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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
Published on: September 18, 2018
A new mobile phone-based tool for assessing energy and certain food intakes in young children: a validation study
Hanna Henriksson1, Stephanie E Bonn, Anna Bergström
1Linköping University, Department of Clinical and Experimental Medicine, Linköping, Sweden.
Insights
The Tool for Energy Balance in Children (TECH) mobile app did not accurately estimate energy or food intake in 3-year-olds. One day of data collection with TECH was insufficient for precise childhood obesity research measurements.
Area of Science:
- Pediatric Nutrition
- Obesity Research
- Mobile Health Technology
Background:
- Childhood obesity is a growing global concern, with potential onset in preschool years.
- Accurate dietary assessment tools are crucial for research but traditional methods are burdensome.
- Mobile phones offer a promising platform for developing new, user-friendly dietary assessment tools.
Purpose of the Study:
- To validate the Tool for Energy Balance in Children (TECH) against criterion methods for energy and food intake.
- To compare TECH's energy intake assessment with total energy expenditure (TEE) using doubly labeled water (DLW).
- To compare TECH's assessment of fruit, vegetable, juice, and sweetened beverage intake with a web-based food frequency questionnaire (KidMeal-Q) in 3-year-olds.
Main Methods:
- Thirty 3-year-old Swedish children participated in the study.
- Energy intake was measured using TECH and compared to TEE derived from the DLW method.
- Intakes of specific food groups (vegetables, fruits, berries, juice, sweetened beverages) were assessed by TECH and KidMeal-Q.
- Statistical analyses included Wilcoxon matched pairs test, Spearman correlations, and Bland-Altman procedures.
Main Results:
- TECH's mean energy intake (5400 kJ/24h) did not significantly differ from TEE (5070 kJ/24h), but Bland-Altman analysis showed wide limits of agreement.
- TECH demonstrated a tendency to overestimate high and underestimate low energy intakes.
- No significant differences were found between TECH and KidMeal-Q for mean intakes of the assessed food groups.
- Moderate correlations were observed between TECH and KidMeal-Q for vegetables, fruits/berries, and juice, but not for sweetened beverages.
Conclusions:
- A single day of data collection using the TECH tool is insufficient for accurately estimating energy and specific food intakes in 3-year-old children.
- Further refinement of the TECH tool is needed to improve its accuracy for childhood dietary assessment.
- TECH shows potential but requires validation over longer periods or with modified protocols for reliable use in childhood obesity research.
Background:
Childhood obesity is an increasing health problem globally. Obesity may be established already at pre-school age. Further research in this area requires accurate and easy-to-use methods for assessing the intake of energy and foods. Traditional methods have limited accuracy, and place large demands on the study participants and researchers. Mobile phones offer possibilities for methodological advancements in this area since they are readily available, enable instant digitalization of collected data, and also contain a camera to photograph pre- and post-meal food items. We have recently developed a new tool for assessing energy and food intake in children using mobile phones called the Tool for Energy Balance in Children (TECH).
Objective:
The main aims of our study are to (1) compare energy intake by means of TECH with total energy expenditure (TEE) measured using a criterion method, the doubly labeled water (DLW) method, and (2) to compare intakes of fruits and berries, vegetables, juice, and sweetened beverages assessed by means of TECH with intakes obtained using a Web-based food frequency questionnaire (KidMeal-Q) in 3 year olds.
Methods:
In this study, 30 Swedish 3 year olds were included. Energy intake using TECH was compared to TEE measured using the DLW method. Intakes of vegetables, fruits and berries, juice, as well as sweetened beverages were assessed using TECH and compared to the corresponding intakes assessed using KidMeal-Q. Wilcoxon matched pairs test, Spearman rank order correlations, and the Bland-Altman procedure were applied.
Results:
The mean energy intake, assessed by TECH, was 5400 kJ/24h (SD 1500). This value was not significantly different (P=.23) from TEE (5070 kJ/24h, SD 600). However, the limits of agreement (2 standard deviations) in the Bland-Altman plot for energy intake estimated using TECH compared to TEE were wide (2990 kJ/24h), and TECH overestimated high and underestimated low energy intakes. The Bland-Altman plots for foods showed similar patterns. The mean intakes of vegetables, fruits and berries, juice, and sweetened beverages estimated using TECH were not significantly different from the corresponding intakes estimated using KidMeal-Q. Moderate but statistically significant correlations (ρ=.42-.46, P=.01-.02) between TECH and KidMeal-Q were observed for intakes of vegetables, fruits and berries, and juice, but not for sweetened beverages.
Conclusion:
We found that one day of recordings using TECH was not able to accurately estimate intakes of energy or certain foods in 3 year old children.
