Relationship between Serum Cadmium Concentration and Lung Function: A Study Using Korea National Health and Nutrition Examination Survey Data
Article information
Abstract
Background
Occupational and environmental exposures to cadmium affects lung. Cadmium accumulation alters intracellular signaling and impairs innate immunity which leads to chronic inflammation. Various factor such as gender, age, smoking status, and comorbidities are known to be associated with blood cadmium levels. The objective of this study was to investigate the association between lung function and serum cadmium concentration, adjusting for these factors.
Methods
The study population included 7,448 adults who are over 40 years old and participated in the Korea National Health and Nutrition Examination Survey (KNHANES) from 2008 to 2017, excluding 2014-2015, when there were no measured values for heavy metals. To investigate the relationship between blood cadmium concentration and estimated glomerular filtration rate (eGFR) and forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC), weights were applied to the subjects and adjusted linear regression analysis was performed.
Results
According to gender, as the blood cadmium concentration increased FEV1/FVC decreased in male smokers with age, body mass index (BMI), education level, hypertension and diabetes adjusted (estimate, –0.01; 95% confidence interval [CI], –0.02 to 0.003). In female current smoker group, as the blood cadmium concentration increased, FEV1/FVC decreased with age, BMI, education level, hypertension, and diabetes adjusted (estimate, –0.02; 95% CI, –0.04 to –0.01).
Conclusion
Lung function represented by FEV1/FVC decreased as the blood cadmium concentration increased in the male and female smoker group. The relationship between blood cadmium concentration and kidney function remains controversial and requires future studies. As a result, our study provided insight into the effects of cadmium concentration on lung function.
Introduction
Pure cadmium is a soft, silver-white metal which is found in the earth’s crust. This metal is accumulated in tobacco leaves. Cadmium oxide, which is generated during smoking deposits locally in the lung tissue or enters the systemic blood circulation. As a result, serum cadmium concentrations are higher in smokers compared to nonsmokers [1,2]. Previous study has shown that an increase in serum cadmium concentration is associated with a decline in forced expiratory volume in 1 second (FEV1) and concluded that cadmium partially mediates the association between smoking and obstructive lung disease [3]. Hassan et al. [4] found that cadmium accumulation in lung tissue was higher in Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage IV compared to GOLD stage I chronic obstructive pulmonary disease (COPD). Since the biological half-life of cadmium is over 25 years in the human body, it is reasonable to suggest that cadmium accumulation influences intracellular signaling resulting in impaired innate immunity. This leads to an increase in susceptibility to infection and progresses to chronic inflammation, fibrosis and emphysema [1,2].
Cadmium is absorbed through lung and gastrointestinal tract. After absorption, it binds to serum albumin and accumulates in the liver. This complex then approaches to the kidney and accumulates in the proximal tubule which causes proximal tubular damage. Previous study has shown that low level exposure to cadmium increases the risk of chronic kidney disease (CKD) and albuminuria [5,6]. Continuous exposure to cadmium can ultimately progress to renal failure and patients with comorbidities such as diabetes and hypertension are at higher risk to the progression [1,7]. Progression to CKD alters fluid homeostasis and vascular tone which affects the physiology of the lung. Uremia, oxidative stress, infections and volume overload are common in CKD patients which increases inflammation. Increased inflammation affects the airway which makes COPD as a common comorbidity in CKD patients [8,9]. Therefore, we also analyzed the association between the kidney function and blood cadmium level.
The systematic review and meta-analysis of environmental studies revealed that exposure to cadmium is positively correlated with an increased risk of cardiovascular disease and coronary heart disease. This is thought to be the result of cadmium’s effect on the vascular system by oxidative stress, inflammation and endothelial cell damage [10]. Moreover, the U.S. Department of Health and Human Services and the International Agency for Research on Cancer designated cadmium as a human carcinogen [1]. Therefore, previous studies showed that cadmium is related with impaired lung function and kidney function, increased risk of cardiovascular disease and cancer.
Smoking and foods such as leafy vegetables are primary sources of cadmium exposure. Workers who are involved in heating cadmium containing materials are at the highest risk of cadmium exposure [1]. Regarding these various sources and adverse effects of cadmium, we evaluated the amount of cadmium absorbed in human body in terms of serum cadmium concentration and its effects on kidney and lung function. The aim of this study was to investigate the effect of cadmium concentration on kidney and lung function by using estimated glomerular filtration rate (eGFR), FEV1, forced vital capacity (FVC) and FEV1/FVC with the data from the Korea National Health and Nutrition Examination Survey (KNHANES).
Materials and Methods
1. Study population and data description
This study used data from the KNHANES conducted by the Korea Disease Control and Prevention Agency. The KNHANES are stratified by region, age, gender and samples are extracted using a complex sampling design method by distributing the data proportionally to the size of each stratification [11]. All subjects participating in the survey from 2008 to 2017 were selected and among them, 2014 and 2015 were excluded from the analysis because heavy metal concentrations were not measured. A total of 7,448 people (3,581 males, 3,867 females) were included in the study. This study was approved by the Institutional Review Board of Kangwon National University Hospital (Registration Number: KNUH-A-2021-07-002) and the requirement for informed consent was waived due to the retrospective nature of this study.
2. Definition of development of CKD, COPD, and variables
If eGFR value was less than 60 mL/min/1.73 m2, it was defined as CKD [12]. FVC, FEV1, and FEV1/FVC were used to represent lung function and FEV1/FVC <0.7 was defined as COPD [13]. Hypertension was defined when patients had systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg [14] or diagnosed as hypertension by doctor or patients who have taken hypertension drugs. Diabetes was defined when patient’s fasting glucose ≥126 mg/dL [15] or diagnosed as diabetes by doctor or patients who have taken diabetes medication.
3. Statistical analysis
In the National Health and Nutrition Survey, an integrated weight was used for statistical analysis in consideration of the sampling rate and response rate in order to represent the whole country with the samples extracted by the complex sampling design method. Age, gender, education level, smoking status, hypertension, diabetes, COPD, and obesity were obtained from the data of the study subjects. In the case of continuous variables, the mean and standard error were expressed, and in the case of categorical variables, frequency was expressed. Obesity was categorized by body mass index (BMI). BMI under 18.5 kg/m2 was defined as underweight, 18.5 kg/m2 or more and less than 25 kg/m2 was defined normal and over 25 kg/m2 was defined as obese [16]. For each variable, a frequency table was presented to confirm the characteristics of the cadmium concentration, and the mean difference test and correlation analysis were performed. Since the cadmium concentration was not normally distributed, the cadmium concentration was log-transformed in order to make the distribution into normal distribution [17].
eGFR was used as an indicator for kidney function, and FEV1 (%), FVC (%), and FEV1/FVC were used as indicators for lung function. Since these variables were normally distributed, univariate and multivariate linear regression models were used to investigate the relationship between the kidney and lung function and cadmium concentration. For multivariable analysis, gender, age, education level, smoking status, hypertension status, diabetes status, COPD status and obesity were adjusted variance inflation factor between variables was 1.83, so we considered the degree of multicolinearity to be acceptable. When the lung function indicators—FEV1 (%), FVC (%), and FEV1/FVC were analyzed, COPD status variable was excluded from the analysis and in the case of FEV1 and FVC, height values were adjusted instead of BMI. Since FEV1 (%) and FVC (%) are affected by age, sex, and height, adjustments for these variables were made in a method similar to that of the previous study [18]. p-values less than 0.05 were considered as statistically significant. SAS program version 9.4 (SAS Institute Inc., Cary, NC, USA) was used for statistical analysis.
Results
1. Characteristics of subjects and mean differences in cadmium concentrations
Seven thousand four hundred forty-eight subjects participated in this study, the general characteristics of subjects according to blood cadmium concentration are presented in Table 1. Blood cadmium concentrations were different according to gender, education level, hypertension, CKD, smoking status and obesity. The geometric mean value of cadmium concentration was higher in female than male (p<0.001) and the higher the education level, the lower the geometric mean value of cadmium concentration was (p<0.001). The geometric mean value of cadmium concentration was higher in subjects with hypertension than normal subjects (p<0.001). Subjects who never smoked had lower cadmium concentrations than current smokers (p<0.001). Subjects who were underweight had the highest cadmium concentration and obese subjects had the lowest cadmium concentration (p<0.001).
Characteristics of study subjects about categorical variables
Correlation between the continuous variables and the log transformed blood cadmium concentration are shown in Table 2. Age, FVC, and FEV1/FVC had statistically significant correlation with blood cadmium concentration (p<0.001, p=0.006, and p=0.009 respectively). Age had a positive correlation with blood cadmium concentration and FEV1/FVC had negative correlation with blood cadmium concentration.
Correlations of log transformed blood cadmium and continuous variable
2. Regression analysis results for eGFR, FEV1, FVC, and FEV1/FVC values
The results of univariate and multivariate linear regressions are presented in Table 3. eGFR, FEV1, FVC, and FEV1/FVC were considered as dependent variables and log transformed blood cadmium concentration was defined as an independent variable. FEV1/FVC was statistically significant in univariate and multivariate models (p<0.001 and p=0.002). The higher the blood cadmium concentration, the lower the FEV1/FVC was, which indicates that subjects with higher blood cadmium concentration had decreased lung function. In the univariate model for FEV1 and FVC, FVC decreased statistically significantly as the cadmium concentration increased (p=0.006).
Multiple regression estimated coefficient of log transformed blood cadmium
3. Regression analysis results for eGFR, FEV1, FVC, and FEV1/FVC values by gender
The results of regression analysis of eGFR, FEV1, FVC, and FEV1/FVC values by gender are presented in Table 4. For male, FEV1/FVC was negatively correlated with blood cadmium level in univariate and multivariate models (p<0.001 and p=0.002). FEV1 also had negative correlation with blood cadmium concentration for both models (p<0.001 and p=0.032).
Multiple regression estimated coefficient of log transformed blood cadmium by gender group
For female subjects, eGFR value decreased statistically significantly as the cadmium concentration increases in the univariate model (p=0.015). FEV1/FVC decreased as the cadmium concentration increase with statistical significance in the univariate model (p=0.002). This difference in results according to gender is considered to be a result of the greater exposure of cadmium due to smoking in male than female. Therefore, in this study, multiple regression analysis was additionally performed by dividing the groups according to the smoking status and both the smoking status and gender.
4. Regression analysis results for eGFR, FEV1, FVC, and FEV1/FVC values by smoking status
The results of multiple regression analysis of eGFR, FEV1, FVC, and FEV1/FVC values by smoking status are presented in Table 5. For current smokers, FEV1/FVC value decreased as the cadmium concentration increased in both models (p<0.001 and p=0.002). For former and never smokers, none of the variables were statistically significant in multivariate analysis.
Multiple regression estimated coefficient of log transformed blood cadmium by smoking status
5. Regression analysis results for eGFR, FEV1, FVC, and FEV1/FVC values by gender and smoking
The subjects were categorized with smoking status and subgroup analyses were performed according to gender. Linear regression by smoking status in male was shown in Table 6 and linear regression by smoking status in female was shown in Table 7. For males who currently smoke, eGFR value increased statistically significant as the cadmium concentration increased in both models (p=0.016 and p=0.014) and FEV1/FVC showed a statistically significant decrease as the cadmium concentration increased in both models (p<0.001 and p=0.001). Additionally, FEV1/FVC values were also negatively correlated in never smoker group with statistical significance in the multivariate analysis (p=0.032).
Multiple regression estimated coefficient of log transformed blood cadmium by smoking status and male
Multiple regression estimated coefficient of log transformed blood cadmium by smoking status and female
For females who currently smoke, eGFR value decreased as the cadmium concentration increased in univariate and multivariate models (p=0.014 and p=0.017) and FEV1/FVC also showed a statistically significant decrease as the cadmium concentration increased in both models (p=0.0002 and p=0.002).
Discussion
Major sources of cadmium exposure are smoking, food intake and occupational exposure. Cadmium accumulates in our body and causes various diseases such as kidney disease, lung disease, and cancer [1]. In this study, KNHANES data from 2008 to 2017 for subjects over 40 years of age were investigated to analyze the effect of cadmium concentration on kidney function and lung function. Blood cadmium concentration was higher in female (geometric mean, 1.27) than male (geometric mean, 0.98). Since depletion of serum iron increases the absorption of cadmium and females have a tendency to have lower serum ferritin level than males, blood cadmium concentration was higher in females [16,19]. Patients with low education level, hypertension and current smokers had higher blood cadmium concentration. Age and lung functions were correlated with log transformed blood cadmium concentration in our study. FEV1/FVC was negatively correlated with log transformed blood cadmium concentration in the univariate and multivariate linear regression models. In the subgroup analysis by gender, FEV1, and FEV1/FVC were negatively correlated in the male group. In the subgroup analysis by smoking status, FEV1/FVC had negative correlation in the current smoker group. In the male current smoker group, eGFR was positively correlated and FEV1/FVC was negatively correlated. In the female current smoker group, eGFR and FEV1/FVC were negatively correlated with log transformed blood cadmium concentration.
Subjects with hypertension and CKD had different levels of blood cadmium concentration compared to normal subjects in our study. However, blood cadmium concentration difference in subjects with diabetes and COPD was statistically insignificant. Kurihara et al. [20] and Kim et al. [21] suggested that cadmium exposure was positively associated with CKD especially in subjects with hypertension or diabetes. The higher the education level was, the lower the blood cadmium concentration was. This was consistent with the previous study which showed that blood cadmium level was significantly higher in the patient group who received less formal education [22].
As a result of multivariate regression analysis, the eGFR value according to the blood cadmium concentration was not statistically significant for all subjects. Previous study on heavy metals and kidney function through data from the U.S. National Health and Nutrition Examination Survey showed that blood cadmium concentration affects kidney function. Moderately high levels of blood cadmium were associated with a higher prevalence of CKD [6]. However, in our study eGFR value increased as the blood cadmium concentration increased in male current smoker group in all models with statistical significance. In a study using 2005 KNHANES data, blood cadmium levels were inversely associated with eGFR in females while the blood cadmium levels were positively associated with eGFR in males with high blood lead levels [23]. Smoking was related with higher blood lead levels in Korean population [24]. Higher lead levels initially increase eGFR through hyperfiltration but eventually lead to a decline in eGFR, resulting in CKD [23]. This might explain the positive association between eGFR and blood cadmium level in current male smokers. Since cadmium accumulates in the renal cortex and causes renal toxicity, urine cadmium concentration reflects the degree of accumulation of cadmium more accurately than the serum cadmium concentration [17]. Serum cadmium concentration in male smoker group might not have accurately reflect the amount of cadmium accumulation in the body. This remains as a limitation of our study and further prospective studies should be conducted to investigate causal relationship. In the subgroup analysis for females and smoking status, as the blood cadmium concentration increased, the eGFR value decreased in the smoker group as shown in Table 7. This was consistent with the previous study [6].
Regarding lung function, analysis performed with the FEV1/FVC value according to the blood cadmium concentration was statistically significant. FEV1/FVC was negatively correlated with the blood cadmium concentration. Since males are more likely to be exposed to cadmium than females due to their higher smoking rate, subgroup analyses were conducted by classifying the subjects by gender and smoking status. Oh et al. [25] showed that higher blood cadmium level was associated with COPD in males but not in females. Kohansal et al. [26] suggested that smoking has similar deleterious effects on lung functions in both genders. In our study, blood cadmium concentration was negatively correlated with lung function in terms of FEV1/FVC regardless of gender.
In the male current smoker group, eGFR values and FEV1/FVC were significant. eGFR and FEV1/FVC values were not significant in former and never smoker group. Regarding female smokers, the eGFR and FEV1/FVC values were significant. Previous study did not reach statistical significance for analysis of blood cadmium concentration and COPD in females including never smokers [25]. However in our study, we had relatively larger number of subjects (7,448 subjects) compared to the previous study (3,622 subjects) and subgroup analysis was done depending on the smoking status. Therefore, cadmium exposure affected kidney and lung function for female smokers. This study used data from the KNAHNES to represent the general population over the age of 40 through weighting, and showed how the blood cadmium concentration affects kidney and lung function and confirmed how it differs between male and female according to smoking status. We analyzed both kidney and lung functions to determine whether their associations with blood cadmium concentration are similar. Blood cadmium concentration was negatively associated with lung function while the association between kidney function was statistically insignificant. Lung function should be regularly monitored in populations exposed to high levels of cadmium and methods to reduce cadmium exposure, such as smoking cessation should be recommended.
However, there are several limitations in our study. First, since the KNAHNES data used in this study was a cross-sectional study, it was not possible to understand the route of exposure to cadmium, so it was insufficient to explain the causal relationship between the exposure and kidney and lung function. Second, since the smoking status relied on questionnaires, there might be some inaccurate data and some subjects might be designated at the wrong group in the smoking status. Third, we did not analyze according to other cadmium intake sources such as food and occupational exposures. These factors might also influence the results. Further studies are needed to clarify the pathophysiology of cadmium’s effect on human body in terms of lung function. Additionally, the use of casual diagrams could help in eliminating confounding bias [27].
In conclusion, the present study analyzes an association between blood cadmium concentrations and kidney and lung function in a Korean population. A significant association exists between FEV1/FVC and blood cadmium concentration in all subjects. Meanwhile, there is no statistical relation between blood cadmium concentration and eGFR according to all subjects. Although our study could not reveal causality between cadmium concentration and health impact indicators, it provided insight into the effects of cadmium concentration on lung disorders.
Notes
Authors’ Contributions
Conceptualization: Kim WJ. Methodology: Lee EJ. Formal analysis: Lee EJ. Data Curation: Lim MN. Funding acquisition: Kim WJ. Software: Lee EJ. Validation: Kim J. Investigation: Kwon OB. Writing - original draft preparation: Kwon OB. Writing - review and editing: Kwon OB, Lim MN, Kim J, Kim WJ. Approval of final manuscript: all authors.
Conflicts of Interest
Woo Jin Kim is an associate editor of the journal, but he was not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.
Funding
This work was supported by the Korea Environment Industry and Technology Institute through the Core Technology Development Project for Environmental Disease Prevention and Management and funded by the Korea Ministry of Environment (grant number: RS-2021-KE001380 and RS-2022-KE002052).