Literature DB >> 32949418

Trends in cannabis use and attitudes toward legalization and use among Australians from 2001-2016: an age-period-cohort analysis.

Navdep Kaur1, Katherine M Keyes1, Ava D Hamilton1, Cath Chapman2, Michael Livingston3, Tim Slade2, Wendy Swift4.   

Abstract

BACKGROUND AND AIMS: Changes in cannabis legalization and availability in Australia necessitate monitoring use and attitudes. We estimated age-period-cohort effects of past-year cannabis use and attitudes toward criminalization and legalization.
DESIGN: Analysis of six waves of the Australian National Drug Strategy Household Survey (NDSHS) every 3 years (2001-2016). SETTING AND PARTICIPANTS: The study was nationally representative of Australian households using multistage random sampling, totaling 145 168 respondents 18-79 years old. Data were collected using telephone, face-to-face, and drop-and-collect. Sample sizes per analysis varied based on data availability (~107 000-127 000 per model). MEASUREMENTS: Six waves of data for past-year cannabis use (by sex and education), attitudes toward criminalization and legalization.
FINDINGS: Past-year cannabis use decreased in young adults ages 18-35 from 2001-2016 (25.1%-18.6%) and increased in middle adults ages 36-55 (8.6%-10.1%) and older adults ages 56-79 (0.6%-3.0%). We observed a positive period effect and negative cohort effect for recent cohorts for past-year use (e.g. 1955 cohort had 1.41 (95% CI: [1.11, 1.70]) increased log odds vs. 1998 cohort had -2.86 (95% CI: [-3.17, -2.55]) increased log odds) compared with the mean across years. Results were consistent by sex and varied by education. We observed a negative period effect for criminalization favorability (0.14 (95% CI: [0.003, 0.28]) increased log odds in 2001 vs. -0.31 (95% CI: [-0.45, -0.17]) increased log odds in 2016) and positive cohort effect for recent cohorts. Last, we observed a positive period effect for legalization support (-0.03 (95% CI: [-0.20, 0.14]) increased log odds in 2001 vs. 0.38 (95% CI: [0.22, 0.55]) increased log odds in 2016) and negative cohort effect for recent cohorts.
CONCLUSION: Cannabis use appears to be increasing in Australia among adults over 35, while decreasing among adolescents and young adults. Legalization support also appears to have been increasing since 2007, signaling discordance between use and attitudes among adolescents and young adults, and potentially predicting increases in use over time. © 2020 Society for the Study of Addiction.

Entities:  

Keywords:  Age-period-cohort; Australia; cannabis; cannabis policy; legalization; time trends, Australia

Mesh:

Year:  2020        PMID: 32949418      PMCID: PMC7972999          DOI: 10.1111/add.15271

Source DB:  PubMed          Journal:  Addiction        ISSN: 0965-2140            Impact factor:   6.526


  38 in total

1.  The epidemiology of cannabis use and cannabis-related harm in Australia 1993-2007.

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4.  An age-period-cohort analysis of cannabis use prevalence and frequency in Germany, 1990-2009.

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Review 6.  Evidence for Sex Convergence in Prevalence of Cannabis Use: A Systematic Review and Meta-Regression.

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7.  Age, period, and cohort effects in synthetic cannabinoid use among US adolescents, 2011-2015.

Authors:  Katherine M Keyes; Caroline Rutherford; Ava Hamilton; Joseph J Palamar
Journal:  Drug Alcohol Depend       Date:  2016-07-28       Impact factor: 4.492

8.  Past-month cannabis use among U.S. individuals from 2002-2015: An age-period-cohort analysis.

Authors:  Devika Chawla; Yang C Yang; Tania A Desrosiers; Daniel J Westreich; Andrew F Olshan; Julie L Daniels
Journal:  Drug Alcohol Depend       Date:  2018-10-17       Impact factor: 4.492

9.  Correct knowledge of medical cannabis legal status in one's own state: Differences between adolescents and adults in the United States, 2004-2013.

Authors:  Pia M Mauro; Julian Santaella-Tenorio; Alexander S Perlmutter; Deborah S Hasin; Christine M Mauro; Silvia S Martins
Journal:  Addict Behav       Date:  2018-07-30       Impact factor: 3.913

10.  The hierarchical age-period-cohort model: Why does it find the results that it finds?

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Journal:  Qual Quant       Date:  2017-02-24
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  2 in total

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