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      The association between physical activity and low back pain: a systematic review and meta-analysis of observational studies

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          Abstract

          The aim of this review was to investigate the association between total and domain-specific physical activity (PA) and non-specific low back pain (LBP) in adults. Seven databases were searched for cohort and cross-sectional studies. Pooled estimates of the association of medium and high levels PA and LBP, using the generic inverse-variance method with fixed- and random-effects models were calculated. Twenty-four studies (15 cohort and nine cross-sectional; 95,796 participants) were included. The pooled fully adjusted risk ratios (RR) from cohort studies comparing medium with lowest activity levels were 0.90 (95%CI 0.85 to 0.96) for total PA, and 0.90 (95%CI 0.85 to 0.96) for leisure-time PA (LTPA). The pooled RR comparing highest with lowest activity levels were 1.00 (95%CI 0.92 to 1.08) for total PA, and 1.01 (95%CI 0.93 to 1.10) for LTPA. The pooled fully adjusted odds ratios (OR) from cross-sectional studies comparing medium with lowest activity levels were 0.93 (95%CI 0.65 to 1.32) for total PA, and 0.77 (95%CI 0.62 to 0.96) for LTPA. The pooled OR comparing highest with lowest activity levels were 1.05 (95%CI 0.89 to 1.23) for total PA, and 0.85 (95%CI 0.79 to 0.93) for LTPA. PA seems to be associated with lower prevalence of LBP.

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          Chapter 3. European guidelines for the management of acute nonspecific low back pain in primary care.

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            Physical activity and low back pain: a U-shaped relation?

            Being physically active is often suggested to be important in the prevention and management of low back pain. This simple view does not take into account that the relation between the level of activity and back pain may be a U-shaped curve - i.e. both inactivity and excessive activities (back-unhealthy activity) present an increased risk for back pain. We explored the U-shaped association between physical activity and chronic low back pain (3 months duration) by analyzing cross-sectional data from the Dutch population-based Musculoskeletal Complaints and Consequences Cohort study (DMC(3), 1998) of a sex-age stratified sample of 25 years and older (n=3364). Type of activity (daily routine, leisure time and sport activity), intensity of and time spent on these activities, and back exertion of sport activities were taken into account. Physical activity was not associated with chronic low back pain (CLBP) when studied by the dimension of activity, by the intensity or by the duration of physical activity. Only engaging in sport activity was associated with less CLBP (OR 0.78: 95% CI 0.66-0.93). The extremes of the total physical activity pattern were associated with CLBP. A moderate increased risk for CLBP was found for both participants with a sedentary lifestyle (OR 1.31: 95% CI 1.08-1.58) and for those being involved in physical strenuous activities (OR 1.22: 95% CI 1.00-1.49). This was especially true for women (sedentary: OR 1.44: 95% CI 1.10-1.83; physically active: OR 1.36: 95% CI 1.04-1.78). This study provides some evidence that the relation between physical activity and CLBP is U-shaped.
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              Effects of Physical Activity and Inactivity on Muscle Fatigue

              The aim of this review was to examine the mechanisms by which physical activity and inactivity modify muscle fatigue. It is well known that acute or chronic increases in physical activity result in structural, metabolic, hormonal, neural, and molecular adaptations that increase the level of force or power that can be sustained by a muscle. These adaptations depend on the type, intensity, and volume of the exercise stimulus, but recent studies have highlighted the role of high intensity, short-duration exercise as a time-efficient method to achieve both anaerobic and aerobic/endurance type adaptations. The factors that determine the fatigue profile of a muscle during intense exercise include muscle fiber composition, neuromuscular characteristics, high energy metabolite stores, buffering capacity, ionic regulation, capillarization, and mitochondrial density. Muscle fiber-type transformation during exercise training is usually toward the intermediate type IIA at the expense of both type I and IIx myosin heavy-chain isoforms. High-intensity training results in increases of both glycolytic and oxidative enzymes, muscle capillarization, improved phosphocreatine resynthesis and regulation of K+, H+, and lactate ions. Decreases of the habitual activity level due to injury or sedentary lifestyle result in partial or even compete reversal of the adaptations due to previous training, manifested by reductions in fiber cross-sectional area, decreased oxidative capacity, and capillarization. Complete immobilization due to injury results in markedly decreased force output and fatigue resistance. Muscle unloading reduces electromyographic activity and causes muscle atrophy and significant decreases in capillarization and oxidative enzymes activity. The last part of the review discusses the beneficial effects of intermittent high-intensity exercise training in patients with different health conditions to demonstrate the powerful effect of exercise on health and well being.
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                Author and article information

                Contributors
                halz2656@uni.sydney.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                3 June 2019
                3 June 2019
                2019
                : 9
                : 8244
                Affiliations
                [1 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Discipline of Physiotherapy, Faculty of Health Sciences, , The University of Sydney, ; Sydney, 2141 Australia
                [2 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Charles Perkins Centre, Prevention Research Collaboration, Sydney School of Public Health, , The University of Sydney, ; Sydney, 2006 Australia
                [3 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Sydney School of Public Health, Sydney Medical School, , The University of Sydney, ; Sydney, 2050 Australia
                Article
                44664
                10.1038/s41598-019-44664-8
                6547713
                31160632
                0c48f126-cdf7-416e-8761-d3d56b7d0f0c
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 May 2018
                : 17 May 2019
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                © The Author(s) 2019

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                epidemiology,risk factors
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                epidemiology, risk factors

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