The Use of Digital Images in 24-Hour Recalls May Lead to Less Misestimation of Portion Size Compared with Traditional Interviewer-Administered Recalls.
BACKGROUND
The Automated Self-Administered 24-hour (ASA24) dietary recall system enhances the feasibility of collecting high-quality intake data in population-based studies.


OBJECTIVE
The aim of this study was to assess the accuracy of portion size reporting in the ASA24 compared with interviewer-administered recalls.


METHODS
True intake for 3 meals was ascertained in 81 adults aged 20-70 y from the Washington, DC area. Participants were randomly assigned to complete an unannounced ASA24 or an interviewer-administered Automated Multiple-Pass Method (AMPM) recall the following day. An adapted Bland-Altman approach was used to assess agreement between true and reported portion sizes. Linear regression was used to assess log-scale differences between true and reported portion sizes by recall mode. The proportions of reported portion sizes within 10% and 25% of truth were estimated. Analyses were conducted for all foods and drinks and predetermined categories.


RESULTS
Mean differences between true and reported portion sizes were 3.7 g for the ASA24 and 11.8 g for the AMPM. According to the Bland-Altman-type plots, between 92% and 100% (depending on food or drink category and recall mode) of observations fell within the limits of agreement. After adjustment for multiple testing, the mean ratio of reported to true portion sizes was significantly >1 for the categories of all foods and drinks, all foods excluding liquids, amorphous or soft foods, and small pieces among AMPM respondents. Misestimation in the AMPM was significantly different from that in the ASA24 for all foods and drinks and for all foods excluding liquids. Small proportions of reported portions fell within 10% (16.2% for the ASA24 and 14.9% for the AMPM) and 25% (37.5% for the ASA24 and 33.2% for the AMPM) of truth.


CONCLUSIONS
The results raise the possibility that digital images tailored to different types and formats of foods may facilitate improved estimation of amounts eaten but highlight the need for continued work in this aspect of dietary assessment. This trial was registered at clinicaltrials.gov as NCT00978406.
School of Public Health and Health Systems, University of Waterloo, Waterloo, Canada; sharon.kirkpatrick@uwaterloo.ca.
Sharon I
http://orcid.org/0000-0001-9896-5975
SI
Kirkpatrick
Office of Dietary Supplements and.
Nancy
N
Potischman
Division of Cancer Prevention and.
Kevin W
KW
Dodd
Westat, Rockville, MD; and.
Deirdre
D
Douglass
Westat, Rockville, MD; and.
Thea P
TP
Zimmerman
Information Management Services, Inc., Rockville, MD.
Lisa L
LL
Kahle
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD.
Frances E
FE
Thompson
Office of Disease Prevention, NIH, Bethesda, MD.
Stephanie M
SM
George
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD.
Amy F
AF
Subar
D000328:Adult; D000368:Aged; D004032:Diet / Q000706:statistics & numerical data; D015930:Diet Records; D004034:Diet Surveys / Q000379:methods*; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D008297:Male; D062407:Meals; D011939:Mental Recall; D008875:Middle Aged; D015596:Nutrition Assessment; D057566:Self Report; D055815:Young Adult
24-hour recall; Automated Multiple-Pass Method; Automated Self-Administered 24-hour dietary assessment tool; dietary intake; portion size