The effects of maximising the UK’s tobacco control score on inequalities in smoking prevalence and premature coronary heart disease mortality: a modelling study

Smoking remains common in England, with 19 % of adults aged 16 and over reported as smokers in 2013 [1]. This prevalence changed slightly from 21 % in 2007 [2]. Furthermore, large differences in smoking prevalence persist across socioeconomic groups; over 30 % of people with routine and manual jobs smoke, compared to less than 15 % of those in managerial and professional occupations [2, 3]. Smoking explains more than one-quarter of the socioeconomic gradient in total mortality in Great Britain [4].

In 2013, smoking caused an estimated 80,000 deaths in England among adults aged 35 and over. This amounts to 17 % of all deaths for these ages, unchanged since 2005. Over 450,000 hospital admissions were attributable to smoking, representing 4 % of all adult admissions [5]. These numbers may underestimate the true burden of smoking, as a recent study has expanded the list of diseases linked to smoking [6].

Circulatory diseases alone represent 17,300 (13 %) deaths and 134,000 (19 %) hospital admissions [2]. Coronary heart disease (CHD) has the highest number of smoking attributable deaths (7900) among circulatory diseases and the third highest number overall, after lung cancer and chronic obstructive pulmonary disease [2].

The United Kingdom (UK) has strong tobacco control policies compared to many European peers, achieving the highest score on the Tobacco Control Scale (TCS) (74 out of 100) among 34 European countries [7]. The TCS is an expert-developed instrument for assessing the strength of tobacco control policies with data compiled via a survey of national representatives to the European Network for Smoking and Tobacco Prevention, supplemented with data from other data sources (described in more detail in [7]). The most recent survey took place in 2013 and represents legislation in place as of 1 January 2014, prices as of 1 July 2013, and tobacco control budget for 2012. The TCS assesses six types of tobacco control policies; price, public place bans, public information campaign spending, advertising bans, health warnings, and treatment, each based on several indicators. World Health Organization MPOWER rankings for the UK are reassuringly similar [8].

Systematic reviews have found some evidence of socioeconomic gradients in effectiveness of tobacco control policies [9‐12]. However, with the exception of taxation, this evidence is limited, mixed and further complicated by different definitions of socioeconomic circumstance (e.g. education, occupation, income). Interestingly, evidence suggest that tobacco tax increases are more effective among the less well-off.

There is a gap in the literature relating socioeconomic inequalities in effectiveness of tobacco control policies, to inequalities in health outcomes. In this study, we therefore evaluated the potential effectiveness of maximising the TCS score for the UK using a model stratified by socioeconomic circumstance (SEC). We then linked predicted reductions in smoking prevalence to reductions in premature CHD mortality in England and assessed changes in inequality of premature CHD mortality.

The previously validated, deterministic, cell-based IMPACT Policy Model has been used to model the change in adult smoking prevalence, in England, that might result from changes in tobacco control policies, and translated it to CHD deaths using a population attributable risk fraction approach [13, 14]. The method has been previously used to analyse health benefits of reduced smoking prevalence in other European countries [15]. The uncertainty was estimated using probabilistic sensitivity analysis in a Monte Carlo approach (please refer to the Additional file 1 for a detailed description). Of the four UK countries, analysis was restricted to England because smoking prevalence can be directly linked to a health outcome using a socioeconomic indicator.

Improving all smoking policies to maximize the TCS could reduce overall smoking prevalence in England from 20 % to approximately 17 % (95 % Confidence Interval (CI): 16.0–18.7 %). This would represent an absolute decrease of some 3 % and a relative reduction of approximately 15 % (95 % CI: 7–21 %). Table 2 shows the adult smoking prevalence for England by IMDQ and gender, at baseline and with full implementation of the TCS policies.

The effect would be greatest among the most deprived quintile, who might achieve an absolute reduction of approximately 5.8 % (95 % CI: 2.2–6.7 %) and a relative reduction of 19 % (95 % CI: 7–21 %) (Fig. 1, Table 2). The reduction would be higher in men (6.4 %; 95 % CI: 2.8–6.9 %), because they have higher baseline smoking prevalence, than in women (5.3 %; 95 % CI: 2.2–5.8 %).

Taxes might contribute about 48 % (95 % CI: 41–57 %) of the predicted decline, and this effect could be substantially larger in the most deprived quintile (68 %). Plain packs would contribute about 15 % overall (95 % CI: 11–17 %) (Additional file 1: Table S3).

The model estimated that a total of approximately 3300 (95 % CI: 2200–4700) premature CHD deaths might be prevented or postponed, about 2 % (95 % CI: 1.4–2.9 %) of all predicted premature CHD deaths from 2015–2025 (Table 2). These deaths prevented or postponed would lead to approximately 52,000 LYG (95 % CI: 35,000–76,000). Due to their higher smoking prevalence and higher CHD mortality, the most deprived quintile should benefit more, resulting in an absolute inequality reduction of some 1000 (95 % CI: 700–2200) premature CHD deaths. The most deprived quintile would also gain the most life years (19,000; 95 % CI: 13,000–29,000). Even if there is no SEC gradient in the tax policy effect (Additional file 1: Table S4), the benefits would still favour the most disadvantaged groups, but the results would not be as strong.

Among men, most (about two-thirds) of the life years gained would be in the age groups 45–54 and 55–64. The remainder would be about evenly split among 35–44 and 65–74. This demonstrates that among younger men even a small reduction in CHD mortality can lead to a substantial gain in life years. This holds across all deprivation quintiles. Among women, most of the gain in life years is at ages 55–64 and 65–74. The CHD mortality at ages 35–44 and 45–54 is too low among women for there to be substantial improvement except among the most deprived (Table 3).

We modelled the effect that fully implementing all elements of the TCS would have on smoking prevalence in England and how the resultant changes might vary by socioeconomic circumstance. Improving all smoking policies to achieve a maximum score on the TCS might reduce smoking prevalence in England by approximately 15 % in relative terms among adults ages 35–74, and even more in the most deprived socioeconomic quintiles. There would be over 3000 fewer premature CHD deaths with the biggest benefits in the most deprived groups.

Reassuringly, our estimated smoking prevalence reduction attributable to the modelled tobacco control policies seems similar to estimates from a recent study using SimSmoke (~15 % versus ~17 % of relative reduction) [39]. Unfortunately, direct comparison of IMPACT and SimSmoke on avoidable deaths is not possible, because SimSmoke estimates deaths from any smoke-attributed disease rather than CHD specifically.

We estimated that an excise tax increase that increased pack price by 20 % would contribute about half of the total reduction in smoking prevalence. This increase is feasible, considering the price of tobacco has increased by more than 80 % over the last ten years [2]. Excise tax increases are generally considered the most immediate and effective path to quitting [40]. In reality, evidence suggest that the more deprived are more sensitive to price change and reduce consumption more than the less deprived [18‐20], rendering tobacco price policies the most equitable option for tobacco control [12]. In addition, the increased tax revenue may be redistributed to the less well-off through targeted smoking cessation and other health promotion programmes, further increasing the equity of this policy.

The TCS is based on a comprehensive, multi-pronged approach to tobacco control and measures three key areas: accessibility, affordability, and acceptability. It is generally agreed that comprehensive approaches to tobacco control work best because they lower initiation, increase cessation and reduce consumption [8, 41]. The TCS score across countries has been shown to be positively correlated with quit attempts [42]. TCS is therefore a useful metric when focussing on adult smoking prevalence, as we have done. Most of the policy categories would also counteract youth initiation of smoking, but different effect sizes and SEC gradients might be needed.

Despite the usefulness of TCS score for policy analysis and relative intra-country comparisons a TCS of 100 does not mean that there is no further room for improvement. This is especially true for countries already scoring high in the TCS, like UK. A typical example is policies on tobacco price, where UK has the highest in Europe; yet it can increase even further depending on political will, achieving a score higher than 100. Therefore, our decision to model the optimum TCS score is based on the possible usefulness for policy makers rather than an ultimate goal for UK tobacco control policy.

Stricter smoking policies have already contributed to rapid improvements in cardiovascular health in the UK [43, 44] and have reduced health inequalities in Ireland [45]. CHD and other vascular diseases can show rapid improvements in mortality due to risk factor changes [46]. We demonstrated that declines in smoking prevalence would lower premature CHD mortality and that the most disadvantaged socioeconomic groups would benefit most. This would reduce absolute inequality of premature CHD mortality. Many other tobacco related cancers and other non-communicable diseases would also benefit from smoking cessation, though the time lag between risk factor change and mortality improvement may not be as immediate.

Improvements in the policies we assessed would make a dent in current adult smoking prevalence in England, but further policy initiatives could have additional impacts and would be required to begin talk of a “Tobacco End Game” [47, 48]. Recent research suggests that e-cigarettes might help with smoking cessation in the short-term but not in the long-term, although further research is needed [49, 50]. A ban on smoking in cars due to be implemented in England on 1^st October 2015 could lead to more people declaring their homes smoke-free [51], which itself might enable quit attempts [52]. Small trials of financial incentives for pregnant women to stop smoking appear promising [53]. The government has also recently consulted on the possibility of a minimum excise tax and a levy on tobacco companies [54], both of which could raise prices further and, in the case of the former, help narrow inequalities in smoking by closing the price gap between cheap and expensive cigarettes [55]. When the tobacco purchase age was raised from 16 to 18 in England, smoking prevalence declined dramatically among 16–17 year olds [56]. Further raising the tobacco purchase age, as currently in place or under consideration in parts of the US, might accelerate long-term reductions [57, 58]. Finally, various more innovative options including ‘very low nicotine content’ (VLNC) cigarettes sold at a lower price than standard cigarettes could play a role in further reducing tobacco use [59]. Yet, challenges lay ahead. The observed and forthcoming reductions in funding for mass media campaigns and smoking cessation services may have detrimental effects on tobacco control and postpone the ‘end game’ further in the future [25, 60].

A comprehensive improvement in tobacco control policies in England could have immediate, long-lasting effects. Health would improve substantially more among those who stand to gain the most, thus narrowing health-related inequalities. Further research is needed to explore the equity of specific tobacco control policies and to identify their optimal mixture to maximise efficiency and equity; particularly considering the challenges that ongoing cuts in Public Health funding across England pose to communities.