Impact of sugar-sweetened beverage taxes on purchases and dietary intake: Systematic review and meta-analysis

Obes Rev. 2019 Sep;20(9):1187-1204. doi: 10.1111/obr.12868. Epub 2019 Jun 19.


The aim was to conduct a systematic review of real-world sugar-sweetened beverage (SSB) tax evaluations and examine the overall impact on beverage purchases and dietary intake by meta-analysis. Medline, EconLit, Google Scholar, and Scopus databases were searched up to June 2018. SSB tax evaluations from any formal jurisdiction from cities to national governments were eligible if there was a comparison between pre-post tax (n = 11) or taxed and untaxed jurisdiction(s) (n = 6). The consumption outcome comprised sales, purchasing, and intake (reported by volume, energy, or frequency). Taxed and untaxed beverage consumption outcomes were examined separately by meta-analysis with adjustment for the size of each tax. The study was registered at PROSPERO (CRD42018100620). The equivalent of a 10% SSB tax was associated with an average decline in beverage purchases and dietary intake of 10.0% (95% CI: -5.0% to -14.7%, n = 17 studies, 6 jurisdictions) with considerable heterogeneity between results (I2 = 97%).The equivalent of a 10% SSB tax was also associated with a nonsignificant 1.9% increase in total untaxed beverage consumption (eg, water) (95% CI: -2.1% to 6.1%, n = 6 studies, 4 jurisdictions). Based on real-world evaluations, SSB taxes introduced in jurisdictions around the world appear to have been effective in reducing SSB purchases and dietary intake.

Keywords: evaluation; excise; meta-analysis; natural experiment; soft drinks; tax.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Systematic Review

MeSH terms

  • Commerce
  • Consumer Behavior / economics
  • Consumer Behavior / statistics & numerical data*
  • Energy Intake
  • Humans
  • Obesity / prevention & control*
  • Sugar-Sweetened Beverages / economics
  • Sugar-Sweetened Beverages / statistics & numerical data*
  • Taxes / statistics & numerical data*