RESUMO
Objective: To investigate the effect of combined exposure to four heavy metals (lead, cadmium, arsenic, mercury) on early kidney injury in occupational population. Methods: A total of 384 workers exposed to combined heavy metals in a non-ferrous metal smelting plant in Guangdong Province were selected as the research subjects using judgment sampling method. The levels of blood lead, urinary cadmium and urinary arsenic were detacted by inductively coupled plasma mass spectrometry, while urinary mercury levels were measured using cold atomic absorption spectroscopy (acidic tin chloride reduction method). The levels of biomarkers such as urinary β2-microglobulin (β2-MG), kidney injury molecule-1 (Kim-1) and neutrophil gelatinase-associated lipocalin (NGAL) were detected by enzyme-linked immunosorbent assay. Spearman correlation analysis, linear regression, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were used to analyze the association between the exposure to the four heavy metals and early kidney injury biomarkers. Results: The median of blood lead, urinary cadmium, urinary arsenic and urinary mercury were 0.47 μmol/L and 4.450, 27.790 and 0.520 μg/gCr, respectively. The median of urinary β2-MG, Kim-1 and NGAL were 62.960, 1.130 and 18.150 μg/gCr, respectively. Spearman correlation analysis showed that urinary levels of β2-MG, Kim-1, and NGAL were weakly correlated with blood lead and urinary mercury levels (all P<0.01), but not correlated with urinary cadmium and urinary arsenic (all P>0.05). The results of multiple linear regression analysis showed that urinary mercury was positively correlated with urinary β2-MG, Kim-1 and NGAL (all P<0.01), urinary arsenic was positively correlated with urinary β2-MG level (P<0.01), and blood lead was negatively correlated with urinary β2-MG and Kim-1 (all P<0.05). The WQS regression analysis showed that the combined effect of the four heavy metals was positively correlated with urinary β2-MG, Kim-1 and NGAL (all P<0.01), with mercury having the highest impact and lead the lowest. BKMR model analysis showed the increasing trend in urinary β2-MG, Kim-1 and NGAL with the increasing levels of the combined exposure to the four heavy metals. Urinary β2-MG, Kim-1 and NGAL decreased when urinary mercury level increased from the 25th percentile to the 75th percentile and the other metals were correspondingly fixed at a certain level. When the blood exposure levels of other metals remained at the corresponding median levels, urinary β2-MG, Kim-1 and NGAL levels were positively correlated with urinary arsenic level, but no significant linear dose-response relationship was observed with the other three heavy metals. Conclusion: sLead, arsenic, and mercury are independently associated with early kidney injury biomarkers in occupational population from non-ferrous metal smelting. The four heavy metals had positive combined effects on urinary β2-MG, Kim-1 and NGAL, with mercury having the greatest impact.
RESUMO
Background Occupational exposure to lead, cadmium, or arsenic is a potential risk factor for blood pressure elevation. Current studies mainly focus on the relationship between a single metal and blood pressure. However, mixed metal exposure often exists in the actual working environment, and the interactive effects of polymetallic interactions on blood pressure and the dose-effect relationship remain unclear yet. Objective To explore the influence proportion of occupational exposure to lead, cadmium, or arsenic on blood pressure and their interactive effects. Methods From January to December 2021, workers from a smelter in southern China were selected. Demographic characteristics, height, weight, and blood pressure of workers were collected through questionnaire and physical examination. At the same time, their urine samples were collected and the levels of urinary lead, urinary cadmium, and urinary arsenic were detected by inductively coupled plasma mass spectrometry, and corrected by urinary creatinine (Cr). Linear regression and logistic regression were used to analyze the relationship between urinary lead, cadmium, and arsenic and blood pressure. Weighted quantile sum (WQS) regression was applied to evaluate the dose-effect relationship between urinary lead, cadmium, and arsenic exposures and blood pressure and the effect weight of each metal on blood pressure. Generalized linear regression and additive/multiplicative scaling were used to identify interactive effects of the three metals on blood pressure. Results A total of 1075 workers were included in this study, with a mean age of (44.68±5.11) years and mean working seniority of (24.66±5.23) years. There were 891 males (88.9%) and 184 were females (17.1%); 24.7% workers were drinkers and 45.7% workers were smokers; 302 workers (28.1%) reported hypertension and 37 of them were taking antihypertensive drugs. The P50 (P25, P75) levels of urinary lead, urinary cadmium, and urinary arsenic were 6.11 (3.71, 11.08), 3.88 (2.68, 5.44), and 26.04 (19.99, 35.11) μg·g−1, respectively. After adjusting for gender, age, working seniority, body mass index, smoking, drinking, and the usage of antihypertensive drugs, systolic and diastolic blood pressure increased by 0.772 and 0.418 mmHg respectively for 10% increase in lead, cadmium, and arsenic mixed exposure. Urinary cadmium, among the three single exposures, had the greatest effect on systolic and diastolic blood pressure, weight (w)=0.523 and 0.551 respectively. The interaction of urinary lead and urinary cadmium was positively correlated with the occurrence of hypertension, multiplicative interaction OR (ORint)=1.88 (95%CI: 1.09, 3.63), attributable proportion due to interaction (AP)=1.19 (95%CI: 0.40, 8.18). Conclusion This study shows that mixed exposure to lead, cadmium, and arsenic has a positive relationship with blood pressure, in which cadmium plays a major role. Co-exposure to lead and cadmium has a positive interactive effect on hypertension development and systolic blood pressure elevation.