Measurement error and results from analytic epidemiology: Dietary fat and breast

Background: International correlational analyses have sug-gested a strong positive association between fat consumption and breast cancer incidence, especially among post-menopausal women. However, case—control studies have been taken to indicate a weaker association, and a recent, pooled cohort analysis reported little evidence of an associa-tion. Differences among study results could be due to dif-ferences in the populations studied, differences in the control for total energy intake, recall bias in the case-control studies, and dietary measurement error biases. Existing measurement error models assume either that the sample data used to validate dietary self-report instruments are without measurement error or that any such error is inde-pendent of both the true dietary exposure and other study subject characteristics. However, growing evidence indicates that total energy and, presumably, both total fat and percent energy from fat are increasingly underreported as percent body fat increases. Purpose: A relaxed dietary measurement model is introduced that allows all measurement error parameters to depend on body mass index (weight in kilograms divided by the square of height in meters) and in-corporates a random underreporting quantity that applies to each dietary self-report instrument. The model was ap-plied to results from international correlational analyses to determine whether the differing associations between dietary fat and postmenopausal breast cancer can be ex-plained by measurement errors in dietary assessment Methods: The relaxed measurement model was developed by use of data on total fat intake and percent energy from fat from 4-day food records (4DFRs) and food-frequency ques-tionnaires (FFQs) from the original Women's Health Trial. This trial was a randomized, controlled, feasibility study of a low-fat dietary intervention carried out from 1985 throug