Research articleTaxation Reduces Social Disparities in Adult Smoking Prevalence
Introduction
International research has estimated that at least one third of socioeconomic disparities in mortality are due to socioeconomic differences in smoking prevalence. In the U.S., Canada, and Poland, eliminating differences that relate to smoking would reduce the social gradient in mortality among men by half.1 In the United Kingdom (UK), tobacco causes approximately two thirds of the differences in risk of death across social class in men.2 In Australia, smoking accounts for over one third of excess deaths that are attributed to low education in men.3 Reducing socioeconomic disparities in smoking behavior will lead to the amelioration of health disparities. Although tobacco-control policies and interventions have been successful in reducing the prevalence of smoking in the general population, disparities in prevalence persist.4 This study examines the role of taxation in reducing these disparities.
Many studies have shown that higher cigarette prices decrease the prevalence of smoking as well as the number of cigarettes consumed by smokers.5, 6 Accordingly, major public health organizations such as the WHO, the World Bank, and the CDC promote increases in the price of cigarettes as an effective and important tobacco-control strategy.7, 8, 9 Further, several studies10, 11, 12, 13, 14, 15, 16, 17, 18 from the U.S., UK, and Canada provide evidence that lower socioeconomic groups, women, older adults, minorities, and youth are more responsive to price. However, there are also reports19, 20, 21 that do not show an effect of price on smoking or a difference in price responsiveness across socioeconomic groups.
A shortcoming of all previously published studies in this field pertains to the use of smoking-prevalence data that are collected annually. Although price data are normally available on a monthly basis or as often as price changes in a given year, population surveys seldom provide smoking data more frequently than annually. Thus, previous analyses have used years as the unit of analysis and correlated average annual price with smoking prevalence. The use of annual data may provide inaccurate estimates of the effect of price on smoking behavior, because each instance of a price increase or stabilization within a given year may have a fast-acting impact on smoking.17
In the present research, a unique data set is used that provides monthly national smoking-prevalence data for sociodemographic groups in the period from February 1991 to December 2006 in Australia. This period saw marked variability in the frequency and extent of increases in the price of cigarettes, with very large increases in state government fees applied to wholesale costs in different states at various times between 1993 and 1995; moderate increases in federal excise and customs duties in 1992 and 1995; and reforms of all the taxes applicable to tobacco products implemented between November 1999 and February 2001, resulting in large increases in budget cigarette brands. Federal excise and customs duties are automatically increased in line with inflation in Australia, but apart from price increases resulting from indexation every 6 months, there was little real change in cigarette prices in 1991, between 1997 and 1999, or in the 70 months from 2001 to the end of 2006.22 The aim of this research was to employ monthly smoking prevalence and price data to examine how the effect of price on prevalence differed across income groups.
Section snippets
Data and Measurement
Data on smoking prevalence, income, and other sociodemographic variables came from face-to-face interviews of 515,866 individuals aged ≥18 years from January 1991 to December 2006. The data were collected by Roy Morgan Research, an Australian market research company, and extracted from their archived data originally collected for its syndicated data collection. This collection is currently known as Roy Morgan Single Source.23 Respondents were from the five largest Australian capital
Results
Of the 515,866 respondents in the analysis, 48% were men, 21% were aged 18–29 years, and 41% were aged 30–49 years. The 2001 Census of the Population in Australia reported that 51% were men, with 19.5% aged 18–29 years, and 34.1% aged 30–49 years. Approximately 18% and 58% of the sample had low and medium levels of education, respectively. Approximately 23% and 45% had low and medium incomes, respectively. Figure 1 shows the trends in the overall smoking prevalence in the study period, between
Discussion
This study examined the differential impact of cigarette prices on smoking prevalence across income groups, using monthly data from the period 1991 to 2006 in Australia. The findings revealed that real price is negatively associated with smoking prevalence and that lower-income groups are more responsive to price.
The study was unique in that it used monthly smoking-prevalence and cigarette-price data up to December 2006 and was therefore able to provide a more accurate and updated estimate of
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2018, Social Science and MedicineA qualitative analysis of low income smokers’ responses to tobacco excise tax increases
2016, International Journal of Drug PolicyCitation Excerpt :Given a 10% price increase decreases tobacco consumption by up to 5% (Chaloupka et al., 2012; Levy, Chaloupka, & Gitchell, 2004), many countries have committed to a sustained programme of tax increases. Several studies report that lower income smokers’ higher price sensitivity means they respond more strongly to excise tax increases, thus reducing overall health inequalities (Brown, Platt, & Amos, 2014; Cowie, Glover, & Gentles, 2014; Guillaumier et al., 2014; Siahpush, Spittal, & Singh, 2007b; Siahpush, Wakefield, Spittal, Durkin, & Scollo, 2009a; Warner, 2000; Wilson & Thomson, 2005a, 2005b) and producing greater net benefits (Hill, Amos, Clifford, & Platt, 2013). However, those who continue to smoke may face an increased economic burden, particularly if tobacco purchases account for a larger proportion of their disposable income or they have co-morbidities to manage (Bader et al., 2011; Farrelly, Nonnemaker, & Watson, 2012; Lawn, 2008; Martire, Mattick, Doran, & Hall, 2011; Voigt, 2010; Warner & Mendez, 2010).