Objectives To quantify acute injuries sustained during weightlifting that result in training restrictions and identify potential risk factors or preventative factors in Master athletes and to evaluate potentially complex interactions of age, sex, health-related and training-related predictors of injuries with machine learning (ML) algorithms.
Methods A total of 976 Masters weightlifters from Australia, Canada, Europe and the USA, ages 35–88 (51.1% women), completed an online survey that included questions on weightlifting injuries, chronic diseases, sport history and training practices. Ensembles of ML algorithms were used to identify factors associated with acute weightlifting injuries and performance of the prediction models was evaluated. In addition, a subgroup of variables selected by six experts were entered into a logistic regression model to estimate the likelihood of an injury.
Results The accuracy of ML models predicting injuries ranged from 0.727 to 0.876 for back, hips, knees and wrists, but were less accurate (0.644) for shoulder injuries. Male Master athletes had a higher prevalence of weightlifting injuries than female Master athletes, ranging from 12% to 42%. Chronic inflammation or osteoarthritis were common among both men and women. This was associated with an increase in acute injuries.
Conclusions Training-specific variables, such as choices of training programmes or nutrition programmes, may aid in preventing acute injuries. ML models can identify potential risk factors or preventative measures for sport injuries.
- weight lifting
- sporting injuries
Data availability statement
Data are available in a public, open access repository. Reference: Huebner, Marianne (2022), Weightlifting Injuries in Master Athletes, Dryad Digital Repository, Dataset, https://doi.org/10.5061/dryad.51c59zwb3.
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Contributors MH conceptualised the study and reviewed the literature. MH is the guarantor of the study. Both authors performed statistical analyses and wrote the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Active weightlifters provided feedback on the survey questions.
Provenance and peer review Not commissioned; externally peer reviewed.
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