Abstract

BackgroundIn the present cross-sectional study, we analyzed the relationships of physical activity level, muscle strength, body composition, injury parameters, and smoking status with bone health in the non-paralyzed upper limb in adult men after spinal cord injuries (SCI).MethodsThe study covered 50 men after spinal cord injuries aged 35.6 ± 4.9 years (25 wheelchair rugby players and 25 non-athletes). Forearm bone mineral density (BMD), bone mineral content (BMC) in distal (dis) and proximal (prox) part was measured by densitometry. Body mass index (BMI) and body fat percentage (BF) were calculated. Fat mass (FM) and fat-free mass (FFM) were estimated from somatic data. An interview was conducted based on the Global Adult Tobacco Survey questionnaire. Muscle strength (maximal hand grip strength) was measured using a Jamar dynamometer.ResultsActive male smokers after SCI had significantly lower BMD dis, BMC dis and prox, T-score dis, and prox (large effect > 0.8) than male non-smokers after SCI. Physical activity was a significant predictor (positive direction) for BMC prox (adjusted R2 = 0.56; p < 0.001). The predictor of interactions of physical activity and fat mass was significant for BMC dis (positive direction, adjusted R2 = 0.58; p < 0.001). It was also found that the predictor of interactions of four variables: physical activity, fat mass, hand grip strength (positive direction), and years of active smoking (negative direction) was significant for BMD dis (adjusted R2 = 0.58; p < 0.001). The predictor of interactions of age at injury (additive direction) and the number of cigarettes smoked per day (negative direction) was significant for T-score prox (adjusted R2 = 0.43; p < 0.001). Non-smoking physically active men after SCI had the most advantageous values of mean forearm BMD.ConclusionRugby can be considered a sport that has a beneficial effect on forearm BMD. The physically active men after SCI had significantly higher bone parameters. Physical activity itself and in interactions with fat mass, hand grip strength (positive direction), and years of active smoking (negative direction) had a significant effect on bone health in non-paralyzed upper limbs. Active smoking may reduce the protective role of physical activity for bone health.

Highlights

  • In the present cross-sectional study, we analyzed the relationships of physical activity level, muscle strength, body composition, injury parameters, and smoking status with bone health in the non-paralyzed upper limb in adult men after spinal cord injuries (SCI)

  • Methods of bone tissue evaluation bone mineral content (BMC) and Bone mineral density (BMD) of the non-dominant forearm in distal and proximal parts were measured by means of dual-energy X-ray absorptiometry (DXA, Norland, Swissray, Fort Atkinson, WI, USA) The Norland Dualenergy X-ray absorptiometry (DXA) instruction recommends two measurement points: on the 1/3 proximal and distal sites of the bone according to the adopted densitometry methodology and the recommendations of the International Society for Clinical Densitometry (ISCD)

  • It was found that the predictor of interactions of four variables: physical activity, fat mass and hand grip strength as well as years of active smoking was significant for BMD dis

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Summary

Introduction

In the present cross-sectional study, we analyzed the relationships of physical activity level, muscle strength, body composition, injury parameters, and smoking status with bone health in the non-paralyzed upper limb in adult men after spinal cord injuries (SCI). The process stabilizes until it reaches equilibrium between 12 and 36 months after the injury. Indicate that the process does not stabilize until approximately 7 to 8 years after injury [1,2,3,4]. Bone mineral density (BMD) in the different parts of the skeleton and limbs declines precipitously in the first 2 years after SCI. For SCI patients, it is the upper limbs that become the primary driver of wheelchair locomotion. It is recommended to monitor BMD in early-stage SCI patients combined with the identification of factors leading to lower BMD [1]

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