Rhon d, Arden n, motte s, fallowfield j, fisher b, bullock g

Abstract accepted for oral presentation at the 2024 ICMM World Congress on Military Medicine.

Musculoskeletal injuries are a significant threat to military readiness; sustained by over half of individuals in many military units each year. These injuries threaten mission capabilities through reduced workforce. Mitigating injury risk requires accurate representation of the problem and adequate data to properly inform decisions. Additionally, the ability to aggregate data and make valid comparisons across settings, military branches, populations and nations is only possible when the same data elements exist. The purpose of this project was to reach international consensus on the minimum core data elements that should be collected and reported when conducting musculoskeletal injury surveillance in military settings.

Consensus was reached for two data principles and 33 minimal data elements. These elements include demographics, health behaviors, service branch, health history, exposure, and injury characteristics. This core checklist can be leveraged by clinicians, researchers and stakeholders working in military settings when comparing and harmonizing data across studies, military service branches, and countries. Ultimately, this will lead to better synthesis of evidence-based practice and ability to generate a greater number of useful prognostic models in the future.

rhon d, Drysdale l, radcliffe c, newman p

Stress fractures are common in military personnel, with training that often leads to overload and repetitive bone stress. These injuries limit duty, affect military readiness, and can end a military career. Injury mitigation is a high priority for military leadership and health, but risk profiles for stress fractures have not been fully explored. Many studies have evaluated risk factors, but meta-analyses of risk with aggregated study data are few. The purpose of this review was to conduct a systematic review of the literature to identify risk factors for stress fracture in military populations, and through meta-analysis, calculate aggregate risk profiles.

The search assessed studies published between January 1995 and September 2023 in PUBMed and CINAHL. Any study assessing risk factors for any type of stress fracture in a military population was considered, as long as an English translation was available. We excluded studies predicting disability, return to duty, or any variable not representing a stress fracture occurrence. When raw data were unavailable, we exported risk statistics as reported (e.g. risk ratios[RR], odds ratios[OR], hazard ratios [HR], rate ratios[RR]) as point estimates with 95% confidence intervals (CI) for categorical variables and means with standard deviations or 95% CI for continuous variables. We used imputation tools in Revman to estimate RR when values were not provided. We used the Prediction model Risk Of Bias ASsessment (PROBAST) Tool to assess methodological quality. We conducted a meta-analysis on unique predictor variables. We assessed heterogeneity of predictors using I2 statistics, and when heterogeneity was moderate to high (> 25%), we used a random effects model.

Despite the abundance of literature assessing risk factors for stress fractures, the variability in the capture and reporting of risk factors made data harmonization challenging. Only 3 factors were significantly associated with risk of developing a stress fracture: decreased bone mineral density in females, increased body weight, and female sex. Standardization of collecting and reporting risk factors is necessary in the future to improve the quality of meta-analysis and collective understanding or stress fracture risk factors.