Development of an approach for estimating usual nutrient intake distributions at the population level
Guenther, PM., Kott, P., & Carriquiry, AL. (1997). Development of an approach for estimating usual nutrient intake distributions at the population level. Journal of Nutrition, 127(6), 1106-1112. http://jn.nutrition.org/cgi/content/full/127/6/1106
Assessment of the dietary intake of a population must consider the large within-person variation in daily intakes. A 1986 report by the National Academy of Sciences (NAS), commissioned by the U.S. Department of Agriculture (USDA), marked an important milestone in the history of this issue. Since that time, USDA has been working cooperatively with statisticians at Iowa State University (ISU), who have further developed the measurement error model approach proposed by NAS. The method developed by the ISU statisticians can be used to estimate usual dietary intake distributions for a population but not for specific individuals. It is based on the assumption that an individual can more accurately recall and describe the foods eaten yesterday than foods eaten at an earlier time. The method requires as few as two independent days of nutrient intake information or three consecutive days for at least a subsample of the individuals. It removes biases of subsequent reporting days compared with the first day, and temporal effects such as day-of-the-week and seasonal effects can be easily removed. The method developed at ISU is described conceptually and applied to data collected in the 1989-91 USDA Continuing Survey of Food intakes by individuals to estimate the proportion of men and women age 20 y and older having "usual" (long-run average) intakes below 30% of energy from fat, below the 1989 Recommended Dietary Allowances for vitamin A and folate, and above 1000 micrograms for folate. These results were compared with the results from the distributions of 1-d intakes and of 3-d mean intakes to demonstrate the effect of within-person variation and asymmetry on usual nutrient intakes in a population.