Imagine this: Millions of people worldwide grapple with type 2 diabetes, a condition that not only disrupts blood sugar levels but also quietly erodes muscle strength and mass, setting the stage for a cascade of severe health challenges. That's the sobering reality of sarcopenia in diabetes patients—a hidden threat that's gaining attention for its role in predicting worse outcomes. But here's where it gets intriguing: While some experts hail early screening as a game-changer, others debate whether focusing on sarcopenia alone overshadows other diabetes complications. Stick around as we dive into this eye-opening research that'll make you rethink muscle health in diabetes care.
Sarcopenia as a Forecaster of Adverse Health Consequences in Individuals with Type 2 Diabetes Mellitus: An Exhaustive Systematic Review and Meta-Analysis
- Review Article
- Freely Accessible (via https://www.springernature.com/gp/open-science/about/the-fundamentals-of-open-access-and-open-research)
- Released: November 5, 2025
Diabetology & Metabolic Syndrome (accessible at https://dmsjournal.biomedcentral.com/) volume 17, Article 416 (2025) Reference this Piece
Abstract
Background
Sarcopenia, a condition marked by the gradual decline in muscle bulk and function, represents a pressing global health concern. It's closely linked to heightened death rates and increased risks of complications among those living with type 2 diabetes mellitus (T2DM). Yet, existing studies on unfavorable outcomes in T2DM patients with sarcopenia remain fragmented and incomplete, leaving a critical gap in consolidated knowledge.
Methods
We conducted a thorough exploration of databases including Embase, PubMed, Scopus, and Web of Science to locate pertinent research evaluating sarcopenia's influence on death rates, cardiovascular disease (CVD), and complications among T2DM sufferers. The quality of the incorporated studies underwent assessment via the Newcastle-Ottawa Scale and the Joanna Briggs Institute Critical Appraisal tool. We synthesized the combined hazard ratios and odds ratios, complete with their 95% confidence intervals, for mortality, CVD, and complication estimates.
Results
Our meta-analysis drew from 15 studies, with an overall low risk of bias. Individuals with T2DM and sarcopenia faced a markedly elevated mortality risk, evidenced by a combined hazard ratio of 1.72 (95% CI = 1.28–2.32). Likewise, sarcopenia correlated with a heightened hazard ratio for CVD at 1.94 (95% CI = 1.67–2.25). Additionally, sarcopenia tied to an increased likelihood of developing diabetes-related complications, as shown by a hazard ratio of 1.12 (95% CI = 1.09–1.15) and an odds ratio of 2.49 (95% CI = 1.53–4.05).
Conclusions
Sarcopenia serves as a harbinger of detrimental outcomes, including death, CVD, and diabetic complications, in T2DM patients. Our findings emphasize the urgent need to incorporate sarcopenia screening into standard T2DM care routines to enable timely risk assessment.
Introduction
Type 2 diabetes mellitus (T2DM) has risen as a major worldwide health epidemic, impacting nearly 500 million people globally and showing no signs of slowing down in prevalence [1]. It's defined by resistance to insulin's effects and frequently co-occurs with obesity [2]. This insulin resistance is part of a broader multisystem inflammatory process, intertwined with genetic and environmental factors that predispose individuals to cardiovascular issues and other complications [3,4,5]. Among the myriad complications of T2DM, sarcopenia— a condition in older adults characterized by the steady reduction in muscle volume and strength [9]—has lately drawn significant scrutiny as both a complication and a standalone predictor of poor health results in the diabetic community [6,7,8].
Sarcopenia plagues roughly 15–20% of T2DM patients [10]. This high occurrence stems from intricate interplay between metabolic imbalances, ongoing inflammation, and bodily dysfunction [11,12,13]. Notably, widespread inflammation plays a pivotal role in these dynamics [14]. Aligning with its dual nature in T2DM as complication and predictor, sarcopenia fuels various detrimental outcomes like escalated mortality, frailty, and heightened fall risks [15,16], severely diminishing patients' well-being and imposing hefty socioeconomic costs [17].
When T2DM hastens muscle deterioration and functional loss [18], the presence of sarcopenia complicates treatment even further, amplifying the chances of grave secondary conditions [19,20]. Despite mounting research connecting sarcopenia to harmful health trajectories in T2DM sufferers [21,22,23], the field lacks a unified synthesis to clarify its predictive power. Therefore, this investigation seeks to unpack sarcopenia's prognostic role in T2DM patients and advocate for its regular evaluation in this group.
Materials and Methods
The review's protocol was documented in the PROSPERO database under the registration number CRD420251004812. The work adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [24], detailed in Supplementary Table 4.
Search Strategy
We executed a comprehensive search across English-language publications in Embase, PubMed, Scopus, and Web of Science, up to March 12, 2025. Manual checks of references from selected studies and pertinent reviews unearthed extra eligible records. The search specifics appear in Supplementary Table 1.
Eligibility Criteria
The inclusion standards were: (1) study type: observational research, encompassing cross-sectional designs and prospective or retrospective cohort studies; (2) participants: adults aged 18 years or older with a confirmed T2DM diagnosis; and (3) exposure: sarcopenia. Diagnostic parameters for sarcopenia encompass metrics like the skeletal muscle mass index (SMI) and guidelines from the Asian Working Group on Sarcopenia (AWGS), the European Working Group on Sarcopenia in Older People (EWGSOP), and the Foundation for the National Institutes of Health (FNIH). (4) Outcomes: Investigations reporting data on death, cardiovascular events, and complications in T2DM patients with and without sarcopenia were eligible. If a cohort produced multiple studies on varying outcomes or distinct subgroups, all pertinent ones were admitted.
Exclusion Criteria
We omitted: (1) non-English publications; (2) repeated articles; (3) studies without extractable outcome data; and (4) reviews, letters, editorials, conference abstracts, and commentaries.
Data Extraction and Quality Evaluation
Two independent reviewers (HB and YL) screened titles and abstracts for potential candidates. Full texts were retrieved and scrutinized for eligibility. Data extraction happened post-final inclusion, conducted independently by two reviewers (HB and YL) using a standardized form. Captured details included first author, publication year, study design, location, participant characteristics, average age, sarcopenia definition, muscle mass measurement method, and outcomes. Hazard ratios (HRs) and odds ratios (ORs), adjusted for confounders, were extracted per study. Discrepancies in selection or extraction were reconciled through consensus, with a third reviewer (LL) intervening if needed. Methodological rigor was appraised by two reviewers using the Joanna Briggs Institute Critical Appraisal tool for cross-sectional studies and the Newcastle–Ottawa Quality Scale for cohort studies. The overall evidence strength for each outcome was rated via the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.
Statistical Analysis
Data presentation used proportions with descriptive statistics, and uncertainties via 95% confidence intervals (CIs). Study traits and main discoveries were summarized narratively. A random-effects model pooled individual study data into overall effect estimates for sarcopenia's impact on T2DM health outcomes. We computed combined HRs and ORs, displayed as forest plots. Adjusted results, corrected for key confounders via multivariate methods, were deemed more trustworthy. Variations in geography and outcome evaluation prompted a random-effects model over fixed-effects, irrespective of heterogeneity signs. Begg’s and Egger’s tests checked for publication bias, with p-values >0.05 indicating none. The trim-and-fill technique estimates missing studies due to bias and adjusts the overall effect [27]. Sensitivity testing used a leave-one-out method to assess heterogeneity and methodological bias effects. All computations utilized RevMan version 5.3 (from The Cochrane Collaboration) and Stata (version 18.0; Stata Corp, College Station, TX, USA), with p < 0.05 as significant.
Subgroup analyses explored heterogeneity sources via sarcopenia definition (AWGS vs. EWGSOP vs. SMI), muscle mass method (dual-energy X-ray absorptiometry (DXA) vs. bioelectrical impedance analysis (BIA) vs. computed tomography (CT)), and region (Asia vs. elsewhere).
Results
Study Selection
A PRISMA flowchart outlining the study inclusion process is in Figure 1. After duplicate removal, 3713 relevant articles were vetted. Title and abstract screening narrowed to 62 eligible ones. Full-text reviews admitted 15 articles [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42], with exclusions detailed in Supplementary Table 5.
Study Characteristics
Table 1 outlines the 15 studies' details. The median sample size hit 762 (range 238–201698). Twelve were cohort studies ([28,29,31,32,34,35,36,38,39,40,41,42]), and three cross-sectional ([30,33,37]). Average baseline ages spanned 21 to 82 years, with follow-ups from 1 to 15.65 years. Gender distribution was 49.4% male and 50.6% female. Populations included large population-based and hospital-based cohorts. Studies originated from diverse regions: mostly Asia (n=12) ([28,30,31,32,33,36,37,38,39,40,41,42]), Europe (n=2) ([29,34]), and South America (n=1) ([35]). Sarcopenia definitions varied: SMI [28,32,33,36,37,38], AWGS ([31,39,40,41,42]), EWGSOP ([29,34,35]), and FNIH ([30]). Muscle mass measurement techniques included DXA ([30,31,33,37,40,41,42]), BIA ([29,34,39]), CT ([28,32,36,38]), and calf circumference (CC) ([35]).
Flowchart of Literature Search and Study Inclusion
Full Size Image (accessible at https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-025-01998-w/figures/1)
Bias Assessment
Study quality scored moderately to highly, ranging from 6 to 9 points. Newcastle–Ottawa scale scores are in Supplementary Table 2.
Links Between Sarcopenia and Elevated Mortality in T2DM Patients
Six cohort studies examined sarcopenia's ties to all-cause mortality in T2DM cases (Figure 2). Meta-analysis indicated that T2DM individuals with sarcopenia bore a significantly higher mortality risk, with a combined HR of 1.72 (95% CI = 1.28–2.32; p < 0.001).
Subgroup breakdowns by sarcopenia definition, region, and measurement method revealed differences. Under AWGS criteria [31,39,41], the combined HR reached 2.41 (95% CI = 1.24–4.69; p = 0.009). EWGSOP [29,35] showed 1.92 (95% CI = 1.34–2.77; p < 0.001). SMI [32] yielded 1.35 (95% CI = 1.32–1.38; p < 0.001). Overall, these underscored increased risks for sarcopenic T2DM patients versus non-sarcopenic ones (Supplementary Figure 1). Regional analysis: Asia [31,32,39,41] had HR 1.77 (95% CI = 1.07–2.94; p = 0.03), and elsewhere [29,35] 1.92 (95% CI = 1.34–2.77; p < 0.001) (Supplementary Figure 2). By method: DXA [31,41] HR 1.88 (95% CI = 0.93–3.80; p = 0.08), BIA [29,39] 2.90 (95% CI = 1.06–7.96; p = 0.04), CT [32] 1.35 (95% CI = 1.32–1.38; p < 0.001), CC [35] 1.72 (95% CI = 1.28–2.32; p = 0.01), highlighting variations (Supplementary Figure 3).
Forest Plot of Sarcopenia's Connection to Mortality
Full Size Image (accessible at https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-025-01998-w/figures/2)
Links Between Sarcopenia and Increased CVD in T2DM Patients
Five studies [29,31,34,40,41] reported adjusted data on sarcopenia and CVD relations. The combined HR stood at 1.94 (95% CI = 1.67–2.25; p < 0.001), linking sarcopenia to higher CVD risks (Figure 3).
Subgroup analyses by definition and method: Both AWGS [31,40,41] and EWGSOP [31,34] associated with elevated CVD risks, HRs 2.09 (95% CI = 1.21–3.62; p = 0.009) and 1.97 (95% CI = 1.53–2.52; p < 0.001) respectively (Supplementary Figure 4). DXA [31,40,41] HR 2.09 (95% CI = 1.21–3.62; p = 0.009), BIA [31,34] 1.97 (95% CI = 1.53–2.52; p < 0.001), mirroring definition results (Supplementary Figure 5).
Forest Plot of Sarcopenia's Connection to CVD
Full Size Image (accessible at https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-025-01998-w/figures/3)
Links Between Sarcopenia and Increased Complication Rates in T2DM Patients
Four studies furnished adjusted HR data on sarcopenia and complications like diabetes-related kidney issues [38,42], diabetic stroke [28], and diabetes-induced dementia [36]. The combined HR was 1.12 (95% CI = 1.09–1.15; p < 0.001), associating sarcopenia with greater T2DM-related complications (Figure 4).
Three studies provided adjusted OR data on complications such as kidney issues [33,37] and stroke [30]. A combined OR of 2.49 (95% CI = 1.53–4.05; p < 0.001) confirmed sarcopenia's link to higher complication odds (Supplementary Figure 6).
Forest Plot of Sarcopenia's Links to Complications
Full Size Image (accessible at https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-025-01998-w/figures/4)
Full Table (accessible at https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-025-01998-w/tables/1)
Discussion
Sarcopenia negatively influences T2DM prognosis, heightens vulnerability to comorbidities, and hinders recovery. It also correlates with poorer blood sugar control, medication tolerance issues, and adherence to lifestyle changes. Though its harmful effects on death, CVD, and diabetic complications are noted, evidence hasn't been systematically clarified.
To our knowledge, no prior work has collated disparate sources to probe sarcopenia's ties to adverse T2DM outcomes. This study bridges that gap with a holistic synthesis of 15 articles evaluating sarcopenia's impact. Findings point to sarcopenia as a risk factor, with elevated HRs for mortality (adjusted HR = 1.72) and CVD events (adjusted HR = 1.94), plus higher diabetes complication rates (adjusted HR = 1.12, adjusted OR = 2.49) in sarcopenic versus non-sarcopenic T2DM patients. Sensitivity checks ensured no single study skewed results.
Prior meta-analyses tackled sarcopenia prevalence and risk factors in T2DM, offering insights [43,44]. Sarcopenia odds are 1.55 times higher in T2DM than non-diabetics, often tied to impaired muscle function over mass [45,46]. Divergent definitions complicate matters [10,47], and timely interventions are vital [20,45].
Our subgroups revealed outcome variations by definition, owing to threshold differences affecting prevalence [10,47]. One study echoed our results, noting predictive differences across definitions [48]. Definitions vary in focus—some emphasize function like grip strength and walking speed for frailty detection, others just mass, potentially underestimating risks. Standardized guidelines exist [6,8,49,50], but adherence is inconsistent, hindering comparisons and calling for unified future research.
Measurement methods also differ. CT offers precise muscle details but is costly and less accessible. Most use DXA or BIA [8], with DXA being accurate yet equipment-intensive [51], and BIA sensitive to hydration, limiting reliability in some groups [51].
Adjusted data from low-bias studies showed sarcopenic T2DM patients at greater mortality risk than counterparts, positioning sarcopenia as a predictor. It raises risks for fractures, cognitive decline [52,53], and is tied to mortality in various settings [54,55,56]. Aligning with this, our study confirms sarcopenia's harmful impact on T2DM survival. Evidence links it to CVD and post-op complications [57,58], with our HRs underscoring integrated cardiovascular care needs for sarcopenic individuals [59]. The presarcopenia connection suggests early action could curb cardiovascular risks.
And this is the part most people miss: Sarcopenia ties to higher diabetes complications compared to non-sarcopenic groups. Included studies covered kidney issues, CVD, dementia, and stroke. Though we combined HRs/ORs for varied complications, low heterogeneity (I2 = 0.0%; I2 = 35%) indicated minimal issues. Sarcopenic T2DM patients face elevated risks, hinting sarcopenia predicts adverse outcomes.
But here's where it gets controversial: Some argue that sarcopenia definitions are too narrow, potentially overlooking broader frailty in diabetes. Critics say this meta-analysis, mostly from Asian cohorts, might not apply globally—ethnic body composition differences could alter sarcopenia's implications. We restricted to English-language studies, risking bias, and relied on observational data, unable to prove causation. Small study numbers in subgroups and possible publication bias (favoring positive results) urge caution.
Conclusion
Our synthesis positions sarcopenia as a forecaster of heightened mortality and complications in T2DM patients. This calls for embedding sarcopenia checks into routine T2DM care for proactive risk identification. Future efforts should develop validated screening tools in diabetes clinics.
Evidence Certainty
GRADE assessment rated mortality evidence very low (suspected bias). CVD and complications (HR) low, complications (OR) moderate (strong association).
Publication Bias and Sensitivity Checks
Mortality funnel plots suggested bias, not CVD or complications (Egger’s p = 0.012 for mortality, non-significant elsewhere). Begg’s test showed no bias (mortality p = 0.452; CVD p = 0.220; complications p = 0.308). Trim-and-fill adjusted mortality to HR 1.43 (95% CI = 1.20–1.71), leaving others unchanged. Sensitivity analyses confirmed robustness—no single study altered results.
Data Availability
Datasets are available from the lead author upon request.
Abbreviations
AWGS: Asian Working Group on Sarcopenia
BIA: Bioelectrical Impedance Analysis
CT: Computed Tomography
CVD: Cardiovascular Disease
DXA: Dual-Energy X-ray Absorptiometry
EWGSOP: European Working Group on Sarcopenia in Older People
FNIH: Foundation for the National Institutes of Health
HR: Hazard Ratios
OR: Odds Ratios
SMI: Skeletal Muscle Mass Index
T2DM: Type 2 Diabetes Mellitus
References
(Full list retained as in original, unchanged for brevity.)
Acknowledgements
Not applicable.
Funding
Supported by Natural Science Foundation of Hunan Province, China (grant 2023JJ50137) and Graduate Nursing Education Teaching Team (193YST011). Funders had no input in design, data, or reporting.
Author Info
Hao Bai, Yaqing Liu, Longhan Zhang, Lingqiao Song, Yiting Pan, Zeyuan Long, Li Liao – School of Nursing, University of South China, Hengyang, Hunan, China.
Contributions
HB, YL, LS, YP, LL conceptualized. HB, YL, LZ searched and analyzed. HB, YL, ZL drafted. LL edited. All revised and approved.
Corresponding Author
Li Liao.
Ethics
Not applicable.
Consent
Not applicable.
Conflicts
None declared.
Now, let's spark some debate: Do you think sarcopenia should be a mandatory screening in diabetes clinics, or is it just adding another layer of complexity to an already overburdened system? Could focusing on muscle health shift attention from blood sugar control? Share your thoughts in the comments—do you agree sarcopenia is underrated, or disagree that it's a key predictor? We'd love to hear your perspectives!
