Assessment of the accuracy of portion size reports using computer-based food photographs aids in the development of an automated self-administered 24-hour recall.
OBJECTIVE
To assess the accuracy of portion-size estimates and participant preferences using various presentations of digital images.


METHODS
Two observational feeding studies were conducted. In both, each participant selected and consumed foods for breakfast and lunch, buffet style, serving themselves portions of nine foods representing five forms (eg, amorphous, pieces). Serving containers were weighed unobtrusively before and after selection as was plate waste. The next day, participants used a computer software program to select photographs representing portion sizes of foods consumed the previous day. Preference information was also collected. In Study 1 (n=29), participants were presented with four different types of images (aerial photographs, angled photographs, images of mounds, and household measures) and two types of screen presentations (simultaneous images vs an empty plate that filled with images of food portions when clicked). In Study 2 (n=20), images were presented in two ways that varied by size (large vs small) and number (4 vs 8).


METHODS
Convenience sample of volunteers of varying background in an office setting.


METHODS
Repeated-measures analysis of variance of absolute differences between actual and reported portions sizes by presentation methods.


RESULTS
Accuracy results were largely not statistically significant, indicating that no one image type was most accurate. Accuracy results indicated the use of eight vs four images was more accurate. Strong participant preferences supported presenting simultaneous vs sequential images.


CONCLUSIONS
These findings support the use of aerial photographs in the automated self-administered 24-hour recall. For some food forms, images of mounds or household measures are as accurate as images of food and, therefore, are a cost-effective alternative to photographs of foods.
Subar
Amy F
AF
National Cancer Institute, Division of Cancer Control and Population Sciences, Applied Research Program, Risk Factor Monitoring and Methods Branch, Bethesda, MD 20892-7344, USA. subara@mail.nih.gov
Crafts
Jennifer
J
Zimmerman
Thea Palmer
TP
Wilson
Michael
M
Mittl
Beth
B
Islam
Noemi G
NG
McNutt
Suzanne
S
Potischman
Nancy
N
Buday
Richard
R
Hull
Stephen G
SG
Baranowski
Tom
T
Guenther
Patricia M
PM
Willis
Gordon
G
Tapia
Ramsey
R
Thompson
Frances E
FE
D000293:Adolescent; D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D004034:Diet Surveys; D004522:Educational Status; D002149:Energy Intake / Q000502:physiology; D005260:Female; D005502:Food / Q000145:classification* / Q000592:standards; D005518:Food Preferences; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods / Q000592:standards*; D008297:Male; D011939:Mental Recall; D008875:Middle Aged; D015596:Nutrition Assessment; D010781:Photography / Q000592:standards; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012858:Size Perception; D055815:Young Adult