TY - JOUR T1 - Not straightforward: modelling non-linearity in training load and injury research JF - BMJ Open Sport & Exercise Medicine JO - BMJ OPEN SP EX MED DO - 10.1136/bmjsem-2021-001119 VL - 7 IS - 3 SP - e001119 AU - Lena Kristin Bache-Mathiesen AU - Thor Einar Andersen AU - Torstein Dalen-Lorentsen AU - Benjamin Clarsen AU - Morten Wang Fagerland Y1 - 2021/08/01 UR - http://bmjopensem.bmj.com/content/7/3/e001119.abstract N2 - Objectives To determine whether the relationship between training load and injury risk is non-linear and investigate ways of handling non-linearity.Methods We analysed daily training load and injury data from three cohorts: Norwegian elite U-19 football (n=81, 55% male, mean age 17 years (SD 1)), Norwegian Premier League football (n=36, 100% male, mean age 26 years (SD 4)) and elite youth handball (n=205, 36% male, mean age 17 years (SD 1)). The relationship between session rating of perceived exertion (sRPE) and probability of injury was estimated with restricted cubic splines in mixed-effects logistic regression models. Simulations were carried out to compare the ability of seven methods to model non-linear relationships, using visualisations, root-mean-squared error and coverage of prediction intervals as performance metrics.Results No relationships were identified in the football cohorts; however, a J-shaped relationship was found between sRPE and the probability of injury on the same day for elite youth handball players (p<0.001). In the simulations, the only methods capable of non-linear modelling relationships were the quadratic model, fractional polynomials and restricted cubic splines.Conclusion The relationship between training load and injury risk should be assumed to be non-linear. Future research should apply appropriate methods to account for non-linearity, such as fractional polynomials or restricted cubic splines. We propose a guide for which method(s) to use in a range of different situations.Data are available in a public, open access repository. Data are available on reasonable request. Data used for simulations are available in a public, open access repository (https://github.com/lenakba/load-injury-non-linearity-study). The Norwegian elite U-19 football data, Norwegian Premier League football data and Norwegian elite youth handball data are available on reasonable request. These are anonymised based on requirements of the Norwegian Data Protection Agency. The removal of background variables for the anonymisation renders the data unusable for any reproducibility purposes; the data are only available for the sake of transparency. ER -