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Table 3 Results of correlated component regression analyses for healthy dietary intake outcome measures

From: Describing socioeconomic gradients in children’s diets – does the socioeconomic indicator used matter?

   BOYS (n = 275)      GIRLS (n = 353)  
Variable CV predictor counta β Model goodness of fit indicesb Variable CV predictor counta β Model goodness of fit indicesb
Fruit intake (8 predictors)    Fruit intake (8 predictors)   
 SEIFA* 100 0.138 R2 = 0.052  Employment* 100 −0.122 R2 = 0.014
 Mother’s education* 100 0.128 R2(CV) = 0.011  Child age* 89 −0.063 R2(CV) = 0.012
 Employment* 96 −0.087 SD (CV) = 0.004  Mother’s occupation* 89 −0.063 SD (CV) = 0.009
 Mother’s occupation* 92 0.067    Marital status* 82 0.033  
 Marital status* 82 0.044    Mother’s education* 77 −0.010  
 Mother’s age* 79 −0.040    Mother’s age* 71 −0.013  
 Child age* 64 −0.035    SEIFA* 71 −0.002  
 Income* 47 0.024    Income* 71 −0.006  
Vegetable intake (1 predictor)    Vegetable intake (1 predictor)   
 Mother’s education* 90 0.120 R2 = 0.015  Employment* 83 −0.099 R2 = 0.010
 SEIFA 67   R2(CV) = 0.007  Mother’s education 74   R2(CV) = 0.005
 Employment 42   SD (CV) = 0.009  Mother’s occupation 10   SD (CV) = 0.003
 Mother’s age 39     SEIFA 9   
 Child age 22     Income 8   
 Income 17     Mother’s age 7   
 Mother’s occupation 2     Child age 5   
 Marital status 1     Marital status 4   
Healthy behavioursC (4 predictors)   Healthy behavioursC (1 predictors)   
 Employment* 100 −0.116 R2 = 0.036  Marital status* 54 0.077 R2 = 0.006
 Marital status* 59 0.076 R2(CV) = 0.008  SEIFA 31   R2(CV) = 0.022
 Mother’s occupation* 57 0.082 SD (CV) = 0.004  Child age 16   SD (CV) = 0.013
 Mother’s education* 48 0.062    Mother’s age 12   
 Income 12     Mother’s occupation 10   
 SEIFA 3     Income 3   
 Mother’s age 1     Employment 3   
 Child age^ --     Mother’s education 1   
  1. *Predictor retained in final model.
  2. ^Predictor not retained in any model.
  3. ß = standardised regression coefficient.
  4. aCross-validation predictor count - Represents number of regressions in which predictor appeared. Predictor count of 100 indicates that predictor was present in all 100 regressions. Indicates importance of predictor together with standardised regression coefficient (β).
  5. bModel goodness of fit indices: R2(CV) = cross-validated R2; SD (CV) = Standard deviation for cross-validated R2.
  6. cHealthy behaviours: Breakfast intake, carrying water bottle, help parents with groceries, help to prepare dinner, eat dinner with the family.