Dataset Information

Automated Self-Administered 24-H Dietary Assessment Tool (ASA24) recalls for parent proxy-reporting of children's intake (> 4 years of age): a feasibility study.

ABSTRACT:

Background

Robust measurement of dietary intake in population studies of children is critical to better understand the diet-health nexus. It is unknown whether parent proxy-report of children's dietary intake through online 24-h recalls is feasible in large cohort studies.

Objectives

The primary objective of this study was to describe the feasibility of the Automated Self-Administered 24-h Dietary Assessment Tool (ASA24) to measure parent proxy-reported child dietary intake. A secondary objective was to compare intake estimates with those from national surveillance.

Methods

Parents of children aged 4-15 years participating in the TARGet Kids! research network in Toronto, Canada were invited by email to complete an online ASA24-Canada-2016 recall for their child, with a subsample prompted to complete a second recall about 2 weeks later. Descriptive statistics were reported for ASA24 completion characteristics and intake of several nutrients. Comparisons were made to the 2015 Canadian Community Health Survey (CCHS) 24-h recall data.

Results

A total of 163 parents completed the first recall, and 46 completed the second, reflecting response rates of 35% and 59%, respectively. Seven (4%) first recalls and one (2%) second recall were excluded for ineligibility, missing data, or inadvertent parental self-report. The median number of foods reported on the first recall was 18.0 (interquartile range (IQR) 6.0) and median time to complete was 29.5 min (IQR 17.0). Nutrient intakes for energy, total fat, protein, carbohydrates, fiber, sodium, total sugars, and added sugars were similar across the two recalls and the CCHS.

Conclusions

The ASA24 was found to be feasible for parent proxy-reporting of children's intake and to yield intake estimates comparable to those from national surveillance, but strategies are needed to increase response rate and support completion to enhance generalizability.

SUBMITTER: Sharpe I

PROVIDER: S-EPMC8194205 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAutomated dietary assessment tools such as ASA24® are useful for collecting 24-hour recall data in large-scale studies. Modifications made during manual data cleaning may affect nutrient intakes.ObjectivesWe evaluated the effects of modifications made during manual data cleaning on nutrient intakes of interest: energy, carbohydrate, total fat, protein, and fiber.MethodsDifferences in mean intake before and after data cleaning modifications for all recalls and average intakes per subject were analyzed by paired t-tests. The Chi-squared test was used to determine whether unsupervised recalls had more open-ended text responses that required modification than supervised recalls. We characterized food types of text response modifications. Correlations between predictive energy requirements, measured total energy expenditure (TEE), and mean energy intake from raw and modified data were examined.ResultsAfter excluding 11 recalls with invalidating technical errors, 1499 valid recalls completed by 393 subjects were included in this analysis. We found significant differences before and after modifications for energy, carbohydrate, total fat, and protein intakes for all recalls (P < 0.05). Limiting to modified recalls, there were significant differences for all nutrients of interest, including fiber (P < 0.02). There was not a significantly greater proportion of text responses requiring modification for home compared with supervised recalls (P = 0.271). Predicted energy requirements correlated highly with TEE. There was no significant difference in correlation of mean energy intake with TEE for modified compared with raw data. Mean intake for individual subjects was significantly different for energy, protein, and fat intakes following cleaning modifications (P < 0.001).ConclusionsManual modifications can change mean nutrient intakes for an entire cohort and individuals. However, modifications did not significantly affect the correlation of energy intake with predictive requirements and measured expenditure. Investigators can consider their research question and nutrients of interest when deciding to make cleaning modifications.

Project description:BackgroundTechnological innovations allow for collection of 24-h recalls (24HRs) in a broader range of studies than previously possible. The web-based Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) has been shown to be feasible and to perform well in capturing true intake among adults. However, data to inform use with children are limited.ObjectiveThis observational feeding study was conducted to evaluate children's ability to accurately report a lunchtime meal using ASA24 without assistance.MethodsThe study was conducted among children (n = 100) aged 10-13 y within a school setting. Students were served an individual cheese pizza, baby carrots, ranch dip, yogurt, a cookie, and 1 choice of water, juice, or milk. Plate waste was collected and weighed. The next day, participants completed ASA24 and a sociodemographic questionnaire. Descriptive statistics were generated to determine match rates by food item and age, and linear regression analyses were conducted to examine associations between sociodemographic characteristics and accuracy of reported energy and nutrient intake. Associations between true and reported energy and nutrient intakes and portion sizes were assessed with use of t tests.ResultsJust under half (49%) of children fully completed ASA24 (median time, 41 min). Children reported an exact, close, or far match for 58% of all foods and beverages consumed, ranging from 29% for dip to 76% for pizza, but also reported some items not consumed as part of the study meal. Older children completed the recall in a shorter time than younger children (mean 31 among 13 y compared with 52 min among 10 y). Intakes of energy (39%), protein (33%), and sodium (78%) were significantly overestimated, whereas portion sizes for cookies (53%) and juice (69%) were underestimated.ConclusionsChildren can report some foods and drinks consumed using ASA24, but our findings suggest challenges with independent completion, necessitating research to examine strategies, such as training and resources, to support data quality.

Project description:BackgroundThe Automated Self-Administered 24-hour (ASA24) dietary recall system enhances the feasibility of collecting high-quality intake data in population-based studies.ObjectiveThe aim of this study was to assess the accuracy of portion size reporting in the ASA24 compared with interviewer-administered recalls.MethodsTrue intake for 3 meals was ascertained in 81 adults aged 20-70 y from the Washington, DC area. Participants were randomly assigned to complete an unannounced ASA24 or an interviewer-administered Automated Multiple-Pass Method (AMPM) recall the following day. An adapted Bland-Altman approach was used to assess agreement between true and reported portion sizes. Linear regression was used to assess log-scale differences between true and reported portion sizes by recall mode. The proportions of reported portion sizes within 10% and 25% of truth were estimated. Analyses were conducted for all foods and drinks and predetermined categories.ResultsMean differences between true and reported portion sizes were 3.7 g for the ASA24 and 11.8 g for the AMPM. According to the Bland-Altman-type plots, between 92% and 100% (depending on food or drink category and recall mode) of observations fell within the limits of agreement. After adjustment for multiple testing, the mean ratio of reported to true portion sizes was significantly >1 for the categories of all foods and drinks, all foods excluding liquids, amorphous or soft foods, and small pieces among AMPM respondents. Misestimation in the AMPM was significantly different from that in the ASA24 for all foods and drinks and for all foods excluding liquids. Small proportions of reported portions fell within 10% (16.2% for the ASA24 and 14.9% for the AMPM) and 25% (37.5% for the ASA24 and 33.2% for the AMPM) of truth.ConclusionsThe results raise the possibility that digital images tailored to different types and formats of foods may facilitate improved estimation of amounts eaten but highlight the need for continued work in this aspect of dietary assessment. This trial was registered at clinicaltrials.gov as NCT00978406.

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Project description:Validation-study data were analysed to investigate retention interval (RI) and prompt effects on the accuracy of fourth-grade children's reports of school-breakfast and school-lunch (in 24-h recalls), and the accuracy of school-breakfast reports by breakfast location (classroom; cafeteria). Randomly selected fourth-grade children at ten schools in four districts were observed eating school-provided breakfast and lunch, and were interviewed under one of eight conditions created by crossing two RIs ('short'--prior-24-hour recall obtained in the afternoon and 'long'--previous-day recall obtained in the morning) with four prompts ('forward'--distant to recent, 'meal name'--breakfast, etc., 'open'--no instructions, and 'reverse'--recent to distant). Each condition had sixty children (half were girls). Of 480 children, 355 and 409 reported meals satisfying criteria for reports of school-breakfast and school-lunch, respectively. For breakfast and lunch separately, a conventional measure--report rate--and reporting-error-sensitive measures--correspondence rate and inflation ratio--were calculated for energy per meal-reporting child. Correspondence rate and inflation ratio--but not report rate--showed better accuracy for school-breakfast and school-lunch reports with the short RI than with the long RI; this pattern was not found for some prompts for each sex. Correspondence rate and inflation ratio showed better school-breakfast report accuracy for the classroom than for cafeteria location for each prompt, but report rate showed the opposite. For each RI, correspondence rate and inflation ratio showed better accuracy for lunch than for breakfast, but report rate showed the opposite. When choosing RI and prompts for recalls, researchers and practitioners should select a short RI to maximise accuracy. Recommendations for prompt selections are less clear. As report rates distort validation-study accuracy conclusions, reporting-error-sensitive measures are recommended.

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