Influence of Immune and Nutritional Biomarkers on Illness Risk During Interval Training

in International Journal of Sports Physiology and Performance

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Helen G. Hanstock
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Andrew D. Govus
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Thomas B. Stenqvist
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Anna K. Melin
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Øystein Sylta
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Monica K. Torstveit
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DOI:
https://doi.org/10.1123/ijspp.2018-0527
Keywords:
endurance athletes; HIT; immunity; training load; URTI
In Print:
Volume 15: Issue 1
Page Range:
60–67
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Intensive training periods may negatively influence immune function, but the immunological consequences of specific high-intensity-training (HIT) prescriptions are not well defined. Purpose: To explore whether 3 different HIT prescriptions influence multiple health-related biomarkers and whether biomarker responses to HIT were associated with upper-respiratory-illness (URI) risk. Methods: Twenty-five male cyclists and triathletes were randomized to 3 HIT groups and completed 12 HIT sessions over 4 wk. Peak oxygen consumption (V˙O2peak) was determined using an incremental cycling protocol, while resting serum biomarkers (cortisol, testosterone, 25[OH]D, and ferritin), salivary immunoglobulin-A (s-IgA), and energy availability (EA) were assessed before and after the training intervention. Participants self-reported upper-respiratory symptoms during the intervention, and episodes of URI were identified retrospectively. Results: Fourteen athletes reported URIs, but there were no differences in incidence, duration, or severity between groups. Increased risk of URI was associated with higher s-IgA secretion rates (odds ratio = 0.90, 90% confidence interval 0.83–0.97). Lower preintervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher V˙O2peak reported higher total symptom scores (incidence rate ratio = 1.07, 90% confidence interval 1.01–1.13). Conclusions: Although multiple biomarkers were weakly associated with risk of URI, the direction of associations between s-IgA, cortisol, EA, and URI risk were inverse to previous observations and physiological rationale. There was a cluster of URIs in the first week of the training intervention, but no samples were collected at this time point. Future studies should incorporate more-frequent sample time points, especially around the onset of new training regimens, and include athletes with suspected or known nutritional deficiencies.

Hanstock and Govus are with Swedish Winter Sports Research Center, Inst for Health Sciences, Mid Sweden University, Östersund, Sweden. Stenqvist, Sylta, and Torstveit are with the Faculty of Health and Sport Science, Dept of Public Health, Sport and Nutrition, University of Agder, Kristiansand, Norway.

Hanstock (helen.hanstock@miun.se) is corresponding author.
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