Alcohol and mortality: combining self-reported (AUDIT-C) and biomarker detected (PEth) alcohol measures among HIV infected and uninfected. J Acquir Immune Defic Syndr. 2018;77(2):135–43.

    PubMed  PubMed Central  Google Scholar 

  15. Molander RC, Yonker JA, Krahn DD. Age-related changes in drinking patterns from mid- to older age: results from the wisconsin longitudinal study. Alcohol Clin Exp Res. 2010;34(7):1182–92.

    PubMed  PubMed Central  Google Scholar 

  16. Chan KK, Neighbors C, Gilson M, Larimer ME, Alan Marlatt G. Epidemiological trends in drinking by age and gender: providing normative feedback to adults. Addict Behav. 2007;32(5):967–76.

    PubMed  Google Scholar 

  17. Alati R, Lawlor DA, Najman JM, Williams GM, Bor W, O’Callaghan M. Is there really a ‘J-shaped’ curve in the association between alcohol consumption and symptoms of depression and anxiety? Findings from the Mater-University study of pregnancy and its outcomes. Addiction. 2005;100(5):643–51.

    PubMed  Google Scholar 

  18. Plunk AD, Syed-Mohammed H, Cavazos-Rehg P, Bierut LJ, Grucza RA. Alcohol consumption, heavy drinking, and mortality: rethinking the j-shaped curve. Alcohol Clin Exp Res. 2014;38(2):471–8.

    PubMed  Google Scholar 

  19. Zeisser C, Stockwell TR, Chikritzhs T. Methodological biases in estimating the relationship between alcohol consumption and breast cancer: the role of drinker misclassification errors in meta-analytic results. Alcohol Clin Exp Res. 2014;38(8):2297–306.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Fillmore KM, Stockwell T, Chikritzhs T, Bostrom A, Kerr W. Moderate alcohol use and reduced mortality risk: systematic error in prospective studies and new hypotheses. Ann Epidemiol. 2007;17(5 Suppl):S16–23.

    PubMed  Google Scholar 

  21. Griswold MG, Fullman N, Hawley C, Arian N, Zimsen SR, Tymeson HD, Venkateswaran V, Tapp AD, Forouzanfar MH, Salama JS, Abate KH. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2018;392(10152):1015–35.

    Google Scholar 

  22. Ortola R, Garcia-Esquinas E, Lopez-Garcia E, Leon-Munoz LM, Banegas JR, Rodriguez-Artalejo F. Alcohol consumption and all-cause mortality in older adults in Spain: an analysis accounting for the main methodological issues. Addiction. 2018;114(1):59–68.

    PubMed  Google Scholar 

  23. Goulden R. Moderate alcohol consumption is not associated with reduced all-cause mortality. Am J Med. 2016;129(2):180–6.

    CAS  PubMed  Google Scholar 

  24. Gaziano JM, Gaziano TA, Glynn RJ, Sesso HD, Ajani UA, Stampfer MJ, et al. Light-to-moderate alcohol consumption and mortality in the Physicians’ Health Study enrollment cohort. J Am Coll Cardiol. 2000;35(1):96–105.

    CAS  PubMed  Google Scholar 

  25. Xi B, Veeranki SP, Zhao M, Ma C, Yan Y, Mi J. Relationship of alcohol consumption to all-cause, cardiovascular, and cancer-related mortality in U.S. adults. J Am Coll Cardiol. 2017;70(8):913–22.

    PubMed  Google Scholar 

  26. Naimi TS, Stockwell T, Zhao J, Xuan Z, Dangardt F, Saitz R, et al. Selection biases in observational studies affect associations between ‘moderate’ alcohol consumption and mortality. Addiction. 2017;112(2):207–14.

    PubMed  Google Scholar 

  27. Justice AC, McGinnis KA, Tate JP, Xu K, Becker WC, Zhao H, et al. Validating harmful alcohol use as a phenotype for genetic discovery using phosphatidylethanol and a polymorphism in ADH1B. Alcohol Clin Exp Res. 2017;41(5):998–1003.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Justice AC, McGinnis KA, Tate JP, Braithwaite RS, Bryant KJ, Cook RL, et al. Risk of mortality and physiologic injury evident with lower alcohol exposure among HIV infected compared with uninfected men. Drug Alcohol Depend. 2016;161:95–103.

    PubMed  PubMed Central  Google Scholar 

  29. Justice AC, Gordon KS, Skanderson M, Edelman EJ, Akgun KM, Gibert CL, et al. Nonantiretroviral polypharmacy and adverse health outcomes among HIV-infected and uninfected individuals. AIDS. 2018;32(6):739–49.

    PubMed  PubMed Central  Google Scholar 

  30. Viel G, Boscolo-Berto R, Cecchetto G, Fais P, Nalesso A, Ferrara SD. Phosphatidylethanol in blood as a marker of chronic alcohol use: a systematic review and meta-analysis. Int J Mol Sci. 2012;13(11):14788–812.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Afshar M, Burnham EL, Joyce C, Clark BJ, Yong M, Gaydos J, et al. Cut-point levels of phosphatidylethanol to identify alcohol misuse in a mixed cohort including critically ill patients. Alcohol Clin Exp Res. 2017;41(10):1745–53.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Gelernter J, Kranzler HR, Sherva R, Almasy L, Koesterer R, Smith AH, et al. Genome-wide association study of alcohol dependence:significant findings in African- and European-Americans including novel risk loci. Mol Psychiatry. 2014;19(1):41–9.

    CAS  PubMed  Google Scholar 

  33. Bierut LJ, Goate AM, Breslau N, Johnson EO, Bertelsen S, Fox L, et al. ADH1B is associated with alcohol dependence and alcohol consumption in populations of European and African ancestry. Mol Psychiatry. 2012;17(4):445–50.

    CAS  PubMed  Google Scholar 

  34. Li D, Zhao H, Gelernter J. Strong association of the alcohol dehydrogenase 1B gene (ADH1B) with alcohol dependence and alcohol-induced medical diseases. Biol Psychiatry. 2011;70(6):504–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Edenberg HJ. The genetics of alcohol metabolism: role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Res Health. 2007;30(1):5–13.

    PubMed  PubMed Central  Google Scholar 

  36. Bradley KA, DeBenedetti AF, Volk RJ, Williams EC, Frank D, Kivlahan DR. AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res. 2007;31(7):1208–17.

    PubMed  Google Scholar 

  37. Justice AC, Modur SP, Tate JP, Althoff KN, Jacobson LP, Gebo KA, et al. Predictive accuracy of the Veterans Aging Cohort Study index for mortality with HIV infection: a North American cross cohort analysis. J Acquir Immune Defic Syndr. 2013;62(2):149–63.

    PubMed  PubMed Central  Google Scholar 

  38. Tate JP, Justice AC, Hughes MD, Bonnet F, Reiss P, Mocroft A, et al. An internationally generalizable risk index for mortality after one year of antiretroviral therapy. AIDS. 2013;27(4):563–72.

    PubMed  PubMed Central  Google Scholar 

  39. Kunzmann AT, Coleman HG, Huang WY, Berndt SI. The association of lifetime alcohol use with mortality and cancer risk in older adults: a cohort study. PLoS Med. 2018;15(6):e1002585.

    PubMed  PubMed Central  Google Scholar 

  40. Knott CS, Coombs N, Stamatakis E, Biddulph JP. All cause mortality and the case for age specific alcohol consumption guidelines: pooled analyses of up to 10 population based cohorts. BMJ. 2015;350:h384.

    PubMed  PubMed Central  Google Scholar 

  41. Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, Lee KY, Lynch K, Sun N, Concato J, Fiellin DA. AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two U.S. populations. Addiction. 2018;113(12):2214–24.

    PubMed  PubMed Central  Google Scholar 

  42. Gaziano JM, Concato J, Brophy M, Fiore L, Pyarajan S, Breeling J, et al. Million veteran program: a mega-biobank to study genetic influences on health and disease. J Clin Epidemiol. 2016;70:214–23.

    PubMed  Google Scholar 

  43. Clarke TK, Adams MJ, Davies G, Howard DM, Hall LS, Padmanabhan S, et al. Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N = 112 117). Mol Psychiatry. 2017;22(10):1376–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Justice AC, Freiberg MS, Tracy R, Kuller L, Tate JP, Goetz MB, et al. Does an index composed of clinical data reflect effects of inflammation, coagulation, and monocyte activation on mortality among those aging with HIV? Clin Infect Dis. 2012;54(7):984–94.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Drs Gordon and McGinnis had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Gordon and Justice were responsibly for study concept and design, interpretation, drafting of manuscript, and critical revisions. All other authors provided critical review and revisions. Kendall Bryant was the Scientific Collaborator for the Cooperative Agreements. Any expressed views do not represent those of the US Government. This work was supported by the National Institutes of Health: The National Institute on Alcohol Abuse and Alcoholism [Grant Nos. U24-AA020794, U01-AA020790, U10-A013566-completed, U01-AA020795, U01-AA020799, U24-AA022001, and U24-AA022007] and the Veterans Integrated Service Network 4: Mental Illness Research, Education, and Clinical Center.

Disclosure

Dr. Kranzler is a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which was sponsored for the past three years by AbbVie, Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Ethypharm, Indivior, Lilly, Lundbeck, Otsuka, and Pfizer. Drs. Kranzler and Gelernter are named as inventors on PCT patent application #15/878,640 entitled: “Genotype-guided dosing of opioid agonists,” filed January 24, 2018.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kirsha S. Gordon.

Ethics declarations

Conflicts of interest

The author declares that they have no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gordon, K.S., McGinnis, K., Dao, C. et al. Differentiating Types of Self-Reported Alcohol Abstinence. AIDS Behav 24, 655–665 (2020). https://doi.org/10.1007/s10461-019-02638-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-019-02638-x

Keywords

Navigation