A Brief Tool to Assess Image-Based Dietary Records and Guide Nutrition Counselling Among Pregnant Women: An Evaluation.
BACKGROUND
Dietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address limitations of traditional methods of recording dietary intake. Feedback on these records can then be provided by the dietitian via smartphone. Efficacy and validity of these methods requires examination.


OBJECTIVE
The aims of the Australian Diet Bytes and Baby Bumps study, which used image-based dietary records and a purpose-built brief Selected Nutrient and Diet Quality (SNaQ) tool to provide tailored nutrition advice to pregnant women, were to assess relative validity of the SNaQ tool for analyzing dietary intake compared with nutrient analysis software, to describe the nutritional intake adequacy of pregnant participants, and to assess acceptability of dietary feedback via smartphone.


METHODS
Eligible women used a smartphone app to record everything they consumed over 3 nonconsecutive days. Records consisted of an image of the food or drink item placed next to a fiducial marker, with a voice or text description, or both, providing additional detail. We used the SNaQ tool to analyze participants' intake of daily food group servings and selected key micronutrients for pregnancy relative to Australian guideline recommendations. A visual reference guide consisting of images of foods and drinks in standard serving sizes assisted the dietitian with quantification. Feedback on participants' diets was provided via 2 methods: (1) a short video summary sent to participants' smartphones, and (2) a follow-up telephone consultation with a dietitian. Agreement between dietary intake assessment using the SNaQ tool and nutrient analysis software was evaluated using Spearman rank correlation and Cohen kappa.


RESULTS
We enrolled 27 women (median age 28.8 years, 8 Indigenous Australians, 15 primiparas), of whom 25 completed the image-based dietary record. Median intakes of grains, vegetables, fruit, meat, and dairy were below recommendations. Median (interquartile range) intake of energy-dense, nutrient-poor foods was 3.5 (2.4-3.9) servings/day and exceeded recommendations (0-2.5 servings/day). Positive correlations between the SNaQ tool and nutrient analysis software were observed for energy (ρ=.898, P<.001) and all selected micronutrients (iron, calcium, zinc, folate, and iodine, ρ range .510-.955, all P<.05), both with and without vitamin and mineral supplements included in the analysis. Cohen kappa showed moderate to substantial agreement for selected micronutrients when supplements were included (kappa range .488-.803, all P ≤.001) and for calcium, iodine, and zinc when excluded (kappa range .554-.632, all P<.001). A total of 17 women reported changing their diet as a result of the personalized nutrition advice.


CONCLUSIONS
The SNaQ tool demonstrated acceptable validity for assessing adequacy of key pregnancy nutrient intakes and preliminary evidence of utility to support dietitians in providing women with personalized advice to optimize nutrition during pregnancy.
School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.|Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.|Gomeroi gaaynggal Centre, Faculty of Health and Medicine, University of Newcastle, Tamworth, Australia.
Amy M
http://orcid.org/0000-0001-6939-1781
AM
Ashman
School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.|Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.
Clare E
http://orcid.org/0000-0003-3298-756X
CE
Collins
Department of Rural Health, Faculty of Health and Medicine, University of Newcastle, Tamworth, Australia.
Leanne J
http://orcid.org/0000-0002-4340-2320
LJ
Brown
Gomeroi gaaynggal Centre, Faculty of Health and Medicine, University of Newcastle, Tamworth, Australia.|Department of Rural Health, Faculty of Health and Medicine, University of Newcastle, Tamworth, Australia.|Priority Research Centre in Reproduction, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.|Mothers and Babies Research Centre, Faculty of Health and Medicine, University of Newcastle, New Lambton Heights, Australia.
Kym M
http://orcid.org/0000-0002-6016-3464
KM
Rae
School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.|Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Callaghan, Australia.
Megan E
http://orcid.org/0000-0003-1303-2063
ME
Rollo
image-based dietary records; nutrition assessment; pregnancy; telehealth