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Meta-Analysis
. 2025 Aug 6:16:1462104.
doi: 10.3389/fendo.2025.1462104. eCollection 2025.

Comparative effectiveness of various combined interventions for type 2 diabetes and obesity: a systematic review and network meta-analysis

Li Cui  1 , Donglei Lu  1 , Sijie Tan  1 , Liquan Cao  1
Affiliations
Meta-Analysis

Comparative effectiveness of various combined interventions for type 2 diabetes and obesity: a systematic review and network meta-analysis

Li Cui et al. Front Endocrinol (Lausanne). .

Abstract

Background: Type 2 diabetes mellitus (T2DM) is a leading cause of severe complications, projected to affect 693 million adults globally by 2045. Addressing obesity, a key factor in T2DM, through exercise can improve metabolic health and reduce inflammation. This study conducts a Bayesian network meta-analysis to evaluate the long-term effects of various combined interventions on inflammatory markers and metabolic health in overweight or obese individuals with T2DM.

Methods: We included randomized controlled trials (RCTs) from January 2000 to April 2023 that examined the effects of aerobic training (AT), resistance training (RT), combined aerobic and resistance training (ART), physical-mental training (PMT), whole-body vibration training (WBT), and acupuncture (ACT) on BMI, lipid profiles, fasting blood glucose (FBG), HbA1c, HOMA-IR, IL-6, and TNF-α. A comprehensive literature search was performed in PubMed, Web of Science, CNKI, MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials. Data extraction and quality assessment were independently conducted by two researchers, and Bayesian network meta-analysis was performed using R software.

Results: A total of 128 RCTs were included. ART showed the most significant improvements in BMI, IL-6, and TNF-α levels. PMT was the most effective in improving lipid profiles (TG, TC, HDL-C, LDL-C) and insulin sensitivity markers (HbA1c, HOMA-IR). The SUCRA rankings indicated ART and PMT as the most beneficial interventions. Meta-regression analysis highlighted that VO2max improvements were closely associated with reductions in BMI and HbA1c.

Conclusion: ART and PMT demonstrated comprehensive benefits across multiple metabolic and inflammatory outcomes. ART effectively reduced BMI, improved glycemic control, and decreased inflammatory markers through mechanisms involving AMPK and mTOR pathways. PMT improved lipid metabolism and insulin sensitivity by reducing stress hormone levels and modulating endocrine and nervous system functions. A precise exercise prescription combining ART, PMT, AT, RT, and ACT is recommended to optimize metabolic health in T2DM patients. Future research should focus on individualized intervention strategies to enhance clinical outcomes.

Systematic review registration: PROSPERO, identifier CRD42024539376.

Keywords: aerobic training; combined aerobic and resistance training; insulin resistance; obesity; resistance training; type 2 diabetes mellitus.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of literature screening.
Figure 2
Figure 2
Summary of literature quality assessment.
Figure 3
Figure 3
(A) Network relationship diagram of BMI outcome indicators. (B) Network relationship diagram of TG outcome indicators. (C) Network relationship diagram of TC outcome indicators. (D) Network relationship diagram of HDL-C outcome indicators. (E) Network relationship diagram of LDL-C outcome indicators. (F) Network relationship diagram of FBG outcome indicators. (G) Network relationship diagram of HbA1c% outcome indicators. (H) Network relationship diagram of HOMA-IR outcome indicators. (I) Network relationship diagram of IL-6 outcome indicators. (J) Network relationship diagram of TNF-α outcome indicators eta-analysis forest plot.
Figure 4
Figure 4
(A) BMI network meta-analysis forest plot. (B) TG network meta-analysis forest plot. (C) TC network meta-analysis forest plot. (D) HDL-C network meta-analysis forest plot. (E) LDL-C network meta-analysis forest plot. (F) FBG network meta-analysis forest plot. (G) HbA1c% network meta-analysis forest plot. (H) HOMA-IR network meta-analysis forest plot. (I) IL-6 network meta-analysis forest plot. (J) TNF-α network meta-analysis forest plot.
Figure 5
Figure 5
△ Meta-regression analysis of VO2max and HbA1c%.
Figure 6
Figure 6
△ Meta-regression analysis of VO2max and HbA1c%.
Figure 7
Figure 7
Two-dimensional evaluation of the comprehensive intervention effects of different non-drug interventions on BMI and HbA1c%.
Figure 8
Figure 8
Two-dimensional evaluation of the comprehensive intervention effects of different non-drug interventions on IL-6 and TNF-α.
Figure 9
Figure 9
Comparison-correction funnel diagram (BMI).
Figure 10
Figure 10
Comparison-correction funnel diagram (TG).
Figure 11
Figure 11
Comparison-correction funnel diagram (TC).
Figure 12
Figure 12
Comparison-Correction Funnel Diagram (HDL-C).
Figure 13
Figure 13
Comparison-correction funnel diagram (LDL-C).
Figure 14
Figure 14
Comparison-correction funnel diagram (FBG).
Figure 15
Figure 15
Comparison-correction funnel diagram (HbA1c%).
Figure 16
Figure 16
Comparison-correction funnel diagram (HOMA-IR).
Figure 17
Figure 17
Comparison-correction funnel diagram (IL-6).
Figure 18
Figure 18
Comparison-correction funnel diagram (TNF-α).
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