Development of a specific index to detect malnutrition in athletes: Validity in weight class or intermittent fasted athletes.

Fasted or weight-category athletes manage their training under strict diet conditions that could impair the stress-recovery balance and result in acute or chronic fatigue. However, to date, no validated biomarker are available to quantify this phenomena. The aim of this study was to assess the validity of a specific index combining plasma albumin and weight change to detect nutrition-related risks of fatigue increase and under-performance in athletes experiencing particular nutritional conditions. An athlete's nutrition risk index (ANRI) equation, based on data from lightweight and heavyweight rowers, was developed using relationship between plasma albumin concentrations combined to weight changes with sport performance and overtraining scores and was tested by odds ratio for failure. The accuracy and sensitivity of this former specific equation was subsequently tested on runners observing the Ramadan-fasting as well as on boxers after a short weight-loss period. Independently of training and performance, lightweight rowers presented lower nutritional parameters than heavyweight (albumin: 37.4 ± 2.7 vs 39.9 ± 1.8 g·L-1, P < 0.05; weight state: 94.5 ± 1.8 vs 99.9 ± 0.9%, P < 0.01). In lightweight, ANRI was related with overtraining score (R2 = 0.21, P < 0.01), risks for failure in competition were enhanced when ANRI increased (OR:2.5, P = 0.03). Relationship of ANRI with overtraining score tended to be also significant in runners (R2 = 0.32, P = 0.06) but not in boxers (P = 0.4). Albumin concentrations combined to weight loss appeared relevant to delineate nutrition-related risks of fatigue and/or competitive failure associated with mid-term diets (about 30 days) as observed in rowers and Ramadan-fasted runners. ANRI may benefit to athletes monitoring by delineating effects of their weight loss program.

Effort regulation in rowing races depends on performance level and exercise mode.

This study investigated the influence of performance level and exercise mode on the rowers' pacing strategies. On-water and indoor split times and placements (every 500-m) were obtained from individual 2000-m performances set at the elite, national and sub-elite competitive levels. The data was sorted into indoor (n=580) and on-water exercises (n=507). Indoor and on-water strategies statistically differed, whatever the competition level (p<0.001). Analysis of absolute and normalised velocities demonstrated higher and steadier paces in elite races compared to national and sub-elite races (p<0.001). On water, intermediate placements highlighted the great influence of taking the front of the race particularly at the elite level (at the elite level 78% of the winners were first at the middle of the race and 100% were in the first three). A "parabolic-shaped" profile could describe all races but performance level and exercise mode may alter this effort regulation to even (elite races) or positive paces (national and sub-elite indoor races). The even paces reported as the optimal strategy were not observed in lower performance levels probably because of rowers' inability to combine higher physiological effort and technical requirements of on-water rowing. Training exercise may account for these paces differences, according to the athletes' competitive level and to exercise mode.

Local muscular endurance and prediction of 1 repetition maximum for bench in 4 athletic populations.

The aim of this study was to determine a predictive equation of 1 repetition maximum (1RM) from local muscular endurance. Different athletic male populations were assessed: racket/ball games players (n = 31), power lifters (n = 22), swimmers (n = 28), and rowers (n = 29). After the 1RM assessment for the bench press, the maximum number of repetitions (MNR) relative to the 1RM (85%, 75%, 60%, 40%, and 20%) was tested. No significant differences in strength evolution from 20% to 100% of the 1RM was found between power lifters and racket/ball games players and between swimmers and rowers. However, differences in the strength evolution appeared between these 2 mixed groups (p < 0.01), with differences appearing from 75% of 1RM to lesser relative strength (p < 0.05). Nonlinear equations fitted best with the actual data for the capacity to repeat lifts. The evolution of strength from 100% to 20% of 1RM was better described when the groups' specific equations were used as demonstrated by r, and residuals range between the predicted minus the measured 1RM. The strength endurance competences for high loads (100%-75%) were adequately modelled by the equation based on the total population. The accuracy of the 1RM prediction was better when a reduced number of lifts was performed. For untrained or novice subjects, the use of group-specific equations for the all evolutionary profile of strength allows a good estimate of 1RM and provides adequate numbers of lifts for all levels of strength, thus optimizing the training programs.