Minimum Days Estimation for Reliable Dietary Intake Information: Findings from a Digital Cohort

Abstract

Accurate dietary assessment is crucial for understanding diet-health relationships, but variability in daily food intake poses challenges in capturing precise data. This study leveraged data from 958 participants of the “Food & You“ digital cohort to determine the minimum number of days required for reliable dietary intake estimation. Participants tracked meals using the AI-assisted MyFoodRepo app, providing a comprehensive dataset of over 315,000 dishes across 23,335 participant days. We employed multiple analytical approaches, including Linear Mixed Models (LMM), Intraclass Correlation Coefficient (ICC), and Coefficient of Variation (CV) methods. LMM analysis revealed significant day-of-week effects, with increased energy, carbohydrate, and alcohol intake on weekends, particularly pronounced in younger individuals and those with higher BMI. ICC and CV analyses demonstrated that the required number of days varies considerably among nutrients and food groups. Water, coffee, and total food quantity by weight could be reliably estimated (ICC>0.9) with just 1-2 days of data. Most macronutrients, including carbohydrates, protein, and fat, achieved good reliability (ICC>0.75 or r=0.8) with 3-4 days of data. Micronutrients and some food groups like meat and vegetables typically required 4-5 days for highly reliable estimation. Optimal day combinations often included both weekdays and weekend days. Our findings largely align with and refine FAO recommendations, suggesting that 3-4 days, typically non-consecutive and including a weekend day, are generally sufficient for reliable estimation of energy and macronutrient intake. However, our results provide more nuanced, nutrient-specific guidelines that can inform the design of future nutritional studies.