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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.
Nutrients
|October 14, 2023
Summary
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.
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.
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