Can alcohol make you happy? A subjective wellbeing approach
Introduction
While alcohol can lower wellbeing – globally, alcohol is the fifth biggest risk factor for premature death and disability (Lim et al., 2012), as well as having a contributing role to a range of social problems and economic costs (Baumberg, 2006) – it is also clearly a source of pleasure. However, there are few empirical studies of links between wellbeing and alcohol (see below), and almost no academic discussion of the implications for policy (rare exceptions being Keane, 2009, Room, 2000).
This lack of evidence is an obstacle to developing evidence-based alcohol policies. The main existing approach for looking at the wellbeing impacts of drinking is the ‘consumer surplus’ approach – but the naïve form that has sometimes been used by policymakers is based on flawed assumptions that produce large overestimates of the positive wellbeing impacts of drinking while largely ignoring negative wellbeing impacts (see below). For example, in relation to recent UK Department of Health proposals to introduce minimum unit pricing, the Treasury conducted an impact assessment using this approach, and found that the costs of minimum pricing (via a loss of positive wellbeing) outweighed its benefits, temporarily halting the policy until a critical note was received from outside experts.
Conversely, other studies estimate the negative wellbeing impacts of drinking while ignoring any positive impacts. Recent studies have found new ways to value negative wellbeing impacts of alcohol, including wellbeing-related ‘harms to others’ (Johansson et al., 2006, Laslett et al., 2010), and reduced health-related quality-of-life among people with an alcohol use disorder (Johansson et al., 2006). However, positive wellbeing impacts are barely mentioned. For example, the leading ex ante impact assessment of alcohol policies, the Sheffield Alcohol Policy Model, estimates that a 50p minimum price in Britain would lead to wellbeing benefits worth more than £2bn over 10 years (Purshouse et al., 2009, p112), while ignoring positive wellbeing impacts.
A new direction is necessary to contribute to evidence-informed policy. This paper therefore outlines an alternative ‘empirical wellbeing’ approach to looking at the link between alcohol and wellbeing, and presents the results of the approach applied to a nationally representative cohort study (Study 1) and an innovative smartphone-based data set (Study 2).
To the extent that previous studies have estimated anything beyond purely negative wellbeing impacts of alcohol, they have used a naïve version of ‘consumer surplus’ (Aslam et al., 2003, cebr, 2009). This starts from the assumption that consumers receive benefits to their individual welfare – ‘utility’ – from drinking that are at least as large as the money they spend. Crucially, they also receive a ‘surplus’ of utility beyond what they pay – i.e. the money that they would have been willing to pay for that drink if the price was raised – which has been argued to be a measure of the ‘pleasure of drinking’ (Aslam et al., 2003:35).
The implication is that involuntary (policy-induced) reductions in alcohol consumption will reduce wellbeing, in two ways:
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Extra spending: people pay a higher price for the drinks that they continue to consume, so the surplus beyond the price they pay will be reduced.
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Reduced drinking: people will stop consuming some drinks, for which they previously received a utility surplus.
Using this logic, the economic consultants NERA in a report for the Greater London Authority estimated that the pleasure of drinking was worth over £2bn in London (Aslam et al., 2003), while the economic consultants cebr in a report for SAB Miller estimated that a 5% reduction in the consumption of moderate drinkers in the UK would cost £600 m/pa (cebr, 2009).
However, the general assumptions on which these estimates are based – perfect rationality, perfect information and perfect foresight – are naïve compared to those made by contemporary welfare economists in the light of evidence from behavioural economics (Cawley and Ruhm, 2011). The assumptions are even more challenging when applied to alcohol. While dependence has been shown to be potentially ‘rational’ in the terms of Becker and Murphy's theory, it seems unlikely that addicts consistently make consumption decisions that maximise their own welfare (e.g. Bernheim and Rangel, 2004). Non-addicted drinkers can also less easily be assumed to be optimising their welfare as they become more intoxicated. Given that the majority of all drinks in the UK are consumed beyond the Government's recommended weekly or daily limits (Baumberg, 2009), policymakers' use of naïve consumer surplus estimates is difficult to justify.
This does not mean that the consumer surplus approach to cost-benefit analysis is fundamentally invalid. Modern welfare economists have produced extensions of the standard model to deal with imperfect information, present-biased preferences, temptation, addiction (Bernheim and Rangel, 2004, Cawley and Ruhm, 2011), and ‘suspect’ choices in general (Bernheim and Rangel, 2007). The challenge, however, is calibrating these models with reliable evidence on which choices are suspect. To the extent that alcohol studies have taken account of ‘suspect’ choices, they have made implausible adjustments, e.g. assuming that policies have no wellbeing impacts on heavy drinkers whatsoever (cebr, 2009, p46). More sophisticated revisions to the consumer surplus approach have been suggested for tobacco and gambling. The Australian Productivity Commission (1999:5.20–5.21) assumed that in the absence of addiction, gambling addicts would behave like non-addicted regular users. While defensible for gambling, this is still fundamentally arbitrary, and considers only addiction rather than intoxication. A more sophisticated recent study (Ashley et al., 2015) uses a series of assumptions to estimate how much people would smoke if they were non-addicted and fully took account of smoking-attributable reduced life expectancy. However, this method only presently exists for tobacco, and further work will be needed to see if it can be convincingly applied to the more complex consequences of drinking.
The main alternative to the consumer surplus approach is the subjective wellbeing approach, which investigates how far drinking makes people describe themselves as (un)happier. Using people's self-reported wellbeing has proved a contentious idea (MacKerron, 2012a), primarily because it is unlikely to be a perfect measure of actual wellbeing. Not only are there questions about how far we have insight into our own levels of happiness, but different people are likely to interpret survey questions on wellbeing differently and even to construct ‘happiness’ differently, confounding attempts to understand reported wellbeing through differences in people's lives (Wilkinson, 2007).
However, many of these problems can be minimised through better research design, such as focusing on changes within a culture – or even within a single individual, as we do below – which are likely to have greater validity (MacKerron, 2012a). We believe that subjective wellbeing approaches are one valuable perspective on wellbeing, a view shared by bodies such as the UK Treasury (Fujiwara and Campbell, 2011), and reflected in the burgeoning field of ‘happiness studies’.
Wellbeing is a multidimensional construct, including (but not limited to) both emotional wellbeing at a particular moment — “the frequency and intensity of experiences of joy, fascination, anxiety, sadness, anger, and affection that make one's life pleasant or unpleasant” (Kahneman and Deaton, 2010:16489) — and a person's wider satisfaction with their life, a cognitive reflection beyond individual moments. It cannot be assumed that any cause has identical impacts on each conception of wellbeing (Kahneman and Deaton, 2010).
This may be particularly true for alcohol because short-term pleasures and pains may overspill beyond the moment of drinking. There are negative short-term overspills via hangovers, and overspills on multiple timescales via health/social harms. More positively, it is often suggested that alcohol improves sociability, with real-world interactions reported to be more agreeable with alcohol (aan het Rot et al., 2008), laboratory studies showing a reduction in social anxiety (Battista et al., 2010), and qualitative research describing ‘anticipatory pleasures’ and ‘retrospective bonding’ around drinking (Brown and Gregg, 2012). However, the scale, dose-response and timing of some of these overspill effects is unclear.
A further issue is that average impacts are likely to conceal considerable heterogeneity. Partly this is because the response to alcohol is ‘biphasic’, with different effects in the ascending and descending limbs of the blood alcohol curve – stimulant effects seem to be restricted to increasing intoxication, whereas sedative effects predominate during decreasing intoxication (Martin et al., 1993) – and with different impacts at different doses. There has been a temptation to suggest that all of the pleasures of drinking come with ‘moderate’ consumption rather than intoxication, but the strong form of this claim has been subject to critique (Keane, 2009, Room, 2000). Instead, heavier drinkers report greater stimulant and lower sedative effects (King et al., 2011), and people expect greater levels of both happiness and misery at higher levels of consumption (Adey et al., 2010).
Heterogeneity is also likely because the pleasures (and pains) of drinking are often due to our own expectations and the reactions of people around us (Room, 2000). This not only means that drinkers’ expectations may influence wellbeing, but that the relationship between alcohol and wellbeing will vary considerably across different cultures (Peele and Grant, 1999), particularly for the social consequences that are most closely bound up with expectations. Alcohol may therefore have different impacts on different concepts of wellbeing, when measured over different time periods, or for different population groups. While we return to this in the Discussion, our analyses here primarily focus on ways of considering the average effects of drinking on subjective wellbeing.
There are no reviews of the impact of alcohol on wellbeing (unlike for depression; see Boden and Fergusson, 2011, which suggests a non-linear causal impact of drinking). A number of individual studies exist, but these are primarily cross-sectional studies where the direction of causality is unclear. Two types of longitudinal study have been conducted:
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The first looks at the lagged impact of drinking on later wellbeing. Among adolescents, alcohol use either has no significant effect (Mason and Spoth, 2011) or is associated with lower later wellbeing (Newcomb et al., 1986); while among young adults, studies variously find that greater levels of drinking are associated with higher later wellbeing (net of the effect of adverse consequences; Molnar et al., 2009); lower later wellbeing (controlling for genetic factors; Koivumaa-Honkanen et al., 2012); or no effect (Bogart et al., 2007). However, while this approach captures slowly-acting effects, it seems unlikely to capture shorter-term pleasures of drinking.
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The second type of study looks at the immediate association of drinking with wellbeing, but further controls for time-invariant unobserved factors using fixed effects (‘FE’) modelling (see below). Only two such studies have been conducted, both using the Russian Longitudinal Monitoring Survey (Graham et al., 2004, Massin and Kopp, 2014); Massin & Kopp's more robust study finds no relationship between alcohol consumption and wellbeing among women, but that heavier drinking men have lower life satisfaction.
However, there are few longitudinal studies of adults, and even these face challenges of causal inference due to the lengthy lags between waves. Moreover, we would expect cross-cultural variation in the cultural associations of alcohol and pleasure, but the only FE studies are from Russia. The remainder of the paper therefore presents two studies using FE analyses of UK data, providing longitudinal data on the short-term relationship between alcohol and wellbeing in Britain for the first time.
Section snippets
Design
To investigate the association between drinking and wellbeing, the analysis uses FE models that examine how far within-person changes in drinking are associated with within-person changes in wellbeing. The strength of FE models is that they remove unobserved, time-invariant confounding, and as a result have been recommended for studying both the impacts of alcohol (French and Popovici, 2011) and influences on wellbeing (Ferrer-i-Carbonell and Frijters, 2004). In Study 1, we use FE analyses of a
Design
Study 1 found no significant relationship between changes in drinking levels/frequency and changes in life satisfaction, but that developing alcohol problems is associated with lower life satisfaction. However, we know that drinking may have different impacts on different aspects of wellbeing over different timescales, and this requires a different type of data. We therefore make use of a unique smartphone-based dataset – ‘Mappiness’– that enables us to examine the association of drinking with
Acknowledgements
With thanks to Kenzo Asahi (LSE) for BCS data work, to attendees at the 2013 meeting of the Kettil Bruun Society, to the ScHARR team for their help and patience, and to editors/reviewers who provided valuable comments. This work was partly funded by the UK Medical Research Council (MRC) and Economic and Social Research Council (ESRC), Interdisciplinary Alcohol Research Programme grant G1000043. Mappiness data collection was funded by the ESRC, grant PTA-031-2006-00280.
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