Effect of extended trading hours on alcohol sales in Norway: study protocol for a stepped wedge cluster-randomized trial.

BACKGROUND AND AIMS: Norwegian alcohol policy measures include national restrictions on sales hours and a state monopoly on retail sales. A 1-hour extension of sales hours on Saturdays in the monopoly outlets took effect from September 2020. We aim to evaluate whether increase in sales hours results in (1) an increase in alcohol sales in the monopoly outlets and (2) an increase in total alcohol sales, including substitution effects from beer sales in grocery stores. DESIGN: The extension of Saturday sales hours is implemented within a stepped wedge cluster-randomized trial design. Block randomization of 62 of the 66 Norwegian trade districts allocated monopoly outlets to one of three sequences regarding date of implementation. SETTING AND PARTICIPANTS: A total of 228 of 335 in total Norwegian state monopoly outlets are eligible and included. INTERVENTION: The extension of sales hours is from 3 p.m. to 4 p.m. starting on the first Saturday in (i) September 2020, (ii) December 2020 or (iii) March 2021. MEASUREMENTS: Growth rates in monthly alcohol sales, measured in litres of pure alcohol, in eligible monopoly outlets (primary outcome) are obtained together with beverage-specific sales and alcohol sales in grocery stores (secondary outcomes). The observation period is set to 72 months prior to and 24 months after implementation. FINDINGS: Power analyses indicate that this stepped wedge cluster-randomized controlled trial has a power above 90%, even at a high significance level (α = 0.01) and with other conservative model specifications. The planned trial offers a rare opportunity to study possible causal effects of a relatively small change in a widely used alcohol policy measure.

Opioid overdose deaths and the expansion of opioid agonist treatment: a population-based prospective cohort study.

BACKGROUND AND AIM: Effective policies to reduce drug-related overdoses remain a public health priority. We aimed to estimate the causal effects of a national opioid agonist treatment (OAT) program on population level drug fatalities. DESIGN: Population-based prospective cohort study exploiting supply driven variation in treatment uptake across cohort-age groups generated by the introduction and scale-up of a national OAT program. A Poisson difference-in-differences model with an intention-to-treat design was used to assess how treatment uptake altered the age profile of risks and infer treatment effects on drug fatalities. SETTING: Norway, from 1996 through 2016. CASES: The data include a total of 5634 drug-related overdose deaths and cover the introduction of the Norwegian OAT program in 1998 and its initial growth period, reaching 12 286 ever-treated recipients by 2016. MEASUREMENTS: Fatal opioid-related overdoses were defined as deaths with a primary cause assigned an International Classification of Diseases 10th Revision (ICD-10) code F11, or X42, X44, X62 or X64 in combination with T40.0-T40.4. Other non-opioid related fatal overdoses were defined by a primary cause registered as F12, F14, F15, F16 or F19, or X42, X44, X62 or 64 in combination with T40.5-T40.9. FINDINGS: An additional 887 deaths (95% credibility interval [CI] = 265-1563) would have been expected in the absence of OAT, which implies one death avoided per 111 (95% CI = 61-342) treatment-exposed person-years. At scale, the program reduced annual overdose mortality by 27% in 2016 (95% CI = 10%-41%) relative to a no-OAT counterfactual, corresponding to 99 fewer expected fatal overdoses (95% CI = 28-180) in 2016. Analysing fatal opioid-related and other drug overdoses separately found similar numbers for avoided opioid-related fatalities (921, with 95% CI = 373-1526) and no treatment effects on non-opioid related fatalities (-38, with 95% CI = -193-154). CONCLUSION: The introduction and rapid scale-up of a national opioid agonist treatment program in Norway was associated with substantial and plausibly causal reductions in drug fatalities.

A multi criteria decision analysis (MCDA) for evaluating and appraising government policy responses to non medical heroin use.

BACKGROUND: Globally, non-medical heroin use is generating significant public health and social harms, and drug policy about heroin is a controversial field that encompasses many complex issues. Policy responses to illegal heroin markets have varied from militarized eradication of the opium poppy and harsh punishment of users, to more tolerant harm reduction approaches with decriminalized possession and use. METHODS: This paper reports the outcomes of a multi-criteria decision analysis (MCDA) on four generic regulatory regimes of heroin: prohibition, decriminalisation, state control and free market. Invited experts on drug harms, addiction, criminology and drug policy developed a comprehensive set of 27 policy outcome criteria against which these drug policy regimes were assessed. RESULTS: State control of heroin was identified as the preferred policy option although other policy regimes scored better on specific outcome criteria. The free market model scored better than decriminalisation, with absolute prohibition scoring worst on every criterium. The ranking of the regimes was robust to variations in the criterion-specific weights. CONCLUSION: The implications of these findings for the development of future policy responses to heroin and opioids generally are discussed in detail. Despite increasing overdose deaths and an opioid epidemic in North America, prohibition remains the predominant policy approach to heroin regulation at present. It is hoped that the current paper adds to the discussion of finding a valid regulatory alternative.

Assessing the effect of public health information by incentivised risk estimation: An example on Swedish snus.

BACKGROUND: The provision of accurate information on health damaging behaviours and products is a widely accepted and widespread governmental task. It is easily mismanaged. This study demonstrates a simple method which can help to evaluate whether such information corrects recipient risk beliefs. METHODS: Participants assess risks numerically, before and after being exposed to a relevant risk communication. Accuracy is incentivised by awarding financial prizes to answers closest to a pursued risk belief. To illustrate this method, 228 students from the University of Oslo, Norway, were asked to estimate the mortality risk of Swedish snus and cigarettes twice, before and after being exposed to one of three risk communications with information on the health dangers of snus. RESULTS: The data allow us to measure how participants updated their risk beliefs after being exposed to different risk communications. Risk information from the government strongly distorted risk perceptions for snus. A newspaper article discussing the relative risks of cigarettes and snus reduced belief errors regarding snus risks, but increased belief errors regarding smoking. The perceived quality of the risk communication was not associated with decreased belief errors. CONCLUSION: Public health information can potentially make the public less informed on risks about harmful products or behaviours. This risk can be reduced by targeting identified, measurable belief errors and empirically assessing how alternative communications affect these. The proposed method of incentivised risk estimation might be helpful in future assessments of risk communications.

A new approach to formulating and appraising drug policy: A multi-criterion decision analysis applied to alcohol and cannabis regulation.

BACKGROUND: Drug policy, whether for legal or illegal substances, is a controversial field that encompasses many complex issues. Policies can have effects on a myriad of outcomes and stakeholders differ in the outcomes they consider and value, while relevant knowledge on policy effects is dispersed across multiple research disciplines making integrated judgements difficult. METHODS: Experts on drug harms, addiction, criminology and drug policy were invited to a decision conference to develop a multi-criterion decision analysis (MCDA) model for appraising alternative regulatory regimes. Participants collectively defined regulatory regimes and identified outcome criteria reflecting ethical and normative concerns. For cannabis and alcohol separately, participants evaluated each regulatory regime on each criterion and weighted the criteria to provide summary scores for comparing different regimes. RESULTS: Four generic regulatory regimes were defined: absolute prohibition, decriminalisation, state control and free market. Participants also identified 27 relevant criteria which were organised into seven thematically related clusters. State control was the preferred regime for both alcohol and cannabis. The ranking of the regimes was robust to variations in the criterion-specific weights. CONCLUSION: The MCDA process allowed the participants to deconstruct complex drug policy issues into a set of simpler judgements that led to consensus about the results.