Commentary on Cobiac et al. (2009): How to use science to improve alcohol policy?
Article first published online: 8 SEP 2009
© 2009 The Author. Journal compilation © 2009 Society for the Study of Addiction
Volume 104, Issue 10, pages 1656–1657, October 2009
How to Cite
REHM, J. (2009), Commentary on Cobiac et al. (2009): How to use science to improve alcohol policy?. Addiction, 104: 1656–1657. doi: 10.1111/j.1360-0443.2009.02749.x
- Issue published online: 8 SEP 2009
- Article first published online: 8 SEP 2009
Cobiac and colleagues  have convincingly demonstrated that science can help the decision making of alcohol policy in the eve of a global alcohol strategy . They combined sophisticated modelling in the tradition of WHO CHOICE methodology (CHOsing Interventions which are Cost Effective: http://www.who.int/choice/en/; for applications to reduce alcohol-attributable harm see ) with local expertise (such as derived from the Advisory Board) to compare realistic interventions in Australia for reducing alcohol-attributable health harm. This is a remarkable approach, which constitutes a marked improvement over the more intuitive expert weightings of different policy options, without explicitly modelling the different options given current knowledge about both interventions and population composition and predicted growth (e.g. ). While the overall result is important and hopefully will impact alcohol policy, I still see room for improvement.
The most crucial aspect of these calculations is the estimation of exposure in the different scenarios, which the authors derived from a nationally representative survey. Yet, what does this mean? First, such surveys notably underestimate per capita consumption as derived from sales and/or production figures. In Australia  the level of underestimation in recent surveys was typically by more than 40% . Such underestimates are common in high-income countries . In addition, in case of the underlying survey, the participation rate was less than 50% with an estimated response rate of less than 40%. Moreover, heavy drinking populations such as the homeless or institutionalized were excluded by sampling design for the underlying survey, as well as for most others. As few drinkers account for substantial amounts of overall alcohol consumed (concentration of consumption; see e.g. ), the underestimation of overall exposure in such surveys is not surprising. For the conclusions of Cobiac and colleagues  this has two consequences: first, the cost-effectiveness ratios for interventions are all underestimated: alcohol interventions such as those examined are even more cost effective compared to other interventions in the health care field. Consequently, there is an even stronger argument for alcohol policy in the current climate of rationing health care!
For future publications reporting on surveys and survey-based research, particularly those claiming national representativeness, reporting the coverage rate (i.e. the proportion of per capita consumption covered by the survey) should be made standard in any good journal, as only knowledge of this coverage rate allows comparison with other results . Per capita consumption figures for these comparisons for all countries are available calculated in a standardized way from the World Health Organization (Global Information System on Alcohol and Health: http://www.who.int/substance_abuse/activities/gad/en/; see also , for background).
Other assumptions are crucial as well. For instance, Cobiac and colleagues  base their estimates for the effectiveness of a mass media campaign on a meta-analysis , which comes to more optimistic predictions as compared to other evaluations of cost effectiveness . It is thus crucial to discuss the applicability of such transfers from the general intervention literature to the specific situation where alcohol policy is to be applied.
Finally, a lot of the authors' predictions are based on simplified assumptions regarding the temporality of effects. While alcohol certainly causes certain forms of cancer , there is a latency period of 15–20 years. As such, if people reduce consumption or quit drinking, the effect on cancer risk will only be seen two decades later . To illustrate this point there is the famous alcohol reform of Gorbachev wherein the effect of nationwide reductions of alcohol was clearly demonstrated for several groups of diseases, but not for cancer . Temporality is crucial for implementing and evaluating alcohol policy and it should be clear to policy makers which effects may be expected and when, as false expectations about avoidable harm and costs  could be very detrimental to improving public health in the long-term.
In summary, there are exceptional opportunities for improving public health with evidence-based alcohol policies , and as demonstrated by Cobiac and colleagues  applying such interventions in a country like Australia can be cost effective. The practical value of such research to policy makers ultimately depends on the underlying assumptions made, and the more realistic these assumptions can be, the greater the overall credibility of the research as a tool for making alcohol policy.
Declaration of interest
The author has received financial assistance to attend meetings organized by the alcohol industry.
We would like to thank M. Livingstone for help in finding data on the underlying surveys, and F. Kanteres for copy editing the text.
- 4Alcohol: No ordinary commodity. Research and public policy. Oxford: Oxford University Press; 2003., , , , , et al.
- 5Australian Bureau of Statistics: Apparent Consumption of Alcohol, Australia, 2004–05. Canberra: Australian Bureau of Statistics; 2006.