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

^aLabel variable – ‘1 of your 5-a-day’ label vs ‘3 of your 5-a-day’ label, coded 1 and 3 respectively

^bGender variable – female vs male, coded 1 and 2 respectively