Ten weeks of branched-chain amino acid supplementation improves select performance and immunological variables in trained cyclists.

We examined if supplementing trained cyclists (32 ± 2 year, 77.8 ± 2.6 kg, and 7.4 ± 1.2 year training) with 12 g/day (6 g/day L-Leucine, 2 g/day L-Isoleucine and 4 g/day L-Valine) of either branched-chain amino acids (BCAAs, n = 9) or a maltodextrin placebo (PLA, n = 9) over a 10-week training season affected select body composition, performance, and/or immune variables. Before and after the 10-week study, the following was assessed: (1) 4-h fasting blood draws; (2) dual X-ray absorptiometry body composition; (3) Wingate peak power tests; and (4) 4 km time-trials. No group × time interactions existed for total lean mass (P = 0.27) or dual-leg lean mass (P = 0.96). A significant interaction existed for body mass-normalized relative peak power (19 % increase in the BCAA group pre- to post-study, P = 0.01), and relative mean power (4 % increase in the BCAA group pre- to post-study, P = 0.01). 4 km time-trial time to completion approached a significant interaction (P = 0.08), as the BCAA group improved in this measure by 11 % pre- to post-study, though this was not significant (P = 0.15). There was a tendency for the BCAA group to present a greater post-study serum BCAA: L-Tryptophan ratio compared to the PLA group (P = 0.08). A significant interaction for neutrophil number existed (P = 0.04), as there was a significant 18 % increase within the PLA group from the pre- to post-study time point (P = 0.01). Chronic BCAA supplementation improves sprint performance variables in endurance cyclists. Additionally, given that BCAA supplementation blunted the neutrophil response to intense cycling training, BCAAs may benefit immune function during a prolonged cycling season.

Income inequality and mortality: time series evidence from Canada.

In this paper, we apply the standard model used in the income strand of the socio-economic status (SES)-population health literature to explain the relationship between mortality and income to pooled cross-section time-series data for Canada. The use of time-series data increases the available degrees of freedom and allows for the possibility that the effects of inequality take time to translate into poorer health outcomes. In light of recent criticisms of aggregate level studies, we do not attempt to differentiate between the absolute and relative inequality hypotheses, but test for the existence of a relationship between mortality and a measure of income inequality. We find that whether an exogenous trend is incorporated or an auto-regressive distributed lag form is used, the coefficients on mean income and the Gini are not significantly different from zero, which contradicts the findings in other parts of the literature, but which is consistent with earlier cross-section evidence for Canada. The results suggest that models that focus exclusively on income as a measure of the impact of SES on mortality are not complete and that health spending and unemployment may be even more important than income growth and dispersion.