Wednesday, December 29, 2010
Why does alcohol have such a powerful grip on us? How much of our relationship with this drug is written in our genes? What are the real dangers of our children drinking too young?
Addiction expert John Marsden, who likes a drink, makes a professional and personal exploration of our relationship with alcohol. He undergoes physical and neurological examinations to determine its impact, and finds out why some people will find it much harder than others to resist alcohol. Even at the age of 14 there may be a way of determining which healthy children will turn into addicts.
John experiments with a designer drug being developed that hopes to replicate all the benefits of alcohol without the dangers. Could this drug replace alcohol in the future?
Addiction expert John Marsden explores our relationship with alcohol. As part of his investigation he looks at work being done to examine how monkeys form the same relationships with alcohol as humans.
The Center for Disease Control and Prevention estimates that 34% of young adults (18-24 year olds) regularly consume "energy drinks" - infusions designed to boost pep through a tasty mixture high in sugar and caffeine. After some inventive youths showed how energy drinks could juice up depressed spirits, by, for example, giving ho-hum whisky a shot of Red Bull, caffeinated alcoholic beverages have become an increasingly popular drink among young adults. Beginning in 2002, beverage manufacturers tried to capitalise on this trend by producing ready-made "alcohol energy drinks" (AEDs). The undertaking has been a remarkable success for the producers of the almost 30 brands of AEDs which subsequently flooded local Circle Ks and 7-Elevens. The US beer market: impact databank review and forecast (2009) reported a six-year 67-fold increase in AED sales.
To coax youths into replacing their Monsters or Jägerbombs (1 shot of Jägermeister and Red Bull) with the pre-made AEDs, manufacturers have had to use marketing, product design and pricing strategies. Like their sober brethren, AEDs are packaged with psychedelic patterns whose dancing neon lizards give a trippy effect before one sip has been swallowed; they have more alcohol content per ounce than your average beer but a sweet smooth taste thanks to the addition of sugar, guarana, glucuronolactone, taurine and wormwood. Although sold in similarly large 24 oz portions, they are cheaper than dry energy drinks.
All of these enterprising efforts were paying off for manufacturers Charge Beverages Corp., New Century Brewing Co., LLC, Phusion Projects, LLC, and United Brands Company Inc. until last week when the US Food and Drug Administration (FDA) delivered the warning that the production and sale of caffeinated beverages was in violation of the Federal Food, Drug, and Cosmetic Act (FFDCA). The companies were given 15 days to respond and were told that, under the FFDCA, continued sale of products like Moonshot and Four Loko could result in product seizure by the FDA who deems caffeine an "unsafe food additive" when combined with malt liquor. Five US states (Mass, Michigan, Utah, Oklahoma, Washington) have already responded by banning sales of the infringing products.
The FDA's denunciatory verdict on AEDs comes after a year-long review of the scientific literature and discussions with expert panels about the health hazards associated with caffeine-infused alcohol. From the information gathered, the administration reached two conclusions: 1) compared to other popular alcoholic beverages, AEDs are associated with an increased rate of binge drinking (5 or more drinks per occasion for males) and consequent health risks, including mortality, and 2) the increased risk is due to the action of the stimulant caffeine which masks the physiomotor impairments induced by alcohol.
Though this announcement has now been well-circulated through the news cycle most reports have missed the most remarkable side of the story. Risks resulting from human behavior are invariably difficult to study. Consider the long slog to show the link between tobacco consumption and lung cancer. Despite the compelling 1950 JAMA report of Ernst Wynder and Evarts Graham, frankly entitled "Tobacco Smoking as a Possible Etiologic Factor in Bronchiogenic Carcinoma: A Study of 684 Proven Cases", it took numerous confirmatory human and animal trials over 14 years before the first Surgeon General's damning report against smoking appeared.
Put in this context, the swiftness and definitiveness of the FDA's verdict on caffeine is truly remarkable. In fact, the speed with which this consensus was reached would only seem possible for evidence based on a randomized trial since the selection bias in an observational study would have difficulty excluding the possibility that excessive drinkers simply have a preference for AEDs. In fact, the O'Brien survey (2008) of North Carolina undergraduates found that, compared to alcohol drinkers who did not mix their spirits with energy drinks, AED drinkers were more likely to be male and a member of a fraternity, a profile not incommensurate with intemperance.
Would a randomised study to address the binge-drinking risk of AED use be possible? And, even supposing that there were no ethical concerns about randomly assigning young adults toad libitum drinking of alcohol, how could such a study isolate the role of caffeine apart from sugar and other additives? How could a laboratory mimic the naturalistic setting of a frat party? What strategy could investigators use to assure an unbiased sample? Recruitment fliers seeking "STUDENTS WILLING TO DRINK FOR RESEARCH" would simply not do.
The study of Ferreira and colleagues (2006) came as close to an ideal experimental design of AED and binge drinking as is ethically conceivable. The researchers recruited 26 young males with no history of substance abuse or excessive use of energy drinks. On three separate occasions they were given a mixture vodka, Red Bull, or vodka combined with Red Bull. The volume and taste per kilogram body weight was fixed with the addition of water and a diet fruit juice. The sample was divided into a low and high dose alcohol condition. Before and after each session, alcohol intoxication was evaluated with a measure of breath alcohol concentration, subjective assessment of somatic states and objective measures of motor coordination. The researchers found that the concentration of alcohol in the breath during the period before and for 2.5 hours after ingestion was not changed with the addition of energy drink. Also, motor function and visual reaction time was similarly impaired 30 minutes after consumption, both the alcohol only (AO) and alcohol + energy (AE) subjects took a comparably longer time on average to place 25 pegs in a pegboard (motor coordination) and to respond to the presentation of a yellow square on a computer screen (visual reaction time) than at baseline. All of this evidence suggests that the addition of a sugary, caffeinated beverage does not impact the physiological effects of alcohol.
But what about the risk of a binge? The researchers did not allow subjects to drink to their limit so binging could not be directly observed. Instead, Ferreira and colleagues measured the perception of drunkenness, which would enable them to infer whether AEDs created a binge-inducing state by diminishing the perception of drunkenness. Of 18 subjective assessments of somatic states measured 30 minutes after alcohol ingestion, the AE group differed from the AO group only in reported alterations of sight. On a visual analog scale from 0 to 100, with 0 being no impairment and 100 maximum impairment, AEs reported an average of 8 and AOs an average of 12. Although the difference was significant based on an analysis of variance, which took into account the three treatment groups, two dose levels, and repeated measures, there was no adjustment for multiple testing. With a type I error rate of 5% for the statistical tests made with each questionnaire item there was a 60% chance that at least one significant finding would be incorrectly found among the 18 items which makes the single difference found hardly surprising.
Despite the high quality of its design, the Ferreiara experimental study did not make a strong case that AED diminishes the perception of intoxication. Perhaps with a more sensitive questionnaire of somatic states more differences between the AOs and AEs would have emerged. Still, even with this improvement, an alternative design would be needed to determine whether the stimulating effects of caffeine alone encourage higher consumption or if one of the other additives of energy drinks is the causal factor. If youths are consuming more alcohol as AEDs because these products are tastier than standard beer or spirits, the FDA's censure of caffeine is unlikely to be an effective prevention strategy.
'Alcohol is more harmful than heroin.' Really? Sample before you speak
Professor David Nutt was back in the headlines this week. In October 2009 he was sacked from his position as UK government's chief drug adviser after suggesting that LSD and heroin were less harmful than alcohol and tobacco, and that taking ecstasy was less dangerous than riding a horse. Now, almost exactly a year on, he has done it again. This time his claim is that alcohol is more harmful than heroin. Professor Nutt’s statement is statistically fuelled. However, it is also statistically flawed.
In their study, Professor Nutt and his colleagues rated the harmfulness of 20 drugs on 16 measures using a scale of 0 – 100, with 0 meaning not harmful and 100 meaning the most harmful. This was a ratio scale where the distance between each point on the scale is equal.
For example, a drug scoring 50 on such a scale is twice as harmful as a drug scoring 25. Using this scale, all the drugs included within the study were rated on all 16 measures in relation to both harm to the user and harm to others. Recognising that some measures are more important than others, Nutt weighted the scores for the measures to reflect the importance of each measure.
Based on the above, Nutt’s statement, which initially sounded farfetched, appears to have a strong statistical grounding. However, once we evaluate Nutt’s sampling strategy, flaws in his methodology are highlighted. The drugs in Nutt’s study were scored by a small group of experts. Such a sampling frame has several disadvantages:
• The experts scoring the drugs, whilst having extensive academic backgrounds, presumably are not drugs users themselves. This means that the measurement of harm to users is really the expert’s perceptions of the harm drugs cause users
• Again, when measuring harm to others, the experts are only offering their perceptions of how drugs harm others as they are unlikely to have direct, mass scale experience of how using each of the 20 drugs can affect others
• The size of the sample of experts is not large enough to make statistical inferences. In commercial research, the findings from any sample lower than n=50 are seen as directional and not significant
Despite employing robust scaling and weighting methods, Nutt’s work appears to be let down by a poorly targeted sampling strategy and a small base size, meaning that the methodology behind the highly impactful headline “Alcohol is More Harmful Than Heroin” is “Nutt quite” as robust as it initially appears. Resultantly, the findings of this study are based more on academic perception than social reality and the findings, at best, are directional.
‘Alcohol is more harmful than heroin’ part 2: Subjectivity Overdose?
Author:Diamanto Mamuneas and Maria Viskaduraki
"If scientists are not allowed to engage in the debate at this interface (between scientific advice and policy making) then you devalue their contribution to policy making and undermine a major source of carefully considered and evidence-based advice."
These were Professor David Nutt’s words, as reported by the BBC on Friday 30th October 2009, soon after Alan Johnson MP – then Home Secretary –forced him to resign as head of the UK’s Advisory Council on the Misuse of Drugs. The dispute had been over the reclassification of cannabis from a Class C to a class B drug; Prof. Nutt had said that the recreational drug poses only a “relatively small risk” of psychotic illness. Just over a year and several more resignations later, Nutt is back with a paper in The Lancet (November 2010) that claims to have settled this dispute using the “multicriteria decision analysis (MCDA) approach”.
“Dawkins’ Law of the Conservation of Difficulty states that obscurantism in an academic subject expands to fill the vacuum of its intrinsic simplicity.”
The MCDA approach is a prime example of this principle. In essence, “multicriteria decision analysis” is an obscurantist name for what ordinary people call “open discussion”. Where is the “scientific” and “evidence based” approach in MCDA? Where is the data? A short description of MCDA shows that there is precious little of either.
So how does MCDA work in this case? Over the course of one day, a group of experts convened to decide how each of 20 drugs deemed relevant in the UK scored (from 0-100) in terms of 16 criteria. This was no technical endeavour – the group got together for a discussion where “scores [were] often changed… as participants share(d) their different experiences and revise(d) their views” One must wonder how accurate these experts could be if they didn’t agree to begin with, and what effect a single dominant voice could have had on the group’s output. Clearly, these experts were providing subjective opinions - and some were learning as they went along!
The facilitator of these discussions was an “independent specialist in decision analysis modelling” who applied “techniques that enable groups to work effectively as a team”. This individual’s illustrious title is another example of Dawkin’s Law of Obscurantism, although the particular teamwork-promoting techniques employed are not elucidated. (Could it have been offering to get in the coffee and biscuits?)
The authors suggest that at least two drugs were assigned the top score of 100 in all criteria: “Weighting subsequently compares the drugs that scored 100 across all the criteria…” Rather than allowing a tie, the panel of experts was then also allowed to choose which they thought was more harmful. Though this isn’t made clear, the implication is that the top two most harmful drugs (at least) were considered equivalent. In other words alcohol and heroin are equally dangerous. The group then chose to consider alcohol more harmful, in line with Professor David Nutt’s past assertions.
Even if Prof Nutt’s publication had had the use of appropriate data, the 16 arbitrarily chosen criteria could not have been used to assess harm in a statistically valid manner. Because what exactly is the ‘harm’ that drug addiction causes? Consider my (mythical) friend Ben, who has recently acquired an addiction to heroin. He suffers health problems from an overdose, which costs the taxpayer (via the NHS) some money. Meanwhile, his wife leaves him, which causes him some emotional distress and he takes this out on his children, leaving them with serious injuries (that also cost the taxpayer). His wife comes back but kicks him out so he experiences a loss in tangibles, leading him to hold up a bank to obtain cash to replace his losses and fund his addiction… And so on. One thing leads to another and Ben now has first-hand experience of Dependence, Drug-specific Damage, Family Adversities, Economic Cost, Crime, Loss of Tangibles, Injury, Loss of Relationships and Drug-related Impairment of Mental Functioning – nine of those 16 judgement-criteria at least! And those criteria are clearly linked with each other. With the criteria being so interdependent it would be impossible to decide the relative correspondence of each with a given drug. Any attempt at weighting or ranking would be skewed by the correlations between different criteria, and different drugs may behave differently in terms of which criteria are inter-dependent, making comparisons impossible.
Nutt and colleagues attempt to compare their own conclusions to those of reports published in the USA and Netherlands and suggest that a handful of correlations between these experts’ subjective judgements and the results generated in these foreign examples lend credibility to this paper. However, they go on to point out, themselves, that “availability and legal status” varies across countries and that these contexts matter to many of the harmful effects of drugs. Furthermore, finding a correlation between an expert’s opinion on heroin and a published study is not surprising. Changes of mind aside, you would expect an expert to have had knowledge of such studies and to be informed by them (after the fact). In other words, the correlation isn’t a chance event that lends credence to the experts’ expertise – it is simply a sign that they keep track of the studies relevant to their field. We do not know that their judgement translates well to a UK context (far lower correlation was reported in the one example given) or that they are capable of judging the effects of different drugs, where the experts are essentially expressing informed opinion, at best, or guessing, at worst. I would be far more impressed if these experts were able to generate predictions that are then shown to hold true by ‘proper’ data.
The thing about ‘proper’ data, however, is that for many of the chosen criteria, any attempt to collect data would be ambitious. Though the authors imply that user numbers were taken into account for some of the criteria (assuming illegal drug use can reliably be estimated), the effects of illegality are more widely spanning. By way of illustration, one is more likely to drive while under the influence of a legal drug than an illegal one because, while both may lead to conspicuous erratic driving behaviour, the overall cost of being caught is greater in the latter case. By the author’s own admission, legal status is linked to effect ,so any data collected in the current legal context could not be used as a counter-argument to impact on a different legal context. For example, data collected now, while cannabis is illegal, cannot predict the effect of any decision to reclassify cannabis as legal: the very act of reclassifying it will change user behaviour, and make the previous data inapplicable.
Unfortunately, the method employed by this paper to implicitly support reclassification does more to damage trust of science than to lend credence to the ideology. Government is so often the target of demands for transparency, and politicians are often so ill-equipped to interpret multifaceted evidence, that science that seeks to inform policy-making ought to stand on the side of clarity and aim to lend some objectivity to what is already an intrinsically highly subjective process.