Ambient particles with aerodynamic diameter <0.1 μm (PM₀.₁) have been suggested to have significant health impact. However, studies on the association between long-term PM₀.₁ exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006–2009 average PM₀.₁ concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM₀.₁ concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM₀.₁ concentration was associated with a 5.75 (95% Confidence interval, 3.24–8.25) mg/dl and a 6.05 (2.85–9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10–1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM₀.₁ exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM₂.₅, PM₁₀, NO₂, SO₂, O₃ and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O₃ had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O₃-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O₃ in the future.

Organophosphate esters (OPEs) are high-production volume chemicals. Use of OPEs has largely increased since the phase-out/ban of polybrominated diphenyl ethers (PBDEs). The ubiquitous occurrence of OPEs, in higher concentrations in abiotic matrices than brominated flame retardants (BFRs), is a concern because several of the OPEs have been linked to adverse health effects. In this study, urinary metabolites of OPEs were measured in a subset of a population-based sample of women of child bearing age recruited in Ontario, and associations between serum lipid levels and urinary concentrations of OPE metabolites were evaluated. Urine samples (n = 120) were extracted using automated solid phase extraction and analysed by ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). Diphenyl phosphate (DPHP), bis(2-chloropropyl) phosphate (BCIPP) and bis(1,3-dichloro-2 propyl) phosphate (BDCIPP) were detected with frequencies of 100%, 76% and 75% at median concentrations of 13.8 ng/mL, 0.5 ng/mL and 1.8 ng/mL, respectively. Bis(2-chloroethyl) hydrogen phosphate (BCEP) and di-cresyl phosphate (DCP; mixture of 3 isomers) were detected in 52% and 42% of the samples, respectively. Detected at lower frequencies were 1-hydroxy-2-propyl bis(1-chloro-2-propyl) phosphate (BCIPHIPP, 29%), bis-2(butoxyethyl) phosphate (BBOEP, 11%), and desbutyl-tris-(2-butoxy-ethyl) phosphate (desbutyl TBOEP, 9%). Using multiple regression model, a negative statistically significant correlation was observed between BCEP and cholesterol (p = 0.04), as well as BCEP and total lipid (p = 0.04). Whereas BCIPP was positively and significantly correlated with cholesterol (p = 0.003) and LDL (p = 0.001). Additional work to further explore these relationships and to evaluate more recently identified OPE metabolites is warranted.

In epidemiological studies on the toxic effects of prenatal exposure to hexachlorobenzene (HCB), researchers report HCB concentrations, either as wet-weight or per lipid weight basis, in matrices like breast milk, and maternal and cord blood. Conversion of exposures across matrices is needed for comparisons of concentrations and dose effect across cohorts. Using data from a birth cohort study in eastern Slovakia, we derived the maternal blood to cord blood HCB concentration ratio utilizing measured concentrations in 1027 paired maternal and cord blood samples, on a per-lipid basis. In addition to data from the Slovak study, the maternal milk to maternal serum ratio was summarized from 23 published studies on partitioning of HCB between human milk lipid and blood lipid. We identified two distinct groups of milk:blood ratios, those ≤0.45 and those ≥0.85. We assumed that using partition ratios ≤0.45 will underestimate HCB exposure estimates. Taking into account this precautionary measure, we suggest a conversion ratio of 1.21, which is the median of the 16 ratios identified in our literature review. We consider our estimate as conservative and providing appropriate safety in risk analysis.

The aim of this research was to study the association of the accumulated human exposure to persistent organic pollutants with serum lipid levels and obesity, in a cohort of 298 adults.In the multivariable analyses, HCB concentrations evidenced a significant quadratic association with levels of total cholesterol, HDL, LDL, and total serum lipids. Likewise, PCBs 138 and 180 were associated with triglycerides and total serum lipids, and PCB 153 with LDL. HCB, p,p′-DDE, and β-HCH showed quadratic associations with BMI. All quadratic models showed a positive trend at low exposure levels, while the slope decreased or even became negative at higher exposure levels. Additionally, PCB 138 was positively associated with BMI but in a linear manner. Our results suggest a potential relationship between historical POP exposure and serum lipids/obesity, which followed a non-linear pattern in most cases.

Associations between polycyclic aromatic hydrocarbons (PAHs) and respiratory diseases have been widely studied, but the effects of PAH on liver toxicity in adolescents are unclear. Here, 3194 adolescents with NHANES data from 2003 to 2016 were selected. PAH exposure was assessed by measuring PAH metabolites in urine. The outcome variables were the levels of alanine aminotransferase (ALT), aspartate amino transferase (AST) and gamma-glutamyl transpeptidase (GGT). The association between PAH exposure and liver function was evaluated by the weighted quantile sum (WQS) and logistic regression, and the associations between PAHs and inflammation and blood lipids were evaluated by linear regression. Covariates were adjusted for age, ethnicity, BMI, physical activity, family income, cotinine, and urinary creatinine. The results showed that for females, mixed PAH exposure was related to an increased ALT level (OR = 2.33, 95% CI 1.15, 4.72), and 2-fluorene contributed the most (38.6%). Urinary 2-fluorene was positively associated with an elevated ALT level (OR = 2.19 95% 1.12, 4.27, p for trend = 0.004). Mechanistically, 2-fluorene can cause a 3.56% increase in the white blood cell count, a 6.99% increase in the triglyceride level, and 1.70% increase in the total cholesterol level. PAHs may have toxic effects, possibly mediated by inflammation and blood lipids, on the adolescent female liver. Additional confirmatory studies are needed.

Few studies have explored the links of air pollution and childhood lipid profiles and dyslipidemias. We aimed to explore this topic in Chinese children and adolescents. This study included 12,814 children aged 7–18 years who participated in a national survey in 2013. Satellite-based spatial-temporal model was used to predict 3-y (2011–2013) average particles with diameters ≤ 1.0 μm (PM₁), ≤2.5 μm (PM₂.₅), ≤10 μm (PM₁₀), and nitrogen dioxide (NO₂) concentrations. Generalized linear mixed models were employed to evaluate the relationships of air pollution and total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and dyslipidemias. Every 10 μg/m³ increase in PM₁, PM₂.₅, PM₁₀, and NO₂ was related to increases of 6.20% [95% confidence interval (CI): 2.44, 10.10], 5.31% (95%CI: 0.41, 10.44), 3.49% (95%CI: 0.97, 6.08), and 5.25% (95%CI: 1.56, 9.07) in TC, respectively. The odds ratio of hypercholesterolemia associated with a 10 μg/m³ increase in PM₁, PM₂.₅, and NO₂ was 2.15 (95%CI: 1.27, 3.65), 1.70 (95%CI: 1.12, 2.60), and 1.43 (95%CI: 1.05, 1.93), respectively. No associations were found for air pollution and other blood lipids. Long-term PM₁, PM₂.₅, PM₁₀, and NO₂ exposures were positively associated with TC levels and risk of hypercholesterolemia in children and adolescents.

Adverse health effects of exposure to air pollution have been investigated in many previous studies. However, there is no study available on the association between maternal exposure to air pollution during pregnancy and cord blood lipid profile. This study, based on 150 mother-newborn pairs residing in Sabzevar, Iran (2018), evaluated the association of exposure to ambient air pollution as well as traffic indicators (total street length in different buffers around residential address and distance to major roads) during entire pregnancy with lipid levels cord blood lipid profile. Concentrations of PM₁₀, PM₂.₅, and PM₁ at maternal residential address were estimated using land use regression (LUR) models. We measured triglyceride (TAG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC) levels and TC/HDL-C and TAG/HDL-C ratio in the cord blood samples to characterize their lipid profile. Multiple linear regression models were developed to estimate the association of exposure to air pollution and traffic indicators with cord blood lipid profile controlled for relevant covariates. Higher concentrations of PM₂.₅ and PM₁₀ were associated with higher levels of TAG, TC, HDL-C, TC/HDL-C, and TAG/HDL-C in cord blood samples. Moreover, higher concentration of PM₁ was associated with higher levels of TAG, TC and LDL-C. There was also a positive association between total street length in 100 m buffer around home and serum levels of TC, TAG, LDL-C and TC/HDL ratio (β = 3.73, 95% confidence intervals (CI): 1.76, 5.71; β = 2.75, 95% CI: 0.97, 4.53; β = 1.87, 95% CI: 0.64, 3.09; β = 0.06, 95% CI: 0.01, 0.11, respectively). However, the associations for total street length in larger buffers and distance to major roads were not statistically significant. Our findings support a relationship between exposure to air pollution during pregnancy and increase in cord blood lipid levels.

Evidence is available about the associations of phthalates or their metabolites with blood lipids, however, the mixture effects of multiple phthalate metabolites on blood lipid traits remain largely unknown. In this pilot study, 106 individuals at three age groups of <18, 18- and ≥60 years were recruited from the residents (n = 1240) who were randomly selected from two communities in Wuhan city, China. The participants completed the questionnaire survey and physical examination as well as provided urine samples in the winter of 2014 and the summer of 2015. We measured urinary levels of nine phthalate metabolites using a high-performance liquid chromatography-tandem mass spectrometry. We estimated the associations of individual phthalate metabolite with blood lipid traits by linear mixed effect (LME) models, and assessed the overall association of the mixture of nine phthalate metabolites with blood lipid traits using Bayesian kernel machine regression (BKMR) models. LME models revealed the negative association of urinary mono-2-ethylhexyl phthalate (MEHP) with total cholesterol (TC) as well as of urinary mono-benzyl phthalate or urinary MEHP with low density lipoprotein cholesterol (LDL-C). BKMR models revealed the negative overall association of the mixture of nine phthalate metabolites with TC or LDL-C, and DEHP metabolites (especially MEHP) had a greater contribution to TC or LDL-C levels than non-DEHP metabolites. The findings indicated the negative overall association of the mixture of nine phthalate metabolites with TC or LDL-C. Among nine phthalate metabolites, MEHP was the most important component for the changes of TC or LDL-C levels, implying that phthalates exposure may disrupt lipid metabolism in the body.

Copper have been reported to be associated with metabolic diseases. However, results on copper exposure with blood lipid profiles are inconsistent, and the underlying mechanisms of this association remain unclear. This study focused on investigating associations between urinary copper and blood lipid profiles; and exploring the potential role of systemic inflammation in such relationships. Concentrations of urinary copper, plasma C-reactive protein (CRP), and four blood lipid parameters (e.g., Total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) were measured in the adult participants from Wuhan-Zhuhai cohort. The associations between copper, CRP, and four blood lipids were assessed by the multivariable linear regression models, and the 3D mesh graphs was used to examine the joint effects of copper exposure and CRP on four blood lipid parameters. In addition, we used mediation analysis to investigate the mediated effects of CRP in the relationships between copper exposure and blood lipid profiles. Each 1% increase in urinary copper was statistically significantly associated with a 5.32% (95% CI: 2.48%, 8.24%) increase in TG after adjusting for the confounders (P < 0.05). No significant associations were observed between urinary copper and the other three blood lipid parameters (all P > 0.05). In addition, urinary copper increased monotonically with plasma CRP elevation, which in turn, was positively associated with TC, TG, and LDL-C and negatively related to HDL-C (all P < 0.05). Results from 3D mesh graphs demonstrated that increased levels of plasma CRP with higher urinary copper corresponded to higher TC, TG, LDL-C, and lower HDL-C concentrations. Mediation analysis observed that CRP mediated 6.27% in the relationships of urinary copper and TG. These findings suggest that systemic inflammation partly mediated the association between copper exposure and abnormal blood lipid, and may contribute to the development of dyslipidemias.