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Using Short Dietary Questions to Develop Indicators of Dietary Behaviour for Use in Surveys Exploring Attitudinal and/or Behavioural Aspects of Dietary Choices
Authors:Alison Daly  Christina M Pollard  Deborah A Kerr  Colin W Binns  Michael Phillips
Institution:1.School of Public Health, Curtin University, Kent Street, Perth 6845, Australia; E-Mails: (D.A.K.); (C.W.B.);2.Department of Health in Western Australia, 189 Royal Street, East Perth 6004, Australia; E-Mail: ;3.Harry Perkins Institute for Medical Research, University of Western Australia, 50 Murray Street, Perth 6000, Australia; E-Mail:
Abstract:For countries where nutrition surveys are infrequent, there is a need to have some measure of healthful eating to plan and evaluate interventions. This study shows how it is possible to develop healthful eating indicators based on dietary guidelines from a cross sectional population survey. Adults 18 to 64 years answered questions about the type and amount of foods eaten the previous day, including fruit, vegetables, cereals, dairy, fish or meat and fluids. Scores were based on serves and types of food according to an established method. Factor analysis indicated two factors, confirmed by structural equation modeling: a recommended food healthful eating indicator (RF_HEI) and a discretionary food healthful eating indicator (DF_HEI). Both yield mean scores similar to an established dietary index validated against nutrient intake. Significant associations for the RF_HEI were education, income, ability to save, and attitude toward diet; and for the DF_HEI, gender, not living alone, living in a socially disadvantaged area, and attitude toward diet. The results confirm that short dietary questions can be used to develop healthful eating indicators against dietary recommendations. This will enable the exploration of dietary behaviours for “at risk” groups, such as those with excess weight, leading to more relevant interventions for populations.
Keywords:dietary behaviours  healthful eating indicators  structural equation modelling  cross sectional
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