Drinking Less But Greater Harm

Could Polarized Drinking Habits Explain the Divergence Between Alcohol Consumption and Harms Among Youth?

Mats Hallgren; Håkan Leifman; Sven Andréasson


Alcohol Alcohol. 2012;47(5):581-590. 

In This Article


Our findings indicate that a polarization in youth drinking is a likely explanation for the recent divergence between per capita alcohol consumption, which has decreased, and alcohol-related harmful effects, which have increased sharply among Stockholm youth over the past decade. For most young people, consumption reduced between 2000 and 2010, while the heaviest consumers (those in the top 5–10% of the drinking distribution) mostly increased their consumption over the same period. There was only one exception to this trend, with the younger females in Year 9 reducing their per capita consumption across all levels of drinking. Yet even here, the reductions over time were smaller among the heaviest drinkers compared with the moderate drinkers—a trend consistent with the polarization hypothesis. Across all the four groups, the dispersion of per capita consumption also increased significantly over time, indicating an increasing number of heavy drinkers in the tail end of the distribution. Together, these changes indicate that more young people drink at extremely high levels over time, while the majority continues to drink less.

Of particular concern are females aged 18–19 years. These young women report the largest increases in both the total volume of alcohol consumed and the frequency of binge drinking. Although we were not able to connect the anonymous self-report data with the hospitalization data, the dramatic increase in alcohol-related hospitalizations among females aged 15–24 years in Stockholm suggests that these young women are over-represented in serious alcohol-related harmful effects and represent a high-risk group for alcohol misuse.

The divergence between per capita consumption and alcohol-related harm has been observed elsewhere, so the polarization hypothesis may well apply to other populations; not only those in Sweden. In the UK, there has been a marked reduction in per capita consumption since ~2000 among 16–24-year olds (Meier, 2010). At the same time, alcohol-attributable hospital admissions have been increasing at a rate of 11% year on year, with an estimated 945,000 alcohol-related admissions in England in 2008/2009 (around 7% of all admission). Similarly, in Victoria, Australia, seven key measures of alcohol-related harm increased in the adult population between 1999 and 2008, while total consumption remained relatively stable (Livingston, 2008). Possible explanations for the divergence suggested by the authors included a rise in heavy episodic drinking (especially among females), an increased preference for higher alcohol content beverages and a polarization in drinking—although the latter possibility was not tested empirically.

The overall increase in alcohol-related hospitalizations in Stockholm could be driven by changes in the drinking behaviour of a relatively small but high-risk group, such as the heavy-drinking 18–19-year-old females identified in this study. This cohort may not be large enough to have much impact on per capita consumption, but large enough to influence hospital admission data, resulting in the present divergence between consumption and harm. A similar idea has been suggested by Mäkela and Österberg (2009) to explain the relatively large impact of a reduction in alcohol taxes in Finland on alcohol-related problems compared with per capita consumption.

On the aggregate level, the mean number of risk factors for alcohol misuse decreased between 2000 and 2010. However, the reduction was not consistent over time and there was intervening variability in scores. We predicted that the total number of risk factors reported by the heaviest drinkers would increase over time, mirroring the pattern seen in the consumption data, but this did not occur. Instead, we found a non-significant reduction in the total risk factor score for the heaviest drinkers, but with large variability in scores. The strength of the association between the risk factor total score and alcohol consumption was large when all the participants were examined (r = 0.468), but reduced to a small association among the heaviest drinkers only (r = 0.123). This weakened relationship might explain the increased variability in scores among the heavy drinkers, as the selected risk factors were responsible only for a small proportion of the total variance in alcohol consumption. Given these findings, the evidence for a polarization effect in the risk factor data is inconclusive.

It is likely that young people who routinely drink to excess are qualitatively different from their 'moderate' drinking peers. Adolescents who regularly drink to extremely high levels typically report more serious and on-going social and psychological problems, making themselves a unique subgroup in this respect (Petraitis et al., 1995; Zufferey et al., 2007). Consequently, the risk factors that apply to the moderate drinkers in the present study may not necessarily influence the behaviour of the heavy drinkers the same way (and visa versa). Risk factors for alcohol misuse differ according to gender (Danielsson et al., 2010) and substance type (Becker and Grilo, 2005), so it is conceivable that they could also vary according to the level of drinking, especially when consumption is exceptionally high. This possibility is supported by two recent studies that found that the risk factors for alcohol misuse in a sample of alcohol-dependent adolescents were different from the risk factors commonly reported in community samples where drinking levels tend to be much lower (Becker and Grilo, 2005; Nation and Helfinger, 2006).

Wider economic and social changes in Sweden have influenced recent drinking trends. Alcohol became more available and affordable as Sweden joined the EU in 1995 and associated trade restrictions were eroded. This general increase in the availability of alcohol may have disproportionately affected some people more than others. A recent Finnish study found that large reductions in the price of alcohol have led to substantial increases in alcohol-related mortality, mainly among individuals from lower socio-economic backgrounds (Herttua et al., 2008). On a societal level, there have been shifts in the distribution of wealth in Sweden, which have resulted in increased social and economic inequalities, especially since the 1990s (Klevmarken, 2006). A study by Fritzell et al. (2007a,b) examining changes in the living conditions of young people in Sweden between 1994 and 2005 (the period immediately following the last economic recession) also found a polarization tendency on three central dimensions of welfare: work and employment, economic resources and health, especially mental health. The full impact of the current global economic crisis remains to be seen. However, it is conceivable that these social changes now affect young people in the form of greater disparities, which are associated with a higher incidence of social problems generally, including heavy drinking.

Our findings have implications for alcohol policy, both in Sweden and elsewhere. First, our data are an important reminder that changes in per capita consumption can hide significant shifts in the drinking habits of heavy drinkers. To see the complete picture, changes in the dispersion of drinking relative to per capita consumption should also be examined. Policy decisions based on changes in per capita consumption alone are insufficient because this can hide the emergence of heavy drinking subgroups. For the moment, we need to know more about the social backgrounds and the risk factors these young people incur, so that targeted interventions can be developed to reduce their current levels of drinking and associated harmful effects.

Although we have not set out to empirically test Skog's theory of the collectivity of drinking cultures—and some have questioned whether this can be done (e.g. Gmel and Rehm, 2000), our findings have implications for this highly influential theory. Given the reductions in per capita consumption seen here, Skog's theory would predict roughly parallel reductions in the heaviest drinkers, but this did not occur. Skog has noted that smaller, high-risk groups might be less influenced by the drinking behaviour of those around them because of social isolation, exclusion or other individual traits. If this is true, then we need to understand why alcohol policies appear to influence the drinking behaviour of some individuals more than others. Previous researchers have observed diverging patterns of alcohol consumption in subgroups (e.g. Gustafsson, 2010), and other exceptions to Skog's general rule of collectivity (Stockwell et al., 1997). What the present study adds is an empirical confirmation that the polarization phenomenon occurs among youth in the Swedish context. Future research should examine the alcohol and risk factor polarization hypotheses in different contexts, and explore associations between changes in consumption and both the number and the type of risk factors that young people are exposed to. What may also be needed is analysis of risk factors over time at community and societal levels, including measures of income and social inequality, which have widened in many parts of the world. Such analyses should be combined with a theory of how societal increases in inequality are linked to individual-level risks for alcohol misuse, and the various mechanisms that are involved.

Strengths and Limitations

The Stockholm Student Survey provides a unique opportunity to closely examine changes in the drinking habits of young people. Both the number of participants and the response rates are consistently high, helping to ensure that the sample is representative. The quality of the data has enabled us to empirically test the polarization hypothesis using both alcohol consumption and risk factor data. The results have implications for alcohol prevention in Sweden and possibly in other countries where similar patterns have been observed.

Our findings are based on self-report surveys and the inherent limitations of such surveys are well known. Respondents tend to under-report the amount of alcohol they consume, particularly at high levels (Northcote and Livingston, 2011). Previous Swedish studies suggest that adolescent non-responders are more likely to be heavy consumers than those who do respond (Romelsjö and Branting, 2000). It is also possible that some of the heaviest drinkers were excluded from the survey because they were not attending school when the survey was conducted. Again, this could lead to an underestimate of consumption. However, our reliance on self-report data does not invalidate our findings; anonymous self-reports are generally valid, provided confidentiality is stressed, which it was in this survey (Campanelli et al., 1987). After the year 2000, the survey was expanded to include additional risk and protective factors. Some of these new factors (e.g. number of heavy drinking friends, social support, etc.) are relevant, but were not included in the analyses because they were absent from the 2000 survey, and therefore, could not be cross-matched with the 2010 data. Using a theory-driven approach to select the risk factors (as opposed to a statistical approach) enabled us to see whether there had been a change over time in the same 13 risk factors, both in the total sample and among the heaviest drinkers. This approach may result in a different number and/or collection of risk factors, compared with a statistical approach driven by logistic regression modelling. Finally, as the questionnaires were anonymous, it was not possible to follow-up non-responders and compare them with the survey participants. We also acknowledge that many factors other than alcohol use per se can influence alcohol-related hospitalization data, including administrative changes to patient admissions.


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