Oral Presentation ANZOS-Breakthrough Discoveries Joint Annual Scientific Meeting 2018

Using online data collection methods to estimate the price and affordability of healthy and less healthy diets under different pricing scenarios. (#92)

Christina Zorbas 1 , Amanda J Lee 2 , Anna Peeters 1 , Tim Landrigan 3 , Kathryn Backholer 1
  1. School of Health and Social Development, Deakin University, Geelong, VIC, Australia
  2. The Australian Prevention Partnership Centre, Queensland University of Technology, Brisbane, QLD, Australia
  3. School of Public Health, Curtin University, Perth, WA, Australia

Introduction

Routine monitoring of diet prices and affordability is critical to inform pricing policies that can improve population diets. Monitoring currently relies on laborious in-store data collection. Studies are yet to comprehensively examine how diet prices can be monitored through the growing availability of online information and how pricing strategies (price promotions and generic brands) affect diet prices/affordability. This study aimed to address these gaps.

Methods

A scraping tool was used to automatically collect online food and beverage prices from a major supermarket chain in June 2018. Pricing information was collected for over 12,000 products. This data was used to compare the price and affordability of two diets (healthy and unhealthy) using the Australian Standardised Affordability and Pricing (ASAP) methods. The price and affordability of a healthy and unhealthy diet was compared under different pricing scenarios, which considered price promotions and generic brands. Diet affordability was measured against the national poverty line and median income quintiles.

Findings

Using the standard in-store approach, the fortnightly price of a healthy diet ($653) was estimated to be cheaper than an unhealthy diet ($820) for a household of four. When accounting for price promotions, the healthy diet remained cheaper, but the price was reduced by 3% compared to 7% for an unhealthy diet. The greatest reduction in diet prices was observed when including generic brands (healthy diet; -19%, unhealthy diet; -17%). All diet prices remained largely unaffordable when measured against the poverty line and lowest income quintile, although generic brands notably improved affordability.

Conclusions

The systematic collection of online supermarket pricing data can facilitate flexible and timely diet price/affordability analyses. These methods should continue to be tested to improve validity against previous Australian studies (by examining sources of pricing discrepancies such as seasonal trends), to ultimately inform robust monitoring methods and pricing policies.