Dataset Information

Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study.

ABSTRACT: BACKGROUND:Attrition rate in new army recruits is higher than in incumbent troops. In the current study, we identified the risk factors for attrition due to injuries and physical fitness failure in recruit training. A variety of predictive models were attempted. METHODS:This retrospective cohort included 19,769 Army soldiers of the Australian Defence Force receiving recruit training during a period from 2006 to 2011. Among them, 7692 reserve soldiers received a 28-day training course, and the remaining 12,077 full-time soldiers received an 80-day training course. Retrieved data included anthropometric measures, course-specific variables, injury, and physical fitness failure. Multivariate regression was used to develop a variety of models to predict the rate of attrition due to injuries and physical fitness failure. The area under the receiver operating characteristic curve was used to compare the performance of the models. RESULTS:In the overall analysis that included both the 28-day and 80-day courses, the incidence of injury of any type was 27.8%. The 80-day course had a higher rate of injury if calculated per course (34.3% vs. 17.6% in the 28-day course), but lower number of injuries per person-year (1.56 vs. 2.29). Fitness test failure rate was significantly higher in the 28-day course (30.0% vs. 12.1%). The overall attrition rate was 5.2 and 5.0% in the 28-day and 80-day courses, respectively. Stress fracture was common in the 80-day course (n?=?44) and rare in the 28-day course (n?=?1). The areas under the receiver operating characteristic curves for the course-specific predictive models were relatively low (ranging from 0.51 to 0.69), consistent with "failed" to "poor" predictive accuracy. The course-combined models performed somewhat better than the course-specific models, with two models having AUC of 0.70 and 0.78, which are considered "fair" predictive accuracy. CONCLUSION:Attrition rate was similar between 28-day and 80-day courses. In comparison to the 80-day full course, the 28-day course had a lower rate of injury but a higher number of injuries per person-year and of fitness test failure. These findings suggest fitness level at the commencement of training is a critically important factor to consider when designing the course curriculum, particularly short courses.

SUBMITTER: Orr RM

PROVIDER: S-EPMC7271478 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study.

Orr Robin M RM Cohen Bruce S BS Allison Stephen C SC Bulathsinhala Lakmini L Zambraski Edward J EJ Jaffrey Mark M

Military Medical Research 20200603 1

<h4>Background</h4>Attrition rate in new army recruits is higher than in incumbent troops. In the current study, we identified the risk factors for attrition due to injuries and physical fitness failure in recruit training. A variety of predictive models were attempted.<h4>Methods</h4>This retrospective cohort included 19,769 Army soldiers of the Australian Defence Force receiving recruit training during a period from 2006 to 2011. Among them, 7692 reserve soldiers received a 28-day training cou ...[more]

PMID: 32493512

Similar Datasets

Project description:BackgroundMultiple studies have demonstrated strong associations between cardiorespiratory fitness and lower cardiovascular disease mortality. In contrast, little is known about associations of fitness with nonfatal cardiovascular events.Methods and resultsLinking individual participant data from the Cooper Center Longitudinal Study with Medicare claims files, we studied 20642 participants (21% women) with fitness measured at the mean age of 49 years and who survived to receive Medicare coverage from 1999 to 2009. Fitness was categorized into age- and sex-specific quintiles (Q) according to Balke protocol treadmill time with Q1 as low fitness. Fitness was also estimated in metabolic equivalents according to treadmill time. Associations between midlife fitness and hospitalizations for heart failure and acute myocardial infarction after the age of 65 years were assessed by applying a proportional hazards model to the multivariate failure time data. After 133514 person-years of Medicare follow-up, we observed 1051 hospitalizations for heart failure and 832 hospitalizations for acute myocardial infarction. Compared with high fitness (Q4-5), low fitness (Q1) was associated with a higher rate of heart failure hospitalization (14.3% versus 4.2%) and hospitalization for myocardial infarction (9.7% versus 4.5%). After multivariable adjustment for baseline age, blood pressure, diabetes mellitus, body mass index, smoking status, and total cholesterol, a 1 unit greater fitness level in metabolic equivalents achieved in midlife was associated with ≈20% lower risk for heart failure hospitalization after the age of 65 years (men: hazard ratio [95% confidence intervals], 0.79 [0.75-0.83]; P<0.001 and women: 0.81 [0.68-0.96]; P=0.01) but just a 10% lower risk for acute myocardial infarction in men (0.91 [0.87-0.95]; P<0.001) and no association in women (0.97 [0.83-1.13]; P=0.68).ConclusionsFitness in healthy, middle-aged adults is more strongly associated with heart failure hospitalization than acute myocardial infarction outcomes decades later in older age.

Project description:Regular physical activity seems to have a positive effect on the microbiota composition of the elderly, but little is known about the added possible benefits of strenuous endurance training. To gain insight into the physiology of the elderly and to identify biomarkers associated with endurance training, we combined different omics approaches. We aimed to investigate the gut microbiome, plasma composition, body composition, cardiorespiratory fitness, and muscle strength of lifetime elderly endurance athletes (LA) age 63.5 (95% CI 61.4, 65.7), height 177.2 (95% CI 174.4, 180.1) cm, weight 77.8 (95% CI 75.1, 80.5) kg, VO2max 42.4 (95% CI 39.8, 45.0) ml.kg-1.min-1 (n = 13) and healthy controls age 64.9 (95% CI 62.1, 67.7), height 174.9 (95% CI 171.2, 178.6) cm, weight 83.4 (95% CI 77.1, 89.7) kg, VO2max 28.9 (95% CI 23.9, 33.9), ml.kg-1.min-1 (n = 9). Microbiome analysis was performed on collected stool samples further subjected to 16S rRNA gene analysis. NMR-spectroscopic analysis was applied to determine and compare selected blood plasma metabolites mostly linked to energy metabolism. The machine learning (ML) analysis discriminated subjects from the LA and CTRL groups using the joint predictors Bacteroides 1.8E + 00 (95% CI 1.1, 2.5)%, 3.8E + 00 (95% CI 2.7, 4.8)% (p = 0.002); Prevotella 1.3 (95% CI 0.28, 2.4)%, 0.1 (95% CI 0.07, 0.3)% (p = 0.02); Intestinimonas 1.3E-02 (95% CI 9.3E-03, 1.7E-02)%, 5.9E-03 (95% CI 3.9E-03, 7.9E-03)% (p = 0.002), Subdoligranulum 7.9E-02 (95% CI 2.5E-02, 1.3E-02)%, 3.2E-02 (95% CI 1.8E-02, 4.6E-02)% (p = 0.02); and the ratio of Bacteroides to Prevotella 133 (95% CI -86.2, 352), 732 (95% CI 385, 1079.3) (p = 0.03), leading to an ROC curve with AUC of 0.94. Further, random forest ML analysis identified VO2max, BMI, and the Bacteroides to Prevotella ratio as appropriate, joint predictors for discriminating between subjects from the LA and CTRL groups. Although lifelong endurance training does not bring any significant benefit regarding overall gut microbiota diversity, strenuous athletic training is associated with higher cardiorespiratory fitness, lower body fat, and some favorable gut microbiota composition, all factors associated with slowing the rate of biological aging.

Dataset Information

Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study.

Publications

Models to predict injury, physical fitness failure and attrition in recruit training: a retrospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets