Elevated serum lead and cadmium levels associated with increased risk of dyslipidemia in children aged 6 to 9 years in Shenzhen, China

Complex metal interaction networks and the mediating role of biological aging in dyslipidemia

Metal mixture exposure is a major risk factor for dyslipidemia. Numerous studies have shown an association between metal mixture exposure, biological aging, and dyslipidemia. However, the interactions between metals, their directions, and the potential mechanisms through which they influence dyslipidemia remain unclear. This study utilized data from a repeated-measures cohort collected between 2016 and 2021, including 403 participants (1612 observations). Levels of metals, including chromium (Cr), cadmium (Cd), lead (Pb), and manganese (Mn), were measured in urine, along with four dyslipidemia biomarkers and their extended indicators. Generalized Estimating Equations (GEE) and Bayesian Kernel Machine Regression (BKMR) were used to analyze the effects of single and combined metal exposures on dyslipidemia. BKMR and the Synergy Index were employed to explore binary metal interactions and their directions. Marginal effects analysis assessed the impact of multiple metal interactions on dyslipidemia, and mediation analysis was conducted to explore the role of KDM.Accel in mediating the relationship between metal exposure and dyslipidemia. The findings indicated that both individual and combined exposures to Cr, Cd, Pb, and Mn significantly affected dyslipidemia. Multiple binary metal interactions exhibited synergistic effects on lipid outcomes. Pb∗Cd∗Cr and Pb∗Cd∗Mn showed an antagonistic effect on non-high-density lipoprotein cholesterol (NHC), while Cd∗Cr∗Mn∗Pb demonstrated synergistic effects on NHC. Additionally, KDM.Accel was identified as a key mediator in the relationship between Pb exposure and dyslipidemia, influencing the associations between Pb and HDL-C, LDL-C, and AC abnormalities. Mixed heavy metal exposure and their interactions are associated with dyslipidemia outcomes, with KDM.Accel playing a mediating role in the relationship between metals and dyslipidemia. This study highlights the potential interactions between metals and the mechanisms by which KDM.Accel may influence dyslipidemia, offering new insights into the connection between metal mixtures and dyslipidemia.

Insufficient Muscle Development Level Associated with Serum Zinc, Manganese and Cobalt Levels in Children Aged 6 to 9 Years in Shenzhen, China

Some trace elements have been found to be associated with muscle mass and muscle function; however, evidence in children is limited, and it remains unclear which trace elements are more relevant. We aimed to explore the association of levels of individual and combined essential trace elements and muscle development level (MDL) in young children. Muscle mass was measured by body composition analysis, and trace elements were determined by using inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression, restricted cubic spline (RCS) and weighted quantile sum regression (WQS) were used to assess the individual and joint associations between trace element levels and MDL. We enrolled 2851 children: 1595 boys (55.9%) and mean age 7.1 years (range 6.8-7.3). The proportion of insufficient muscle mass in the whole body, limbs, upper and lower limbs was 1.9%, 6.5%, 44.9% and 4.6%, respectively. The odds of insufficient MDL decreased with the fourth versus first quartile of zinc (OR = 0.67, 95% CI: 0.51-0.89), manganese (OR = 0.80, 95% CI: 0.65-1.00), and cobalt (OR = 0.89, 95% CI: 0.81-0.99) and was increased with the fourth quartile of nickel (OR = 2.23, 95% CI: 1.72-2.89) and selenium (OR = 1.51, 95% CI: 1.14-1.98). The RCS yielded similar results, except for the discrepancy in high cobalt levels. The odds of insufficient MDL decreased with the combination of nine trace elements (OR = 0.84, 95% CI: 0.73-0.97), primarily zinc (weight = 0.297), manganese (weight = 0.198) and cobalt (weight = 0.173). Insufficient MDL in young children was mainly in upper limbs. Low levels of zinc, manganese, and cobalt, individually or combined, were significantly associated with risk of insufficient MDL. Further foods rich in zinc, manganese, and cobalt should be suggested to supplement in diet, and increase exercise of upper limbs to improve insufficient MDL in the young children should be needed.

Associations of per- and polyfluoroalkyl substances and heavy metals with blood lipid profiles in a representative sample of Korean adolescents

BACKGROUND

Previous studies on the associations of per- and polyfluoroalkyl substances (PFASs) and heavy metals with lipid profiles among adolescents have been scarce. We sought to investigate the associations of PFASs and heavy metals with blood lipid levels in a representative sample of Korean adolescents.

METHODS

Data from the Korean National Environmental Health Survey (2018-2020) were used. Concentrations of PFASs [perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid, perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDeA)], lead, and mercury were measured in serum, whole blood, and urine samples, respectively. Linear regression, Bayesian kernel machine regression (BKMR), and k-means clustering analyses were employed to evaluate the associations between pollutants and lipid levels.

RESULTS

In the linear regression analyses, PFOA levels were associated with higher low-density lipoprotein cholesterol (LDL-C) levels; PFOS with higher total cholesterol (TC) levels; PFNA with higher TC, LDL-C, and non-high-density lipoprotein cholesterol (non-HDL-C) levels; PFDeA with higher TC, LDL-C, non-HDL-C, and high-density lipoprotein cholesterol levels; and mercury with higher TC and non-HDL-C levels. The BKMR analysis revealed that the PFAS and heavy metal mixture was associated with higher LDL-C levels (1.8% increase in LDL-C at the 75th percentile of all PFAS and heavy metal concentrations compared to their median values, 95% credible interval: 0.5, 3.1), primarily driven by the effect of PFDeA. Compared to individuals in the low pollutant exposure cluster (geometric mean levels of PFOA, PFOS, PFHxS, PFNA, PFDeA, lead, and mercury were 2.7 μg/L, 6.2 μg/L, 1.6 μg/L, 0.7 μg/L, 0.4 μg/L, 0.8 μg/dL, and 0.3 μg/L, respectively), those in the high pollutant exposure cluster (5.1 μg/L, 10.7 μg/L, 3.7 μg/L, 1.3 μg/L, 0.6 μg/L, 0.9 μg/dL, and 0.4 μg/L, respectively) demonstrated higher TC levels (2.5% increase in TC, 95% confidence interval: 0.1, 5.0) in the k-means clustering analysis.

CONCLUSION

Due to the limitations of this study, such as its cross-sectional design, these results should be interpreted cautiously and confirmed in future studies before drawing implications for public health strategies aimed at promoting health during adolescence and later in life.

Metal mixture exposures and serum lipid levels in childhood: the Rhea mother-child cohort in Greece

BACKGROUND

Growing evidence suggests that cardiovascular disease develops over the lifetime, often beginning in childhood. Metal exposures have been associated with cardiovascular disease and important risk factors, including dyslipidemia, but prior studies have largely focused on adult populations and single metal exposures.

OBJECTIVE

To investigate the individual and joint impacts of multiple metal exposures on lipid levels during childhood.

METHODS

This cross-sectional study included 291 4-year-old children from the Rhea Cohort Study in Heraklion, Greece. Seven metals (manganese, cobalt, selenium, molybdenum, cadmium, mercury, and lead) were measured in whole blood using inductively coupled plasma mass spectrometry. Serum lipid levels included total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol. To determine the joint and individual impacts of child metal exposures (log2-transformed) on lipid levels, Bayesian kernel machine regression (BKMR) was employed as the primary multi-pollutant approach. Potential effect modification by child sex and childhood environmental tobacco smoke exposure was also evaluated.

RESULTS

BKMR identified a positive association between the metal mixture and both total and LDL cholesterol. Of the seven metals examined, selenium (median 90.6 [IQR = 83.6, 96.5] µg/L) was assigned the highest posterior inclusion probability for both total and LDL cholesterol. A difference in LDL cholesterol of 8.22 mg/dL (95% CI = 1.85, 14.59) was observed when blood selenium was set to its 75th versus 25th percentile, holding all other metals at their median values. In stratified analyses, the positive association between selenium and LDL cholesterol was only observed among boys or among children exposed to environmental tobacco smoke during childhood.

IMPACT STATEMENT

Growing evidence indicates that cardiovascular events in adulthood are the consequence of the lifelong atherosclerotic process that begins in childhood. Therefore, public health interventions targeting childhood cardiovascular risk factors may have a particularly profound impact on reducing the burden of cardiovascular disease. Although growing evidence supports that both essential and nonessential metals contribute to cardiovascular disease and risk factors, such as dyslipidemia, prior studies have mainly focused on single metal exposures in adult populations. To address this research gap, the current study investigated the joint impacts of multiple metal exposures on lipid concentrations in early childhood.

Association between blood arsenic concentration and dyslipidemia: Mediating effect of lipid peroxidation in the elderly

BACKGROUND

The earlier investigations have revealed heavy metals exposure is implicated in the pathogenesis of dyslipidemia. The goal was to evaluated the relationship of blood arsenic (As) concentration with dyslipidemia in the elderly through a cross-sectional study.

METHODS

The entire 360 elderly population were selected. Fasting blood specimens, demographic information, and clinical characteristics were obtained. The concentration of blood As was detected using ICP-MS. Serum 8-iso-PGF2α, a biomarker of lipid peroxidation, was measured by ELISA.

RESULTS

Pearson correlative analysis hinted there were strong relationships of blood As with liver function indices in the elderly. Besides, blood As was positively associated with total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL-C), and apolipoprotein A-I (ApoA I). Further multivariate linear and logistic regression suggested that the incidences of TC and LDL-C elevation were upregulated with the rising tertiles of blood As. Blood As was positively related with the prevalence of dyslipidemia (OR=3.609; 95%CI: 1.353, 6.961). Additionally, serum 8-iso-PGF2α was dramatically and positively linked to the levels of blood As and lipid profiles. Mediation analyses verified that 8-iso-PGF2α partially mediated the correlations between blood As with TC (36.63%) and LDL-C (34.03%).

CONCLUSION

Blood As concentration is positively related to lipid profiles in the elderly. Higher blood As concentration elevates the prevalence of dyslipidemia. Lipid peroxidation partially mediates the correlation of As exposure with dyslipidemia.