Alannah K.A. McKay, Peter Peeling, David B. Pyne, Nicolin Tee, Marijke Welveart, Ida A. Heikura, Avish P. Sharma, Jamie Whitfield, Megan L. Ross, Rachel P.L. van Swelm, Coby M. Laarakkers, and Louise M. Burke
This study implemented a 2-week high carbohydrate (CHO) diet intended to maximize CHO oxidation rates and examined the iron-regulatory response to a 26-km race walking effort. Twenty international-level, male race walkers were assigned to either a novel high CHO diet (MAX = 10 g/kg body mass CHO daily) inclusive of gut-training strategies, or a moderate CHO control diet (CON = 6 g/kg body mass CHO daily) for a 2-week training period. The athletes completed a 26-km race walking test protocol before and after the dietary intervention. Venous blood samples were collected pre-, post-, and 3 hr postexercise and measured for serum ferritin, interleukin-6, and hepcidin-25 concentrations. Similar decreases in serum ferritin (17–23%) occurred postintervention in MAX and CON. At the baseline, CON had a greater postexercise increase in interleukin-6 levels after 26 km of walking (20.1-fold, 95% CI [9.2, 35.7]) compared with MAX (10.2-fold, 95% CI [3.7, 18.7]). A similar finding was evident for hepcidin levels 3 hr postexercise (CON = 10.8-fold, 95% CI [4.8, 21.2]; MAX = 8.8-fold, 95% CI [3.9, 16.4]). Postintervention, there were no substantial differences in the interleukin-6 response (CON = 13.6-fold, 95% CI [9.2, 20.5]; MAX = 11.2-fold, 95% CI [6.5, 21.3]) or hepcidin levels (CON = 7.1-fold, 95% CI [2.1, 15.4]; MAX = 6.3-fold, 95% CI [1.8, 14.6]) between the dietary groups. Higher resting serum ferritin (p = .004) and hotter trial ambient temperatures (p = .014) were associated with greater hepcidin levels 3 hr postexercise. Very high CHO diets employed by endurance athletes to increase CHO oxidation have little impact on iron regulation in elite athletes. It appears that variations in serum ferritin concentration and ambient temperature, rather than dietary CHO, are associated with increased hepcidin concentrations 3 hr postexercise.
Jos J. de Koning
Oliver C. Witard, Laurent Bannock, and Kevin D. Tipton
The acute response of muscle protein synthesis (MPS) to resistance exercise and nutrition is often used to inform recommendations for exercise programming and dietary interventions, particularly protein nutrition, to support and enhance muscle growth with training. Those recommendations are worthwhile only if there is a predictive relationship between the acute response of MPS and subsequent muscle hypertrophy during resistance exercise training. The metabolic basis for muscle hypertrophy is the dynamic balance between the synthesis and degradation of myofibrillar proteins in muscle. There is ample evidence that the process of MPS is much more responsive to exercise and nutrition interventions than muscle protein breakdown. Thus, it is intuitively satisfying to translate the acute changes in MPS to muscle hypertrophy with training over a longer time frame. Our aim is to examine and critically evaluate the strength and nature of this relationship. Moreover, we examine the methodological and physiological factors related to measurement of MPS and changes in muscle hypertrophy that contribute to uncertainty regarding this relationship. Finally, we attempt to offer recommendations for practical and contextually relevant application of the information available from studies of the acute response of MPS to optimize muscle hypertrophy with training.
Kobe C. Houtmeyers, Arne Jaspers, and Pedro Figueiredo
Elite sport practitioners increasingly use data to support training process decisions related to athletes’ health and performance. A careful application of data analytics is essential to gain valuable insights and recommendations that can guide decision making. In business organizations, data analytics are developed based on conceptual data analytics frameworks. The translation of such a framework to elite sport may benefit the use of data to support training process decisions. Purpose: The authors aim to present and discuss a conceptual data analytics framework, based on a taxonomy used in business analytics literature to help develop data analytics within elite sport organizations. Conclusions: The presented framework consists of 4 analytical steps structured by value and difficulty/complexity. While descriptive (step 1) and diagnostic analytics (step 2) focus on understanding the past training process, predictive (step 3) and prescriptive analytics (step 4) provide more guidance in planning the future. Although descriptive, diagnostic, and predictive analytics generate insights to inform decisions, prescriptive analytics can be used to drive decisions. However, the application of this type of advanced analytics is still challenging in elite sport. Thus, the current use of data in elite sport is more focused on informing decisions rather than driving them. The presented conceptual framework may help practitioners develop their analytical reasoning by providing new insights and guidance and may stimulate future collaborations between practitioners, researchers, and analytics experts.