Influência da fase de treinamento sobre parâmetros nutricionais, físicos e psicobiológicos de atletas paralímpicos brasileiros
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Data
2015-09-30
Autores
Rodrigues, Dayane Ferreira [UNIFESP]
Orientadores
Mello, Marco Tulio de [UNIFESP]
Tipo
Dissertação de mestrado
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Atletas paralímpicos têm obtido resultados de grande expressividade, porém, algumas variáveis podem influenciar o desempenho atlético, bem como, alterar o comportamento em fases distintas de treinamento. Objetivo: verificar se existe diferença entre três fases de treinamento distintas no consumo de energia, de macronutrientes, na composição corporal, na ansiedade e qualidade subjetiva de sono, de atletas brasileiros da seleção permanente de atletismo paralímpico. Método: Foram avaliados 18 atletas em três fases de treinamento distintas: (1) pós-competição no final de 2011, (2) pós-férias no início de 2012 e (3) pré-competição em Junho de 2012. O consumo de macronutrientes, a ansiedade, a qualidade de sono e a sonolência diurna foram avaliados por meio dos seguintes questionários respectivamente: recordatório de 24 horas, inventário de ansiedade traço-estado, índice de qualidade de sono de Pittsburgh e escala de sonolência de Epworth. Para estimar o índice glicêmico das refeições considera a proporção de carboidratos de cada alimento em relação ao valor de carboidrato total da refeição e o valor proporcional do índice glicêmico. A composição corporal foi avaliada pelo método de pletismografia por deslocamento de ar. Os resultados foram apresentados como mediana e erro padrão e o nível de significância adotado foi p<0,05. Resultados: O consumo de carboidratos dos atletas nas três fases de treinamento foi inferior ao recomendado. Entre as fases de treinamento pós-competição e pós-férias (avaliações 1 e 2), houve aumento da massa magra (valores absolutos: p=0,004/ valores relativos: p=0,010) e diminuição da massa gorda ( valores absolutos: p=0,028 /valores relativos: p=0,018) no período pós-férias. Entretanto, ao comparar os períodos pós-férias e pré-competição (avaliações 2 e 3) ocorreu uma diminuição de massa magra (valores absolutos: p=0,003/ valores relativos: p=0,006) e aumento de massa gorda (valores absolutos: p=0,004 /valores relativos: p=0,006), no período pré-competição. Ao se avaliar os parâmetros psicobiológicos nas diferentes fases de treinamento, houve diferença apenas no tempo total de sono entre as avaliações 2 e 3 (p=0,024) com aumento na avaliação 3 (p=0,016). Para ansiedade-estado, houve um predomínio de nível médio nos períodos pós-competição (=8; df=1; p=0,005) e pós-férias (=16,333; df=2; p = 0.001) e a eficiência de sono >85% foi predominante nas avaliações 1, 2 e 3 (=8; df=1; p=0,005/ = 14,222; df=1; p=0,001/ =14,222; df=1; p=0,001). No período pós-competição os atletas com boa qualidade de sono apresentaram consumo intermediário de carboidratos em gramas/Kg/dia (p=0,007) e menor consumo de lipídeos em gramas/Kg/dia (p=0,02). Além disso, houve uma correlação média negativa, entre consumo diário de proteínas em gramas (r=-0,59; p=0,01), o percentual de energia de proteínas consumido (r=-0,57; p=0,01) com a eficiência de sono. Também houve uma correlação negativa média (r=-0,52; p=0,03) entre consumo diário de proteínas em gramas com o tempo total de sono e consumo diário de carboidratos (r=-0,48; p=0,04) e latência de sono. A latência de sono apresentou correlação média positiva com índice glicêmico do jantar (r=0,57; p=0,02) e correlação preditiva positiva (r=0,84; p=0,02) com índice glicêmico do jantar e da ceia. Conclusões: Os atletas apresentaram um consumo inadequado de carboidratos nas três fases de treinamento. No período pré-competição houve diminuição de massa magra e aumento de massa gorda. Além disso, quanto maior o IG do jantar maior a latência do sono. No período pós-competição quanto maior o consumo de proteínas menor a eficiência e o tempo total de sono. Porém, quanto maior o consumo de carboidratos menor a latência e maior eficiência de sono.
The paralympic athletes have been obtained results of great expressiveness; however, some variables can influence the athletic performance, as well as change the behavior in different training stages. Aim: to analyze if there is difference between three different training stages in the consumption of macronutrients and energy, in body composition, in anxiety and in subjective sleep quality. Methods: Eighteen athletes were evaluated in three different training stages: (1) post-competition, in the end of 2011, (2) post-holiday, in the beginning of 2012 and (3) pre-competition, in 2012 June. The questionnaires used to evaluate consumption of macronutrients, the anxiety, the sleep quality and the sleepiness respectively were: 24-hour dietary recall, State-Trait Anxiety Inventory, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale. To estimate the glycemic index of meals is considered the carbohydrate proportion of each food in relation to the total carbohydrate value and the proportional value of glycemic index. The body composition was evaluated using the air displacement plethysmography. The results were presented as median and standard error and the level of significance was p<0.05. Results: The carbohydrate consumption was lower than recommended in all training stages. Between post-competition and post-holiday (evaluations 1 and 2), the athletes presented an increase in fat free mass (Absolute values: p=0.004/Relative values: p=0.010) and a decrease in the fat mass (absolute values: 0=0.028/relative values: p=0.018) in post-holiday stage. However, between post-holiday and pre-competition (evaluations 2 and 3) was found a decrease in fat free mass, (valores absolutos: p=0,003/ valores relativos: p=0,006) and increase in fat mass (valores absolutos: p=0,004 /valores relativos: p=0,006), in pre-competition stage. For the evaluations of psychobiological parameters there was a statistically significant difference in the total sleep time between the evaluations 2 and 3 (p=0.024) with an increase in the evaluation 3 (p=0.016). For the state-anxiety, there was a dominance of medium level in post-competition (=8; df=1; p=0,005) and post-holiday periods (=16,333; df=2; p = 0.001), and the sleep efficiency higher than 85% was dominance in three evaluations (=8; df=1; p=0,005/ = 14,222; df=1; p=0,001/ =14,222; df=1; p=0,001). In the post-competition period, the athletes with good sleep quality presented an intermediate consumption of carbohydrates (p=0.007) smaller consumption of lipids (p=0.02). In addition, a medium negative correlation was found between diary consumption of proteins (r=0.59; p=0.01) and sleep efficiency, and between the protein percentage of energy consumed (r=0.57; p=0.01) and sleep efficiency. There was also a medium negative correlation (r=-0.52; p=0.03) between diary consumption of proteins and the total sleep time, and between diary consumption of carbohydrates and the sleep latency (r=-0.48; p=0.04). There was a medium positive correlation (r=0.55; p=0.02) between daily consumption of carbohydrates and sleep efficiency. In the pre-competition period, athletes with poor sleep quality presented higher carbohydrate consumption (p=0.03). A medium positive correlation was found between sleep latency and the glycemic index (GI) of dinner (r=0.57; p=0.02) and a predictive positive correlation between sleep latency and GI of dinner+supper (r=0.84; p=0.02). Conclusions: the athletes demonstrated an inadequate carbohydrate intake in the three phases of training. In the pre-competition period, athletes showed a decreased in lean body mass and an increased in fat mass. Furthermore, was observed that when the dinner GI is higher, the sleep latency also increased. In the post-competition period, was demonstrated that when the greater protein consumption, smaller the sleep efficiency and total sleep time. However, there was found that when carbohydrate intake is higher, the sleep efficiency also higher, but, the sleep latency was lower.
The paralympic athletes have been obtained results of great expressiveness; however, some variables can influence the athletic performance, as well as change the behavior in different training stages. Aim: to analyze if there is difference between three different training stages in the consumption of macronutrients and energy, in body composition, in anxiety and in subjective sleep quality. Methods: Eighteen athletes were evaluated in three different training stages: (1) post-competition, in the end of 2011, (2) post-holiday, in the beginning of 2012 and (3) pre-competition, in 2012 June. The questionnaires used to evaluate consumption of macronutrients, the anxiety, the sleep quality and the sleepiness respectively were: 24-hour dietary recall, State-Trait Anxiety Inventory, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale. To estimate the glycemic index of meals is considered the carbohydrate proportion of each food in relation to the total carbohydrate value and the proportional value of glycemic index. The body composition was evaluated using the air displacement plethysmography. The results were presented as median and standard error and the level of significance was p<0.05. Results: The carbohydrate consumption was lower than recommended in all training stages. Between post-competition and post-holiday (evaluations 1 and 2), the athletes presented an increase in fat free mass (Absolute values: p=0.004/Relative values: p=0.010) and a decrease in the fat mass (absolute values: 0=0.028/relative values: p=0.018) in post-holiday stage. However, between post-holiday and pre-competition (evaluations 2 and 3) was found a decrease in fat free mass, (valores absolutos: p=0,003/ valores relativos: p=0,006) and increase in fat mass (valores absolutos: p=0,004 /valores relativos: p=0,006), in pre-competition stage. For the evaluations of psychobiological parameters there was a statistically significant difference in the total sleep time between the evaluations 2 and 3 (p=0.024) with an increase in the evaluation 3 (p=0.016). For the state-anxiety, there was a dominance of medium level in post-competition (=8; df=1; p=0,005) and post-holiday periods (=16,333; df=2; p = 0.001), and the sleep efficiency higher than 85% was dominance in three evaluations (=8; df=1; p=0,005/ = 14,222; df=1; p=0,001/ =14,222; df=1; p=0,001). In the post-competition period, the athletes with good sleep quality presented an intermediate consumption of carbohydrates (p=0.007) smaller consumption of lipids (p=0.02). In addition, a medium negative correlation was found between diary consumption of proteins (r=0.59; p=0.01) and sleep efficiency, and between the protein percentage of energy consumed (r=0.57; p=0.01) and sleep efficiency. There was also a medium negative correlation (r=-0.52; p=0.03) between diary consumption of proteins and the total sleep time, and between diary consumption of carbohydrates and the sleep latency (r=-0.48; p=0.04). There was a medium positive correlation (r=0.55; p=0.02) between daily consumption of carbohydrates and sleep efficiency. In the pre-competition period, athletes with poor sleep quality presented higher carbohydrate consumption (p=0.03). A medium positive correlation was found between sleep latency and the glycemic index (GI) of dinner (r=0.57; p=0.02) and a predictive positive correlation between sleep latency and GI of dinner+supper (r=0.84; p=0.02). Conclusions: the athletes demonstrated an inadequate carbohydrate intake in the three phases of training. In the pre-competition period, athletes showed a decreased in lean body mass and an increased in fat mass. Furthermore, was observed that when the dinner GI is higher, the sleep latency also increased. In the post-competition period, was demonstrated that when the greater protein consumption, smaller the sleep efficiency and total sleep time. However, there was found that when carbohydrate intake is higher, the sleep efficiency also higher, but, the sleep latency was lower.
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RODRIGUES, Dayane Ferreira. Influência da fase de treinamento sobre parâmetros nutricionais, físicos e psicobiológicos de atletas paralímpicos brasileiros. 2015. 123 f. Dissertação (Mestrado em Nutrição) - Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, 2015.