Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

Environmental risk score of multiple pollutants for kidney damage among residents in vulnerable areas by occupational chemical exposure in Korea

This study aimed to develop an environmental risk score (ERS) of multiple pollutants (MP) causing kidney damage (KD) in Korean residents near abandoned metal mines or smelters and evaluate the association between ERS and KD by a history of occupational chemical exposure (OCE). Exposure to MP, consisting of nine metals, four polycyclic aromatic hydrocarbons, and four volatile organic compounds, was measured as urinary metabolites. The study participants were recruited from the Forensic Research via Omics Markers (FROM) study (n = 256). Beta-2-microglobulin (β2-MG), N-acetyl-β-D-glucosaminidase (NAG), and estimated glomerular filtration rate (eGFR) were used as biomarkers of KD. Bayesian kernel machine regression (BKMR) was selected as the optimal ERS model with the best performance and stability of the predicted effect size among the elastic net, adaptive elastic net, weighted quantile sum regression, BKMR, Bayesian additive regression tree, and super learner model. Variable importance was estimated to evaluate the effects of metabolites on KD. When stratified with the history of OCE after adjusting for several confounding factors, the risks for KD were higher in the OCE group than those in the non-OCE group; the odds ratio (OR; 95% CI) for ERS in non-OCE and OCE groups were 2.97 (2.19, 4.02) and 6.43 (2.85, 14.5) for β2-MG, 1.37 (1.01, 1.86) and 4.16 (1.85, 9.39) for NAG, and 4.57 (3.37, 6.19) and 6.44 (2.85, 14.5) for eGFR, respectively. We found that the ERS stratified history of OCE was the most suitable for evaluating the association between MP and KD, and the risks were higher in the OCE group than those in the non-OCE group.

Mixture effects of trace element levels on cardiovascular diseases and type 2 diabetes risk in adults using G-computation analysis

There is an increasing concern about the health effects of exposure to a mixture of pollutants. This study aimed to evaluate the associations between serum levels of heavy/essential metals ([Arsenic (As), Cadmium (Cd), Mercury (Hg), Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Iron (Fe), and Zinc (Zn)]) and the risk of developing cardiovascular diseases (CVDs) and type 2 diabetes mellitus (T2D). Data were collected from 450 participants (150 with CVDs, 150 with T2D, and 150 healthy subjects) randomly selected from the Ravansar Non-Communicable Disease (RaNCD) cohort in Western Iran, covering the years 2018-2023. Trace element levels in the serum samples were assayed using ICP-MS. Logistic regression was performed to estimate the adjusted risk of exposure to single and multi-metals and CVD/T2D. Odds ratios were adjusted for age, sex, education, residential areas, hypertension, and BMI. The mixture effect of exposure to multi-metals and CVD/T2D was obtained using Quantile G-computation (QGC). In the logistic regression model, chromium, nickel, and zinc levels were associated with CVD, and significant trends were observed for these chemical quartiles (P < 0.001). Arsenic, chromium, and copper levels were also associated with T2D. The weight quartile sum (WQS) index was significantly associated with both CVD (OR 4.17, 95% CI 2.16-7.69) and T2D (OR 11.96, 95% CI 5.65-18.26). Cd, Pb, and Ni were the most heavily weighed chemicals in these models.The Cd had the highest weight among the metals in the CVD model (weighted at 0.78), followed by Hg weighted at 0.197. For T2D, the serum Pb (weighted at 0.32), Ni (weighted at 0.19), Cr (weighted at 0.17), and Cd (weighted at 0.14) were the most weighted in the G-computation model. The results showed the significant role of toxic and essential elements in CVDs and T2D risk. This association may be driven primarily by cadmium and mercury for CVDs and Pb, Ni, Cr, and Cd for T2D, respectively. Prospective studies with higher sample sizes are necessary to confirm or refute our preliminary results as well as to determine other important elements.

The simulation of the emission of iron fumes caused by shielded metal arc welding using a computational fluid dynamics method

Computational fluid dynamics (CFD) is an indispensable simulation tool for predicting the emission of pollutants in the work environment. Welding is one of the most common industrial processes that might expose the operators and surrounding workers to certain hazardous gaseous metal fumes. In the present study, we used computational fluid dynamics (CFD) methodology for simulating the emission of iron fumes from the shielded metal arc welding (SMAW) procedure. A galvanized steel chamber was fabricated to measure the pollutant concentration and identify the size of the fume created by the SMAW. Then, the emission of welding aerosol was simulated using a method of computational fluid-particle dynamics with the ANSYS 2020 R1 software. The highest amount of welding fumes concentration was related to iron fumes (i.e., 3045 μg/m³ with a diameter of 0.25 μm). The results of the current study indicated that the local exhaust and general ventilation system can prevent the spreading of welding fumes to the welder's breathing zone and the surrounding environment. CFD was also found to be an efficient method for predicting the emission of the iron fumes created by SMAW as well as for selecting an appropriate ventilation system. However, further studies that take the modeling of welding-generated emission of additional metal particles and gases into account will need to be undertaken.

Combined exposure to multiple metals on cardiovascular disease in NHANES under five statistical models

BACKGROUND

It is well-documented that heavy metals are associated with cardiovascular disease (CVD). However, there is few studies exploring effect of metal mixture on CVD. Therefore, the primary objective of present study was to investigate the joint effect of heavy metals on CVD and to identify the most influential metals in the mixture.

METHODS

Original data for study subjects were obtained from the National Health and Nutrition Examination Survey. In this study, adults with complete data on 12 kinds of urinary metals (antimony, arsenic, barium, cadmium, cobalt, cesium, molybdenum, mercury, lead, thallium, tungsten, and uranium), cardiovascular disease, and core covariates were enrolled. We applied five different statistical strategies to examine the CVD risk with metal exposure, including multivariate logistic regression, adaptive elastic net combined with Environmental Risk Score, Quantile g-computation, Weighted Quantile Sum regression, and Bayesian kernel machine regression.

RESULTS

Higher levels of cadmium, tungsten, cobalt, and antimony were significantly associated with Increased risk of CVD when covariates were adjusted for multivariate logistic regression. The results from multi-pollutant strategies all indicated that metal mixture was positively associated with the risk of CVD. Based on the results of multiple statistical strategies, it was determined that cadmium, tungsten, cobalt, and antimony exhibited the strongest positive correlations, whereas barium, lead, molybdenum, and thallium were most associated with negative correlations.

CONCLUSION

Overall, our study demonstrates that exposure to heavy metal mixture is linked to a higher risk of CVD. Meanwhile, this association may be driven primarily by cadmium, tungsten, cobalt, and antimony. Further prospective studies are warranted to validate or refute our primary findings as well as to identify other important heavy metals linked with CVD.

Effect of welding fumes on the cardiovascular system: a six-year longitudinal study

Objective This study investigated whether low-to-moderate exposure to welding fumes is associated with adverse effects on the cardiovascular system. Methods To test this, we performed a longitudinal analysis of 78 mild steel welders and 96 controls; these subjects were examined twice, six years apart (ie, timepoints 1 and 2). All subjects (male and non-smoking at recruitment) completed questionnaires describing their health, work history, and lifestyle. We measured their blood pressure, endothelial function (by EndoPAT), and risk markers for cardiovascular disease [low-density lioprotein (LDL), homocysteine, C-reactive protein]. Exposure to welding fumes was assessed from the responses to questionnaires and measurements of respirable dust in their breathing zones adjusted for use of respiratory protection equipment. Linear mixed-effect regression models were used for the longitudinal analysis. Results Median respirable dust concentrations, adjusted for respirable protection, of the welders were 0.7 (5-95 percentile range 0.2-4.2) and 0.5 (0.1-1.9) mg/m ³at timepoints 1 and 2, respectively. Over the six-year period, welders showed a statistically significant increase in systolic [5.11 mm Hg, 95% confidence interval (CI) 1.92-8.31] and diastolic (3.12 mm Hg, 95% CI 0.74-5.5) blood pressure compared with controls (multi-variable adjusted mixed effect models). Diastolic blood pressure increased non-significantly by 0.22 mm Hg (95% CI -0.02-0.45) with every additional year of welding work. No consistent significant associations were found between exposure and endothelial function, LDL, homocysteine, or C-reactive protein. Conclusion Exposure to welding fumes at low-to-moderate levels is associated with increased blood pressure, suggesting that reducing the occupational exposure limit (2.5 mg/m ³for inorganic respirable dust in Sweden) is needed to protect cardiovascular health of workers.

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM_2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM_2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 μg/m³ in 3-year average exposure to PM_2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM_2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM_2.5. SUMMARY: Long-term PM_2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM_2.5.

Continuous monitoring of cerebrovascular reactivity through pulse transit time and intracranial pressure

OBJECTIVE

Cerebrovascular reactivity (CR) is a mechanism that maintains stable blood flow supply to the brain. Pressure reactivity index (PRx), the correlation coefficient between slow waves of invasive arterial blood pressure (ABP) and intracranial pressure (ICP) has been validated for CR assessment. However, in clinical ward, not every subarachnoid hemorrhage (SAH) patient has invasive ABP monitoring. Pulse transit time (PTT), the propagation time of a pulse wave travelling from the heart to peripheral arteries, has been suggested as a surrogate measure of ABP. In this study, we proposed to use PTT instead of invasive ABP to monitor CR.

APPROACH

Forty-five SAH patients with simultaneous recordings of invasive ABP, ICP, oxygen saturation level (SpO2) and electrocardiograph (ECG) were included. PTT was calculated as the time from the ECG R-wave peak to the onset of SpO2. PTT based pressure reactivity index (tPRx) was calculated as the correlation coefficient between slow waves of PTT and ICP. Wavelet tPRx (wtRx) was calculated as the cosine of wavelet phase shift between PTT and ICP. Meanwhile, PRx and wPRx were also calculated using invasive ABP and ICP as input.

MAIN RESULTS

The result showed a negative relationship between PTT and ABP (r  =  -0.58, p   <  0.001). tPRx negatively correlated with PRx (r  =  -0.51, p   =  0.003). Wavelet method correlated well with correlation method demonstrated through positive relationship between wPRx and PRx (r  =  0.82, p   <  0.001) as well as wtPRx and tPRx (r  =  0.84, p   <  0.001).

SIGNIFICANCE

PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable. Key points • Pulse transit time (PTT), defined as the propagation time of a pulse wave travelling from the heart to the peripheral arteries, has been proposed as a surrogate measure of ABP. The relationship between PTT and ABP in SAH patients remains unknown. • Cerebrovascular reactivity (CR) assessment through PTT has advantages over invasive ABP, as it avoids bleeding and infection risk, and can be used outside of the ICU. • We introduced a new method to assess CR using PTT and ICP through correlation based method and wavelet based method. • We found that beat-to-beat PTT was negatively related with invasive ABP in SAH patients. A significant linear relationship exists between PTT-based CR parameter and a well validated method, PRx. PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable in SAH patients.

Assessing exposure to metals using biomonitoring: Achievements and challenges experienced through surveys in low- and middle-income countries

In this narrative account based on a keynote presentation on exposure biomonitoring of metals in low- and middle-income countries (LMIC), we first briefly address practical issues that have arisen from our experience during the conduct of various surveys in LMIC. These have included the statistical handling of multiple pollutants in the same subject, the problem of correctly adjusting for urinary flow in spot samples of urine, and the possible external contamination of samples when doing field surveys in challenging environments. We then review and present selected results from surveys conducted in the mining area of Katanga in the Democratic Republic of Congo (DR Congo), where we documented high urinary levels of cobalt and other trace metals (arsenic, uranium) in people living close (<3 km) to mining or smelting operations (Banza et al., 2009). Consumption of contaminated foodstuffs (maize, legumes, fish) and, especially among children, dust ingestion proved to be the main sources of exposure to cobalt (Cheyns et al., 2014). Urinary biomonitoring studies among artisanal workers involved in mining cobalt, craftsmen working malachite, and workers processing gold ore revealed high to extremely high values of cobalt (largely exceeding the Biological Exposure Index of 15 μg/L), as well as other trace metals such as uranium, manganese, lead or mercury, depending on the type of jobs. This abundant biomonitoring data has been valuable to argue for improved enforcement of legislation to protect workers and citizens against the hazards posed by the mining activities in the area. Epidemiological studies have been undertaken and are ongoing to assess the human health impact of this pollution.

Preoperative profile of inflammatory factors in aqueous humor correlates with postoperative inflammatory response in patients with congenital cataract

Purpose

To measure the aqueous humor concentrations of inflammatory factors in patients with congenital cataract and to investigate the relationship between the levels and postoperative inflammatory responses.

Methods

Aqueous humor samples were prospectively collected from 65 eyes of children with congenital cataracts from January to June 2015. The levels of 41 inflammation-related cytokines, chemokines, and growth factors in aqueous humor were measured using multiplex bead immunoassay. Data on patient demographics and postoperative inflammatory response evaluation of posterior capsule opacification (EPCO) scores were collected for correlation analysis of short- and long-term postoperative inflammatory responses, respectively.

Results

Fifteen inflammatory factors were differentially expressed between congenital cataract and age-related cataract. EGF and IL-3 were positively correlated, whereas IL-8 and MCP-1 were negatively correlated with age. TNFα, IL-17A, IL-3, and sCD40L were preferably expressed in specific morphological types of congenital cataract. One month and 3 months postoperatively, PDGF-AA exhibited a positive correlation with the EPCO scores, whereas IL-1RA exhibited a negative correlation. Macrophage-derived chemokine (MDC) showed a positive correlation with the EPCO scores 1 year postoperatively.

Conclusions

This study provided a comprehensive preoperative profile of inflammatory factors and their correlations with postoperative inflammatory responses in patients with congenital cataract. These factors may serve as potential biomarkers to predict the postoperative inflammatory response. These findings will also facilitate the development of anti-inflammatory medications in the perioperative period.

Association between Dietary Intake and Coronary Artery Calcification in Non-Dialysis Chronic Kidney Disease: The PROGREDIR Study

Coronary artery calcification (CAC) is a widespread condition in chronic kidney disease (CKD). Diet may play an important role in CAC, but this role is not clear. This study evaluated the association between macro-and micronutrient intakes and CAC in non-dialysis CKD patients. We analyzed the baseline data from 454 participants of the PROGREDIR study. Dietary intake was evaluated by a food frequency questionnaire. CAC was measured by computed tomography. After exclusion of participants with a coronary stent, 373 people remained for the analyses. The highest tertile of CAC was directly associated with the intake of phosphorus, calcium and magnesium. There was a higher intake of pantothenic acid and potassium in the second tertile. After adjustments for confounding variables, the intake of pantothenic acid, phosphorus, calcium and potassium remained associated with CAC in the generalized linear mixed models. In order to handle the collinearity between these nutrients, we used the LASSO (least absolute shrinkage and selection operator) regression to evaluate the nutrients associated with CAC variability. In this approach, the nutrients that most explained the variance of CAC were phosphorus, calcium and potassium. Prospective studies are needed to confirm these findings and assess the role of interventions regarding these micronutrients on CAC prevention and progression.