Journal article

The Relative Validity of the Menzies Remote Short-Item Dietary Assessment Tool (MRSDAT) in Aboriginal Australian Children Aged 6-36 Months

Emma Tonkin, Dani Kennedy, Rebecca Golley, Rebecca Byrne, Athira Rohit, Therese Kearns, Sarah Hanieh, Beverley-Ann Biggs, Julie Brimblecombe

NUTRIENTS | MDPI | Published : 2018

Abstract

The Menzies Remote Short-item Dietary Assessment Tool (MRSDAT) can be used to derive a dietary index score, which measures the degree of compliance with the Australian Dietary Guidelines. This study aimed to determine the relative validity of a dietary index score for children aged 6⁻24 months, living in a Remote Aboriginal Community (RAC), derived using MRSDAT. This validation study compared dietary index scores derived using MRSDAT with those derived from the average of three 24-h recalls. Participants were aged 6⁻36 months at the first dietary assessment and were living in a RAC. The level of agreement between the two methods was explored using Lin’s concordance correlation coefficient (C..

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Grants

Awarded by NHMRC Centre for Research Excellence in The Early Prevention of Obesity in Childhood


Awarded by NHMRC Early Career Fellowship


Funding Acknowledgements

This research was funded by a Menzies School of Health Research small grant and an Indigenous Research Initiative Seed Funding Scheme from the University of Melbourne. Rebecca Golley is an investigator within and Rebecca Byrne is supported by funding from the NHMRC Centre for Research Excellence in The Early Prevention of Obesity in Childhood (APP1101675). Therese Kearns was supported by a NHMRC Early Career Fellowship (GNT1052716). Julie Brimblecombe was supported by a Heart Foundation Future Leader Fellowship. Sarah Hanieh is supported by an NHMRC Early Career Fellowship. We would like to thank community researchers Veronica Gondarra and Roslyn Dhurrkay, and retired Aboriginal health practitioner Yalurr Dhanarrandji, for their assistance in data collection, and the communities that supported the research, and all those who participated their time. We would also like to thank Menzies statistician Associate Professor Federica Barzi for her technical support.