| Literature DB >> 35799947 |
Hongshuo Shi1, Shaoting Wang2, Yufeng Zhang1, Pulin Liu1, Chengda Dong1, Dan Wang1, Guomin Si3, Wenbo Wang4, Yujie Li4.
Abstract
Objectives: Tai chi (TC) is a potential complementary treatment for type 2 diabetes mellitus (T2DM). This overview systematically summarizes and evaluates the existing evidence of TC in the treatment of T2DM.Entities:
Mesh:
Year: 2022 PMID: 35799947 PMCID: PMC9256439 DOI: 10.1155/2022/6587221
Source DB: PubMed Journal: J Diabetes Res Impact factor: 4.061
Search strategy for the PubMed database.
| Query | Search term |
|---|---|
| #1 | “Tai Ji”[Mesh] |
| #2 | “Tai-ji” OR “Tai Chi” OR “Chi, Tai” OR “Tai Ji Quan” OR “Ji Quan, Tai” OR “Quan, Tai Ji” OR “Taiji" OR “Taijiquan” OR “T'ai Chi” OR “Tai Chi Chuan” OR “Tai ji” |
| #3 | #1 OR #2 |
| #4 | “Diabetes Mellitus, Type 2”[Mesh] |
| #5 | “Diabetes Mellitus, Noninsulin-Dependent” OR “Diabetes Mellitus, Ketosis-Resistant” OR “Diabetes Mellitus, Ketosis Resistant” OR “Ketosis-Resistant Diabetes Mellitus” OR “Diabetes Mellitus, Non Insulin Dependent” OR “Diabetes Mellitus, Non-Insulin-Dependent” OR “Non-Insulin-Dependent Diabetes Mellitus” OR “Diabetes Mellitus, Stable” OR “Stable Diabetes Mellitus” OR “Diabetes Mellitus, Type II” OR "NIDDM” OR “Diabetes Mellitus, Noninsulin Dependent” OR “Diabetes Mellitus, Maturity-Onset” OR “Diabetes Mellitus, Maturity Onset” OR “Maturity-Onset Diabetes Mellitus” OR “Maturity Onset Diabetes Mellitus” OR “MODY” OR “Diabetes Mellitus, Slow-Onset” OR “Diabetes Mellitus, Slow Onset” OR “Slow-Onset Diabetes Mellitus” OR “Type 2 Diabetes Mellitus” OR “Noninsulin-Dependent Diabetes Mellitus” OR “Noninsulin Dependent Diabetes Mellitus" OR “Maturity-Onset Diabetes” OR “Diabetes, Maturity-Onset” OR “Maturity Onset Diabetes" OR “Type 2 Diabetes” OR “Diabetes, Type 2” OR “Diabetes Mellitus, Adult-Onset" OR “Adult-Onset Diabetes Mellitus” OR “Diabetes Mellitus, Adult Onset” |
| #6 | #4 OR #5 |
| #7 | Meta-Analysis as Topic [Mesh] |
| #8 | “Systematic review” OR “meta-analysis” OR “meta analysis” OR “meta-analyses” OR “Review, Systematic” |
| #9 | #7 OR #8 |
| #10 | #3 AND #6 AND #9 |
Figure 1The flowchart of the screening process.
Characteristics of the included SRs/MAs. Note: N: nonexercise; AE: aerobic exercise; ST: standard treatment.
| Author, year (country) | Trials (subjects) | Intervention group | Control group | Quality assessment | Main results |
|---|---|---|---|---|---|
| Mengyao Chao, 2018 (China) [ | 14 (798) | TC | N, AE | Jadad | TC can effectively influence the management of blood glucose and HbA1c in patients with T2DM. Long-term adherence to TC has a better effect on reducing blood sugar and HbA1c levels in patients with T2DM |
| Myeong Soo Lee, 2015 (South Korea) [ | 15 (754) | TC, TC+control group | N, ST, AE | Cochrane criteria | In conclusion, the evidence that TC may benefit people with T2DM compared with exercise therapy is not convincing. In addition, evidence from RCTs comparing TC with conventional antidiabetic drugs appears to be mixed |
| Shuai Guo, 2021 (China) [ | 23 (1,800) | TC, TC+control group | ST, AE | Cochrane criteria | Compared with routine clinical treatment, TC has better effects on blood sugar control, lipid metabolism, and body composition and is superior to aerobic exercise in improving partial metabolic control. The optimal intervention time window for TC may vary for different metabolic markers |
| Ting-Wei Xia, 2019 (China) [ | 17 (774) | TC, TC+control group | N, ST, AE | Cochrane criteria | TC appears to be effective in treating T2DM compared to control interventions. Different training times and methods will lead to differences in effects |
| Zonglei Zhou, 2019 (China) [ | 23 (1,235) | TC | AE, ST | PEDro scale | TC was effective in controlling biomedical outcomes and improving the quality of life-related outcomes in patients with T2DM, but no effects on balance and fasting insulin were observed |
| Yao Ge, 2020 (China) [ | 13 (856) | TC, TC+control group | N, ST | Cochrane criteria | TC exercise can control blood sugar level and regulate lipoprotein concentration in patients with T2DM, which can provide the basis for exercise therapy for later stage diabetes |
| Yongjin Liu, 2017 (China) [ | 10 (740) | TC | N, AE | Cochrane criteria | TC exercise can regulate the level of glucose and lipid metabolism and improve the quality of life in patients with T2DM and can be used as an important part of exercise therapy for diabetes |
| Qing Tang, 2017 (China) [ | 11 (764) | TC | CT | Cochrane criteria | TC helps improve blood sugar control, weight loss, blood lipid regulation, and quality of life in patients with T2DM |
Result of the AMSTAR-2 assessments. Note: Y: yes; PY: partial yes; N: no; VL: very low; L: low. Note: key items are marked in italic.
| Author, year (country) | Q1 |
| Q3 |
| Q5 | Q6 |
| Q8 |
| Q10 |
| Q12 |
| Q14 |
| Q16 | Quality |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mengyao Chao, 2018 (China) [ | Y | PY | Y | Y | Y | Y | N | Y | Y | N | Y | Y | N | Y | Y | Y | VL |
| Myeong Soo Lee, 2015 (South Korea) [ | Y | PY | Y | Y | Y | Y | N | Y | Y | N | Y | Y | Y | Y | N | Y | VL |
| Shuai Guo, 2021 (China) [ | Y | PY | Y | Y | Y | Y | N | Y | Y | N | Y | Y | N | Y | N | Y | VL |
| Ting-Wei Xia, 2019 (China) [ | Y | PY | Y | Y | Y | Y | N | Y | Y | N | Y | Y | Y | Y | Y | Y | VL |
| Zonglei Zhou, 2019 (China) [ | Y | PY | Y | Y | Y | Y | N | Y | Y | N | Y | Y | N | Y | Y | Y | VL |
| Yao Ge, 2020 (China) [ | Y | PY | Y | PY | Y | Y | N | N | Y | N | Y | Y | N | Y | N | Y | VL |
| Yongjin Liu, 2017 (China) [ | Y | PY | Y | PY | Y | Y | N | Y | Y | N | Y | Y | N | Y | Y | Y | VL |
| Qing Tang, 2017 (China) [ | Y | PY | Y | PY | Y | Y | N | Y | Y | N | Y | Y | N | Y | N | Y | VL |
Results of the ROBIS assessments. Note: √: low risk; ×: high risk.
| Author, year (country) | Phase 1 | Phase 2 | Phase 3 | |||
|---|---|---|---|---|---|---|
| Assessing relevance | Domain 1: study eligibility criteria | Domain 2: identification and selection of studies | Domain 3: collection and study appraisal | Domain 4: synthesis and findings | Risk of bias in the review | |
| Mengyao Chao, 2018 (China) [ | √ | √ | √ | √ | √ | × |
| Myeong Soo Lee, 2015 (South Korea) [ | √ | √ | √ | × | × | √ |
| Shuai Guo, 2021 (China) [ | √ | √ | √ | √ | × | × |
| Ting-Wei Xia, 2019 (China) [ | √ | √ | √ | √ | √ | √ |
| Zonglei Zhou, 2019 (China) [ | √ | √ | √ | √ | × | × |
| Yao Ge, 2020 (China) [ | √ | √ | × | × | × | × |
| Yongjin Liu, 2017 (China) [ | √ | √ | × | √ | √ | × |
| Qing Tang, 2017 (China) [ | √ | √ | × | × | × | × |
Results of the PRISMA checklist. Note: Y: yes; N: no.
| Section/topic | Items | Mengyao Chao, 2018 (China) [ | Myeong Soo Lee, 2015 (South Korea) [ | Shuai Guo, 2021 (China) [ | Ting-Wei Xia, 2019 (China) [ | Zonglei Zhou, 2019 (China) [ | Yao Ge, 2020 (China) [ | Yongjin Liu, 2017 (China) [ | Qing Tang, 2017 (China) [ | Number of yes (%) |
|---|---|---|---|---|---|---|---|---|---|---|
| Title | Q1. Title | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
|
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| Abstract | Q2. Structured summary | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
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| Introduction | Q3. Rationale | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
| Q4. Objectives | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
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| Methods | Q5. Protocol and registration | N | N | N | N | N | N | N | N | 0% |
| Q6. Eligibility criteria | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q7. Information sources | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q8. Search | N | N | Y | N | Y | N | N | N | 25% | |
| Q9. Study selection | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q10. Data collection process | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q11. Data items | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q12. Risk of bias in individual studies | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q13. Summary measures | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q14. Synthesis of results | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q15. Risk of bias across studies | N | N | N | Y | Y | N | N | N | 25.00% | |
| Q16. Additional analyses | Y | N | Y | Y | Y | N | N | Y | 62.50% | |
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| Results | Q17. Study selection | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
| Q18. Study characteristics | Y | Y | Y | Y | Y | N | Y | Y | 88% | |
| Q19. Risk of bias within studies | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q20. Results of individual studies | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q21. Synthesis of results | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q22. Risk of bias across studies | Y | N | N | Y | Y | N | Y | N | 50.00% | |
| Q23. Additional analysis | Y | N | Y | Y | Y | N | Y | Y | 75.00% | |
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| Discussion | Q24. Summary of evidence | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
| Q25. Limitations | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
| Q26. Conclusions | Y | Y | Y | Y | Y | Y | Y | Y | 100% | |
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| Funding | Q27. Funding | Y | Y | Y | Y | Y | Y | Y | Y | 100% |
Results of evidence quality. ①The included studies have a large bias in methodology such as randomization, allocation concealment, and blinding. ②The confidence interval overlaps less, or the I2 value of the combined results was larger. ③The sample size from the included studies does not meet the optimal sample size, or the 95% confidence interval crosses the invalid line. ④The funnel chart is asymmetry. ∗The 95% confidence interval does not cross the invalid line.
| Author, year (Country) | Outcomes | Studies (participants) | Limitations | Inconsistency | Indirectness | Imprecision | Publication bias | Relative effect (95% CI) | Quality |
|---|---|---|---|---|---|---|---|---|---|
| Mengyao Chao, 2018 (China) [ | FBG (tai chi versus nonexercise) | 10 (489) | -1① | -1② | 0 | 0 | -1④ | MD = −1.39 (-1.95, -0.84)∗ | Very low |
| FBG (tai chi versus other aerobic exercises) | 7 (342) | -1① | -1② | 0 | -1③ | -1④ | MD = −0.21 (-0.61, 0.19) | Very low | |
| HbA1c (tai chi versus nonexercise) | 7 (293) | -1① | 0 | 0 | -1③ | -1④ | MD = −0.73 (-0.95, -0.52)∗ | Very low | |
| HbA1c (tai chi versus other aerobic exercises) | 7 (372) | -1① | -1② | 0 | -1③ | -1④ | MD = −0.19 (-0.37, 0.00)∗ | Very low | |
| PBG (tai chi versus nonexercise) | 5 (162) | -1① | 0 | 0 | -1③ | -1④ | MD = −2.07 (-2.89, -1.26)∗ | Very low | |
| PBG (tai chi versus other aerobic exercises) | 3 (84) | -1① | 0 | 0 | -1③ | -1④ | MD = −0.44 (-1.42, 0.54) | Very low | |
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| Myeong Soo Lee, 2015 (South Korea) [ | HbA1c (tai chi versus ST) | 3 (127) | -1① | 0 | 0 | -1③ | -1④ | MD = −0.54 (−1.23, 0.15) | Very low |
| HbA1c (tai chi versus other aerobic exercises) | 2 (148) | -1① | 0 | 0 | -1③ | -1④ | MD = 0.00 (−0.31, 0.31) | Very low | |
| HbA1c (no) | 2 (84) | -1① | -1② | 0 | -1③ | -1④ | MD = −1.58 (−3.83, 0.67) | Very low | |
| FBG (tai chi versus ST) | 4 (188) | -1① | 0 | 0 | -1③ | -1④ | MD = −1.57 (−2.34, −0.80)∗ | Very low | |
| FBG (tai chi versus other aerobic exercises) | 4 (212) | -1① | 0 | 0 | -1③ | -1④ | MD = −0.03 (−0.49, 0.42) | Very low | |
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| Shuai Guo, 2021 (China) [ | FBG (tai chi versus ST) | 15 (1,023) | -1① | -1② | 0 | 0 | -1④ | MD = −1.04 (-1.42, -0.66)∗ | Very low |
| FBG (tai chi versus other aerobic exercises) | 8 (619) | -1① | -1② | 0 | -1③ | -1④ | MD = −0.03 (-0.30, 0.23) | Very low | |
| HbA1c (tai chi versus ST) | 9 (749) | -1① | -1② | 0 | 0 | -1④ | MD = −0.73 (-1.03, -0.43)∗ | Very low | |
| HbA1c (tai chi versus other aerobic exercises) | 5 (504) | -1① | 0 | 0 | 0 | -1④ | MD = −0.33 (-0.61, 0.04)∗ | Low | |
| PBG (tai chi versus ST) | 2 (260) | -1① | 0 | 0 | -1③ | -1④ | MD = −1.58 (-1.94,-1.22)∗ | Very low | |
| TCL (tai chi versus ST) | 11 (868) | -1① | -1② | 0 | 0 | -1④ | MD = −0.51 (-0.88, -0.14)∗ | Very low | |
| TCL (tai chi versus other aerobic exercises) | 5 (423) | -1① | 0 | 0 | -1③ | -1④ | MD = −0.08 (-0.24, 0.09) | Very low | |
| TG (tai chi versus ST) | 9 (745) | -1① | -1② | 0 | 0 | -1④ | MD = −0.40 (-0.72, -0.07)∗ | Very low | |
| TG (tai chi versus other aerobic exercises) | 4 (332) | -1① | -1② | 0 | -1③ | -1④ | MD = 0.04 (−0.22, 0.31) | Very low | |
| HDL (tai chi versus ST) | 9 (798) | -1① | -1② | 0 | 0 | -1④ | MD = 0.39 (0.14, 0.63)∗ | Very low | |
| HDL (tai chi versus other aerobic exercises) | 5 (538) | -1① | 0 | 0 | 0 | -1④ | MD = 0.24 (0.07, 0.41)∗ | Low | |
| LDL (tai chi versus ST/other aerobic exercises) | 9 (730) | -1① | -1② | 0 | 0 | -1④ | MD = −0.79 (-1.27, -0.30)∗ | Very low | |
| BMI (tai chi versus ST) | 5 (358) | -1① | 0 | 0 | 0 | -1④ | MD = −1.15 (-1.79, -0.51)∗ | Low | |
| SBP (tai chi versus ST) | 5 (390) | -1① | 0 | 0 | -1③ | -1④ | MD = −11.86 (-14.47, -9.25)∗ | Very low | |
| DBP (tai chi versus ST) | 5 (390) | -1① | -1② | 0 | -1③ | -1④ | MD = −7.93 (-12.39, -3.46)∗ | Very low | |
| FINs (tai chi versus ST) | 3 (255) | -1① | 0 | 0 | -1③ | -1④ | MD = −1.02 (-1.39, -0.64)∗ | Very low | |
| HOMA-IR (tai chi versus ST) | 3 (255) | -1① | -1② | 0 | -1③ | -1④ | MD = −0.65 (-1.01, -0.30)∗ | Very low | |
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| Ting-Wei Xia, 2019 (China) [ | FBG | 13 (616) | -1① | -1② | 0 | 0 | -1④ | SMD = −0.54 (-0.91, -0.16)∗ | Very low |
| HbA1c | 9 (517) | -1① | -1② | 0 | 0 | -1④ | SMD = −0.68 (-1.17, -0.19)∗ | Very low | |
| TCL | 8 (343) | -1① | 0 | 0 | -1③ | -1④ | SMD = −0.35 (-0.54, -0.16)∗ | Very low | |
| TG | 8 (359) | -1① | 0 | 0 | -1③ | -1④ | SMD = −0.19 (-0.31, -0.07)∗ | Very low | |
| HDL | 6 (290) | -1① | 0 | 0 | -1③ | -1④ | SMD = 0.04 (− 0.01, 0.09) | Very low | |
| LDL | 6 (290) | -1① | -1② | 0 | -1③ | -1④ | SMD = −0.49 (− 1.06, 0.08) | Very low | |
| BMI | 6 (296) | -1① | 0 | 0 | -1③ | -1④ | SMD = −0.61 (− 0.85, − 0.38)∗ | Very low | |
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| Zonglei Zhou, 2019 (China) [ | FBG | 21 (1,115) | -1① | -1② | 0 | 0 | 0 | SMD = −0.67 (-0.87, -0.47)∗ | Low |
| HbA1c | 12 (714) | 0 | 0 | 0 | 0 | 0 | MD = −0.53 (-0.62, -0.44)∗ | High | |
| FINs | 8 (500) | -1① | -1② | 0 | -1③ | 0 | SMD = −0.32 (-0.71, 0.07) | Very low | |
| HOMA-IR | 5 (332) | 0 | 0 | 0 | -1③ | 0 | MD = −0.41 (-0.78, -0.04)∗ | Moderate | |
| TCL | 10 (658) | -1① | -1② | 0 | 0 | 0 | SMD = −0.59 (-0.90, -0.27)∗ | Low | |
| BMI | 7 (388) | 0 | 0 | 0 | -1③ | 0 | MD = −0.82 (-1.28, -0.37)∗ | Moderate | |
| Balance | 2 (107) | 0 | -1② | 0 | -1③ | 0 | MD = 2.71 (-3.29, 8.71) | Low | |
| SBP | 5 (290) | 0 | -1② | 0 | -1③ | 0 | MD = −10.03 (-15.78, -4.29)∗ | Low | |
| DBP | 5 (290) | 0 | 0 | 0 | -1③ | 0 | MD = −4.85 (-8.23, -1.47)∗ | Moderate | |
| Physical function | 5 (389) | -1① | -1② | 0 | -1③ | 0 | MD = 7.07 (0.79, 13.35)∗ | Very low | |
| Bodily pain | 5 (389) | -1① | 0 | 0 | -1③ | 0 | MD = 4.30 (0.83, 7.77)∗ | Low | |
| Social function | 6 (426) | 0 | -1② | 0 | 0 | 0 | MD = 13.84 (6.22, 21.47)∗ | Moderate | |
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| Yao Ge, 2020 (China) [ | FBG | 9 (560) | -1① | -1② | 0 | 0 | -1④ | SMD = −0.607 (-0.930, -0.284)∗ | Very low |
| HbA1c | 7 (434) | -1① | -1② | 0 | 0 | -1④ | SMD = −0.585 (-0.784, -0.386)∗ | Very low | |
| TCL | 7 (533) | -1① | -1② | 0 | -1③ | -1④ | SMD = −0.418 (-0.897, 0. 061) | Very low | |
| TG | 6 (480) | -1① | -1② | 0 | 0 | -1④ | SMD = −0.833 (-1.383, -0.283)∗ | Very low | |
| HDL | 4 (420) | -1① | -1② | 0 | 0 | -1④ | SMD = 0.458 (0. 063, 0.852)∗ | Very low | |
| LDL | 3 (76) | -1① | -1② | 0 | -1③ | -1④ | SMD = −1.252 (-2.305, -0.199) | Very low | |
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| Yongjin Liu, 2017 (China) [ | FBG | 9 (727) | -1① | 0 | 0 | 0 | 0 | SMD = −0.39 (-0.54, -0.24)∗ | Moderate |
| HbA1c | 7 (645) | -1① | 0 | 0 | 0 | 0 | MD = −0.59 (-0.73, -0.44)∗ | Moderate | |
| TCL | 7 (612) | -1① | -1② | 0 | -1③ | 0 | SMD = −0.24 (-0.58, 0.10) | Very low | |
| TG | 7 (612) | -1① | -1② | 0 | 0 | 0 | SMD = −0.52 (-0.85, -0.19)∗ | Low | |
| HDL | 6 (566) | -1① | 0 | 0 | 0 | 0 | SMD = 0.31 (0.14, 0.47)∗ | Moderate | |
| LDL | 6 (462) | -1① | -1② | 0 | 0 | 0 | MD = −0.32 (-0.59, -0.05)∗ | Low | |
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| Qing Tang, 2017 (China) [ | FBG | 7 (354) | -1① | -1② | 0 | -1③ | -1④ | MD = −0.74 (-1.32, -0.16)∗ | Very low |
| HbA1c | 7 (572) | -1① | -1② | 0 | 0 | -1④ | MD = −0.77 (-1.16, -0.39)∗ | Very low | |
| BMI | 4 (316) | -1① | 0 | 0 | -1③ | -1④ | MD = −1.64, (-2.35, -0.92)∗ | Very low | |
| TG | 6 (518) | -1① | -1② | 0 | 0 | -1④ | MD = −0.33 (-0.49, -0.17)∗ | Very low | |
| TCL | 6 (518) | -1① | -1② | 0 | 0 | -1④ | MD = −0.08 (-0.33, -0.48)∗ | Very low | |
| Quality of Life | 2 (264) | -1① | 0 | 0 | -1③ | -1④ | MD = 45.47 (18.24, 72.71)∗ | Very low | |