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Estimating the distribution of usual intake of micronutrients via asymmetric models

Grant number: 15/15195-7
Support Opportunities:Regular Research Grants
Start date: May 01, 2016
End date: April 30, 2018
Field of knowledge:Health Sciences - Nutrition - Nutritional Analysis of Population
Principal Investigator:José Eduardo Corrente
Grantee:José Eduardo Corrente
Host Institution: Instituto de Biociências (IBB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
Associated researchers:Giovana Fumes Ghantous

Abstract

The analysis of nutritional data has been a major challenge for both professionals in the field of nutrition as the area of Statistics. Several methods of analysis of consumption data have been proposed, such as Iowa State University (ISU) method, Iowa State University for Food (ISUF) method and National Cancer Institute (NCI) using mixed models with measurement errors in order to remove the within-person variability, the main effect observed due to the variability of the diet. Such models are needed to estimate the prevalence of inadequate nutrient consumption that is made using the Dietary Reference Intakes (DRI) as cutoffs. The main problem lies in the fact that various nutrients have strongly asymmetric distribution. In these cases, the use of Box-Cox transformations are not effective to correctly estimate the consumption distribution. Such transformations are used in both the ISU method as in NCI and a back transformation is needed to return in the original data scale. The advantage of using asymmetric models is, according to the parameters interpretation, there is no need to use a transformation in the data. Then, the aim of this project will b to implement asymmetric distributions using a random effect models similar to NCI in order to obtain a better estimate of the distribution intake of micronutrients, make some comparisons with NCI (only for the part of nutrient intake) method and use data from nutritional surveys for adults and older adults form São Paulo and Botucatu cities. (AU)

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