Background Accurately assessing dietary intake can promote improved nutrition. The PortionSize app (Pennington Biomedical Research Center) was designed to quantify and provide real-time feedback on the intake of energy, food groups, saturated fat, and added sugar. Objective This study aimed to assess the preliminary feasibility and validity of estimating food intake via the PortionSize app among adults. Methods A total of 15 adults (aged 18-65 years) were recruited and trained to quantify the food intake from a simulated meal by using PortionSize. Trained personnel prepared 15 simulated meals and covertly weighed (weigh back) the amount of food provided to participants as well as food waste. Equivalence tests (±25% bounds) were performed to compare PortionSize to the weigh back method. Results Participants were aged a mean of 28 (SD 12) years, and 11 were female. The mean energy intake estimated with PortionSize was 742.9 (SD 328.2) kcal, and that estimated via weigh back was 659.3 (SD 190.7) kcal (energy intake difference: mean 83.5, SD 287.5 kcal). The methods were not equivalent in estimating energy intake (P=.18), and PortionSize overestimated energy intake by 83.5 kcal (12.7%) at the meal level. Estimates of portion sizes (gram weight; P=.01), total sugar (P=.049), fruit servings (P=.01), and dairy servings (P=.047) from PortionSize were equivalent to those estimated via weigh back. PortionSize was not equivalent to weigh back with regard to estimates for carbohydrate (P=.10), fat (P=.32), vegetable (P=.37), grain (P=.31), and protein servings (P=.87). Conclusions Due to power limitations, the equivalence tests had large equivalence bounds. Though preliminary, the results of this small pilot study warrant the further adaptation, development, and validation of PortionSize as a means to estimate energy intake and provide users with real-time and actionable dietary feedback.
BACKGROUND Accurately assessing dietary intake can promote improved nutrition. The PortionSize© app is designed to quantify and provide real-time feedback on intake of energy, food groups, saturated fat, and added sugar. OBJECTIVE This study assessed the preliminary validity of estimating food intake using the PortionSize app among adults. METHODS Fifteen adults (18-65 years) were recruited and trained to quantify food intake from a simulated meal using PortionSize. Trained personnel prepared 15 simulated meals and covertly weighed (weigh back [WB]) the amount of food provided to participants, as well as food waste. Equivalence tests (+/- 25% bounds) were performed to compare PortionSize to WB. RESULTS Participants were 28 ± 12 years (Mean ± SD) and 73.3% female. Mean energy intake (EI) estimated with PortionSize was 742.9 ± 328.2 kcal and WB was 659.3 ± 190.7 kcal (mean EI difference, 83.5 ± 287.5 kcal). The methods were not equivalent in estimating EI (P = .18), and PortionSize overestimated EI by 83.5 kcal (12.7%) at the meal level. Estimates of portion size (gram weight), total sugar, fruit, and dairy servings with PortionSize were equivalent to WB (all P values < .05). PortionSize was not equivalent to WB for carbohydrate, fat, vegetables, grain, and protein servings (all P values > .05). CONCLUSIONS Due to power limitations, the equivalence tests had large equivalence bounds. Though preliminary, the results of this small pilot study warrant further development and validation of PortionSize as means to estimate EI and provide users with real time and actionable feedback. CLINICALTRIAL Registered at ClinicalTrails.gov (NCT04494971); https://clinicaltrials.gov/ct2/show/NCT04494971
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