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Randomized Controlled Trial
. 2020 Oct 29;12(11):3334.
doi: 10.3390/nu12113334.

Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial

Megan E Rollo  1   2 , Rebecca L Haslam  1   2 , Clare E Collins  1   2
Affiliations
Randomized Controlled Trial

Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial

Megan E Rollo et al. Nutrients. .

Abstract

Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report generated using the Australian Eating Survey® (AES) food frequency questionnaire data; and (2) high personalization, involving structured video calls with a dietitian using the AES report plus dietary self-monitoring with text message feedback. Intake was measured at baseline and 12 weeks using the AES and diet quality using the Australian Recommended Food Score (ARFS). Fifty participants (aged 39.2 ± 12.5 years; Body Mass Index 26.4 ± 6.0 kg/m2; 86.0% female) completed baseline measures. Significant (p < 0.05) between-group differences in dietary changes favored the high personalization group for total ARFS (5.6 points (95% CI 1.3 to 10.0)) and ARFS sub-scales of meat (0.9 points (0.4 to 1.6)), vegetarian alternatives (0.8 points (0.1 to 1.4)), and dairy (1.3 points (0.3 to 2.3)). Additional significant changes in favor of the high personalization group occurred for proportion of energy intake derived from energy-dense, nutrient-poor foods (-7.2% (-13.8% to -0.5%)) and takeaway foods sub-group (-3.4% (-6.5% to 0.3%). Significant within-group changes were observed for 12 dietary variables in the high personalization group vs one variable for low personalization. A higher level of personalized support combining the AES report with one-on-one dietitian video calls and dietary self-monitoring resulted in greater dietary change compared to the AES report alone. These findings suggest nutrition-related web and mobile technologies in combination with personalized dietitian delivered advice have a greater impact compared to when used alone.

Keywords: behavioral nutrition intervention; digital health; personalized nutrition; telehealth.

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Conflict of interest statement

The funders had no role in the design of the study, in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. The Australian Eating Survey® is a food frequency questionnaire, which is available for use on a fee-paying basis and is managed by the University of Newcastle.

Figures

Figure 1
Figure 1
Examples of graphical feedback provided in the Australian Eating Survey® (AES) report: (a) proportion of energy intake from core and non-core food groups; (b) adequacy of fibre and micronutrient intake; and (c) proportion of energy intake from macronutrients.
Figure 2
Figure 2
Flow diagram of study participants.
Figure 3
Figure 3
Participant feedback on the AES (a) and associated dietary feedback report (b).
See this image and copyright information in PMC

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