Adolescents’ alcohol use and strength of policy relating to youth access, trading hours and driving under the influence: findings from Australia
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© 2018 Society for the Study of Addiction Aims: To determine (i) whether the strength of Australian alcohol control policy in three domains (youth access, trading hours and drink driving) changed during the 2000s; and (ii) estimate associations between these policies and adolescent drinking after adjusting for television alcohol advertising exposures, alcohol outlet density, alcohol price changes, exposure to negative articles about alcohol in daily newspapers and adult drinking prevalence. Design: Repeated cross-sectional surveys conducted triennially from 2002 to 2011. Multi-level modelling examined the association between alcohol control policies and drinking prevalence after adjusting for covariates. Setting: Four Australian capital cities between 2002 and 2011. Participants: Students aged 12–17 years participating in a triennial national representative school-based survey (sample size range/survey: 9805–13 119). Measurements: Outcome measures were: past month drinking and risky drinking (5+ drinks on a day) in the past 7 days. Policy strength in each of three domains (youth access, trading hours, drink-driving) were the key predictor variables. Covariates included: past 3-month television alcohol and alcohol-control advertising, alcohol outlet density, alcohol price change, negatively framed newspaper alcohol articles, adult drinking prevalence and student demographic characteristics. Findings: During the study period, the strength of youth access policies increased by 10%, trading hours policies by 14% and drink-driving policies by 58%. Past-month and risky drinking prevalence decreased (e.g. past-month: 2002: 47.4% to 2011: 26.3%). Multivariable analyses that included all policy variables and adjusted for year, student and other covariates showed past-month drinking to be associated inversely with stronger trading hours policies [odds ratio (OR) = 0.80, 95% confidence interval (CI) = 0.69, 0.94], but not youth access (OR = 0.92 95% CI = 0.81, 1.04) or drink-driving (OR = 1.00, 95% CI = 0.93, 1.09). Risky drinking was associated inversely with stronger youth access policies (OR = 0.82, 95% CI = 0.69, 0.98), but not trading hours (OR = 0.85, 95% CI = 0.66, 1.09) or drink-driving (OR = 1.02, 95% CI = 0.90, 1.14) policies. Conclusions: Population-directed policies designed to reduce alcohol availability and promotion may reduce adolescents’ alcohol use.
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