Kendrin R Sonneville1, Michael W Long2, Zachary J Ward3, Stephen C Resch3, Y Claire Wang4, Jennifer L Pomeranz5, Marj L Moodie6, Rob Carter6, Gary Sacks7, Boyd A Swinburn7, Steven L Gortmaker2. 1. Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan. Electronic address: kendrins@umich.edu. 2. Department of Social and Behavioral Sciences, Harvard School of Public Health, Harvard University, Boston, Massachusetts. 3. Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts. 4. Department of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, New York. 5. Department of Public Health, Center for Obesity Research and Education, Temple University, Philadelphia, Pennsylvania. 6. Deakin Health Economics, Deakin University, Melbourne, Victoria, Australia. 7. WHO Collaborating Centre for Obesity Prevention, Deakin University, Melbourne, Victoria, Australia.
Abstract
INTRODUCTION: Food and beverage TV advertising contributes to childhood obesity. The current tax treatment of advertising as an ordinary business expense in the U.S. subsidizes marketing of nutritionally poor foods and beverages to children. This study models the effect of a national intervention that eliminates the tax subsidy of advertising nutritionally poor foods and beverages on TV to children aged 2-19 years. METHODS: We adapted and modified the Assessing Cost Effectiveness framework and methods to create the Childhood Obesity Intervention Cost Effectiveness Study model to simulate the impact of the intervention over the 2015-2025 period for the U.S. population, including short-term effects on BMI and 10-year healthcare expenditures. We simulated uncertainty intervals (UIs) using probabilistic sensitivity analysis and discounted outcomes at 3% annually. Data were analyzed in 2014. RESULTS: We estimated the intervention would reduce an aggregate 2.13 million (95% UI=0.83 million, 3.52 million) BMI units in the population and would cost $1.16 per BMI unit reduced (95% UI=$0.51, $2.63). From 2015 to 2025, the intervention would result in $352 million (95% UI=$138 million, $581 million) in healthcare cost savings and gain 4,538 (95% UI=1,752, 7,489) quality-adjusted life-years. CONCLUSIONS: Eliminating the tax subsidy of TV advertising costs for nutritionally poor foods and beverages advertised to children and adolescents would likely be a cost-saving strategy to reduce childhood obesity and related healthcare expenditures.
INTRODUCTION: Food and beverage TV advertising contributes to childhood obesity. The current tax treatment of advertising as an ordinary business expense in the U.S. subsidizes marketing of nutritionally poor foods and beverages to children. This study models the effect of a national intervention that eliminates the tax subsidy of advertising nutritionally poor foods and beverages on TV to children aged 2-19 years. METHODS: We adapted and modified the Assessing Cost Effectiveness framework and methods to create the Childhood Obesity Intervention Cost Effectiveness Study model to simulate the impact of the intervention over the 2015-2025 period for the U.S. population, including short-term effects on BMI and 10-year healthcare expenditures. We simulated uncertainty intervals (UIs) using probabilistic sensitivity analysis and discounted outcomes at 3% annually. Data were analyzed in 2014. RESULTS: We estimated the intervention would reduce an aggregate 2.13 million (95% UI=0.83 million, 3.52 million) BMI units in the population and would cost $1.16 per BMI unit reduced (95% UI=$0.51, $2.63). From 2015 to 2025, the intervention would result in $352 million (95% UI=$138 million, $581 million) in healthcare cost savings and gain 4,538 (95% UI=1,752, 7,489) quality-adjusted life-years. CONCLUSIONS: Eliminating the tax subsidy of TV advertising costs for nutritionally poor foods and beverages advertised to children and adolescents would likely be a cost-saving strategy to reduce childhood obesity and related healthcare expenditures.
Authors: Juan Mielgo-Ayuso; Raquel Aparicio-Ugarriza; Adrian Castillo; Emma Ruiz; Jose M Avila; Javier Aranceta-Bartrina; Angel Gil; Rosa M Ortega; Lluis Serra-Majem; Gregorio Varela-Moreiras; Marcela González-Gross Journal: BMC Public Health Date: 2017-01-19 Impact factor: 3.295
Authors: Oliver T Mytton; Emma Boyland; Jean Adams; Brendan Collins; Martin O'Connell; Simon J Russell; Kate Smith; Rebekah Stroud; Russell M Viner; Linda J Cobiac Journal: PLoS Med Date: 2020-10-13 Impact factor: 11.069