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Understanding the Variation within a Dietary Guideline Index Score to Identify the Priority Food Group Targets for Improving Diet Quality across Population Subgroups.

Gilly A HendrieGreg LyleChelsea E MauchJoyce HaddadRebecca K Golley
Published in: International journal of environmental research and public health (2021)
Globally, population dietary intakes fall below the guideline recommendations and large-scale interventions have had modest success in improving diet quality. To inform the development of more targeted approaches, this study analysed the variations in self-reported data from an online survey of Australian adults collected between 2015 and 2020, to identify common combinations of low scoring components within a dietary guideline index. A low score was defined as meeting less than half the guideline recommendations (a score <50 out of 100). Among 230,575 adults, a single component analysis showed that 79.5% had a low score for discretionary choices, 72.2% for healthy fats and 70.8% for dairy. The combinations approach showed 83.0% of individuals had two to five low scoring components, with men, younger adults aged 18-30 years and individuals with obesity (BMI ≥ 30) more likely to have five or more. The most common dietary pattern combination included low scores for discretionary choices, dairy and healthy fats. There was a considerable but systematic variation in the low scoring components within the dietary patterns, suggesting that interventions with the flexibility to address particular combinations of key food groups across subgroups could be an effective and resource efficient way to improve diet quality in the population.
Keyphrases
  • physical activity
  • weight loss
  • metabolic syndrome
  • type diabetes
  • clinical practice
  • quality improvement
  • machine learning
  • artificial intelligence