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

Abstract

Objective Substance 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. Methods The 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. Results Latent 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. Conclusions Most 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.

Polydrug Definition and Assessment: The State of the Art

“…This way of evaluating polydrug use by means of latent class analysis and taking into account parameters such as frequency of consumption and how substances are combined has been further developed up until today [ 27 , 28 , 29 ] and is considered useful for the detection of high-risk groups when applying selective prevention [ 30 ].…”