# Table 4 Beta co-efficients and their significance in all regression analyses, predicting subsequent FV consumption, fruit consumption and vegetable consumption (N = 194)

Model 1 Model 2 Model 3 Model 4
Predictors Beta value, significance Predictors Beta value, significance Predictor Beta value, significance Predictors Beta value, significance
Subsequent FV consumption
Labela β = − 0.15, p = 0.04 Labela β = − 0.10, p = 0.09 Labela x usual FV consumption β = 0.34, p < 0.01 Labela x Genderb β = − 0.17, p < 0.01
Usual FV consumption β = 0.56, p < 0.01 Genderb β = − 0.23, p < 0.01 Usual FV consumption β = 0.57, p < 0.01
Genderb β = − 0.18, p < 0.01
Subsequent fruit consumption
Labela β = − 0.10, p = 0.18 Labela β = − 0.06, p = 0.38 Labela x usual FV consumption β = 0.28, p < 0.01 Labela x Genderb β = − 0.14, p = 0.03
Usual FV consumption β = 0.45, p < 0.01 Genderb β = − 0.22, p < 0.01 Usual FV consumption β = 0.46, p < 0.01
Genderb β = − 0.19, p < 0.01
Subsequent vegetable consumption
Labela β = − 0.19, p = 0.01 Labela β = − 0.14, p = 0.02 Labela x usual FV consumption β = 0.34, p < 0.01 Labela x Genderb β = − 0.21, p < 0.01
Usual FV consumption β = 0.53, p < 0.01 Genderb β = − 0.21, p < 0.01 Usual FV consumption β = 0.54, p < 0.01
Genderb β = − 0.16, p = 0.01
1. aLabel variable – ‘1 of your 5-a-day’ label vs ‘3 of your 5-a-day’ label, coded 1 and 3 respectively
2. bGender variable – female vs male, coded 1 and 2 respectively