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Open Access Research

Nutrient estimation from an FFQ developed for a black Zimbabwean population

Anwar T Merchant12*, Mahshid Dehghan13, Jephat Chifamba4, Getrude Terera4 and Salim Yusuf123

Author Affiliations

1 Population health Research Institute, McMaster University, Hamilton ON, Canada

2 Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton ON, Canada

3 Department of Medicine, McMaster University, Hamilton ON, Canada

4 Department of Physiology, University of Zimbabwe College of Health Sciences, Harare, Zimbabwe

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Nutrition Journal 2005, 4:37  doi:10.1186/1475-2891-4-37

Published: 13 December 2005

Abstract

Background

There is little information in the literature on methods of food composition database development to calculate nutrient intake from food frequency questionnaire (FFQ) data. The aim of this study is to describe the development of an FFQ and a food composition table to calculate nutrient intake in a Black Zimbabwean population.

Methods

Trained interviewers collected 24-hour dietary recalls (24 hr DR) from high and low income families in urban and rural Zimbabwe. Based on these data and input from local experts we developed an FFQ, containing a list of frequently consumed foods, standard portion sizes, and categories of consumption frequency. We created a food composition table of the foods found in the FFQ so that we could compute nutrient intake. We used the USDA nutrient database as the main resource because it is relatively complete, updated, and easily accessible. To choose the food item in the USDA nutrient database that most closely matched the nutrient content of the local food we referred to a local food composition table.

Results

Almost all the participants ate sadza (maize porridge) at least 5 times a week, and about half had matemba (fish) and caterpillar more than once a month. Nutrient estimates obtained from the FFQ data by using the USDA and Zimbabwean food composition tables were similar for total energy intake intra class correlation (ICC) = 0.99, and carbohydrate (ICC = 0.99), but different for vitamin A (ICC = 0.53), and total folate (ICC = 0.68).

Conclusion

We have described a standardized process of FFQ and food composition database development for a Black Zimbabwean population.