Show simple item record

The latent class structure of substance use in US adults 50 years and older

dc.contributor.authorSchepis, Ty S.
dc.contributor.authorMcCabe, Sean Esteban
dc.date.accessioned2021-12-02T02:29:24Z
dc.date.available2023-01-01 21:29:23en
dc.date.available2021-12-02T02:29:24Z
dc.date.issued2021-12
dc.identifier.citationSchepis, Ty S.; McCabe, Sean Esteban (2021). "The latent class structure of substance use in US adults 50 years and older." International Journal of Geriatric Psychiatry 36(12): 1867-1877.
dc.identifier.issn0885-6230
dc.identifier.issn1099-1166
dc.identifier.urihttps://hdl.handle.net/2027.42/170979
dc.description.abstractObjectiveSubstance use rates have increased in adults 50 years and older, and substance use in this population is associated with significant consequences. Given that little is known about their underlying substance use patterns, the objective was to identify latent classes of adults 50 years and older by past‐year substance use, past‐month substance use, and past‐year substance use disorder (SUD) diagnosis.MethodsThe National Survey on Drug Use and Health is an annual nationwide cross‐sectional U.S. survey. Participants were 35,229 civilian, non‐institutionalized U.S. residents, 50 years and older. Past‐year and past‐month alcohol, tobacco, marijuana, heroin, cocaine, methamphetamine use, and opioid, stimulant, and tranquilizer/sedative prescription drug misuse (PDM) were captured, as was past‐year DSM‐IV SUD from these substances. Correlates included mental health, physical health, and healthcare utilization variables.ResultsLatent class analysis indicated four past‐year or past‐month substance use subgroups (Alcohol‐Only, Alcohol‐Tobacco‐Marijuana, Cocaine‐Polydrug, PDM‐Polydrug), with SUD prevalence rising from 3.2% to 17.3%, 68.8%, and 78.5% by past‐year subgroup; similarly, rates of past‐year suicidal ideation increased from 2.1%, to 4.8%, 12.0%, and 20.4% by past‐year subgroup. For SUD, there were three subgroups (Low Nicotine Dependence [ND], High Alcohol Use Disorder, Multiple SUDs). Over 90% of adults were in a low‐risk subgroup (i.e., Alcohol‐Only and Low ND), but members of Cocaine‐Polydrug, PDM‐Polydrug, or Multiple SUDs latent classes had high rates of mental and physical health concerns.ConclusionsMost adults 50 and older have lower risk profiles, but those engaged in PDM or cocaine use are heavily substance‐involved and need screening and likely multi‐disciplinary intervention.Key pointsWe found four similar latent classes for past‐year and past‐month substance use/prescription drug misuse (PDM) in adults 50 years and older: Alcohol‐Only, Alcohol‐Tobacco‐Marijuana, Cocaine‐Polydrug, and PDM‐PolydrugWhile the Alcohol‐Only classes were most of the sample, those in the Cocaine‐Polydrug and the PDM‐Polydrug were particularly high risk for mental and physical health problems, including suicidal ideationFor substance use disorder (SUD), we found three classes: Low Nicotine Dependence, High Alcohol Use Disorder, and Multiple SUDsThe Multiple SUD class was the highest risk group, with the highest rates of mental and physical health concerns
dc.publisherWiley Periodicals, Inc.
dc.publisherCambridge University Press
dc.subject.othersubstance use
dc.subject.othersubstance use disorder
dc.subject.otherprescription drug misuse
dc.subject.otherolder adults
dc.titleThe latent class structure of substance use in US adults 50 years and older
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelGay/Lesbian/Bisexual/Transgender Studies
dc.subject.hlbsecondlevelGeriatrics
dc.subject.hlbsecondlevelInternal Medicine and Specialties
dc.subject.hlbsecondlevelJudaic Studies
dc.subject.hlbsecondlevelPharmacy and Pharmacology
dc.subject.hlbsecondlevelPsychiatry
dc.subject.hlbsecondlevelSocial Work
dc.subject.hlbsecondlevelWomen’s and Gender Studies
dc.subject.hlbtoplevelHealth Sciences
dc.subject.hlbtoplevelHumanities
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/170979/1/gps5605.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/170979/2/gps5605_am.pdf
dc.identifier.doi10.1002/gps.5605
dc.identifier.sourceInternational Journal of Geriatric Psychiatry
dc.identifier.citedreferenceMcCabe SE, Arterberry BJ, Dickinson K, et al. Assessment of changes in alcohol and marijuana abstinence, co‐use, and use disorders among US young adults from 2002 to 2018. JAMA Pediatr. 2021; 175 ( 1 ): 64 – 72.
dc.identifier.citedreferenceSchneider KE, Brighthaupt SC, Winiker AK, Johnson RM, Musci RJ, Linton SL. Characterizing profiles of polysubstance use among high school students in Baltimore, Maryland: a latent class analysis. Drug Alcohol Depend. 2020; 211: 108019.
dc.identifier.citedreferenceSilveira ML, Green VR, Iannaccone R, Kimmel HL, Conway KP. Patterns and correlates of polysubstance use among US youth aged 15‐17 years: wave 1 of the Population Assessment of Tobacco and Health (PATH) Study. Addiction. 2019; 114 ( 5 ): 907 ‐ 916.
dc.identifier.citedreferenceHagenaars JA, McCutcheon AL. Applied Latent Class Analysis. Cambridge University Press; 2002.
dc.identifier.citedreferenceDe Nadai AS, Little TB, McCabe SE, Schepis TS. Diverse diagnostic profiles associated with prescription opioid use disorder in a nationwide sample: one crisis, multiple needs. J Consult Clin Psychol. 2019; 87 ( 10 ): 849 ‐ 858.
dc.identifier.citedreferenceJemberie WB, Padyab M, Snellman F, Lundgren L. A multidimensional latent class Analysis of harmful alcohol use among older adults: subtypes within the Swedish addiction severity index registry. J Addiction Med. 2020; 14 ( 4 ): e89 ‐ e99.
dc.identifier.citedreferenceChoi NG, Marti CN, DiNitto DM. Choi BY. Alcohol use as risk factors for older adults’ emergency department visits: a latent class Analysis. West J Emerg Med. 2015; 16 ( 7 ): 1146 ‐ 1158.
dc.identifier.citedreferenceGrant BF, Chu A, Sigman R, et al. Source and Accuracy Statement: National Epidemiologic Survey on Alcohol and Related Conditions‐III (NESARC‐III). National Institute on Alcohol Abuse and Alcoholism; 2014.
dc.identifier.citedreferenceCenter for Behavioral Health Statistics and Quality. 2016 National Survey on Drug Use and Health: Methodological Resource Book (Section 8, data collection final report). Substance Abuse and Mental Health Services Administration; 2017.
dc.identifier.citedreferenceSubstance Abuse and Mental Health Services Administration. Reliability of Key Measures in the National Survey on Drug Use and Health. Substance Abuse and Mental Health Services Administration; 2010.
dc.identifier.citedreferenceNational Institute of alcohol abuse and alcoholism. NIAAA newsletter, Winter 2004. In. Vol 3. Office of Research Translation and Communications, NIAAA; 2004.
dc.identifier.citedreferenceAmerican Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM‐IV‐TR. 4th ed. American Psychiatric Association; 2000.
dc.identifier.citedreferenceShiffman S, Sayette MA. Validation of the nicotine dependence syndrome scale (NDSS): a criterion‐group design contrasting chippers and regular smokers. Drug Alcohol Dependence. 2005; 79 ( 1 ): 45 ‐ 52.
dc.identifier.citedreferenceShiffman S, Waters A, Hickcox M. The nicotine dependence syndrome scale: a multidimensional measure of nicotine dependence. Nicotine Tob Res. 2004; 6 ( 2 ): 327 ‐ 348.
dc.identifier.citedreferenceCenter for Behavioral Health Statistics and Quality. 2018 National survey on drug use and health public use file codebook. Substance Abuse and Mental Health Services Administration; 2019
dc.identifier.citedreferenceCenter for Behavioral Health Statistics and Quality. Evaluation of imputation methods for the national survey on drug use and health. Substance Abuse and Mental Health Services Administration; 2017.
dc.identifier.citedreferenceZanarini MC, Frankenburg FR. Attainment and maintenance of reliability of axis I and II disorders over the course of a longitudinal study. Compr Psychiatr. 2001; 42 ( 5 ): 369 ‐ 374.
dc.identifier.citedreferenceKessler RC, Barker PR, Colpe LJ, et al. Screening for serious mental illness in the general population. Arch Gen Psychiatr. 2003; 60 ( 2 ): 184 ‐ 189.
dc.identifier.citedreferenceCenter for Behavioral Health Statistics and Quality. National Survey on Drug Use and Health (NSDUH): Summary of Methodological Studies, 1971‐2014. Substance Abuse and Mental Health Services Administration; 2014.
dc.identifier.citedreferenceCenter for Behavioral Health Statistics and Quality. 2016 National Survey on Drug Use and Health: Methodological Resource Book (Section 13: Statistical Inference Report). Substance Abuse and Mental Health Services Administration; 2017.
dc.identifier.citedreferenceCollins LM, Lanza ST. Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. 718. John Wiley & Sons; 2010.
dc.identifier.citedreferenceSchwarz G. Estimating the dimension of a model. Ann Stat. 1978; 6 ( 2 ): 461 ‐ 464.
dc.identifier.citedreferenceKass RE, Raftery AE. Bayes factors. J Am Stat Assoc. 1995; 90 ( 430 ): 773 ‐ 795.
dc.identifier.citedreferenceClark SL, Muthén B. Relating latent class analysis results to variables not included in the analysis. In: 2009.
dc.identifier.citedreferenceMasyn KE. Latent class analysis and finite mixture modeling. In: Little TD, ed. The Oxford handbook of quantitative methods. Oxford University Press; 2013: 551 ‐ 611.
dc.identifier.citedreferenceTucker JS, Huang W, Green HD, Jr., Pollard MS. Patterns of substance use and associations with mental, physical, and social functioning: a latent class Analysis of a national sample of U.S. Adults ages 30‐80. Subst Use Misuse. 2021; 56 ( 1 ): 131 ‐ 139.
dc.identifier.citedreferenceU.S. Preventive Services Task Force. Screening for unhealthy drug use: US preventive Services Task Force recommendation statement. J Am Med Assoc. 2020; 323 ( 22 ): 2301 ‐ 2309.
dc.identifier.citedreferenceO’Malley PM, Bachman JG, Johnston LD. Reliability and consistency in self‐reports of drug use. Int J Addict. 1983; 18: 805 ‐ 824.
dc.identifier.citedreferenceJohnston LD, O’Malley PM. Issues of validity and population coverage in student surveys of drug use. NIDA Res Monogr. 1985; 57: 31 ‐ 54.
dc.identifier.citedreferenceCunningham D, Flicker L, Murphy J, Aldworth J, Myers S, Kennet J. Incidence and impact of controlled access situations on nonresponse. American Association for Public Opinion Research 60th Annual Conference; 2015.
dc.identifier.citedreferenceSubstance Abuse and Mental Health Services Administration. Results from the 2018 national survey on drug use and health: detailed tables. In: Rockville MD, ed. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration; 2019.
dc.identifier.citedreferenceHan BH, Moore AA, Sherman S, Keyes KM, Palamar JJ. Demographic trends of binge alcohol use and alcohol use disorders among older adults in the United States, 2005‐2014. Drug Alcohol Depend. 2017; 170: 198 ‐ 207.
dc.identifier.citedreferenceGrucza RA, Sher KJ, Kerr WC, et al. Trends in adult alcohol use and binge drinking in the early 21st‐century United States: a meta‐analysis of 6 national survey series. Alcohol Clin Exp Res. 2018; 42 ( 10 ): 1939 ‐ 1950.
dc.identifier.citedreferenceHan BH, Sherman S, Mauro PM, Martins SS, Rotenberg J, Palamar JJ. Demographic trends among older cannabis users in the United States, 2006‐13. Addiction. 2017; 112 ( 3 ): 516 ‐ 525.
dc.identifier.citedreferenceSchepis TS, McCabe SE. Trends in older adult nonmedical prescription drug use prevalence: results from the 2002‐2003 and 2012‐2013 National Survey on Drug Use and Health. Addict Behav. 2016; 60: 219 ‐ 222.
dc.identifier.citedreferenceWest NA, Severtson SG, Green JL, Dart RC. Trends in abuse and misuse of prescription opioids among older adults. Drug Alcohol Depend. 2015; 149: 117 ‐ 121.
dc.identifier.citedreferenceSchauer GL, Berg CJ, Kegler MC, Donovan DM, Windle M. Assessing the overlap between tobacco and marijuana: trends in patterns of co‐use of tobacco and marijuana in adults from 2003‐2012. Addict Behav. 2015; 49: 26 ‐ 32.
dc.identifier.citedreferenceHan BH, Palamar JJ. Trends in cannabis use among older adults in the United States, 2015‐2018. JAMA Intern Med. 2020; 180 ( 4 ): 609 ‐ 611.
dc.identifier.citedreferenceSchepis TS, Teter CJ, Simoni‐Wastila L, McCabe SE. Prescription tranquilizer/sedative misuse prevalence and correlates across age cohorts in the US. Addict Behav. 2018; 87: 24 ‐ 32.
dc.identifier.citedreferenceHan BH, Palamar JJ. Marijuana use by middle‐aged and older adults in the United States, 2015‐2016. Drug Alcohol Depend. 2018; 191: 374 ‐ 381.
dc.identifier.citedreferenceHan BH, Moore AA, Ferris R, Palamar JJ. Binge drinking among older adults in the United States, 2015 to 2017. J Am Geriatr Soc. 2019; 67 ( 10 ): 2139 ‐ 2144.
dc.identifier.citedreferenceSchepis TS, McCabe SE, Teter CJ. Sources of opioid medication for misuse in older adults: results from a nationally representative survey. Pain. 2018; 159 ( 8 ): 1543 ‐ 1549.
dc.identifier.citedreferenceChoi NG, DiNitto DM, Marti CN. Alcohol and other substance use, mental health treatment use, and perceived unmet treatment need: comparison between baby boomers and older adults. Am J Addict. 2015; 24 ( 4 ): 299 ‐ 307.
dc.identifier.citedreferenceMaree RD, Marcum ZA, Saghafi E, Weiner DK, Karp JF. A systematic review of opioid and benzodiazepine misuse in older adults. Am J Geriatr Psychiatr. 2016; 24 ( 11 ): 949 ‐ 963.
dc.identifier.citedreferenceWu LT, Blazer DG. Substance use disorders and psychiatric comorbidity in mid and later life: a review. Int J Epidemiol. 2014; 43 ( 2 ): 304 ‐ 317.
dc.identifier.citedreferenceBlow FC, Barry KL. Alcohol and substance misuse in older adults. Curr Psychiatr Rep. 2012; 14 ( 4 ): 310 ‐ 319.
dc.identifier.citedreferenceSchepis TS, Ford JA, Wastila L, McCabe SE. Opioid‐involved prescription drug misuse and poly‐prescription drug misuse in U.S. older adults. Aging Ment Health. in press.
dc.identifier.citedreferencePark TW, Saitz R, Ganoczy D, Ilgen MA, Bohnert AS. Benzodiazepine prescribing patterns and deaths from drug overdose among US veterans receiving opioid analgesics: case‐cohort study. Br Med J. 2015; 350: h2698.
dc.identifier.citedreferenceJones JD, Mogali S, Comer SD. Polydrug abuse: a review of opioid and benzodiazepine combination use. Drug Alcohol Depend. 2012; 125 ( 1‐2 ): 8 ‐ 18.
dc.identifier.citedreferenceTucker JS, Huang W, Green HD, Jr., Pollard MS. Patterns of substance use and associations with mental, physical, and social functioning: a latent class analysis of a national sample of U.S. adults ages 30‐80. Subst Use Misuse. in press.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.