Assessment of Nutrient Status in Athletes and the Need for Supplementation

An athlete's carbohydrate intake can be judged by whether total daily intake and the timing of consumption in relation to exercise maintain adequate carbohydrate substrate for the muscle and central nervous system ("high carbohydrate availability") or whether carbohydrate fuel sources are limiting for the daily exercise programme ("low carbohydrate availability"). Carbohydrate availability is increased by consuming carbohydrate in the hours or days prior to the session, intake during exercise, and refuelling during recovery between sessions. This is important for the competition setting or for high-intensity training where optimal performance is desired. Carbohydrate intake during exercise should be scaled according to the characteristics of the event. During sustained high-intensity sports lasting ~1 h, small amounts of carbohydrate, including even mouth-rinsing, enhance performance via central nervous system effects. While 30-60 g · h(-1) is an appropriate target for sports of longer duration, events >2.5 h may benefit from higher intakes of up to 90 g · h(-1). Products containing special blends of different carbohydrates may maximize absorption of carbohydrate at such high rates. In real life, athletes undertake training sessions with varying carbohydrate availability. Whether implementing additional "train-low" strategies to increase the training adaptation leads to enhanced performance in well-trained individuals is unclear.

National surveys of food intake rely on the 24-h dietary recall method for assessing the nutrient intakes of Americans. This observational validation study was conducted under controlled conditions to test the effectiveness of the US Department of Agriculture (USDA) 5-step multiple-pass method for dietary recall; to test the ability of normal weight, overweight, and obese women to recall food intake; and to test the accuracy of macronutrient recall. Women (n = 49) aged 21-65 y with a body mass index (in kg/m(2)) of 20-45 selected all meals and snacks for 1 d from a wide variety of foods. A 24-h dietary recall with the use of the USDA 5-step multiple-pass method was administered by telephone the following day. Analysis of variance and covariance tested the overall accuracy of recall and the effect of BMI on dietary recall. As a population, the women overestimated their energy and carbohydrate intakes by 8-10%. No significant differences between mean actual and recalled intakes of energy and the macronutrients were observed in the obese women. Normal-weight and overweight women significantly (P < 0.01) overestimated their energy, protein, and carbohydrate intakes. Recalled fat intake was not significantly different from actual intake in women across the BMI range studied. The USDA 5-step multiple-pass method effectively assessed mean energy intake within 10% of mean actual intake on the previous day. Obese women more accurately recalled food intake than did overweight and normal-weight women despite undereating on the day of the study.

We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing US adult populations from 1999 to 2009. We report on total energy, protein, and protein density intakes. Results were similar across sexes, but there was heterogeneity across studies. Using a FFQ, the average correlation coefficients for reported versus true intakes for energy, protein, and protein density were 0.21, 0.29, and 0.41, respectively. Using a single 24-hour recall, the coefficients were 0.26, 0.40, and 0.36, respectively, for the same nutrients and rose to 0.31, 0.49, and 0.46 when three 24-hour recalls were averaged. The average rate of under-reporting of energy intake was 28% with a FFQ and 15% with a single 24-hour recall, but the percentages were lower for protein. Personal characteristics related to under-reporting were body mass index, educational level, and age. Calibration equations for true intake that included personal characteristics provided improved prediction. This project establishes that FFQs have stronger correlations with truth for protein density than for absolute protein intake, that the use of multiple 24-hour recalls substantially increases the correlations when compared with a single 24-hour recall, and that body mass index strongly predicts under-reporting of energy and protein intakes.