Towards Automated Risk-Factor Surveillance: Using Digital Grocery Purchasing Data to Measure Socioeconomic Inequalities in the Impact of In-Store Price Discounts on Dietary Choice

Authors

  • Hiroshi Mamiya
  • Erica Moodie
  • Deepa Jahagirdar
  • David Buckeridge

DOI:

https://doi.org/10.5210/ojphi.v8i1.6481

Abstract

We explored the utility of electronic grocery store transaction data to assess the impact of in-store discounting of soda, a previously unknown risk factor of obesity and overweight, which cause substantial societal and economic burden worldwide. We found the strong impact of price discounting on the purchase of soda, particularity among stores located in lower educational attainment. The finding suggest the importance of monitoring store-level price discount, health disparity in terms of susceptibility to in-store price promotion of energy-dense food products, and the usefulness of digital grocery purchase data for the community surveillance of dietary choice.

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Published

2016-03-24

How to Cite

Mamiya, H., Moodie, E., Jahagirdar, D., & Buckeridge, D. (2016). Towards Automated Risk-Factor Surveillance: Using Digital Grocery Purchasing Data to Measure Socioeconomic Inequalities in the Impact of In-Store Price Discounts on Dietary Choice. Online Journal of Public Health Informatics, 8(1). https://doi.org/10.5210/ojphi.v8i1.6481

Issue

Section

Lightning Talks