The Use of Food Frequency Questionnaires (FFQs) is both Pseudo-scientific and Illogical
The recent paper by Zong et al should be retracted because their methods are pseudo-scientific and their data and results are inadmissible as scientific evidence.
In a series of publications,1-4 my colleagues and I empirically refuted the memory-based dietary assessment methods (M-BMs; e.g., food frequency questionnaires, FFQs) employed by Zong et al. We unequivocally demonstrated that M-BM-data were physiologically implausible (i.e., incompatible with life 5) and therefore could not be representative of dietary consumption. More importantly, our work established that because M-BM-data were derived from non-empirical phenomena (i.e., memories), the errors associated with M-BM-data were non-quantifiable due to false memories, omissions (i.e., forgetting), intentional misreporting (i.e., lying), and gross misestimation. It is important to note that the distinction between quantifiable and nonquantifiable errors is the demarcation between valid scientific (i.e., falsifiable) data and data that are pseudo-scientific and “inadmissible.”2
Furthermore, FFQs lack any semblance of face validity (i.e., FFQs cannot possibly measure what they were intended to measure.). During the study period there were over 100,000 items in the US Food Supply available for consumption by Zong et al.’s participants. It defies logic and common sense to speculate that data from FFQs with <150 total items (i.e., a list with <0.2% of available foods and beverages) could be representative of actual dietary consumption.
Specifically, the USDA Food Composition Databases lists >77,000 items and a simple search using the terms provided by Zong et al. yields results that are orders of magnitude greater than the number of items on their FFQs. For example, using the search term “oatmeal” returns 522 items; the term “brown rice” produces 339 items, and “whole wheat bread” produces 721 items. Therefore, each item on Zong et al.'s FFQs returns hundreds of possible foods and beverages that vary in energy and nutrient composition. Nevertheless, Zong et al. credulously assumed their FFQs were representative of dietary consumption. This is inane. Given the inestimable number of physiologic interactions between the <0.2% of the foods and beverages that were available for consumption and actually on the FFQs, and the 99.8% of potential dietary components that were not on the FFQs (and therefore not estimated nor quantified), Zong et al.’s use of FFQs is pseudo-scientific, illogical, and lacking in both scientific and common sense.
Stated simply, Zong et al.'s data, results, and conclusions are meaningless. As such, their paper should be retracted.
Edward Archer, PhD, MS
Chief Science Officer
1. Archer E, Hand GA, Blair SN. Validity of U.S. nutritional surveillance: National Health and Nutrition Examination Survey caloric energy intake data, 1971-2010. PLoS One 2013;8(10):e76632. doi: 10.1371/journal.pone.0076632
2. Archer E, Pavela G, Lavie CJ. The Inadmissibility of What We Eat in America and NHANES Dietary Data in Nutrition and Obesity Research and the Scientific Formulation of National Dietary Guidelines. Mayo Clinic Proceedings 2015;90(7):911-26. doi: 10.1016/j.mayocp.2015.04.009 [published Online First: 2015/06/14]
3. Archer E, Pavela G, Lavie CJ. A Discussion of the Refutation of Memory-Based Dietary Assessment Methods (M-BMs): The Rhetorical Defense of Pseudoscientific and Inadmissible Evidence. Mayo Clinic Proceedings 2015;90(12):1736-38.
4. Archer E, Blair SN. Reply to LS Freedman et al. Advances in nutrition (Bethesda, Md) 2015;6(4):489-90. doi: 10.3945/an.115.009183 [published Online First: 2015/07/17]
5. Ioannidis JPA. Implausible results in human nutrition research. BMJ 2013;347 doi: 10.1136/bmj.f6698
Competing interests: No competing interests