Training Load and Baseline Characteristics Associated With New Injury/Pain Within an Endurance Sporting Population: A Prospective Study

in International Journal of Sports Physiology and Performance

Click name to view affiliation

Richard Johnston
Search for other papers by Richard Johnston in
Current site
Google Scholar
PubMed
Close
,
Roisin Cahalan
Search for other papers by Roisin Cahalan in
Current site
Google Scholar
PubMed
Close
,
Laura Bonnett
Search for other papers by Laura Bonnett in
Current site
Google Scholar
PubMed
Close
,
Matthew Maguire
Search for other papers by Matthew Maguire in
Current site
Google Scholar
PubMed
Close
,
Alan Nevill
Search for other papers by Alan Nevill in
Current site
Google Scholar
PubMed
Close
,
Philip Glasgow
Search for other papers by Philip Glasgow in
Current site
Google Scholar
PubMed
Close
,
Kieran O’Sullivan
Search for other papers by Kieran O’Sullivan in
Current site
Google Scholar
PubMed
Close
, and
Thomas Comyns
Search for other papers by Thomas Comyns in
Current site
Google Scholar
PubMed
Close
Restricted access

Purpose: To determine the association between training-load (TL) factors, baseline characteristics, and new injury and/or pain (IP) risk in an endurance sporting population (ESP). Methods: Ninety-five ESP participants from running, triathlon, swimming, cycling, and rowing disciplines initially completed a questionnaire capturing baseline characteristics. TL and IP data were submitted weekly over a 52-wk study period. Cumulative TL factors, acute:chronic workload ratios, and exponentially weighted moving averages were calculated. A shared frailty model was used to explore time to new IP and association to TL factors and baseline characteristics. Results: 92.6% of the ESP completed all 52 wk of TL and IP data. The following factors were associated with the lowest risk of a new IP episode: (a) a low to moderate 7-d lag exponentially weighted moving averages (0.8–1.3: hazard ratio [HR] = 1.21; 95% confidence interval [CI], 1.01–1.44; P = .04); (b) a low to moderate 7-d lag weekly TL (1200–1700 AU: HR = 1.38; 95% CI, 1.15–1.65; P < .001); (c) a moderate to high 14-d lag 4-weekly cumulative TL (5200–8000 AU: HR = 0.33; 95% CI, 0.21–0.50; P < .001); and (d) a low number of previous IP episodes in the preceding 12 mo (1 previous IP episode: HR = 1.11; 95% CI, 1.04–1.17; P = .04). Conclusions: To minimize new IP risk, an ESP should avoid high spikes in acute TL while maintaining moderate to high chronic TLs. A history of previous IP should be considered when prescribing TLs. The demonstration of a lag between a TL factor and its impact on new IP risk may have important implications for future ESP TL analysis.

Johnston and Comyns are with the Dept of Physical Education and Sport Sciences; Cahalan and O’Sullivan, the School of Allied Health; and Cahalan, O’Sullivan, and Comyns, the Health Research Inst, University of Limerick, Limerick, Ireland. Bonnett is with the Dept of Biostatistics, University of Liverpool, Liverpool, United Kingdom. Johnston and Maguire are with Irish Rugby Football Union, Ulster Rugby, Belfast, United Kingdom. Nevill is with the Faculty of Education Health and Wellbeing, University of Wolverhampton, Wolverhampton, United Kingdom. Glasgow is with Irish Rugby Football Union, Lansdowne Road, Dublin, Ireland. O’Sullivan is with Sports Spine Center, Aspetar Orthopedic and Sports Medicine Hospital, Doha, Qatar.

Johnston (Richard.Johnston@ul.ie) is corresponding author.

Supplementary Materials

    • Supplementary Material (PDF 156 KB)
    • Supplementary Table 1 (PDF 94 KB)
  • Collapse
  • Expand