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Using Crowdsourced Food Image Data for Assessing Restaurant Nutrition Environment: A Validation Study.

Weixuan Lyu1,2, Nina Seok2, Xiang Chen1

  • 1Department of Geography, University of Connecticut, Storrs, CT 06269, USA.

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Crowdsourced food images can help assess restaurant nutrition, but have biases. Supplementing this data with other sources is crucial for a complete understanding of the restaurant nutrition environment.

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Area of Science:

  • Nutrition Science
  • Public Health
  • Data Science

Background:

  • Crowdsourced food images and image recognition offer a scalable method for assessing restaurant nutrition environments.
  • Previous studies validated food image recognition technology accuracy.
  • The validity of crowdsourced images as a primary data source for large-scale assessments remains under-explored.

Purpose of the Study:

  • To comprehensively examine the validity of using crowdsourced food images for assessing the restaurant nutrition environment.
  • To evaluate the representativeness of crowdsourced data for understanding restaurant nutrition quality and customer dietary behaviors.

Main Methods:

  • Collected data from multiple sources in the Greater Hartford region.
  • Examined the validity of crowdsourced food images for restaurant nutrition assessment.
  • Analyzed potential selection biases in crowdsourced food image data.

Main Results:

  • Crowdsourced food images are useful for initial restaurant nutrition quality assessment and identifying popular food items.
  • Crowdsourced data exhibit selection bias at multiple levels.
  • The data do not fully represent overall restaurant nutrition quality or customer dietary behaviors.

Conclusions:

  • Crowdsourced food images provide a valuable initial assessment tool but are insufficient as a sole data source.
  • Supplementing crowdsourced image data with field surveys, store audits, and commercial data is essential for a representative assessment.
  • A multi-source data approach is recommended for accurate restaurant nutrition environment evaluation.