OBJECTIVE: Adult cannabis use has increased in the United States since 2002, particularly after 2007, contrasting with stable/declining trends among youth. We investigated whether specific age groups disproportionately contributed to changes in daily and nondaily cannabis use trends. METHOD: Participants ages 12 and older (N = 722,653) from the 2002-2014 National Survey on Drug Use and Health reported past-year cannabis use frequency (i.e., daily = ≥300 days/year; nondaily = 1-299 days/year; none). Multinomial logistic regression was used to model change in past-year daily and nondaily cannabis use prevalence by age group (i.e., 12-17, 18-25, 26-34, 35-49, 50-64, ≥65), before and after 2007. Multinomial logistic regressions estimated change in relative odds of cannabis use frequency over time by age, adjusting for other sociodemographics. RESULTS: Daily cannabis use prevalence decreased in ages 12-17 before 2007 and increased significantly across adult age categories only after 2007. Increases did not differ significantly across adult ages 18-64 and ranged between 1 and 2 percentage points. Nondaily cannabis use decreased among respondents ages 12-25 and 35-49 before 2007 and increased across adult age categories after 2007, particularly among adults 26-34 (i.e., 4.5 percentage points). Adjusted odds of daily versus nondaily cannabis use increased after 2007 for ages 12-64. CONCLUSIONS: Increases in daily and nondaily cannabis use prevalence after 2007 were specific to adult age groups in the context of increasingly permissive cannabis legislation, attitudes, and lower risk perception. Although any cannabis use may be decreasing among teens, relative odds of more frequent use among users increased in ages 12-64 since 2007. Studies should assess not only any cannabis use, but also frequency of use, to target prevention efforts of adverse effects of cannabis that are especially likely among frequent users.
OBJECTIVE: Adult cannabis use has increased in the United States since 2002, particularly after 2007, contrasting with stable/declining trends among youth. We investigated whether specific age groups disproportionately contributed to changes in daily and nondaily cannabis use trends. METHOD:Participants ages 12 and older (N = 722,653) from the 2002-2014 National Survey on Drug Use and Health reported past-year cannabis use frequency (i.e., daily = ≥300 days/year; nondaily = 1-299 days/year; none). Multinomial logistic regression was used to model change in past-year daily and nondaily cannabis use prevalence by age group (i.e., 12-17, 18-25, 26-34, 35-49, 50-64, ≥65), before and after 2007. Multinomial logistic regressions estimated change in relative odds of cannabis use frequency over time by age, adjusting for other sociodemographics. RESULTS: Daily cannabis use prevalence decreased in ages 12-17 before 2007 and increased significantly across adult age categories only after 2007. Increases did not differ significantly across adult ages 18-64 and ranged between 1 and 2 percentage points. Nondaily cannabis use decreased among respondents ages 12-25 and 35-49 before 2007 and increased across adult age categories after 2007, particularly among adults 26-34 (i.e., 4.5 percentage points). Adjusted odds of daily versus nondaily cannabis use increased after 2007 for ages 12-64. CONCLUSIONS: Increases in daily and nondaily cannabis use prevalence after 2007 were specific to adult age groups in the context of increasingly permissive cannabis legislation, attitudes, and lower risk perception. Although any cannabis use may be decreasing among teens, relative odds of more frequent use among users increased in ages 12-64 since 2007. Studies should assess not only any cannabis use, but also frequency of use, to target prevention efforts of adverse effects of cannabis that are especially likely among frequent users.
Authors: Hannah Carliner; Pia M Mauro; Qiana L Brown; Dvora Shmulewitz; Reanne Rahim-Juwel; Aaron L Sarvet; Melanie M Wall; Silvia S Martins; Geoffrey Carliner; Deborah S Hasin Journal: Drug Alcohol Depend Date: 2016-11-11 Impact factor: 4.492
Authors: Richard A Grucza; Arpana Agrawal; Melissa J Krauss; Jahnavi Bongu; Andrew D Plunk; Patricia A Cavazos-Rehg; Laura J Bierut Journal: J Am Acad Child Adolesc Psychiatry Date: 2016-04-07 Impact factor: 8.829
Authors: Tina Djernis Gundersen; Niels Jørgensen; Anna-Maria Andersson; Anne Kirstine Bang; Loa Nordkap; Niels E Skakkebæk; Lærke Priskorn; Anders Juul; Tina Kold Jensen Journal: Am J Epidemiol Date: 2015-08-16 Impact factor: 4.897
Authors: Carlos Blanco; Deborah S Hasin; Melanie M Wall; Ludwing Flórez-Salamanca; Nicolas Hoertel; Shuai Wang; Bradley T Kerridge; Mark Olfson Journal: JAMA Psychiatry Date: 2016-04 Impact factor: 21.596
Authors: Reto Auer; Eric Vittinghoff; Kristine Yaffe; Arnaud Künzi; Stefan G Kertesz; Deborah A Levine; Emiliano Albanese; Rachel A Whitmer; David R Jacobs; Stephen Sidney; M Maria Glymour; Mark J Pletcher Journal: JAMA Intern Med Date: 2016-03 Impact factor: 44.409
Authors: Lesia M Ruglass; Adriana Espinosa; Skye Fitzpatrick; M Kamran Meyer; Kechna Cadet; Alexander Sokolovsky; Kristina M Jackson; Helene R White Journal: Subst Use Misuse Date: 2019-10-01 Impact factor: 2.164
Authors: Shadiya L Moss; Julian Santaella-Tenorio; Pia M Mauro; Katherine M Keyes; Silvia S Martins Journal: Addiction Date: 2018-12-18 Impact factor: 6.526
Authors: Shannon Gravely; Pete Driezen; Danielle M Smith; Ron Borland; Eric N Lindblom; David Hammond; Ann McNeill; Andrew Hyland; K Michael Cummings; Gary Chan; Mary E Thompson; Christian Boudreau; Nadia Martin; Janine Ouimet; Ruth Loewen; Anne C K Quah; Maciej L Goniewicz; James F Thrasher; Geoffrey T Fong Journal: Int J Drug Policy Date: 2020-04-16
Authors: Morgan M Philbin; Pia M Mauro; Julian Santaella-Tenorio; Christine M Mauro; Elizabeth N Kinnard; Magdalena Cerdá; Silvia S Martins Journal: Int J Drug Policy Date: 2019-01-23