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Fast and efficient estimation of micronutrient intake in Brazil (804.16)
Author(s) -
Biesalski Hans,
Feuerstein Clarissa,
Lambert Christine,
Finco Fernanda
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.804.16
Subject(s) - micronutrient , malnutrition , environmental health , food group , nutrient , food composition data , population , dietary reference intake , vitamin , estimation , respondent , geography , medicine , food science , biology , ecology , pathology , political science , law , economics , orange (colour) , management
A fast and efficient detection of micronutrient deficiencies is needed to fight Hidden Hunger, which causes numerous development disorders. In this work we developed a method of detecting micronutrient malnutrition, which is based on intake data of food groups, not on single foods. This facilitates data acquisition for interviewer and respondent as well as time management for data input. The focus is on accurate estimation of intake of the most misrepresented micronutrients in the Brazilian diet (iron, vitamin A, vitamin E, thiamin, calcium, folate). The Food groups were created from 24‐Hour Dietary Recalls on two non‐consecutive days of 34,003 Brazilian inhabitants, retrieved from the National Dietary Survey 2008‐2009. Traditional food groups, like vegetables or fruits, were refined by isolating food types that considerably bias the average nutrient amount of each group. This has been accomplished by considering population’s consumption variance and by using cluster analysis to isolate food types with an extreme deviating nutrient amount. As a result, 20 stable food groups were formed, based on their average food consumption and nutrient composition. The average nutrient amount was calculated for population subgroups defined by the 5 geographic regions of Brazil and four income groups. In conclusion, the program can help to uncover cases of malnutrition and facilitate actively the governmental efforts.