Is long-term PM1 exposure associated with blood lipids and dyslipidemias in a Chinese rural population?

Clean air policy reduces the atherogenic lipid profile levels: Results from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) Study

Evidence of the associations between long-term exposure to PM2.5 and O3 and human blood lipid concentrations is abundant yet inconclusive. Whether clean air policies could improve lipid profiles remains unclear. In total, 2979312 participants from a Chinese nationwide prospective study were included. For cross-sectional analyses, linear mixed-effects models were utilized to assess the associations of pollutants with lipid profiles (TC, LDL-C, TG, HDL-C). For longitudinal analyses, a quasi-experimental design and difference-in-differences models were employed to investigate the impact of China's Clean Air Act. In the cross-sectional analyses, each IQR increase in PM2.5 was associated with 2.49 % (95 % CI: 2.36 %, 2.62 %), 2.51 % (95 % CI: 2.26 %, 2.75 %), 3.94 % (95 % CI: 3.65 %, 4.23 %), and 1.54 % (95 % CI: 1.38 %, 1.70 %) increases in TC, LDL-C, TG, and HDL-C, respectively. For each IQR increase in O3, TC, LDL-C, TG, and HDL-C changed by 1.06 % (95 % CI: 0.95 %, 1.17 %), 1.21 % (95 % CI: 1.01 %, 1.42 %), 1.78 % (95 % CI: 1.54 %, 2.02 %), and -0.63 % (95 % CI: -0.76 %, -0.49 %), respectively. Longitudinal analyses showed that the intervention group experienced greater TC, LDL-C, and HDL-C reductions (1.77 %, 4.26 %, and 7.70 %, respectively). Our findings suggest that clean air policies could improve lipid metabolism and should be implemented in countries with heavy air pollution burdens.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities

Background

Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse.

Methods

Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders.

Results

The mean annual exposure in Chennai and Delhi was 40 and 102 μg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi.

Conclusion

These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey

Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM1, PM2.5, PM10) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from -0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (-0.241 in Romania and -0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality.

The Exposure Peaks of Traffic-Related Ultrafine Particles Associated with Inflammatory Biomarkers and Blood Lipid Profiles

In this article, we explored the effects of ultrafine particle (UFP) peak exposure on inflammatory biomarkers and blood lipids using two novel metrics-the intensity of peaks and the frequency of peaks. We used data previously collected by the Community Assessment of Freeway Exposure and Health project from participants in the Greater Boston Area. The UFP exposure data were time-activity-adjusted hourly average concentration, estimated using land use regression models based on mobile-monitored ambient concentrations. The outcome data included C-reactive protein, interleukin-6 (IL-6), tumor necrosis factor-alpha receptor 2 (TNF-RII), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides and total cholesterol. For each health indicator, multivariate regression models were used to assess their associations with UFP peaks (N = 364-411). After adjusting for age, sex, body mass index, smoking status and education level, an increase in UFP peak exposure was significantly (p < 0.05) associated with an increase in TNF-RII and a decrease in HDL and triglycerides. Increases in UFP peaks were also significantly associated with increased IL-6 and decreased total cholesterol, while the same associations were not significant when annual average exposure was used. Our work suggests that analysis using peak exposure metrics could reveal more details about the effect of environmental exposures than the annual average metric.

Assessing the effects of air pollution and residential greenness on frailty in older adults: a prospective cohort study from China

Many studies have established a correlation between air pollution and green space with age-related diseases, yet the relationship between air pollution, green space, and frailty among older adults is not fully understood. The primary objective of this investigation is to examine the longitudinal association among air pollution, green space, and frailty in older adults, as well as the potential interaction and mediating effect. Analyzed data were obtained from the multi-wave CLHLS investigation (2008-2018). The participants' environmental exposure was evaluated using six air pollutants (PM1, PM2.5, PM10, PM10-2.5, O3, and NO2), and normalized difference vegetation index (NDVI). Annual ambient air pollutants were estimated using satellite-based spatiotemporal models. Time-varying Cox proportional risk models were employed to investigate the longitudinal relationships between air pollutants, greenness, and the onset of frailty in the elderly population. We conducted a variety of subgroup analyses, sensitivity analyses, and assessed potential interaction and causal mediating effects. A total of 6953 eligible elderly individuals were enrolled in our study. In the fully adjusted model, per IQR uptick in levels of PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 corresponded to a 17% (95% CI 1.10-1.24), 25% (95% CI 1.17-1.34), 29% (95% CI 1.20-1.39), 35% (95% CI 1.24-1.47), 12% (95% CI 1.04-1.20), and 11% (95% CI 1.05-1.18) increase in frailty risk, respectively. For NDVI, increased IQR was significantly negatively associated with the risk of frailty (aHR 0.82, 95% CI 0.77-0.87). Our results revealed a significant interaction effect among O3, NO2, and residential greenness. PM1, PM2.5, PM10, and PM10-2.5 play a mediating role in the estimated relationship between residential greenness and frailty. In summary, our study reveals that PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 correspond to elevated risks of frailty in the elderly. Residential greenness is associated with a lower risk of frailty in the elderly. Residential greenness can exert a positive impact on frailty by reducing particulate matter concentrations.

Association between exposure to air pollution and blood lipids in the general population of Spain

BACKGROUND AND AIMS

We aimed to assess the associations of exposure to air pollutants and standard and advanced lipoprotein measures, in a nationwide sample representative of the adult population of Spain.

METHODS

We included 4647 adults (>18 years), participants in the national, cross-sectional, population-based di@bet.es study, conducted in 2008-2010. Standard lipid measurements were analysed on an Architect C8000 Analyzer (Abbott Laboratories SA). Lipoprotein analysis was made by an advanced 1 H-NMR lipoprotein test (Liposcale®). Participants were assigned air pollution concentrations for particulate matter <10 μm (PM10 ), <2.5 μm (PM2.5 ) and nitrogen dioxide (NO2 ), corresponding to the health examination year, obtained by modelling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model).

RESULTS

In multivariate linear regression models, each IQR increase in PM10 , PM2.5 and NO2 was associated with 3.3%, 3.3% and 3% lower levels of HDL-c and 1.3%, 1.4% and 1.1% lower HDL particle (HDL-p) concentrations (p < .001 for all associations). In multivariate logistic regression, there was a significant association between PM10 , PM2.5 and NO2 concentrations and the odds of presenting low HDL-c (<40 mg/dL), low HDL-p (

CONCLUSIONS

Our study shows an association between the exposure to air pollutants and blood lipids in the general population of Spain, suggesting a link to atherosclerosis.

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Key Words

• HDL
• air pollution
• cholesterol
• lipids
• lipoprotein
• triglyceride

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MESH Headings

• Male
• Adult
• Humans
• Nitrogen Dioxide/analysis
• Spain/epidemiology
• Cross-Sectional Studies
• Air Pollution/adverse effects
• Air Pollution/analysis
• Air Pollutants/analysis
• Particulate Matter/analysis
• Lipids
• Lipoproteins/analysis
• Environmental Exposure/adverse effects

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Grants

• RC-0006-2016 Consejería de Salud y Bienestar Social, Junta de Andalucía
• CM21/00214 Instituto de Salud Carlos III
• INT21/00037 Instituto de Salud Carlos III
• PI17/02136 Instituto de Salud Carlos III
• PI20/01322 Instituto de Salud Carlos III

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Affiliation(s)

Sergio Valdés Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Viyey Doulatram-Gamgaram Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain
Cristina Maldonado-Araque Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Eva García-Escobar Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Sara García-Serrano Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Wasima Oualla-Bachiri Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Marta García-Vivanco Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) - División de Contaminación Atmosférica, Madrid, Spain
Juan Luis Garrido Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) - División de Contaminación Atmosférica, Madrid, Spain
Victoria Gil Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) - División de Contaminación Atmosférica, Madrid, Spain
Fernando Martín-Llorente Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) - División de Contaminación Atmosférica, Madrid, Spain
Alfonso Calle-Pascual Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Department of Endocrinology and Nutrition and Instituto de Investigación Sanitaria University Hospital S. Carlos (IdISSC), Department Medicine II, Universidad Complutense (UCM), Madrid, Spain
Luis Castaño Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Hospital Universitario Cruces, BioCruces, UPV/EHU, Barakaldo, Spain Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
Elías Delgado Department of Endocrinology and Nutrition, Hospital Universitario Central de Asturias/University of Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
Edelmiro Menéndez Department of Endocrinology and Nutrition, Hospital Universitario Central de Asturias/University of Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
Josep Franch-Nadal Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain EAP Raval Sud, Institut Català de la Salut, Red GEDAPS, Primary Care, Unitat de Suport a la Recerca (IDIAP - Fundació Jordi Gol), Barcelona, Spain
Sonia Gaztambide Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain Department of Endocrinology and Nutrition, Hospital Universitario Cruces - BioCruces Bizkaia - UPV-EHU, Baracaldo, Barcelona, Spain
Joan Girbés Diabetes Unit, Hospital Arnau de Vilanova, Valencia, Spain
F Javier Chaves Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Genomic Studies and Genetic Diagnosis Unit, Fundación de Investigación del Hospital Clínico de Valencia - INCLIVA, Valencia, Spain
José L Galán-García Department of Applied Mathematics, University of Málaga, Málaga, Spain
Gabriel Aguilera-Venegas Department of Applied Mathematics, University of Málaga, Málaga, Spain
Joan Carles Vallvé Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Rovira i Virgili University, IISPV, Reus, Spain
Núria Amigó Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Metabolomics Platform, Universitat Rovira i Virgili, IISRV, Reus, Spain Biosfer Teslab, Reus, Spain
Montse Guardiola Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Rovira i Virgili University, IISPV, Reus, Spain
Josep Ribalta Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Rovira i Virgili University, IISPV, Reus, Spain
Gemma Rojo-Martínez Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga/Universidad de Málaga, Instituto de Investigación Biomedica de Málaga-IBIMA, Málaga, Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain

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Long-term exposure to PM1 is associated with increased prevalence of metabolic diseases: evidence from a nationwide study in 123 Chinese cities

Exposure to particulate matter (PM) has been linked to metabolic diseases. However, the effects of PM with an aerodynamic diameter ≤ 1.0 µm (PM1) on metabolic diseases remain unclear. This study is aimed at assessing the associations of PM1 with metabolic disease risk and quantifying the concentration-response (C-R) relationship of PM1 with metabolic disease risk. A national cross-sectional study was conducted, including 12,495 middle-aged and older adults in 123 Chinese cities. The two-year average concentration of PM1 was evaluated using satellite-based spatiotemporal models. Metabolic diseases, including abdominal obesity, diabetes, hypertension, dyslipidemia, and metabolic syndrome, were identified based on physical examination, blood standard biochemistry examination, and self-reported disease histories. Generalized linear models and C-R curves were used to evaluate the associations of PM1 with metabolic diseases. A total of 12,495 participants were included in this study, with a prevalence of 45.73% for abdominal obesity, 20.22% for diabetes, 42.46% for hypertension, 41.01% for dyslipidemia, and 33.78% for metabolic syndrome. The mean ± standard deviation age of participants was 58.79 ± 13.14 years. In addition to dyslipidemia, exposure to PM1 was associated with increased risks of abdominal obesity, diabetes, hypertension, and metabolic syndrome. Each 10 μg/m3 increase in PM1 concentrations was associated with 39% (odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.33, 1.46) increase in abdominal obesity, 18% (OR = 1.18, 95%CI 1.12, 1.25) increase in diabetes, 11% (OR = 1.11, 95%CI 1.06, 1.16) increase in hypertension, and 25% (OR = 1.25, 95%CI 1.19, 1.31) in metabolic syndrome, respectively. C-R curves showed that the OR values of abdominal obesity, diabetes, hypertension, and metabolic syndrome were increased gradually with the increase of PM1 concentrations. Subgroup analysis indicated that exposure to PM1 was associated with increased metabolic disease risks among participants with different lifestyles and found that solid fuel users were more susceptible to PM1 than clean fuel users. This national cross-sectional study indicated that exposure to higher PM1 might increase abdominal obesity, diabetes, hypertension, and metabolic syndrome risk, and solid fuel use might accelerate the adverse effects of PM1 on metabolic syndrome risk. Further longitudinal cohort studies are warranted to establish a causal inference between PM1 exposure and metabolic disease risk.

Association between Air Pollution and Lipid Profiles

Dyslipidemia is a critical factor in the development of atherosclerosis and consequent cardiovascular disease. Numerous pieces of evidence demonstrate the association between air pollution and abnormal blood lipids. Although the results of epidemiological studies on the link between air pollution and blood lipids are unsettled due to different research methods and conditions, most of them corroborate the harmful effects of air pollution on blood lipids. Mechanism studies have revealed that air pollution may affect blood lipids via oxidative stress, inflammation, insulin resistance, mitochondrial dysfunction, and hypothalamic hormone and epigenetic changes. Moreover, there is a risk of metabolic diseases associated with air pollution, including fatty liver disease, diabetes mellitus, and obesity, which are often accompanied by dyslipidemia. Therefore, it is biologically plausible that air pollution affects blood lipids. The overall evidence supports that air pollution has a deleterious effect on blood lipid health. However, further research into susceptibility, indoor air pollution, and gaseous pollutants is required, and the issue of assessing the effects of mixtures of air pollutants remains an obstacle for the future.

Identifying the Relationship between PM2.5 and Hyperlipidemia Using Mendelian Randomization, RNA-seq Data and Model Mice Subjected to Air Pollution

Air pollution is an important public health problem that endangers human health. However, the casual association and pathogenesis between particles < 2.5 μm (PM2.5) and hyperlipidemia remains incompletely unknown. Mendelian randomization (MR) and transcriptomic data analysis were performed, and an air pollution model using mice was constructed to investigate the association between PM2.5 and hyperlipidemia. MR analysis demonstrated that PM2.5 is associated with hyperlipidemia and the triglyceride (TG) level in the European population (IVW method of hyperlipidemia: OR: 1.0063, 95%CI: 1.0010-1.0118, p = 0.0210; IVW method of TG level: OR: 1.1004, 95%CI: 1.0067-1.2028, p = 0.0350). Mest, Adipoq, Ccl2, and Pcsk9 emerged in the differentially expressed genes of the liver and plasma of PM2.5 model mice, which might mediate atherosclerosis accelerated by PM2.5. The studied animal model shows that the Paigen Diet (PD)-fed male LDLR-/- mice had higher total cholesterol (TC), TG, and CM/VLDL cholesterol levels than the control group did after 10 times 5 mg/kg PM2.5 intranasal instillation once every three days. Our study revealed that PM2.5 had causality with hyperlipidemia, and PM2.5 might affect liver secretion, which could further regulate atherosclerosis. The lipid profile of PD-fed Familial Hypercholesterolemia (FH) model mice is more likely to be jeopardized by PM2.5 exposure.

Association of Long-term exposure to air pollution and residential greenness with lipid profile: Mediating role of inflammation

Lipidemic effect of air pollutants are still inconsistent and their joint effects are neglected. Meanwhile, identified inflammation pathways in animal have not been applied in epidemiological studies, and beneficial effect of residential greenness remained unclear. Therefore, we used data from typically air-polluted Chinese cities to answer these questions. Particulate matter (PM) with a diameter of ≤ 1 µm (PM₁), PM with a diameter of ≤ 2.5 µm (PM_2.5), PM with a diameter of ≤ 10 µm (PM₁₀), sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) were predicted by space-time extremely randomized trees model. Residential greenness was reflected by Normalized Difference Vegetation Index (NDVI). Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured, and atherogenic coefficient (AC) and TG/HDL-C (TGH) ratio were calculated to indicate lipid metabolism. Generalized additive mixed model and quantile g-computation were respectively conducted to investigate individual and joint lipidemic effect of air pollutants. Covariates including demographical characteristics, living habits, meteorological factors, time trends, and disease information were considered to avoid confounding our results. Complement C3 and high-sensitivity C-reactive protein (hsCRP) were analyzed as potential mediators. Finally, association between NDVI and lipid markers were explored. We found that long-term air pollutants exposure were positively associated with lipid markers. Complement C3 mediated 54.72% (95% CI: 0.30, 63.10) and 72.53% (95% CI: 0.65, 77.61) of the association between PM₁ and TC and LDL-C, respectively. We found some significant associations of lipid markers with NDVI_1000 m rather than NDVI_500 m. BMI, disease status, smoke/drink habits are important effect modifiers. Results are robust in sensitive analysis. Our study indicated that air pollutants exposure may detriment lipid metabolism and inflammation may be the potential triggering pathways, while greenness may exert beneficial effects. This study provided insights for the lipidemic effects of air pollution and greenness.

The protective effect of p-Coumaric acid on hepatic injury caused by particulate matter in the rat and determining the role of long noncoding RNAs MEG3 and HOTAIR

Increasing air pollution is associated with serious human health problems. P-coumaric acid (PC) is a herbal phenolic compound that exhibits beneficial pharmacological potentials. Here, the protective effect of PC on liver injury induced by air pollution was examined. Thirty-two adult male Wistar rats (200-250 g) were divided randomly into four groups (n = 8). The groups were; Control (rats received DMSO and then exposed to clean air), PC (rats received PC and then exposed to clean air), DMSO + Dust (rats received DMSO and then exposed to dust), and PC + Dust (the animals received PC and then exposed to dust). The clean air, DMSO, PC, and dust were administrated 3 days a week for 6 consecutive weeks. The rats were anesthetized and their blood samples and liver sections were taken to conduct molecular, biomedical, and histopathological tests. Dust exposure increased the liver enzymes, bilirubin, triglyceride, cholesterol, and the production of liver malondialdehyde, and decreased in liver total anti-oxidant capacity and serum high-density lipoprotein. It also increased the mRNA expression of inflammatory-related cytokines, decreased the mRNA expression of SIRT-1, decreased the expression levels of miR-20b5p, and MEG3 while increased the expression levels of miR-34a, and HOTAIR. Dust exposure also increased the liver content of three cytokines TNF-α, NF-κB, HMGB-1, and ATG-7 proteins. PC enhanced liver function against adverse effects of dust through recovering almost all the studied variables. Exposure to dust damaged the liver through induction of oxidative stress, inflammation, and autophagy. PC protected the liver against dust-induced cytotoxicity.

Microcystins Exposure Associated with Blood Lipid Profiles and Dyslipidemia: A Cross-Sectional Study in Hunan Province, China

Increasing evidence from experimental research suggests that exposure to microcystins (MCs) may induce lipid metabolism disorder. However, population-based epidemiological studies of the association between MCs exposure and the risk of dyslipidemia are lacking. Therefore, we conducted a population-based cross-sectional study involving 720 participants in Hunan Province, China, and evaluated the effects of MCs on blood lipids. After adjusting the lipid related metals, we used binary logistic regression and multiple linear regression models to examine the associations among serum MCs concentration, the risk of dyslipidemia and blood lipids (triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)). Moreover, the additive model was used to explore the interaction effects on dyslipidemia between MCs and metals. Compared to the lowest quartile of MCs exposure, the risk of dyslipidemia [odds ratios (OR) = 2.27, 95% confidence interval (CI): 1.46, 3.53] and hyperTG (OR = 3.01, 95% CI: 1.79, 5.05) in the highest quartile was significantly increased, and showed dose-response relationships. MCs were positively associated with TG level (percent change, 9.43%; 95% CI: 3.53%, 15.67%) and negatively associated with HDL-C level (percent change, -3.53%; 95% CI: -5.70%, -2.10%). In addition, an additive antagonistic effect of MCs and Zn on dyslipidemia was also reported [relative excess risk due to interaction (RERI) = -1.81 (95% CI: -3.56, -0.05)], and the attributable proportion of the reduced risk of dyslipidemia due to the antagonism of these two exposures was 83% (95% CI: -1.66, -0.005). Our study first indicated that MCs exposure is an independent risk factor for dyslipidemia in a dose-response manner.

Association of solid fuel use with a risk score capturing dementia risk among middle-aged and older adults: A prospective cohort study

OBJECTIVES

Whether household air pollution is associated with dementia risk remains unknown. This study examined the associations between solid fuel use for cooking and heating (the main source of household air pollution) and dementia risk.

METHODS

This analysis included data on 11,352 participants (aged 45+ years) from the 2011 wave of China Health and Retirement Longitudinal Study, with follow-up to 2018. Dementia risk was assessed by a risk score using the Rotterdam Study Basic Dementia Risk Model (BDRM), which was subsequently standardized for analysis. Household fuel types of cooking and heating were categorized as solid (e.g., coal and crop residue) and clean (e.g., central heating and solar). Multivariable analyses were performed using generalized estimating equations. Moreover, we examined the joint associations of solid fuel use for cooking and heating with the BDRM score.

RESULTS

After adjusting for potential confounders, we found an independent and significant association of solid (vs. clean) fuel use for cooking and heating with a higher BDRM score (e.g., β = 0.17 for solid fuel for cooking; 95% confidence interval [CI]: 0.15-0.19). Participants who used solid (vs. clean) fuel for both cooking and heating had the highest BDRM score (β = 0.32; 95% CI: 0.29-0.36). Subgroup analysis suggested stronger associations in participants living in rural areas.

CONCLUSIONS

Solid fuel use for cooking and heating was independently associated with increased dementia risk in Chinese middle-aged and older adults, particularly among those living in rural areas. Our findings call for more efforts to facilitate universal access to clean energy for dementia prevention.

p-Coumaric acid has pure anti-inflammatory characteristics against hepatopathy caused by ischemia-reperfusion in the liver and dust exposure

Objectives

Studies show that chronic injuries like air pollution or acute damage such as hepatic ischemia-reperfusion (IR) cause various cellular pathologies such as oxidative stress, apoptosis, autophagy, and inflammation in hepatocytes. p-Coumaric acid (p-CA) is known as an antioxidant with many therapeutic impacts on inflammatory-related pathologies. In this experiment, we aimed to assess the hepatoprotective effects of p-CA on liver damage induced by dust and IR injury in adult male rats.

Materials and Methods

Forty-eight adult male Wistar rats were divided into 6 groups; Control (CTRL); sham; DMSO+Dust+Laparotomy (LPT); DMSO+Dust+Ischemia-reperfusion (IR); p-CA+Dust+LPT; and p-CA+Dust+IR. Clean air, DMSO, p-CA, and dust were administrated 3 days a week for 6 consecutive weeks. Animals were sacrificed, the blood samples were aspirated and the liver sections were prepared for biochemical and histopathological assessments.

Results

Significantly (P<0.05), the results represented that dust and IR can potentially increase the levels of ALT, AST, direct and total bilirubin, triglyceride, and cholesterol in serum. Also, MDA, TNF-α , NF-κB . HMGB-1 and ATG-7 levels were increased in hepatocytes. Gene expression of Nrf2, HOX-1, IL-6, HOTAIR, and miR-34a showed an incremental trend in the liver tissue. Total antioxidant capacity (TAC) in hepatocytes was decreased following dust exposure and IR induction. Also, miR-20b-5p, MEG3, and SIRT1 in the liver were decreased in dust and dust+IR groups.

Conclusion

p-CA alleviated pathological changes caused by dust exposure and IR injury. p-CA protected hepatic injury induced by dust and IR by inhibition of oxidative injury, inflammation, and autophagy.

Long-term effect of submicronic particulate matter (PM1) and intermodal particulate matter (PM1-2.5) on incident dyslipidemia in China: A nationwide 5-year cohort study

BACKGROUND

There is insufficient evidence of associations between incident dyslipidemia with PM₁ (submicronic particulate matter) and PM_1-2.5 (intermodal particulate matter) in the middle-aged and elderly. We aimed to determine the long-term effects of PM₁ and PM_1-2.5 on incident dyslipidemia respectively.

METHODS

We studied 6976 individuals aged ≥45 from the China Health and Retirement Longitudinal Study from 2013 to 2018. The concentrations of particular matter (PM) for every individual's address were evaluated using a satellite-based spatiotemporal model. Dyslipidemia was evaluated by self-reported. The generalized linear mixed model was applied to quantify the correlations between PM and incident dyslipidemia.

RESULTS

After a 5-year follow-up, 333 (4.77%) participants developed dyslipidemia. Per 10 μg/m³ uptick in four-year average concentrations of PMs (PM₁ and PM_1-2.5) corresponded to 1.11 [95% confidence interval (CI): 1.01-1.23)] and 1.23 (95% CI: 1.06-1.43) fold risks of incident dyslipidemia. Nonlinear exposure-response curves were observed between PM and incident dyslipidemia. The effect size of PM₁ on incident dyslipidemia was slightly higher in males [1.14 (95% CI: 0.98-1.32) vs. 1.04 (95% CI: 0.89-1.21)], the elderly [1.23 (95% CI: 1.04-1.45) vs. 1.03 (95% CI: 0.91-1.17)], people with less than primary school education [1.12 (95% CI: 0.94-1.33) vs. 1.08 (95% CI: 0.94-1.23)], and solid cooking fuel users [1.17 (95% CI: 1.00-1.36) vs. 1.06 (95% CI: 0.93-1.21)], however, the difference was not statistically significant (Z = -0.82, P = 0.413; Z = -1.66, P = 0.097; Z = 0.32, P = 0.752; Z = -0.89, P = 0.372).

CONCLUSIONS

Long-term exposure to PM₁ and PM_1-2.5 were linked with an increased morbidity of dyslipidemia in the middle-aged and elderly population. Males, the elderly, and solid cooking fuel users had higher risk. Further studies would be warranted to establish an accurate reference value of PM to mitigate growing dyslipidemia.

Residential greenness and dyslipidemia risk: Dose-response relations and mediation through BMI and air pollution

BACKGROUND

Evidence on associations of residential greenness with dyslipidemia is limited, particularly regarding dose-response relations and mediation.

OBJECTIVES

To investigate associations between greenness and dyslipidemia, non-linear dose-response relationships and mediators.

METHODS

This cross-sectional study draws on the 2018 Fujian Behavior and Disease Surveillance (FBDS) cohort that used multi-stage stratified random sampling from the general population of Fujian Province, China. Participants with one or more abnormities in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), or low-density lipoprotein cholesterol (LDL-C) were classified as having dyslipidemia. Residential greenness was operationalized as 3-year average of the normalized difference vegetation index (NDVI_500m) and enhanced vegetation index (EVI_500m). A doubly robust approach was used for effect quantification. Dose-response relations were studied with natural cubic splines. Mediation via physical activity (PA), body mass index (BMI), PM_2.5, PM₁₀, SO₂, and NO₂ was also examined.

RESULTS

Data from 43,183 participants were analyzed. Increases in NDVI_500m and EVI_500m residential greenness were associated with decreased dyslipidemia risk and improved blood lipids. Non-linear dose response relationships were discovered. Significant reduction of dyslipidemia risk was observed at levels of EVI_500m > 0.48 and NDVI_500m > 0.65. Joint mediation effects of PA, BMI, PM_2.5, PM₁₀, NO₂, and SO₂ on the associations of NDVI_500m and EVI_500m with dyslipidemia risk were 49.74% and 44.64%, respectively.

CONCLUSIONS

Increased residential exposure to greenness was associated with decreased risk of dyslipidemia. A non-linear dose-response relationship between greenness and dyslipidemia suggests that specific thresholds of greenness need to be reached in order to achieve effects. BMI, PM_2.5, and PM₁₀ partially mediated the association.

Synergism of cell adhesion regulatory genes and instant air pollutants on blood pressure elevation

Accumulating evidence suggests that an instant exposure to particulate matter (PM) may elevate blood pressure (BP), where cell-adhesion regulatory genes may be involved in the interplay. However, few studies to date critically examined their interaction, and it remained unclear whether these genes modified the association. To assess the association between instant PM exposure and BP, and to examine whether single-nucleotide polymorphisms (SNPs) mapped in four cell adhesion regulatory genes modify the relationship, a cross-sectional study was performed, based on the baseline of an ongoing family-based cohort in Beijing, China. A total of 4418 persons from 2089 families in Northern China were included in the analysis. Four tagged SNPs in cell adhesion regulatory genes were selected among ZFHX3, CXCL12, RASGRP1 and MIR146A. A generalized additive model (GAM) with a Gaussian link was adopted to estimate the change in blood pressure after instant PM_2.5 or PM₁₀ exposure. A cross-product term of PM_2.5/PM₁₀ and genotype was incorporated into the GAM model to test for interaction. The study observed that an instant exposure to either PM_2.5 or PM₁₀ was found to be associated with elevated systolic blood pressure (SBP). On average, a 10 μg/m³ increase in instant exposure to PM_2.5 and PM₁₀ concentration corresponded to 0.140% (95% CI: 0.014%-0.265%, P = 0.029) and 0.173% (95% CI: 0.080%-0.266%, P < 0.001) higher SBP. However, diastolic blood pressure (DBP) was not elevated as the PM_2.5 or PM₁₀ concentration increased (P > 0.05). A synergetic interaction on SBP was observed between SNPs in four cell adhesion regulatory genes (rs2910164 in MIR146A, rs2297630 in CXCL12, rs7403531 in RASGRP1, and rs7193343 in ZFHX3) and instant PM_2.5 exposure (P_{for interaction} <0.05). Briefly, as carriers of risk alleles in each of these four genes increased, an enhanced association was found between instant PM_2.5 exposure and SBP.

Systemic inflammation accelerates the adverse effects of air pollution on metabolic syndrome: Findings from the China health and Retirement Longitudinal Study (CHARLS)

Long-term exposure to air pollution and systemic inflammation are associated with increased prevalence of metabolic syndrome (MetS); however, their joint effects in Chinese middle-aged and older adults is unknown. In this cross-sectional study, 11,838 residents aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS) Wave 3 in 2015 were included. MetS was diagnosed using the Joint Interim Societies' definition. C-Reactive Protein (CRP) was assessed to reflect systemic inflammation. Individual exposure to air pollutants (particulate matter with a diameter ≤2.5 μm (PM_2.5) or ≤ 10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO)) was evaluated using satellite-based spatiotemporal models according to participant residence at county-level. Generalized linear models (GLMs) were applied to examine the association between air pollution and MetS, and the modification effects of CRP between air pollution and MetS were estimated using interaction terms of CRP and air pollutants in the GLM models. The prevalence of MetS was 32.37%. The adjusted odd ratio (OR) of MetS was 1.192 (95% confidence interval (CI): 1.116, 1.272), 1.177 (95% CI: 1.103, 1.255), 1.158 (95% CI: 1.072, 1.252), 1.303 (95% CI: 1.211,1.403), 1.107 (95% CI: 1.046, 1.171) and 1.156 (95% CI:1.083, 1.234), per inter-quartile range increase in PM_2.5 (24.04 μg/m³), PM₁₀ (39.00 μg/m³), SO₂ (19.05 μg/m³), NO₂ (11.28 μg/m³), O₃ (9.51 μg/m³) and CO (0.46 mg/m³), respectively. CRP was also associated with increased prevalence of MetS (OR = 1.049, 95% CI: 1.035, 1.064; per 1.90 mg/L increase in CRP). Interaction analysis suggested that high CRP levels enhanced the association between air pollution exposure and MetS. Long-term exposure to air pollution is associated with increased prevalence of MetS, which might be enhanced by systemic inflammation. Given the rapidly aging society and heavy burden of MetS, measures should be taken to improve air quality and reduce systemic inflammation.

Associations of residential greenness with obesity and BMI level among Chinese rural population: findings from the Henan Rural Cohort Study

In recent years, increasing evidence supports the notion that obesity risk is affected by residential greenness. However, limited studies have been established in low- and middle-income countries, especially in China. The study aimed to evaluate the associations of residential greenness with obesity and body mass index (BMI) level in Chinese rural-dwelling adults. A total of 39,259 adults from the Henan Rural Cohort Study (HRCS) were included in the analyses. According to the guideline for prevention and control of overweight and obesity in Chinese adults, obesity was defined as BMI ≥ 28 kg/m². Residential greenness was measured by satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Generalized linear mixed models were used to study the associations between exposure to residential greenness with obesity and BMI level. Higher residential greenness was significantly correlated with lower odds of obesity and BMI level. For example, in the full-adjusted analyses, an interquartile range (IQR) increase in EVI_500-m was linked with reduced odds of obesity (OR = 0.77, 95%CI 0.72-0.82) and BMI level (β =  - 0.41 kg/m², 95%CI - 0.48 to - 0.33 kg/m²). Mediation analyses showed air pollution and physical activity could be potential mediators in these associations. Besides, we found that the association of NDVI_500-m with BMI was stronger in females and low-income populations. Higher residential greenness was associated with a lower prevalence of obesity and BMI level, particularly among females and the low-income population. These relationships were partially mediated by reducing air pollution and increasing physical activity.

Revisiting the atmospheric particles: Connecting lines and changing paradigms

Historically, the atmospheric particles constitute the most primitive and recent class of air pollutants. The science of atmospheric particles erupted more than a century ago covering more than four decades of size, with past few years experiencing major advancements on both theoretic and data-based observational grounds. More recently, the plausible recognition between particulate matter (PM) and the diffusion of the COVID-19 pandemic has led to the accretion of interest in particle science. With motivation from diverse particle research interests, this paper is an 'old engineer's survey' beginning with the evolution of atmospheric particles and identifies along the way many of the global instances signaling the 'size concept' of PM. A theme that runs through the narrative is a 'previously known' generational evolution of particle science to the 'newly procured' portfolio of knowledge, with important gains on the application of unmet concepts and future approaches to PM exposure and epidemiological research.

Healthier Lifestyles Attenuated Association of Single or Mixture Exposure to Air Pollutants with Cardiometabolic Risk in Rural Chinese Adults

There is little research on how long-term exposure to independent and multiple air pollutants changes cardiometabolic risk in adults. In addition, previous studies focused on only the effect of one or two lifestyles on cardiometabolic risk. The evidence on the interactive effects of the lifestyle score and exposure to independent and mixtures of air pollutants on cardiometabolic risk is lacking. A total of 33,638 rural residents were included in the cross-sectional study. The three-year average concentrations of air pollutants for participants were predicted by using a satellite-based prediction. The air pollution score was created to assess the combined exposure of four air pollutants (PM1, PM2.5, PM10, and NO2). A gender−age-specific cardiometabolic risk score was calculated. Multivariable-adjusted linear regression and quantile g-computation were used to investigate the associations between air pollutants and cardiometabolic risk. Interaction plots were applied to describe the interactive effects of air pollution and the healthy lifestyle score on cardiometabolic risk. Per interquartile range (IQR) unit increases in PM1, PM2.5, PM10, or NO2 were associated with 0.162 (95% CI: 0.091, 0.233), 0.473 (95% CI: 0.388, 0.559), 0.718 (95% CI: 0.627, 0.810), and 0.795 (95% CI: 0.691, 0.898) unit increases in cardiometabolic risk score (all p < 0.05), respectively. A 0.854 (95% CI: 0.768, 0.940) unit increase in cardiometabolic risk was associated with each IQR increase in air pollution score. Furthermore, the strengths of associations of PM1, PM2.5, PM10, NO2, and the air pollution score on cardiometabolic risk score were attenuated with the healthy lifestyle score increase. In addition, there was no statistical significance after the lifestyle score equal to four scores for the effect of PM1 on the cardiometabolic risk score. In conclusions, individual or joint air pollutants were associated with an increased cardiometabolic risk. Improving the healthy lifestyle may be an effective method to improve cardiometabolic health in highly polluted rural regions.

Associations of long-term exposure to ambient ozone with hypertension, blood pressure, and the mediation effects of body mass index: A national cross-sectional study of middle-aged and older adults in China

BACKGROUND

The associations between long-term exposure to ozone (O₃) and respiratory diseases are well established. However, its association with cardiovascular disease (CVD) remains controversial. In this study, we examined the associations between O₃ and the prevalence of hypertension and blood pressure, and the mediation effects of body mass index (BMI) in Chinese middle-aged and older adults.

METHODS

In this national cross-sectional study, we estimated the O₃ exposure of 12,028 middle-aged and older adults from 126 county-level cities in China, using satellite-based spatiotemporal models. Generalized linear mixed models were used to evaluate the associations of long-term exposure to O₃ with hypertension and blood pressure, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure (PP). Mediation effect models were applied to examine the mediation effects of BMI among O₃-induced hypertension and elevated blood pressure.

RESULTS

Each 10 μg/m³ increase in O₃ concentration was significantly associated with an increase of 13.7% (95% confidence interval (CI): 4.8%, 23.3%) in the prevalence of hypertension, an increase of 1.128 mmHg (95% CI: 0.248, 2.005), 0.679 mmHg (95% CI: 0.059, 1.298), 0.820 mmHg (95%CI: 0.245, 1.358) in SBP, DBP, and MAP, respectively. Mediation effect models showed that BMI played 40.08%, 37.25%, 39.95%, and 33.51% mediation roles in the effects of long-term exposure to O₃ on hypertension, SBP, DBP, and MAP, respectively.

CONCLUSIONS

Long-term exposure to O₃ can increase the prevalence of hypertension and blood pressure levels of middle-aged and older adults, and an increase of BMI would be an important modification effect for O₃-induced hypertension and blood pressure increase.

Effects of long-term exposure to PM2.5 and chemical constituents on blood lipids in an essential hypertensive population: A multi-city study in China

Previous studies on the effects of fine particulate matter (PM_2.5) and chemical constituents on lipid disorder among hypertension populations, particularly in China, are very limited. We aimed to examine the effects of long-term exposure to PM_2.5 and chemical constituents on dyslipidemias in China. Finally, we included 34,841 participants with essential hypertension from 19 regions in China during 2010-2011. Data were modeled using the generalized additive mixed model. We found that PM_2.5 and chemical constituents exposure were positively associated with the increased risk of dyslipidemias and increased levels of total cholesterol (TC) and triglyceride (TG). The odds ratio for hypercholesterolemia was 1.356 [95% confidence interval (CI): 1.246, 1.477] for PM_2.5, and the strongest association with PM_2.5 constituents was found for nitrate. Each 10 μg/m³ increase in PM_2.5 showed a significant increase of TC by 2.60% (95% CI: 2.03, 3.17) and TG by 2.91% (95% CI: 1.60, 4.24), respectively. Meanwhile, an interquartile range increase in nitrate, ammonium and organic matter had stronger associations with TC and TG parameters than black carbon, sulfate, and mineral dust. Our findings may contribute to a better understanding of the chronic effects of PM_2.5 and chemical constituents on lipid disorder in an essential hypertensive population.

Traffic-related air pollution, biomarkers of metabolic dysfunction, oxidative stress, and CC16 in children

BACKGROUND

Previous research has revealed links between air pollution exposure and metabolic syndrome in adults; however, these associations are less explored in children.

OBJECTIVE

This study aims to investigate the association between traffic-related air pollutants (TRAP) and biomarkers of metabolic dysregulation, oxidative stress, and lung epithelial damage in children.

METHODS

We conducted cross-sectional analyses in a sample of predominantly Latinx, low-income children (n = 218) to examine associations between air pollutants (nitrogen dioxide (NO₂), nitrogen oxides (NO_x), elemental carbon, polycyclic aromatic hydrocarbons, carbon monoxide (CO), fine particulates (PM_2.5)) and biomarkers of metabolic function (high-density lipoprotein (HDL), hemoglobin A1c (HbA1c), oxidative stress (8-isoprostane), and lung epithelial damage (club cell protein 16 (CC16)).

RESULTS

HDL cholesterol showed an inverse association with NO₂ and NO_x, with the strongest relationship between HDL and 3-month exposure to NO₂ (-15.4 mg/dL per IQR increase in 3-month NO₂, 95% CI = -27.4, -3.4). 8-isoprostane showed a consistent pattern of increasing values with 1-day and 1-week exposure across all pollutants. Non-significant increases in % HbA1c were found during 1-month time frames and decreasing CC16 in 3-month exposure time frames.

CONCLUSION

Our results suggest that TRAP is significantly associated with decreased HDL cholesterol in longer-term time frames and elevated 8-isoprostane in shorter-term time frames. TRAP could have the potential to influence lifelong metabolic patterns, through metabolic effects in childhood.

Long-term PM0.1 exposure and human blood lipid metabolism: New insight from the 33-community study in China

Ambient particles with aerodynamic diameter <0.1 μm (PM_0.1) have been suggested to have significant health impact. However, studies on the association between long-term PM_0.1 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 PM_0.1 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 PM_0.1 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 PM_0.1 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 PM_0.1 exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

Abnormal fasting blood glucose enhances the risk of long-term exposure to air pollution on dyslipidemia: A cross-sectional study

Both long-term exposure to air pollution and abnormal fasting blood glucose (FBG) are linked to dyslipidemia prevalence. However, the joint role of air pollution and FBG on dyslipidemia remains unknown clearly. In this study, we aimed to test whether abnormal FBG could enhance the risks of long-term exposure to air pollutants on dyslipidemia in general Chinese adult population. The present study recruited 8917 participants from 4 cities in Hebei province, China. Participants' individual exposure to air pollutants was evaluated by the Empirical Bayesian Kriging statistical model in ArcGIS10.2 geographic information system. Dyslipidemia was defined according to Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults. Subjects were grouped into normal, prediabetes, diabetes according to FBG level. Generalized linear models were applied to analyze the interaction of air pollutants and FBG on dyslipidemia prevalence. The prevalence of dyslipidemia was 43.83% in our investigation. After adjusting all covariates, we found the risk of four air pollutants (PM_2.5, PM₁₀, NO₂, SO₂) on dyslipidemia prevalence was stronger as higher FBG level, and the adjusted odd ratio of interaction (OR_inter (95% CI)) between PM_2.5, PM₁₀, NO₂, SO₂ and FBG levels on dyslipidemia was 1.171 (1.162, 1.189), 1.119 (1.111, 1.127), 1.124 (1.115, 1.130), 1.107 (1.098, 1.115), respectively. Stratified analyses indicated the modifying effects of FBG on the association of air pollution with dyslipidemia were stronger among male, less than 65 years old, overweight/obesity (all P_inter<0.1). Our study concluded that high FBG levels strengthened the risk of long-term exposure to air pollution on dyslipidemia, especially more noticeable in male, less than 65 years old, overweight.

The Relationship between Exposure to Airborne Particulate and DNA Adducts in Blood Cells in an Urban Population of Subjects with an Unhealthy Body Mass Index

Bulky DNA adducts are a combined sign of aromatic chemical exposure, as well as an individual's ability to metabolically activate carcinogens and repair DNA damage. The present study aims to investigate the association between PM exposure and DNA adducts in blood cells, in a population of 196 adults with an unhealthy BMI (≥25). For each subject, a DNA sample was obtained for quantification of DNA adducts by sensitive³²P post-labelling methods. Individual PM₁₀ exposure was derived from daily mean concentrations measured by single monitors in the study area and then assigned to each subject by calculating the mean of the 30 days (short-term exposure), and of the 365 (long-term exposure) preceding enrolment. Multivariable linear regression models were used to study the association between PM₁₀ and DNA adducts. The majority of analysed samples had bulky DNA adducts, with an average value of 3.7 ± 1.6 (mean ± SD). Overall, the findings of the linear univariate and multiple linear regression showed an inverse association between long-term PM₁₀ exposure and adduct levels; this unexpected result might be since the population consists of subjects with an unhealthy BMI, which might show an atypical reaction to airborne urban pollutants; a hermetic response which happens when small amounts of pollutants are present. Pollutants can linger for a long time in the adipose tissue of obese persons, contributing to an increase in oxidative DNA damage, inflammation, and thrombosis when exposure is sustained.

Acute and lag effects of ambient fine particulate matter on the incidence of dyslipidemia in Chengdu, China: A time-series study

High levels of ambient fine particulate matter (PM_2.5) might increase the risk of death due to cardiovascular diseases (CVDs). As a critical risk factor for CVDs, dyslipidemia can cause CVDs or exacerbate pre-existing ones. This study aimed to investigate whether a short-time exposure to PM_2.5 leads to dyslipidemia (HyperTC, HyperLDL-C, HyperTG and HypoHDL-C) in adults. The serum lipid data were provided by the Sichuan Provincial People's Hospital Medical Examination Center. We included 309,654 subjects aged 18-79 between May 10, 2015, and May 10, 2017. An advanced distributed lag nonlinear model (DLNM) was applied to investigate the acute and lag effects of ambient PM_2.5 on the risk of dyslipidemia. This study was also stratified by sex, age, BMI and season to examine potential effect modification. We observed that the associations between an interquartile increase in PM_2.5 (43 μg/m³) and dyslipidemia were [relative risk (RR); 95% confidence interval (CI)]: 1.042 (1.013, 1.071) for HyperLDL-C and 1.027 (1.006, 1.049) for HyperTC at lag0 day. The lag effects were found at lag6 day for HyperLDL-C, in lag4-6 days for HyperTC and lag4-7 days for HyperTG. Short-term exposure to ambient PM_2.5 was related to dyslipidemia and the effect modification was observed in the subgroup analysis. The female and normal-weight populations were more susceptible to the risks of PM_2.5 on HyperLDL-C and HyperTC.

Long-term exposure to air pollution and the blood lipid levels of healthy young men

BACKGROUND

There is insufficient evidence of an association between long-term exposure to air pollution and changes in blood lipid levels, and assessments may be influenced by residual confounding factors, such as socioeconomic status.

OBJECTIVES

To investigate the associations between long-term exposure to air pollution and blood lipid profiles while controlling for the risk of residual confounding factors.

METHODS

We conducted a study involving conscripted Korean soldiers to assess the associations between air pollution and blood lipid levels. The soldiers, who were randomly distributed among military units throughout the country, led homogenous lives and were subjected to health checkups 8-12 months post-enlistment. We analyzed data pertaining to those who enlisted and underwent health checkups in 2019 (n = 12,778) using linear mixed models. Additionally, we evaluated quantile-specific associations using quantile regression models. We also assessed interactions based on body mass index (BMI) at the time of enlistment (≥25.0 vs. < 25.0 kg/m²).

RESULTS

The linear mixed models revealed that a 10-µg/m³ increase in fine particulate matter ≤ 2.5 μm (PM_2.5) decreased high-density lipoprotein cholesterol (HDL-C) levels by -0.66% (95% confidence interval [CI]: -1.21, -0.10), and a 10-ppb increase in nitrogen dioxide (NO₂) increased total cholesterol (TC) levels by 1.04% (95% CI: 0.24, 1.84). In the quantile regression models, associations were also found at specific deciles. PM_2.5 exposure contributed to higher TC, NO₂ resulted in higher triglycerides and lower HDL-C, and ozone (O₃) led to lower HDL-C. The association between O₃ and TC differed according to BMI (p-value for interaction = 0.03); among those with a BMI ≥ 25.0 kg/m², a 10-ppb increase in O₃ increased TC by 1.09% (95% CI: 0.20, 1.09).

DISCUSSION

These results shed new light on the importance of controlling air pollution, which can contribute to abnormal blood lipid levels, an independent risk factor for cardiovascular disease.

Association of household solid fuel use and long-term exposure to PM2.5 with arthritis in middle-aged and older population in China: A cohort study

Air pollutants are common modifiable risk factors for arthritis. To explore the longitudinal effects of air pollution on arthritis based on a cohort study in middle-aged and elder people of China. Data was obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. A total of 7449 participants aged 45 years and older were involved in our study. The generalized linear mixed models were conducted to examine the separate and joint effects of household air pollution and outdoor air pollution on arthritis, respectively. We found a strong significant association between air pollution and arthritis incidence. Individuals cooking primarily with solid fuel were more likely in higher risk of arthritis compared with cleaner fuel (OR= 1.15; 95% CI: 1.08-1.23). The group-based trajectory model identified four trajectory groups, compared with group "High-Decreasing rapidly", adjusted ORs of incident arthritis for group "Middle-Decreasing moderately", "Low-Decreasing slowly" and "Low-Stably" were 1.36 (95% CI, 1.03-1.79), 1.36 (95% CI, 1.01-1.83) and 1.81 (95% CI, 1.30-2.52), respectively. These associations were generally higher in participants younger than 65 years. In addition, solid fuel use and PM2.5 exposure had additive and multiplicative effects on arthritis. The results suggested that solid fuel use and long-term PM2.5 exposure were associated with a higher incidence of arthritis. Therefore, it is necessary to restrict solid fuel use to reduce household air pollution and make stronger environmental protection policies to reduce PM2.5 concentration.

Joint effect of multiple air pollutants on lipid profiles in obese and normal-weight young adults: The key role of ozone

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 PM_2.5, 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.

Is residential greenness associated with dyslipidemia and lipid levels in Chinese rural-dwelling adults? The Henan rural cohort study

Scarce epidemiologic research examined the associations between residential greenness and dyslipidemia or lipid levels in low/middle-income countries. Baseline statistics (2015-2017) of 39,259 rural-dwelling adults were obtained from a Chinese longitudinal study. The blood lipid level was measured utilizing an enzymatic assay method. According to the 2016 Chinese guidelines on dyslipidemia (revision), patients with dyslipidemia were defined. Participants' exposure to residential greenness was characterized by the satellite-based normalized difference vegetation index (NDVI). Mixed effects logistic regression and mixed effects linear regression were performed to assess the associations of residential greenness with dyslipidemia and lipid levels. The median (interquartile range, IQR) of 3-year average NDVI_1000-m was 0.521 (0.089) units. Each IQR increase in NDVI_1000-m was significantly linked with increased odds of hyperbetalipoproteinemia (OR = 1.33, 95%CI 1.21-1.46). The same increment in NDVI_1000-m was associated with lower total cholesterol (TC) levels and increased low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels. For instance, the %changes in HDL-C levels was 0.71% (95%CI 0.17%-1.26%). The above relationships were partially mediated by reducing air pollution and lowering body mass index (BMI). Interaction effect analysis observed the greenness-lipid association was stronger in males than females (i.e., NDVI_1000-m-TC association). Long-term exposure to residential greenness was associated with odds of dyslipidemia and lipid levels in Chinese rural-dwelling adults, particularly among males. Considering the cross-sectional study design, more longitudinal studies are needed to identify the causal associations.

The Protective Effect of Topical Spermidine on Dry Eye Disease with Retinal Damage Induced by Diesel Particulate Matter2.5

Air pollutants, especially ambient fine particulate matter2.5, may contribute to various ocular surface disorders, including dry eye disease, keratitis and conjunctivitis. A natural polyamine spermidine has a protective effect on the retina and optic nerve; however, no study has been conducted on the application of spermidine in particulate matter2.5-induced dry eye disease. In the present study, we investigated the effect of spermidine eye drops in topically exposed particulate matter2.5-induced dry eye models of Sprague-Dawley rats, by hematological, biochemical and histological evaluation. Spermidine eye drops attenuated the particulate matter2.5 exposure-induced reduction of tear secretion and corneal epithelial damage. Furthermore, spermidine protected against conjunctival goblet cell loss and retinal ganglion cell loss induced by particulate matter2.5. Additionally, spermidine markedly prevented particulate matter2.5-induced infiltration of cluster of differentiation3⁺ and cluster of differentiation4⁺ T lymphocytes and F4/80⁺ macrophages on lacrimal gland. Moreover, over expression of pro-inflammatory cytokines, including tumor necrosis factor-α, interleukin-6 and interleukin-17 in the lacrimal gland and cornea. Meanwhile, the levels of serum total cholesterol and low-density lipoprotein cholesterol were markedly increased by topical exposure to particulate matter2.5, but this change in the lipid profile was decreased by spermidine. Taken together, spermidine may have protective effects against particulate matter2.5-induced dry eye symptoms via stabilization of the tear film and suppression of inflammation and may in part contribute to improving retinal function and lipid metabolism disorder.

The Protective Effect of Oral Application of Corni Fructus on the Disorders of the Cornea, Conjunctiva, Lacrimal Gland and Retina by Topical Particulate Matter 2.5

Particulate matter 2.5 (PM_2.5) may aggravate dry eye disease (DED). Corni Fructus (CF), which is fruit of Cornus officinalis Sieb. et Zucc., has been reported to have various beneficial pharmacological effects, whereas the effect of CF on the eye is still unknown. Therefore, in this study, we investigated the effect of oral administration of water extract of CF (CFW) on the eye, hematology, and biochemistry in a DED model induced by topical exposure to PM_2.5. Furthermore, the efficacy of CFW compared with cyclosporine (CsA), an anti-inflammatory agent, and lutein, the posterior eye-protective agent. Sprague-Dawley rats were topically administered 5 mg/mL PM_2.5 in both eyes four times daily for 14 days. During the same period, CFW (200 mg/kg and 400 mg/kg) and lutein (4.1 mg/kg) were orally administered once a day. All eyes of rats in the 0.05% cyclosporine A (CsA)-treated group were topically exposed to 20 μL of CsA, twice daily for 14 days. Oral administration of CFW attenuated the PM_2.5-induced reduction of tear secretion and corneal epithelial damage. In addition, CFW protected against goblet cell loss in conjunctiva and overexpression of inflammatory factors in the lacrimal gland following topical exposure to PM_2.5. Furthermore, CFW markedly prevented PM_2.5-induced ganglion cell loss and recovered the thickness of inner plexiform layer. Meanwhile, CFW treatment decreased the levels of total cholesterol and low-density lipoprotein cholesterol in serum induced by PM_2.5. Importantly, the efficacy of CFW was superior or similar to that of CsA and lutein. Taken together, oral administration of CFW may have protective effects against PM_2.5-induced DED symptoms via stabilization of the tear film and suppression of inflammation. Furthermore, CFW may in part contribute to improving retinal function and lipid metabolism disorder.

Particulate matter air pollutants and cardiovascular disease: Strategies for intervention

Air pollution is consistently linked with elevations in cardiovascular disease (CVD) and CVD-related mortality. Particulate matter (PM) is a critical factor in air pollution-associated CVD. PM forms in the air during the combustion of fuels as solid particles and liquid droplets and the sources of airborne PM range from dust and dirt to soot and smoke. The health impacts of PM inhalation are well documented. In the US, where CVD is already the leading cause of death, it is estimated that PM2.5 (PM < 2.5 μm in size) is responsible for nearly 200,000 premature deaths annually. Despite the public health data, definitive mechanisms underlying PM-associated CVD are elusive. However, evidence to-date implicates mechanisms involving oxidative stress, inflammation, metabolic dysfunction and dyslipidemia, contributing to vascular dysfunction and atherosclerosis, along with autonomic dysfunction and hypertension. For the benefit of susceptible individuals and individuals who live in areas where PM levels exceed the National Ambient Air Quality Standard, interventional strategies for mitigating PM-associated CVD are necessary. This review will highlight current state of knowledge with respect to mechanisms for PM-dependent CVD. Based upon these mechanisms, strategies for intervention will be outlined. Citing data from animal models and human subjects, these highlighted strategies include: 1) antioxidants, such as vitamins E and C, carnosine, sulforaphane and resveratrol, to reduce oxidative stress and systemic inflammation; 2) omega-3 fatty acids, to inhibit inflammation and autonomic dysfunction; 3) statins, to decrease cholesterol accumulation and inflammation; 4) melatonin, to regulate the immune-pineal axis and 5) metformin, to address PM-associated metabolic dysfunction. Each of these will be discussed with respect to its potential role in limiting PM-associated CVD.

Association of long-term exposure to PM2.5 with blood lipids in the Chinese population: Findings from a longitudinal quasi-experiment

BACKGROUND

Although epidemiological studies on the effect of chronic fine particulate matter (PM_2.5) exposure on lipid disorders have been conducted, it is unclear if improved air quality is associated with beneficial changes in the blood lipid profile. In China, clean air actions introduced in 2013 have rapidly reduced the concentration of ambient PM_2.5.

METHODS

We conducted a change-by-change study, based on two waves (2011 and 2015) of a national survey of the same 5111 Chinese adults before and after implementation of the clean air actions. Long-term PM_2.5 exposure was assessed using a state-of-the-art estimator at the city level. Based on the within-individual differences between the two waves, we associated PM_2.5 changes with the variations of four lipid biomarkers-triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C)-using a mixed-effects regression model. The robustness and homogeneity of the association were tested via sensitivity analyses.

RESULTS

For each 10 μg/m³ reduction in PM_2.5, LDL-C, and TC decreased by 2.71 (95% confidence interval [CI] 0.10-5.32) and 4.16 (95% CI 1.24-7.08)mg/dL, respectively. There was no significant association with HDL-C or TG. The results were robust among models adjusted for different covariates. PM_2.5 was a significant risk factor for dyslipidemia with an adjusted relative risk of 1.21 (95% CI 1.09-1.34). The association between PM_2.5 and LDL-C was stronger in the elderly or adults who did not take medications.

CONCLUSIONS

The results suggest that PM_2.5 exert a cardiotoxic effect by increasing the risk of lipid disorders. Improvement of air quality could prevent dyslipidemia by reducing LDL-C and TC levels. Clean air policies should be implemented as public health measures in countries with aging societies, especially developing ones with a high air pollution burden.

Associations of Particulate Matter Sizes and Chemical Constituents with Blood Lipids: A Panel Study in Guangzhou, China

Existing evidence is scarce concerning the various effects of different PM sizes and chemical constituents on blood lipids. A panel study that involved 88 healthy college students with five repeated measurements (440 blood samples in total) was performed. We measured mass concentrations of particulate matter with diameters ≤ 2.5 μm (PM_2.5), ≤1.0 μm (PM_1.0), and ≤0.5 μm (PM_0.5) as well as number concentrations of particulate matter with diameters ≤ 0.2 μm (PN_0.2) and ≤0.1 μm (PN_0.1). We applied linear mixed-effect models to assess the associations between short-term exposure to different PM size fractions and PM_2.5 constituents and seven lipid metrics. We found significant associations of greater concentrations of PM in different size fractions within 5 days before blood collection with lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A (ApoA1) levels, higher apolipoprotein B (ApoB) levels, and lower ApoA1/ApoB ratios. Among the PM_2.5 constituents, we observed that higher concentrations of tin and lead were significantly associated with decreased HDL-C levels, and higher concentrations of nickel were associated with higher HDL-C levels. Our results suggest that short-term exposure to PM in different sizes was deleteriously associated with blood lipids. Some constituents, especially metals, might be the major contributors to the detrimental effects.

The comparison of AOD-based and non-AOD prediction models for daily PM2.5 estimation in Guangdong province, China with poor AOD coverage

The large amount of missing values has challenged the application of satellite-retrieved aerosol optical depth (AOD) in mapping surface PM_2.5 concentrations. In this study, we developed a non-AOD random forest model to estimate daily concentrations of PM_2.5 in Guangdong Province, China, where more than 80% of AOD data were missing. The predictive ability of the non-AOD model was compared with that of a AOD-based model. Daily ground-based measurements of PM_2.5 were obtained from 148 ground-monitoring sites in Guangdong with a 60 km rectangle buffer from January 2016 to December 2018. Daily MODIS MAIAC AOD were downloaded from NASA at a resolution of approximately 1 km. Two random forest models were developed to predict ground-level PM_2.5 with one included AOD as a predictor and the other one without AOD. The two random forest models were developed using the same dataset and their predictive abilities were compared. The results of 10-fold cross validation (CV) showed that the non-AOD and AOD-based random forest models yielded similar performance. The CV R² (RMSE) for the non-AOD model in 2016-2018 were 0.82 (8.4 μg/m³), 0.81 (9.5 μg/m³) and 0.78 (9.4 μg/m³), and those for AOD-based model were 0.83 (8.2 μg/m³), 0.82 (9.2 μg/m³) and 0.80 (9.0 μg/m³), respectively. Higher consistency of estimated PM_2.5 were observed in areas close to monitoring sites than those far away from sites, and in southern coastal than northern areas. As the non-AOD random forest model is not affected by AOD missingness, it can be used for epidemiological studies to estimate individual-level exposure to PM_2.5 at a high resolution without spatial or temporal gaps.

Exposure to ambient air pollution and blood lipids in children and adolescents: A national population based study in China

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 (PM_2.5), ≤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, PM_2.5, 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, PM_2.5, 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, PM_2.5, PM₁₀, and NO₂ exposures were positively associated with TC levels and risk of hypercholesterolemia in children and adolescents.