title: The prospective impact of food pricing on improving dietary consumption: A systematic review and meta-analysis.
abstract: BACKGROUND
  While food pricing is a promising strategy to improve diet, the prospective impact of food pricing on diet has not been systematically quantified.
  
  
  OBJECTIVE
  To quantify the prospective effect of changes in food prices on dietary consumption.
  
  
  METHODS
  We systematically searched online databases for interventional or prospective observational studies of price change and diet; we also searched for studies evaluating adiposity as a secondary outcome. Studies were excluded if price data were collected before 1990. Data were extracted independently and in duplicate. Findings were pooled using DerSimonian-Laird's random effects model. Pre-specified sources of heterogeneity were analyzed using meta-regression; and potential for publication bias, by funnel plots, Begg's and Egger's tests.
  
  
  RESULTS
  From 3,163 identified abstracts, 23 interventional studies and 7 prospective cohorts with 37 intervention arms met inclusion criteria. In pooled analyses, a 10% decrease in price (i.e., subsidy) increased consumption of healthful foods by 12% (95%CI = 10-15%; N = 22 studies/intervention arms) whereas a 10% increase price (i.e. tax) decreased consumption of unhealthful foods by 6% (95%CI = 4-8%; N = 15). By food group, subsidies increased intake of fruits and vegetables by 14% (95%CI = 11-17%; N = 9); and other healthful foods, by 16% (95%CI = 10-23%; N = 10); without significant effects on more healthful beverages (-3%; 95%CI = -16-11%; N = 3). Each 10% price increase reduced sugar-sweetened beverage intake by 7% (95%CI = 3-10%; N = 5); fast foods, by 3% (95%CI = 1-5%; N = 3); and other unhealthful foods, by 9% (95%CI = 6-12%; N = 3). Changes in price of fruits and vegetables reduced body mass index (-0.04 kg/m2 per 10% price decrease, 95%CI = -0.08-0 kg/m2; N = 4); price changes for sugar-sweetened beverages or fast foods did not significantly alter body mass index, based on 4 studies. Meta-regression identified direction of price change (tax vs. subsidy), number of intervention components, intervention duration, and study quality score as significant sources of heterogeneity (P-heterogeneity<0.05 each). Evidence for publication bias was not observed.
  
  
  CONCLUSIONS
  These prospective results, largely from interventional studies, support efficacy of subsidies to increase consumption of healthful foods; and taxation to reduce intake of unhealthful beverages and foods. Use of subsidies and combined multicomponent interventions appear most effective.
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States of America.|Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America.
authors.forename: Ashkan
authors.initials: A
authors.lastname: Afshin
authors.affiliation: Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America.
authors.forename: José L
authors.initials: JL
authors.lastname: Peñalvo
authors.affiliation: Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America.|School of Medicine, Stanford University, Stanford, CA, United States of America.
authors.forename: Liana
authors.initials: L
authors.lastname: Del Gobbo
authors.affiliation: Department of Cardiology, Boston Medical Center, Boston, MA, United States of America.
authors.forename: Jose
authors.initials: J
authors.lastname: Silva
authors.affiliation: School of Medicine, Tufts University, Boston MA, United States of America.
authors.forename: Melody
authors.initials: M
authors.lastname: Michaelson
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Martin
authors.initials: M
authors.lastname: O'Flaherty
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Simon
authors.initials: S
authors.lastname: Capewell
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.|Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.|Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.|Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.
authors.forename: Donna
authors.initials: D
authors.lastname: Spiegelman
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.|Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.
authors.forename: Goodarz
authors.initials: G
authors.lastname: Danaei
authors.affiliation: Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America.
authors.forename: Dariush
authors.initials: D
authors.lastname: Mozaffarian
mesh_terms: D050154:Adiposity; D003365:Costs and Cost Analysis; D004435:Eating; D005523:Food Supply / Q000191:economics*; D006801:Humans