TABLE 4.
Consumption level | |||||||
---|---|---|---|---|---|---|---|
Quintile 1 | Quintile 2 | Quintile 3 | Quintile 4 | Quintile 5 | P-trend | P-interaction1 | |
Breakfast fat intake | |||||||
Participants | |||||||
Urban | 118 | 147 | 186 | 234 | 389 | ||
Rural | 469 | 440 | 401 | 353 | 198 | ||
Change in global cognitive score, β (95% CI)2 | — | — | — | — | — | <0.0001 | |
Urban | 0 | −0.00 (−0.22 to 0.22) | 0.18 (−0.03 to 0.40) | 0.38 (0.16–0.59) | 0.42 (0.20–0.64) | <0.0001 | |
Rural | 0 | −0.10 (−0.23 to 0.02) | −0.01 (−0.15 to 0.12) | 0.12 (−0.02 to 0.26) | 0.09 (−0.09 to 0.27) | 0.0438 | |
Change in verbal memory score, β (95% CI) | — | — | — | — | — | <0.0001 | |
Urban | 0 | −0.00 (−0.22 to 0.22) | 0.14 (−0.07 to 0.36) | 0.35 (0.14–0.57) | 0.42 (0.20–0.65) | <0.0001 | |
Rural | 0 | −0.11 (−0.23 to 0.02) | −0.05 (−0.18 to 0.08) | 0.11 (−0.03 to 0.25) | 0.01 (−0.16 to 0.19) | 0.1836 | |
Breakfast carbohydrates intake | |||||||
Participants | |||||||
Urban | 319 | 275 | 185 | 164 | 131 | ||
Rural | 268 | 312 | 402 | 423 | 456 | ||
Change in global cognitive score, β (95% CI) | — | — | — | — | — | <0.0001 | |
Urban | 0 | 0.03 (−0.12 to 0.18) | 0.01 (−0.16 to 0.19) | −0.11 (−0.30 to 0.08) | −0.29 (−0.50 to −0.09) | 0.0075 | |
Rural | 0 | 0.11 (−0.06 to 0.27) | 0.06 (−0.10 to 0.22) | −0.09 (−0.26 to 0.08) | 0.06 (−0.11 to 0.23) | 0.6565 | |
Change in verbal memory score, β (95% CI) | — | — | — | — | — | <0.0001 | |
Urban | 0 | 0.01 (−0.14 to 0.16) | −0.03 (−0.21 to 0.15) | −0.19 (−0.38 to 0.00) | −0.32 (−0.53 to −0.11) | 0.0016 | |
Rural | 0 | 0.09 (−0.08 to 0.25) | 0.06 (−0.11 to 0.22) | −0.10 (−0.27 to 0.07) | 0.06 (−0.10 to 0.23) | 0.7994 |
An interaction analysis was conducted to explore whether the associations of energy and macronutrient intakes with changes in cognitive scores differed between subgroups of age, gender, education, urbanicity, follow-up period, physical activity, BMI, and blood pressure using general linear regression models. A significant interaction was only observed for urbanicity. General linear regression models were used to obtain coefficients (95% CIs) for the changes in cognition associated with breakfast fat and carbohydrate intakes. The changes in cognitive scores were computed as the scores at baseline subtracted from those at follow-up.
A multivariable analysis was adjusted for communities in cities or counties as random effects and age, gender, education, years of follow-up, smoking, alcohol intake, physical activity, cognitive score (baseline), BMI, and systolic and diastolic blood pressure, as well as intakes of total energy, breakfast energy, fiber, sodium, potassium, grains, vegetables, fruits, red meat, processed meat, fish, and poultry at baseline as fixed effects.