Affiliations 

  • 1 School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia
  • 2 School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
  • 3 Enable Institute, Faculty of Health Sciences, Curtin University, Perth, Australia
  • 4 Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Perth, Australia
  • 5 Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States
  • 6 School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States
  • 7 Department of Nutrition, Dietetics and Food, Monash University, Melbourne, Australia
  • 8 School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
  • 9 Health Section, Health and Disability Branch, Australian Bureau of Statistics, Canberra, Australia
JMIR Res Protoc, 2021 Dec 16;10(12):e32891.
PMID: 34924357 DOI: 10.2196/32891

Abstract

BACKGROUND: The assessment of dietary intake underpins population nutrition surveillance and nutritional epidemiology and is essential to inform effective public health policies and programs. Technological advances in dietary assessment that use images and automated methods have the potential to improve accuracy, respondent burden, and cost; however, they need to be evaluated to inform large-scale use.

OBJECTIVE: The aim of this study is to compare the accuracy, acceptability, and cost-effectiveness of 3 technology-assisted 24-hour dietary recall (24HR) methods relative to observed intake across 3 meals.

METHODS: Using a controlled feeding study design, 24HR data collected using 3 methods will be obtained for comparison with observed intake. A total of 150 healthy adults, aged 18 to 70 years, will be recruited and will complete web-based demographic and psychosocial questionnaires and cognitive tests. Participants will attend a university study center on 3 separate days to consume breakfast, lunch, and dinner, with unobtrusive documentation of the foods and beverages consumed and their amounts. Following each feeding day, participants will complete a 24HR process using 1 of 3 methods: the Automated Self-Administered Dietary Assessment Tool, Intake24, or the Image-Assisted mobile Food Record 24-Hour Recall. The sequence of the 3 methods will be randomized, with each participant exposed to each method approximately 1 week apart. Acceptability and the preferred 24HR method will be assessed using a questionnaire. Estimates of energy, nutrient, and food group intake and portion sizes from each 24HR method will be compared with the observed intake for each day. Linear mixed models will be used, with 24HR method and method order as fixed effects, to assess differences in the 24HR methods. Reporting bias will be assessed by examining the ratios of reported 24HR intake to observed intake. Food and beverage omission and intrusion rates will be calculated, and differences by 24HR method will be assessed using chi-square tests. Psychosocial, demographic, and cognitive factors associated with energy misestimation will be evaluated using chi-square tests and multivariable logistic regression. The financial costs, time costs, and cost-effectiveness of each 24HR method will be assessed and compared using repeated measures analysis of variance tests.

RESULTS: Participant recruitment commenced in March 2021 and is planned to be completed by the end of 2021.

CONCLUSIONS: This protocol outlines the methodology of a study that will evaluate the accuracy, acceptability, and cost-effectiveness of 3 technology-enabled dietary assessment methods. This will inform the selection of dietary assessment methods in future studies on nutrition surveillance and epidemiology.

TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12621000209897; https://tinyurl.com/2p9fpf2s.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32891.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.