Saha Sanjoy, Lozano Chloe Panizza, Broyles Stephanie, Martin Corby K, Apolzan John W
Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States.
JMIR Form Res. 2022 Jun 15;6(6):e38283. doi: 10.2196/38283.
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.
This study aimed to assess the preliminary feasibility and validity of estimating food intake via the PortionSize app among adults.
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.
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).
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.
准确评估饮食摄入量有助于改善营养状况。“份量大小”应用程序(彭宁顿生物医学研究中心)旨在对能量、食物类别、饱和脂肪和添加糖的摄入量进行量化并提供实时反馈。
本研究旨在评估成年人通过“份量大小”应用程序估计食物摄入量的初步可行性和有效性。
共招募了15名成年人(年龄在18 - 65岁之间),并对他们进行培训,使其使用“份量大小”应用程序对模拟餐食的食物摄入量进行量化。训练有素的人员准备了15份模拟餐食,并秘密称量(回称)提供给参与者的食物量以及食物残渣量。进行等效性测试(±25%界限)以将“份量大小”应用程序与回称法进行比较。
参与者的平均年龄为28(标准差12)岁,其中11名是女性。用“份量大小”应用程序估计的平均能量摄入量为742.9(标准差328.2)千卡,通过回称法估计的为659.3(标准差190.7)千卡(能量摄入量差异:平均83.5,标准差287.5千卡)。在估计能量摄入量方面,两种方法不等效(P = 0.18),在餐食层面,“份量大小”应用程序高估能量摄入量83.5千卡(12.7%)。“份量大小”应用程序对份量大小(克重;P = 0.01)、总糖(P = 0.049)、水果份数(P = 0.01)和乳制品份数(P = 0.047)的估计与通过回称法估计的结果等效。在碳水化合物(P = 0.10)、脂肪(P = 0.32)、蔬菜(P = 0.37)、谷物(P = 0.31)和蛋白质份数(P = 0.87)的估计方面,“份量大小”应用程序与回称法不等效。
由于样本量限制,等效性测试的等效界限较大。尽管是初步研究,但这项小型试点研究的结果值得对“份量大小”应用程序进行进一步调整、开发和验证,使其成为估计能量摄入量并为用户提供实时且可行的饮食反馈的一种手段。