Potentials and limitations of a food group-based algorithm to assess dietary nutrient intake of women in rural areas in Tanzania

• Published in: International journal of food sciences and nutrition Vol. 75; no. 4; pp. 436 - 444
• Main Authors: Eleraky, Laila, Stuetz, Wolfgang, Rybak, Constance, Frank, Jan, Biesalski, Hans Konrad, Mbwana, Hadijah, Kinabo, Joyce, Lambert, Christine
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis Ltd 18.05.2024
• Subjects: Algorithms; Biomarkers; Bivariate analysis; computer software; Correlation coefficient; Correlation coefficients; Dietary intake; energy; Food; food composition; Food groups; Food intake; iron; Micronutrients; nutrient intake; Nutrients; Rural areas; Software; Tanzania; zinc; Tanzania; Validation; iron; vitamin A; nutrition assessment; zinc
• ISSN: 0963-7486; 1465-3478; 1465-3478
• DOI: 10.1080/09637486.2024.2335523

The aim of this study was to evaluate the accuracy of nutrient intake assessment with the food group-based algorithm "Calculator of Inadequate Micronutrient Intake" (CIMI) in comparison to the established nutrition software NutriSurvey. Using Food Frequency Questionnaires and 24-h dietary recalls of 1010 women from two rural districts in Tanzania, 23 relevant typical Tanzanian food groups were identified and subsequently the dietary protocols assessed CIMI algorithm were compared by bivariate correlations and Bland-Altman analysis with the results of the NutriSurvey software (reference) and were set in relation to blood biomarkers of 666 participants. CIMI and NutriSurvey calculations regarding macro- and micronutrient intakes were similar. The Bland-Altman analyses and correlation coefficients of energy (0.931), protein (0.898), iron (0.775) and zinc (0.838) confirm the agreement of both calculations. The food group based CIMI algorithm is a practical tool to identify the inadequacy of macro- and micronutrient intake at population level.