Taxes and Subsidies for Improving Diet and Population Health in Australia: A Cost-Effectiveness Modelling Study
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Mendeley | Further Information

{"title"=>"Taxes and Subsidies for Improving Diet and Population Health in Australia: A Cost-Effectiveness Modelling Study", "type"=>"journal", "authors"=>[{"first_name"=>"Linda J.", "last_name"=>"Cobiac", "scopus_author_id"=>"35108698100"}, {"first_name"=>"King", "last_name"=>"Tam", "scopus_author_id"=>"57191093851"}, {"first_name"=>"Lennert", "last_name"=>"Veerman", "scopus_author_id"=>"8222114200"}, {"first_name"=>"Tony", "last_name"=>"Blakely", "scopus_author_id"=>"7006795650"}], "year"=>2017, "source"=>"PLoS Medicine", "identifiers"=>{"scopus"=>"2-s2.0-85014457986", "sgr"=>"85014457986", "issn"=>"15491676", "doi"=>"10.1371/journal.pmed.1002232", "pmid"=>"28196089", "isbn"=>"1111111111", "pui"=>"614693425"}, "id"=>"f5d2be5f-b65e-3e2f-ba37-49260f3b140a", "abstract"=>"BACKGROUND An increasing number of countries are implementing taxes on unhealthy foods and drinks to address the growing burden of dietary-related disease, but the cost-effectiveness of combining taxes on unhealthy foods and subsidies on healthy foods is not well understood. METHODS AND FINDINGS Using a population model of dietary-related diseases and health care costs and food price elasticities, we simulated the effect of taxes on saturated fat, salt, sugar, and sugar-sweetened beverages and a subsidy on fruits and vegetables, over the lifetime of the Australian population. The sizes of the taxes and subsidy were set such that, when combined as a package, there would be a negligible effect on average weekly expenditure on food (<1% change). We evaluated the cost-effectiveness of the interventions individually, then determined the optimal combination based on maximising net monetary benefit at a threshold of AU$50,000 per disability-adjusted life year (DALY). The simulations suggested that the combination of taxes and subsidy might avert as many as 470,000 DALYs (95% uncertainty interval [UI]: 420,000 to 510,000) in the Australian population of 22 million, with a net cost-saving of AU$3.4 billion (95% UI: AU$2.4 billion to AU$4.6 billion; US$2.3 billion) to the health sector. Of the taxes evaluated, the sugar tax produced the biggest estimates of health gain (270,000 [95% UI: 250,000 to 290,000] DALYs averted), followed by the salt tax (130,000 [95% UI: 120,000 to 140,000] DALYs), the saturated fat tax (97,000 [95% UI: 77,000 to 120,000] DALYs), and the sugar-sweetened beverage tax (12,000 [95% UI: 2,100 to 21,000] DALYs). The fruit and vegetable subsidy (-13,000 [95% UI: -44,000 to 18,000] DALYs) was a cost-effective addition to the package of taxes. However, it did not necessarily lead to a net health benefit for the population when modelled as an intervention on its own, because of the possible adverse cross-price elasticity effects on consumption of other foods (e.g., foods high in saturated fat and salt). The study suggests that taxes and subsidies on foods and beverages can potentially be combined to achieve substantial improvements in population health and cost-savings to the health sector. However, the magnitude of health benefits is sensitive to measures of price elasticity, and further work is needed to incorporate potential benefits or harms associated with changes in other foods and nutrients that are not currently modelled, such as red and processed meats and fibre. CONCLUSIONS With potentially large health benefits for the Australian population and large benefits in reducing health sector spending on the treatment of non-communicable diseases, the formulation of a tax and subsidy package should be given a more prominent role in Australia's public health nutrition strategy.", "link"=>"http://www.mendeley.com/research/taxes-subsidies-improving-diet-population-health-australia-costeffectiveness-modelling-study", "reader_count"=>79, "reader_count_by_academic_status"=>{"Unspecified"=>8, "Professor > Associate Professor"=>1, "Researcher"=>8, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>4, "Student > Master"=>20, "Other"=>6, "Student > Bachelor"=>16, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>8, "Professor > Associate Professor"=>1, "Researcher"=>8, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>4, "Student > Master"=>20, "Other"=>6, "Student > Bachelor"=>16, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>14, "Agricultural and Biological Sciences"=>6, "Philosophy"=>1, "Business, Management and Accounting"=>3, "Chemistry"=>2, "Economics, Econometrics and Finance"=>6, "Environmental Science"=>2, "Nursing and Health Professions"=>8, "Biochemistry, Genetics and Molecular Biology"=>2, "Medicine and Dentistry"=>23, "Neuroscience"=>1, "Sports and Recreations"=>1, "Physics and Astronomy"=>1, "Psychology"=>2, "Social Sciences"=>6, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>23}, "Social Sciences"=>{"Social Sciences"=>6}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>2}, "Unspecified"=>{"Unspecified"=>14}, "Environmental Science"=>{"Environmental Science"=>2}, "Chemistry"=>{"Chemistry"=>2}, "Neuroscience"=>{"Neuroscience"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>6}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>8}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"New Zealand"=>1, "Australia"=>1}, "group_count"=>5}

Scopus | Further Information

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