The effect of fiscal policy on diet, obesity and chronic disease: a systematic review
Anne Marie Thow a, Stephen Jan b, Stephen Leeder c & Boyd Swinburn d
a. Menzies Centre for Health Policy, University of Sydney, Victor Coppleson Building (D02), Sydney, NSW, 2006, Australia.
b. The George Institute for International Health, Sydney, Australia.
c. Menzies Centre for Health Policy, University of Sydney, Sydney, Australia.
d. Deakin University, Melbourne, Australia.
Correspondence to Anne Marie Thow (e-mail: email@example.com).
(Submitted: 13 August 2009 – Revised version received: 03 January 2010 – Accepted: 05 January 2010 – Published online: 22 February 2010.)
Bulletin of the World Health Organization 2010;88:609-614. doi: 10.2471/BLT.09.070987
The World Health Organization (WHO) has recommended the use of fiscal policy to influence food prices “in ways that encourage healthy eating”.1,2 Although this is consistent with growing worldwide interest in the effect of fiscal policy on diet,3–5 evidence supporting the use of taxes is weak. This review considers international evidence on the impact of food taxes and subsidies.
The current obesity epidemic reflects an increasingly “obesogenic” food environment and long-term changes in activity levels and energy expenditure.6 Currently, financial incentives favour the consumption of highly processed, energy-dense foods since it is consistently cheaper, in terms of energy content for a given price, than less energy-dense and often more nutrient-rich foods.7,8 Taxing less healthy foods could create a financial incentive for consumers to avoid them. Studies on the effect of manipulating food prices show that both individual consumers 9,10 and population groups11–14 do respond as predicted.
The poor health outcomes associated with the consumption of energy-dense food8,15 may justify levying taxes on such food to pay for health care and to decrease consumption, a measure that has proved effective for tobacco control.16 However, taxation structures that worked for tobacco (i.e. an excise tax on a single provenly harmful substance) may not be readily transferable to food, which is essential for life and involves far more complex choices.
Very little evidence about the use of food taxes as a public health strategy is available. Cash & Lacanilao17 examined pricing and taxation studies on food and concluded that more evidence is needed on the efficacy of taxation as a health intervention to support taking action. In a more recent review, Powell and Chaloupka18 predicted that a small change in food prices would have little effect on body weight in the United States of America (USA), whereas a “non-trivial” change in food prices would affect body weight. They suggested that a combination of taxes and subsidies would have the greatest effect on body weight.
This review extends previous work on the effects of fiscal policy on food consumption patterns, obesity and chronic disease by updating evidence from the peer-reviewed literature and by incorporating carefully selected evidence from the non-peer-reviewed or grey literature, including modelling studies, all of which act as sources of evidence for policy-makers.
The Medline, ProQuest and Business Source Premier academic databases and Google Scholar were searched using the term “tax” or “subsidy” with the terms “food”, “soft drink”, “obesity”, “diet”, “nutrition”, “consumption” and “fat”, or their equivalent Medical Subject Heading terms, as appropriate. The first 150 articles identified from each search using Google Scholar were examined. Only English-language literature was included.
The criteria for including a study in this systematic review were that it: (i) was either an empirical or modelling study, (ii) examined a tax or subsidy on a specific food product (i.e. general agricultural subsidies or food taxes were excluded), and (iii) assessed the effect of the tax on a health outcome such as food consumption, body weight or disease. Empirical studies were defined as those that assessed the effect of an actual tax, while modelling studies were those that predicted rather than measured outcomes.
Articles were initially selected on the basis of their titles. Those whose abstracts were deemed irrelevant were then excluded, leaving 24 articles from Medline, 13 from ProQuest and 2 from Business Source Premier. In addition, 55 papers from Google Scholar were judged relevant. Once duplicate references were removed, 62 remained. Thereafter, 41 papers were excluded following a full text review, leaving 21. The reference lists from three recent reviews17–19 were also examined, yielding two further publications, and the details of one recently published study were obtained directly from a co-author.20 Finally, 24 studies were included in the current review (Fig. 1).
Fig. 1. Selection of manuscripts for systematic review of studies on the effects of fiscal policy on food consumption
For the purposes of the analysis, studies were classified according to: (i) the outcome assessed, such as the effect on food consumption or expenditure, body weight or health, (ii) whether they were modelling or empirical studies, and (iii) whether or not they were peer-reviewed.
Of the 24 studies reviewed, 13 were from the peer-reviewed literature, including one published in an edited book, and 11 were published online, as summarized in Table 1 (available at: http://www.who.int/bulletin/volumes/88/8/09-070987). All were published between 2000 and 2009, and mostly since 2006. All studies but one were set in high-income countries, and more than half were in the USA.
Table 1. Studies on the effects of fiscal policy on food consumption included in systematic literature review
The majority of studies used predictive models to assess the effect of a proposed tax on consumption. Only 6 studies used observational data and 4 of these used data at the population rather than the individual level to look for associations between taxes and body weight.
Nine studies assessed the effect of taxes on food consumption or expenditure alone, five on consumption and body weight, four on consumption and disease, and six on body weight only. Studies on soft drink taxes were the most common: there were 10 such studies, 2 of which also included “snack” taxes. Thereafter, 7 studies examined food taxation based on nutrient content, most commonly fat. Three studies assessed fruit and vegetable subsidies, and another assessed three taxes on a variety of “unhealthy” foods.
Effect on consumption
The four peer-reviewed studies on food consumption all found that a subsidy, tax or change to a tax altered consumption in the expected direction. In an empirical study in Ireland, Bahl et al.21 found that a 20% reduction in a soft drink tax resulted in a 6.8% increase in average soft drink consumption. However, had all of the tax reduction been passed on, consumption would actually have risen by 15%.
Three studies modelled the effect of proposed taxation strategies on the whole diet. Smed et al.24 examined seven scenarios for taxing unhealthy and subsidizing healthy foods and nutrients in Denmark. Each involved the equivalent of halving value added tax (VAT) on fruit and vegetables. They concluded that subsidizing specific nutrients was more effective than subsidizing food groups. Their best revenue-neutral scenario decreased average consumption of sugar by 6.5%, fat by 2.5% and saturated fat by 3.6%, and increased consumption of fibre by 6.5%.
In a similar study, Jensen & Smed22 found that younger consumers and lower-income groups changed their consumption most in response to taxes. Their best taxation scenario reduced average sugar and saturated fat consumption by 16% and 8%, respectively, and increased average fibre consumption by 15%. Santarossa & Mainland23 modelled the level of tax required to reduce average energy and fat consumption to the recommended level in Scotland: reductions of 17.5% and 20%, respectively. The tax would have to increase the price of meat by 1%, dairy products by 4%, eggs by 11%, and fats and oils by 24%.
In one study from the grey literature, Tefft37 found that an actual increase of 10% in soft drink taxes in one state in the USA decreased average expenditure by 0.7%. However, the study monitored aggregate expenditure only and consumers may have reduced expenditure by buying cheaper drinks rather than by reducing the volume they consumed.
In contrast, Gabe34 modelled a proposed 10% soft drink tax in the USA using sales data and predicted that it would reduce sales by 4.8%. In addition, Gustavsen35 predicted that increasing soft drink prices in Norway by 27%, by doubling production taxes and VAT, would reduce average consumption by 44% in heavy soft drink consumers and by 17% in light consumers. In Sweden, Nordström & Thunström36 predicted that a 50% subsidy for healthy grain products bearing the healthy food certification keyhole symbol of the Swedish Food Administration, as judged by fat, sugar, fibre and calorie content, would be required to increase average fibre intake to the recommended level (i.e. by 38%). They proposed a 114% tax on bakery and ready-to-eat products, to be used to fund the subsidy and also to prevent unwanted increases in fat, salt and sugar consumption associated with the subsidy alone. A smaller subsidy on fruit and vegetables for people with low incomes modelled by Dong & Lin33 predicted an increase in average consumption of around 2–5%.
Effect on consumption and body weight
Two peer-reviewed studies modelled the effect of taxes on consumption and body weight. Chouinard et al.25 predicted that an extremely high tax on dairy fat would be needed to reduce average fat consumption and body weight in the USA because a 50% tax lowered fat intake from dairy products by only 3%, approximately 2–3 g/day, and thus had no effect on body weight.
Kuchler et al.27 predicted that a 20% tax on salty snack foods in the USA would reduce consumption by only 115–170 g per person per year, equivalent to an average reduction in energy intake of approximately 830 calories, with no effect on body weight. However, in an earlier, unpublished study, Kuchler et al.26 showed that, if price elasticity (i.e. the change in consumption in response to a given change in price) was greater than assumed in their later published study (i.e. −0.7 rather than −0.45), then a 30% tax might reduce consumption by nearly 1.4 kg per person per year, or 7000 calories on average, with a corresponding drop in average body weight of 0.9 kg annually.
One study in the grey literature by Allais et al.38 modelled how a 10% tax on cheese and butter products, sugar and fat products and ready-made meals in France would affect diet as a whole. They predicted reductions in average total energy intake of 3.5%, in saturated fat intake of 4.5% and in average weight of 1.3 kg/person per year. They also predicted the unintended side effect that sodium, vitamin B and good fat intake would decrease.
In the USA, Fantuzzi39 modelled the effects of both a 20% tax and a tax of US$ 0.10 per calorie on soft drinks and predicted that they would not affect consumption or body weight. This study was limited, however, by the fact that a tax of US$ 0.10 per calorie is equivalent to a tax of US$ 9 on a standard can containing 90 calories. Farra et al.40 modelled the impact of a 10% excise tax on soft drinks in the USA and predicted that per capita consumption would be reduced by 23 litres per year, equivalent to a 1.4 kg decrease in body weight.
Effect on food consumption and health
Three studies investigated effects on cardiovascular disease. Marshall modelled extending the VAT at 17.5% in the United Kingdom of Great Britain and Northern Ireland to food products that were the main sources of saturated fat.29 He calculated that saturated fat consumption would decrease sufficiently to reduce deaths from ischaemic heart disease by 1.8–2.6%, or 1800–2500 deaths per year in the country.
Mytton et al.30 examined the effect of a similar tax change but considered the whole diet. Extending VAT to products high in saturated fat increased the number of deaths from cardiovascular disease because of a predicted compensatory increase in the consumption of products containing higher levels of salt. In contrast, extending VAT to unhealthy products, as identified by a nutrient scoring system, reduced cardiovascular disease deaths by around 1.2% per annum. The best possible outcome predicted was a 1.7% reduction. A similar study by Nnoaham et al.,20which included an analysis of differential population effects, predicted that the most effective strategy was taxation of less healthy foods combined with subsidies for fruit and vegetables.
Cash et al.28 modelled a fruit and vegetable subsidy in the USA that would lead to a lasting price reduction of 1%. They predicted that 6733 cases of coronary heart disease and 2946 cases of ischaemic stroke would be prevented in the country at an average cost of US$ 1.29 million per life saved.
Effect on body weight
Asfaw31 assessed the direct effects of taxes and subsidies on body weight using historical data on price and consumption changes. The findings indicated that government subsidies for bread and sugar may have contributed to an obesity epidemic in Egypt and that reducing subsidies to create a 1% increase in bread and sugar prices per 100 calories would reduce the average body mass index (BMI) of mothers in the country by 0.12% and 0.11%, respectively.
In an empirical analysis of the relationship between obesity prevalence and state soft drink or junk food taxes in the USA, Kim & Kawachi15 found no association. However, states with no taxes and those that repealed taxes had higher relative increases in obesity prevalence than those with taxes.
Schroeter et al.32 found that a 10% tax on food eaten away from home in the USA would slightly increase average body weight by disproportionately increasing food consumption at home, whereas a 10% tax on soft drinks would decrease average body weight by around 0.1%, or 0.09 kg/capita per day. A 10% subsidy for fruit and vegetables would increase average body weight by around 0.2% per day and a 10% subsidy for diet soft drinks would decrease it by 0.07% per day.
Fletcher et al.41 analysed the relationship between soft drink taxes in states in the USA, which averaged 3%, and population BMI between 1990 and 2006 and found that even relatively large tax increases had little effect. Similarly, Oaks43 found no relationship between obesity prevalence and a snack and soft drink tax of 5.5% in Maine, USA, on comparing the obesity rate over 15 years with that in New Hampshire, a state with no tax.
Gelbach et al.42 used data on the effect of food price changes on obesity prevalence between 1982 and 1996 in the USA to model the impact of a 100% tax on “unhealthy” foods. He predicted that a 100% tax would decrease the average BMI by approximately 1% and the incidence of overweight and obesity by 2% and 1%, respectively. However, the study did not include sweets among “unhealthy” foods because pricing data were not available.
Quality of the evidence
Detailed comments on the quality of the studies, which varied widely, are listed in Table 2 (available at: http://www.who.int/bulletin/volumes/88/8/09-070987). Generally, empirical studies should provide more robust results than predictive studies, which involve assumptions about consumer responses to price changes. For example, Cash & Lacanilao17 cautioned against using price elasticity estimates to simulate substantial price changes in modelling studies, as values have to be extrapolated well outside observed data ranges. However, empirical studies that used regression analysis to assess the link between taxes and obesity were also methodologically weak because consumption of the taxed foods was not measured, making it difficult to determine whether taxes caused the observed weight changes.
Table 2. Quality of the evidence in studies on the effects of fiscal policy on food consumption included in systematic literature review
There were also inconsistencies in measures of exposure and outcomes between modelling studies. Several studies examined consumption of the taxed food only, while others considered the whole diet. For example, Marshall’s study29 focused solely on the effect of a tax on saturated fat consumption and assumed that decreased fat consumption would lead to a decrease in heart disease, while Mytton et al.’s revision of the study predicted an increase in heart disease due to the increased salt consumption that inadvertently resulted from the tax on products high in saturated fat. Also, studies expressed weight change differently. Some reported weight change per day or year as if any change would continue for many years.27,32,40 This is clearly not possible physiologically. It could be corrected by assessing the change from one steady-state to another that would occur in response to a change in energy intake.44,45
This review was broader in scope than previous reviews in that the majority of studies came from the grey literature or were modelling studies.17,18 The studies showed that taxes and subsidies on food have the potential to influence consumption considerably and improve health, particularly when they are large.18 Santarossa & Mainland23 and Gustavsen35 proposed taxes that raised the price of unhealthy foods by about 25%, Nordström & Thunström’s healthy grain subsidy was 50%,36 and Marshall29 and Mytton et al.30 both considered a VAT rate of 17.5%. In contrast, Chouinard et al.25 and Kuchler et al.27 found that taxes of 50% and 20%, respectively, had little or no effect on consumption or body weight. However, Chouinard et al. modelled a tax on only fat from dairy products, which form a core food group in the USA and may be less price elastic than fat from other food groups. Kuchler et al. emphasized that the price elasticity estimates used in modelling substantially changed consumption and body weight outcomes.26
Taxes may also reinforce efforts to educate consumers. Being aware that a product has been taxed because it is unhealthy may discourage purchases. Cash & Lacanilao46 observed this effect when warning labels were placed on products that were taxed because of their high fat content.
One argument against fat taxes is their potential regressivity: they impose a larger burden on the poor than the rich.47 Farra et al.40 found that a soft drink tax would impose a disproportionate burden on low-income families who did not reduce consumption, and Nnoaham et al.20 found that taxes on unhealthy food had a regressive effect that was not counterbalanced by greater health gains, although they may have underestimated gains in poor people. In addition, Leicester & Windmeijer48 estimated that the rich would spend less than 0.1% of their income on a fat tax in the United Kingdom compared to 0.7% for the poor. However, Smed et al.24 found that food taxes were only slightly regressive and that lower-income households reduced their consumption proportionately more than wealthier households, as has been observed with tobacco taxes.49 Combining food taxes with subsidies could help alleviate potential regressivity by enabling consumers to switch to more healthy products without incurring additional costs.
This review highlights the inadequate evidence available for informing policy-making. In particular, the review’s findings are limited by the high proportion of modelling studies, which are based on assumptions and subject to data limitations. Moreover, many modelling studies analysed only target food consumption and overlooked shifts in consumption within or across food categories. No experimental studies were available, which probably reflects the difficulty of designing such studies of interventions at a population level, and the empirical studies included had limited sensitivity. Wide variations in data sources and analytical methods also made it difficult to compare the effectiveness of the taxes assessed. Other limitations are that only English-language studies were included and that the majority of the evidence came from high-income countries.
Finally, the administrative aspects of policy implementation, such as selecting a taxation mechanism, will be important for ensuring that taxes are acceptable. The administrative costs involved and the use of revenue either as a source of funds for health programmes or as an alternative income stream were not considered in any of the studies in this review, although in several the estimated revenue gained or lost with a tax or subsidy was reported. These factors may be critical for ensuring the political acceptability of a tax.
This review indicates that food taxes and subsidies can influence consumption in high-income countries and that imposing substantial taxes on fattening foods may improve health outcomes such as body weight and chronic disease risk. The findings support current recommendations that taxes and subsidies should be included as part of a comprehensive strategy to prevent obesity.
Further research is recommended in four areas. First, experimental studies are needed to document actual responses of both prices and consumers to changes in food taxation. These will predominantly involve the evaluation of natural experiments. Second, future modelling studies should examine changes in the entire diet resulting from price changes rather than in single food items to take account of shifts in food consumption within or across food categories. These studies will require the standardization of models for converting energy imbalances to weight changes, thereby avoiding simple, arithmetic equations that imply that weight changes indefinitely. Third, there is a need for research into consumer responses to food taxes in developing countries where differential population effects may be greater. Finally, implementation and administrative costs need to be examined as they represent potential barriers to the feasibility of these interventions.
- World Health Organization. Global strategy on diet, physical activity and health. Geneva: WHO; 2004.
- World Health Organization. 2008–2013 action plan for the global strategy for the prevention and control of noncommunicable diseases. Geneva: WHO; 2008.
- Chopra M, Darnton-Hill I. Tobacco and obesity epidemics: not so different after all? BMJ 2004; 328: 1558-60 doi: 10.1136/bmj.328.7455.1558 pmid: 15217877.
- World Bank. Repositioning nutrition as central to development: a strategy for large-scale action. Washington: The World Bank; 2006.
- Nestle M. The ironic politics of obesity. Science 2003; 299: 781- doi: 10.1126/science.299.5608.781 pmid: 12574583.
- Swinburn B, Egger G. The runaway weight gain train: too many accelerators, not enough brakes. BMJ 2004; 329: 736-9 doi: 10.1136/bmj.329.7468.736 pmid: 15388619.
- Drewnowski A. Obesity and the food environment: dietary energy density and diet costs. Am J Prev Med 2004; 27: 154-62 doi: 10.1016/j.amepre.2004.06.011 pmid: 15450626.
- Finkelstein EA, Ruhm CJ, Kosa KM. Economic causes and consequences of obesity. Annu Rev Public Health 2005; 26: 239-57 doi: 10.1146/annurev.publhealth.26.021304.144628 pmid: 15760288.
- French SA. Public health strategies for dietary change: schools and workplaces. J Nutr 2005; 135: 910-2 pmid: 15795458.
- Michels KB, Bloom BR, Riccardi P, Rosner BA, Willett WC. A study of the importance of education and cost incentives on individual food choices at the Harvard School of Public Health cafeteria. J Am Coll Nutr 2008; 27: 6-11 pmid: 18460476.
- Beydoun MA, Powell LM, Wang Y. The association of fast food, fruit and vegetable prices with dietary intakes among US adults: is there modification by family income? Soc Sci Med 2008; 66: 2218-29 doi: 10.1016/j.socscimed.2008.01.018 pmid: 18313824.
- Boizot-Szantaï C, Etilé F. The food prices/body mass index relationship: theory and evidence from a sample of French adults. Paris: Institut National de la Recherche Agronomique; 2005.
- Bourke RM. Marketed fresh food: a successful part of the Papua New Guinea economy. Dev Bull (Canberra) 2005; 67: 22-4.
- Guo X, Popkin BM, Mroz TA, Zhai F. Food price policy can favorably alter macronutrient intake in China. J Nutr 1999; 129: 994-1001 pmid: 10222391.
- Kim D, Kawachi I. Food taxation and pricing strategies to “thin out” the obesity epidemic. Am J Prev Med 2006; 30: 430-7 doi: 10.1016/j.amepre.2005.12.007 pmid: 16627131.
- Laxminarayan R, Mills AJ, Breman JG, Measham AR, Alleyne G, Claeson M, et al., et al. Advancement of global health: key messages from the Disease Control Priorities Project. Lancet 2006; 367: 1193-208 doi: 10.1016/S0140-6736(06)68440-7 pmid: 16616562.
- Cash SB, Lacanilao RD. Taxing food to improve health: economic evidence and arguments. Agric Resource Econ Rev 2007; 36: 174-82.
- Powell LM, Chaloupka FJ. Food prices and obesity: evidence and policy implications for taxes and subsidies. Milbank Q 2009; 87: 229-57 doi: 10.1111/j.1468-0009.2009.00554.x pmid: 19298422.
- Brownell KD, Frieden TR. Ounces of prevention–the public policy case for taxes on sugared beverages. N Engl J Med 2009; 360: 1805-8 doi: 10.1056/NEJMp0902392 pmid: 19357400.
- Nnoaham KE, Sacks G, Rayner M, Mytton O, Gray A. Modelling income group differences in the health and economic impacts of targeted food taxes and subsidies. Int J Epidemiol 2009; 38: 1324-33 doi: 10.1093/ije/dyp214 pmid: 19483200.
- Bahl R, Bird R, Walker MB. The uneasy case against discriminatory excise taxation: soft drink taxes in Ireland. Public Finance Rev 2003; 31: 510-33 doi: 10.1177/1091142103253753.
- Jensen JD, Smed S. Cost-effective design of economic instruments in nutrition policy. Int J Behav Nutr Phys Act 2007; 4: 10- doi: 10.1186/1479-5868-4-10 pmid: 17408494.
- Santarossa JM, Mainland DD. Employing an environmental taxation mechanism to reduce fat intake. In: Chern WS, Rickertson K, eds. Health, nutrition and food demand. Oxford: CABI Publishing; 2003. pp. 223-45.
- Smed S, Jensen JD, Denver S. Socio-economic characteristics and the effect of taxation as a health policy instrument. Food Policy 2007; 32: 624-39 doi: 10.1016/j.foodpol.2007.03.002.
- Chouinard HH, Davis DE, LaFrance JT, Perloff JM. Fat taxes: big money for small change. Forum Health Econ Policy 2007; 10: 2-.
- Kuchler F, Tegene A, Harris JM. Taxing snack foods: what to expect for diet and tax revenues. Agric Info Bull 2004; 8: 1-11.
- Kuchler F, Tegene A, Harris JM. Taxing snack foods: manipulating diet quality or financing information programs. Rev Agric Econ 2005; 27: 4-20 doi: 10.1111/j.1467-9353.2004.00204.x.
- Cash SB, Sunding DL, Zilberman D. Fat taxes and thin subsidies: prices, diet, and health outcomes. Acta Agric Scand, Section C - Econ 2005; 2: 167-74.
- Marshall T. Exploring a fiscal food policy: the case of diet and ischaemic heart disease. BMJ 2000; 320: 301-5 doi: 10.1136/bmj.320.7230.301 pmid: 10650031.
- Mytton O, Gray A, Rayner M, Rutter H. Could targeted food taxes improve health? J Epidemiol Community Health 2007; 61: 689-94 doi: 10.1136/jech.2006.047746 pmid: 17630367.
- Asfaw A. Do government food price policies affect the prevalence of obesity? Empirical evidence from Egypt. World Dev 2007; 35: 687-701 doi: 10.1016/j.worlddev.2006.05.005.
- Schroeter C, Lusk J, Tyner W. Determining the impact of food price and income changes on body weight. J Health Econ 2008; 27: 45-68 doi: 10.1016/j.jhealeco.2007.04.001 pmid: 17521754.
- Dong D, Lin B. Fruit and vegetable consumption by low-income Americans: would a price reduction make a difference? Washington: United States Department of Agriculture Economic Research Service; 2009.
- Gabe T. Fiscal and economic impacts of beverage excise taxes imposed by Maine Public Law 629. Orono: University of Maine, School of Economics; 2008.
- Gustavsen G. Public policies and the demand for carbonated soft drinks: a censored quantile regression approach. In: The future of rural Europe in the global agric-food system: Proceedings of the: XIth Congress of the EAAE (European Association of Agricultural Economists); Copenhagen, 24–27 August 2005.
- Nordström J, Thunström L. The impact of tax reforms designed to encourage a healthier grain consumption. Umeå: Umeå University; 2007.
- Tefft N. The effects of a soft drink tax on household expenditures [draft]. Cited with permission. Bates University; 2008. Available from: http://abacus.bates.edu/~ntefft/research/soft_drink_tax.pdf [accessed 3 February 2009].
- Allais O, Bertail P, Nichèle V. The effects of a ”fat tax” on the nutrient intake of French households. Presented at the: European Association of Agricultural Economists' 2008 International Congress, Ghent, 26–29 August 2008. Available from: http://ideas.repec.org/p/ags/eaae08/43967.html [accessed 17 February 2010].
- Fantuzzi K. Carbonated soft drink consumption: implications for obesity policy. Storrs: University of Connecticut; 2008.
- Farra J, Jones J, Mishra A. An analysis of policy options for reducing obesity in Georgia. 2005 (Unpublished report, accessed initially through Google Scholar).
- Fletcher JM, Frisvold D, Tefft N. Can soft drink taxes reduce population weight? Contemp Econ Pol 2009;28:23-35. I
- Gelbach JB, Klick J, Stratmann T. Cheap donuts and expensive broccoli: the effect of relative prices on obesity (Research Paper No. 261). Tallahassee: Florida State University College of Law; 2007. Available from: http://ssrn.com/abstract=976484 [accessed 3 February 2009].
- Oaks B. An evaluation of the snack tax on the obesity rate of Maine. San Marcos: Texas State University, Department of Political Science; 2005.
- Swinburn BA, Sacks G, Lo SK, Westerterp KR, Rush EC, Rosenbaum M, et al., et al. Estimating the changes in energy flux that characterize the rise in obesity prevalence. Am J Clin Nutr 2009; 89: 1723-8 doi: 10.3945/ajcn.2008.27061 pmid: 19369382.
- Swinburn BA, Jolley D, Kremer PJ, Salbe AD, Ravussin E. Estimating the effects of energy imbalance on changes in body weight in children. Am J Clin Nutr 2006; 83: 859-63 pmid: 16600939.
- Cash SB, Lacanilao R. An experimental investigation of the impact of fat taxes: price effects, food stigma, and information effects on economic instruments to improve dietary health. Edmonton: University of Alberta, Department of Rural Economy; 2008.
- Caraher M, Cowburn G. Taxing food: implications for public health nutrition. Public Health Nutr 2005; 8: 1242-9 doi: 10.1079/PHN2005755 pmid: 16372919.
- Leicester A, Windmeijer F. The “fat tax”: economic incentives to reduce obesity. London: Institute for Fiscal Studies; 2004.
- Remler DK. Poor smokers, poor quitters, and cigarette tax regressivity. Am J Public Health 2004; 94: 225-9 doi: 10.2105/AJPH.94.2.225 pmid: 14759931.