Mixed
Energy-adjusted nutrient intake analysis is the optimal method for presenting and analyzing dietary data in epidemiological studies, as it reduces bias from low energy reporting and eliminates confounding by total energy intake.
When analyzing dietary data, especially in large studies, use energy-adjusted nutrient intake (regression-based) rather than simply excluding under-reporters. This method reduces bias from low energy reporting and provides a more accurate assessment of nutrient composition independent of body size and activity level.
For both methods, regression-based adjustment of nutrient intake to mean dietary energy intake by gender appears on balance to be the optimal approach to data presentation and analysis, in view of the complex problem of low energy reporting.
Why this rating
Supported by statistical comparison of three methods (all records, LER excluded, energy-adjusted) showing energy adjustment performs best on balance.
Source
Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers
Eric J. Brunner et al. · British Journal Of Nutrition · 2001
DOI 10.1079/bjn2001414
More from this paper
- A machine-readable Food Frequency Questionnaire (FFQ) provides nutrient intake estimates with validity comparable to a 7-day diet diary (7DD) when validated against biomarkers, making it a suitable tool for ranking individuals in large-scale epidemiological studies despite systematic biases in absolute intake estimation.Good
- Food Frequency Questionnaires (FFQ) tend to overestimate plant-derived micronutrients (like carotenes) and underestimate fat intake compared to 7-day diet diaries, but these systematic biases do not necessarily invalidate their ability to rank individuals for epidemiological purposes.Good
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