Evaluation of a Web-Based Food Record for Children Using Direct Unobtrusive Lunch Observations: A Validation Study

BACKGROUND: High-quality, Web-based dietary assessment tools for children are needed to reduce cost and improve user-friendliness when studying children’s dietary practices. OBJECTIVE: To evaluate the first Web-based dietary assessment tool for children in Norway, the Web-based Food Record (WebFR), by comparing children’s true school lunch intake with recordings in the WebFR, using direct unobtrusive observation as the reference method. METHODS: A total of 117 children, 8-9 years, from Bærum, Norway, were recruited from September to December 2013. Children completed 4 days of recordings in the WebFR, with parental assistance, and were observed during school lunch in the same period by 3 observers. Interobserver reliability assessments were satisfactory. Match, omission, and intrusion rates were calculated to assess the quality of the recordings in the WebFR for different food categories, and for all foods combined. Logistic regression analyses were used to investigate whether body mass index (BMI), parental educational level, parental ethnicity or family structure were associated with having a “low match rate” (≤70%). RESULTS: Bread and milk were recorded with less bias than spreads, fruits, and vegetables. Mean (SD) for match, omission, and intrusion rates for all foods combined were 73% (27%), 27% (27%), and 19% (26%), respectively. Match rates were statistically significantly associated with parental educational level (low education 52% [32%] versus high 77% [24%], P=.008) and parental ethnicity (non-Norwegian 57% [28%] versus others 75% [26%], P=.04). Only parental ethnicity remained statistically significant in the logistic regression model, showing an adjusted odds ratio of 6.9 and a 95% confidence interval between 1.3 and 36.4. CONCLUSIONS: Compared with other similar studies, our results indicate that the WebFR is in line with, or better than most of other similar tools, yet enhancements could further improve the WebFR.