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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
Published on: September 18, 2018
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Calorie Compensation Patterns Observed in App-Based Food Diaries.
Amruta Pai1, Ashutosh Sabharwal1
1Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
Nutrients
|September 28, 2023
Summary
This study introduces a new method to track calorie compensation in daily life using food diary apps. It reveals individual eating patterns and identifies behaviors linked to unhealthy weight gain.
Area of Science:
- Behavioral Science
- Nutritional Science
- Computational Health
Background:
- Self-regulation of food intake is crucial for weight management.
- Calorie compensation, adjusting intake based on previous meals, is a key aspect of self-regulation.
- Previous studies primarily used controlled preload tests, limiting understanding of real-world compensatory behaviors.
Purpose of the Study:
- To propose and validate a novel methodology for measuring calorie compensation profiles in free-living conditions using app-based food diary data.
- To analyze individual compensation patterns, including under-, over-, non-, and precise compensation.
- To identify behavioral phenotypes associated with poor compensatory eating and potential weight gain.
Main Methods:
- Leveraged extensive observational food diary data from 1622 MyFitnessPal users.
- Developed a methodology to analyze compensation profiles as distributions over time, rather than single indices.
- Validated the sufficiency of four weeks of data for accurate user compensation profile characterization.
Main Results:
- Meal compensation is more prevalent than day-level compensation.
- Dinner compensation occurs more frequently than lunch compensation.
- Users tend to overcompensate for missed calories more than for excess calories, with precise compensation being least common.
- Poor compensatory behaviors correlate with lower adherence to daily calorie goals.
Conclusions:
- The proposed methodology effectively characterizes individual calorie compensation profiles in free-living settings.
- Identified specific patterns in meal and day compensation, and over/under-compensation tendencies.
- This approach can identify behavioral phenotypes for early weight gain markers, aiding in preventative strategies.
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