Dataset Information

Comparison of the NHANES dietary screener questionnaire to the Automated Self-Administered 24-Hour Recall for Children in the Healthy Communities Study.

ABSTRACT:

Background

A dietary screener questionnaire (DSQ) was used to assess dietary outcomes among children in the Healthy Communities Study (HCS), a study of the relationships between programs and policies to prevent child obesity and child diet, physical activity and weight outcomes.

Methods

To compare dietary intake estimates derived from the DSQ against those from the Automated Self-Administered 24-Hour Recalls for Children (ASA24-Kids) among children, a measurement error model, using structural equation modelling, was utilized to estimate slopes, deattenuated correlation coefficients, and attenuation factors by age and sex, ethnicity, and BMI status.

Participants/setting

A randomly selected sub-sample of HCS participants aged 4-15 years in 130 communities throughout the U.S. who completed the DSQ and up to two ASA24-Kids recalls (n?=?656;13% of HCS participants).

Results

For most nutrient/foods examined, the DSQ yielded larger mean intake estimates than the ASA24-Kids, and agreement between the two measures varied by food/nutrient, age and sex, ethnicity, and BMI category. Deattenuated correlation coefficients of 0.4 or greater were observed for added sugars from SSBs (0.54), fruits and vegetables (0.40), and dairy foods (0.50). Lower deattenuated correlation coefficients were seen for total added sugars (0.37), whole grains (0.34), and fiber (0.34). Attenuation factors were most severe for total added sugars intake among overweight children, and for several other dietary outcomes among children aged 9-11 years.

Conclusions

The DSQ was found to be a tool with acceptable agreement with the ASA24-Kids for measuring multiple dietary outcomes of interest in the HCS, although there may be potential due to measurement error to underestimate results (bias towards the null). In future studies, measurement error modelling and regression calibration may be possible solutions to correct for bias due to measurement error in most food/nutrient intake estimates from the DSQ when used among children.

SUBMITTER: Hewawitharana SC

PROVIDER: S-EPMC6260716 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Comparison of the NHANES dietary screener questionnaire to the Automated Self-Administered 24-Hour Recall for Children in the Healthy Communities Study.

Hewawitharana Sridharshi Chintha SC Thompson Frances Elizabeth FE Loria Catherine M CM Strauss Warren W Nagaraja Jyothi J Ritchie Lorrene L Webb Karen Lucy KL

Nutrition journal 20181127 1

<h4>Background</h4>A dietary screener questionnaire (DSQ) was used to assess dietary outcomes among children in the Healthy Communities Study (HCS), a study of the relationships between programs and policies to prevent child obesity and child diet, physical activity and weight outcomes.<h4>Methods</h4>To compare dietary intake estimates derived from the DSQ against those from the Automated Self-Administered 24-Hour Recalls for Children (ASA24-Kids) among children, a measurement error model, usin ...[more]

PMID: 30482218

Similar Datasets

Project description:BackgroundThe Automated Self-Administered 24-hour Recall (ASA24), a freely available Web-based tool, was developed to enhance the feasibility of collecting high-quality dietary intake data from large samples.ObjectiveThe purpose of this study was to assess the criterion validity of ASA24 through a feeding study in which the true intake for 3 meals was known.DesignTrue intake and plate waste from 3 meals were ascertained for 81 adults by inconspicuously weighing foods and beverages offered at a buffet before and after each participant served him- or herself. Participants were randomly assigned to complete an ASA24 or an interviewer-administered Automated Multiple-Pass Method (AMPM) recall the following day. With the use of linear and Poisson regression analysis, we examined the associations between recall mode and 1) the proportions of items consumed for which a match was reported and that were excluded, 2) the number of intrusions (items reported but not consumed), and 3) differences between energy, nutrient, food group, and portion size estimates based on true and reported intakes.ResultsRespondents completing ASA24 reported 80% of items truly consumed compared with 83% in AMPM (P = 0.07). For both ASA24 and AMPM, additions to or ingredients in multicomponent foods and drinks were more frequently omitted than were main foods or drinks. The number of intrusions was higher in ASA24 (P < 0.01). Little evidence of differences by recall mode was found in the gap between true and reported energy, nutrient, and food group intakes or portion sizes.ConclusionsAlthough the interviewer-administered AMPM performed somewhat better relative to true intakes for matches, exclusions, and intrusions, ASA24 performed well. Given the substantial cost savings that ASA24 offers, it has the potential to make important contributions to research aimed at describing the diets of populations, assessing the effect of interventions on diet, and elucidating diet and health relations. This trial was registered at clinicaltrials.gov as NCT00978406.

Project description:BackgroundAssessment 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.MethodsSixty 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.ResultsParticipants 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 (r = 0.80 P < 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% (r = 0.68 P < 0.01; kappa score = 0.50) while small portions (less than 100 g) were overestimated by 17.1% (r = 0.46 P < 0.01; kappa score = 0.43). A nonsignificant underestimation (-13.9 kcal ± 646.3 kcal; P = 0.83) of energy intake was noted.ConclusionR24W 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.

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: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:Background: Latin American countries show a fast-growing rate of non-communicable diseases (NCDs) and diet is a critical risk factor that must be properly assessed. Automated dietary assessment tools to collect 24-h dietary recalls (24HR) are lacking in Argentina. Objective: This study aimed to develop an open-access automated tool (MAR24) for collecting 24HR using a multiple pass method and a database containing foods and recipes commonly consumed in Argentina. Methods: MAR24 was developed based on data from 1,285 24HR provided by male and female participants aged 18 to 68 years from the six Argentinian geographical regions. The main structure and interface of the tool were designed using Visual Basic for Applications programming language in Excel Microsoft Office 365, integrating the five steps of the United States Department of Agriculture (USDA) Automated Multiple-Pass Method (AMPM) for the application of 24HR in Spanish. The tool underwent alpha testing and expert assessment to address structural and usability issues. Critical feedback and face validation from researchers and experienced dietitians, and repeated testing to collect 24HR were used to adjust and improve the tool. Results: A total of 968 food items and 100 standard Argentinian recipes were added to its database. MAR24 allows the estimation of the nutrient profile of dietary intake. The analytic food composition includes energy and 50 nutrients including water, macronutrients, total dietary fiber, total sugar, 10 minerals, 19 vitamins, eight fatty acids, cholesterol, ethyl alcohol, caffeine, and theobromine. MAR24 includes a user manual and technical manual to guide users to apply changes (e.g., add foods or recipes, or change food designation according to local terms) to fit different research and clinical applications. Conclusions: MAR24 is the first tool that uses the AMPM methodology for 24HR applications in Argentina. The tool may be used in clinical practice and clinical trials for monitoring purposes, and in validation of food frequency questionnaires (FFQ) for nutritional epidemiology studies addressing dietary-associated risk factors for NCDs.

Dataset Information

Comparison of the NHANES dietary screener questionnaire to the Automated Self-Administered 24-Hour Recall for Children in the Healthy Communities Study.

Background

Methods

Participants/setting

Results

Conclusions

Publications

Comparison of the NHANES dietary screener questionnaire to the Automated Self-Administered 24-Hour Recall for Children in the Healthy Communities Study.

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