Primary analyses
REGRESSIONS
Primary outcomes for this study were size choice (medium or large), hypothetical kcals ordered, and hypothetical money spent from each outlet. For each outlet, binary logistic regressions were used to examine the association between calorie labelling condition (present/absent) and pricing condition (proportional/value) as predictors of product size choice. Body Mass Index (BMI), highest level of education (university educated or less than university educated), the five food choice motives, age, gender (male/non-male) and ethnicity (white/non-white) were included as covariates. Multiple linear regressions with robust standard errors (and the same predictors as mentioned above) were used to examine associations between pricing condition and calorie labelling condition with total kcals ordered and total money spent. Results for primary analyses were considered significant at p < .05. For all models we examined the impact of including the interaction between labelling condition and pricing condition as a predictor. All interactions were non-significant, so these were removed from the separate models (i.e. size choice, kcals ordered, hypothetical spend) to minimize model overfitting.