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Validation of a Newly Automated Web-based 24-hour Dietary Recall Using Fully Controlled Feeding Studies

Overview
Journal BMC Nutr
Publisher Biomed Central
Date 2020 Mar 11
PMID 32153814
Citations 45
Authors
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Abstract

Background: Assessment of food intake is a cornerstone of nutritional research. However, the use of minimally validated dietary assessment methods is common and can generate misleading results. Thus, there is a need for valid, precise and cost-effective dietary assessment tools to be used in large cohort studies.The objective is to validate a newly developed automated self-administered web-based 24-h dietary recall (R24W), within a population of adults taking part in fully controlled feeding studies.

Methods: Sixty two adults completed the R24W twice while being fed by our research team. Actual intakes were precisely known, thereby allowing the analysis of the proportion of adequately self-reported items. Association between offered and reported portion sizes was assessed with correlation coefficients and agreement with the kappa score while systematics biases were illustrated with Bland-Altman Plot.

Results: Participants received an average of 16 food items per testing day. They reported 89.3% of the items they received. The more frequently omitted food categories were vegetables included in recipes (40.0%) as well as side vegetables (20.0%) and represented less than 5% of the actual daily energy intake. Offered and self-reported portion sizes were significantly correlated ( = 0.80  < 0.001) and demonstrated a strong agreement as assessed by the kappa score of 0.62. Reported portion sizes for individual food items were on average 3.2 g over the offered portion sizes. Portions of 100 g and above were on average underestimated by 2.4% ( = 0.68  < 0.01; kappa score = 0.50) while small portions (less than 100 g) were overestimated by 17.1% ( = 0.46  < 0.01; kappa score = 0.43). A nonsignificant underestimation (-13.9 kcal ± 646.3 kcal;  = 0.83) of energy intake was noted.

Conclusion: R24W performed well as participants were able to report the great majority of items they ate and selected portion size strongly related to the one they received. This suggests that food items are easily to find within the R24W and images of portion sizes used in this dietary assessment tool are adequate and can provide valid food intake evaluation.

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References
1.
Archer E, Hand G, Blair S . Validity of U.S. nutritional surveillance:National Health and Nutrition Examination Survey caloric energy intake data, 1971-2010. PLoS One. 2013; 8(10):e76632. PMC: 3793920. DOI: 10.1371/journal.pone.0076632. View

2.
Hebert J, Ebbeling C, Matthews C, Hurley T, Ma Y, Druker S . Systematic errors in middle-aged women's estimates of energy intake: comparing three self-report measures to total energy expenditure from doubly labeled water. Ann Epidemiol. 2002; 12(8):577-86. DOI: 10.1016/s1047-2797(01)00297-6. View

3.
Thompson F, Dixit-Joshi S, Potischman N, Dodd K, Kirkpatrick S, Kushi L . Comparison of Interviewer-Administered and Automated Self-Administered 24-Hour Dietary Recalls in 3 Diverse Integrated Health Systems. Am J Epidemiol. 2015; 181(12):970-8. PMC: 4462333. DOI: 10.1093/aje/kwu467. View

4.
Masson L, McNeill G, Tomany J, Simpson J, Peace H, Wei L . Statistical approaches for assessing the relative validity of a food-frequency questionnaire: use of correlation coefficients and the kappa statistic. Public Health Nutr. 2003; 6(3):313-21. DOI: 10.1079/PHN2002429. View

5.
Illner A, Freisling H, Boeing H, Huybrechts I, Crispim S, Slimani N . Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. Int J Epidemiol. 2012; 41(4):1187-203. DOI: 10.1093/ije/dys105. View