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Given the oft quoted proposition that health promotion interventions frequently increase, rather than decrease, socioeconomic inequalities in health (SEIH),1 we were interested to read the article by Lowey et al.2 However, we believe that the title of this article is misleading, that the authors have not analysed the data to its fullest potential, and that a number of the conclusions drawn are unjustified.
The authors do not present any data on the magnitude of inequalities in smoking in the areas studied either before or after the introduction of smoking cessation services. Without such data, conclusions relating to the impact of the intervention on inequalities in smoking rates by deprivation quintile can-not be drawn. As the authors note, the lack of data on overall smoking rates in the different deprivation quintiles means that one cannot immediately determine the impact of the intervention on smoking rates and hence inequalities. However, it is possible to carry out sensitivity analyses based on estimated smoking rates to investigate the potential impact of the intervention on inequalities in smoking.
Table 1 shows the number of male smokers before and after the intervention, using data published in the paper and hypothetical pre-intervention smoking rates representing perfect equality (25% in both the least and most deprived quintiles), extreme inequality (5% in the least deprived, and 50% in the most deprived quintiles) and the degree of inequality quoted in the paper using data from the General Household Survey (15% in the least deprived and 39% in the most deprived quintiles). We have also calculated relative risks of smoking in the most deprived, compared with the least deprived, quintile before and after the intervention as a measure of inequality. In all three scenarios, it can be seen that the quit rates achieved by the intervention in people living in the most and least deprived quintiles have a very small effect on the relative risk of smoking in the least compared with the most deprived quintile, and hence on inequality.
From our further analysis of the published data, we conclude that the authors’ claims that “services are reducing inequalities between geographical areas” are not justified and hence the title of the article is misleading. Furthermore, the conclusion that “NHS smoking cessation services are successfully attracting significant number of people from deprived areas” seems of limited validity. Only 1.13% (3799 of 336 800) of people from the most deprived quintile actually accessed services. Even if 50% of people in the most deprived quintile were smokers, this still only represents 2.26% of smokers in this quintile.
We believe that the proposition that health promotion interventions may often increase, rather than decrease, overall SEIH13 is feasible, and worthy of further consideration. Analyses such as those attempted by Lowey et al, and completed by us, are essential for confirming or refuting the validity of this hypothesis. As we have shown, simple statistics can be used to quantify and compare the degree of inequality within a population. Authors should be careful to ensure that their claims are substantiated by the data they present and be prepared to extend analysis with sensitivity models where necessary to test relevant hypotheses.
Effect of NHS smoking cessation services on the relative risk of smoking in people living in the most and least deprived quintiles using hypothetical smoking rates
Authors’ reply
Adams and White fall shy of refuting that smoking cessation services are reducing inequalities. However, using our data1 and speculative levels of smoking, they examine how smoking cessation services might have changed the relative risk of smoking between the least and most derived areas. Like Adams and White we are aware of data from the national household survey2 on prevalence of smoking according to deprivation. Furthermore, since then a smoking prevalence survey has been published for two of the primary care trusts (one relatively affluent, Bebington and West Wirral and one relatively deprived, Birkenhead and Wallasey) within our study area. Prevalence of smoking for these was measured at 13% and 25% respectively.3 Using these figures and those from the General Household Survey (15% smokers in least deprived areas and 39% in the most deprived) we have tested whether greater proportions of smokers are quitting from deprived areas. Data from our study showed that the proportions of males quitting from deprived areas are significantly higher (table 1). In our original paper we chose not to publish any such analyses as the actual prevalence of smoking across our study areas was not known. Instead, in our comments we acknowledged the urgency with which such data are needed.1
We would not dispute that currently changes in smoking prevalence resulting from smoking cessation services are relatively modest. However, this is to be expected as only a fraction of all smokers are currently accommodated by such services. Furthermore, disproportionate effects on areas of high deprivation are also reduced by a greater drop out rates of people recruited from those most deprived areas. Again this is an issue we have suggested is tackled as a matter of urgency.
In reality, smoking cessation services can never dramatically affect relative risks of smoking (between least and most deprived areas) while the number of people they see represent such small proportions of the smoking population. However, we have shown that modest investment in such services has had an impact disproportionately on more deprived populations. Consequently, greater investment in smoking cessation services (as part of a suite of interventions to reduce smoking) may even deliver the changes in relative risk sought by Adams and White.
Estimated proportions of male smokers quitting by deprivation quintile
Footnotes
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Funding: Jean Adams is supported by the BUPA/FPHM Joint Research Fellowship, 2001–4.