Markers of low energy availability in overreached athletes: a systematic review and meta-analysis
Abstract
Background Overreaching is the transient reduction in performance that occurs following training overload and is driven by an imbalance between stress and recovery. Low energy availability (LEA) may drive underperformance by compounding training stress; however, this has yet to be investigated systematically. Objective The aim of this study was to quantify changes in markers of LEA in athletes who demonstrated underperformance, and exercise performance in athletes with markers of LEA. Methods Studies using a ≥ 2-week training block with maintained or increased training loads that measured exercise performance and markers of LEA were identified using a systematic search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Changes from pre- to post-training were analyzed for (1) markers of LEA in underperforming athletes and (2) performance in athletes with ≥ 2 markers of LEA. Results From 56 identified studies, 14 separate groups of athletes demonstrated underperformance, with 50% also displaying ≥ 2 markers of LEA post-training. Eleven groups demonstrated ≥ 2 markers of LEA independent of underperformance and 37 had no performance reduction or ≥ 2 markers of LEA. In underperforming athletes, fat mass (d = - 0.29, 95% confidence interval [CI] - 0.54 to - 0.04; p = 0.02), resting metabolic rate (d = - 0.63, 95% CI - 1.22 to - 0.05; p = 0.03), and leptin (d = - 0.72, 95% CI - 1.08 to - 0.35; p 2 = 84.86%) could not be explained by the perf…
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LEA and/or LCA should be excluded from an OTS diagnosis as LEA is the underlying aetiology for a REDs diagnosis.
“It is important to note that LEA and/or LCA, although challenging to assess, should be excluded from an OTS diagnosis as LEA is the underlying aetiology for a REDs diagnosis.37 59”
From 2023 international olympic committee's (IOC) consensus statement on relative energy deficiency in sport (REDs) (2023) · cites this paper as [59]
Cites
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283 · see citing works
(2007) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318149f111 · Cited by 1,554 · see citing works
Mountjoy, M., Sundgot-Borgen, J., Burke, L., Carter, S., Constantini, N., Lebrun, C., Meyer, N., Sherman, R., Steffen, K., Budgett, R., et al. (2014) · British Journal of Sports Medicine · doi:10.1136/bjsports-2014-093502 · Cited by 1,469 · cited 1× · see citing works
“Later, an expanded model termed Relative Energy Deficiency in Sport (RED-S) emerged, which is a syndrome of “impaired physiological function including, but not limited to, metabolic rate, menstrual function, bone health, immunity, protein synthesis, cardiovascular health” that also affects men [7].”
(2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318279a10a · Cited by 1,233 · see citing works
The heterogeneity statistic I2 can be biased in small meta-analyses
von Hippel, P. T. (2015) · BMC Medical Research Methodology · doi:10.1186/s12874-015-0024-z · Cited by 1,229 · see citing works
Cunningham, J. (1991) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/54.6.963 · Cited by 607 · see citing works
Johnstone, A. M., Murison, S. D., Duncan, J. S., Rance, K. A., & Speakman, J. R. (2005) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/82.5.941 · Cited by 514 · see citing works
Energy Availability in Athletics: Health, Performance, and Physique
Melin, A. K., Heikura, I. A., Tenforde, A., & Mountjoy, M. (2019) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.2018-0201 · Cited by 258 · see citing works
Hilton, L. K., & Loucks, A. B. (2000) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.2000.278.1.e43 · Cited by 214 · cited 2× · see citing works
“Decreased levels of leptin [29, 38, 39], T3 [28, 40], testosterone (males only) [41], insulin [29, 32, 39], IGF-1 [42], osteocalcin [42], procollagen 1 N-terminal propeptide [33, 42]”
BackgroundOvarian Suppression Impairs Sport Performance in Junior Elite Female Swimmers
VanHeest, J. L., Rodgers, C. D., Mahoney, C. E., & De Souza, M. J. (2014) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e3182a32b72 · Cited by 203 · see citing works
Adaptive thermogenesis with weight loss in humans
Müller, M. J., & Bosy‐Westphal, A. (2013) · Obesity · doi:10.1002/oby.20027 · Cited by 181 · see citing works
Stellingwerff, T., Heikura, I. A., Meeusen, R., Bermon, S., Seiler, S., Mountjoy, M. L., & Burke, L. M. (2021) · Sports Medicine · doi:10.1007/s40279-021-01491-0 · Cited by 171 · cited 6× · see citing works
“However, the severity and duration of reduced energy availability needs to be considered to avoid the injury, illness and/or impaired performance that can occur with LEA, and eventually RED-S.”
BackgroundResultInfluentialGuidelines to classify female subject groups in sport-science research
Decroix, L., De Pauw, K., Foster, C., & Meeusen, R. (2016) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2015-0153 · Cited by 167 · cited 1× · see citing works
“Studies from non-competitive athlete groups were included only if participants could be classified at or above a ‘recreationally trained’ level of fitness [18, 19].”
BackgroundStaal, S., Sjödin, A., Fahrenholtz, I., Bonnesen, K., & Melin, A. K. (2018) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.2017-0327 · Cited by 101 · see citing works
Stellingwerff, T. (2018) · International Journal of Sport Nutrition and Exercise Metabolism · doi:10.1123/ijsnem.2017-0312 · Cited by 72 · see citing works
Muscle Glycogen Content during Endurance Training under Low Energy Availability
KOJIMA, C., ISHIBASHI, A., TANABE, Y., IWAYAMA, K., KAMEI, A., TAKAHASHI, H., & GOTO, K. (2020) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000002098 · Cited by 55 · see citing works
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Mountjoy, M., Ackerman, K. E., Bailey, D. M., Burke, L. M., Constantini, N., Hackney, A. C., Heikura, I. A., Melin, A., Pensgaard, A. M., Stellingwerff, T., et al. (2023) · British Journal of Sports Medicine · doi:10.1136/bjsports-2023-106994 · Cited by 724 · see citing works
- Authors
- Kuikman, M. A., Coates, A. M., & Burr, J. F.
- Affiliations
- University of Guelph (CA)
- Corresponding author
- Burr, Jamie F.
- Venue
- Sports Medicine
- Published
- 2022-07-11
- Volume
- 52
- Issue
- 12
- Pages
- 2925-2941
- ISSN
- 0112-1642 (ISSN-L)
- 1179-2035
- OpenAlex
- W4285077514
- Cited by
- 18
- References
- 16
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 4 · 2023: 5 · 2022: 1
- FWCI
- 0.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
- Health Sciences › Medicine › Rehabilitation › Exercise and Physiological Responses
- Keywords
- low energy availability, overreaching, training overload, exercise performance, underperformance, athletes, fat mass, resting metabolic rate, leptin, cortisol, insulin, testosterone, training stress, recovery, energy balance, training load, body composition, hormonal markers, injury risk, injury recovery time, injury prevention, injury rehabilitation
- MeSH terms
- Humans, Hydrocortisone, Testosterone, Biomarkers, Exercise, Athletes
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