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Article

Diabetic Kidney Disease Associated with Chronic Exposure to Low Doses of Environmental Cadmium

by
Soisungwan Satarug
1,*,
Tanaporn Khamphaya
2,
Donrawee Waeyeng
3,
David A. Vesey
1,4 and
Supabhorn Yimthiang
2
1
Centre for Kidney Disease Research, The University of Queensland, Translational Research Institute, Woolloongabba, Brisbane, QLD 4102, Australia
2
Occupational Health and Safety, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand
3
Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand
4
Department of Kidney and Transplant Services, Princess Alexandra Hospital, Brisbane, QLD 4102, Australia
*
Author to whom correspondence should be addressed.
Stresses 2026, 6(1), 4; https://doi.org/10.3390/stresses6010004 (registering DOI)
Submission received: 27 November 2025 / Revised: 21 December 2025 / Accepted: 15 January 2026 / Published: 16 January 2026
(This article belongs to the Section Animal and Human Stresses)
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Abstract

Accumulating evidence suggests that exposure to pollution from environmental cadmium (Cd) contributes to diabetic kidney disease as indicated by albuminuria and a progressive decrease in the estimated glomerular filtration rate (eGFR). This study examined the effects of Cd exposure on eGFR and the excretion rates of albumin (Ealb) and β2-microglobulin (Eβ2M) in 65 diabetics and 72 controls. Excretion of Cd (ECd) was a measure of exposure, while excretion of N-acetylglucosaminidase (ENAG) reflected the extent of kidney tubular cell injury. In participants with an elevated excretion of Eβ2M, the prevalence odds ratios (POR) for a reduced eGFR rose 6.4-fold, whereas the POR for albuminuria rose 4.3-fold, 4.1-fold, and 2.8-fold in those with a reduced eGFR, diabetes, and hypertension, respectively. Using covariance analysis, which adjusted for the interactions, 43% of the variation in Ealb among diabetics could be explained by female gender (η2 = 0.176), ENAG (η2 = 0.162), hypertension (η2 = 0.146), smoking (η2 = 0.107), and body mass index (η2 = 0.097), while the direct contribution of ECd to Ealb variability was minimal (η2 = 0.005). Results from a mediating-effect analysis imply that Cd could contribute to albuminuria and a falling eGFR through inducing tubular cell injury, leading to reduced reabsorption of albumin and β2M.

Graphical Abstract

1. Introduction

Prediabetes and diabetes (DM) are, respectively, designated when fasting plasma glucose (FPG) concentrations are ≥110 and ≥126 mg/dL [1]. Persistent albuminuria and a progressive decline in an estimated glomerular filtration rate (eGFR) are the complications of diabetes, known as diabetic kidney disease (DKD) [2,3,4]. The severity of DKD has been based on albumin excretion rate (Ealb), expressed as urinary albumin-to-creatinine ratio (ACR) where microalbuminuria and macroalbuminuria are described [3,4]. Notably, however, about 30% of DKD patients had abnormal eGFR together with normal ACR figures; <20 mg/g creatinine (cr) in men and <30 mg/g cr in women [4,5,6].
A wide spectrum of DKD has increasingly been recognized, suggesting involvement of different pathogenic factors. Exposure to low doses of the metabolic stressor, cadmium (Cd), has emerged as one of the potential contributors to DKD onset and its progression; the mechanism, however, remains unclear. Cd is a widespread xenometal with no physiological role in the body or nutritional value but it can induce, in multiple tissues and organs, oxidative stress, chronic systemic inflammation, and insulin resistance [7].
Acquired Cd accumulates mostly within the kidney tubular cells, where its levels increase through to the age of 50 years but decline thereafter due to its release into the urine as the injured tubular cells die for any reason [8]. Thus, excretion of Cd (ECd) reflects kidney accumulation of Cd and its nephrotoxicity at the present time [9]. A prospective cohort study causally linked a fall of eGFR at a high rate to ECd [10]. Furthermore, increased risks of prediabetes, diabetes and albuminuria were associated with ECd, while FPG correlated with ECd [11,12,13,14,15]. Excretion of N-acetylglucosaminidase (NAG) and kidney injury molecule-1 have also been related to ECd [16,17,18].
The kidney and liver are the two organs in the body that produce and release glucose into the circulation; 30% of the gluconeogenesis during fasting state comes from the kidney [19,20,21,22]. In addition, the kidney is responsible for filtration, and retrieval of 160 to 180 g of glucose each day, mediated by the sodium glucose co-transporter 1 (SGLT1) and SGLT2 [22]. Increased abundance of the glucose transporters may raise the renal threshold for glucose excretion [20]. The deterioration of eGFR in DKD patients can be attenuated by SGLT2 inhibitors [23].
Intriguingly, the excretion rates of NAG (ENAG) and β2-microglobulin (Eβ2M) were enhanced in DM [24,25,26,27,28], while glycemic risk indices were associated with an elevated ENAG that preceded albuminuria [29]. This study explored how Cd exposure induces albuminuria and a falling eGFR by examining associations of Ealb, ENAG and eGFR in Cd-exposed DM (n = 65) and Cd-exposed controls (n = 72). Also, we show the effects of adjusting Ealb, ENAG, Eβ2M, and ECd to creatinine excretion (Ecr) that could obscure Cd effects.

2. Results

2.1. Descriptive Data on the Controls and Diabetics

This cohort had 30 men and 107 women with an overall mean age (range) of 59.7 (41–80) years and an overall mean BMI (range) of 25.6 (15–48) kg/m2 (Table 1).
Respective percentages (%) of smoking, reduced eGFR, and hypertension were 10.4, 11.9, and 54.2. Nearly half (49.3%) had FPG ≥ 110 mg/dL, while 39.6% had FPG ≥ 126 mg/dL. One of the 72 subjects (1.4%), recruited to the non-diabetic control group, had FPG ≥ 126 mg/dL, a diabetes diagnosis level. The overall % Ecr-based albuminuria was 22.4 and 26 for Ccr-based albuminuria.
Across the three groups, % smoking and reduced eGFR were similar, while % hypertension was highest, middle, and lowest in the ≥10 yr DM (80), <10 yr DM (54.1), and CTRL (44.9). Ccr-based microalbuminuria was highest, middle, and lowest in the ≥10 yr DM (52), <10 yr DM (33.3), and CTRL (12.9), while % macroalbuminuria were 0, 10.8, and 8. The variations in age, eGFR, DBP, ECd/Ecr, and ECd/Ccr across the three groups were insignificant. The variables showing significant variations across the three study groups were BMI, FPG, SBP, [β2M]u, Ealb/Ecr, and Ealb/Ccr.

2.2. Comparing Cd Exposure and Other Measured Variables in Three Study Groups

The distribution of ECd, eGFR, FPG ([Glc]p), and serum β2M are presented in Figure 1.
Neither ECd/Ccr (Figure 1A) nor eGFR (Figure 1B) show a significant variation across the three study groups, while FPG (Figure 1C) and serum β2M (Figure 1D) were higher in diabetics than controls.
Figure 2 presents the distribution of data on kidney tubular cell injury (ENAG/Ccr) and its function, assessed with Ealb/Ccr, Eβ2M/Ccr, and FrTDβ2M.
ENAG/Ccr (Figure 2A), Ealb/Ccr (Figure 2B), and Eβ2M/Ccr (Figure 2C) were elevated in the diabetics, compared to controls, while the FrTDβ2M was reduced in the diabetics compared to controls (Figure 2D).

2.3. Logistic Regression Modeling of Albuminuria and a Reduced eGFR

Logistic regression model analysis was used to define the determinants of the prevalence odds ratios (POR) for albuminuria and a reduced eGFR (Table 2).
Age, BMI, ECd/Ccr, smoking, and gender had little effects on the POR for albuminuria. However, this parameter was increased 4.3-fold, 4.1-fold, and 2.8-fold in those with reduced eGFR (p = 0.027), diabetes (p = 0.020), and hypertension (p = 0.032). Age and Eβ2M/Ccr ≥ 3, µg/L filtrate were associated with 1.15-fold and 6.4-fold increases in the POR for reduced eGFR, respectively.
For Ecr-based data (Table S1), the POR for albuminuria was increased 5.7-fold, 7.1-fold, and 3.7-fold in women (p = 0.015), those with diabetes (p < 0.001), and hypertension (p = 0.027). Notably, however, an association of Ecr-based albuminuria with reduced eGFR did not reach a statistically significance level (p = 0.052). Age was the only variable associated with reduced eGFR (POR 1.052, p = 0.002) (Table S2).
In a covariance analysis, the models explained significant fractions of Ealb in CTRL, DM, women, <10 yr DM, ≥ 10 yr DM, and the normal eGFR group, but they explain a little variation of Ealb in men and the reduced eGFR group (Table 3 and Table 4). Results of covariance analysis of Ealb using Ecr-based data are provided in Table S3.
In CTRL (Table 3), Ealb was explained by FrTDβ2M (η2 = 0.228), hypertension (η2 = 0.210), smoking (η2 = 0.194), and gender (η2 = 0.115). In DM, Ealb was explained by gender (η2 = 0.176), ENAG (η2 = 0.162), hypertension (η2 = 0.146), smoking (η2 = 0.107), and BMI (η2 = 0.097).
In the <10 yr DM group (Table 4), Ealb was explained by gender (η2 = 0.370), smoking (η2 = 0.254) and ENAG (η2 = 0.158). Hypertension was the most influential variable affecting Ealb (η2 = 0.576), followed by smoking (η2 = 0.482), and BMI (η2 = 0.427). The variation of Ealb in the normal eGFR was modestly explained by ENAG (η2 = 0.082) and hypertension (η2 = 0.079).
In covariance analysis of eGFR, the models explained significant fractions of eGFR variability in CTRL, DM, women, <10 yr DM, ≥10 yr DM, and the normal eGFR group, but they explain a little eGFR variation in men and the reduced eGFR group (Table 5 and Table 6). Results of covariance analysis of eGFR using Ecr-based data are presented in Table S4.
In CTRL (Table 5), ENAG explained the largest fraction eGFR variation (η2 = 0.301). The eGFR variation among DM was explained by ENAG (η2 = 0.199), Eβ2M (η2 = 0.183), and age (η2 = 0.140). In women, eGFR was explained by ENAG (η2 = 0.222), FPG (η2 = 0.109), and Eβ2M (η2 = 0.072). In the ≥10 y DM group (Table 6), ENAG explained the largest fraction eGFR variation (η2 = 0.301). In the normal eGFR group, FPG explained the largest fraction of the eGFR variation (η2 = 0.151), followed by ENAG (η2 = 0.128) and Eβ2M (η2 = 0.065).

2.4. Bivariate Analysis of Ealb

Table 7 provides results of the Spearman’s rank correlation analysis.
Ealb varied inversely with FrTDβ2M (r = −0.237) and directly with FPG (r = 0.273), ENAG (r = 0.327), and Eβ2M (r = 0.265). A correlation between Ealb and ECd was insignificant. Apparently, the strength of the Ealb/ENAG correlation was the highest, compared to the other four variables tested. Consequently, scatterplots and regression analysis were used to further examine the Ealb and ENAG/Ccr relationship in subgroups (Figure 3).
Ealb showed a moderate association with ENAG in diabetics but not in controls (Figure 3A). It was strongly associated only with those who had FPG ≥ 110 mg/dL (Figure 3B). Ealb showed a strong association with Eβ2M in diabetics (Figure 3C) and those with FPG ≥ 110 mg/dL (Figure 3D). The associations of Ealb with Eβ2M in controls and those with FPG < 110 mg/dL were insignificant (Figure 3C,D).
Given the particularly strong correlation of eGFR versus ENAG (r = −0.467) (Table 5), scatterplots and regression analysis were used to further examine the correlations of eGFR with ENAG/Ccr in subgroups (Figure 4).
eGFR was inversely associated with Ealb only in women (Figure 4A) and those with hypertension (Figure 4B). It also showed an inverse association with ENAG in women only (Figure 4C). In those with hypertension, eGFR showed a more closely inverse association with ENAG, compared to the normotensive group.

2.5. The Mediating Effects of Cd on Ealb and eGFR

Cd explained insignificant proportions of the variations in Ealb and eGFR, while ENAG appeared to be a contributor to the variability of Ealb and eGFR (Table 4, Table 5 and Table 6). Thus, a simple mediation model analysis was conducted to determine whether Cd could influence Ealb and eGFR through ENAG (Figure 5).
In Figure 5, ENAG was depicted as the mediator of Cd effect on Ealb (model A) and eGFR (model B). In both models A and B, the Sobel test of the direct effects of Cd were insignificant, reflected by β values and p-values for the direct effect (c’) parameter. The significant indirect effect (a*b) inferred that ENAG mediated fully the effects of Cd on Ealb and eGFR (Figure 5a,b).

3. Discussion

The present Thai cohort with a modest sample size (65 DM and 72 CTRL) has provided several insights into the kidney’s responses to the metabolic stress (hyperglycemia) due to the perturbation by low doses of the xenometal Cd. The results of logistic regression modeling and covariance analyses of the specific kidney responses, namely albuminuria and a reduced eGFR, have revealed the dominant roles of the kidney tubular cells in these responses.

3.1. Urinary Cd, FPG, and Albuminuria in CTRL and DM

Urinary Cd has been widely used as an indicator of the body burden of the metal. Its use for such purposes is based on a direct relationship between urinary Cd and the accumulation of Cd in liver and kidneys [30,31,32,33]. Studies on Swedish kidney transplant donors showed that urinary Cd of 0.42 μg/g cr corresponded to kidney Cd of 25 μg/g wet tissue weight [32]; urinary Cd 0.34 μg/g cr in women corresponded to kidney Cd of 17.1 μg/g, and urinary Cd of 0.23 μg/g cr in men corresponded to kidney Cd of 12.5 μg/g [33].
A study from Korea reported an association between increased risk of DM with ECd levels of 2–3 µg/g cr, where a significant correlation was found between ECd and FPG [11]. In a study on a U.S. population adjusting for potential confounders, ECd of 1–2 μg/g cr was associated with 24–48% increases in risk of prediabetes and diabetes [12]. The low levels of Cd exposure experienced by cohort participants were reflected by the ECd geometric mean below 1 µg/g cr (Table 1). Such a low-level exposure was insufficient to induce DM, evident from an insignificant correlation between ECd and FPG (r = 0.166, p = 0.053) (Table 5) and the fact that macroalbuminuria was found only in the DM group. Because the DM and CTRL had ECd in the same range (Table 1, Figure 1), the observed macroalbuminuria could be attributed to DM. In comparison, however, microalbuminuria was found in all three study groups as such that the parameter could be induced by Cd. These data suggested that the kidney’s handling of albumin, including reabsorption and its degradation within the proximal tubular cells, were particularly sensitive to Cd, consistent with the studies from Spain and China, where the increment of albuminuria risk was observed at ECd as little as 0.3 µg/g cr [14,15].
Another notable finding was the tendency to understate and/or obscure the extent of tubular cell disturbance by Cd accumulation when ECd and Ealb were adjusted to Ecr (Tables S1–S4). For example, the % ACR-based microalbuminuria in the CTRL, <10 yr DM, and the ≥10 yr DM groups were 8.3, 35.1, and 44%, while the corresponding % of microalbuminuria in Ccr-based data were 12.9, 33.3, and 52% (Table 1). A clear-dose response relationship was apparent from the Ccr-based albuminuria prevalence data.

3.2. Albuminuria and Reduced eGFR: The Tubular Rule

In an analysis of risk factors for albuminuria (Table 2), diabetes, reduced eGFR and hypertension independently increased the risk for albuminuria. Age, BMI, ECd/Ccr, smoking, and gender had little effects on the prevalence odds for albuminuria in the present cohort. An impaired tubular function, indicated by Eβ2M/Ccr ≥ 3 µg/L filtrate and age, were independent risk factors for a reduced eGFR. Using Ecr-based data, the relationship between a reduced eGFR and risk of albuminuria was obscured as was the relationship between tubular dysfunction and a reduced eGFR (Tables S1 and S2).
Covariance analyses (Table 3 and Table 4) provide further evidence for the tubular roles in albuminuria onset and a falling eGFR. In CTRL, FrTDβ2M accounted for the largest fraction of the variation in Ealb (η2 = 0.228), while ENAG explained the largest fraction of the eGFR variation (η2 = 0.301). In DM, gender contributed the most to the variation in Ealb (η2 = 0.176) followed by ENAG (η2 = 0.162), hypertension (η2 = 0.146), smoking (η2 = 0.107), and BMI (η2 = 0.097). ENAG explained the largest fraction of eGFR variation in DM (η2 = 0.199), followed by Eβ2M (η2 = 0.183) and age (η2 = 0.140).
An independent association between ENAG and postprandial hyperglycemia comes from the glucose tolerance test conducted on Japanese subjects with prediabetes, where ENAG correlated directly with 2 h plasma glucose levels [25]. Of relevance, a suspected environmental diabetogenic chemical, bisphenol A, has been found to be associated with elevated ENAG levels [34].
The above observations are consistent with the SPRINT Trial, where clinical and demographic characteristics were found to be associated with unique profiles of tubular damage, which indicated under-recognized patterns of kidney tubule disease among individuals with reduced eGFR [35].

3.3. Different Responses in Men and Women

In subgroup analysis, an inverse association of eGFR and Ealb was found only in women (Figure 4A) as was an inverse association of eGFR with ENAG (Figure 4C). In covariance analysis, ENAG was the only variable that accounted for a significant proportion of the eGFR variation among men (η2 = 0.307). In comparison, 52% of the variation in the eGFR among women could be explained, where the highest contribution came from ENAG (η2 = 0.222), followed by FPG (η2 = 0.109), and Eβ2M (η2 = 0.072).
Intriguingly, in a study from Taiwan (n = 157, aged 20–29 years), adjusting for confounders, ENAG was associated with ECd in women, while Ealb and Eβ2M were associated with ECd in men [36]. Rising levels of plasma insulin in response to fasting and glucose stimulation due to impaired hepatic insulin extraction was evident in female rats only in a recent empirical study investigating the perturbation of glucose metabolism in rats exposed to Cd [37].
We speculate that differences in protective factors, like body iron status, zinc, and copper are key players. This speculation was based on the observation that urinary zinc-to-copper ratios were associated with worsening eGFR in women only (β = −7.76), while a positive association between eGFR and serum ferritin, an indicator of iron stores (β = 5.32), was found in men only [38]. Anemia may contribute to a rapid reduction in eGFR in DM [39]. The correlation between urinary copper-to-zinc ratio and kidney damage markers have been noted in a study from Mexico [40].
In a more recent study using rats exposed to Cd in drinking water for 1–6 months, Cd was found to cause a decrease in the iron content in proximal tubular cells [41]. Early experimental works suggested the involvement of female sex hormones such as progesterone and β-estradiol [42,43,44,45]. For instance, the hepatoxicity of Cd was enhanced by treating male Fischer 344 (F344) rats with progesterone [38,39,40], while progesterone was found to enhance cellular Cd accumulation [45], possibly through its effects on the abundance of ZIP/ZnT-specialized transport proteins for cellular Cd/zinc influx and efflux [46,47].

3.4. Mediation Analysis for the Indirect Effects of Cd

As shown in Table 5, Ealb correlated more strongly with ENAG than with FrTDβ2M, FPG, and Eβ2M, while a correlation between Ealb and ECd was insignificant. In subgroup analysis (Figure 3), the Ealb/ENAG association was present only in DM and those with FPG ≥ 110 mg/dL. Of relevance, a cross-sectional study from Japan (DM = 245, CTRL= 39) showed that Ealb/Ecr and ENAG/Ecr were associated with glycemia risk index, and the elevation of ENAG/Ecr occurred before the onset of albuminuria.
As also shown in Table 5, eGFR inversely correlated with ENAG (r = −0.467), and its inverse association with ENAG was found in women together with an inverse association of eGFR with Ealb (Figure 5). The small number of men (n = 29) compared to women (n = 106) was a likely explanation for the statistically insignificant eGFR/ENAG and eGFR/Ealb associations among men. A further research study with enough men is required, using mediation analysis (Figure 5).
In summary, covariance analysis of albuminuria and a reduced eGFR (Table 3 and Table 4) suggests the minimal direct contribution of Cd to albuminuria and eGFR reductions. However, results of the mediation analysis (Figure 5) imply that tubular injury (ENAG) could mediate the association of Cd with albuminuria and eGFR loss. These findings underscore the critical tubular role in maintaining plasma glucose levels, and the sustained injury to tubular cells from any causes can potentially influence risk of hyperglycemia. The kidney is known for producing and releasing glucose into the circulation as well as for the filtration and reabsorption of glucose, mediated primarily by SGLT2 [19,20,21,22]. In clinical trials, SGLT2 inhibitors attenuated the loss of eGFR and the progression to an end stage, and decreased the deaths from kidney failure 30–40% [23].
DKD is a leading cause of kidney failure, when dialysis or a kidney transplant is required for survival. Avoidance of foods known to contain high Cd may slow the progression of DKD to the end stage. Control of hypertension and FPG together with maintaining an optimal body weight are necessary to hinder DKD development and progression. These suggestions come from the covariance analyses, where FPG explained the largest fraction of the eGFR variation (η2 = 0.151), followed by ENAG (η2 = 0.128), and Eβ2M (η2 = 0.065) in subjects with a normal eGFR.
Hypertension was the most influential variable affecting Ealb (η2 = 0.576), followed by smoking (η2 = 0.482), and BMI (η2 = 0.427) in the ≥10 yr DM group. In comparison, Ealb variation in the <10 yr DM group was explained by gender (η2 = 0.370), followed by smoking (η2 = 0.254) and ENAG (η2 = 0.158). Neither BMI nor hypertension contributed significantly to Ealb in the <10 yr DM group.

3.5. Strengths, Limitations, and Future Investigations

A cross-sectional design with a Thai cohort was employed to uniquely explore the interaction of environmental exposure with diabetes. Its major strength was the use of multiple indicators of renal effects; eGFR, ENAG, Ealb, FrTDβ2M, and Eβ2M. A focus on women could be considered a strength because women represented a subgroup with an elevated risk of Cd nephrotoxicity, suitable for mechanistic investigation with a modest number of participants. Such a small sample size was justifiable because of the high proportions of Ealb (43%) and eGFR (60%) that could be explained for the DM group. Furthermore, 52% of the Ealb variation among women were explained, and 67% of the Ealb variation in the ≥10 yr DM group could be accounted for (Table 3, Table 4 and Table 5).
Unlike previous research that has examined the nephrotoxicity of Cd, the present work showed the indirect role of Cd via tubular injury in a diabetic context through a mediation analysis. Notably, however, a cross-sectional design precluded a causality inference. Findings underscore the tubular role in DKD pathogenesis, forming the foundation for future studies using structural equation modeling (SEM) to explore the potential reno-protective effects of plant foods.
Other limitations include a one-time-only assessment of Cd exposure and kidney function, the limited sample size, gender imbalance, and the inability to adequately adjust potential confounders.

4. Materials and Methods

4.1. Participants

Individuals with diabetes (n = 65) and non-diabetic controls (n = 72) in the present study were chosen from a pre-existing cohort of 88 persons with diagnosed diabetes and 88 without diabetes [48]. They met the enrollment criteria, which included living at current addresses for at least 40 years and attending annual health checkups at the Pak Poon municipality health center, Nakhon Si Thammarat Province, Thailand. Exclusion criteria were non-resident status, pregnancy, breast feeding, and those with records of ill-health status such as heart disease, stroke, and cancer.
Participants provided written informed consent and they received study objectives, study protocols, potential risks, and benefits. Sociodemographic information, educational attainment, and occupation were collected using structured interview questionnaires as were health status, family history of diabetes, use of dietary supplements, alcohol consumption, and smoking status [49].

4.2. Collection, Storage, and Compositional Analysis of Blood and Urine Samples

Whole blood and urine samples were collected in the morning after an overnight fast at the Pak Poon health center. Urine samples were collected in metal-free polypropylene collection cups. For the glucose assay, blood samples were collected in heparinized tubes, using fluoride as an inhibitor of glycolysis. For analysis of blood metals, ethylene diamine tetra acetic acid was an anticoagulant. All test tubes, bottles, and pipettes used in metal analysis were acid-washed and rinsed thoroughly with deionized water.
Blood and urine samples were kept on ice during transportation to the laboratory, where sample aliquots were prepared. The pH of urine aliquots was adjusted to >6 using 1 M NaOH to prevent the degradation of β2M in acidic conditions. Aliquots of urine, whole blood, serum, and plasma were stored at −80 °C for later analysis.
Graphite furnace atomic absorption spectrometry (GBC Scientific Equipment, Hampshire, IL, USA) was employed to determine Cd concentrations in urine and whole blood samples. To prepare samples for AAS, blood samples were deproteinized with 5% HNO3 as previously described [50]. For the instrumental calibration, the certified reference material of nine elements (Centipur®, Merck KGaA, Darmstadt, Germany) was used. Duplicate samples were analyzed for consistency checks. Blank samples were included for contamination monitoring. Reference urine and whole blood metal control levels 1, 2, and 3 (Lyphocheck, Bio-Rad, Hercules, CA, USA) were used for accuracy and precision assurance and quality control purposes.
The limit of detection (LOD) for urinary Cd was 0.1 µg/L. For any urine sample containing Cd below the LOD, the concentration assigned was the LOD divided by the square root of 2 [51].
The urinary NAG assay was based on colorimetry, using 4-nitrophenyl N-acetyl-β-D-glucosaminide as a substrate (Merck KGaA, Darmstadt, Germany). Urinary and serum concentrations of β2M were determined using the human beta-2 microglobulin/β2M ELISA pair set (Sino Biological Inc., Wayne, PA, USA). The lower limit of β2M detection was 3.13 pg/mL. The oxidase–peroxidase method (Glu Colorimetric Assay Kit, Elabscience, Catalog No: E-BC-K234-M, Houston, TX, USA) was used to determine plasma glucose concentrations [52]. Jaffe’s alkaline picrate method was used to determine urinary and plasma creatinine concentrations [53]. All assays provided coefficients of variation (CV) within acceptable clinical chemistry standards.

4.3. Correction for Differences in Urine Dilution

Because urine samples were collected at a single time point (voided urine), a correction for differences among people in urine volume (dilution) was undertaken. Accordingly, Ealb, ENAG, Eβ2M, and ECd were normalized to creatinine clearance (Ccr), using the equation: Ex/Ccr = [x]u[cr]p/[cr]u, where x = alb, NAG, β2M, or Cd; [x]u = urine concentration of x (mass/volume); [cr]p = plasma creatinine concentration (mg/dL); and [cr]u = urine creatinine concentration (mg/dL). Ex/Ccr was expressed as an amount of x excreted per volume of the glomerular filtrate [54]. This Ccr-normalization is unaffected by variation in muscle mass, while correcting for both dilution and functioning nephrons.
Ealb, ENAG, Eβ2M, and ECd were normalized to creatinine excretion (Ecr), using the equation: Ex/Ecr = [x]u/[cr]u, where x = alb, NAG, β2M, or Cd; [x]u = urine concentration of x (mass/volume); and [cr]u = urine creatinine concentration (mg/dL). Ex/Ecr was expressed as an amount of x excreted per g of creatinine. Results of logistic regression and covariance analysis conducted with Ecr-based data are provided in SM (Tables S1–S4).
Ecr-normalization corrects for difference in urine dilution only and it is affected by a large variation in muscle mass, especially between men and women. Ecr-adjustment can create non-differential errors/imprecisions that can obscure or even nullify the dose–response relationships [55]. Previously, the risk of abnormal Eβ2M values was not significantly related to ECd when ECd and Eβ2M were adjusted to Ecr [56].

4.4. Computation for eGFR and Fractional Tubular Degradation of β2M

Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were used to compute eGFR [57]. CKD stages 1, 2, 3, 4, and 5 corresponded to eGFR of 90–119, 60–89, 30–59, 15–29, and <15 mL/min/1.73 m2, respectively.
The fractional tubular degradation of filtered β2M (FrTDβ2M) (Equation (1)) was computed using rate of glomerular filtration of β2M (Fβ2M), mg/d (Equation (2)) and amount of β2M undergoing tubular degradation per volume of glomerular filtrate (TDβ2M/Ccr), mg/L filtrate) (Equation (3)) [58].
FrTDβ2M = (TDβ2M/Ccr)/[β2M]s
Fβ2M = eGFR[β2M]s
TDβ2M/Ccr = [β2M]s − Eβ2M/Ccr

4.5. Analysis for the Indirect Effects of Cd

The Baron and Kenny method was used to examine the indirect and/or direct effects Cd on Ealb and eGFR [59,60,61]. The mediation model with one mediator is depicted in Scheme 1.
The statistical parameters a, b, and c’ are β coefficients describing the effect of IV on M, the effect of M on DV, and the direct effect of IV on DV, respectively. The product a*b indicates the indirect effect of IV on DV, mediated by M. The Sobel test is employed to define a statistical significance level of the indirect effect (a*b).

4.6. Statistical Analysis

Data were analyzed with IBM SPSS Statistics 21 (IBM Inc., New York, NY, USA). The Kruskal–Wallis test was employed to assess the variation in any continuous variable across three study groups: CTRL, <10 yr DM, and ≥10 yr DM. The Pearson Chi-squared test assessed differences in percentages across the three study groups. The one-sample Kolmogorov–Smirnov test assessed deviation from a normal distribution of any continuous variable. Logarithmic transformation was applied to ECd/Ccr, Ealb/Ccr, Eβ2M/Ccr, and ENAG/Ccr that showed rightward skewing before they were subjected to parametric statistics analyses, scatterplots, and linear regressions.
The POR values for albuminuria and a reduced eGFR were obtained using logistic regression modeling, which adjusted for potential confounders (Table 2). The univariate of analysis of covariance was undertaken to identify the contributors to the variation in Ealb and eGFR (Table 3, Table 4, Table 5 and Table 6). Spearman’s rank correlation analysis was used to assess bivariate relationships of nine variables: Ealb/Ccr, age, BMI, eGFR, FPG, ECd/Ccr, ENAG/Ccr, Eβ2M/Ccr, and FrTDβ2M (Table 7).

5. Conclusions

Exposure to low-level Cd, insufficient to induce abnormally high fasting plasma glucose concentrations, is not associated with a significant increase in risk of albuminuria or a reduced eGFR. However, in the presence of diabetes and/or hyperglycemia, exposure to low-level Cd could contribute to enhanced excretions of albumin and β2-microglobulin, while aggravating eGFR reduction through damage to tubular cells, which compromises protein degradation pathways in the proximal tubular cells of kidneys.
Control of hypertension and maintaining an optimal body weight are necessary preventive measures against DKD development and its progression, as is glycemic control.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/stresses6010004/s1; Table S1: Determinants of the prevalence odds ratios for albuminuria with Ecr-based data; Table S2: Determinants of the prevalence odds ratios for reduced eGFR with Ecr-based data; Table S3: Covariance analysis for albumin excretion rates with Ecr-based data; Table S4: Covariance analysis for eGFR with Ecr-based data.

Author Contributions

Conceptualization, S.S., D.A.V. and S.Y.; methodology, S.Y., T.K. and D.W.; formal analysis, S.Y. and S.S.; investigation, S.Y., D.W. and T.K.; resources, S.Y. and D.A.V.; original draft preparation, S.S., D.A.V. and S.Y.; review and editing, S.S. and D.A.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research project was funded by the Research Grant, WU-IRG-63-026, of Walailak University, Nakhon Si Thammarat Province, Thailand.

Institutional Review Board Statement

This study was undertaken in compliance with the guidelines of the Declaration of Helsinki and approved by the Office of the Human Research Ethics Committee of Walailak University, Nakhon Si Thammarat Province, Thailand. Approval number WUEC-24-275-01 (7 August 2024).

Informed Consent Statement

Written informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials. Further inquiries can be directed to a corresponding author.

Acknowledgments

We thank the staff of a health promoting center in Pakpoon Municipality, Nakhon Si Thammarat Province, Thailand for their assistance with collection of biological and biochemical samples and data.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GFRglomerular filtration rate
eGFRestimated GFR
Cdcadmium
ECdurinary excretion rate of Cd
albalbumin
Ealburinary excretion rate of alb
NAGN-acetylglucosaminidase
ENAGurinary excretion rate of NAG
crcreatinine
Ccrcreatinine clearance
β2Mβ2-microglobulin
Fβ2Mrate of glomerular filtration of β2M
Eβ2Murinary excretion rate of β2M
TDβ2Mrate of tubular degradation of β2M
FrTDβ2Mfractional tubular degradation of filtered β2M

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Figure 1. Urinary Cd excretion rates and levels of eGFR, FPG, and serum β2M in controls and diabetics. Boxplots of data on ECd/Ccr (A), eGFR (B), [Glc]p (C), and serum levels of β2M (D) in controls and subjects with diabetes for <10 and ≥10 years, respectively. Each box represents the 25th and 75th percentile values of the variable indicated on the x-axis. A horizontal line inside each box represents the median. Circles and asterisks represent outliers.
Figure 1. Urinary Cd excretion rates and levels of eGFR, FPG, and serum β2M in controls and diabetics. Boxplots of data on ECd/Ccr (A), eGFR (B), [Glc]p (C), and serum levels of β2M (D) in controls and subjects with diabetes for <10 and ≥10 years, respectively. Each box represents the 25th and 75th percentile values of the variable indicated on the x-axis. A horizontal line inside each box represents the median. Circles and asterisks represent outliers.
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Figure 2. Excretion rates of NAG, albumin, and β2M and the fractional tubular degradation of β2M in controls and diabetics. Boxplots of data on ENAG/Ccr (A), Ealb/Ccr (B), Eβ2M/Ccr (C), and FrTDβ2M (D) in controls and subjects with DM for <10 and ≥10 years, respectively. Each box represents the 25th and 75th percentile values of the variable indicated on the x-axis. A horizontal line inside each box represents the median. Circles and asterisks represent outliers.
Figure 2. Excretion rates of NAG, albumin, and β2M and the fractional tubular degradation of β2M in controls and diabetics. Boxplots of data on ENAG/Ccr (A), Ealb/Ccr (B), Eβ2M/Ccr (C), and FrTDβ2M (D) in controls and subjects with DM for <10 and ≥10 years, respectively. Each box represents the 25th and 75th percentile values of the variable indicated on the x-axis. A horizontal line inside each box represents the median. Circles and asterisks represent outliers.
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Figure 3. Excretion of albumin and β2M in relation to the excretion of NAG. Scatterplots related Ealb/Ccr to ENAG/Ccr and Eβ2M/Ccr to ENAG/Ccr in controls and diabetics (A,C) and those with FPG <110 and ≥110 mg/dL (B,D).
Figure 3. Excretion of albumin and β2M in relation to the excretion of NAG. Scatterplots related Ealb/Ccr to ENAG/Ccr and Eβ2M/Ccr to ENAG/Ccr in controls and diabetics (A,C) and those with FPG <110 and ≥110 mg/dL (B,D).
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Figure 4. Reduction in eGFR in relation to the excretion of albumin and NAG. Scatterplots related eGFR to Ealb/Ccr in men and women, and (A) subjects with and without hypertension (B). Scatterplots related eGFR to ENAG/Ccr in men and women and (C) subjects with and without hypertension (D).
Figure 4. Reduction in eGFR in relation to the excretion of albumin and NAG. Scatterplots related eGFR to Ealb/Ccr in men and women, and (A) subjects with and without hypertension (B). Scatterplots related eGFR to ENAG/Ccr in men and women and (C) subjects with and without hypertension (D).
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Figure 5. Mediating effects of Cd by tubular injury and impaired functions. The Sobel test for the effects of ECd on Ealb (a) and eGFR (b) mediating through ENAG. ECd, excretion of cadmium; Ealb, excretion of albumin; ENAG, excretion of NAG; Eβ2M, excretion of β2M; CI; bootstrapped confidence interval.
Figure 5. Mediating effects of Cd by tubular injury and impaired functions. The Sobel test for the effects of ECd on Ealb (a) and eGFR (b) mediating through ENAG. ECd, excretion of cadmium; Ealb, excretion of albumin; ENAG, excretion of NAG; Eβ2M, excretion of β2M; CI; bootstrapped confidence interval.
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Scheme 1. A simple mediation model with one mediator. IV, independent variable; DV, dependent variable; M, mediator.
Scheme 1. A simple mediation model with one mediator. IV, independent variable; DV, dependent variable; M, mediator.
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Table 1. Descriptive characteristics of controls and diagnosed diabetics.
Table 1. Descriptive characteristics of controls and diagnosed diabetics.
VariablesAll Subjects
n = 137		CTRL
n = 72		Diagnosed DMp
<10 yrs, n = 37 ≥10 yrs, n = 25
Women, %78.479.275.780.00.894
Smoking, %10.411.110.88.00.905
Mean age (range), years59.5 (41–80)61.2 (43–80)58.3 (42–75)56.6 (41–78)0.073
Mean BMI (range), kg/m225.6 (15–48)24.6 (15–48)26.7 (15–36)26.6 (20–35)0.016
FPG, mg/dL130 (61)94 (11)172 (76)170 (58)<0.001
FPG ≥ 110 mg/dL, %49.311.191.996.0<0.001
FPG ≥ 126 mg/dL, %39.61.481.188.0<0.001
Reduced eGFR a, %11.99.78.124.00.116
Mean SBP (range) 138 (103–187)134 (107–173)140 (106–184)144 (103–176)0.030
Mean DBP (range)84 (61–106)84 (62–103)85 (65–106)86 (61–101)0.399
Hypertension, %54.244.954.180.00.011
[β2M]u, µg/L67 (58)42 (37)84 (58)114 (73)<0.001
ECd/Ecr, µg/g cr1.00 (1.87)0.99 (1.94)0.72 (1.54)1.41 (2.11)0.267
Ealb/Ecr (ACR), mg/g cr39.8 (103)12.4 (26.1)59.8 (115)89.2 (177)0.002
Microalbuminuria b, %22.48.335.144.0<0.001
Macroalbuminuria, %3.708.18.00.046
(Ealb/Ccr) × 100, mg/L filtrate37.2 (107)9.76 (19.2)51.4 (96.8)95.2 (205)0.003
Microalbuminuria c, %2612.9 33.352.0<0.001
Macroalbuminuria, %4.5010.880.023
CTRL, control; DM, diabetes; BMI, body mass index; FPG, fasting plasma glucose; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; DBP, diastolic blood pressure; β2M, β2-microglobulin; Cd, cadmium; cr, creatinine; Ecr, excretion of cr; alb, albumin; Ccr, creatinine clearance. Continuous variables are presented as arithmetic mean and standard deviation (SD) values. a Reduced eGFR was defined as eGFR ≤ 60 mL/min/1.73 m2. b Micro(macro)albuminuria was based on Ealb/Ecr ≥ 20 (300) and ≥30 (300) mg/g cr in men and women, respectively. c Micro(macro)albuminuria was based on Ealb/Ccr ≥ 0.2 (2) mg/L filtrate.
Table 2. Determinants of the prevalence odds ratios for albuminuria and reduced eGFR.
Table 2. Determinants of the prevalence odds ratios for albuminuria and reduced eGFR.
Independent VariablesAlbuminuria aReduced eGFR b
POR (95% CI)pPOR (95% CI)p
Age, years0.988 (0.936, 1.043)0.6671.153 (1.055, 1.260)0.002
BMI0.988 (0.899, 1.086)0.7991.049 (0.920, 1.197)0.473
Log[(ECd/Ccr)], µg/L filtrate0.870 (0.471, 1.608)0.6581.542 (0.679, 3.502)0.301
Smoking0.384 (0.062, 2.384)0.3041.866 (0.119, 29.24)0.657
Gender2.749 (0.769, 9.831)0.1203.195 (0.218, 46.85)0.397
Reduced eGFR4.294 (1.185, 15.56)0.027––
Diabetes 4.081 (1.601, 10.40)0.0031.883 (0.509, 6.969)0.343
Hypertension 2.786 (1.091, 7.114)0.032––
Eβ2M/Ccr ≥ 3 µg/L filtrate––6.372 (1.137, 35.71)0.035
a Albuminuria was based on Ealb/Ccr ≥ 0.2 mg/L filtrate in women and men. b Reduced eGFR was defined as eGFR ≤ 60 mL/min/1.73 m2. POR, prevalence odds ratios; CI, confidence interval; BMI, body mass index; Cd, cadmium; ECd, excretion of Cd; cr, creatinine; Ccr, creatinine clearance; β2-microglobulin, β2M.
Table 3. Covariance analysis for albumin excretion rates stratified by DM and gender.
Table 3. Covariance analysis for albumin excretion rates stratified by DM and gender.
Independent VariablesLog10 [(Ealb/Ccr)], µg/L Filtrate
CTRL, n = 44DM, n = 56Women, n = 77Men, n = 23
η2pη2pη2pη2p
Age0.0730.1170.0160.3950.0070.4930.0100.709
BMI0.0500.1960.0970.0330.0020.7240.0110.699
ECd/Ccr0.0760.1100.0050.6520.0000280.9650.0380.470
FrTDβ2M0.2280.0040.0180.3650.0080.4660.0500.405
Log10[(ENAG/Ccr)]0.0610.1530.1620.0050.0540.0500.2680.040
Gender0.1150.0460.1760.003––––
Smoking0.1940.0080.1070.025––0.0000440.981
HTN0.2100.0060.1460.0080.1210.0030.1090.212
Gender × HTN0.0440.2260.1220.016––
Smoking × HTN0.0210.4080.1780.003––0.0350.489
Unadjusted
(Adjusted) R2		0.422
(0.246)		0.0280.535 (0.431)<0.0010.237 (0.172)0.0030.434 (0.111)0.301
η2 = eta squared; HTN, hypertension; ×, represents an interaction term; R2, coefficient of determination. η2 indicates the fraction of Ealb/Ccr variation explained by each independent variable in CTRL, DM, women and men. Adjusted R2 indicates the fraction of total variation of Ealb/Ccr explained by all independent variables in CTRL, DM, women and men. For all tests, p-values ≤ 0.05 indicate statistically significant levels.
Table 4. Covariance analysis for albumin excretion rates stratified by DM duration and eGFR values.
Table 4. Covariance analysis for albumin excretion rates stratified by DM duration and eGFR values.
Independent VariablesLog10 [(Ealb/Ccr)], µg/L Filtrate
<10 yr DM, n = 34≥10 yr DM, n = 20Normal eGFR, n = 88Reduced eGFR, n =12
η2pη2pη2pη2p
Age0.1160.0960.1270.2320.0210.1980.0600.640
BMI0.0330.3830.4270.0150.0020.6990.0090.861
ECd/Ccr0.0030.7880.0040.8320.0210.1980.0920.558
FrTDβ2M0.0340.3790.0010.9370.0290.1340.0030.919
Log10[(ENAG/Ccr)]0.1580.0490.1980.1270.0820.0100.1150.510
Gender0.3700.0010.3060.0500.0010.783––
Smoking0.2540.0100.4820.0090.0010.839––
HTN0.1170.0940.5760.0030.0790.0120.1780.404
Gender × HTN0.0210.493––0.0010.822––
Smoking × HTN0.0760.182––0.0140.298––
Unadjusted
(Adjusted) R2		0.585
(0.495)		0.0090.810
(0.671)		0.0040.247
(0.149)		0.0110.668
(0.088)		0.473
η2 = eta squared; HTN, hypertension; ×, represents an interaction term; R2, coefficient of determination. η2 indicates the fraction of Ealb/Ccr variation explained by each independent variable in subjects grouped by DM duration and eGFR values. Adjusted R2 indicates the fraction of total variation of Ealb/Ccr explained by all independent variables in subjects grouped by DM duration and eGFR values. For all tests, p-values ≤ 0.05 indicate statistically significant levels.
Table 5. Covariance analysis for eGFR stratified by DM and gender.
Table 5. Covariance analysis for eGFR stratified by DM and gender.
Independent VariableseGFR, mL/min/1.73 m2
CTRL, n = 44DM, n = 56Women, n = 77Men, n = 23
η2pη2pη2pη2p
Age0.0260.3640.1830.0030.0990.0080.0190.626
BMI0.0050.6940.0050.6530.0180.2650.0470.439
ECd/Ccr0.0630.1510.0090.5200.0080.4450.0660.357
Log10[(ENAG/Ccr)]0.3010.0010.1990.0020.222<0.0010.3070.032
Log10[(Eβ2M/Ccr)]0.0180.4540.1400.0100.0720.0230.0310.532
FPG0.0130.5260.0540.1190.1090.0050.1470.158
Gender0.0530.1920.0090.520––––
Smoking0.0580.1690.0190.366––0.0320.527
HTN0.0050.6800.0200.3480.0140.3240.0040.829
Gender × HTN0.0050.6980.0030.741––––
Smoking × HTN0.0160.4760.0490.140––0.1100.227
Unadjusted (adjusted) R20.510 (0.341)0.0070.683 (0.603)<0.0010.564 (0.520)<0.0010.562 (0.258)0.151
eGFR, estimated glomerular filtration rate; η2 = eta squared; HTN, hypertension; ×, represents an interaction term; R2, coefficient of determination. η2 indicates the fraction of the eGFR variation explained by a corresponding independent variable in CTRL, DM, women, and men. Adjusted R2 indicates the fraction of total variation in eGFR explained by all independent variables in CTRL, DM, women, and men. For all tests, p-values ≤ 0.05 indicate statistically significant levels.
Table 6. Covariance analysis for eGFR stratified by DM duration eGFR values.
Table 6. Covariance analysis for eGFR stratified by DM duration eGFR values.
Independent VariableseGFR, mL/min/1.73 m2
<10 yr DM, n = 34≥10 yr DM, n = 20Normal eGFR, n = 88Reduced eGFR, n =12
η2pη2pη2pη2p
Age0.1340.0790.1260.2570.0220.1980.3050.335
BMI0.0040.7560.0400.5330.0210.2020.3990.253
ECd/Ccr0.0240.4720.1890.1570.0030.6110.2440.398
Log10[(ENAG/Ccr)]0.0570.2620.5430.0060.1280.0010.1160.574
Log10[(Eβ2M/Ccr)]0.1560.0570.2540.0950.0650.0250.0710.664
FPG0.0530.2790.0960.3270.151<0.0010.3560.288
Gender0.0220.4900.0470.4970.0020.686––
Smoking0.0040.7620.0230.6370.0080.433––
HTN0.0020.8240.0160.6990.0090.4160.4280.231
Gender × HTN0.0050.753––0.0300.129––
Smoking × HTN0.0250.460––0.0150.284––
Unadjusted (adjusted) R20.585
(0.377)		0.0190.874
(0.761)		0.0020.417
(0.332)		<0.0010.749
(0.080)		0.515
eGFR, estimated glomerular filtration rate; η2 = eta squared; HTN, hypertension; ×, represents an interaction term; R2, coefficient of determination. η2 indicates the fraction of the eGFR variation explained by a corresponding independent variable in subjects grouped by DM duration and eGFR values. Adjusted R2 indicates the fraction of total variation in eGFR explained by all independent variables in subjects grouped by DM duration and eGFR values. For all tests, p-values ≤ 0.05 indicate statistically significant levels.
Table 7. Bivariate relationship analysis of DKD indicators.
Table 7. Bivariate relationship analysis of DKD indicators.
Variables Spearman’s Rank Correlation Coefficient
EAlb/CcrAgeBMIeGFRFPGECd/CcrENAG/CcrEβ2M/Ccr
Age0.085
BMI0.076−0.262 **
eGFR−0.136−0.356 **0.161
FPG0.273 **−0.222 **0.184 *0.089
ECd/Ccr0.1060.078−0.083−0.227 **0.166
ENAG/Ccr0.327 **−0.1150.002−0.467 **0.278 **0.328 **
Eβ2M/Ccr0.265 **0.170 *−0.066−0.515 **0.306 **0.496 **0.534 **
FrTDβ2M −0.237 **−0.0960.0480.434 **−0.215 *−0.527 **−0.536 **−0.891 **
BMI, body mass index; eGFR, estimated glomerular filtration rate FPG, fasting plasma glucose concentration; FrTDβ2M, fractional tubular degradation of β2-microglobulin. * Significant correlation at the 0.05 level. ** Significant correlation at the 0.01 level.
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Satarug, S.; Khamphaya, T.; Waeyeng, D.; Vesey, D.A.; Yimthiang, S. Diabetic Kidney Disease Associated with Chronic Exposure to Low Doses of Environmental Cadmium. Stresses 2026, 6, 4. https://doi.org/10.3390/stresses6010004

AMA Style

Satarug S, Khamphaya T, Waeyeng D, Vesey DA, Yimthiang S. Diabetic Kidney Disease Associated with Chronic Exposure to Low Doses of Environmental Cadmium. Stresses. 2026; 6(1):4. https://doi.org/10.3390/stresses6010004

Chicago/Turabian Style

Satarug, Soisungwan, Tanaporn Khamphaya, Donrawee Waeyeng, David A. Vesey, and Supabhorn Yimthiang. 2026. "Diabetic Kidney Disease Associated with Chronic Exposure to Low Doses of Environmental Cadmium" Stresses 6, no. 1: 4. https://doi.org/10.3390/stresses6010004

APA Style

Satarug, S., Khamphaya, T., Waeyeng, D., Vesey, D. A., & Yimthiang, S. (2026). Diabetic Kidney Disease Associated with Chronic Exposure to Low Doses of Environmental Cadmium. Stresses, 6(1), 4. https://doi.org/10.3390/stresses6010004

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