Table A3.
The effect of resilience on dietary outcome variables within high or low experimentally manipulated SS conditions.
| Effect of Resilience | |||||
|---|---|---|---|---|---|
| Outcome | SS Condition | Coefficient | Standard Error |
t Value | p-Value * |
| SFA (g) | High | −0.056 | 0.033 | −1.70 | 0.092 |
| Low | 0.028 | 0.033 | 0.86 | 0.393 | |
| Sodium (mg) | High | −4.302 | 5.584 | −0.77 | 0.443 |
| Low | 4.604 | 5.560 | 0.83 | 0.409 | |
| Sugar (g) | High | −0.373 | 0.241 | −1.55 | 0.125 |
| Low | 0.621 | 0.240 | 2.59 | 0.011 | |
| Energy (kcal) | High | −7.165 | 2.866 | −2.50 | 0.014 |
| Low | 4.105 | 2.854 | 1.44 | 0.153 | |
| % Energy needs | High | −0.394 | 0.153 | −2.57 | 0.011 |
| Low | 0.228 | 0.153 | 1.49 | 0.138 | |
* p-values are used to test whether the slope is significantly different from zero. They are computed from the general linear regression models with dummy coding of either high SS = 0 or low SS = 0 [44] After correction for multiple comparisons, values were considered to be statistically significant at p < 0.01.