Objective:To assess the effects of population tobacco control interventions on social inequalities in smoking.Data sources:Medical, nursing, psychological, social science and grey literature databases, bibliographies, hand-searches and contact with authors.Study selection:Studies were included (n = 84) if they reported the effects of any population-level tobacco control intervention on smoking behaviour or attitudes in individuals or groups with different demographic or socioeconomic characteristics.Data extraction:Data extraction and quality assessment for each study were conducted by one reviewer and checked by a second.Data synthesis:Data were synthesised using graphical (“harvest plot”) and narrative methods. No strong evidence of differential effects was found for smoking restrictions in workplaces and public places, although those in higher occupational groups may be more likely to change their attitudes or behaviour. Smoking restrictions in schools may be more effective in girls. Restrictions on sales to minors may be more effective in girls and younger children. Increasing the price of tobacco products may be more effective in reducing smoking among lower-income adults and those in manual occupations, although there was also some evidence to suggest that adults with higher levels of education may be more price-sensitive. Young people aged under 25 are also affected by price increases, with some evidence that boys and non-white young people may be more sensitive to price.Conclusions:Population-level tobacco control interventions have the potential to benefit more disadvantaged groups and thereby contribute to reducing health inequalities.

BackgroundOne attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies.MethodsWe coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality.ResultsWe plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups.ConclusionThe harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.

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