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.

Polybrominated diphenyl ethers (PBDEs) have been used as flame retardants (FRs) in China for decades, even after they were identified as persistent organic pollutants. In this study, serum samples were collected from 172 adults without occupational exposure who were residents of a well-known FR production region (Laizhou Bay, north China), and PBDE congeners were measured to assess their occurrence, congener profile and influencing factors in serum. Moreover, the relationships between serum concentrations of PBDEs and thyroid/liver function indicators were analyzed to evaluate whether human exposure to PBDEs would lead to thyroid/liver injury. All 8 PBDE congeners were detected at higher frequencies and serum concentrations than those found in general populations. The median levels of ∑PBDEs, BDE-209 and ∑₃₋₇PBDEs (sum of tri-to hepta-BDEs) were 64.5, 56.9 and 7.2 ng/g lw (lipid weight), respectively, which indicated that deca-BDE was the primarily produced PBDE in Laizhou Bay and that the lower brominated BDEs were still ubiquitous in the environment. Gender was a primary influencing factor for some BDE congeners in serum; their levels in female serum samples were significantly lower than those in male serum samples. Serum PBDE levels showed a downward trend with increased body mass index (BMI), which might reflect the increasing serum lipid contents. Serum levels of some BDE congeners were significantly positively correlated with certain thyroid hormones and antibodies, including free triiodothyronine (fT3), total triiodothyronine (tT3), total thyroxine (tT4) and thyroid peroxidase antibody (TPO-Ab). Levels of some congeners were significantly negatively correlated with some types of serum lipid, including cholesterol (CHOL), low density lipoprotein (LDL) and total triglyceride (TG). Other than serum lipids, only two liver function indicators, total protein (TP) and direct bilirubin (DBIL), were significantly correlated with certain BDE congeners (BDE-100 and BDE-154). Our results provide new evidence on the thyroid-disrupting and hepatotoxic effects of PBDEs.

The effect of prenatal exposure to perfluoroalkyl substances (PFAS) on lipid concentrations in newborns is unknown. Using data from the Shanghai-Minhang Birth Cohort Study, we prospectively assessed the health effects of prenatal exposure to individual and multiple PFAS on cord lipid concentrations. Maternal plasma samples collected at 12–16 weeks of gestation were analyzed for eleven PFAS, and cord blood samples were analyzed for lipids: total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). We used multiple linear regression models to evaluate the associations of each individual PFAS with each lipid parameter, and used Bayesian Kernel Machine Regression (BKMR) models to assess the overall and single-exposure effects of eight PFAS with the detection rate above 80% on cord lipid concentrations. In multiple linear regression models, for each unit increase in ln-transformed maternal concentrations of perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUdA), and perfluorotridecanoic acid (PFTrDA), ln-transformed TC concentration decreased by 0.15 mg/dL (95% confidence interval (CI): −0.25, −0.05), 0.12 mg/dL (95% CI: −0.19, −0.05), 0.12 mg/dL (95% CI: −0.19, −0.05), and 0.05 mg/dL (95% CI: −0.09, −0.01), respectively, and ln-transformed HDL-C concentration decreased by 0.17 mg/dL (95% CI: −0.29, −0.05), 0.12 mg/dL (95% CI: −0.20, −0.03), 0.12 mg/dL (95% CI: −0.20, −0.03), and 0.06 mg/dL (95% CI: −0.11, −0.00), respectively. Statistically significant inverse associations were also observed between ln-transformed concentrations of PFDA, PFUdA, or PFTrDA and ln-transformed cord concentrations of TG and LDL-C. In BKMR models, the mixture of eight PFAS showed suggestively inverse association with all ln-transformed lipid concentrations, such that ln-transformed TC concentration of exposure to the 75th percentile of the mixture was 0.11 units (95% credible interval, −0.21, −0.01) lower than the 25th percentile exposure. Our findings indicated that prenatal exposure to PFAS may disrupt lipid metabolism in newborns.

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are synthetically manufactured chemicals recognized to be toxic, bioaccumulative, and persistent. Previous studies on PFAS exposure and serum lipid levels have mainly focused on individual PFASs; however, the influence of multiple-PFAS exposure on the serum lipid profile remains unclear. This study was performed to evaluate the combined effects of multiple PFASs on serum lipid levels. Based on the National Health and Nutrition Examination Survey (NHANES) data (2011–2014), we first established a linear regression model to estimate the association between single-PFAS exposure and the serum lipid profile. Then, a weighted quantile sum (WQS) regression model and a Bayesian kernel machine regression (BKMR) model were used to evaluate the effects of multiple-PFAS exposure on the serum lipid profile. A mediating effect model was used to assess how albumin mediates these effects. We found that PFASs were significantly associated with the levels of serum lipids, including high-density lipoprotein (HDL), low-density lipoprotein (LDL) and total cholesterol (TC). The WQS index was significantly correlated with the levels of HDL (β: 2.03, 95% CI: 0.74–3.32, P-value = 0.002), LDL (β: 4.16, 95% CI: 1.07–7.24, P-value = 0.008) and TC (β: 6.54, 95% CI: 3.00–10.1, P-value < 0.001). In the BKMR analysis, our results demonstrated that the effect of PFASs on serum lipids increased significantly when the concentrations of the PFASs were at their 60th percentiles or above compared to those at their 50th percentile. Mediation analysis showed that albumin mediated the effects of selected PFASs on the levels of serum lipids except for triglycerides (TG). PFAS exposure was correlated with the levels of serum lipids, and this correlation was mediated by albumin. Our results suggest that a comprehensive evaluation of multi-PFAS exposure could better characterize real-life exposure compared with single-PFAS exposure.

Both air pollution and dyslipidemias contributed to large number of deaths and disability-adjusted life lost years. Long-term air pollution exposure was related to changed blood lipids and risk of dyslipidemias. This study was designed to evaluate relationships between air pollutants, blood lipids and prevalence of dyslipidemias in a Chinese rural population exposed to high-level air pollution based on baseline data of The Henan Rural Cohort study. An amount of 39,057 participants from rural areas in China were included. The 3-year average exposure of air pollutants (PM2.5, PM10, NO2) was estimated by a spatiotemporal model. Logistic and linear regression models were employed to explore relationships between air pollutants, blood lipids (TC, TG, HDL-C and LDL-C) and prevalence of dyslipidemias. The three-year concentration of PM2.5, PM10 and NO2 was 72.8 ± 2.3 μg/m3, 131.5 ± 5.7 μg/m3and 39.1 ± 3.1 μg/m3, respectively. Overall, increased air pollution exposure was related to increased TC and LDL-C, while decreased TG and HDL-C. Each 1-μg/m3 increment of PM2.5 was related to 0.10% (0.07%–0.19%) increase in TC, 0.63% (0.50%–0.77%) increase in LDL-C, 2.93% (2.70%–3.16%) decrease in TG, 0.49% (0.38%–0.60%) decrease in HDL-C; and 5.7% (95%CI: 3.7%–7.6%), 4.0% (95%CI: 2.1%–6.0%) and 3.8% (95%CI: 2.5%–5.1%) increase in odds for hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia, respectively. Stronger associations were found in male and older participants. Findings suggest that air pollutants were associated with changed blood lipid levels and higher risk of dyslipidemias among rural population. Male and elder people should pay more attention to personal safety protection.

With the development of society and the economy, many Chinese cities are shrouded in pollution haze for much of the year. Scientific studies have identified various adverse effects of air pollutants on human beings. However, the relationships between air pollution and blood lipid levels are still unclear. The objective of this study is to explore the short and long-term effects of air pollution on eight blood lipid markers among elderly hypertension inpatients complicated with or without type 2 diabetes (T2D). Blood lipid markers which met the pre-established inclusion criteria were exported from the medical record system. Air pollution data were acquired from the official environmental protection website. Associations between the air quality index and the blood lipid indexes were analyzed by one-way ANOVA and further Bonferroni correction. In an exposure time of 7 days or longer, blood lipid markers were somewhat affected by poor air quality. However, the results could not predict whether atherosclerosis would be promoted or inhibited by poorer air condition. Changes of blood lipid markers of hypertension inpatients with or without T2D were not completely the same, but no blood lipid markers had an opposite trend between the two populations. The air quality index was associated with changes to blood lipid markers to some extent in a population of hypertension inpatients with or without T2D. Further studies are needed to investigate the potential mechanism by which air pollutants induce blood lipids changes.