Journal of Sport and Health Science最新文献

Background: A quality diet and an active lifestyle are both important cornerstones of cardiovascular disease (CVD) prevention. However, despite their interlinked effects on metabolic health, the 2 behaviors are rarely considered jointly, particularly within the context of CVD prevention. We examined the independent, interactive, and joint associations of diet and physical activity with CVD hospitalization, CVD mortality, and all-cause mortality.

Methods: CVD-free Australian participants aged 45-74 years (n = 85,545) reported physical activity, diet, sociodemographic, and lifestyle characteristics at baseline (2006-2009) and follow-up (2012-2015), and data were linked to hospitalization and death registries (03/31/2019 for CVD hospitalization and all-cause mortality and 12/08/2017 for CVD mortality). Diet quality was categorized as low, medium, and high based on meeting dietary recommendations. Physical activity was operationalized as (a) total moderate-to-vigorous physical activity (MVPA) as per guidelines, and (b) the composition of MVPA as the ratio of vigorous-intensity physical activity (VPA) to total MVPA. We used a left-truncated cause-specific Cox proportional hazards model using time-varying covariates.

Results: During a median of 10.7 years of follow-up, 6576 participants were admitted to the hospital for CVD and 6581 died from all causes (876 from CVD during 9.3 years). A high-quality diet was associated with a 17% lower risk of all-cause mortality than a low-quality diet, and the highest MVPA category (compared with the lowest) was associated with a 44% and 48% lower risk of CVD and all-cause mortality, respectively. Multiplicative interactions between diet and physical activity were non-significant. For all outcomes, the lowest risk combinations involved a high-quality diet and the highest MVPA categories. Accounting for total MVPA, some VPA was associated with further risk reduction of CVD hospitalization and all-cause mortality.

Conclusion: For CVD prevention and longevity, one should adhere to both a healthy diet and an active lifestyle and incorporate some VPA when possible.

Purpose: This umbrella systematic review (SR) of SRs and meta-analysis seeks to comprehensively synthesize existing literature to identify and consolidate the diverse range of risk factors contributing to running-related injuries (RRIs).

Methods: Systematic searches were conducted on June 28, 2023, across Web of Science, SPORTDiscus, Scopus, PubMed, and Cochrane Library. We included SRs, whether accompanied by meta-analyses or not, that focused on investigating risk factors for RRIs within observational studies. The methodological quality of the SRs was evaluated using the Assessing the Methodological Quality of Systematic Reviews II. To assess the extent of overlap across reviews, the corrected covered area metric was calculated.

Results: From 1509 records retrieved, 13 SRs were included. The degree of overlap between SRs was low (4%), and quality varied from critically low (n = 8) to low (n = 5). Two hundred seven outcomes assessed in 148 primary studies were identified as being associated with the occurrence of RRIs. The effect sizes of the associations for which risk measures were reported (n = 131) were classified as large (n = 30, 23%), medium (n = 38, 29%), small (n = 48, 37%) or no effect (n = 15, 11%). Running/training characteristics, health and lifestyle factors, along with morphological and biomechanical aspects, exhibit large effect sizes in increasing the risk for RRIs.

Conclusion: Drawing from the outcomes of the low-quality SRs and associations with large effect sizes, our findings indicate that running/training characteristics and health and lifestyle factors, as well as morphological and biomechanical aspects, are all implicated in elevating the risk of RRIs, emphasizing the multifactorial basis of injury incidence in running. Given the low quality and heterogeneity of SR, individual findings warrant cautious interpretation.

Background: When recommending avoidance of static stretching prior to athletic performance, authors and practitioners commonly refer to available systematic reviews. However, effect sizes (ES) in previous reviews were extracted in major part from studies lacking control conditions and/or pre-post testing designs. Also, currently available reviews conducted calculations without accounting for multiple study outcomes, with ES: -0.03 to 0.10, which would commonly be classified as trivial.

Methods: Since new meta-analytical software and controlled research articles have appeared since 2013, we revisited the available literatures and performed a multilevel meta-analysis using robust variance estimation of controlled pre-post trials to provide updated evidence. Furthermore, previous research described reduced electromyography activity-also attributable to fatiguing training routines-as being responsible for decreased subsequent performance. The second part of this study opposed stretching and alternative interventions sufficient to induce general fatigue to examine whether static stretching induces higher performance losses compared to other exercise routines.

Results: Including 83 studies with more than 400 ES from 2012 participants, our results indicate a significant, small ES for a static stretch-induced maximal strength loss (ES = -0.21, p = 0.003), with high magnitude ES (ES = -0.84, p = 0.004) for stretching durations ≥60 s per bout when compared to passive controls. When opposed to active controls, the maximal strength loss ranges between ES: -0.17 to -0.28, p < 0.001 and 0.040 with mostly no to small heterogeneity. However, stretching did not negatively influence athletic performance in general (when compared to both passive and active controls); in fact, a positive effect on subsequent jumping performance (ES = 0.15, p = 0.006) was found in adults.

Conclusion: Regarding strength testing of isolated muscles (e.g., leg extensions or calf raises), our results confirm previous findings. Nevertheless, since no (or even positive) effects could be found for athletic performance, our results do not support previous recommendations to exclude static stretching from warm-up routines prior to, for example, jumping or sprinting.

Background: Assessment and quantification of skeletal muscle within the aging population is vital for diagnosis, treatment, and injury/disease prevention. The clinical availability of assessing muscle quality through diagnostic ultrasound presents an opportunity to be utilized as a screening tool for function-limiting diseases. However, relationships between muscle echogenicity and clinical functional assessments require authoritative analysis. Thus, we aimed to (a) synthesize the literature to assess the relationships between skeletal muscle echogenicity and physical function in older adults (≥60 years), (b) perform pooled analyses of relationships between skeletal muscle echogenicity and physical function, and (c) perform sub-analyses to determine between-muscle relationships.

Methods: CINAHL, Embase, MEDLINE, PubMed, and Web of Science databases were systematically searched to identify articles relating skeletal muscle echogenicity to physical function in older adults. Risk-of-bias assessments were conducted along with funnel plot examination. Meta-analyses with and without sub-analyses for individual muscles were performed utilizing Fisher's Z transformation for the most common measures of physical function. Fisher's Z was back-transformed to Pearson's r for interpretation.

Results: Fifty-one articles (n = 5095, female = ∼2759, male = ∼2301, 72.5 ± 5.8 years, mean ± SD (1 study did not provide sex descriptors)) were extracted for review, with previously unpublished data obtained from the authors of 13 studies. The rectus femoris (n = 34) and isometric knee extension strength (n = 22) were the most accessed muscle and physical qualities, respectively. The relationship between quadriceps echogenicity and knee extensor strength was moderate (n = 2924, r = -0.36 (95% confidence interval: -0.38 to -0.32), p < 0.001), with all other meta-analyses (grip strength, walking speed, sit-to-stand, timed up-and-go) resulting in slightly weaker correlations (r:  -0.34 to -0.23, all p < 0.001). Sub-analyses determined minimal differences in predictive ability between muscle groups, although combining muscles (e.g., rectus femoris + vastus lateralis) often resulted in stronger correlations with maximal strength.

Conclusion: While correlations are modest, the affordable, portable, and noninvasive ultrasonic assessment of muscle quality is a consistent predictor of physical function in older adults. Minimal between-muscle differences suggest that echogenicity estimates of muscle quality are systemic. Therefore, practitioners may be able to scan a single muscle to estimate full-body skeletal muscle quality/composition, while researchers should consider combining multiple muscles to strengthen the model.