A Monte Carlo simulation to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level

Abstract

AbstractObjective:The aim of this study was to validate the EAR cut-point method for assessing the prevalence of nutrient inadequacy at the population level.Design and subjects:Different methods for estimating the prevalence of inadequate intake were compared: the cut-off point method, with cut-off points at the Recommended Dietary Allowance (RDA), 0.66 RDA, 0.50 RDA and the Estimated Average Requirement (EAR); the probability approach; and a Monte Carlo simulation. In total, 591 men and 674 women, aged 20–55 years, were included in the analyses.Results:The prevalence of inadequate intake as estimated by the EAR cut-point method was similar to the prevalence of inadequacy estimated by both probabilistic methods. The cut-point method with RDA, 0.66 RDA and 0.50 RDA as cut-off limits induced an over- or an underestimation of the real prevalence of inadequacy.Conclusions:Probabilistic methods consider both the intake variability and the requirement variability, and, as a result, their estimation should be closer to the real prevalence of inadequacy. The use of the EAR cut-point method yields a good estimation of the prevalence of inadequate intake, comparable to the probability approach, and limits over- and underestimation of the prevalence induced by other cut-off points.