Mixed

Failure to correct for measurement error in dietary assessment variables (saturated fat, calories, alcohol) biases relative risk estimates toward the null, potentially masking true associations between diet and disease outcomes.

When interpreting nutritional studies, be aware that self-reported diet data often underestimates the true strength of a diet-disease link due to measurement error. Researchers use statistical corrections to adjust these numbers; if a study reports a 'corrected' risk, it is likely a more accurate reflection of reality than the raw data. For individuals, this means a lack of statistical significance in a single study regarding a specific nutrient (like saturated fat) might be due to measurement noise rather than a true lack of effect, though this specific study found no important effect of saturated fat even after correction.