Experimental study protocol of the project "MOtor function and VItamin D: Toolkit for motor performance and risk Assessment (MOVIDA)".
Musculoskeletal injuries, a public health priority also in the military context, are ascribed to several risk factors, including: increased reaction forces; low/reduced muscle strength, endurance, body mass, Vitamin D level, and bone density; inadequate lifestyles and environment. The MOVIDA Project...
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| Autores principales: | , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Public Library of Science (PLoS)
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/48e0bd43d4e94f84a75a11e936262e3b |
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| Sumario: | Musculoskeletal injuries, a public health priority also in the military context, are ascribed to several risk factors, including: increased reaction forces; low/reduced muscle strength, endurance, body mass, Vitamin D level, and bone density; inadequate lifestyles and environment. The MOVIDA Project-funded by the Italian Ministry of Defence-aims at developing a transportable toolkit (assessment instrumentation, assessment protocols and reference/risk thresholds) which integrates motor function assessment with biological, environmental and behavioural factors to help characterizing the risk of stress fracture, stress injury or muscle fatigue due to mechanical overload. The MOVIDA study has been designed following the STROBE guidelines for observational cross-sectional studies addressing healthy adults, both militaries and civilians, with varying levels of physical fitness (sedentary people, recreational athletes, and competitive athletes). The protocol of the study has been designed and validated and is hereby reported. It allows to collect and analyse anamnestic, diagnostic and lifestyle-related data, environmental parameters, and functional parameters measured through portable and wearable instrumentation during adapted 6 minutes walking test. The t-test, one and two-way ANOVA with post-hoc corrections, and ANCOVA tests will be used to investigate relevant differences among the groups with respect to biomechanical parameters; non-parametric statistics will be rather used for non-normal continuous variables and for quantitative discrete variables. Generalized linear models will be used to account for risk and confounding factors. |
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