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New alcohol guidelines: what you need to know

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 9th Febraury 2016.

Last month the UK Chief Medical Officers (CMOs) published new guidelines for alcohol consumption. These are the first new guidelines since 1995 and are based on the latest evidence on the effects of alcohol consumption on health.

The guidelines provide recommendations for weekly drinking limits, single drinking episodes and recommendations for pregnant women, drawing heavily on the Sheffield Alcohol Policy Model, which uses the most up to date evidence on both the short- and long-term risks of alcohol.

What are the new guidelines?

Guidelines for weekly drinking

For the new weekly drinking guidelines, the CMOs recommend that:

  • It’s safest for both men and women to not regularly drink more than 14 units of alcohol per week;
  • It’s best to spread these units over 3 days or more;
  • Having several drink-free days each week is a good way of cutting down the amount you drink;
  • The risk of developing a range of illnesses increases with any amount you drink on a regular basis.

There are two key changes here from the guidelines we’ve been used to:

First, there’s no difference in recommendations for men and women. This is because there is increasing evidence that although women are more at risk from the long-term health effects of alcohol, men are more at risk from the short-term effects of drinking (they’re more likely to expose themselves to risky situations while drinking).

Second, there is an explicit statement that there is no ‘safe’ level of alcohol consumption. Over the past 21 years, the link between alcohol and cancer has become much clearer. For example, we now know that while the lifetime risk ofbreast cancer is 11% among female non-drinkers, the lifetime risk for a woman drinking within the new guidelines is 13%. A woman drinking over 35 units a week increases her risk of breast cancer to 21%.

In their report, the CMOs are also at pains to point out that the evidence supporting alcohol’s protective effects on ischaemic heart disease is now weaker than in 1995. Furthermore, any potential protective effect of alcohol is mainly observed among older women at very low levels of consumption. Previously some have used this to claim that drinking is better than abstinence – the new guidelines refute this.

The new guidance says it's safest for men and women to drink no more than 14 units each week.

The new guidance says it’s safest for men and women to drink no more than 14 units each week.

Guidelines for single drinking episodes

The new guidelines are the first to provide guidance on drinking on single occasions, recommending drinkers:

  • Limit the total amount consumed on any occasion;
  • Drink slowly, with food and alternating with water;
  • Avoid risky places and activities and ensure they have a safe method of getting home.

These new recommendations reflect the fact that many alcohol consumers may drink heavily on occasion and provide guidance to avoid the risk of injury and ischaemic heart disease which increase with heavy drinking.

Heavy drinking episodes are linked with a higher risk of injury.

Heavy drinking episodes are linked with a higher risk of injury.

Guidelines for drinking during pregnancy

The new guidelines suggest that:

  • The safest approach for pregnant women is not to drink alcohol at all, to keep risks to the baby to a minimum.
  • Drinking during pregnancy can lead to long-term harm to the baby, with the risk increasing with the more alcohol consumed;
  • The risk of harm to the baby is likely to be low if a woman has drunk only small amounts of alcohol before she knew she was pregnant or during pregnancy.

The CMOs report that while the evidence on the effects of low alcohol consumption during pregnancy remains ‘elusive’, taking a precautionary approach is most prudent when it comes to a baby’s long term health. However, given the elusive evidence, the guidance is also careful to note that mothers should not be too concerned if they have drunk early in their pregnancy, as this kind of stress may be even more harmful to the developing baby.

Pregnant women are advised not to drink alcohol at all.

Pregnant women are advised not to drink alcohol at all.

A note on risk

These recommendations are based on a level of alcohol consumption which confers a 1% lifetime risk of death from alcohol. Their purpose is therefore tominimise risk from alcohol, rather than eliminate it. Indeed, the guidelines explicitly state that there is no safe level of alcohol consumption. So what does a 1% lifetime risk mean and how does this compare to other health behaviours?

Lifetime mean risks

  • Being killed through BASE jumping (0.3%);
  • Being killed in a car accident (0.4%);
  • Being diagnosed with bowel cancer from eating three rashers of bacon every day (1%);
  • Dying from an alcohol related disease, if drinking within the new guidelines (1%);
  • Smokers dying from a smoking related disease (50%, although new estimates suggest that this may be as high as 67%).

Put in the context of smoking, the risk posed by drinking within the new guidelines seems tiny (although it’s still more risky than BASE jumping!) However, it’s important to note that alcohol consumption and smoking are quite different. Alcohol consumption is perceived as normal in our society and is much more prevalent than cigarette smoking. By contrast, the acceptability of smoking is reducing and unlike social alcohol consumers, smokers are constantly being told to quit smoking.

This 1% risk level is that which is deemed ‘acceptable’ by the CMO. However, everyone will have a different ‘acceptable’ level of risk, which depends in part on how much pleasure is obtained from drinking. While some will think that increasing their risk of death from alcohol to 5% is acceptable, others will not accept any risk and will use these guidelines to cut out alcohol completely.

Criticisms of the new guidelines

As expected, the ‘nanny state’ criticism has been bandied around in pubs, on message boards and on social media since the publication of these guidelines. Others claim that these new guidelines are simply scaremongering. However, it’s important to remember that these are recommendations, not rules.

The last word must go to CMO Professor Dame Sally Davies, who addressed this criticism by saying that:

What we are aiming to do with these guidelines is give the public the latest and most up- to-date scientific information so that they can make informed decisions about their own drinking and the level of risk they are prepared to take.

What do you think? Are these new guidelines useful? Will they help reduce alcohol related harm?

What do you think? Are these new guidelines useful? Will they help reduce alcohol related harm?

Links

Primary paper

Department of Health (2016) Health risks from alcohol: new guidelines. Open Consultation, 8 Jan 2016 (Consultation closes on 1 April 2016)

Department of Health (2016). Alcohol Guidelines Review – Report from the Guidelines development group to the UK Chief Medical Officers.

Other references

Centre for Public Health (2016). CMO Alcohol Guidelines Review – A summary of the evidence of the health and social impacts of alcohol consumption. Liverpool John Moores University.

Centre for Public Health (2016). CMO Alcohol Guidelines Review – Mapping systematic review level evidence. Liverpool John Moores University.

Department of Health (1995). Sensible drinking: Report of an inter-departmental working group.

Photo credits

 

A behavioural insights bar: How wine glass size may influence wine consumption

by Olivia Maynard @OliviaMaynard17

Now that the festive season is almost upon us, I’ve been wading through the list of jobs I’ve been putting off for longer than I can remember, with the hope of starting afresh in 2016.

One of these jobs is wrapping up some of the studies I’ve been running this year, tidying up the data files and deciding what to do with the results. Obviously it’s best practice to write up all studies for publication in peer-reviewed journals, but sometimes this isn’t possible straight away (for example, when we’ve collected pilot data which will inform larger studies or research grants), although journals specifically for pilot and feasibility work do exist. However, it’s still important to share the findings, at the very least to prevent other research groups from running exactly the same pilot study (avoiding the file drawer effect).

The pilot study I’m trying to wrap up was conducted in September this year and is worth reporting, not only because the research is interesting, but also because the method of data collection was novel.

In December 2014 we were approached by the Behavioural Insights Team (BIT), who asked whether we’d be interested in running an experiment at their annual conference. Alongside a star-studded list of speakers, the BIT had planned to demonstrate to conference delegates the power of behavioural insights, by running a series of mini-experiments throughout the conference. We were asked to contribute, not only because I had previously worked in the BIT as part of a placement during my PhD, but also because of TARG’s track record in running behavioural experiments to influence alcohol consumption, both in the lab and in the ‘real-world’.

glassThe team asked us to run an experiment in the Skylon bar in the Royal Festival Hall – the venue of the conference drinks reception. After an initial assessment of the bar (yes, this is a tough job!) and discussing various possible experiments we could conduct, we finally decided to examine the impact of glass size on alcohol consumption. While considerable previous research has shown that plate size is an important driver in food consumption, and we have shown that glass shape (i.e., curved versus straight) influences alcohol consumption, there is very little research on the impact of glass size on alcohol consumption. Larger wine glasses are increasingly common and these may increase wine consumption and drinking speed by suggesting larger consumption norms to consumers, or by tricking consumers into thinking there’s a smaller amount in the glass than in a smaller glass which is equally full.

The primary aim of this pilot study was to determine the feasibility of implementing a glass size intervention study in a real-world drinking environment in order to inform future studies in this area.

Method

Prior to starting the study, as with every TARG study, we published the protocol online on the Open Science Framework. Depending on the side of the bar they were stood in, delegates attending the drinks reception were provided with either a small or a large wine glass, each of which was filled to the same volume. Every 15 minutes we counted the number of delegates on the two sides of the bar and every hour (for three hours) we counted the number of empty wine bottles on each side of the bar. We calculated the average volume of wine consumed per delegate each hour and then compared these between the two groups.

Results

From a feasibility point of view, the study worked as well as expected. Follow-up interviews with the manager of the bar indicated that bar staff enjoyed the process of participating in a study and were happy to participate again in future studies.

However, because we were conducting this in the real-world, rather than in our carefully controlled laboratory environment, we encountered a few logistical challenges. Here are the key points we learned from running this pilot study:

  1. In the real-world, there’s a necessary trade-off between collecting the data and not disrupting normal behaviour

bottles

Ideally we would have counted the number of empty bottles more frequently than every hour in order to get a more accurate measure of how much was consumed by the delegates. However prior to the start of the study, the bar manager suggested that this would interfere with their service and the bar staff reiterated this after the study had finished. As the bar staff were vital to the success of this pilot study, we didn’t think it was appropriate to push for more data collection than they felt comfortable with.

  1. Complete control of the environment isn’t possible in the real-world

controlkey

To prevent delegates from moving between the two sides of the bar we placed physical barriers between them, such as sofas, plants and lamps. However, inevitably, some delegates who wanted to ‘work the room’ at what was essentially a networking event did make their way past the barriers we set up. Other than instructing the waiters to replace the glass of those who had moved sides with the glass size appropriate for the side of the bar they were now in, there was very little we could do about this, short of frog-marching delegates back to their original side (which we thought wouldn’t go down very well on this occasion!)

  1. Accurate enforcement of study conditions is more difficult in the real-world

pouring

If we had conducted this study in the laboratory, we would have randomised participants to receive one of two glass sizes and carefully poured the exact volume of wine into their glass. In this real-world study, however, we had to rely on the waiters to accurately pour the wine into the glasses. Although highly trained, the waiters may also have fallen foul of the visual illusion the different glasses present (an effect which has been shown in previous real-world experiments). Future studies could monitor waiter pouring behaviour before and during the study.

  1. Studies in real bars have some other unexpected challenges…

full glassess

The BIT had asked that we present the results at 9am the following morning, allowing a nine hour turnaround from the end of the study to data presentation. This time pressure was not helped by the large quantities of complimentary champagne being served at the event, which considerably slowed down data entry and analysis at midnight!

Despite this substantial challenge, the results of the study were presented the following morning.

These data suggested that there was no difference in volume of wine consumed between the groups drinking from larger glasses and those drinking from tablesmaller glasses. As this study wasn’t powered to detect a meaningful difference between the two groups, we weren’t really surprised by this finding. However, these pilot data, along with the lessons learned from conducting the study will be used to inform our future research studies and grant applications.

And there we have it – another pilot study out of the file drawer and another item crossed off my ‘to-do’ list.

I’d like to thank the entire Behavioural Insights Team, in particular Ariella Kristal and Gabrielle Stubbs, for making this study happen, Carlotta Albanese from the Skylon bar and David Troy and Jim Lumsden from TARG for helping with all the data collection (and data entry at midnight).

Can we use the inhalation of 7.5% CO2 as a model to probe cognition and behaviour in anxiety?

by Alex Kwong @tskwong

A lot of the work conducted in the Tobacco and Alcohol research group (TARG) mainly focuses around tobacco and alcohol research (funny that…). However, when we’re not getting people intoxicated in the name of science (yes we do that), we’re also carrying research ranging from body perception, to emotion recognition and anxiety research. The latter is something that I’ve focused on, and to cut a long story short, we make people anxious by making them breathe in air enriched with carbon-dioxide (CO2), about 7.1% more than what you would normally breathe. Once people are anxious, we assess them on a number of outcomes, some clinically relevant, some more practical and applied.

Needless to say, breathing in about 7% more CO2 for a period of up to 20 minutes should make you anxious for a number of reasons (to be explained later on). But can breathing in a gas that is enriched with CO2 act as a viable model for anxiety, capable of assessing cognition and behaviours that are susceptible to anxiety? In this post I’ll explore some of the previous research utilising this model, and look at some of the future directions of the model and how it could be used as a training tool to help improve performance under anxiety. By then, hopefully you’ll agree with me that the model is good at experimentally inducing anxiety, and you’ll sign up for all our studies.

Possibly the most influential research on the inhalation of CO2 has been by Bailey et al. (2005) and work from David Nutt’s former lab in Bristol. They found that breathing in CO2 enriched gas for a period of 20 minutes decreased positive mood (feelings of happiness and relaxation) and increased negative mood (worry and fear). Since then, a plethora of research has supported this, and also found that the model induces symptoms such as sweating, increased heart rate and blood pressure and hypoxia, all common in generalised anxiety disorder (GAD). Interestingly, other research has found that we can actually reduce these responses to the CO2 model by giving people anxiolytic drugs. As such, the model of 7.5% CO2 has been considered a validated model of human anxiety induction that is generalisable to anxiety disorders such as GAD.

But why does breathing in a gas that is enriched with CO2 cause these sort of feelings? One explanation is that breathing in CO2 causes chemoreceptors to mislead the body into thinking that it is starved of oxygen. This leads to fear like responses, as well as increased breathing rates and higher blood pressure and heart rate. If you’ve ever had the pleasure of taking part in one of these CO2 experiments, you’ll likely agree that these things happen. I’ll just stress at this point that effects of the gas are transient and usually disappear quickly after the inhalation. Some people even enjoy the experience, so I hope I’m still selling this to you.

CO2 set-up

A typical experimental set up with the CO2.

So if it makes you feel like you’re experiencing physiological anxiety, then it’s obviously a model of human anxiety right? Well what about the psychological components? People with GAD often have a hypervigilance to threat, even when there is nothing threatening around. Additionally, their attention to negative stimuli is increased, even in the presence of other emotional content. Anxious sufferers also interpret ambiguous information as potentially dangerous or threatening. Can the CO2 model can tap into some of these psychological components that are common in GAD?

To address this, one study found that the inhalation of 7.5% CO2 caused quicker eye-movements to be made towards threatening stimuli. Another study found that CO2 caused attention to reflect a hyper vigilance to threatening information. Otherresearch in preparation has found that people were worse at correctly identify emotional faces during CO2. Lastly, Cooper et al. (2013) found that CO2 caused people to interpret ambiguous information in CCTV footage as threatening. These findings support the 7.5% CO2 model affecting psychological processes similar to those in GAD.

Great! So the model seems to be similar to the experience of GAD, what next? Well, what’s also quite fascinating is that if we have a model for anxiety, we could predict how people will behave in situations like sport, musical performances, decision-making, medical and security services etc – behaviours that can induce feelings of anxiety or be affected by anxiety, even in those without a disorder. Understanding how people will behave in stressful situations might help improve performances in the future.

The CO2 model has been used to investigate this. Attwood et al. (2013) found that 7.5% CO2 impaired the ability to match pairs of faces, a finding which has tremendous implications for military and forensic settings (e.g., border crossings and proof of sale purchases like alcohol and tobacco). More recently, we also found that the inhalation of 7.5% CO2 impairs the ability to remember faces that have previously been seen. Importantly, ‘witnesses’ did not report lower confidence of their choices despite this impaired ability, which has implications for the judicial system (e.g., courtrooms and line-ups).

Upcoming research has suggested that CO2 impairs decision-making on a gambling task, by making people choose more exploratory decisions which in turn causes less money earned. Other research has suggested that the CO2 causes excessive force production which could affect military, surgical and sporting behaviours. The same research also suggested that people speed up when asked to tap in time with a metronome, which could detriment musical performances and any task that requires accurate bodily timing. Together, this research shows that the inhalation of 7.5% CO2 may be a useful tool for examine how anxiety may affect behaviours.

Mask

The amount of Bane and Darth Vader impressions I got from participants was staggering – “It would be extremely anxious…, for you”

By now you should be getting the picture that a) the CO2 model is good for inducing anxiety and b) that I am incredibly biased in favouring this model. But I think there are good reasons to endorse this stance. Many previous studies that induce anxiety are time limited, meaning that ‘anxiety’ may only affect certain stages of the task. Other studies only produce one single ‘hit’ to cause anxiety (e.g., one phobic stimuli, one bodily stressor), which may not be characteristic of anxiety as a whole. However, one anxiety inducer that I think is quite neat is the threat of electric shock. Threatening people with electric shock is a great way to induce anxiety but in some experiments, the shock doesn’t actually come, so people quickly learn that there is no threat and thereby no longer remain anxious, which is a problematic for anxiety research.

The CO2 model is not without its flaws. Tasks can only be conducted within the 20 minute inhalation window. That said, there is no limit to how many times someone can be CO2’d. Practically, people may decide they no longer want to feel anxious during the inhalation and so drop out, but this is likely to be a problem in anxiety research generally. Perhaps most importantly, whilst we have conducted numerous CO2 experiments, we are still unsure exactly how the model works on all attentional and behavioural mechanisms. Future research is looking at how the CO2 model affects the brain, and our eye-movements. There is also research that has explored psychological interventions, such as mindfulness training, and whether this can reduce some of the symptoms brought on by the CO2 inhalation. It’ll also be really interesting to see whether the model can be utilised as a training tool for people who need to perform under anxious conditions. Research has shown that practising under conditions of anxiety can help improve performance at a later stage and so the next step would be to see if people can perform better in real life anxious situations, if they’ve practised on the CO2 model first.

In summary, the CO2 model seems to be a reliable way to induce anxiety that can impact on both cognition and behaviour. The model is validated by a wealth of research showing its similarity to GAD. Although the model is not perfect for inducing anxiety, it is one of the more promising tools we currently have, and subsequent research should continue to use the model as a viable probe for exploring cognition and behaviour under anxiety.

The effect of smoking-free psychiatric hospitals on smoking behaviour: more evidence needed

By Olivia Maynard @OliviaMaynard17 

This blog originally appeared on the Mental Elf site on 18th May 2015.

One in three people with mental health illnesses in the UK smoke, as compared with one in five of the general population. In addition, smokers with mental illnesses smoke more heavily, are more dependent on nicotine and are less likely to be given help to quit smoking. As a result, they are more likely to suffer from smoking-related diseases, and on average die 12-15 years earlier than the general population.

Since July 2008, mental health facilities in England have had indoor smoking bans. However, NICE guidelines recommend that all NHS sites, including psychiatric hospitals become completely smoke-free, a recommendation previously examined by the Mental Elf.

This NICE recommendation has been criticised by those who argue that:

  1. Tobacco provides necessary self-medication for the mentally ill;
  2. Smoking cessation interferes with recovery from mental illness;
  3. Smoking cessation is the lowest priority for those with mental illnesses;
  4. People with mental illnesses are not interested in quitting;
  5. People with mental illness cannot quit smoking.

Many people argue that forcing people to quit smoking when they are having an acute mental health episode is tantamount to abuse.

Judith Prochaska, a researcher at Stanford University, has previously addressed each of these arguments (she calls them ‘myths’) (Prochaska, 2011). The abridged summary of the evidence surrounding myths 1, 2 and 3 is that:

  1. Smoking actually worsens mental health outcomes; in fact, the argument that nicotine provides self-medication is one which has been promoted by the tobacco industry itself;
  2. Smoking cessation does not exacerbate mental health outcomes;
  3. Smoking cessation should be a high priority, given that mental health patients are much more likely to die from tobacco-related disease than mental illness.

These are interesting and important arguments and more evidence surrounding them is also available here (Prochaska, 2010).

However, in this blog post I focus on ‘myths’ 4 and 5, drawing on a recent systematic review investigating the impact of a smoke-free psychiatric hospitalisation on patients’ motivations to quit (myth 4) and smoking behavior (myth 5) (Stockings et al., 2014).

This systematic review brings together mostly cross-sectional studies that look at the impact that smoke-free hospitals have on psychiatric inpatients who smoke.

Methods and results

Stockings and colleagues searched for studies examining changes in patients’ smoking-related behaviours, motivation and beliefs either during or following an admission to an adult inpatient psychiatric facility.

Study characteristics

Fourteen studies matched these inclusion criteria, two of which were conducted in the UK. The majority of the studies used a cross-sectional design and none were randomised controlled trials. The studies were all quite different, with the number of participants ranging from 15-467 and the length of admission ranging from 1-990 days. Crucially, the type of smoking ban varied considerably between the studies, so I’ll consider these separately.

Facilities with complete smoking bans

Six studies were conducted in facilities with complete bans. All of these offered nicotine dependence treatment, including nicotine replacement therapy (NRT) or brief advice.

  • Only one of these statistically assessed smoking behaviour, finding that cigarette consumption was lower during admission compared with prior to admission.
  • Three studies assessed smoking behaviour after discharge, finding that the majority of patients resumed smoking within five days. However, there was some evidence from the two larger studies that smoking prevalence was still lower at two weeks and three months post-discharge compared with prior to admission.
  • The one study to statistically assess smoking-related beliefs and motivations found that patients expected to be more successful at quitting following discharge compared with at admission. Higher doses of NRT were related to higher expectations of success.

Facilities with incomplete bans

Eight studies were conducted in facilities with incomplete bans. 

  • Four banned smoking indoors and all of these offered nicotine dependence treatment:
    • Only one of these statistically assessed smoking behaviour, finding that quit attempts increased from 2.2% when smoking was permitted in specific rooms, to 18.4% after the ban.
    • One study that assessed smoking prevalence post-discharge found that all participants (n = 15) resumed smoking.
    • One study found that participants expected to be more successful in smoking cessation post-discharge as compared with at admission.
  • Three allowed smoking in designated rooms, with no nicotine dependence treatment:
    • There were mixed results among the two studies which assessed smoking prevalence during admission.
    • Compared with at admission, there was some evidence of increased motivation to quit smoking.
  • One restricted smoking to five pre-determined intervals per day, with no nicotine dependence treatment:
    • Motivation to quit was lower at discharge compared with at admission.

This review suggests that complete bans are the most effective at encouraging smoking cessation and that NRT or brief advice are crucial.

Conclusions

The authors concluded that:

Smoke-free psychiatric hospitalisation may have the potential to impact positively on patients’ smoking behaviours and on smoking-related motivation and beliefs.

Strengths and limitations

The fourteen studies included in this review were all quite different from each other and had a number of limitations including:

  • Small sample sizes;
  • Incomplete reporting of key outcomes;
  • Failure to use controlled, experimental research designs;
  • Differences in the types of smoking bans in place;
  • Inconsistent provision of nicotine dependence treatment.

These key differences and limitations prevented statistical examination of the results as a whole. This means that making firm conclusions is difficult. There is clearly a need for more research in this area.

This area of research is far from complete, so we cannot make any firm conclusions about smoke-free psychiatric hospitals at this stage.

Summary

There is evidence that people with mental illnesses are interested in quitting smoking (myth 4) and that they are able to (myth 5). However, we still need more studies to examine these questions with well-powered (i.e. large sample sizes), high-quality (i.e., experimental) research designs.

The evidence presented in this systematic review suggests that complete bans are the most effective at encouraging smoking cessation and that the provision of nicotine dependence treatment, such as NRT or brief advice, is also crucial.

Although a handful of the studies assessed smoking behaviour after discharge, none of the facilities viewed this as an important outcome. Given the high level of smoking-related disease among those with mental health illnesses, ensuring that individuals remain abstinent from smoking after discharge is important for the continuing good health of these individuals.

Importantly, none of the studies in this review explored the impact of smoke-free legislation on mental health outcomes. Although the evidence suggests that smoking cessation actually improves mental health outcomes, future research should continue to examine this relationship.

Over to you

Do you have a mental health illness yourself, or support someone who does? Do you work with people with mental health illnesses? Should psychiatric hospitals become smoke-free?

We'd love to hear your views about this systematic review and more generally on this often emotive topic. Please use the comment box below to share your knowledge and experience.

Links

Primary paper

Stockings EA. et al (2014) The impact of a smoke-free psychiatric hospitalization on patient smoking outcomes: a systematic review. Aust NZ J Psychiatry 2014 May 12;48(7):617-633. [PubMed abstract]

Other references

Prochaska, J. J. (2010). Failure to treat tobacco use in mental health and addiction treatment settings: A form of harm reduction? Drug and Alcohol Dependence, 110(3), 177-182. doi: http://dx.doi.org/10.1016/j.drugalcdep.2010.03.002

Prochaska, J. J. (2011). Smoking and Mental Illness — Breaking the Link. New England Journal of Medicine, 365(3), 196-198. doi: doi:10.1056/NEJMp1105248

 

Promoting smoking cessation in people with schizophrenia

by Meg Fluharty @MegEliz_

This blog originally appeared on the Mental Elf site on 14th May 2015.

shutterstock_276469196People with schizophrenia have a considerable reduction in life expectancy compared to the general population (Osborn et al 2007; Lawrence et al 2013). A number of factors lead to cardiovascular disease (Osborn et al 2007; Lawrence et al 2013; Nielsen et al, 2010) one of which is smoking.People with schizophrenia smoke at much higher rates and more heavily than the general population (Ruther et al 2014, Hartz et al 2014).Stubbs et al (2015) carried out a review to assess the current cessation interventions available for individuals with serious mental illnesses and establish if any disparities currently lie in the delivery of these interventions.60% of premature deaths in people with schizophrenia are due to medical conditions including heart and lung disease and infectious illness caused by modifiable risk factors such as smoking, alcohol consumption and intravenous drug use.

Methods

The authors searched several electronic databases (Embase, PubMed, and CINAHL) using the following keywords: “smoking cessation”, “smoking”, “mental illness”, “serious mental illness” and “schizophrenia.”

Studies were eligible if they included individuals with a DSM or ICD-10 diagnosis of schizophrenia and reported a cessation intervention.

The authors included both observational and intervention studies as well as systematic-reviews and meta-analyses.

This paper is a clinical overview (not a systematic review) of a wide range of different studies relevant to smoking cessation in schizophrenia and other severe mental illnesses.

Results

Pharmacological interventions

 Non-pharmacological interventions

  • The evidence for E-cigarettes was inconsistent, with the authors concluding more evidence was needed before clinicians consider e-cigarettes within mental health settings. Additionally, e-cigarette use in people with schizophrenia should have side effects monitored closely.
  • There was little research on exercise in schizophrenia, but one study found a reduction in tobacco consumption.

Behavioural approaches

  • Behavioural approaches such as offering smoking cessation advice alongside pharmacotherapy have been found successful with no harmful side effects.

Disparities in smoking cessation interventions

  • An investigation of GP practices found individuals with schizophrenia did not receive smoking cessation interventions proportional to their needs.

Support while quitting

  • People with serious mental illnesses experience more severe withdrawal symptoms compared to the general population, and therefore should be given extra support during cessation attempts (Ruther et al 2014).
  • Psychiatrists should re-evaluate choice and the dose of antipsychotic medicine being given after abstinence from smoking is achieved. This is because of nicotine’s metabolic influence on antipsychotic medicine.
  • Alongside smoking cessation, exercise should be promoted among people with schizophrenia to combat weight gain and the increased metabolic risk.

People with serious mental illness are likely to need more support when quitting smoking, because they generally suffer more severe withdrawal symptoms.

Discussion

In light of the findings, the authors suggest several steps for clinicians to help people with schizophrenia quit smoking:

  • Patients’ current smoking status, nicotine dependency, and previous quit attempts should be assessed. Assessing nicotine dependency will help predict the level of withdrawal symptoms the patient is likely to experience upon quitting.
  • Cessation attempts are best timed when the patient is stable. Patients should be thoroughly advised on the process needed to give them the best chance of quitting smoking, Thus, allowing the patient to formulate their quit plan and take ownership of their own quit attempt.
  • Cessation counselling should be provided, particularly what to expect with withdrawal symptoms (e.g. depression and restlessness) and how to cope.
  • Pharmacological support should be provided (Bupropion recommended) when there is even mild tobacco dependence.
  • Clinicians should carefully monitor patients’ medication and fluxions in weight for a minimum of 6 months after quitting smoking, and when needed recommended exercise to combat weight gain.

The authors provide a well laid out summary of their findings, alongside some excellent suggestions for clinicians to consider on how to best promote cessation in practice.

However, it should be stressed that Stubbs et al (2015) only searched for high qualities studies and provided an overview of them –  this is not a systematic review or meta-analysis. They included several types of studies, set little inclusion criteria and listed no exclusion criteria. This is quite different from a systematic review with a meta-analysis, which would set stricter predefined search and eligibility criteria, which identify a set of studies all tackling the same question, thus allowing for the statistical pooling and comparison of these studies.

This is not a systematic review, but it does offer some very useful practical advice for clinicians who are trying to promote smoking cessation.

Links

Primary paper

Stubbs B, Vancampfort D, Bobes J, De Hert M, Mitchell AJ. How can we promote smoking cessation in people with schizophrenia in practice? A clinical overview. Acta Psychiatrica Scandinavica. 2015: 1-9. 
[PubMed abstract]

Other references

Osborn DPJ, Levy G, Nazareth I, Petersen I, Islam A, King MB. Relative risk of cardiovascular and cancer mortality in people with severe mental illness from the United Kingdom’s General Practice Research Database. Arch Gen Psychiatry 2007;64:242–249.

Lawrence D, Hancock KJ, Kisely S. The gap in life expectancy from preventable physical illness in psychi- atric patients in Western Australia: retrospective analysis of population based registers. BMJ 2013;346: f2539-f.

Nielsen RE, Uggerby AS, Jensen SOW, McGrath JJ. Increasing mortality gap for patients diagnosed with schizophrenia over the last three decades – a Danish nationwide study from 1980 to 2010. Schizophr Res 2013;146:22–27.  
[PubMed abstract]

Ruther T, Bobes J, de Hert M et al. EPA guidance on tobacco dependence and strategies for smoking cessation in people with mental illness. Eur Psychiatry 2014;29:65– 82. 
[PubMed abstract]

Hartz SM, Pato CN, Medeiros H et al. Comorbidity of severe psychotic disorders with measures of substance use. JAMA Psychiatry 2014;71:248–254.

 

Motivational interviewing may help people quit smoking, but more research is needed

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 30th April 2015.

Both pharmacological (i.e. bupropion and varenicline) and non-pharmacological (i.e. brief advice from physicians) interventions have been shown to be effective in assisting people to stop smoking. Evidence also suggests that combining both these types of interventions can help people to stop smoking and both are considered equally important in quitting success.

Motivational interviewing (MI) is a counselling-based intervention which focusses on encouraging behaviour change by helping people to explore and resolve their uncertainties about changing their behaviour. MI avoids an aggressive or confrontational approach and aims to increase the self-belief of the individual. MI was initially developed to treat alcohol abuse, but may be helpful in encouraging smoking cessation.

In a recent Cochrane systematic review, Lindson-Hawley and colleagues from the Cochrane Tobacco Addiction Group aimed to determine whether or not MI is an effective method of smoking cessation (Lindson-Hawley et al, 2015).

Motivational interviewing focusses on encouraging behaviour change by helping people to explore and resolve their uncertainties about changing their behaviour.

Methods

The authors searched online databases and studies were included if:

  • Participants were tobacco users and were not pregnant or adolescents;
  • The intervention was based on MI techniques;
  • The control group received brief advice or usual care;
  • Some monitoring of the quality of the MI intervention was included;
  • Smoking abstinence was reported at least 6 months after the start of the programme.

The main outcome measure was smoking abstinence, using the most rigorous definition of abstinence for each study. Biochemically-validated measures of abstinence (i.e., carbon monoxide breath testing or saliva cotinine samples) were also used where available. Those participants lost to follow-up were considered to be continuing to smoke.

Results across studies were combined in a meta-analysis.

Results

Twenty eight studies published between 1997 and 2014 were found to match the strict inclusion criteria.

The total dataset included over 16,000 participants and studies varied in:

  • The length of the MI sessions (ranging from 10 to 60 minutes)
  • The number of sessions (one to six sessions)
  • Who the sessions were delivered by (primary care physicians, hospital clinicians, nurses or counsellors)

Some of the main findings included:

  • A modest (26%) increase in quitting among those receiving MI as compared with control (although the true value is likely to lie between 16-36%).
  • Sub-group analyses found that:
    • MI delivered by primary care physicians increased the likelihood of successful quitting by 349% (53-794%) as compared with control
    • When it was delivered by counsellors, quit rates increased by only 25% as compared with control
    • MI delivered by nurses was not found to be more effective than control
  • Shorter sessions (less than 20 minutes) increased the chances of quitting relative to control by 69%, as compared with longer sessions, which only increased the chances of quitting by 20%.
  • There was little difference in the likelihood of quitting between single MI sessions (26%) and multiple sessions (20%) as compared with control.
  • There was little difference between MI delivered face-to-face as compared with via the telephone only.
  • There was no evidence for a difference for MI delivered to smokers who were motivated to quit as compared with those with low levels of motivation.

Compared with brief advice or usual care, motivational interviewing yielded a significant increase in quitting. However, study quality means that these results should be interpreted with caution.

Strengths

This review adds 14 additional studies to a previous review conducted in 2010. The addition of these new studies altered the results of the original review very little, providing strong support for the validity of these findings.

Two previous systematic reviews have also examined the effectiveness of MI for smoking cessation, observing modest positive effects of MI (Heckman et al., 2010, Hettema and Hendricks, 2010), although these studies used a broader inclusion criteria than used here and therefore may have underestimated the effects of MI.

The majority of studies included in this review adequately reported their design and methods. Some studies did not report information about blinding of the outcome assessment or how participants were allocated to conditions. However, sensitivity analyses indicated that these factors did not influence the findings of the review.

Limitations

The authors report some evidence for publication bias, such that studies reporting a positive effect of MI were more likely to be published, potentially compromising the results of this systematic review.

Eight of the 24 studies did not use biochemically-validated measures of abstinence. When analyses excluded these studies, the size of the beneficial effect of MI increased. Future research should use the biochemically-validated abstinence measures so as to ensure that smoking cessation is reliably reported.

Conclusions

These results indicate that MI is more effective at promoting smoking cessation than usual care or brief advice, although the effect is modest.

Some components of MI counselling appear to increase the effectiveness of MI for smoking cessation, including delivery by a primary care physician. The reviewers suggest that physicians may be better placed to use the MI approach given their established rapport with the patient. However, this effect is based on only two studies and therefore the importance of physician delivery should not be overstated.

Shorter sessions and fewer follow-ups were also found to be more effective than longer sessions with more follow-up sessions. One explanation given by the authors is that a single session is enough to motivate someone to quit smoking. Prolonging the time before the quit date may mean participants lose focus on their goal to stop smoking.

While MI seems to be effective in promoting smoking cessation, future research should continue to explore the components of MI which optimise the success of this intervention. The relationship between non-pharmacological interventions such as MI and pharmacological interventions should also be considered.

This review confirms that motivational interviewing for smoking cessation is supported by moderate level evidence.

Links

Primary paper

Lindson-Hawley N, Thompson TP, Begh R. Motivational interviewing for smoking cessation. Cochrane Database of Systematic Reviews 2015, Issue 3. Art. No.: CD006936. DOI: 10.1002/14651858.CD006936.pub3.

Other references

Heckman, C. J., Egleston, B. L. & Hofman, M. T. (2010). Efficacy of motivational interviewing for smoking cessation: a systematic review and meta-analysisTobacco Control, 19, 410-416.

Hettema, J. E. & Hendricks, P. S. (2010). Motivational interviewing for smoking cessation: A meta-analytic review. Journal of Consulting and Clinical Psychology, 78, 868-884. [DARE summary]

 

E-cigarettes and teenagers: cause for concern?

By Marcus Munafo @MarcusMunafo 

This blog originally appeared on the Mental Elf site on 20th April 2015

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Electronic cigarettes (e-cigarettes) are a range of products that deliver vapour which typically contains nicotine (although zero-nicotine solutions are available). The name is misleading because some products are mechanical rather than electronic, and because they are not cigarettes. While first-generation products were designed to be visually similar to cigarettes, second- and third-generation products are visually distinctive and come in a variety of shapes and sizes. Critically, these products do not contain tobacco, and are therefore intended to deliver nicotine without the harmful constituents of tobacco smoke.

There has been rapid growth in the popularity and use of e-cigarettes in recent years, accompanied by growth in their marketing. At present they are relatively unregulated in many countries, although countries are introducing various restrictions on their availability and marketing. For example, a ban on sales to under-18s will be introduced in England and Wales in 2015.

These products have stimulated considerable (and often highly polarized) debate in the public health community. On the one hand, if they can support smokers in moving away from smoking they have enormous potential to reduce the harms associated with smoking. On the other hand, the quality and efficacy of these products remains largely unknown and is likely to be highly variable, and data on the long-term consequences of their use (e.g., the inhalation of propylene glycol vapour and flavourings) is lacking. There is also a concern that these products may re-normalise smoking, or act as a gateway into smoking.

E-cigarettes and teenagers: a gateway

Methods

This study reports the results of a survey conducted by Trading Standards in the North-West of England on 14 to 17 year-old students. The survey focuses on tobacco-related behaviours, and a question on access to e-cigarettes was introduced in 2013. This enabled identification of factors associated with e-cigarette use among people under 18 years old.

The study used data from the 5th Trading Standards North West Alcohol and Tobacco Survey among 14 to 17 year-olds in North-West England, conducted in 2013. The questionnaire was made available to secondary schools across the region through local authority Trading Standards departments, and delivered by teachers during normal school lessons. Compliance was not recorded, and the sample was not intended to be representative but to provide a sample from a range of communities.

The survey consisted of closed, self-completed questions covering sociodemographic variables, alcohol consumption and tobacco use. There were also questions on methods of access to alcohol and tobacco, as well as involvements in violence when drunk. E-cigarette access was assessed by the question “Have you ever tried or purchased e-cigarettes?”.

The study used data from the North West Alcohol and Tobacco Survey, which asked 14 to 17 year-olds lots of questions about their substance use behaviour.

Results

A total of 114 schools participated, and the total dataset included 18,233 participants, of which some were removed for missing data or spoiled questionnaires (e.g., unrealistic answers), so that the final sample for analysis was 16,193. Some of the main findings of the survey included:

  • In total, 19.2% of respondents reported having accessed e-cigarettes, with this being higher in males than females, and increasing with age and socioeconomic deprivation.
  • Level of e-cigarette access was higher among those who had smoked, ranging from 4.9% of never smokers, through 50.7% of ex-smokers, 67.2% of light smokers and 75.8% of heavy smokers.
  • E-cigarette use was associated with alcohol use, with those who drank alcohol more likely to have accessed e-cigarettes than non-drinkers, as well as with smoking by parents/guardians.

Nearly 1 in 5 of the young people surveyed

Conclusion

The authors conclude that their results raise concerns around the access to e-cigarettes by children, particularly among those who have never smoked cigarettes. They argue that their findings suggest that the children who access e-cigarettes are also those most vulnerable to other forms of substance use and risk-taking behavior, and conclude with a call for the “urgent need for controls on e-cigarette sales to children”. The study has some important strengths, most notably its relatively large size, and ability to determine which respondents were living in rich and poor areas.

Understanding the determinants of e-cigarette use, and patterns of use across different sections of society, is important to inform the ongoing debate around their potential benefits and harms. However, it is also not clear what this study tells us that was not already known. The results are consistent with previous, larger surveys, which show that young people (mostly smokers) are trying e-cigarettes. Critically, these previous surveys have shown that while some young non-smokers are experimenting with electronic cigarettes, progression to regular use among this group is rare. Product labels already indicate that electronic cigarettes are not for sale to under-18s, and in 2014 the UK government indicated that legislation will be brought forward to prohibit the sale of electronic cigarettes to under-18s in England and Wales (although at present no such commitment has been made in Scotland).

This study does not add anything significant to our knowledge about e-cigarettes.

Limitations

There are a number of important limitations to this study:

  • As the authors acknowledge, this was not meant to be a representative survey, and the results can therefore not be generalized to the rest of the north-west of England, let alone the wider UK.
  • As a cross-sectional survey it was not able to follow up individual respondents, for example to determine whether never smokers using e-cigarettes progress to smoking. This problem is common to most e-cigarette surveys to date.
  • The question asked does not tell us whether the participants actually used the e-cigarette they accessed, or what liquid was purchased with the e-cigarette (e.g., the concentration of nicotine). Zero-nicotine solutions are available, and there is evidence that these solutions are widely used by young people.
  • The results are presented confusingly, with numerous percentages (and percentages of percentages) reported. For example, 4.9% of never smokers reported having accessed e-cigarettes, but this is less than 3% of the overall sample (fewer than 500 out of 16,193 respondents). This is potentially an important number to know, but is not reported directly in the article.

Summary

This study does not add much to what is already known. Young people experiment with substances like tobacco and alcohol, and as e-cigarettes have become widely available they have begun to experiment with these too. However, to describe electronic cigarette use as “a new drug use option” and part of “at-risk teenagers’ substance using repertoires” is probably unnecessarily alarmist, given that:

  1. There is evidence that regular use of e-cigarettes among never smokers is negligible
  2. There is little evidence of e-cigarette use acting as a gateway to tobacco use
  3. The likelihood that e-cigarette use will be associated with very low levels of harm

It's alarmist to suggest

Links

Primary reference

Huges K, Bellis MA, Hardcastle KA, McHale P, Bennett A, Ireland R, Pike K. Associations between e-cigarette access and smoking and drinking behaviours in teenagers. BMC Public Health 2015; 15: 244. doi: 10.1186/s12889-015-1618-4

Other references

Young Persons Alcohol and Tobacco Survey 2013. Lancashire County Council’s Trading Standards.

High potency cannabis and the risk of psychosis

By Eleanor Kennedy @Nelllor_

This blog originally appeared on the Mental Elf site on 24th March 2015

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Smoking higher-potency cannabis may be a considerable risk factor for psychosis according to research conducted in South London (Di Forti, et al., 2015).

Cannabis is the most widely used illicit drug in the UK and previous research has suggested an association between use of the drug and psychosis, however the causal direction and underlying mechanism of this association are still unclear.

This recent case-control study published in Lancet Psychiatry, aimed to explore the link between higher THC (tetrahydrocannabinol) content and first episode psychosis in the community.

To compare the impact of THC content on first episode psychosis, participants were asked whether they mainly consumed skunk or hash. Analysis of seized cannabis suggests that skunk has THC content of between 12-16%, while hash has a much lower THC content ranging from 3-5% (Potter, Clark, & Brown, 2008; King & Hardwick, 2008).

Cannabis hash and skunk have very different quantities of the active THC component.

Methods

The researchers used a cross-sectional case-control design. Patients presenting for first-episode psychosis were recruited from a clinic in the South London and Maudsley NHS Foundation Trust; patients who had an identifiable medical reason for the psychosis diagnosis were excluded. Control participants were recruited from the local area using leaflets, internet and newspaper adverts. There were 410 case-patients and 370 controls recruited.

Researchers gathered data on participants’ cannabis use in terms of lifetime history and frequency of use as well as type of cannabis used, i.e. skunk or hash. Participants were also asked about their use of other drugs including alcohol and tobacco, as well as providing demographic information.

Results

The case-patients and control participants were different in a couple of key areas (note: psychosis is more common in men and in ethnic minorities):

Case patients Control participants 
Male 66% 56%
Age 27.1 years 30.0 years
Caribbean or African ethnic origin 57% 30%
Completed high level of education 57% 90%
Ever been employed 88% 95%
Lifetime history of ever using cannabis 67% 63%

Participants with first episode psychosis were more likely to:

  • Use cannabis every day
  • Use high-potency cannabis
  • Have started using cannabis at 15 years or younger
  • Use skunk every day

A logistic regression adjusted for age, gender, ethnic origin, number of cigarettes smoked, alcohol units, and lifetime use of illicit drugs, education and employment history showed thatcompared to participants who had never used cannabis:

  • Participants who had ever used cannabis were not at increased risk of psychosis
  • Participants who had used cannabis at age 15 were at moderately increased risk of psychotic disorder
  • People who used cannabis or skunk everyday were roughly 3 times more likely to have diagnosis of psychotic disorder

A second logistic regression was carried out to explore the effects of a composite measure of cannabis exposure which combined data on the frequency of use and the type of cannabis used.Compared with participants who had never used cannabis:

  • Individuals who mostly used hash (occasionally, weekends or daily) did not have any increased risk of psychosis
  • Individuals who smoked skunk less than once a week were nearly twice as likely to be diagnosed with psychosis
  • Individuals who smoked skunk at weekends were nearly three times as likely to be diagnosed with psychosis
  • Individuals who smoked skunk daily were more than five times as likely to be diagnosed with psychosis

The population attributable factor (PAF) was calculated to estimate the proportion of disorder that would be prevented if the exposure were removed:

  • 19.3% of psychotic disorders attributable to daily cannabis use
  • 24.0% of psychotic disorders attributable to high potency cannabis use
  • 16.0% of psychotic disorders attributable to skunk use every day

These findings raising awareness among young people of the risks associated with the use of high-potency cannabis

Conclusions

The results of this study support the theory that higher THC content is linked with a greater risk of psychosis, with daily use of skunk conferring the highest risk. Recruiting control participants from the same area as the case participants meant that the two groups were more likely to be matched on not only demographic factors but also in terms of the actual cannabis that both groups were consuming.

The study has some limits, such as the cross-sectional design which cannot be used to establish causality. Also the authors have not included any comparison between those who smoke hash and those who consume skunk so no conclusions can be drawn about the relative harm of hash.

Media reports about the study have mainly focussed on the finding that ‘24% of psychotic disorders are attributable to high potency cannabis use’. This figure was derived from a PAF calculation which assumes causality and does not allow for the inclusion of multiple, potentially interacting, risk factors. Crucially the PAF depends on both the prevalence of the risk factor and the odds ratio for the exposure; the PAF can be incredibly high if the risk factor is common in a given population.

In this case, the prevalence rate of lifetime cannabis use was over 60% in both participant groups. According to EMCDDA, the lifetime prevalence of cannabis use in the UK is 30% among adults aged 15-64, so it is arguable that this study sample is not representative of the rest of the UK. The authors themselves note that “the ready availability of high potency cannabis in south London might have resulted in a greater proportion of first onset psychosis cases being attributed to cannabis use than in previous studies”, which is a more accurate interpretation than media reports claiming that “1 in 4 of all new serious mental disorders” is attributable to skunk use.

Future studies looking at the relationship between cannabis and psychosis should also aim to differentiate high and low potency cannabis. Longitudinal cohort studies are particularly useful as they have the same advantages as a case-control design but data about substance use could be more reliable as ‘lifetime use’ can be gathered from multiple measurements collected at a number of time points across the lifetime.

This innovative study is the first to distinguish between different strengths of cannabis in this way.

Links

Primary study

Di Forti M. et al (2015). Proportion of patients in south London with first-episode psychosis attributable to use of high potency cannabis: a case-control study (PDF). The Lancet Psychiatry, 2(3), 233-238.

Other references

King L, & Hardwick S. (2008). Home Office Cannabis Potency Study (PDF). Home Office Scientific Development Branch.

Potter DJ, Clark P, & Brown MB. (2008). Potency of Delta(9)-THC and other cannabinoids in cannabis in England in 2005: Implications for psychoactivity and pharmacology (PDF). Journal of Forensic Sciences, 53(1), 90-94.

Screening of A Royal Hangover: TARG goes to the movies

By David Troy @DavidTroy79 

I recently hosted a documentary screening of ‘A Royal Hangover’ on behalf of the Tobacco and Alcohol Research Group at the University of Bristol. The film documents anecdotes from all facets of the drinking culturpic1e in the UK, from politicians to police, medical specialists to charities, the church and scientists, and addicts and celebrities, with high profile personalities such as Russell Brand and controversial figures such as sacked Government Drugs Advisor Professor David Nutt. The director Arthur Cauty kindly agreed to take part in a question and answer session after the film to discuss his experience making the film and debate the issues raised in the film.

The film begins with Arthur talking about his own relationship with alcohol (or his lack of one).  He preferred to shoot silly films, play music or wrestle than go out drinking with his friends. The film deals with the history of alcohol starting off in the 16th and 17th century when it was safer to drink beer than water. Even babies were given what was called “small beer for small people”. In the early 18th century, gin became the drink of choice and reached epidemic levels, famously depicted in William Hogarth’s ‘Gin Lane’. pic2Gin was unregulated and sold not just in public houses but in general stores and on the street. Moving on to the 20th century, Lloyd George recognised the danger of alcohol to the war effort in World War 1, and was quoted as saying that “we are fighting Germany, Austria and drink; and as far as I can see, the greatest of these deadly foes is drink”. Around this time, restrictions on the sale of alcohol were introduced by government. During World War 2, beer was seen as important to morale and a steady supply of it was seen as important to the war effort. Since then, we have seen a steady increase in consumption levels through the ‘hooligan/lager lout’ phenomenon of the 1980’s and the binge drinking of the 1990’s and the early 2000’s. Consumption levels have been falling slightly since the mid 2000’s but there are still 10 million people drinking above the government’s recommended level.

During the film, Arthur investigates how different societies treat alcohol. French and American drinkers describe a more reserved and responsible attitude to alcohol. This is somewhat contradicted by 2010 data in a recent report by the World Health Organisation which reports that French people over the age of 15 on average consume 12.2 litres of pure alcohol a year compared to Britons at 11.6 and Americans at 9.2 litres respectively. The drinking culture of France and the United States is certainly different to that of the UK. The French consume more wine, less beer, and tend to drink alcohol whilst eating food. The US (outside of ‘Spring Break’ culture) is more disapproving of public intoxication. However, neither society should be held up as a gold standard when it comes to alcohol use.

The film talks about the enormous cost of alcohol to England; approximately £21 billion annually in healthcare (£3.5 billion), crime (£11 billion) and lost productivity (£7.3 billion) costs. These are the best data available, but costs of this nature are difficult to calculate. Arthur talked to professionals on the front line – he interviewed a GP who said that a huge proportion of her time is devoted to patients with alcohol problems and their families. She has to treat the “social and psychological wreck” that comes when one family member has an alcohol addiction. A crime commissioner from Devon and Cornwall police states that 50% of violence is alcohol-related in his area.

The film attempts to understand the reasons why alcohol use is at current levels, and offers some possible solutions. Alcohol is twice as affordable now as in the 1980’s and is more freely available than ever. This needs to be curtailed. Evidence suggests that alcoholic beverages were 61% more affordable per person in 2012 than in 1980, and the current number of licensed premises in England and Wales is at the highest level repic3corded in over 100 years. Licensed premises with off sales only alcohol licences have also reached a record high, more than doubling in number compared with 50 years ago. The evidence shows that price increases and restrictions on availability are successful in reducing alcohol consumption. More alcohol education in schools was highlighted as being necessary. The evidence suggests that alcohol education in schools can have some positive impact on knowledge and attitudes. Overall, though, school-based interventions have been found to have small or no effects on risky alcohol behaviours in the short-term, and there is no consistent evidence of longer-term impact. Alcohol education in schools should be part of the picture but other areas may prove more fruitful. The film suggests that parental and peer attitudes towards alcohol affect drinking norms, and these attitudes need to change. In multiple surveys, it has been found that the behaviour of friends and family is the most common influential factor in determining how likely and how often a young person will drink alcohol. Alcohol marketing was cited as a problem and it needs to regulated more stringently. Alcohol marketing increases the likelihood that adolescents will start to use alcohol and increases the amount used by established drinkers, according to a report commissioned by the EU. The exposure of children to alcohol marketing is of current concern. A recent survey showed that primary school aged children as young as 10 years old are more familiar with beer brands, than leading brands of biscuits, crisps and ice-cream.

David Nutt discussed research he conducted with colleagues, which assessed the relative harms of 20 drugs, including both harms to the individual and to others. They found that alcohol was the most harmful drug overall. Professor Nutt also covered the circumstances surrounding his sacking as government’s chief drug advisor; he claimed that ecstasy and LSD were less dangerous than alcohol, which led to his dismissal. This highlights the inherent tension between politics and science. Evidence can diverge from government policy and popular opinion, and scientists can lose their positions when reporting evidence that is politically unpopular. In my view, the reluctance of governments to implement evidence-based alcohol policies is frustrating; minimum unit pricing (MUP) being the latest example. Despite good evidence supporting how MUP can reduce alcohol-related harms, lobbying by the alcohol industry has halted its progress.

The film deals with the human cost of alcohol misuse, with personal stories of addiction permeating the film. Carrie Armstrong (who writes a blog discussing her battle with alcohol addiction), as well as Persia Lawson and Joey Rayner (who write a lifestyle blog ‘Addictive Daughter’), discussed the havoc alcohol caused in their lives, and explained how young men and women come to them for help with their own alcohol dependencies. Russell Brand talked about his own alcohol addiction during the film. He contends that his drug and alcohol use was medicinal and thinks that alcohol and drug addicts “have a spiritual craving, a yearning and we don’t the language, we don’t have the code to express that in our society”. Arthur interviewed Chip Somers of Focus 12, who talked about the low levels of funding to treat alcohol addiction. Only a small minority (approximately seven per cent) of the 1.6 million alcohol dependants in the UK can get access to treatment compared to two-thirds of addicts of other drugs.

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Arthur recorded over 100 hours of footage of drinkers on nights out during the course of filming. He described it as follows: “As the sun goes down, society fades away and what emerges from the shadows is a monster of low inhibition, aggression and casual chaos”. He sums it up as us “going to war on ourselves. On one side is the police, the emergency services, the council and various groups of volunteers and on the other side you’ve got everybody else”. He was assaulted three times and witnessed multiple scenes of violence close up. His bravery is admirable – there were many scenes I found difficult to watch. The scenes of senseless violence were horrible to look at, as were the images of individuals who were so intoxicated as to be helpless and in need of medical attention.

The Q&A after the screening was quite illuminating. Arthur spoke about the reception the film has been receiving at home and abroad. The reception has been great in the United States, where the film has had successful showings at film festivals. The interest in the UK has been a little disappointing, however, which Arthur puts down to the reluctance of society at large to acknowledge our dysfunctional relationship with alcohol. Nevertheless, there has been positive feedback from viewers of the film. Many people have contacted Arthur to tell him how the film has opened their eyes to their own relationship with alcohol and prompted them to make a change. The audience was keen to engage in the conversation. One person, who has a family member with an alcohol addiction, said how important it is to raise awareness of these issues. Another person called for policy measures to be implemented such as MUP to curb use across the population.

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Arthur came across as someone who is acutely aware of the damage alcohol is causing in the UK, and is doing what he can to raise the public’s consciousness about it. He has presented a unique look at booze Britain, in equal parts shocking, hilarious, sympathetic and thought provoking – a film we can all relate to. It was a very enjoyable and informative evening and I hope the audience took something away from it. I believe the arts and sciences need to work together to improve how knowledge is communicated. It was my hope that by showing this documentary, information on alcohol harms in society would be more accessible to a general audience. Change begins with the acknowledgement of new information that alters the view of ourselves and our behavior. It has been estimated that over 7 million people in the UK are unaware of the damage their personal alcohol use is doing. I believe the blame lies on both sides. Alcohol researchers need to communicate the harms of alcohol in more engaging and accessible ways and members of the general public need to seek out such information. All too often scientists get the reputation as being cold, boring, and amoral. Collaborating with filmmakers and other proponents of the arts on events such as the one I hosted can assist in changing that stereotype.

Is moderate alcohol consumption good for you?

By Marcus Munafo @MarcusMunafo 

This blog originally appeared on the Mental Elf site on 13th March 2015

wine

This is something many of us would like to be true – the idea that the occasional glass of wine has health benefits is compelling in a society like the UK where alcohol consumption is widespread.

Certainly the observational data indicate a J-shaped associationbetween alcohol consumption and mortality (O’Keefe et al, 2007), with the lowest mortality observed at low to moderate levels of alcohol consumption (equivalent to perhaps a pint of beer a day for men, and about half that for women).

However, observational studies like this are fraught with difficulties.

  1. First, people may not report their alcohol consumption reliably.
  2. Second, and more importantly, alcohol consumption is associated with a range of other lifestyle behaviours, such as diet and smoking, which will themselves influence mortality, so that isolating any specific association of alcohol is extremely difficult.
  3. Third, how non-drinkers are defined may be important – lifetime abstainers may be different from former drinkers (who could have stopped drinking because of health problems).

The last point illustrates the problem of reverse causality; alcohol consumption may be causally associated with a range of health outcomes, but some of those health outcomes may also be causally associated with alcohol consumption.

In a recent study in the BMJ, the authors argue that the problems associated with the choice of an appropriate referent group of non-drinkers are often overlooked in research into alcohol-related mortality.

They also argue that age is not adequately considered, which may be relevant because of physiological changes to the ageing body that influence elimination of blood alcohol. Knott and colleagues explored the association between alcohol consumption and all cause mortality for people aged less than 65 years and aged 65 or more, and separated never and former drinkers.

The lowest mortality observed is at low to moderate levels of alcohol consumption (equivalent to perhaps a pint of beer a day for men, and about half that for women).

Methods

The authors used data from the Health Survey for England, an annual, nationally-representative cross sectional survey of the general population, linked to national mortality registration data.

The analysis focused on adults aged 50 years or older, and investigated two measures of alcohol consumption: self-reported average weekly consumption over the past year, and self-reported consumption on the heaviest day in the past week. The outcome was all cause mortality (i.e., any death recorded during the period of data collection).

The primary statistical analyses were proportional hazards analyses for each of the two age groups of interest (less than 65 years and 65 years or more). They tested for whether any associations observed differed between males and females and, given strong evidence of a sex-dose interaction, reported sex-specific models for each age group of interest.

Statistical adjustment was made for a comprehensive list of potential confounders, such as geographical location, ethnicity, cigarette smoking, obesity and a range of socio-demographic variables.

Results

Protective associations were only observed with statistical significance (a point I’ll return to below) among younger men (aged 50 to 64 years) and older women (65 years or older), using a never drinker referent category after full adjustment.

Among younger men a protective relationship between alcohol consumption and all cause mortality was observed among those who reported consuming 15.1 to 20 units per week (hazard ratio 0.49, 95% confidence interval 0.26 to 0.91).

Among older women, the range of protective use was broader but lower, with reductions in hazards of all cause mortality observed at all consumption levels up to 10 units per week of less.

The study supports a moderate protective effect of alcohol.

Conclusions

The authors conclude that observed associations between low levels of alcohol consumption and reduced all cause mortality may in part be due to inappropriate selection of a referent group (all non-drinkers, rather than never drinkers) and inadequate statistical adjustment for potential confounders.

They also conclude that beneficial dose response relationships between alcohol consumption and all cause mortality may be specific to women aged 65 years or older.

There is a relative lack of data on older populations in relation to the association between alcohol consumption and all cause mortality, which this study addresses. The consideration of different definitions of the referent category is also valuable – the authors are correct that conventional definitions of “non-drinker” may be problematic.

However, to what extent should we believe the conclusion that beneficial dose response relationships may be age- and sex-specific?

As David Spiegelhalter has pointed out, the authors base their conclusion on which associations achieved statistical significance and which did not. However, the hazard ratios for all cause mortality are consistently lower for alcohol consumers than non-consumers in this study. Although the confidence intervals are wider for some consumption levels and in some sub-groups (males vs females, or younger vs older), the individual hazard ratios are all consistent with each other.

The wide confidence intervals reflect a lack of statistical power, principally due to the small number of never drinkers, and the small number of deaths. Although the data set is relatively large, by carving it up into a number of sub-groups, the statistical power for the individual comparisons is reduced. Spiegelhalter points out that the entire comparison for participants in the younger age group is based on 17 deaths in the male baseline group and 19 deaths in the female group.

As Andrew Gelman and Hal Stern have said, the difference between “significant” and “non-significant” is not (necessarily) itself significant. Indeed, focusing on statistical significance (rather than effect size and precision) can lead to exactly the problems encountered here. Low statistical power is also a problem, reducing the likelihood that a statistically significant finding is true, and (perhaps more importantly) dramatically reducing the precision of our effect size estimates.

Should we believe that beneficial dose response relationships are age- and sex-specific?

Strengths and limitations

There are some strengths to this study, notably the use of a more considered referent category of never drinkers, and the statistical adjustment for a broad range of potential confounders.

However, the primary conclusion of the authors does not seem to be borne out by their own data – hazard ratios for all cause mortality are lower for alcohol consumers than non-consumers at all levels of consumption, for both men and women, and for both the younger and older age groups.

Is moderate alcohol consumption good for us then? The observational data, including that from this study, continues to suggest so.

However we should also remain wary of evidence from observational studies, which can be notoriously unreliable, and cannot confirm that an association is causal. Ultimately, we may need to use novel methods to answer this question, such as Mendelian randomization which utilized the properties of genetic variants to enable stronger causal inference.

We should be wary of evidence from observational studies, which can be notoriously unreliable, especially in underpowered studies like this one.

Link

Knott CS, Coombs N, Stamatakis E, Biddulph JP. (2015) All cause mortality and the case for age specific alcohol consumption guidelines: pooled analyses of up to 10 population based cohorts (PDF). British Medical Journal, 350, h384. doi: 10.1136/bmj.h384

O’Keefe HF, Bybee KA, Lavie CJ. (2007) Alcohol and cardiovascular health: the razor-sharp double-edged sword. J Am Coll Cardiol. 2007;50(11)

Spiegelhalter D. (2015) Misleading conclusions from alcohol protection study. Understanding Uncertainty website, last accessed 11 Mar 2015.