Physiological variables such as maximal oxygen uptake (VO₂max), velocity at maximal oxygen uptake (vVO₂max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO₂max, vVO₂max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.

The aim of this longitudinal study was to explore temporal patterns of physical activity (PA) and adiposity in Spanish adolescents. Eighty healthy adolescents were followed over a 2-year period (42 girls and 38 boys). A PA score was estimated using the Physical Activity Questionnaire for Adolescents (PAQ-A). Adiposity was assessed by anthropometric measurements; body mass index (BMI) and fat mass percent (FMP) were calculated using standard equations. Sexual maturity was estimated by percentage of predicted adult stature. Dietary intake was assessed by a self-administered food-frequency questionnaire. Three assessments were performed: September 2011 (S1), 2012 (S2), and 2013 (S3). A repeated-measures ANOVA was conducted to examine temporal changes in PA and FMP and sex change in maturation categories (two factor mixed-design, 2x2x3). A stepwise linear regression was conducted in order to estimate the predictors of FMP change. Significant changes for FMP were found between S1, S2, and S3 (23.41±8.24 vs. 21.89±7.82 vs. 22.05±8.06, p<0.05; respectively); a significant interaction of FMP with sex was observed (F = 4.387, p<0.05 for S2-S3), but not for maturation. PA at S2 was significantly higher than S3 (2.58±0.72 vs. 2.29±0.73, p<0.001). An interaction between PA change and sex was statically significant (F = 4.889, p<0.05 for S2-S3). A reduction in PA was observed after the S2 period without changes in adiposity. In contrast, a significant reduction in FMP was seen between S1 and S2, while PA did not significantly change. There were no significant differences for nutritional variables between S1 and S3, and nutrition was not a determinant of the changes in PA or FMP. Our results suggest that body composition changes observed during adolescence are not driven by changes in PA. Moreover, the interaction analysis suggests that PA behavior is affected by sex, but is not modified by maturation.

The lean body mass (LBM) components have been suggested as important predictors of anaerobic performance, which is highly involved in basketball. We explored with descriptive cross-sectional design the relationship between anaerobic performance and full molecular and cellular body composition profile in young male basketball players. Twenty-one players (age = 16.8 ± 1.6 years; body mass = 76.3 ± 15.7 kg, height = 189.3 ± 12.6 cm) were recruited, 11 elite and 10 local level. Participants were evaluated on multicomponent body composition [LBM, appendicular lean soft tissue (ALST), bone mineral content (BMC), total body water (TBW), intracellular water (ICW) and extracellular water (ECW)] and field-based anaerobic performance (vertical jump, linear sprint, and handgrip strength). The stepwise regression analyses adjusted for confounders showed significant relationships of whole-body and regional body composition components with handgrip and jump performance (P ≤ 0.03). Prediction models combining body composition variables assessed by bioimpedance analysis (BIA) and double-energy X-ray absorptiometry (DXA) revealed that lean mass and hydration ratios (ICW/ECW and ECW/TBW) were strongly associated with jump performance (CMJ and CMJ25kg), independently of the competition level (P < 0.01). The novel finding in this study was that water quality (ICW/ECW) and water distribution (ECW/TBW, ICW) of total and regional LBM were the main predictors of vertical jump capacity in young basketball players.

Introducción: la influencia del ejercicio físico en sujetos entrenados tiene efectos beneficiosos en la condición física y la composición corporal. Sin embargo, el desentrenamiento tiene un efecto desfavorable en todas ellas.Objetivo: el propósito del estudio fue analizar los cambios de la composición corporal después de un periodo de desentrenamiento de seis semanas de duración en dos grupos: uno de 43 jóvenes varones jugadores de fútbol (grupo experimental [GE], n = 43), y un grupo control de escolares no activos de la misma edad (grupo control [GC], n = 10).Métodos: las variables de composición corporal fueron evaluadas mediante antropometría, para estimar la masa grasa (MG) y la masa muscular esquelética (MME), y mediciones de bioimpedancia eléctrica, para estimar agua corporal total (ACT), agua extra (AEC) e intracelular (AIC). Las mediciones se realizaron tanto en situación de entrenamiento como de desentrenamiento.Resultados: tras el desentrenamiento, se encontraron diferencias significativas en el ACT (35,5 ± 5,2 vs.36,7 ± 4,9 kg), el AIC (14,2 ± 1,8 vs. 14,8 ± 1,6 kg) y el AEC (21,5 ± 3,6 vs.22,0 ± 3,4 kg, p < 0,001 para todas las variables), sin existir diferencias en los ratios AEC/ACT (0,4 ± 0,02 vs.0,4 ± 0,02) y AIC/ACT (0,6 ± 0,02 vs.0,597 ± 0,02, ambos p > 0,05). La MG aumentó significativamente (8,6 ± 3,2 vs.8.95 ± 3,1 kg, p < 0,01); sin embargo, la MME no sufrió modificaciones (21,2 ± 2,5 vs.22,22 ± 2,8 kg, p > 0,05).Conclusiones: el principal resultado de este estudio fue que en un periodo de desentrenamiento de seis semanas se observaron aumentos del ACT y de su distribución en el grupo de jóvenes futbolistas. La importancia fisiológica de esta desadaptación en el rendimiento deportivo tiene que ser analizada en futuros estudios.

Master athletes are considered as a model of healthy aging because they can limit the age-related decline of physiological abilities compared to sedentary individuals. The main objective of this study is to analyze age-related changes and annual training on body composition (BC) and cardiorespiratory fitness (CRF) parameters. The participants in this retrospective cross-sectional study were 176 male cyclists, aged 40–60 years. BC was evaluated through anthropometric measurements and CRF was determined by an incremental cycle ergometer test to exhaustion. A comparative study between age groups was carried out through a one-way ANOVA test and the associations between the variables were assessed by Spearman’s correlation coefficients and multiple regression analysis to estimate the performance. Training was generally associated with a decrease in both body weight and body fat (p < 0.05). A decrease in resting heart rate was observed as a vagal effect of kilometers cycled per year (p < 0.05). Kilometers cycled per year were associated with an increase in peak power output, which was larger in the master 40 group (p < 0.05) with a non-significant upward in VO₂max (p > 0.05). In the performance prediction model, the included variables explained 52% of the variance. In summary, the changes induced by age were minimal in BC and negligible in CRF, whereas HR decreased with age. Training load was generally associated with a decrease in body weight, BMI and body fat percentage that was particularly notable in the abdominal skin folds. A decrease in HRrest was observed as a vagal effect due to kilometers cycled per year, and age did not seem to have a significant effect. The annual cycling kilometers were associated with to high PPO that is greater in the M40 group and a non-significant upward trend in VO₂max.