Índice glicêmico e carga glicêmica da dieta de atletas e sua associação com desempenho físico

Abstract

Glycemic Index (GI) and Glycemic Load (GL) were proposed to enhance physical performance, but there is no consensus in the literature. Objectives: To associate GI and GL of the diet with athletes’ physical performance. Methods: Body weight, height, % body fat, food data and information about exercise training from modalities and genders were collected. The RAST was applied to evaluate the performance and obtain results referent to Fatigue Index and Relative Maximum Power (RMP). Data were categorized into tertiles according to performance. TestT-student, Anova One-Way with Bonferroni post-hoc, and Kruskal-Wallis were used to evaluate the difference between tertiles and multiple linear regression models to evaluate the relationship between performance and GI/GL, adjusted for weekly training hours, sports modalities, carbohydrate, body fat %, age and sex. Results: Athletes showed Age: 18 ± 6.5, BMI: 23 ± 3.1% body fat: 14 ± 6.9, Training hours: 12 ± 6.8, CHO: 5.0 ± 3.1, IG: 53.3 ± 7.2, CG: 36.9 ± 18.7, FI: 5.1 ± 2.6, maxPower: 7.2 ± 1.9. There were differences between the BMI tertiles to IF (1st: 4.0 ± 2.2 and 3rd: 6.0 ± 2.6), body fat %andMaxPower (1st: 8.0 ± 1.7 and 3rd: 6.0 ± 1.8) and energy per day and maxPower (1º: 6,5 ± 2,2 and 3º: 7,8 ± 1,3). CG was associated to MaxPower adjusted by the trainning, sports modalities and carbohydrate. As protein diet was associatioted to fatigue adjusted for, body fat %, age and sex. Conclusion: CG of athlete’s diet it’s a predictor of Power and no relationship were found about GI. Protein diet was a strong predictor of fatigue and further studies are needed.