REF-369 · Cadegiani & Kater, 2019 · BMC Sports Science, Medicine and Rehabilitation, · Paper · PubMed
In 39 athletes (14 with overtraining syndrome), OTS was triggered independently by eating patterns
Daily carbohydrate, protein and calorie intake — and not by training patterns; once present, it independently lowered cortisol, late GH and ACTH responses, the testosterone:estradiol ratio, neutrophils and vigor
Participants
n=39 athletes: 14 with overtraining syndrome (OTS) and 25 healthy athletes (ATL). Training patterns were similar in the two groups.
Protocol
Two clusters of analysis on the full EROS data (117 markers): logistic regression of five modifiable factors (carbohydrate, protein and calorie intake, sleep quality, concurrent cognitive effort) as risk factors for OTS, and multivariate linear regression of OTS against 38 dependent variables.
Key Findings
Daily carbohydrate, daily protein and overall daily calorie intake were each independent triggers of OTS; sleep, social and training characteristics depended on other factors to induce it. Excessive training was not a risk factor here, because training did not differ between groups.
Once present, OTS independently reduced cortisol, late growth-hormone and ACTH responses to stimulation, the testosterone-to-estradiol ratio, neutrophils, the neutrophil-to-lymphocyte ratio, vigor, hydration status and muscle mass, and increased tension and visceral fat.
The authors conclude OTS can be triggered by eating patterns regardless of training patterns.
Practical Application
In 39 athletes, overtraining syndrome was independently associated with under-eating — low daily carbohydrate, protein and total calories — rather than with training load, and it came with blunted cortisol/GH/ACTH responses and a lower testosterone:estradiol ratio (Cadegiani & Kater 2019). When an athlete looks overtrained, ask about intake before blaming the training.
No blood marker diagnoses overtraining on its own — the ECSS/ACSM consensus (REF-206) says none meets the criteria for general acceptance; labs are for excluding other causes (iron, thyroid, infection, energy deficit) and for an athlete's own trend.
Not from this paper; the base's own practice: a routine panel once or twice a year (blood count, metabolic panel, morning cortisol, TSH/fT4, testosterone or oestradiol, ferritin, vitamin D, CRP); during a suspected overreach add CK.
Biomarker changes are late signals — subjective wellness and HRV usually move first (REF-368).
Limitations
Small groups (14 vs 25), one research group, cross-sectional: associations, not causes.
117 markers analysed — multiple-comparison risk.
The abstract gives no sport or performance level.
Full text not read; everything above is from the abstract.
How this entry was checked and changed
Why this level
small case-control, one research group
Content correction 2026-09-27
Anchored to Cadegiani & Kater 2019, BMC SSMR 11:21, DOI 10.1186/s13102-019-0132-x (the entry said "11:14"; the article number is 21). Identified by a title/author search and attached with the owner's explicit OK (2026-09-27).
The second citation (Slivka 2010, Aviat Space Environ Med 81(8):786-791) does not exist at that address and was removed; a probable intended paper (Slivka 2010, J Strength Cond Res) was not attached.
The unverified "working summary" (CRP/IL-6, CK, HRV, DHEA, IGF-1 patterns) was replaced with the abstract's findings; lab-panel advice stays labelled as practice. Level C+ -> B.
Protocol section added from the abstract.