year, 3-years and 5-years, respectively.

Table 1. Baseline characteristics of daily smokers in the intervention and the control group of the Inter99 study.

To answer our research-question we looked at the generalised linear mixed model. Odds ratios of abstinence from smoking for persons in the intervention group with low and medium education were generally higher, when comparing with control group, than for persons with high education, even though they were nonsignificant for persons with low education at three and five-year follow-up (Table 2). This indicates that persons with lower SEP apparently benefitted more of the smoking cessation intervention. However, the interaction between group and education was non-significant (p = 0.510, 0.805 and 0.508 at one-, threeand five-year follow-up), indicating that the differences in quit rates across educational groups were not significantly different in the intervention and the control group. The interaction between education and time was non-significant (p = 0.962). Neither did we find the three-way interaction between group, education and time significant (p = 0.878).


In this randomised population-based intervention study we found that smokers across all educational levels did benefit from the anti-smoking intervention, and that the intervention did not increase the social inequality in smoking. Persons with higher education had generally higher abstinence rates than persons with lower education, both in the intervention and in the control group, and the gap increased over time. Abstinence rates were highest in the intervention group, offering lifestyle counselling and group based smoking cessation, and lowest in the control group.

There is no sign that the intervention had increased the social inequality in smoking. At five-year follow-up, smokers with low education in the intervention group reported to quit at the higher rates than smokers with moderate education in the control group. In general, odds ratios of abstinence from smoking for persons with low/ medium education in the intervention group were higher, than for persons in the control group, indicating that persons with low/medium education maybe benefitted more of the smoking cessation intervention than those with high education. Yet, the interaction term between education and group was not significant. This could be

Table 2. Probability of being abstinent from smoking across socioeconomic groups, measured by length of education. High intensity intervention group A compared with control group C (= reference). Five years follow-up of the Inter99 study (1999-2006), Denmark.

explained by the fact that relatively few persons had low and high education (small groups with broad confidence intervals).

To our knowledge, no previous randomised studies have described the effect of a high risk strategy. This strategy, described by Geoffrey Rose, seeks to protect susceptible individuals, and implies some form of screening and risk assessment. This is followed by a prevention practice, for example providing protection against the effects of exposure (e.g. hepatitis vaccine), reducing the level of exposure (e.g. statins) or removing the exposure (e.g. smoking cessation). The high risk strategy is typically implemented in the health care system and is provided by health care professionals [24]. In our study, we screened for high risk of IHD and offered lifestyle counselling in order to remove the negative health effects of an unhealthy lifestyle.

Can we answer the question “what messages and interventions work to get lower socioeconomic groups to stop smoking?” A recent review concluded that there is considerable evidence that media campaigns to promote smoking cessation are often less effective among socioeconomically disadvantaged populations [25]. Increasing the price of cigarettes may provide a means of reducing social disparities in smoking [26,27]. However, not all studies have found this beneficial effect [28], and as smoking prevalence in the Western countries is falling, price increases may become less effective as an inducement for hard-core smokers to quit [29]. A recent study found that a higher price on tobacco actually increased social inequality in smoking, as poor smokers were heavier, more tobacco-dependent smokers, who had difficulties to quit [30].

The effect of a smoking ban in public places, showed a significant reduction in acute coronary events after a smoking ban, which tended to be greater among lower socioeconomic groups [31]. Partial bans, on the other hand (e.g. allowing smoking in some bars/restaurants), may be more likely to worsen socioeconomic inequalities in smoking prevalence [32].

The English National Health Service stop smoking services offer free professional support, and focus on the individual, thereby reminding of the high risk strategy. An observational study found that these services probably make a modest contribution to reducing inequalities in smoking prevalence [33].

It has recently been suggested that a new strategy, “the vulnerable populations theory” could be a good supplement to the other well-established public health strategies. The idea was to move away from the risk factor epidemiological thought, which tends to focus largely on behaviour alone, and suggest that some groups are vulnerable with regard to the social structure and their practices [34]. Other authors have argued that the term “vulnerable populations” is not without problems, including potential stigmatisation [35]. It is important that we debate the consequences of the established public health strategies and discuss new strategies.

This study shows that it is feasible to attract smokers with low SEP to a programme with lifestyle counselling, and group-based smoking cessation. The Inter99 study used a proactive recruitment strategy by sending personal invitations with a prearranged date and time. It is worth to note that smokers with low education who were offered assistance to quit obtained higher quit-rates than smokers with moderate education in the control group, at five-year follow-up.

The multi-factorial approach (the lifestyle consultation also addressed diet, physical activity and alcohol consumption) may have been important in order to reach a more unselected group of smokers. Probably, many smokers, and especially smokers with low education, would not have attended the clinic if we had invited smokers only, and focused on smoking cessation only. Successful change of lifestyle inspired some non-motivated smokers. e.g. we experienced that some obese smokers, who had experienced a successful loss of weight when participating in a diet and exercise group, found confidence to join a smoking cessation group at next follow-up visit. Thus, the potentially active components of this intervention are difficult to untangle.

Measuring SEP is very complex and each measurement has different strengths and weaknesses. There is no single best indicator of SEP [36,37]. In general, education is relevant to people regardless of age or working circumstances, it is a strong determinant of employment and income and it reflects knowledge. The variable used in this paper, occupational education, is a frequently used measure of SEP in Denmark, significantly associated with chronic disease [19].

The most important weakness is the low participation rate and drop-out in the follow-up, which leads to selection, as abstinence is known to be associated with attendance [38]. In a baseline publication we found that participation rate was higher in younger women than in younger men, and it increased with increasing age until 55 years of age after which it declined. The participants in the intervention group did not differ from those in the control group, regarding former admissions for all causes, IHD, CVD, and diabetes [14]. We suppose that there was a higher dropout in continuous smokers in the intervention, as the expectations of quitting were higher than in the control group. The social non-smoking norm in those with high education would probably result in a higher dropout of continuous smokers with high education. We can not rule out the possibility that bias in self-report may have affected results. In both cases we suppose that bias would be more pronounced in the intervention groups than in the control group. The possibility of residual confounding due to unknown or unmeasured confounders always exists.

The strengths of this study are the randomisation, the large size, the long follow-up and the setting in a general population, including unselected smokers from all socioeconomic levels. The known baseline differences between smokers in the intervention and the control group have been adjusted for. The use of advanced statistical analyses which hold under a missing at random assumption increases the probability of valid results. Even though we only presented self-reported abstinence in this paper, smoking abstinence has previously been validated in the intervention groups [18].


In this population-based randomised intervention study, smokers across all educational levels benefited from the anti-smoking intervention, and the intervention did not increase the social inequality in smoking. It is worth to note that smokers with low education who were offered assistance to quit obtained as high quit-rates as smokers with moderate/high education in the control group, at five-year follow-up. As there is evidence that mass media increase social inequality in smoking, legislation combined with proactive smoking cessation support to smokers with low SEP seem a better alternative, when planning strategies to reduce social inequalities in health.


We thank the whole Inter99-staff and all persons participating in the study. Also, we thank the funding providers. Both those who funded this paper and those who funded the Inter99 study. This work was supported by: Tryg Foundation and Helse Foundation. The Inter99 study was funded by: Danish Medical Research Council; The Danish Centre for Evaluation and Health Technology AsSEPsment; Novo Nordisk; Copenhagen County; Danish Heart Foundation; The Danish Pharmaceutical Association; Augustinus Foundation; Becket Foundation; Ib Henriksens Foundation. The researchers are all independent of the founders. The study was initiated by Torben Jorgensen, Knut Borch-Johnsen, Troels Thomsen and Hans Ibsen. The Steering Committee of the Inter99 study: Professor D.M.Sci. Torben Jorgensen (principal investigator), Professor D.M.Sci., Knut Borch-Johnsen (principal investigator on the diabetes part) and Ph.D. MPH Charlotta Pisinger.


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