Effect of combat sports on physical fitness and activities of daily living of older adults: a systematic review and meta-analysis of randomized controlled trials
Abstract
Objective. To analyze the effects of combat sports (CS) on the physical fitness of older individuals.
Methods. A systematic review and meta-analysis were conducted following the PRISMA criteria and registered in PROSPERO (CRD42022378159). MEDLINE (via PubMed), Scopus, SPORTDiscus, and Web of Science databases were searched for randomized controlled trials (RCTs) that observed older adults submitted to CS programs that reported physical fitness outcomes. The methodological quality and the risk of bias were evaluated using the TESTEX scale and Cochrane Collaboration tool, respectively.
Results. Seventeen RCTs were included in the systematic review and 6 provided data for the meta-analysis. The CS analyzed in the studies were Tai Chi Chuan, Taekwondo, and Jiu-Jitsu, with a duration of interventions ranging from 8 to 48 weeks (≅ 57 min/session, 3 ×/week). There was evidence of increases in muscle strength, flexibility, agility, and balance in the participants who practiced CS (p < 0.05). There was a reduction in the absolute values of execution time in the Timed Up and Go (TUG) test after the intervention, indicating improvement in balance (standardized mean difference [SMD]: -0.38; 95% confidence interval (CI): -0.60 to 0.16; p < 0.01; I2 = 0%). Balance assessed by the Berg balance scale (BBS) showed significant differences (SMD: 0.44; 95% CI: 0.27 to 0.61; p < 0.01; I2 = 0%) in favor of participants in the experimental group.
Conclusions. The current results pointed out that the different CS is effective in physical fitness, improving the performance of activities of daily living in older adults.
INTRODUCTION
Physical fitness can be considered as the individual’s ability to participate in activities of daily living (ADLs) and leisure with enthusiasm and attention, without excessive fatigue. Cardiorespiratory capacity, endurance, muscle strength, morphological characteristics, and flexibility are part of the components of physical fitness and are related to the level of physical activity. In this sense, physical fitness is an important health-related parameter that can indicate the risk of developing noncommunicable diseases 1,2.
The practice of physical exercises can contribute to increasing the quality of life and preventing cardiovascular and mental diseases in older adults. Thus, different types of exercises involving cardiorespiratory capacity, balance, immunity, strength, and muscle mass are prescribed for older adults to maintain functional capacity and improve the performance of ADLs 3,4.
Combat sports (CS) are considered physical exercises and represent different sports modalities. CS includes attack and defense simulations involving upper and lower limb movements, takedowns, and a combination of these techniques 5. A large part of the world’s population practices some type of CS recreationally or in high performance. CS can be smooth, characterized by light and relaxed movements performed slowly, aiming at posture regulation, with fast, vigorous, and dynamic movements, which impose maximum force on the impact surface 6. At CS modalities most found in the literature are Aikido, Boxing, Capoeira, Fencing, French Boxing, Full Contact, Hapkido, Jet Kune Do, Judo, Jiu-Jitsu, Karate, Kempo, Kendo, Kickboxing, Kung Fu, Mixed Martial Arts, Muay Thai, Qigong, Sumo, Sambo, Soo Bahk Do, Taekwondo, Tai Chi Chuan, and Wrestling 5,7,8.
The regular practice of CS can improve physical fitness, cognitive, and psychological functions, considering the possible stimulation of factors related to physical, mental, and spiritual well-being, and the improvement of physical abilities 5,9,10. However, the effects of CS on physical fitness and their relationship with performance in ADLs in the older population are still not fully understood. Therefore, the present study aimed to analyze the effects of CS on the physical fitness of older individuals.
METHODS
This systematic review with meta-analysis was conducted in accordance with established guidelines from Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 11 and was approved by the International Prospective Register of Systematic Reviews (PROSPERO) as number CRD42022360904.
SEARCH STRATEGIES
EndNote online 20.0.1 literature management software was used to manage literature search records. Two independent and experienced authors conducted an electronic search, without language or time filters, from the 1st to the 20th of December 2022, in the MEDLINE (via PubMed), Scopus, SPORTDiscus, and Web of Science databases. Any conflict was resolved by a third author. Descriptors related to the theme were selected based on a literature review and verified by the Medical Subject Headings (MeSH) and Health Sciences Descriptors (DeCS) metadata systems. Then, the descriptors were grouped into a single Boolean phrase (Appendix A).
ELIGIBILITY CRITERIA
The inclusion criteria were designed according to the population, intervention, comparison, outcome, and study design (PICOS) strategy 12, as follows: (a) Population: older adults (aged ≥ 60 years) of both sexes. Participants with neurological (e.g., Parkinson’s disease), musculoskeletal, metabolic, and cardiovascular diseases were excluded; (b) Intervention: CS not associated with another type of training; (c) Comparison: other interventions and/or control group; (d) Outcome: physical fitness variables (e.g., balance, functional autonomy, muscle strength, flexibility, agility); (e) Study design: RCTs that analyzed the effects of CS on physical fitness in apparently healthy older adults. Articles published in conferences, systematic reviews, and meta-analyses were excluded.
RISK OF BIAS ASSESSMENT
Two experienced authors independently assessed the elected RCTs for risk of bias using the Cochrane Collaboration’s tool, available at . Any discrepancies and doubts were resolved by a third author. Bias from the following sources was assessed: 1) random sequence generation; 2) allocation concealment; 3) blinding of participants and personnel; 4) blinding of outcome assessments; 5) incomplete outcome data; 6) selective reporting; 7) other bias. Each domain has the risk of bias established as low, uncertain, or high risk of bias. The final score is assigned with the highest classification among the domains evaluated in each RCT 13.
ASSESSMENT OF METHODOLOGICAL QUALITY
For the evaluation of methodological quality, we used the Tool for the assEssment of Study qualiTy and reporting in EXercise (TESTEX), which analyzes the quality of the study, as it is a report evaluation tool, specifically designed for use in exercise training studies. TESTEX is a 15-point scale used in experimental studies, including internal validity assessment criteria and presentation of the statistical analysis used. One point is attributed to each criterion defined in the scale and zero point is attributed to the absence of these indicators. The scale comprises the following criteria: 1) specification of inclusion criteria; 2) random allocation; 3) allocation confidentiality; 4) similarity of groups in the initial or baseline phase; 5) evaluator blinding (for at least one key outcome); 6) measurement of at least one primary outcome in 85% of the allocated subjects (up to three points); 7) intention-to-treat analysis; 8) comparison between groups of at least one primary outcome (up to two points); 9) report measures of variability for all reported outcome measures; 10) monitoring of activities in control groups; 11) constancy in relative exercise intensity; 12) characteristics of exercise volume and energy expenditure 14.
DATA EXTRACTION
To extract data from the included articles, an electronic spreadsheet was used, according to the eligibility criteria, in duplicate and independently. Then, the data extracted from the articles were evaluated by two evaluators. A third evaluator was responsible for possible divergences and decisions for a consensus. The extracted variables were: authors, year of publication, country, characteristics of the study population (age, sex, and sample size), intervention data, including general and specific exercises, intervention duration (weeks), training volume (duration of the training session, in minutes, and training frequency, in times per week), evaluation and results for the CS applied to older adults in the physical fitness variables.
META-ANALYSIS
The Review Manager 5.4.1 program (RevMan version 5.4.1; The Cochrane Collaboration, Oxford, UK, available at was used to analyze physical fitness in older practitioners of CS. The statistical technique of meta-analysis is used when two or more independent studies can be grouped 15. As the variables were continuous, we chose to use the statistical method of inverse variance and the analysis model with fixed effect. Effect measure was the difference between the means with a confidence interval (CI) of 95% of the studies. The meta-analysis and the distribution of the studies were analyzed by the weight of each variable in the statistical procedure. The risk of bias in the selected studies was classified as low, uncertain, or high based on the criteria established by the Cochrane Collaboration’s tool 13. Each standardized mean difference (SMD) was weighted according to the inverse variance method. The SMD values in each RCT were pooled with a random (if heterogeneity was significant) or fixed-effects model (if heterogeneity was by chance). SMD values were interpreted as: < 0.2: weak; 0.2-0.79: moderate; ≥ 0.8: strong 16. A statistically significant effect was indicated by p < 0.05.
EVIDENCE-LEVEL ASSESSMENT
Two authors independently assessed the certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach with the GRADE PRO website, available at . GRADE specifies four categories: “high”, “moderate”, “low”, and “very low”, applied to a body of evidence. RCTs begin with high-quality evidence. Five aspects can decrease the quality of evidence: methodological limitations, inconsistency, indirect evidence, inaccuracy, and publication bias. On the other hand, three aspects can increase the quality of the evidence: effect size, dose-response gradient, and confounding factor 17. Heterogeneity between studies was analyzed using I2 statistics. I2 values are interpreted as low heterogeneity (0-50%), moderate heterogeneity (50-74%), and high heterogeneity (≥ 75%) 13,18.
RESULTS
A total of 1415 publications were found from the database search following the proposed search methodology (MEDLINE via PubMed = 445; Scopus = 211; SPORTDiscus = 47; Web of Science = 712). After using the selection criteria, a total of 17 randomized controlled trials (RCTs) were included in this systematic review. From these studies, 6 studies provided data to be included in the meta-analysis (Fig. 1).
Figure 2 summarizes the risk of bias analysis of the RCTs. In all the assessed studies, it was neither practical nor possible to blind the participants and/or evaluators. It was judged that this presented a high risk of bias. All other domains were judged to have a low to unclear risk of bias.
Table I presents the methodological quality of studies using the TESTEX tool. According to the TESTEX scale (0 to 15 points), all included studies scored above 10 points. The most sensitive points in the studies were: blinding of the evaluator to assess the outcome (100% of the studies) and blinding of the participants (94% of the studies).
Table II shows the characteristics of the studies by author/year, country of origin, study design, age (mean ± standard deviation), sex and number of participants per group, and total sample. The year of publication of the studies varied between 2004 and 2021. Regarding the country of origin, most of the studies were carried out in the United States of America (USA) (n = 5; 31%). The mean age of the experimental group (EG) and control group (CG) was 71 years. The average number of participants in the EG and CG was 40 participants. The total number of participants was 1384 (681 in the EG and 703 in the CG).
The type of intervention, the CS, the duration, and the training volume were reported in Table III. Among the CS evidenced in the present systematic review, Tai Chi Chuan appears in 12 studies (75%), Taekwondo in 4 studies (25%), and Jiu-Jitsu in 1 study (6%). The duration of the intervention varied between 8 and 48 weeks with an average of 19 weeks and the training volume had an average of 57 minutes per session with a frequency of 3 times a week.
Table IV presents the data of the evaluation variables and outcomes of the included studies. The variables walking speed, cardiorespiratory fitness, muscle strength, flexibility, and balance were investigated by different tests.
Figure 3 shows the results of the meta-analysis of the studies that investigated balance using the Time Up Go (TUG) test. The effect size was calculated by SMD with 95% CI. When calculating the effect size, the negative sign means greater effects for EG when compared to CG. Participants who received the CS intervention achieved improvements in balance (p < 0.05) when compared to the CG. The average effect size of all RCTs is represented by the diamond and should be interpreted equally. There was a reduction in the absolute values of the execution time in seconds in the TUG test after the intervention, indicating improvement in balance (95% CI: -0.60 to -0.16) with inconsistency I2 = 0% and p < 0.01.
Figure 4 presents the results of the meta-analyses of studies that used the Berg Balance Scale (BBS) for balance assessment. There was a significant difference in balance (95% CI: 0.27 to 0.61) in favor of CS participants with inconsistency I2 = 0% and p < 0.01.
Table V presents the level of evidence of the meta-analyzed studies on the balance variable using the (GRADE) tool.
DISCUSSION
This study investigated the effects of CS on variables related to physical fitness in older adults. The most researched CS was Tai Chi Chuan 19-28, followed by Taekwondo 29-32, and Jiu-Jitsu 33.
Among the physical fitness variables, balance was the most analyzed variable in the included studies (n = 11; 69%) 19-27,29,30,34, which showed improvements after the intervention period (p < 0.05). Balance can be checked dynamically and/or statically and by different testing protocols. In this systematic review, the tests used were the single-leg (right and left) stance time, one-leg balance, sensory organization vestibular test, BBS, TUG, functional reach test, and 2.44 m up-and-go test.
Cho e Roh 30, Lee et al. 31, Kim et al. 32, and Queiroz et al. 33 evaluated the cardiorespiratory capacity. These studies prioritized rapid tests to assess this variable. The tests used were aerobic endurance, heart rate, 2 min step, and 2 min walk. There were increases (p < 0.05) in the EG when compared to the CG in the post-test.
Muscle strength was another variable evaluated in some of the included studies 19,20,26-28,30-33 and had increases (p < 0.05) with CS interventions. This variable was assessed by the hand grip strength, leg strength, 30s tests chair stand, 30s arm curl, chair rise, sit-to-stand, and trunk flexion. Kujach et al. 35 conducted an RCT to evaluate muscle strength in older men and women, with a mean age of 68 years, divided into EG and CG. EG participants performed Judo training (12 weeks, 3 ×/week, 45 min/session) and showed increases (p < 0.05) in isometric knee muscle strength assessed by a dynamometer 5 used interventions with Judo and Karate (13 months, 3 ×/week, 60 min/session) and found improvements (p < 0.05) in EG in lower limb muscle strength, functional autonomy, quality of life, and bone remodeling. These variables were assessed using the 10-repetition maximum (RM) test, the Latin American Development Group for Maturity (GDLAM) protocol, the Osteoporosis Assessment Questionnaire (OPAQ), and dual-energy X-ray densitometry (DXA), respectively. These studies show that improvements in these physical fitness variables can be a potential factor in improving ADLs in older adults.
Walking speed, flexibility, and agility variables were investigated in a few studies compared to other variables in this systematic review. The walking speed variable was investigated by Li et al. 20 and Li et al. 21 and showed improvements (p < 0.05) through the 50-foot walk and dynamic gait index tests. The flexibility variable was assessed by Queiroz et al. 33, who found increases (p < 0.05) in flexibility through the lower body flexibility and upper body flexibility tests. It is noteworthy that a sedentary lifestyle and aging accelerate important motor losses in performing ADLs, such as reduced physical fitness. The regular practice of physical exercises reduces these losses and can improve the responses of walking speed, flexibility, and agility variables 36.
Studies conducted by Song et al. 19, Li et al. 20, Li et al. 21, Chyu et al. 22, Maciaszek and Osinski 23, Lee et al. 24, Chang et al. 25, Kim et al. 26, Penn et al. 27, Ma et al. 28, Youm et al. 29, Cho e Roh et al. 30, Lee et al. 31, Kim et al. 32, Queiroz et al. 33, Lam et al. 34 and Song et al. 37, analyzed different physical fitness variables (muscle strength, balance, flexibility, agility, walking speed, and cardiorespiratory capacity) in older adults. Corroborating these studies, Arkkugangas et al. 38 conducted an RCT and used Judo training on 142 participants aged between 18 and 68 years. After 10 weeks of training, increases (p < 0.05) were found in the variables muscle strength, balance, and walking speed. The tests used were mini-BESTest, tandem heel raise, tandem with heel raise with closed eyes to assess balance, backward for gait speed, and the chair stand on one leg-left/right test to assess muscle strength. It is worth remembering that these improvements in physical fitness are essential for maintaining ADL in older adults.
Regarding the risk of bias, all included studies showed a high risk in terms of blinding participants and/or evaluators.
One of the limitations of this systematic review and meta-analysis was the variety of tests to assess the same study variables. This makes it difficult to diagnose results in the intervening physical qualities used. Another important limiting factor is the small number of RCTs addressing other CS, which are distinguished both by the wide variety of modalities and by the way the training is carried out.
CONCLUSIONS
The CS described in this study are effective in improving the physical fitness of older adults, with positive effects on physical performance and functional autonomy to carry out ADLs. Favorable results were found in different physical variables, such as muscle strength, flexibility, balance, walking speed, agility, and cardiorespiratory capacity, associating CS with improved physical fitness of older individuals submitted to Tai Chi Chuan, Taekwondo, or Jiu-Jitsu. Nevertheless, it is worth emphasizing that the included studies showed great heterogeneity in the application of testing protocols in assessing the physical fitness variables, even when it was the same physical quality. On the other hand, the studies showed positive results in the CS relation and the physical fitness of older individuals. It is suggested that future studies investigate, with randomized methods, other CS (e.g., Judo, Krav Maga, Karate) and the possible effects on physical health (e.g., muscle power) and mental health (e.g., self-image, self-esteem, and depression) in older adults.
Conflict of interest statement
The authors declare no conflict of interest.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author contributions
DGL: creation of the study, construction of methods and results; JBPdC: translation, development of methods and final adjustments; CJB-P: preparation of methods and discussion; BGL: elaboration of results, assessment of risk of bias and methodological quality; LLdS: elaboration of the conclusion and assessment of the risk of bias and methodological quality; PJM-P: elaboration of the discussion; RGdSV: configuration of risk of bias and methodological quality tools and discussion.
Ethical consideration
Not applicable.
Figures and tables
Database | Search phrase |
---|---|
PubMed | Search: ((“martial arts”[MeSH Terms] OR (“martial”[All Fields] AND “arts”[All Fields]) OR “martial arts”[All Fields]) AND (“aged”[MeSH Terms] OR “aged”[All Fields] OR “elderly”[All Fields] OR “elderlies”[All Fields] OR “elderlys”[All Fields] OR “elderlys”[All Fields])) AND (clinicaltrial[Filter] OR randomizedcontrolledtrial[Filter]) |
Scopus | ( (TITLE-ABS-KEY (martial AND arts) OR TITLE-ABS-KEY (combat AND sport) AND TITLE-ABS-KEY (elderly) OR TITLE-ABS-KEY (older)) |
SPORTDiscus | AB martial arts OR AB Fighting OR AB combat sports AND AB aged OR alder adults OR elderly OR seniors OR geriatrics |
Web of Science | (((AB = (martial arts)) AND AB = (aged) |
Study | Study quality | Sub-total (0 to 5) | Study reporting | Sub-total (0 to 10) | Total (0 to 15) | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6a | 6b | 6c | 7 | 8 | 8b | 9 | 10 | 11 | 12 | ||||
Song et al. 19 | 1 | 0 | 0 | 1 | 1 | 3 | 1 | 0* | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 12 |
Li et al. 20 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Li et al. 21 | 1 | 1 | 0 | 1 | 1 | 5 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Chyu et al. 22 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Song et al. 37 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Youm et al. 29 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 9 | 12 |
Maciaszek and Osinski 23 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Lam et al. 34 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Lee et al. 24 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Queiroz et al. 33 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Chang et al. 25 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Cho and Roh 30 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Kim et al. 26 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Lee et al. 31 | 1 | 1 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 13 |
Ma et al. 28 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Penn et al. 27 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Kim et al. 32 | 1 | 1 | 0 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 10 | 14 |
Author | Year | Country | Age: mean ± SD (years) | Sex | Groups (n) | Total (n) |
---|---|---|---|---|---|---|
Song et al. 19 | 2003 | Korea | EG: 64.80 ± 6.0 | ♀ | EG: 22 | 43 |
CG: 62.5 ± 5.6 | CG: 21 | |||||
Li et al. 20 | 2004 | USA | EG: 75.30 ± 7.8 | ♀ | EG: 62 | 118 |
CG: 75.45 ± 7.8 | CG: 56 | |||||
Li et al. 21 | 2005 | USA | EG: 76.94 ± 4.7 | ♀/♂ | EG: 125 | 256 |
CG: 77.99 ± 5.2 | CG: 131 | |||||
Chyu et al. 22 | 2010 | USA | EG: 72.4 ± 6.2 | ♀ | EG: 30 | 61 |
CG: 71.3 ± 6.0 | CG: 31 | |||||
Song et al. 37 | 2010 | Australia | EG: 63.03 ± 7.3 | ♀ | EG: 30 | 65 |
CG: 61.20 ± 8.0 | CG: 35 | |||||
Youm et al. 29 | 2011 | Korea | EG1: 69.4 ± 5.8 | ♀ | EG: 20 | 30 |
EG2: 71.4 ± 7.6 | CG: 10 | |||||
CG: 70.6 ± 4.8 | ||||||
Maciaszek and Osinski 23 | 2012 | Poland | EG: 70.30 ± 5.9 | ♂ | EG: 20 | 40 |
CG: 69.10 ± 5.9 | CG: 20 | |||||
Lam et al. 34 | 2014 | China | EG: 77.20 ± 6.3 | ♀/♂ | EG: 171 | 389 |
CG: 78.30 ± 6.6 | CG: 218 | |||||
Lee et al. 24 | 2015 | USA | EG: 83.50 ± 8.9 | ♀/♂ | EG: 10 | 20 |
CG: 84.80 ± 8.1 | CG: 10 | |||||
Queiroz et al. 33 | 2016 | Brazil | EG: 69.5 ± 6.1 | ♂ | EG: 31 | 62 |
CG: 70.7 ± 6.4 | CG: 31 | |||||
Chang et al. 25 | 2016 | China | EG: 60.13 ± 2.7 | ♀ | EG: 22 | 43 |
CG: 60.30 ± 2.9 | CG: 21 | |||||
Cho and Roh 30 | 2019 | Korea | EG: 68.89 ± 4.16 | ♀ | EG: 19 | 37 |
CG: 69.00 ± 4.41 | GC: 18 | |||||
Kim et al. 26 | 2019 | Korea | EG1: 71.40 ± 3.3 | ♀ | EG1: 28 | 58 |
EG2: 70.90 ± 4.3 | EG2: 30 | |||||
Lee et al. 31 | 2019 | USA | EG: 70.00 ± 4.0 | ♀ | EG: 29 | 59 |
CG: 70.00 ± 4.0 | CG: 30 | |||||
Ma et al. 28 | 2019 | China | EG: 67.5 ± 6.3 | ♀/♂ | EG: 17 | 33 |
CG: 72.80 ± 6.7 | CG: 16 | |||||
Penn et al. 27 | 2019 | Taiwan | EG1: 76.45 ± 8.6 | ♀/♂ | EG1: 20 | 50 |
EG2: 75.27 ± 5.2 | EG2: 15 | |||||
CG: 73.40 ± 8.2 | CG: 15 | |||||
Kim et al. 32 | 2021 | Korea | EG: 72.90 ± 5.8 | ♀ | EG: 10 | 20 |
CG: 71.90 ± 3.1 | CG: 10 |
Study | Intervention | Combat sport | Duration (weeks) | Volume of training | |
---|---|---|---|---|---|
DT (min) | FT (×/week) | ||||
Song et al. 19 | EG1: warm-up, Tai Chi Chuan, cool down (20 min) | Tai Chi Chuan | 12 | 20 | 3 |
CG: no exercise | |||||
Li et al. 20 | EG: warm-up (10 min), Tai Chi Chuan (40 min), cooldown (10 min) | Tai Chi Chuan | 24 | 60 | 3 |
CG: low-impact exercise: controlled breathing, stretching, and relaxation | |||||
Li et al. 21 | EG: warm-up (5-10 min), Tai Chi practice (40 min), cooldown (5-10 min) | Tai Chi Chuan | 26 | 60 | 3 |
CG: warm-up (5-10 min), stretching, breathing, and relaxation (40 min), cooldown (5-10 min) | |||||
Chyu et al. 22 | EG: warm-up (10 min), Tai Chi Chuan (25 min), cooldown (10 min) | Tai Chi Chuan | 24 | 60 | 3 |
CG: no exercise | |||||
Song et al. 37 | EG: warm-up (10 min), Tai Chi Chuan (40-45 min), cool-down (5-10 min) | Tai Chi Chuan | 24 | 60 | 3 |
CG: no exercise | |||||
Youm et al. 29 | EG1: warm-up, taekwondo training, cooldown | Taekwondo | 12 | 60 | 3 |
EG2: warm-up, stretching, walking, cooldown | |||||
Intensity (EG1 and EG2): | |||||
weeks 1 to 4: 40-50% HRmax and 9-11 RPE | |||||
weeks 5 to 12: 50-60% of HRmax and 9-13 RPE | |||||
CG: no exercise | |||||
Maciaszek and Osinski 23 | EG: warm-up (10 min), Tai Chi Chuan (30 min), cool-down (5 min) | Tai Chi Chuan | 18 | 45 | 2 |
CG: no exercise | |||||
Lam et al. 34 | EG: Tai Chi Chuan | Tai Chi Chuan | 48 | 30 | 3 |
CG: stretching and relaxation exercises | |||||
Lee et al. 24 | EG: mobility (5 min), warm-up (10 min), Tai Chi Chuan (40 min), cooldown (5 min) | Tai Chi Chuan | 12 | 60 | 3 |
CG: limbs mobilization exercise | |||||
Queiroz et al. 33 | EG: warm-up and stretching (30 min), Jiu-Jitsu (50 min), cool down (10 min) | Jiu Jitsu | 12 | 90 | 2 |
CG: no exercise | |||||
Chang et al. 25 | EG: Tai Chi Chuan | Tai Chi Chuan | 24 | 60 | 4 |
CG: no exercise | |||||
Cho e Roh 30 | EG: warm-up, walking, stretching, taekwondo training, cooldown | Taekwondo | 16 | 60 | 5 |
Intensity: 50-80% HRmax | |||||
CG: no exercise | |||||
Kim et al. 26 | EG: warm-up (15 min), Tai Chi Chuan (35 min), cooldown (10 min) | Tai Chi Chuan | 12 | 60 | 2 |
Lee at al. 31 | EG: warm-up, taekwondo training, cooldown | Taekwondo | 12 | 60 | 3 |
Intensity: week 1 to 4: 30-40% of HRR; | |||||
last 4 weeks: increased up to 50-60% of HRR | |||||
CG: no exercise | |||||
Ma et al. 28 | EG: warm-up (10 min), Tai Chi Chuan (40 min), and cool-down (10 min) | Tai Chi Chuan | 24 | 60 | 3 |
CG: no exercise | |||||
Penn et al. 27 | EG1: individualized tai-chi exercise (30 min) | Tai Chi Chuan | 8 | 30 | 3 |
EG2: traditional Tai-Chi exercise (30 min) | |||||
CG: no exercise | |||||
Kim et al. 32 | EG: warm-up, taekwondo training, and cooldown. | Taekwondo | 12 | 90 | 3 |
Intensity: weeks 1 to 4: 40-59% of HRR | |||||
weeks 5 to 12: 60-75% of HRR CG: no exercise |
Study | Evaluation | Results |
---|---|---|
Song et al. 19 | Muscle strength | ↑ Abdominal muscle strength (30 seconds) |
Balance | ↑ Balance | |
Li et al. 20 | Muscle strength | ↑ Chair rise |
Balance | ↑ Right leg-stand; ↑ Left leg stand | |
Walking speed | ↓ 50-foot walk | |
Li et al. 21 | Balance | ↑ BBS; ↑ Functional reach, ↑ TUG |
Walking speed | ↑ 50-Foot walk; ↑ Dynamic gait index | |
Chyu et al. 22 | Balance | ↑ Stride width; ↑ Sensory Organization Test |
Song et al. 37 | Muscle strength | ↑ Knee endurance extensor |
Youm et al. 29 | Balance | ↓ COP trajectories |
Maciaszek and Osinski 23 | Balance | ↓ 8 foot up to go; ↑ Forward; ↑ Back; ↑ Maximum sway area |
Lam et al. 34 | Balance | ↑ BBS |
Lee at al. 24 | Balance | ↓ Sequential weight shifting test; ↑ FRD; ↑ Accuracy |
Queiroa et al. 33 | Muscle strength | ↑ Lower body strength; ↑ Upper body strength |
Flexibility | ↑ Lower body flexibility; ↑ Upper body flexibility | |
Cardiorespiratory fitness | ↑ Aerobic endurance | |
Chang et al. 25 | Balance | ↑ Knee joint kinesthesia; ↑Ankle joint kinesthesia |
Cho e Roh 30 | Muscle strength | ↑ 30 s chair stand; ↑ Chair sit-and-reach; ↔ 30s arm curl |
Balance | ↔ 2.44 m TUG | |
Cardiorespiratory fitness | ↑ 2 min step | |
Kim et al. 26 | Muscle strength | ↓ 5 × STS; ↑ 30s STS |
Balance | ↑ TUG; ↑ FR; ↑ OLS | |
Lee et al. 31 | Muscle strength | ↑ Hand grip strength; ↑ Leg strength |
Cardiorespiratory fitness | ↓ Heart rate | |
Ma et al. 28 | Muscle strength | ↑ Gastrocnemius muscle activation onset latency; ↑ Time to peak force of knee; ↑ Time to peak force of knee flexors extensors |
Penn et al. 27 | Muscle strength | EG1: ↑ Lower-limb muscle strength |
EG2: ↑ Lower-limb muscle strength | ||
Balance | EG1: ↑ BBS; ↓ TUG; ↑ FRD | |
EG2: ↑ BBS | ||
Kim et al. 32 | Muscle strength | ↑ Handgrip strength; ↑ Step count; ↑ Trunk flexion in a sitting position |
Cardiorespiratory fitness | ↑ 2 min walk |
Certainty assessment | No. of participants | Effect | Certainty | Importance | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
No. of studies | Study design | Risk of bias | Inconsistency | Indirectness | Imprecision | Other considerations | EG | CG | Relative (95% CI) | Absolute (95% CI) | ||
Balance (analyzed with TUG) | ||||||||||||
3 | RCTs | Not serious | Not serious | Not serious | Not serious | None | 159 | 164 | __ | Mean – 0.38 highest (– 0.60 lower to – 0.16 higher) | ⊕⊕⊕⊕HIGH | Important |
Balance (analyzed with BBS) | ||||||||||||
3 | RCTs | Not serious | Not serious | Not serious | Not serious | None | 236 | 315 | __ | Mean 0.44 highest (0.27 lower to 0.61 higher) | ⊕⊕⊕⊕ HIGH | Important |
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