Can a Simple Dietary Index Derived from a Sub-Set of Questionnaire Items Assess Diet Quality in a Sample of Australian Adults?

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Abstract

Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004-2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman's rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen's weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.

Original languageEnglish
Article number486
JournalNutrients
Volume10
Issue number4
DOIs
Publication statusPublished - 13 Apr 2018

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nutritional adequacy
Nutrition Policy
Dietary Guidelines
questionnaires
Diet
longitudinal studies
sampling
Longitudinal Studies
physical activity
Surveys and Questionnaires
Smoking
methodology
Exercise
Health

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title = "Can a Simple Dietary Index Derived from a Sub-Set of Questionnaire Items Assess Diet Quality in a Sample of Australian Adults?",
abstract = "Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004-2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman's rho = 0.78 and 0.84; gross misclassification = 1.8{\%}; correct classification = 64.9{\%} and 69.7{\%}; and, Cohen's weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62{\%} and 73{\%} of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.",
author = "Alexia Bivoltsis and Trapp, {Georgina S A} and Matthew Knuiman and Paula Hooper and Ambrosini, {Gina L}",
year = "2018",
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T1 - Can a Simple Dietary Index Derived from a Sub-Set of Questionnaire Items Assess Diet Quality in a Sample of Australian Adults?

AU - Bivoltsis, Alexia

AU - Trapp, Georgina S A

AU - Knuiman, Matthew

AU - Hooper, Paula

AU - Ambrosini, Gina L

PY - 2018/4/13

Y1 - 2018/4/13

N2 - Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004-2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman's rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen's weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.

AB - Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004-2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman's rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen's weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.

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JO - Nutrients

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