Tamara Bucher1, Carmen Keller1. 1. ETH Zürich,Institute of Food,Nutrition and Health (IFNH),Universitätstrasse 16,8092 Zurich,Switzerland.
Abstract
OBJECTIVE: To date, no data exist on the agreement of food choice measured using an online tool with subsequent actual consumption. This needs to be shown before food choice, measured by means of an online tool, is used as a dependent variable to examine intake in the general population. DESIGN: A 'web-buffet' was developed to assess food choice. SETTING: Choice was measured as planned meal composition from photographic material; respondents chose preferred foods and proportions for a main meal (out of a possible 144 combinations) online and the validity was assessed by comparison of a meal composed from a web-buffet with actual food intake 24-48 h later. Furthermore, correlations of food preferences, energy needs and health interest with meals chosen from the web-buffet were analysed. SUBJECTS: Students: n 106 (Study I), n 32 (Study II). RESULTS: Meals chosen from the web-buffet (mean = 2998 kJ, SD = 471 kJ) agreed with actual consumption (rs = 0.63, P < 0.001) but were on average 367 kJ (10.5%) lower in energy than consumed meals (mean = 3480 kJ, SD = 755 kJ). Preferences were highly associated with chosen amounts and health interest was negatively correlated with the energy selected (rs = -0.40, P<0.001). CONCLUSIONS: Meal composition choice in the web-buffet agrees sufficiently well with actual intake to measure food choice as a dependent variable in online surveys. However, we found an average underestimation of subsequent consumption. High correlations of preferences with chosen amounts and an inverse association of health interest with total energy further indicate the validity of the tool. Applications in behavioural nutrition research are discussed.
OBJECTIVE: To date, no data exist on the agreement of food choice measured using an online tool with subsequent actual consumption. This needs to be shown before food choice, measured by means of an online tool, is used as a dependent variable to examine intake in the general population. DESIGN: A 'web-buffet' was developed to assess food choice. SETTING: Choice was measured as planned meal composition from photographic material; respondents chose preferred foods and proportions for a main meal (out of a possible 144 combinations) online and the validity was assessed by comparison of a meal composed from a web-buffet with actual food intake 24-48 h later. Furthermore, correlations of food preferences, energy needs and health interest with meals chosen from the web-buffet were analysed. SUBJECTS: Students: n 106 (Study I), n 32 (Study II). RESULTS: Meals chosen from the web-buffet (mean = 2998 kJ, SD = 471 kJ) agreed with actual consumption (rs = 0.63, P < 0.001) but were on average 367 kJ (10.5%) lower in energy than consumed meals (mean = 3480 kJ, SD = 755 kJ). Preferences were highly associated with chosen amounts and health interest was negatively correlated with the energy selected (rs = -0.40, P<0.001). CONCLUSIONS: Meal composition choice in the web-buffet agrees sufficiently well with actual intake to measure food choice as a dependent variable in online surveys. However, we found an average underestimation of subsequent consumption. High correlations of preferences with chosen amounts and an inverse association of health interest with total energy further indicate the validity of the tool. Applications in behavioural nutrition research are discussed.