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A combination of statistical methods for the analysis of the relative validation data of the quantitative food frequency questionnaire used in the THUSA study

Published online by Cambridge University Press:  02 January 2007

UE MacIntyre ,
CS Venter ,
HH Vorster  and
HS Steyn
UE MacIntyre*
Affiliation:
Department of Paediatrics and Child Health, PO Box 168, Medical University of Southern Africa, 0204South Africa
CS Venter
Affiliation:
Department of Nutrition and Family Ecology, Potchefstroom University for Christian Higher Education, South Africa
HH Vorster
Affiliation:
Department of Nutrition and Family Ecology, Potchefstroom University for Christian Higher Education, South Africa
HS Steyn
Affiliation:
Statistical Services, Potchefstroom University for Christian Higher Education, South Africa
*
*Corresponding author: Email paeds@iweb.co.za
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Abstract

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Objective:

To apply structural equation modelling (SEM) and estimation of variance components to the relative validation data obtained from the quantitative food frequency questionnaire (QFFQ) used in the Transition, Health and Urbanisation in South Africa (THUSA) study.

Design:

A cross-sectional study.

Setting:

A community-based field study in an African population conducted during 1996.

Subjects:

Residents of the North West Province, South Africa, aged between 15 and 65 years.

Methods:

Relative validity of the QFFQ was tested against 7-day weighed food records, 24-hour urinary nitrogen (UN) excretion and estimated basal metabolic rate (BMR). SEM and estimation of variance components were applied to the log-transformed energy, protein, fat, calcium, iron, vitamin A and vitamin C intakes. UN excretion was used as a biomarker in the application of the SEM to protein and estimated BMR to energy intakes.

Results:

Constant bias (αQ) derived by the SEM varied from 0.85 (vitamin C) to 5.8 (energy). There was significant proportional bias for all nutrients except vitamin C. Validation coefficients (ρ(Q, T )) varied from 0.3 (fat, calcium, iron) to 0.7 (vitamin C). The inclusion of estimated BMR in the SEM for energy increased ρ(Q, T ) from 0.38 to 0.42. The estimation of variance components gave slightly lower correlations for the relationship between intakes from the QFFQ and the unknown true intake.

Conclusions:

Robust statistical methods were successfully applied in a relative validation study for a QFFQ in an African population. Estimated BMR as a biomarker for energy intake produced more meaningful results than UN excretion as a biomarker for protein intake.

Keywords

Dietary surveysRelative validityStatistical methods

Information

Type
Research Article
Information
Public Health Nutrition , Volume 4 , Issue 1 , February 2001 , pp. 45 - 51
Copyright
Copyright © CABI Publishing 2001

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