• Marcus K Taylor, Lisa M Hernández, Matthew R Schoenherr, and Eodcm Jeremiah Stump.
• Naval Health Research Center, 140 Sylvester Road, San Diego, CA.
• Mil Med. 2019 Oct 1; 184 (9-10): e474-e481.

IntroductionCardiorespiratory fitness (CRF) is a crucial performance requirement of specialized military occupations. Age and physical activity are established predictors of CRF, but it is not clear how these predictors combine with each other and/or with genetic predisposition. The goal of this study was to derive inclusive explanatory models of CRF in US Navy Explosive Ordnance Disposal (EOD) operators, synthesizing conventional (e.g., age, body composition, and physical activity) and novel influences (e.g., genetic variance).Materials And MethodsIn this cross-sectional study, 40 male, active duty EOD operators completed a graded exercise test to assess maximal oxygen consumption and ventilatory threshold (VT) using the Bruce protocol. Aerobic performance was further quantified via time of test termination and time at which VT was achieved. Body composition was determined via dual x-ray absorptiometry, and physical activity was assessed by self-report. Genetic variants underlying human stress systems (5HTTLPR, BclI, -2 C/G, and COMT) were assayed. Descriptive analyses were conducted to summarize subject characteristics. Hypotheses were tested with linear regression models. Specifically, separate univariate regression models first determined associations between each of the independent and dependent variables. This protocol was approved by the Naval Health Research Center Institutional Review Board (NHRC.2015.0013).ResultsIn univariate regression models, age, body composition, physical activity, and 5HTTLPR consistently predicted CRF and/or aerobic performance (R2 range 0.07-0.55). Multivariate regression models routinely outperformed the univariate models, explaining 36-62% of variance.ConclusionThis study signifies a shift toward inclusive explanatory models of CRF and aerobic performance, accounting for combined roles of genetic, physiologic, and behavioral influences. Although we were able to quantify combined effects, we were unable to evaluate interaction effects (e.g., gene-gene, gene-behavior) due to limited statistical power. Other limitations are that this specialized military population may not readily generalize to broader populations, and the current sample was all male. Considering these limitations, we aim to replicate this study in various populations, both male and female. Despite its limitations, this study reflects a shift toward more comprehensive predictive models of CRF, explaining the unique and shared contributions of genetic predisposition, physiology, and behavior. These findings have implications for assessment, selection, and training of specialized military members, and may also impact mission success and survivability. Future studies are needed to better characterize additive, interactive, and mediated effects.© Association of Military Surgeons of the United States 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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