Umbrella review protocol type 2 diabetes mellitus and fracture risk

Abstract

BACKGROUND

Type 2 diabetes mellitus (T2DM) represents a major global public health challenge, with projections indicating that the number of affected individuals could reach 853 million by 2050. While microvascular and macrovascular complications in diabetic patients are well-documented, there is a growing focus on skeletal involvement, particularly diabetic osteoporosis. Traditionally, the increased fracture risk in T2DM has been attributed to mechanisms like the accumulation of advanced glycation end products and oxidative stress. However, emerging evidence suggests that T2DM patients may experience compensatory skeletal adaptations, such as increases in bone density, which complicate the relationship between T2DM and fracture risk. This study utilizes an umbrella meta-analysis to systematically assess the association between T2DM and fracture risk, aiming to clarify existing controversies in the literature.

AIM

To thoroughly evaluate the association between T2DM and fracture risks at various anatomical sites, including overall fractures, hip fractures, and non-vertebral fractures. The goal is to provide an evidence-based foundation for developing individualized fracture management strategies in clinical practice.

METHODS

Conducted in accordance with PRISMA guidelines, this umbrella meta-analysis involved a systematic literature search across the PubMed, Web of Science, and EMBASE databases up to October 1, 2025. The search aimed to identify meta-analyses that evaluated the association between T2DM and fracture risk. Inclusion criteria were limited to studies involving T2DM patients, with fracture risk as the outcome measure, expressed as relative risk (RR) and 95% confidence intervals (CIs). The methodological quality of the studies was assessed using the AMSTAR 2 tool. Statistical analyses employed either fixed-effects or random-effects models based on I² heterogeneity statistics, and sensitivity analyses were performed to confirm the robustness of the findings.

RESULTS

A total of 16 studies were included in the analysis. The findings revealed a significant association between T2DM and an increased risk of total fractures (RR = 1.23, 95%CI: 1.17-1.28), with low heterogeneity observed (I² = 44.8%). Site-specific analyses showed heterogeneous associations: Increased risks were identified for non-vertebral fractures (RR = 1.22, 95%CI: 1.18-1.27), ankle fractures (RR = 1.43, 95%CI: 1.21-1.64), and upper arm fractures (RR = 1.43, 95%CI: 1.21-1.64). Conversely, the risk of hip fractures was significantly reduced (RR = 0.80, 95%CI: 0.72-0.89), although this result exhibited considerable heterogeneity (I² = 94.9%). No significant associations were found for vertebral or humeral fractures. Sensitivity analyses confirmed the robustness of the hip fracture outcome after excluding outliers. A forest plot for total fractures visually illustrated a consistent trend toward increased risk. Furthermore, funnel plot analysis indicated mild publication bias, which did not compromise the primary conclusions. The observed heterogeneity in the hip fracture analysis was mainly due to specific study deviations.

CONCLUSION

T2DM shows a heterogeneous association with fracture risk, highlighting the need for the development of site-specific clinical strategies. The reduced risk of hip fractures may indicate compensatory skeletal adaptation, while the increased risk at other sites is linked to diabetic complications like neuropathy. Future research should focus on large-scale cohort studies, inclusive of ethnic diversity, and the optimization of risk prediction tools to improve fracture prevention and management in T2DM patients.

Key Words: Type 2 diabetes mellitus; Fracture risk; Umbrella meta-analysis; Bone fragility; Heterogeneity

Core Tip: This umbrella review reveals the complex, site-specific relationship between type 2 diabetes mellitus (T2DM) and fracture risk. Contrary to the elevated risk for overall, non-vertebral, and ankle fractures, T2DM was associated with a significantly reduced risk of hip fracture. This paradoxical finding challenges conventional views and may be attributed to skeletal compensatory adaptations in T2DM, such as adaptive increases in bone density. The study underscores the necessity of moving beyond a generalized fracture risk assessment and developing individualized, site-specific prevention and management strategies for patients with T2DM.

INTRODUCTION

Diabetes poses a significant global public health challenge. It is projected that the number of individuals with diabetes will rise to 853 million by 2050[1]. Affected individuals are at risk of developing various microvascular and macrovascular complications[2]. Notably, diabetic osteoporosis resulting from skeletal system involvement is increasingly becoming a clinical focus[3]. Conventional perspectives suggest that diabetes increases fracture risk through several pathological mechanisms. One key factor is the accumulation of advanced glycation end products (AGEs) resulting from chronic hyperglycemia, which undermines the integrity of bone collagen[3-5]; dysregulation of calcium and phosphorus metabolism[6]; reduced bone strength due to oxidative stress and microvascular complications[7-9]; and increased fall propensity associated with neuropathy[10,11]. Collectively, these mechanisms increase the susceptibility to fractures in diabetic patients. In addition to the well-known metabolic pathways, the specific biochemical abnormalities associated with type 2 diabetes mellitus (T2DM), such as insulin resistance, chronic hyperglycemia, and dyslipidemia, have complex effects on bone health that traditional bone mineral density (BMD) assessments do not fully capture. Insulin resistance, in particular, disrupts the metabolic balance of bone by diminishing insulin’s anabolic effect on bone formation, which may consequently result in relatively increased bone resorption[12].

Persistent hyperglycemia accelerates the accumulation of AGEs, damaging the integrity of bone collagen and reducing bone toughness. Meanwhile, dyslipidemia and oxidative stress may impair the vascular function and remodeling process of bone[13]. These alterations primarily lead to a decline in bone quality, specifically in microstructure and material properties, rather than simply reducing bone mass. This explains the paradox where some T2DM patients exhibit normal or even elevated BMD while still facing an increased risk of fractures[14]. Therefore, the assessment of fracture risk in T2DM patients should go beyond BMD measurement and incorporate biochemical indicators and bone quality assessment systems.

However, recent evidence-based medical research has revealed more complex clinical scenarios. Unlike the prevalent bone density reduction observed in patients with type 1 diabetes[15], patients with T2DM exhibit unique skeletal compensatory adaptations[3,16,17]. Multiple longitudinal studies have indicated that, as the disease progresses, patients with T2DM may experience adaptive thickening of bone density[18-20]. This alteration in bone metabolism may result in a different trajectory for the development of fracture risk than previously understood. These findings require substantial revisions to traditional views on the skeletal complications associated with T2DM. They also highlight the necessity for a more dynamic evaluation framework to assess the evolution of fracture risk in patients with diabetes, considering various stages and types of the disease.

Clinical studies have shown that diabetes-related fractures display distinct patterns, notably with particularly high incidences of hip and vertebral fractures[21-24]. There are significant differences in fracture risk associated with various types of diabetes. Type 1 diabetes is typically linked to decreased BMD and an increased susceptibility to fractures. In contrast, the relationship between bone metabolism characteristics and fracture risk in T2DM is more complex[25]. This disparity may be attributed to the unique metabolic features of patients with T2DM, including insulin resistance, hyperinsulinemia, and the multifaceted effects of obesity on bone metabolism[17,26]. This umbrella meta-analysis aims to systematically integrate existing high-level evidence and evaluate the association between T2DM and fracture risk. By conducting a systematic review of current literature and grading the evidence, this study will provide a crucial foundation for developing individualized clinical strategies for managing fracture risk in patients with diabetes[27].

MATERIALS AND METHODS

Research design

This study constitutes an umbrella review, rigorously adhering to the PRISMA guidelines. The research protocol has been prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO 2025 CRD420251164534. Available from: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251164534), and all analyses were conducted in accordance with the pre-established plan.

Search strategy

A comprehensive search was performed on the PubMed, Web of Science, and EMBASE databases to identify relevant meta-analysis regarding the association between T2DM and fracture risk (search cutoff date: October 1, 2025). The search strategy included the following Medical Subject Headings with free-text terms (such as “type 2 diabetes”, “fracture risk”, “osteoporosis”, “bone fragility”). Moreover, a supplementary search will be performed by screening the references of the included literature. The detailed search strategy is presented in the Supplementary material.

Inclusion criteria

A systematic review and meta-analysis were conducted to evaluate the association between T2DM and the risk of fractures. The study focused exclusively on patients with T2DM, excluding studies that combined type 1 and T2DM without independent analysis. The primary exposure of interest was T2DM, while the control group included non-diabetic individuals. The main outcome measure was the risk of fractures, specifically at sites such as the vertebrae and hips, as well as non-vertebral fractures. Only studies that reported relative risk (RR) and 95% confidence intervals (CIs) were included, as the databases utilized only recorded RR as the effect measure. Studies lacking extractable RR data or reporting other effect measures, such as the standardized mean difference or mean difference, were excluded. Additionally, original research papers, case reports, and narrative reviews were not considered.

Methodological quality assessment

Two reviewers (Zhou WH and Wang RT) independently assessed the quality of the included meta-analyses using the AMSTAR 2 tool, which encompasses 16 items rated as yes, partial, no, or not applicable (Table 1). The quality of evidence was evaluated using the GRADE system, categorizing it as high, moderate, low, or very low, with particular attention to the risk of bias, heterogeneity, and publication bias.

Table 1 The results of quality assessment included meta-analyses based on A Measurement Tool to Assess Systematic Reviews 2 questionnaire.

Ref.	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11	Q12	Q13	Q14	Q15	Q16	Overall
Moayeri et al[22]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	High
Fan et al[28]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Moderate
Wang et al[29]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	High
Bai et al[30]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Moderate
Ni et al[31]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Moderate
Dou et al[32]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	High
Vilaca et al[33]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	Moderate
Zhang et al[34]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Low
Thong et al[35]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	High
Qiu et al[36]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	Moderate
Ji et al[37]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	High
Jia et al[38]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	Moderate
Gao et al[39]	√	×	√	√	√	√	×	√	√	×	√	√	√	√	√	×	High
Vilaca et al[40]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Low
Dytfeld et al[41]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	High
Wang et al[42]	√	×	√	√	×	×	×	√	√	×	√	√	√	√	√	×	Moderate

Q1: Did the research questions and inclusion criteria for the review include the components of patient, intervention, comparison, outcome; Q2: Did the report of the review contain an explicit statement that the review methods were established before performing the review, and did the report justify any significant deviations from the protocol; Q3: Did the review authors explain their selection of the study designs for inclusion in the review; Q4: Did the review authors use a comprehensive literature search strategy; Q5: Did the review authors perform study selection in duplicate; Q6: Did the review authors perform data extraction in duplicate; Q7: Did the review authors provide a list of excluded studies and justify the exclusions; Q8: Did the review authors describe the included studies in adequate detail; Q9: Did the review authors use a satisfactory technique for assessing the risk of bias in individual studies that were included in the review; Q10: Did the review authors report on the sources of funding for the studies included in the review; Q11: If meta-analysis was performed, did the review authors use appropriate methods for the statistical combination of results; Q12: If a meta-analysis was performed, did the review authors assess the potential impact of risk of bias in individual studies on the results of the meta-analysis or other evidence synthesis; Q13: Did the review authors account for risk of bias in individual studies when interpreting/discussing the review results; Q14: Did the review authors provide a satisfactory explanation for and discussion of any heterogeneity observed in the review results; Q15: If they performed quantitative synthesis, did the review authors conduct an adequate investigation of publication bias (small-study bias) and discuss its likely impact on the review results; Q16: Did the review authors report any potential sources of conflict of interest, including any funding they received for conducting the review.

Study selection and data extraction

An initial screening of titles and abstracts was conducted by two reviewers (Zhou ZY and Zou WH), based on pre-established inclusion criteria. For studies deemed potentially eligible, Zhou ZY and Wang RT independently retrieved the full texts and conducted a final assessment for inclusion. Any discrepancies were resolved through discussion or by consulting a third reviewer (Wang RT). Data extracted from the included studies included the first author, publication year, sample size, and follow-up duration. Specific information regarding fracture types was also collected, focusing on vertebral, hip, and non-vertebral fracture outcomes. All outcomes were recorded as RR values along with their corresponding 95%CIs, since the available databases contained only RR effect measures without alternative statistical metrics such as standardized mean differences or mean differences. Additionally, indicators of heterogeneity, including the I² statistic and the statistical model used (random-effects/DerSimonian-Laird or fixed-effects/inverse-variance), were extracted.

Statistical analysis

All statistical analyses were performed using STATA version 16.0 (StataCorp, TX, United States). The selection of statistical models was determined by the degree of between-study heterogeneity: When the I² statistic did not exceed 50% (indicating acceptable heterogeneity), a fixed-effects model (inverse-variance weighting method) was applied; when the I² value exceeded 50% (suggesting substantial heterogeneity), a random-effects model (DerSimonian-Laird method) was employed to account for between-study variation.

Heterogeneity was quantitatively assessed using the I² statistic, with classification thresholds defined as follows: Values below 25% indicated low heterogeneity, values between 25% and 50% indicated moderate heterogeneity, and values above 50% indicated high heterogeneity. A sensitivity analysis was performed by sequentially excluding individual studies to assess the robustness and stability of the pooled results. All effect estimates were reported as RR along with corresponding 95%CIs. Additionally, forest plots were generated to visually present the pooled effect sizes alongside study-specific outcomes. The statistical significance level for all analyses was set at P < 0.05.

RESULTS

Learning choices

The initial database search yielded a total of 326 studies: 244 from PubMed, 69 from Web of Science, and 13 from EMBASE. After identifying 95 duplicates, the titles and abstracts of the remaining 231 articles were thoroughly screened. This process led to the exclusion of 29 articles, which included experimental papers, meta-analysis protocols, and related reviews. The full texts of 202 articles were then evaluated, resulting in the exclusion of 184 meta-analyses due to concerns regarding data authenticity and reliability. Ultimately, an umbrella analysis was conducted on 18 meta-analyses that met the inclusion criteria (Figure 1).

Figure 1 Inclusion and exclusion of literature.

Overall fracture incidence rate

After confirming the baseline comparability, a meta-analysis of fracture incidence was performed on the 16 reported studies[22,28-42]. Results of the fixed-effects model demonstrated a significant inverse association between T2DM and overall fracture risk (RR = 1.23, 95%CI: 1.17-1.28, I² = 44.8%, Figure 2A). Funnel plot analysis showing mild publication bias (Figure 2B).

Figure 2 Association between type 2 diabetes mellitus and overall fracture incidence. A: Forest plot of type 2 diabetes mellitus and the overall fracture incidence rate; B: Funnel plot of type 2 diabetes mellitus and overall fracture incidence. CI: Confidence interval.

Incidence of hip fractures

A total of 11 studies reported the incidence of hip fractures. Significant heterogeneity was observed among the studies (I² = 94.9%, P < 0.001)[28-30,32,35,37-40,42]. The random-effects model showed that T2DM was associated with a significantly reduced risk of hip fracture (RR = 0.80, 95%CI: 0.72-0.89; Figure 3A). A sensitivity analysis was conducted by sequentially excluding individual studies, with results presented in Figure 3B. The study by Thong et al[35] (2018) was identified as an outlier, exhibiting an abnormally high-risk ratio (RR = 5.79, 95%CI: 3.55-9.44) that substantially deviated from the other studies. After excluding this study, the sensitivity analysis revealed that the pooled effect estimate remained robust (RR = 0.81, 95%CI: 0.73-0.90; Figure 3C), although there was significant heterogeneity.

Figure 3 Association between type 2 diabetes mellitus and incidence of hip fractures. A: Forest plot illustrating the association between type 2 diabetes mellitus (T2DM) mellitus and hip; B: Sensitivity analysis of T2DM and hip fracture incidence; C: Forest plot of T2DM and hip fracture incidence after heterogeneity literature exclusion. CI: Confidence interval.

Incidence of non-pyramidal fractures

Analysis of the pooled data from five studies utilizing a fixed-effects model indicated a significantly increased risk of non-vertebral fractures in patients with T2DM (RR = 1.22, 95%CI: 1.18-1.27, I² = 0.0%; Figure 4A)[39,40].

Figure 4 Forest plot. A: Association between type 2 diabetes mellitus (T2DM) and the incidence of nonvertebral fractures; B: T2DM and ankle fracture incidence; C: Association between T2DM and incidence of upper arm fractures; D: T2DM and vertebral fractures; E: T2DM and foot fractures; F: T2DM and humeral fractures. CI: Confidence interval.

Incidence of ankle fractures

Four studies were included in the analysis[22,29,32,33]. The fixed-effects model indicated that T2DM was significantly associated with an increased risk of ankle fracture (RR = 1.43, 95%CI: 1.21-1.64, I² = 0.0%, Figure 4B).

Incidence of humeral fractures

Two studies were included in the analysis[29,32]. A fixed-effects model revealed a strong association between T2DM and upper arm fracture risk (RR = 1.43, 95%CI: 1.21-1.64, I² = 0.0%; Figure 4C).

Incidence of vertebral fractures

Overall, six studies were included in the analysis[29,30,32,38,41,42]. Results of the fixed-effects model demonstrated no significant association between T2DM and vertebral fracture risk (RR = 1.10, 95%CI: 0.98-1.21, I² = 0.0%, Figure 4D).

Incidence of foot fractures

One study was enrolled in the analysis[22]. Notably, results of the fixed-effects model indicated a significant association between T2DM and an elevated risk of foot fractures (RR = 1.37, 95%CI: 1.21-1.53, I² = 0.0%; Figure 4E). These findings need to be further investigated.

Incidence of humeral fractures

Only one study was included[22]. It was observed that no association existed between T2DM and the risk of humeral fracture (RR = 1.09, 95%CI: 0.86-1.31, I² = 0.0%, Figure 4F).

DISCUSSION

Diabetes-related skeletal complications represent a significant public health research priority globally[43]. The relationship between T2DM and fracture risk remains a topic of debate, primarily attributable to the intricate characteristics of bone metabolism observed in individuals with T2DM[44,45]. Conventional perspectives posit that diabetes increases fracture risk through multiple pathological mechanisms[46]. However, unique compensatory skeletal adaptations in individuals with T2DM challenge this traditional understanding[47,48]. Consequently, there exists an urgent necessity to systematically synthesize high-level evidence to elucidate the association patterns between these conditions.

This study represents an umbrella meta-analysis aimed at investigating the relationship between T2DM and fracture risk. Adhering rigorously to PRISMA guidelines, we systematically identified and evaluated pertinent meta-analyses. The objective is to provide evidence-based guidance for clinical practice and to address existing gaps in the differential assessment of fracture risks across various anatomical sites.

This systematic analysis of 16 eligible studies uncovers heterogeneous associations between T2DM and fracture risks across anatomical locations. Pooled analysis revealed a significantly elevated overall fracture risk among diabetic patients (RR = 1.23, 95%CI: 1.17-1.28), thereby supporting the adverse impact of diabetes on skeletal health to a certain extent. However, site-specific analyses demonstrated distinct patterns: Significant risk increases were noted for non-vertebral fractures (RR = 1.22, 95%CI: 1.18-1.27), ankle fractures (RR = 1.43, 95%CI: 1.21-1.64), upper arm fractures (RR = 1.43, 95%CI: 1.21-1.64), and foot fractures (RR = 1.37, 95%CI: 1.21-1.53). In contrast, hip fracture risk exhibited a significant reduction (RR = 0.80, 95%CI: 0.72-0.89), while no significant associations were identified for vertebral or humeral fractures.

Notably, substantial heterogeneity was evident in the hip fracture analysis (I² = 94.9%, P < 0.001). Sensitivity analysis, which excluded the outlier study by Thong et al[35] (2018), sustained robust pooled effects (RR = 0.81, 95%CI: 0.73-0.90); however, heterogeneity persisted, suggesting multifactorial modulation of hip fracture risk specificity.

A systematic review of 16 eligible studies demonstrated a heterogeneous relationship between T2DM and fracture risk across different anatomical sites. The observed site-specific pattern of fracture susceptibility could be ascribed to distinct underlying pathophysiological mechanisms. The elevated risks of overall fractures, non-vertebral fractures, and ankle fractures may be linked to adverse alterations in bone quality[49]. Conventional hypotheses attribute these alterations to multiple mechanisms, including the accumulation of AGEs compromising collagen integrity, oxidative stress diminishing bone strength, and neuropathy increasing the propensity for falls[50]. The significant risk of foot and ankle fractures is closely linked to sensory impairment caused by diabetic peripheral neuropathy. Additionally, microcirculatory disturbances resulting from vascular complications further worsen skeletal fragility[51].

These differential risk profiles may be attributed to the distinct pathophysiological mechanisms of T2DM and the skeletal metabolic adaptations that occur. Conventional paradigms explain the elevated fracture risk through several mechanisms, including the accumulation of advanced glycation end-products, which impair the integrity of bone collagen[50,52], oxidative stress compromising bone strength[53], and neuropathy increasing fall propensity[54]. These mechanisms likely contribute to the increased risks for overall, non-vertebral, and ankle fractures. Notably, the heightened risk of foot and ankle fractures is particularly associated with sensory impairment and balance deterioration caused by diabetic peripheral neuropathy[55,56], compounded by microcirculatory disturbances from vascular complications that exacerbate skeletal fragility[51]. The elevated upper arm fracture risk may stem from compensatory injuries during protective arm movements in falls[57,58].

The unexpected finding pertaining to the reduced risk of hip fractures is hypothesized to be related to skeletal compensatory adaptations and metabolic characteristics in individuals with T2DM[59]. Multiple studies indicate that bone density may adaptively increase as T2DM progresses[60-62]. This structural alteration may confer a degree of mechanical protection to the hip. Furthermore, obesity, frequently comorbid with T2DM, may stimulate bone formation through increased mechanical loading[63]. Additionally, hormones such as estrogen secreted by adipose tissue may positively regulate hip bone mass[64]. Substantial heterogeneity indicates that differences across studies, such as variations in age structure, obesity severity, glycemic control, and follow-up duration, may obscure the true association with hip fracture risk. This variability necessitates cautious interpretation of the findings.

Additionally, the sources of heterogeneity in this study stem from disparities in research design and population characteristics. The included studies differed in sample size, follow-up periods, fracture diagnostic criteria, and the extent of adjustment for confounding factors. Notably, some studies failed to adequately consider the potential effects of glucose-lowering medications (e.g., insulin, metformin) on bone metabolism, which may have biased the effect estimates[25]. Publication bias analysis indicated a slight bias in the publication of overall fracture risk studies. While this did not significantly change the main conclusions, it emphasizes the importance of considering unpublished negative results in future research. The quality assessment conducted using the AMSTAR 2 tool revealed inconsistent quality among the included meta-analyses. Methodological limitations in certain studies, such as incomplete search strategies and inadequate handling of heterogeneity, may affect the reliability of the evidence synthesized in this umbrella review.

This study demonstrates several methodological strengths. As an umbrella meta-analysis examining the association between T2DM and fracture risk, it systematically synthesizes high-level evidence and evaluates fracture risks across various anatomical sites, thereby addressing a gap in site-specific analyses that are often overlooked in conventional studies. The research strictly adhered to PRISMA guidelines and utilized standardized search strategies and quality assessment tools. Sensitivity analyses confirmed the robustness of the findings, ensuring transparency and reproducibility. Additionally, by exclusively focusing on T2DM and excluding type 1 diabetes, this study enhances the specificity of its conclusions.

However, several limitations must be acknowledged. First, certain fracture types (e.g., foot and humeral fractures) were analyzed in only one or two studies with limited sample sizes, which restricts the generalizability of the findings. Second, key variables such as disease duration, glycemic control levels, and treatment regimens were not sufficiently detailed in the included studies, limiting the assessment of their modifying effects on fracture risk. Third, the study populations lacked racial diversity, with most evidence derived from European, North American, and select Asian populations, potentially limiting global applicability. Finally, despite conducting sensitivity analyses, high heterogeneity in hip fracture outcomes remains unresolved, indicating the need for further investigation into its sources.

Based on these findings, individualized fracture risk management strategies should be implemented in clinical practice for patients with T2DM. Given the elevated risks for non-vertebral, ankle, upper arm, and foot fractures, clinicians should enhance skeletal health monitoring in these patients. Prevention strategies should include bone density assessments and fall risk evaluations. Specific measures include optimizing glycemic control to reduce the accumulation of advanced glycation end-products and mitigate bone quality impairment; implementing balance training and foot care to minimize fall and foot injury risks; and supplementing with calcium and vitamin D for high-risk individuals to improve bone metabolism. The observed reduction in hip fracture risk should not be overinterpreted; clinical decisions must consider individual patient factors such as age, obesity, and comorbidities to avoid underestimating potential hip fracture risks.

CONCLUSION

Future research should focus on several key directions. First, large-scale cohort studies with long-term follow-up are needed to stratify T2DM patients by disease duration, glycemic control levels, and treatment regimens, clarifying how these factors impact fracture risks at different anatomical sites. Second, additional high-quality studies targeting fracture types with limited sample sizes (such as foot and humeral fractures) are necessary to strengthen the evidence base. Third, expanding study populations to include diverse ethnicities and age groups will enhance the global applicability of the findings. Fourth, investigating the underlying molecular mechanisms of bone metabolism abnormalities in T2DM may provide a theoretical foundation for developing targeted skeletal protection interventions. Fifth, optimizing fracture risk assessment tools (e.g., FRAX score) for T2DM patients by incorporating diabetes-specific indicators will improve the accuracy of risk prediction.

This umbrella meta-analysis clarifies the heterogeneous associations between T2DM and fracture risks across various skeletal sites, providing critical evidence for developing individualized fracture risk management strategies in clinical practice. Further high-quality and refined studies are essential to strengthen the evidence base and advance the prevention and management of skeletal complications in T2DM.

ACKNOWLEDGEMENTS

Thanks are extended to the Affiliated Nanhua Hospital, University of South China for their assistance.