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Fulltext A Systematic Review Examining Contributors to Misestimation of Food and Beverage Intake Based on Short-Term Self-Report Dietary Assessment Instruments Administered to Adults

Whitton C, Ramos-García C, Kirkpatrick SI, Healy JD, Dhaliwal SS, Boushey CJ, et al.

Adv Nutr, 2022 Dec 22;13(6):2620-2665.
PMID: 36041186 DOI: 10.1093/advances/nmac085

Error in self-reported food and beverage intake affects the accuracy of dietary intake data. Systematically synthesizing available data on contributors to error within and between food groups has not been conducted but may help inform error mitigation strategies. In this review we aimed to systematically identify, quantify, and compare contributors to error in estimated intake of foods and beverages, based on short-term self-report dietary assessment instruments, such as 24-h dietary recalls and dietary records. Seven research databases were searched for studies including self-reported dietary assessment and a comparator measure of observed intake (e.g., direct observation or controlled feeding studies) in healthy adults up until December 2021. Two reviewers independently screened and extracted data from included studies, recording quantitative data on omissions, intrusions, misclassifications, and/or portion misestimations. Risk of bias was assessed using the QualSyst tool. A narrative synthesis focused on patterns of error within and between food groups. Of 2328 articles identified, 29 met inclusion criteria and were included, corresponding to 2964 participants across 15 countries. Most frequently reported contributors to error were omissions and portion size misestimations of food/beverage items. Although few consistent patterns were seen in omission of consumed items, beverages were omitted less frequently (0-32% of the time), whereas vegetables (2-85%) and condiments (1-80%) were omitted more frequently than other items. Both under- and overestimation of portion size was seen for most single food/beverage items within study samples and most food groups. Studies considered and reported error in different ways, impeding the interpretation of how error contributors interact to impact overall misestimation. We recommend that future studies report 1) all error contributors for each food/beverage item evaluated (i.e., omission, intrusion, misclassification, and portion misestimation), and 2) measures of variation of the error. The protocol of this review was registered in PROSPERO as CRD42020202752 (https://www.crd.york.ac.uk/prospero/).
Fulltext Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study

Whitton C, Healy JD, Collins CE, Mullan B, Rollo ME, Dhaliwal SS, et al.

JMIR Res Protoc, 2021 Dec 16;10(12):e32891.
PMID: 34924357 DOI: 10.2196/32891

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.
Accuracy of energy and nutrient intake estimation versus observed intake using four technology-assisted dietary assessment methods: a randomized crossover feeding study

Whitton C, Collins CE, Mullan BA, Rollo ME, Dhaliwal SS, Norman R, et al.

Am J Clin Nutr, 2024 May 04.
PMID: 38710447 DOI: 10.1016/j.ajcnut.2024.04.030

BACKGROUND: Technology-assisted 24-hour dietary recalls (24HR) have been widely adopted in population nutrition surveillance. Evaluations of 24HR inform improvements but direct comparisons of 24HR methods for accuracy in reference to a measure of true intake are rarely undertaken in a single study population.
OBJECTIVE: To compare the accuracy of energy and nutrient intake estimation of four technology-assisted dietary assessment methods relative to true intake across breakfast, lunch, and dinner.
METHODS: In a controlled feeding study with a crossover design, 152 participants (55% women; mean age 32y (SD 11); mean BMI 26 kg/m2 (SD 5)) were randomized to one of three separate feeding days to consume breakfast, lunch, and dinner, with unobtrusive weighing of foods and beverages consumed. Participants undertook a 24HR the following day (Automated Self-Administered Dietary Assessment Tool-Australia© (ASA24); Intake24-Australia©; mobile Food Record™ - Trained Analyst (mFR-TA); or Image-Assisted Interviewer-Administered 24-hour recall (IA-24HR)). When assigned to IA-24HR, participants referred to images captured of their meals using the mobile Food Record™ app. True and estimated energy and nutrient intakes were compared, and differences among methods were assessed using linear mixed models.
RESULTS: The mean difference between true and estimated energy intake as a percentage of true intake was 5.4% (95% CI 0.6, 10.2) using ASA24, 1.7% (95% CI -2.9, 6.3) using Intake24, 1.3% (95% CI -1.1, 3.8) using mFR-TA, and 15.0% (95% CI 11.6, 18.3) using IA-24HR. The variances of estimated and true energy intakes were statistically significantly different for all methods (P<0.01), apart from Intake 24 (P=0.1). Differential accuracy in nutrient estimation was present among the methods.
CONCLUSIONS: Under controlled conditions, Intake24, ASA24, and mFR-TA estimated average energy and nutrient intakes with reasonable validity, but intake distributions were estimated accurately by Intake24 only (energy and protein). This study may inform considerations regarding instruments of choice in future population surveillance.
TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry Number ACTRN12621000209897; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381165&isReview=true.

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