Cooking Skills (CS) and Food Skills (FS) Ability
The CS and FS scales proved to have acceptable internal reliability (Cronbach’s alpha reported in Table 2, both > .90) and all items provided an acceptable two-factor structure as expected (cooking skills and food skills components), explaining 73.5 % of the variance.
Males scored significantly lower than females for CS (38.0 ± 27.6 versus 55.4 ± 28.4); older participants scored significantly higher than younger participants (43.5 ± 28.7 versus 52.4 ± 29.3); and those with no formal education or compulsory level education only, scored significantly lower than those with further or higher education (see Table 3).
Overall, the sample mean was 45.8 (SD 38.6) for food skills; males scored significantly lower than females (35.5 ± 35.7 versus 53.8 ± 39.0); older participants scored significantly higher than younger participants (40.9 ± 36.5 versus 51.2 ± 40.2); and again, those with no formal education or compulsory level education only scored significantly lower on food skills ability (Table 3).
Sample by ECI and DINE Classifications
Table 1 displays descriptive information for the sample broken down into low, medium and high scoring ECI tertiles, and DINE Fat and Fibre high, medium and low classifications. Older participants were significantly more likely to report healthier ECI scores (T2 and T3) and have a higher fibre intake (DINE), though the pattern was not clear for DINE Fat intake. The same pattern of results was noted for females. They also displayed significantly lower saturated fat scores compared to males. With regard to level of education and ECI scores, those with the lowest education scored poorly on the ECI (falling into T1 and T2 mainly) and were significantly more likely to report low levels of fibre intake. By contrast, those with a university education were significantly more likely to score in the highest ECI tertile (T3, i.e., making the healthiest choices) and have a significantly lower saturated fat intake. With regard to socio-economic grouping, those classified as ABC1 showed a graded pattern of response with few falling into the unhealthiest ECI range (T1) and most falling into T3. The greatest proportion of C2DE respondents (70 %) fell into unhealthier tertiles T1 and T2). The greatest proportion of ABC1 participants scored in the lowest range of saturated fat intake, whereas the greatest proportion of C2DE participants scored high on saturated fat intake. There was no significant difference between the socio-economic groupings in relation to fibre intake.
Those with the greater nutrition knowledge reported significantly healthier food choices as measured by the ECI (p < 0.0001), and those consuming the least amount of saturated fat (DINE) had significantly greater nutrition knowledge (p < 0.0001). Where participants indicated a greater concern for the healthiness of food this was reflected in their dietary intake, as the average score for food and health concern was greatest in the healthiest ECI tertile (T3); lowest in the high saturated fat intake group; and, highest in the high fibre intake group, in line with current dietary recommendations. There was an association between cooking identity and diet quality, with those who saw themselves as good cooks and those with greater food neophilia (openness and interest in food) displaying healthier ECI scores, lower saturated fat and higher fibre scores). Daily meal preparation frequency showed a significant trend towards a healthier dietary profile for ECI scores (p < 0.0001) and DINE-fibre score when cooking on more than just one occasion per day (p < 0.0001). Cooking skills and food skills both showed the same pattern of responses for ECI scores in that those classified into the healthiest ECI tertile reported the greatest cooking and food skills abilities. In addition, those classified as having a high saturated fat intake scored (DINE) significantly lower on both cooking skills and food skills ability.
BMI did not differ significantly across categories of diet quality.
Correspondence between DINE and ECI
Descriptive statistics for the three dietary measures illustrate a clear pattern; DINE Fat intake scores were highest in the lowest (unhealthiest) ECI tertile and reduced significantly as the ECI scores increased (Table 1). The reverse pattern was observed for fibre intake, with the highest DINE Fibre scores noted in the healthiest ECI tertile. Correspondence was further illustrated by correlations between the diet measures; ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001).
The association between ECI tertiles and DINE Fat and DINE Fibre respectively was examined using crosstabs with the chi2 statistic; this illustrated that the greatest proportion of participants classified in the lowest ECI tertile (unhealthiest) were also those consuming the greatest amount of saturated fat (n = 130); and those classified in the highest ECI range, T3 (healthiest) were also those consuming the least amount of saturated fat according to the DINE (n = 162), χ2 (4) = 41.3, p < 0.001. Similarly, the greatest proportion of participants scoring poorly in the ECI (i.e., lowest tertile) were most likely to have a low fibre intake as measured by the DINE Fibre score (n = 164); and those in the healthiest ECI tertile were most likely to be categorised as having a high fibre intake (n = 145), χ2 (4) = 123.8, p < 0.001 (data not shown here, see Supplementary Material for Tables 1 and 2).
Associations between cooking skills and food skills ability and diet quality
A positive correlation was found between cooking skills ability (CS) and food skills ability (FS) (r = 0.76, p < 0.001) indicating the scales measure highly related components (though distinct as shown by principal components analysis, data not presented here). In relation to cooking and food skills abilities and diet outcomes, the same pattern of results was found for both cooking skills and for food skills and two of the diet quality indicators in that both showed a positive correlation with the ECI (cooking skills ability and ECI r = 0.26, p < 0.001; food skills ability and ECI r = 0.19, p < 0.001); both scales also showed a negative correlation with DINE Fat scores (cooking skills ability and DINE Fat r = -0.22, p < 0.001; food skills ability and DINE Fat r = -0.11, p < 0.001).
Predictors of diet quality
In the regression analysis predicting ECI scores (Table 4), numerous socio-demographic, knowledge-related, and psychological variables remained significant in the final model including: age, gender, education level, socio-economic status, nutrition knowledge, food and health consciousness, cooking identity and meal preparation frequency, with food and health consciousness having the highest predictor value (β = 0.172, p < 0.001). Neither cooking skills ability nor food skills ability added any variance explained to the final model which overall accounted for 19.5 % of the variance (R2) in ECI dietary score (Model F [11,1047] = 22.782, p < 0.001).
In the regression analysis predicting DINE Fat intake all models were significant with gender, nutrition knowledge, food and health consciousness, cooking identity, food neophilia, meal preparation frequency, cooking skills ability and food skills ability all contributing significantly to the final model, with the strongest contribution coming from cooking skills ability (β = -0.296, p < 0.001) where greater cooking skills were associated with lower fat intake. The final model accounted for 19.0 % of the variance (R2) in DINE Fat intake score (Model F [11,1047] = 22.038, p < 0.001).
Finally, in the regression analysis predicting DINE Fibre intake all models were significant with age, education level, food and health consciousness, cooking identity, food neophilia, meal preparation frequency and cooking skills ability all significantly contributing to the final model, with the strongest contribution from cooking identity (β = 0.242, p < 0.001). Here, a greater cooking identity was as associated with increased fibre intake although greater perceived CS ability was associated with lower fibre intake. The final model accounted for 10.1 % of the variance (R2) in DINE Fibre intake score (Model F [11,1047] = 10.623, p < 0.001).
All three regressions were re-run substituting the variables CS and FS ability with CS competence and FS competence (i.e. the total number of CS or FS the participant reported using before rating their ability on each, respectively). The patterns of dietary results was unchanged for ECI and DINE Fat scores, although the regressions explained less variance. For DINE Fibre the results were minimally different in that CS competence (versus CS ability) did not contribute significantly to the model with less variance was explained overall.