Association between anemia and the risk of diabetic foot ulcer: A meta-analysis

Abstract

BACKGROUND

Diabetic foot ulcers (DFUs) are a major complication of diabetes mellitus, and anemia is commonly observed in diabetic patients. However, the relationship between anemia and the risk of developing DFUs remains unclear.

AIM

To investigate the relationship between anemia and the risk of DFUs in diabetic patients through a meta-analysis.

METHODS

A systematic search was conducted across PubMed, Embase, and Web of Science databases to identify studies that reported the co-occurrence of anemia and DFUs in diabetic patients. The primary outcome was an association between anemia and DFU risk, expressed as odds ratios (ORs). Secondary outcomes included the risk of DFU per 1-g/dL decrease in hemoglobin and the difference in hemoglobin levels between patients with and without DFU. Statistical analyses were performed using random-effects models to account for heterogeneity.

RESULTS

Sixteen studies involving 170,949 diabetic patients were included in the analysis. The results indicated a significant association between anemia and an increased risk of DFUs (eight studies, n = 166173, OR: 2.72, 95%CI: 1.73–4.25, P < 0.001; I² = 93%). Subgroup analyses supported consistent findings across various patient characteristics, analytic models, and study quality scores (P for subgroup differences, all > 0.05). Additionally, each 1-g/dL decrease in hemoglobin was associated with an excess risk of DFUs (four studies, n = 2543, OR: 1.65, 95%CI: 1.21–2.27, P = 0.002; I² = 68%). Furthermore, diabetic patients with DFUs exhibited significantly lower hemoglobin levels compared to those without DFUs (nine studies, n = 3986, mean difference: -2.13 g/dL, 95%CI: -2.58 to -1.68, P < 0.001; I² = 90%).

CONCLUSION

Anemia can be associated with an increased risk of DFUs in diabetic patients. Monitoring and managing anemia in diabetic population may help mitigate the risk of DFUs, emphasizing the need for early interventions. Further research is required to investigate the underlying mechanisms and potential therapeutic strategies.

Key Words: Anemia; Diabetic foot ulcer; Hemoglobin; Meta-analysis; Risk factor

Core Tip: This meta-analysis reveals a significant association between anemia and an increased risk of diabetic foot ulcers (DFUs) in diabetic patients, with an odds ratio (OR) of 2.72. Each 1-g/dL decrease in hemoglobin appears to further elevates DFU risk (OR: 1.65), and diabetic patients with DFUs show significantly lower hemoglobin levels (-2.13 g/dL). These findings highlight the importance of anemia monitoring and management in diabetes care to reduce DFU risk. By providing reasonable evidence from 16 studies involving over 170000 patients, this study underscores the need for early interventions and further research into underlying mechanisms and therapeutic strategies.

INTRODUCTION

Diabetic foot ulcers (DFUs) are a major complication of diabetes mellitus (DM), with a global prevalence ranging from 4% to 10% among patients with DM[1,2]. DFUs are a leading cause of hospitalization and lower-limb amputation, and they profoundly impact the quality of life of affected individuals, contributing to both physical and psychological burden[3,4]. The development of DFUs is influenced by a variety of factors, including neuropathy, peripheral artery disease, poor glycemic control, and infection[5]. In addition to these well-established risk factors, emerging evidence suggests that conditions such as anemia may also play a crucial role in the pathogenesis and progression of DFUs[6]. Identifying new and modifiable risk factors like anemia could provide valuable insights for improving early diagnosis and prevention strategies, ultimately mitigating the high morbidity associated with DFUs[7].

Anemia, characterized by low hemoglobin levels, is a common comorbidity in patients with DM, with prevalence rates ranging from 10% to 30%[8,9]. Several factors contribute to the development of anemia in diabetic patients, among which are chronic kidney disease[10], poor nutritional status[11], inflammatory cytokine activation[12], and iron deficiency[13]. Although anemia is widely recognized as a significant clinical concern in diabetes, its potential role in the development and progression of DFUs remains poorly understood[6].

Anemia may exacerbate the wound healing process by impairing tissue oxygenation, reducing immune function, and promoting inflammation, which are all critical factors for proper wound recovery[14]. Furthermore, anemia may directly compromise vascular supply to the lower extremities, exacerbating the risks posed by DM-related vascular dysfunction[15]. Despite these plausible mechanisms, clinical evidence regarding the relationship between anemia and DFUs remains inconclusive, highlighting the need for more comprehensive research to clarify the role of anemia in DFU development[16-31].

Therefore, the aim of this meta-analysis was to systematically evaluate the association between anemia and the risk of DFUs in diabetic patients. Achieving clearer insights into whether anemia can be considered a modifiable risk factor for DFUs can lead to more effective treatments.

MATERIALS AND METHODS

In conducting this meta-analysis, the study adhered to the guidelines of PRISMA 2020[32,33] and the Cochrane Handbook for Systematic Reviews and Meta-analyses[32], including the protocols for study design, data extraction, statistical analysis, and results presentation. Additionally, the meta-analysis protocol was registered with the International Prospective Register of Systematic Reviews under registration identifier CRD42024620404.

Literature search

To identify studies pertinent to this meta-analysis, we conducted a comprehensive search of PubMed, Embase, and Web of Science databases using an extensive array of search terms, which included: (1) "anemia" OR "anaemia" OR "low hemoglobin"; (2) "diabetic" OR "diabetes" OR "diabetes mellitus" OR "type 2 diabetes" OR "type 1 diabetes" OR "T2D" OR "T1D" OR "T2DM" OR "T1DM"; (3) "foot" OR "feet" OR "leg" OR "lower-extremity" OR "lower extremity" OR "lower extremities"; and (4) "ulcer" OR "ulcers" OR "wound" OR "wounds" OR "ulceration". The search was restricted to studies involving human subjects and included only full-length articles published in English in peer-reviewed journals. Additionally, a manual screening of the references of relevant original and review articles was performed to identify any additional eligible studies. The literature search covered the period from the inception of the databases up to November 14, 2024.

Inclusion and exclusion criteria

The inclusion criteria for potential studies were defined according to the PICOS framework:

P (patients): Patients with a confirmed diagnosis of DM, including both type 1 and 2 diabetes.

I (exposure): Patients with anemia, diagnosed by a low serum hemoglobin level, with the severity of anemia consistent with the criteria reported in the original studies.

C (comparison): Patients without anemia.

O (outcome): Incidence or prevalence of DFU compared between diabetic patients with and without anemia, the risk of DFU per 1 g/dL decrease in serum hemoglobin, or the difference in serum hemoglobin levels between diabetic patients with and without DFU.

S (study design): Observational studies, such as cohort studies, case-control studies, or cross-sectional studies.

Studies were excluded if they were reviews, editorials, meta-analyses, preclinical research, involved non-DM patients, lacked anemia as the exposure, or did not report DFU as an outcome. In cases of overlapping populations, the study with the largest sample size was included in the meta-analysis.

Study quality assessment and data extraction

The literature search, study selection, quality assessment, and data extraction were independently performed by two authors, with any discrepancies resolved through discussion with the corresponding author. Study quality was assessed using the Newcastle–Ottawa Scale[34], which evaluates the selection of study participants, control of confounding factors, and outcome measurement and analysis, with scores ranging from 1 to 9, with a score of 9 indicating the highest quality. Data extracted for analysis included study characteristics (author, year, country, and design), participant details (number of diabetic patients, mean age, sex, and duration of diabetes), number of patients with DFU, definition of anemia, outcomes reported, and variables matched or adjusted when the association between anemia and DFU in patients with diabetes was estimated.

Statistical analyses

The primary outcome of this study was the association between anemia and the risk of DFUs in patients with DM, which was expressed as odds ratios (ORs) with 95%CIs. Secondary outcomes included the risk of DFU per 1 g/dL decrease of serum hemoglobin expressed as ORs and 95%CIs, and the difference of serum hemoglobin between diabetic patients with and without DFU, presented as the mean difference (MD) with 95%CIs. ORs and their standard errors were derived from 95%CIs or P-values and were subsequently log-transformed to stabilize variance and achieve a normalized distribution[32]. To assess for heterogeneity, we used the Cochrane Q test and I² statistics[35], with I² > 50% indicating statistically significant heterogeneity. A random-effects model was applied to synthesize the results, accounting for study variability[32]. A sensitivity analysis was conducted by sequentially excluding individual studies to evaluate the robustness of the evidence. For the primary outcome, subgroup analyses were performed to explore the influence of various factors on the results, including the study design, mean age of patients, the proportion of male subjects, analytic models (univariate or multivariate analyses), and NOS scores of the included studies. The medians of continuous variables were used as cutoff points to define subgroups. Publication bias was evaluated using funnel plots and visual inspection for asymmetry, supplemented by Egger’s regression test[36]. Analyses were performed using RevMan (version 5.1; Cochrane Collaboration, Oxford, United Kingdom) and Stata software (version 12.0; Stata Corporation, College Station, TX, United States).

RESULTS

Study identification

The study selection process is summarized in Figure 1. Initially, a total of 591 potentially relevant records were identified from the three databases searched and citations of related articles, after removing 101 duplicates. A screening of titles and abstracts led to the exclusion of 461 articles that did not align with the objectives of the meta-analysis. The full texts of the remaining 29 articles were independently reviewed by two authors, resulting in the exclusion of 13 studies for various reasons, as detailed in Figure 1. Ultimately, 16 articles were included in the quantitative analysis[16-31].

Figure 1 Flowchart of database search and study inclusion. DFU: Diabetic foot ulcer; HGB: Hemoglobin.

Overview of the study characteristics

Table 1 presents the summarized characteristics of the studies included in the meta-analysis. One article contributed two datasets from two separate case-control studies[21], resulting in 17 datasets from six case-control studies[16-18,20,21] and 11 cross-sectional studies[19,22-31] and a total of 170949 patients with DM were included in the meta-analysis. The mean ages of the patients ranged from 42.6 to 67.9 years, with the proportion of men varying between 48.4% and 74.0%. Overall, 50611 (29.6%) patients were diagnosed with DFUs. Generally, anemia was defined as serum hemoglobin levels of < 13 g/dL in men and < 12 g/dL in women in six studies[19,20,23,27,30,31], and according to database codes in one study[28]. The primary outcome, which assessed the association between anemia and DFU, was reported in eight studies[16,19,20,23,27,28,30,31]. The secondary outcome that assessed the risk of DFU per 1-g/dL decrease of hemoglobin was reported in four studies[18,22,26,29], and the secondary outcome that assessed the difference in hemoglobin levels between patients with and without DFU was reported in nine studies[17,18,20,21,24-26,29]. Multivariate analysis was employed in nine studies to evaluate the association between anemia and DFU[16,18,20,22,24,26-29], whereas univariate analysis was used in the remaining eight studies[17,19,21,23,25,30,31]. The included studies achieved NOS scores ranging from six to eight, reflecting a generally moderate to high quality of methodology and reporting (Table 2).

Table 1 Characteristics of the included studies.

Ref.	Country	Design	No. of patients with DM	Mean age (years)	Men (%)	Duration of diabetes (years)	No. of patients with DFU	Definition of anemia	Outcomes reported	Variables matched or adjusted
Hokkam et al[16], 2009	Egypt	CC	300	57.6	58.7	17.1	180	NR	OR of anemia	Age, duration of diabetes, insulin use, and smoking
Khanbhai et al[17], 2012	UK	CC	40	65	60	NR	10	NA	Difference of HGB	None
Jiang et al[18], 2015	China	CC	1333	58.7	58.8	8.7	452	NA	Difference of HGB and OR per 1-g/dL decrease of HGB	Age, sex, BMI, blood lipids, smoking, diabetic complications, OADs, and insulin use
Alsayegh et al[19], 2017	Kuwait	CS	1580	52.3	50.3	NR	429	Males < 13 g/dL, females < 12 g/dL	OR of anemia	None
Shareef et al[20], 2019	Pakistan	CC	322	NR	73.9	NR	161	Males < 13 g/dL, females < 12 g/dL	Difference of HGB and OR of anemia	Age, sex, blood lipids, and HbA1c
Shi et al[21], 2021	China	CC	1001	58.7	71.5	10.8	494	NA	Difference of HGB	None
Shi et al[21], 2021	China	CC	487	61.7	71.7	9.5	231	NA	Difference of HGB	None
Jiang et al[22], 2022	China	CS	853	60.5	69.2	11.7	369	NA	OR per 1-g/dL decrease of HGB	Age, sex, duration of DM, smoking, diabetic complications, and comorbidities
Ardelean et al[24], 2023	Romania	CS	112	63.8	66.1	NR	80	NA	Difference of HGB	Age, sex, BMI, and DM duration
Li et al[25], 2023	China	CS	334	67.3	52.1	9.8	84	NA	Difference of HGB	None
Li et al[26], 2023	China	CS	145	67.9	53.8	12.1	80	NA	Difference of HGB and OR per 1-g/dL decrease of HGB	Age, sex, DM duration, Scr, HbA1c, Alb, TC and CRP
Afrid et al[23], 2023	Pakistan	CS	371	42.6	73.4	8.7	97	Males < 13 g/dL, females < 12 g/dL	OR of anemia	None
Rupasinghe et al[30], 2024	Sri Lanka	CS	252	56.9	48.8	NR	18	Males < 13 g/dL, females < 12 g/dL	OR of anemia	None
Zaki et al[31], 2024	Saudi Arabia	CS	100	60	74	NR	81	Males < 13 g/dL, females < 12 g/dL	OR of anemia	None
Fan et al[28], 2024	US	CS	161834	65.8	62.4	NR	47604	Database codes of IDA	OR of anemia	Age, sex, comorbidities, and ethnicity
Cao et al[27], 2024	US	CS	1673	64.7	52.6	NR	136	Males < 13 g/dL, females < 12 g/dL	OR of anemia	Age, sex, race and ethnicity, BMI, comorbidities, smoking, alcohol drinking, blood lipids, HbA1c, and serum ferritin
Jiang et al[29], 2024	China	CS	212	65	53.3	11.3	105	NA	Difference of HGB and OR per 1-g/dL decrease of HGB	Age, sex, DM duration, PAD, smoking, blood lipids, and SCr

Alb: Albumin; BMI: Body mass index; CC: Case-control; CRP: C-reactive protein; CS: Cross-sectional; DFU: Diabetic foot ulcer; DM: Diabetes mellitus; HbA1c: Hemoglobin A1c; HGB: Hemoglobin; NR: Not reported; OR: Odds ratio; PAD: Peripheral artery disease; SCr: Serum creatinine; TC: Total cholesterol.

Table 2 Study quality evaluation via the Newcastle-Ottawa scale.

Ref.	Adequate definition of cases	Representativeness of cases	Selection of controls	Definition of controls	Control for age	Control for other confounders	Exposure ascertainment	Same methods for events ascertainment	Non-response rates	Total
Hokkam et al[16], 2009	0	1	1	1	1	1	0	1	1	7
Khanbhai et al[17], 2012	1	0	1	1	0	0	1	1	1	6
Jiang et al[18], 2015	1	0	1	1	1	1	1	1	1	8
Alsayegh et al[19], 2017	1	1	1	1	0	0	1	1	1	7
Shareef et al[20], 2019	0	1	1	1	1	1	1	1	1	8
Shi et al[21], 2021	1	1	1	1	0	0	1	1	1	7
Jiang et al[22], 2022	1	0	1	1	1	1	1	1	1	8
Ardelean et al[24], 2023	0	1	1	1	1	1	1	1	1	8
Li et al[25], 2023	0	1	1	1	0	0	1	1	1	6
Li et al[26], 2023	1	0	1	1	1	1	1	1	1	8
Afrid et al[23], 2023	1	0	1	1	0	0	1	1	1	6
Rupasinghe et al[30], 2024	1	0	1	1	0	0	1	1	1	6
Zaki et al[31], 2024	1	0	1	1	0	0	1	1	1	6
Fan et al[28], 2024	0	0	1	1	1	1	0	1	1	6
Cao et al[27], 2024	1	0	1	1	1	1	1	1	1	8
Jiang et al[29], 2024	1	0	1	1	1	1	1	1	1	8

OR for the association between anemia and DFU

Overall, eight studies[16,19,20,23,27,28,30,31] (n = 166173) reported on the association between anemia and DFUs. Because two studies[19,20] reported the outcomes in men and women separately, these datasets were included independently in the meta-analysis, resulting in a total of 10 datasets. The pooled results indicated that anemia in diabetic patients was significantly associated with a higher risk of DFU (OR: 2.72, 95%CI: 1.73-4.25, P < 0.001; I² = 93%; Figure 2A). Sensitivity analyses were performed by excluding one dataset at a time, which did not significantly change the results (OR: 2.19-3.05, P all < 0.05). Subsequent subgroup analyses indicated that the association between anemia and DFU was more pronounced in case-control studies compared to cross-sectional studies (OR: 2.77 vs 1.81, P for subgroup difference < 0.001; Figure 2B). Further subgroup analyses yielded similar results across studies with mean patients ages < or ≥ 55 years (P for subgroup difference = 0.53; Figure 2C), studies with a proportion of men < or ≥ 60% (P for subgroup difference = 0.92; Figure 2D), studies employing univariate or multivariate analyses (P for subgroup difference = 0.30; Figure 2E), and studies with varying NOS scores (P for subgroup difference = 0.54; Figure 2F).

Figure 2 Forest plots for the meta-analysis of the association between anemia and the risk of diabetic foot ulcers in patients with diabetes. A: Overall meta-analysis; B: Subgroup analysis according to study design; C: Subgroup analysis according to the mean ages of the patients; D: Subgroup analysis according to the proportion of men of the included patients; E: Subgroup analysis according to the analytic models; F: Subgroup analysis according to the Newcastle–Ottawa Scale scores of the included studies. NOS: Newcastle–Ottawa Scale.

OR for the risk of DFU per 1-g/dL decrease of hemoglobin

The pooled results of four studies[18,22,26,29] (n = 2543) indicated that the per 1-g/dL decrease of serum hemoglobin was associated with an increased risk of DFU (OR: 1.65, 95%CI: 1.21-2.27, P = 0.002; I² = 68%; Figure 3A). Sensitivity analyses, conducted by excluding one dataset at a time, did not significantly change the results (OR: 1.45-1.89, P all < 0.05).

Figure 3 Forest plots for the meta-analysis of the secondary outcomes. A: Meta-analysis for the risk of diabetic foot ulcers per 1-g/dL decrease of hemoglobin; B: Meta-analysis comparing serum hemoglobin between diabetic patients with and without diabetic foot ulcer. DFU: Diabetic foot ulcer; DM: Diabetes mellitus.

Difference of serum hemoglobin between diabetic patients with and without DFU

The meta-analysis involving nine studies[17,18,20,21,24-26,29] (n = 3986) indicated that diabetic patients with DFU had a significantly lower level of serum hemoglobin compared to those without DFU (MD: -2.13 g/dL, 95%CI: -2.58 to -1.68, P < 0.001; I² = 90%; Figure 3B). Further sensitivity analyses, conducted by omitting one dataset at a time, yielded similar results (-1.95 to -2.24, P all < 0.05).

Publication bias

The funnel plots for the meta-analysis assessing the association between anemia and DFUs are presented in Figure 4A. Visual inspection of the plots revealed symmetry, indicating a low risk of publication bias, which was further corroborated by Egger’s regression analysis (P = 0.26). Similarly, the funnel plots for the meta-analysis comparing serum hemoglobin between diabetic patients with and without DFU (Figure 4B) also appear symmetrical, suggesting a low likelihood of publication bias. Egger’s regression analysis for this comparison also revealed a low risk of publication bias (P = 0.33). However, the assessment of publication bias underlying the meta-analysis regarding the risk of DFU per 1-g/dL decrease in serum hemoglobin could not be determined, as only four studies were included for this outcome.

Figure 4 Funnel plots for estimating the potential publication biases underlying the meta-analyses. A: Funnel plots for the meta-analysis of the association between anemia and the risk of diabetic foot ulcers in patients with diabetes; B: Funnel plots for the meta-analysis comparing serum hemoglobin between diabetic patients with and without diabetic foot ulcers. MD: Mean difference; OR: Odds ratio; SE: Standard error.

DISCUSSION

The results of this meta-analysis consistently demonstrated a significant association between anemia and an increased risk of DFU in patients with DM. The pooled OR for the primary outcome, which examined the association between anemia and DFU, was 2.72, which indicates that diabetic patients with anemia have more than twice the odds of developing a DFU compared to those without anemia. Additionally, the risk of DFU increased with every 1-g/dL decrease in hemoglobin, with a pooled OR of 1.65. This finding was further supported by the observed lower serum hemoglobin levels in diabetic patients with DFU compared to those without, with a MD of -2.13 g/dL. The quality evaluation of the included studies with NOS showed moderate to high quality, and moderate to substantial heterogeneity was observed underlying the above outcomes. The results of the meta-analysis suggest that anemia is a significant and independent risk factor for DFU, reinforcing the importance of monitoring and managing anemia in diabetic patients to potentially reduce the burden of diabetic foot complications.

Our meta-analysis differs from the previous meta-analysis by Yammine et al[6], which focused exclusively on patients with DFUs and examined anemia prevalence across different DFU severities. Their findings demonstrated that severe DFU cases had lower hemoglobin levels and worse outcomes, including non-healing ulcers, amputation, and increased mortality[6]. In contrast, our meta-analysis assesses whether anemia is a risk factor for the development of DFU. By including diabetic patients with and without DFUs, we provide a broader epidemiological perspective on anemia as a potential modifiable risk factor for DFU onset. This distinction highlights the necessity of our study, as understanding risk factors for DFU development is crucial for primary prevention. Future research should explore the relationship between anemia severity and DFU severity to further clarify its clinical implications.

The underlying mechanisms linking anemia to DFU development remain speculative, and to the best of our knowledge, no experimental studies have directly evaluated this relationship. However, potential pathways can be hypothesized based on broader pathophysiological insights. Anemia, characterized by reduced hemoglobin levels, diminishes the blood’s oxygen-carrying capacity, which is essential for tissue repair and wound healing[37]. Anemia-induced hypoxia may impair fibroblast function, collagen synthesis, and angiogenesis, with hypoxia-inducible factor-1α potentially playing a role[38]. Increased systemic inflammation, as evidenced by elevated cytokines such as interleukin-6 and tumor necrotic factor-α, could contribute to chronic inflammatory states and oxidative stress, further delaying wound healing[39]. Additionally, anemia-related endothelial dysfunction and nitric oxide depletion may exacerbate microvascular ischemia, worsening diabetic neuropathy and peripheral artery disease, which are known contributors to DFU risk[40]. Moreover, reduced blood flow and oxygen delivery to the lower extremities may further compromise the healing of diabetic foot wounds, increasing their susceptibility to infection and delaying recovery[41]. While our meta-analysis confirms the epidemiological association between anemia and DFUs, future experimental studies are needed to validate these mechanisms and explore potential therapeutic targets.

The findings of our meta-analysis revealed that the association between anemia and DFUs was stronger in case-control studies than in cross-sectional studies. This discrepancy may have stemmed from variations in study design and patient selection. Case-control studies are specifically designed to focus on identifying risk factors by comparing individuals with DFUs to those without, which can lead to a more accurate identification of the factors associated with DFU development, including anemia[42]. In contrast, cross-sectional studies typically assess associations at a single point in time, which may limit the ability to draw conclusions about the temporal relationship between anemia and DFUs[43]. Moreover, case-control studies often employ more rigorous matching and adjustment for confounding factors, thus leading to more robust findings. The lack of significant differences in the association across various subgroups based on demographic characteristics, such as age, sex, or proportion of men, indicates that the impact of anemia on DFU risk is consistent across diverse patient populations. This further supports the role of anemia as a modifiable risk factor for DFUs in diabetic patients.

This meta-analysis has several strengths that enhance the validity of its findings. First, it includes up-to-date literature, including studies published up to November 2024, ensuring that the analysis reflects the most current evidence on the topic. Second, we evaluated multiple outcomes to assess the association between anemia and DFUs, including the risk of DFUs per 1-g/dL decrease in hemoglobin and the difference in hemoglobin levels between diabetic patients with and without DFU. These complementary analyses provide a comprehensive understanding of how anemia may influence DFU risk across different hemoglobin levels. Third, sensitivity and subgroup analyses were performed to test the robustness of the results. These analyses, which involved assessing individual studies one at a time to consider the influence of study design, patient characteristics, and methodological quality, consistently supported the primary finding that anemia is a significant risk factor for DFUs. This strengthens the overall conclusions drawn from the meta-analysis and minimizes the potential impact of bias or confounding factors.

However, several limitations should be considered when interpreting the results. First, the included studies were observational in design, which limits the ability to establish causality. In addition, we included observational studies with varying designs, which potentially introduced confounding factors. However, subgroup analyses according to study design revealed a significant association between anemia and DFUs in both cross-sectional and case-control studies. Besides, although the results consistently suggested an association between anemia and DFU risk, we cannot definitively conclude that anemia directly causes DFUs. Longitudinal and prospective studies are needed to confirm the causal relationship between anemia and DFUs in diabetic patients. Second, there was significant heterogeneity across the studies, as indicated by the I² statistic, particularly for the primary outcome. This variability may be attributed to differences in study design, population characteristics, and definitions of anemia, as well as potential confounding factors that were not consistently adjusted for across studies. Despite performing subgroup analyses to explore the sources of heterogeneity, the presence of unexplained variability means that the results should be interpreted with caution. Another important limitation is the lack of data on glycemic control, particularly HbA1c levels, in diabetic patients with and without DFU. Since poor glycemic control is associated with both DFU development and anemia—via mechanisms such as chronic inflammation and microvascular dysfunction—it poses a potential confounder that we could not fully account for in our analysis. Future studies should investigate the role of glycemic status in modifying the relationship between anemia and DFU risk. Third, some of the included studies did not fully adjust for all potential confounding factors, such as comorbidities, diabetes duration, or treatment regimens, which may have influenced both anemia and DFU risk. These unadjusted factors could introduce bias into the findings and limit the generalizability of the results. Finally, our analysis was unable to differentiate between types of anemia due to limited data in the included studies. Different anemia subtypes, such as iron deficiency anemia, anemia of chronic disease, or renal anemia, may have varying impacts on DFU risk. Future studies should aim to distinguish between anemia subtypes to better understand their specific roles in DFU pathogenesis.

Given that our meta-analysis is based on observational studies, we could not definitively establish a causal relationship between anemia and DFUs. While the consistent association observed supports a potential link, future prospective cohort studies are needed to confirm whether anemia precedes and contributes to DFU development. Additionally, interventional trials assessing whether anemia correction improves DFU outcomes would provide valuable clinical insights. Further research should also explore optimal treatment strategies for anemia in diabetic patients at risk of DFUs, as this could potentially reduce their burden and improve wound healing. Additionally, studies should explore the mechanisms by which anemia exacerbates DFU risk, including the roles of hypoxia, inflammation, and vascular dysfunction. Investigating optimal management strategies for anemia in diabetic patients at risk for DFUs is crucial, as this could lead to more targeted and effective treatment protocols. Finally, it would be valuable to assess whether correcting anemia could improve DFU healing and reduce the need for amputations in this patient population.

CONCLUSION

In conclusion, this meta-analysis provides reasonable evidence of an association between anemia and the risk of DFUs in patients with DM. Despite the limitations inherent in observational studies and the heterogeneity observed across the included studies, these findings highlight the importance of anemia as a modifiable risk factor for DFUs. Clinicians should consider monitoring hemoglobin levels in diabetic patients and address anemia as part of a comprehensive strategy to prevent and manage diabetic foot complications. Further research is needed to confirm these findings, explore the underlying mechanisms, and investigate potential interventions aimed at reducing the burden of DFUs in diabetic patients. Future randomized trials should also investigate the association between anemia treatment and improvement of DFU incidence and healing.