Increased body fat is independently and negatively related with cardiorespiratory fitness levels in children and adolescents with normal weight.

Body mass index (BMI) is related with cardiorespiratory fitness (CRF), but less is known regarding the combined relationships between BMI and body fat (BF) on CRF. Cross-sectional study included 2361 girls and 2328 boys aged 10–18 years living in the area of Lisbon, Portugal. BMI was calculated by measuring height and weight, and obesity was assessed by international criteria. BF was assessed by bioimpedance. CRF was assessed by the 20-m shuttle run and the participants were classified as normal-to-high or low-CRF level according to Fitness gram criterion-referenced standards. The prevalence of low CRF was 47 and 39% in girls and boys, respectively. The corresponding values for the prevalence of obesity were 4.8 and 5.6% (not significant) and of excess BF of 12.1 and 25.1% (P <0.001), respectively. In both sexes, BMI and BF were inversely related with CRF: r = – 0.53 and – 0.45 for BMI and % BF, respectively, in boys and the corresponding values in girls were – 0.50 and – 0.33 (all P <0.01). When compared with a participant with normal BMI and BF, the odds ratios (95% confidence interval) for low CRF were 1.94 (1.46–2.58) for a participant with normal BMI and high BF, and 6.19 (5.02–7.63) for a participant with high BMI and high BF. The prevalence of low-CRF levels is high in Portuguese youths. BF negatively influences CRF levels among children/adolescents with normal BMI.

A mathematical model to describe fat oxidation kinetics during graded exercise.

PURPOSE: The purpose of this study was to develop a mathematical model (sine model, SIN) to describe fat oxidation kinetics as a function of the relative exercise intensity [% of maximal oxygen uptake (%VO2max)] during graded exercise and to determine the exercise intensity (Fatmax) that elicits maximal fat oxidation (MFO) and the intensity at which the fat oxidation becomes negligible (Fatmin). This model included three independent variables (dilatation, symmetry, and translation) that incorporated primary expected modulations of the curve because of training level or body composition. METHODS: Thirty-two healthy volunteers (17 women and 15 men) performed a graded exercise test on a cycle ergometer, with 3-min stages and 20-W increments. Substrate oxidation rates were determined using indirect calorimetry. SIN was compared with measured values (MV) and with other methods currently used [i.e., the RER method (MRER) and third polynomial curves (P3)]. RESULTS: There was no significant difference in the fitting accuracy between SIN and P3 (P = 0.157), whereas MRER was less precise than SIN (P < 0.001). Fatmax (44 +/- 10% VO2max) and MFO (0.37 +/- 0.16 g x min(-1)) determined using SIN were significantly correlated with MV, P3, and MRER (P < 0.001). The variable of dilatation was correlated with Fatmax, Fatmin, and MFO (r = 0.79, r = 0.67, and r = 0.60, respectively, P < 0.001). CONCLUSIONS: The SIN model presents the same precision as other methods currently used in the determination of Fatmax and MFO but in addition allows calculation of Fatmin. Moreover, the three independent variables are directly related to the main expected modulations of the fat oxidation curve. SIN, therefore, seems to be an appropriate tool in analyzing fat oxidation kinetics obtained during graded exercise.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.