# Table 4 Regression analyses predicting mothers' a) actual frequency and b) recommended frequency of behaviour for 'Providing breakfast', 'Cooking from Scratch' and 'Having a proper 'sit-down' meal'

Breakfast 1 B SE B Β 95% CI for B p =
a) Actual frequency (log)
INT -.04 .01 -.32 -.06 to -.03 .0001
PBC-C -.11 .02 -.35 -.15 to -.07 .0001
PBC-SE .14 .03 .36 .09 to .19 .0001
Model Adj R2 = .19, F(3,296) = 23.65, p < 0.0001
b) Recommended frequency
INT .39 .03 .68 .34 to .45 .0001
PBC-C .12 .07 .09 -.01 to .26 .07
PBC- SE -.04 .09 -.02 -.21 to .13 .65
Model Adj R2 = .49, F(3,296) = 96.30, p < 0.0001
Cooking from scratch
a) Actual frequency
B SE B Β 95% CI for B p =
INT .93 .04 .76 .85 to 1.03 .0001
PBC-C .02 .09 .01 -.15 to .20 .83
PBC-SE .27 .08 -.13 .11 to .43 0.001
Model Adj R2 = .66, F(3,296) = 193.63, p < 0.0001
b) Recommended frequency
Int .37 .03 .55 .31 to .43 .0001
PBC-C -.05 .06 -.04 -.17 to .07 .41
PBC- SE .30 .06 .27 .31 to .43 .0001
Model Adj R2 = .44, F(3,296) = 78.2, p < 0.0001
Sit down meal B SE B Β 95% CI for B p =
a) Actual frequency
INT 1.03 .06 .76 .92 to 1.15 .0001
PBC-C -.05 .16 .02 -.28 to -.18 .64
PBC-SE .20 .14 .07 .07 to .47 .15
Model Adj R2 = .62, F(3,296) = 161.5, p > 0.0001
b) Recommended frequency
Int .44 .02 .73 .40 to .48 .0001
PBC-C .01 .04 .01 -.07 to .09 .81
PBC- SE .27 .05 .20 .17 to .37 .0001
Model Adj R2 = .74, F(3,296) = 283.4, p > 0.0001
1. 1Transformation (log) reduced overall skewness in the 'breakfast' actual frequency variable, but since the transformed variable remained skewed we also dichotomised this into 2 categories, 'every day' and 'less than every day', and carried out a logistic regression using the same predictors as a check. The model was significant, Chi Square = 45.71, p < 0.0001; Nagelkerke R2 = .22, with all predictors being highly significant using the Wald test (all p < 0.0001).