Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus that affects approximately one-third of diabetic patients (1). It causes varying degrees of visual impairment (2), which significantly impacts the quality of life of patients and imposes substantial economic burdens on society (3). Notably, its pathogenesis is complex and multifaceted, including oxidative stress, inflammation, and mitochondrial disorders, among others (4). At present, there is a pressing need to identify the risk factors and intervention strategies for DR in order to enhance the prognosis of patients with DR.

As is well documented, heavy metals are ubiquitously present in the air, soil, water, food, and manufactured products (5–9). Exposure to heavy metals may increase the risk of various ocular diseases, including DR, age-related macular degeneration (AMD), glaucoma, and cataracts (10–13). Zhu et al. demonstrated that the accumulation of serum cesium (Cs) and cadmium (Cd) was significantly correlated with the risk of developing DR (10). Similarly, the findings of Li et al. indicated that exposure to certain heavy metals, including lithium (Li), Cd, strontium (Sr), and magnesium (Mg), may increase the risk of developing proliferative DR, whereas selenium (Se) appears to be a protective factor (14). Zhang et al. observed a significant negative correlation between serum manganese (Mn) levels and DR prevalence in individuals with type 2 diabetes mellitus in the United States (15). However, the correlation between serum Cd, mercury (Hg), and lead (Pb), and DR was not statistically significant (15). Other studies have determined a potential association between cobalt (Co), barium (Ba), molybdenum (Mo), antimony (Sb), thallium (Tl), and tungsten (Tu) and the risk of diabetes (16–18), but their relationship with DR remains elusive. Although previous studies have preliminarily explored the link between heavy metals and DR, certain limitations remain. For instance, earlier studies exclusively investigated the association between the levels of serum heavy metals and DR risk, with a lack of research on the effect of urinary heavy metals on DR. Serum heavy metal levels may correlate with recent exposure, whereas urine heavy metal concentrations reflect long-term exposure (19). Furthermore, heavy metals are frequently co-exposed in the environment, and interactions between metals may also have an impact on human health (20, 21). However, studies on co-exposure to heavy metals and DR risk are lacking. Additionally, there is a lack of epidemiological studies to elucidate the effects of other heavy metals, such as Co and Sb, on the risk of developing DR.

The present study extracted U.S. demographic data from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 to investigate the relationship between heavy metals and the risk of DR. A total of 10 urinary heavy metals, namely Ba, Cd, Co, Cs, Mo, Pb, Sb, Tl, Tu, and Hg were analyzed. The effect of single and multiple metals on DR risk was evaluated using weighted logistic regression analysis. Furthermore, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) model were applied to investigate the relationship between heavy metals co-exposure and DR. In addition, dose–response relationships between heavy metals and DR were explored using restricted cubic spline (RCS) regression. Lastly, subgroup analysis was conducted based on glycemic control levels. Our findings are anticipated to provide new epidemiological evidence to enhance the understanding of the correlation between heavy metals and DR and assist in the prevention of DR.

To the best of our knowledge, this is the first cross-sectional study to investigate the effects of urinary heavy metals on the risk of DR in a substantial, nationally representative sample utilizing various statistical techniques. Herein, the results of weighted logistic regression demonstrated that Co, Sb, and Hg were associated with DR risk in the single-metal model, and this association was also observed in the multi-metal model. Both the WQS and BMKR models suggested that mixed exposure to these 10 heavy metals was positively associated with DR risk. Furthermore, the results of the RCS regression displayed a linear and positive correlation between Co and Sb and DR risk but a non-linear correlation between Hg concentrations and DR risk. The results of the subgroup analyses signaled that the aforementioned associations appeared to be more pronounced in the poorly-controlled group.

Co is widely distributed in nature. Humans are commonly exposed to Co through multiple routes, including food, environmental pollution, occupational exposure, and medical interventions (34). Besides, it is an essential element for human health, serving as the metallic component of vitamin B12 (35). Despite its vital importance, its potential toxicity can elicit adverse health effects after prolonged exposure. A cross-sectional study identified a positive correlation between diabetes and urinary Co concentrations (16). Consistently, a study discovered a strong correlation between elevated urinary Co levels and increased levels of FPG and HbA1c in male participants (36). At the same time, Cancarini et al. concluded that the Co concentration in the tear film of diabetic patients was higher than that in the control group (37). This increase may be attributed to the rise in conjunctival vascular permeability caused by diabetes, similar to the increase in retinal vascular permeability driven by diabetes (a characteristic of DR) (38). In our study, diabetic patients with higher urinary concentrations of Co were more likely to develop DR. This may be ascribed to the oxidizing effect of Co promoting the formation of free radicals, inducing oxidative stress responses, and contributing to mitochondrial dysfunction (39). Of note, accumulating evidence suggests that oxidative damage and mitochondrial dysfunction promote the development of DR (40, 41).

Sb is a toxic heavy metal to which humans are primarily exposed through the consumption of food and air, soil, and water exposure. Numerous studies have demonstrated that it exerts various toxic effects on vital organs, including but not limited to the pancreas, liver, lungs, intestines, and spleen (42). A cross-sectional study conducted in the USA demonstrated an association between urine Sb concentrations and insulin resistance (16). Likewise, a cross-sectional study conducted in China found that urinary Sb levels are linked to an increased risk of increased FPG levels, impaired fasting glucose, and diabetes (18). Furthermore, a prospective study indicated that pregnant women with higher exposure to Sb may face an increased risk of gestational diabetes mellitus (43). Xiao et al. reported that elevated urinary Sb concentrations are linked to a higher incidence of type 2 diabetes, and this process is partially implicated in oxidative DNA damage (44). These studies collectively imply that Sb exposure may contribute to the development of diabetes. However, to date, there has been no report on the correlation between Sb levels and DR. Our study uncovered that diabetic patients with elevated urinary Sb levels have a significantly increased risk of developing DR, especially in those with poor glycemic control.

Hg is a highly toxic heavy metal that can cause significant harm to numerous organs in the human body (45). Currently, research on the relationship between Hg levels and diabetes risk remains inconclusive. Earlier studies found no significant association between blood or urine Hg concentrations and an increased risk of diabetes in adults (46–48). However, Tsai et al. observed a significant increase in Hg levels in the red blood cells of type 2 diabetes patients compared to those without the condition (49). A large prospective cohort study determined that people with high Hg exposure during early adulthood were at a higher risk of developing diabetes in the future (50). Furthermore, research has demonstrated that Hg can selectively affect β cells in the pancreas, resulting in cellular dysfunction and apoptosis (51). In this study, urine Hg levels among diabetes patients with DR were higher compared to those without DR, although the difference was not statistically significant. Additionally, a clear non-monotonic relationship was identified between Hg levels and the risk of DR. This may be due to the fact that the chief source of human exposure to Hg is the consumption of marine fish, which are rich in omega-3 fatty acids that counteract the toxicity of Hg (52, 53). A significant positive correlation was observed between Hg concentrations and DR risk only in the well-controlled group, warranting further investigation.

Heavy metals stimulate reactive oxygen species production, leading to oxidative damage, which is one of the mechanisms involved in disease development (54). The retina is a high-oxygen-consuming tissue that is highly susceptible to damage from oxidative stress. Previous studies have shown a robust correlation between oxidative stress and retinal vascular impairment under hyperglycemic conditions (55). However, the role of heavy metals in DR development via oxidative stress mechanisms remains unclear. Thus, further experimental validation is necessary.

This study has several advantages. Firstly, it is the first study that investigated the correlation between urinary heavy metals and DR risk, considering both the single and co-exposure effects of heavy metals. In contrast, Zhang et al. focused on the relationship between blood heavy metals and DR risk without exploring the combined effects of heavy metals on DR (15). Furthermore, our study included a higher number of metals than those conducted by Zhang et al. (15) and reported for the first time that urinary levels of Co, Sb, and Hg may be associated with DR risk. Secondly, weighted logistic regression, WQS regression model, BMKR model, and RCS regression were employed to investigate the correlation between heavy metals and DR risk in a diabetes population from multiple perspectives. These statistical methods have been extensively utilized to explore the effects of heavy metals on diabetes and hypertension (21, 56). Finally, previous research has demonstrated a correlation between heavy metal exposure and HbA1c levels. High HbA1c level has been established as a risk factor for DR. Therefore, subgroup analysis was initially conducted based on glycemic control (determined by HbA1c value) to investigate the correlation between urine levels of heavy metals and DR risk.

Nevertheless, some limitations of this study merit acknowledgment. Given the inherent shortcomings of cross-sectional studies (57), this study could not establish a causal relationship between metal exposure and the risk of DR. Furthermore, relying on self-report questionnaires for DR diagnosis may introduce recall bias. In addition, the dataset lacked precise information regarding retinopathy severity, thereby limiting further analysis. The concentrations of heavy metals in urine are affected by various factors, not all of which were accounted for in this study, potentially compromising the reliability of the results. Additionally, selection bias selection bias may be present due to missing data and the exclusion of participants with incomplete information. Therefore, further studies are necessitated to corroborate our findings and to investigate the relationship between metal concentrations and DR severity, as well as to elucidate the underlying mechanisms by which metals affect DR.

Overall, our cross-sectional study demonstrated that several heavy metals, including Co, Sb, and Hg, were significantly associated with an elevated risk of DR. Furthermore, a linear and positive correlation was observed between the concentrations of Co and Sb and the risk of DR, while a non-linear correlation was identified between Hg levels and DR risk. The results of the subgroup analyses signaled that the aforementioned associations appeared to be more pronounced in the poorly-controlled group. The results of the mixture exposure analysis indicated a positive association between mixed metal exposure and the risk of DR. This association was observed in both the well-controlled group and the poorly-controlled group. Due to the limitations of the present study, subsequent investigations are required to substantiate these findings and to clarify the mechanisms by which heavy metals affect DR.

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

CM: Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. CG: Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. CC: Formal analysis, Methodology, Writing – review & editing. SH: Formal analysis, Methodology, Writing – original draft. DL: Data curation, Methodology, Writing – original draft. QQ: Conceptualization, Supervision, Writing – review & editing.