ObjectivesTo determine whether the relationship between training load and injury risk is non-linear and investigate ways of handling non-linearity.MethodsWe 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.ResultsNo 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.ConclusionThe 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.

Talent development is integral to the policy and organizational practice of competitive sport, but has also been associated with excessive amounts of training and competition, and athlete injuries and illnesses. The lack of available prospective data on the training and match activities of youth athletes and their health problems is therefore of concern. The aim of this study was two-fold: (a) to examine the amount and frequency of training load, match activities, injury and illness incidence, and prevalence among Norwegian youth elite handball players over the course of the 2018–2019 competitive season; and (b) to explore whether the injury rates are related to the sex or competition level of players, or their membership of the youth international team. We recruited 205 handball players (64% female, 36% male), aged 15–18 years (17.2 years ± 0.9) from five different sport school programs in southeast Norway. Data were collected daily from September 2018 to May 2019, during the competitive handball season. The variables included types of athlete activities, the number of activities, the rating of perceived exertion (RPE), and the duration of training and matches. Injury and illness data were collected weekly using the Oslo Sports Trauma Research Center (OSTRC) questionnaire. The mean number of matches per week per player was 0.9 ± 1.29; the number of weekly training events was 6.1 ± 4.4; and the mean weekly session RPE was 986 ± 1 412 arbitrary units. The players reported a total of 472 injuries, and the mean number of injuries per player was 2.3 ± 2.9. The results demonstrated a 53% weekly injury prevalence, of which 38% were categorized as substantial injuries. Male players and players who participated at the highest level of senior competition and/or the youth international team reported significantly lower weekly incidences of health problems, compared to other players. Our findings showed that players enrolled in sport school programs are exposed to high training and competition loads, and that both general and substantial health problems are common. The potential implications for talent development and future research are discussed.

No abstract

ObjectivesDetermine how to assess the cumulative effect of training load on the risk of injury or health problems in team sports.MethodsFirst, we performed a simulation based on a Norwegian Premier League male football dataset (n players=36). Training load was sampled from daily session rating of perceived exertion (sRPE). Different scenarios of the effect of sRPE on injury risk and the effect of relative sRPE on injury risk were simulated. These scenarios assumed that the probability of injury was the result of training load exposures over the previous 4 weeks. We compared seven different methods of modelling training load in their ability to model the simulated relationship. We then used the most accurate method, the distributed lag non-linear model (DLNM), to analyse data from Norwegian youth elite handball players (no. of players=205, no. of health problems=471) to illustrate how assessing the cumulative effect of training load can be done in practice.ResultsDLNM was the only method that accurately modelled the simulated relationships between training load and injury risk. In the handball example, DLNM could show the cumulative effect of training load and how much training load affected health problem risk depending on the distance in time since the training load exposure.ConclusionDLNM can be used to assess the cumulative effect of training load on injury risk.

Background and purpose: Intraoperative periprosthetic femoral fractures (IPFFs) can occur during primary total hip arthroplasty (THA). We describe the incidence of IPFFs during THA in Norway and estimate potential risk factors that could be associated with IPFFPatients and methods — Data from the Norwegian Arthoplasty Register (1987–2020) was used: 2,268 IPFFs from 218,423 primary THAs in 172,598 patients. The following factors were analyzed: sex, age, diagnosis, previous operation on the same hip, surgical approach, and stem fixation technique. Association of these factors with IPFF risk was assessed using multivariable Poisson regression. Results: IPFF occurred during 2,268 operations with an incidence of 1.0% among all primary THAs. The risk of IPFF was associated with female sex (relative risk 1.8; 99% CI 1.5–2.1), age 80–90 years and age over 90 years (compared with age 60–70 years: 1.3; CI 1.0–1.6 and 2.6; CI 1.6–4.3, respectively), non-osteoarthritis diagnoses (2.2; CI 1.9–2.6), previous surgery to the same hip (1.8; CI 1.5–2.2), lateral approach (compared with the posterior approach: 1.5; CI 1.1–2.0), and cementless stem fixation (2.7; CI 2.0–3.6). Interpretation: Surgeons should be aware of the factors associated with an increased risk of IPFF: female sex, age above 80 years, non-osteoarthritis diagnoses, and previous surgery to the same hip. Cemented stem fixation and posterior approach should be favored in high-risk patients, such as elderly women.