Effects of endurance exercise and dietary protein intake on osteokine, bone turnover, and inflammatory markers in endurance runners: A narrative review
Bibliographic record
Abstract
Bone stress injuries are pervasive among endurance runners due to repetitive sport-specific mechanical loading and a higher prevalence of low energy availability (i.e., inadequate dietary energy intake relative to exercise energy expenditure). Chronic endurance exercise promotes bone formation, thus, runners typically have higher bone mineral density (BMD) than non-weightbearing athletes and sedentary individuals. However, runners may experience increased bone resorption for hours to days following an endurance exercise bout. If recovery is insufficient, uncoupled bone turnover can pose a significant risk to their bone health. While skeletal-immune system crosstalk has been studied, the interaction during and after exercise in athletes is an emerging area of research. Nutritional interventions have been investigated for their effects on bone metabolism surrounding exercise. However, limited research has examined dietary protein intake in endurance athletes, particularly concerning its effects on bone metabolism and osteoimmunology. This narrative review provides an overview of the evidence on the effects of endurance exercise and dietary protein intake on osteokines, bone turnover, and inflammatory markers in endurance athletes. Acute bouts of high-intensity running increase osteokines and bone turnover markers that promote bone resoprtion which parallels increases in pro-inflammatory markers in endurance athletes, suggesting crosstalk between these systems during and after exercise. Chronic endurance exercise promotes increased resting levels of bone formation, while reducing resting pro-inflammatory markers. Adequate dietary protein ingestion habitually and pre-, during, and post-exercise may attenuate bone resportion and pro-inflammatory markers in endurance athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".