Ambient air pollution and lipid profile: Systematic review and meta-analysis

The modification effect of fasting blood glucose level on the associations between short-term ambient air pollution and blood lipids

The association between short-term ambient air pollution (AAP) exposure and blood lipids is inconsistent across populations. This study aimed to investigate the modifying effects of fasting blood glucose (FBG) levels on the associations between short-term AAP exposure  and blood lipids in 110,637 male participants from Beijing, China. The results showed that FBG modified the association between short-term AAP exposure and blood lipids, especially low-density lipoprotein cholesterol (LDL-C). In the hyperglycemia group, a 10-μg/m3 increase in particles with diameters ≤ 2.5 μm (PM2.5), particles with diameters ≤ 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), or a 1-mg/m3 increase in carbon monoxide (CO) was associated with a 0.454%, 0.305%, 1.507%, 0.872%, or 3.961% increase in LDL-C, respectively. In the nonhyperglycemic group, short-term increases in air pollutants were even associated with small decreases in LDL-C. The findings demonstrate that lipids in hyperglycemic individuals are more vulnerable to short-term AAP exposure than those in normal populations.

Relationship between exposure to fine particulate matter and cardiovascular risk factors and the modifying effect of socioeconomic status: a cross-sectional study in Beijing, China

Accumulating research suggested that long-term exposure to fine particulate matter (PM2.5) is related to cardiovascular disease (CVD). However, evidence regarding the relationship between PM2.5 and CVD risk factors remains inconsistent. We hypothesized that this association may be partially modified by socioeconomic status (SES). To investigate the relationships and to test the modifying effect of SES, we included baseline data for 21,018 adults from September 2017 to May 2018. PM2.5 concentrations were determined by employing an amalgamation of linear measurements obtained from monitoring stations located near the participants' residential and workplace addresses. We assessed SES across several domains, including income, education, and occupation levels, as well as through a composite SES index. The results indicated that for every 10 μg/m3 increase in PM2.5 exposure, the risk of hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and hyperhomocysteinemia (HHcy) increased by 7.7% [Odds ratio (OR) = 1.077, 95% Confidence Interval (CI) = 1.011, 1.146], 19.6% (OR = 1.196, 95% CI = 1.091, 1.312), 4.2% (OR = 1.042, 95% CI = 1.002, 1.084), and 17.1% (OR = 1.171, 95% CI = 1.133, 1.209), respectively. Compared to the high SES group, those with low SES are more prone to hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and HHcy. Notably, the disparities in SES appear significant in the relationship between PM2.5 exposure and hypercholesterolemia as well as hyperbetalipoproteinemia. But for diabetes and HHcy, the modification effect of SES on PM2.5 shows an inconsistent pattern. In conclusion, the results confirm the association between PM2.5 and cardiovascular risk factors and low SES significantly amplified the adverse PM2.5 effect on dyslipidemia. It is crucial to emphasize a need to improve the socioeconomic inequality among adults in Beijing and contribute to the understanding of the urgency in protecting the health of vulnerable groups.

Association between residential air pollution exposure and cardiovascular risk factors in adults living in northern France

Air pollution is associated with elevated cardiovascular mortality and an increase in cardiovascular risk factors. However, the literature data on associations between air pollution and cardiovascular risk factors are contradictory. To explore the relationship between residential exposure to atmospheric pollutants and cardiovascular risk factors (lipid biomarker and blood pressure levels). We studied a sample of 2339 adult participants in the ELISABET study from the Dunkirk and Lille urban areas of France. The mean annual exposure to atmospheric pollutants (PM10, NO2 and SO2) at the home address was estimated via an air dispersion model. The associations were probed in multivariate linear regression models. The mean NO2 level was 26.05 μg/m3 in Lille and 19.96 µg/m3 in Dunkirk. The mean PM10 level was 27.02 μg/m3 in Lille and 26.53 μg/m3 in Dunkirk. We detected a significant association between exposure to air pollutants and the high-density lipoprotein (HDL) (which is a protective factor against cardiovascular diseases) level: for a 2 µg/m3 increment in PM10, the HDL level decreased by 1.72% (p = 0.0037). None of the associations with other lipid variables or with blood pressure were significant. We didn't find evidence significant associations for most of the risk factors but, long-term exposure of adults to moderate levels of ambient air pollution was associated with a decrement in HDL.

The impact of co-exposure to air and noise pollution on the incidence of metabolic syndrome from a health checkup cohort

Previous studies have found associations between the incidence of metabolic syndrome (MetS) and exposure to air pollution or road traffic noise. However, investigations on environmental co-exposures are limited. This study aimed to investigate the association between co-exposure to air pollution and road traffic noise and MetS and its subcomponents. Participants living in Taipei City who underwent at least two health checkups between 2010 and 2016 were included in the study. Data were sourced from the MJ Health database, a longitudinal, large-scale cohort in Taiwan. The monthly traffic noise exposure (Lden and Lnight) was computed using a dynamic noise map. Monthly fine particulate data at one kilometer resolution were computed from satellite imagery data. Cox proportional hazards regression models with month as the underlying time scale were used to estimate hazard ratios (HRs) for the impact of PM2.5 and road traffic noise exposure on the risk of developing MetS or its subcomponents. Data from 10,773 participants were included. We found significant positive associations between incident MetS and PM2.5 (HR: 1.88; 95% CI 1.67, 2.12), Lden (HR: 1.10; 95% CI 1.06, 1.15), and Lnight (HR: 1.07; 95% CI 1.02, 1.13) in single exposure models. Results further showed significant associations with an elevated risk of incident MetS in co-exposure models, with HRs of 1.91 (95% CI 1.69, 2.16) and 1.11 (95% CI 1.06, 1.16) for co-exposure to PM2.5 and Lden, and 1.90 (95% CI 1.68, 2.14) and 1.08 (95% CI 1.02, 1.13) for co-exposure to PM2.5 and Lnight. The HRs for the co-exposure models were higher than those for models with only a single exposure. This study provides evidence that PM2.5 and noise exposure may elevate the risk of incident MetS and its components in both single and co-exposure models. Therefore, preventive approaches to mitigate the risk of MetS and its subcomponents should consider reducing exposure to PM2.5 and noise pollution.

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.

Associations of low levels of air pollution with cardiometabolic outcomes and the role of diet quality in individuals with obesity

BACKGROUND

Exposure to air pollution is associated with adverse cardiometabolic health effects and increased mortality, even at low concentrations. Some of the biological mechanisms through which air pollution can affect cardiometabolic health overlap with health outcomes associated with diet quality and changes in diet.

OBJECTIVE

The objective of this study is to investigate associations of air pollutants at average concentrations below the World Health Organization, 2021 air quality guidelines with cardiometabolic outcomes. Furthermore, potential interaction between air pollutants and diet quality will be assessed.

METHODS

82 individuals with obesity participated in a combined weight loss and weight loss maintenance study for a total of 33 weeks. A secondary analysis was conducted incorporating air pollution measurements. Data were analysed with linear mixed-effects models.

RESULTS

A total of 17 significant associations were observed for single pollutants with 10 cardiometabolic outcomes, predominantly related to blood lipids, hormones, and glucose regulation. Diet quality, as measured by the Baltic Sea Diet score, did not appear to mediate the association of air pollution with cardiometabolic outcomes, however, diet quality was observed to significantly modify the association of PM2.5 with total cholesterol, and the associations of NO and O3 with ghrelin.

DISCUSSION

These findings suggest that exposure to ambient air pollutants, especially particulate matter, at levels below World Health Organization, 2021 air quality guidelines, were associated with changes in cardiometabolic risk factors. Diet may be a personal-level approach for individuals to modify the impact of exposure to air pollution on cardiometabolic health.

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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Role of metabolic risk factors in the relationship between ambient fine particulate matter and depressive symptoms: Evidence from a longitudinal population study

BACKGROUND

There is growing evidence indicating a connection between fine particulate matter (PM2.5) and depressive symptoms. Metabolic risk factors are critical determinants of depressive symptoms. However, the mediating role of these factors on the association between PM2.5 and depressive symptoms remains elusive. We aimed to investigate whether and to what extent metabolic risk factors mediated the link between long-term PM2.5 exposure and depressive symptoms.

METHODS

This study comprised 7794 individuals aged between 30 and 79 years who participated in two waves of the on-site surveys in the China Multi-Ethnic Cohort. Ambient PM2.5 concentrations were assessed utilizing a random forest method based on satellite data. We employed the Patient Health Questionnaire-9 to assess depressive symptoms at wave 2, and the overall as well as three sub-domain symptom scores (emotional, neurovegetative, and neurocognitive symptoms) were calculated. Three metabolic risk factors, including hypertension, diabetes, and dyslipidemia, were considered. Mediation analyses were conducted to assess the indirect effects of PM2.5 on depressive symptoms through metabolic risk factors.

RESULTS

We found a positive association between chronic exposure to ambient PM2.5 and overall depressive symptoms as well as the three sub-domains. In mediation analyses, metabolic risk factors partially mediated the associations of PM2.5 on depressive symptoms. The natural indirect effects (RR, 95% CI) of PM2.5 on overall, emotional, neurovegetative, and neurocognitive symptoms mediated through metabolic risk factors were 1.004(1.001, 1.007), 1.004 (1.001, 1.008), 1.004 (1.001, 1.007), and 1.003(0.999, 1.007), respectively. Larger indirect effects were found in elderly participants (mediated proportion, 29.3%), females (13.3%), and people who did not consume alcohol (19.6%).

CONCLUSIONS

Metabolic risk factors may act as mediators in the relationship between chronic PM2.5 exposure and depression. Treatment of metabolic risk factors may be an opportunity to reduce the burden of depression caused by long-term exposure to PM2.5.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BACKGROUND

Most studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours.

METHODS

We used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations.

RESULTS

Neighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure.

CONCLUSIONS

Within a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents' cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

Association between ambient air pollution and thyroid hormones levels: A systematic review and meta-analysis

BACKGROUND

Growing studies have focused on the effects of ambient air pollution on thyroid hormones (THs), but the results were controversial. Therefore, a systematic review and meta-analysis was conducted by pooling current evidence on this association.

METHODS

Four databases were searched for studies examining the associations of particulate matter [diameter ≤10 μm (PM10) or ≤2.5 μm (PM2.5)] and gaseous [sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO)] pollutants with THs levels. Random effects models were used to pool the changes in THs levels with increasing air pollutant concentrations. Subgroup analyses were constructed by region, design, sample size, pollutant concentrations, evaluated methods, and potential risk exposure windows.

RESULTS

A total of 14 studies covering 357,226 participants were included in this meta-analysis. The pooled results showed significant associations of exposure to PM2.5, PM10, NO2, SO2, and CO with decreases in free thyroxine (FT4) with percent changes (PC) ranging from -0.593 % to -3.925 %. PM2.5, NO2, and CO were negatively associated with levels of FT4/FT3 (PC: from -0.604 % to -2.975 %). In addition, results showed significant associations of PM2.5 with hypothyroxinemia and high thyroid-stimulating hormone (TSH). Subgroup analyses indicated that PM2.5 and NO2 were significantly associated with FT4 in studies of Chinese, and similar significant findings were found in studies of PM2.5 and FT4/FT3 in areas with higher concentrations of air pollutants and larger samples. PM2.5 exposure in the first trimester was found to be associated with lower FT4 levels in pregnant women.

CONCLUSION

Our findings suggest that exposure to air pollution is associated with changes in THs levels. Enhanced management of highly polluted areas, identification of harmful components and sources of PM, and protection from harmful exposures in early pregnancy may be of great public health importance for the population's thyroid function.

Short-Term Exposure to Nitrogen Dioxide Modifies Genetic Predisposition in Blood Lipid and Fasting Plasma Glucose: A Pedigree-Based Study

(1) Background: Previous studies suggest that exposure to nitrogen dioxide (NO2) has a negative impact on health. But few studies have explored the association between NO2 and blood lipids or fasting plasma glucose (FPG), as well as gene-air pollution interactions. This study aims to fill this knowledge gap based on a pedigree cohort in southern China. (2) Methods: Employing a pedigree-based design, 1563 individuals from 452 families participated in this study. Serum levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), and FPG were measured. We investigated the associations between short-term NO2 exposure and lipid profiles or FPG using linear mixed regression models. The genotype-environment interaction (GenoXE) for each trait was estimated using variance component models. (3) Results: NO2 was inversely associated with HDLC but directly associated with TG and FPG. The results showed that each 1 μg/m3 increase in NO2 on day lag0 corresponded to a 1.926% (95%CI: 1.428-2.421%) decrease in HDLC and a 1.400% (95%CI: 0.341-2.470%) increase in FPG. Moreover, we observed a significant genotype-NO2 interaction with HDLC and FPG. (4) Conclusion: This study highlighted the association between NO2 exposure and blood lipid profiles or FPG. Additionally, our investigation suggested the presence of genotype-NO2 interactions in HDLC and FPG, indicating potential loci-specific interaction effects. These findings have the potential to inform and enhance the interpretation of studies that are focused on specific gene-environment interactions.

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.

Associations between exposure to ambient particulate matter and advanced liver fibrosis in Chinese MAFLD patients

BACKGROUND & AIMS

Liver fibrosis is an important feature in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). This study aimed to explore the association between long-term ambient particulate matter (PM) exposure and advanced liver fibrosis (ALF) in MAFLD participants.

METHODS

A cross-sectional study of 23170 adults recruited from 33 provinces of China from 2010 to 2020. ALF was detected using the nonalcoholic fatty liver disease fibrosis score (NFS). The annual average levels of particulate matter with aerodynamic diameters of ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5) and ≤ 10 µm (PM10) were calculated using validated spatiotemporal models. Generalized additive models were applied to analyze the association between PM and ALF in patients with MAFLD.

RESULTS

One-year exposure to higher levels of all PM was found to increase the risk of ALF, with odds ratios (ORs) of 1.10 (95% CI 1.06-1.14), 1.05 (1.03-1.07), and 1.03(1.02-1.04) for each 10 μg/m3 increase in PM1, PM2.5 and PM10, respectively. With the dissection of the impact of PM1 in PM2.5, PM2.5 in PM10 and PM1 in PM10, we found that PM2.5 had a stronger impact on ALF (both Pinteraction＜0.05) in comparison with PM1 and PM10.

CONCLUSIONS

Long-term exposure to PM is associated with ALF in patients with MAFLD, with PM2.5 playing a dominant role.

Exposure to ambient air pollutants, serum miRNA networks, lipid metabolism, and non-alcoholic fatty liver disease in young adults

BACKGROUND AND AIM

Ambient air pollution (AAP) exposure has been associated with altered blood lipids and liver fat in young adults. MicroRNAs regulate gene expression and may mediate these relationships. This work investigated associations between AAP exposure, serum microRNA networks, lipid profiles, and non-alcoholic fatty liver disease (NAFLD) risk in young adults.

METHODS

Participants were 170 young adults (17-22 years) from the Meta-AIR cohort of the Children's Health Study (CHS). Residential AAP exposure (PM2.5, PM10, NO2, 8-hour maximum O3, redox-weighted oxidative capacity [Oxwt]) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Fasting serum lipids were assayed. Liver fat was imaged by MRI and NAFLD was defined by ≥ 5.5% hepatic fat fraction. Serum microRNAs were measured via NanoString and microRNA networks were constructed by weighted gene correlation network analysis. The first principal component of each network represented its expression profile. Multivariable mixed effects regression models adjusted for sociodemographic, behavioral, and clinical covariates; baseline CHS town code was a random effect. Effects estimates are scaled to one standard deviation of exposure. Mediation analysis explored microRNA profiles as potential mediators of exposure-outcome associations. DIANA-mirPATH identified overrepresented gene pathways targeted by miRNA networks.

RESULTS

Prior-month Oxwt was associated with NAFLD (OR=3.45; p = 0.003) and inversely associated with microRNA Network A (β = -0.016; p = 0.026). Prior-year NO2 was associated with non-HDL-cholesterol (β = 7.13; p = 0.01) and inversely associated with miRNA Network A (β = -0.019; p = 0.022). Network A expression was inversely associated with NAFLD (OR=0.35; p = 0.010) and non-HDL-C (β = -6.94 mg/dL; p = 0.035). Network A members miR-199a/b-3p and miR-130a, which both target fatty acid synthase, mediated 21% of the association between prior-month Oxwt exposure with NAFLD (p = 0.048) and 23.3% of the association between prior-year NO2 exposure and non-HDL-cholesterol (p = 0.026), respectively.

CONCLUSIONS

Exposure to AAP may contribute to adverse lipid profiles and NAFLD risk among young adults via altered expression of microRNA profiles.

Associations of residential greenness and ambient air pollution with overweight and obesity in older adults

OBJECTIVE

This study aimed to examine the impact of greenness and fine particulate matter <2.5 μm (PM2.5 ) on overweight/obesity among older adults in China.

METHODS

A total of 21,355 participants aged ≥65 years were included from the Chinese Longitudinal Healthy Longevity Survey between 2000 and 2018. Normalized difference vegetation index (NDVI) with a radius of 250 m and PM2.5 in a 1 × 1-km grid resolution were calculated around each participant's residence. Cox proportional hazards models were used to estimate the effects of NDVI and PM2.5 on overweight/obesity. Interaction and mediation analyses were conducted to explore combined effects.

RESULTS

The study observed 1895 incident cases of overweight/obesity over 109,566 person-years. For every 0.1-unit increase in NDVI the hazard ratio of overweight/obesity was 0.91 (95% CI: 0.88-0.95), and for every 10-μg/m3 increase in PM2.5 the hazard ratio was 1.11 (95% CI: 1.07-1.14). The effect of NDVI on overweight/obesity was partially mediated by PM2.5 , with a relative mediation proportion of 20.10% (95% CI: 1.63%-38.57%).

CONCLUSIONS

Greenness exposure appears to lower the risk of overweight/obesity in older adults in China, whereas PM2.5 , acting as a mediator, partly mediated this protective effect.

Exposure to ambient air pollution and metabolic kidney diseases: evidence from the Northeast China Biobank

BACKGROUND

At present, there is no epidemiological evidence of the association between metabolic kidney diseases (MKD) and exposure to air pollution.

METHODS

We investigated the association between exposure to long-term air pollution and the risk of developing MKD using samples from the Northeast China Biobank.

RESULTS

Data from 29 191 participants were analyzed. MKD prevalence was 3.23%. Every standard deviation increment in PM2.5 increased the risk of MKD [odds ratio (OR) = 1.37, 95% confidence interval (CI) 1.19-1.58), diabetic kidney disease (DKD) (OR = 2.03, 95% CI 1.52-2.73), hypertensive kidney disease (BKD) (OR = 1.31, 95% CI 1.11-1.56), hyperlipidemic kidney disease (PKD) (OR = 1.39, 95% CI 1.19-1.63) and obese kidney disease (OKD) (OR = 1.34, 95% CI 1.00-1.81). PM10 increased the risk of MKD (OR = 1.42, 95% CI 1.20-1.67), DKD (OR = 1.38, 95% CI 1.03-1.85), BKD (OR = 1.30, 95% CI 1.07-1.58) and PKD (OR = 1.50, 95% CI 1.26-1.80). Sulfur dioxide increased the risk of MKD (OR = 1.57, 95% CI 1.34-1.85), DKD (OR = 1.81, 95% CI 1.36-2.40), BKD (OR = 1.44, 95% CI 1.19-1.74) and PKD (OR = 1.72, 95% CI 1.44-2.04). Ozone decreased the risk of PKD (OR = 0.83, 95% CI 0.70-0.99). Age, ethnicity and air pollution interacted to affect the risk of MKD, BKD and PKD. Associations between air pollution and CKD or metabolic disease were weaker than those with MKD. The association between air pollution and MKD became stronger when compared with participants with non-metabolic disease.

CONCLUSIONS

Air pollution may cause MKD or facilitate the progression from metabolic disease to renal failure.

Environmental factors and incidence of thyroid cancer in the world (1990-2019): an ecological study

Thyroid cancer (TC) is the most common endocrine malignancy. Environmental risk factors such as presence of pollutants in air as well as the combustion of fossil fuels or carbon as a cooking habit in closed environments inside houses affect thyroid hormonal homeostasis and diseases. This study aimed to estimate the association between environmental risk factors and the incidence of thyroid cancer worldwide from 1990 to 2019 including particulate pollutants coming from fossil fuels employed in closed environments. Data on the incidence of thyroid cancer and some environmental risk factors were extracted from the Global Cancer Observatory (GLOBOCAN) for 204 countries and territories from 1990 to 2019. Pearson's correlation coefficient was used to determine the correlation between the thyroid cancer incidence and environmental risk factors. Finally, a generalized additive model was fitted for modeling. R 3.5.0 was used for analysis of the data. The most relevant results showed that the age-standardized incidence rate (ASIR) of thyroid cancer has a positive and significant correlation with environmental air pollution by O3 (r=0.63, P value<0.001), by particulate matter pollution (r=0.23, P value<0.001), and by household PM2.5 air pollution (r=0.52, P value≤0.001). In contrast, the correlation between ASIR and high temperature (T>25.6°C) (r=-0.27, P value<0.001) is negative and significant. The modeling results showed that particulate matter pollution and O3 pollution and household PM2.5 air pollution which originated from solid fuels are risk factors for thyroid cancer. Therefore, more research in this field is necessary in areas with high levels of air pollution at the national and international levels.

Urban densification over 9 years and change in the metabolic syndrome: A nationwide investigation from the ORISCAV-LUX cohort study

A growing body of evidence suggests that urban densification may be protective against obesity, type 2 diabetes, and cardiometabolic diseases, yet studies on how built environmental features relate to metabolic syndrome (MetS) and its components are scarce. This longitudinal study examines the associations of baseline urban density and densification over 9 years with MetS and MetS components, among 510 participants enrolled in both waves of the ORISCAV-LUX study (2007-2017) in Luxembourg. A continuous MetS score (siMS) was calculated for each participant. Six features of residential built environments were computed around participants' home address: street connectivity, population density, density of amenities, street network distance to the nearest bus station, density of public transport stations, and land use mix. A composite index of urban densification (UDI) was calculated by averaging the six standardized built environment variables. Using adjusted generalized estimating equation (GEE) models, one-SD increase in UDI was associated with a worsening of the siMS score (β = 0.07, 95% CI: 0.02, 0.13), higher triglyceride levels (β = 0.05, 95% CI: 0.02, 0.09), and lower HDL-c levels (β = -1.29, 95% CI: -2.20, -0.38). The detrimental effect of UDI on lipid levels was significant only for participants living in dense areas at baseline. Higher baseline UDI, as well as increased UDI over time among movers, were also associated with greater waist circumference. There were no associations between UDI, fasting plasma glucose and systolic blood pressure. Sex and neighborhood socio-economic status did not moderate the associations between UDI and the cardiometabolic outcomes. Overall, we found limited evidence for an effect of urban densification on MetS and its components. Understanding urban dynamics remains a challenge, and more research investigating the independent and joint health effect of built environment features is needed to support urban planning and design that promote cardiometabolic health.

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.

PPARγ As a Potential Target for Adipogenesis Induced by Fine Particulate Matter in 3T3-L1 Preadipocytes

Mounting evidence has shown that ambient PM_2.5 exposure is closely associated with the development of obesity, and adipose tissue represents an important endocrine target for PM_2.5. In this study, the 3T3-L1 preadipocyte differentiation model was employed to comprehensively explore the adipogenic potential of PM_2.5. After 8 days of PM_2.5 exposure, adipocyte fatty acid uptake and lipid accumulation were significantly increased, and adipogenic differentiation of 3T3-L1 cells was promoted in a concentration-dependent manner. Transcriptome and lipidome analyses revealed the systematic disruption of transcriptional and lipid profiling at 10 μg/mL PM_2.5. Functional enrichment and visualized network analyses showed that the peroxisome proliferator-activated receptor (PPAR) pathway and the metabolism of glycerophospholipids, glycerolipids, and sphingolipids were most significantly affected during adipocyte differentiation. Reporter gene assays indicated that PPARγ was activated by PM_2.5, demonstrating that PM_2.5 promoted adipogenesis by activating PPARγ. The increased transcriptional and protein expressions of PPARγ and downstream adipogenesis-associated markers (e.g., Fabp4 and CD36) were further cross-validated using qRT-PCR and western blot. PM_2.5-induced adipogenesis, PPARγ pathway activation, and lipid remodeling were significantly attenuated by the supplementation of a PPARγ antagonist (T0070907). Overall, this study yielded mechanistic insights into PM_2.5-induced adipogenesis in vitro by identifying the potential biomolecular targets for the prevention of PM_2.5-induced obesity and related metabolic diseases.

Nine-year exposure to residential greenness and the risk of metabolic syndrome among Luxembourgish adults: A longitudinal analysis of the ORISCAV-Lux cohort study

Growing evidence shows a beneficial effect of exposure to greenspace on cardiometabolic health, although limited by the cross-sectional design of most studies. This study examined the long-term associations of residential greenness exposure with metabolic syndrome (MetS) and MetS components within the ORISCAV-LUX study (Wave 1: 2007-2009, Wave 2: 2016-2017, n = 395 adults). Objective exposure to residential greenness was measured in both waves by the Soil-Adjusted Vegetation Index (SAVI) and by Tree Cover Density (TCD). Linear mixed models were fitted to estimate the effect of baseline levels and change in residential greenness on MetS (continuous score: siMS score) and its components (waist circumference, triglycerides, HDL-cholesterol, fasting plasma glucose and systolic blood pressure), respectively. This study provides evidence that an increase in SAVI, but not TCD, may play a role in preventing MetS, as well as improving HDL-cholesterol and fasting plasma glucose levels. Greater baseline SAVI was also associated with lower fasting plasma glucose levels in women and participants living in municipalities with intermediate housing price, and greater baseline TCD was associated with larger waist circumference. Overall, findings suggest a mixed impact of increased greenness on cardiometabolic outcomes. Further longitudinal research is needed to better understand the potential effects of different types of greenness exposure on cardiometabolic outcomes.

Associations of thiocyanate, nitrate, and perchlorate exposure with dyslipidemia: a cross-sectional, population-based analysis

The aim of this study was to assess the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with dyslipidemia, individually and in combination, which has not previously been studied. Data from the 2001-2002 and 2005-2016 National Health and Nutrition Examination Surveys (NHANES) were analyzed in this cross-sectional study. The dependent variables were continuous serum lipid variables (triglycerides [TG], total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and apolipoprotein B [Apo B]) and binary serum lipid variables, with the latter reflecting dyslipidemia (elevated TG, ≥ 150 mg/dL; elevated TC, ≥ 200 mg/dL; elevated LDL-C, ≥ 130 mg/dL; lowered HDL-C, < 40 mg/dL in men and < 5 0 mg/dL in women; elevated non-HDL-C, ≥ 160 mg/dL; and elevated Apo B, ≥ 130 mg/dL). Multivariate logistic, linear, and weighted quantile sum (WQS) regression analyses were used to explore the associations of thiocyanate, nitrate, and perchlorate with the continuous and binary serum lipid variables. The linearity of the associations with the binary serum lipid variables was assessed using restricted cubic spline (RCS) regression. A total of 15,563 adults were included in the analysis. The multivariate linear and logistic regression analyses showed that thiocyanate was positively associated with multiple continuous (TG, TC, LDL-C, non-HDL-C, and Apo B, but not HDL-C) and binary (elevated TG, TC, LDL-C, and non-HDL-C) serum lipid variables, whereas perchlorate was negatively associated with elevated LDL-C. Multivariate RCS logistic regression revealed a linear dose-response relationship between thiocyanate and elevated TG, TC, LDL-C, non-HDL-C, and Apo B, but a nonlinear relationship with lowered HDL-C (inflection point = 1.622 mg/L). WQS regression showed that a mixture of thiocyanate, nitrate, and perchlorate was positively associated with all binary serum lipid variables except for Apo B. Our findings indicate that urinary thiocyanate, nitrate, and perchlorate concentrations, individually and in combination, were associated with dyslipidemia.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

Association of Short-Term Exposure to PM2.5 with Blood Lipids and the Modification Effects of Insulin Resistance: A Panel Study in Wuhan

Results of previous studies about the acute effects of fine particulate matter (PM2.5) on blood lipids were inconsistent. This study aimed to quantify the short-term effects of PM2.5 on blood lipids and estimate the modifying role of insulin resistance, reflected by the homeostasis model assessment of insulin resistance (HOMA-IR). From September 2019 to January 2020, the study recruited 70 healthy adults from Wuhan University for a total of eight repeated data collections. At each visit, three consecutive days were monitored for personal exposure to PM2.5, and then a physical examination was carried out on the fourth day. The linear mixed-effect models were operated to investigate the impact of PM2.5 over diverse exposure windows on blood lipids. With the median of the HOMA-IR 1.820 as the cut-off point, participants were assigned to two groups for the interaction analyses. We found the overall mean level (standard deviation, SD) of PM2.5 was 38.34 (18.33) μg/m3. Additionally, with a 10 μg/m3 rise in PM2.5, the corresponding largest responses in triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), as well as high-density lipoprotein cholesterol (HDL-C), were −0.91% (95% confidence interval (CI): −1.63%, −0.18%), −0.33% (95% CI: −0.64%, −0.01%,), −0.94% (95% CI: −1.53%, −0.35%), and 0.67% (95% CI: 0.32%, 1.02%), respectively. The interaction analyses revealed that a significantly greater reduction in the four lipids corresponded to PM2.5 exposure when in the group with the lower HOMA-IR (<1.820). In conclusion, short-term PM2.5 exposure over specific time windows among healthy adults was associated with reduced TG, TC, as well as LDL-C levels, and elevated HDL-C. Additionally, the association of PM2.5−lipids may be modulated by insulin resistance.

Exposures to low-levels of fine particulate matter are associated with acute changes in heart rate variability, cardiac repolarization, and circulating blood lipids in coronary artery disease patients

Exposure to air pollution is a major risk factor for cardiovascular disease, disease risk factors, and mortality. Specifically, particulate matter (PM), and to some extent ozone, are contributors to these effects. In addition, exposures to these pollutants may be especially dangerous for susceptible populations. In this repeated-visit panel study, cardiovascular markers were collected from thirteen male participants with stable coronary artery disease. For 0-4 days prior to the health measurement collections, daily concentrations of fine PM (PM_2.5) and ozone were obtained from local central monitoring stations located near the participant's homes. Then, single (PM_2.5) and two-pollutant (PM_2.5 and ozone) models were used to assess whether there were short-term changes in cardiovascular health markers. Per interquartile range increase in PM_2.5, there were decrements in several heart rate variability metrics, including the standard deviation of the normal-to-normal intervals (lag 3, -5.8%, 95% confidence interval (CI) = -11.5, 0.3) and root-mean squared of successive differences (five day moving average, -8.1%, 95% CI = -15.0, -0.7). In addition, increases in PM_2.5 were also associated with changes in P complexity (lag 1, 4.4%, 95% CI = 0.5, 8.5), QRS complexity (lag 1, 4.9%, 95% CI = 1.4, 8.5), total cholesterol (five day moving average, -2.1%, 95% CI = -4.1, -0.1), and high-density lipoprotein cholesterol (lag 2, -1.6%, 95% CI = -3.1, -0.1). Comparisons to our previously published work on ozone were conducted. We found that ozone affected inflammation and endothelial function, whereas PM_2.5 influenced heart rate variability, repolarization, and lipids. All the health changes from these two studies were found at concentrations below the United States Environmental Protection Agency's National Ambient Air Quality Standards. Our results imply clear differences in the cardiovascular outcomes observed with exposure to the two ubiquitous air pollutants PM_2.5 and ozone; this observation suggests different mechanisms of toxicity for these exposures.

Mechanistic insights into the health benefits of fish-oil supplementation against fine particulate matter air pollution: a randomized controlled trial

BACKGROUND

Dietary fish-oil supplementation might attenuate the associations between fine particulate matter (PM_2.5) and subclinical biomarkers. However, the molecular mechanisms remain to be elucidated. This study aimed to explore the molecular mechanisms of fish-oil supplementation against the PM_2.5-induced health effects.

METHODS

We conducted a randomized, double-blinded, and placebo-controlled trial among healthy college students in Shanghai, China, from September 2017 to January 2018. A total of 70 participants from the Fenglin campus of Fudan University were included. We randomly assigned participants to either supplementation of 2.5-gram fish oil (n = 35) or sunflower-seed oil (placebo) (n = 35) per day and conducted four rounds of health measurements in the last two months of the trial. As a post hoc exploratory study, the present untargeted metabolomics analysis used remaining blood samples collected in the previous trial and applied a Metabolome-Wide Association Study framework to compare the effects of PM_2.5 on the metabolic profile between the sunflower-seed oil and fish oil groups.

RESULTS

A total of 65 participants completed the trial (34 of the fish oil group and 31 of the sunflower-seed oil group). On average, ambient PM_2.5 concentration on the day of health measurements was 34.9 µg/m³ in the sunflower-seed oil group and 34.5 µg/m³ in the fish oil group, respectively. A total of 3833 metabolites were significantly associated with PM_2.5 in the sunflower-seed oil group and 1757 in the fish oil group. Of these, 1752 metabolites showed significant between-group differences. The identified differential metabolites included arachidonic acid derivatives, omega-3 fatty acids, omega-6 fatty acids, and omega-9 fatty acids that were related to unsaturated fatty acid metabolism, which plays a role in the inflammatory responses.

CONCLUSION

This trial suggests fish-oil supplementation could mitigate the PM_2.5-induced inflammatory responses via modulating fatty acid metabolism, providing biological plausibility for the health benefits of fish-oil supplementation against PM_2.5 exposure.

TRIAL REGISTRATION

This study is registered at ClinicalTrails.gov (NCT03255187).

The neighbourhood environment and profiles of the metabolic syndrome

BACKGROUND

There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components.

METHODS

We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO₂ and PM_2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles.

RESULTS

LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO₂ were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM_2.5 was associated with unhealthier metabolic profiles with MetS.

CONCLUSIONS

This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components.

Associations between APOL1 genetic variants and blood pressure in African American mothers and children from a U.S. pregnancy cohort: Modification by air pollution exposures

INTRODUCTION

Carriage of high-risk APOL1 genetic variants is associated with increased risks for kidney diseases in people of African descent. Less is known about the variants' associations with blood pressure or potential moderators.

METHODS

We investigated these associations in a pregnancy cohort of 556 women and 493 children identified as African American. Participants with two APOL1 risk alleles were defined as having the high-risk genotype. Blood pressure in both populations was measured at the child's 4-6 years visit. We fit multivariate linear and Poisson regressions and further adjusted for population stratification to estimate the APOL1-blood pressure associations. We also examined the associations modified by air pollution exposures (particulate matter ≤2.5 μ m in aerodynamic diameter [PM2.5] and nitrogen dioxide) and explored other moderators such as health conditions and behaviors.

RESULTS

Neither APOL1 risk alleles nor risk genotypes had a main effect on blood pressure in mothers or children. However, each 2-μg/m3 increase of four-year average PM2.5 was associated with a 16.3 (95%CI: 5.7, 26.9) mmHg higher diastolic blood pressure in mothers with the APOL1 high-risk genotype, while the estimated effect was much smaller in mothers with the low-risk genotype (i.e., 2.9 [95%CI: -3.1, 8.8] mmHg; Pinteraction = 0.01). Additionally, the associations of APOL1 risk alleles and the high-risk genotype with high blood pressure (i.e., SBP and/or DBP ≥ 90th percentile) were stronger in girls vs. boys (Pinteraction = 0.02 and 0.005, respectively).

CONCLUSION

This study sheds light on the distribution of high blood pressure by APOL1 genetic variants and informs regulatory policy to protect vulnerable population subgroups.

Cardiovascular effects of traffic-related air pollution: A multi-omics analysis from a randomized, crossover trial

A system-wide cardiovascular response to traffic-related air pollution (TRAP) has been rarely described. To systemically understand the mechanisms underlying cardiovascular effects of TRAP, we conducted a randomized, crossover trial in 56 young adults, who engaged in two 4-hour exposure sessions on a main road and in a park, alternately. We measured personal exposures to traffic-related air pollutants (TRAPs), including fine and ultrafine particulate matter, black carbon, nitrogen dioxide, and carbon monoxide. Lipidomics, targeted proteomics, urine metabolomics, targeted biomarkers, ambulatory blood pressure and electrocardiogram were measured. We used linear mixed-effects models to estimate the associations. The exposures to TRAPs except for fine particulate matter in the road session were 2-3 times higher. We observed elevated blood pressure and decreased heart rate variability (HRV) after TRAP exposure, accompanied by dozens of molecular alterations involving systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and lipid metabolism. Pathways like vascular smooth muscle cell proliferation and biomarkers like trimethylamine N-Oxide might also be disturbed. Some of these TRAP-related molecular biomarkers were also associated with changes of blood pressure or HRV. Our results provided systematical mechanistic profiling for the cardiovascular effects of TRAP using multi omics, which may have implications in TRAP control.

Outdoor air quality and human health: An overview of reviews of observational studies

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NO_X, NO₂, O₃, PM₁₀, PM_2.5, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM_2.5, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM_2.5, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

Multiple environmental exposures and obesity in eastern China: An individual exposure evaluation model

Obesity has caused a huge burden of disease. Few studies have explored individuals' environmental exposure level and the impact of multiple environmental exposures on obesity. The aim of this study was to explore individual air pollution exposure evaluation, and the association between and multiple environmental factors and obesity among adult residents in rural areas of China. In this study, 8400 residents of 14 districts and counties in eastern of China were selected by multistage stratified cluster sampling, and a total of 8377 residents were included in the final analysis. We adopted BMI (Body Mass Index) > 28 kg/m² as the definition of obesity. First, an individual air pollution evaluation model was established based on the monitoring data of air pollution stations closest to residential address, different demographic characteristics of residents and daily living habits using generalized linear model and random forest model. Then, we used Bayesian Kernel Machine Regression (BKMR) and Quantile g-Computation (QgC) models to explore multiple environmental exposures on obesity. The results showed that six air pollutants were significantly positively associated with obesity, and green space had a significant protective effect on obesity. The BKMR model showed that the effects of different air pollutants on obesity were significantly enhanced by each other, while green space significantly reduced the positive effect of air pollution on obesity. The QgC model showed a significant positive association with obesity when all environmental factors were exposed as a whole, especially in males, higher household incomes and young people. It suggested that relevant authorities should improve regional air quality and green space to reduce the burden of disease caused by obesity.

Global association between atmospheric particulate matter and obesity: A systematic review and meta-analysis

BACKGROUND

Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. Although several studies have shown a link between particulate pollution and obesity, the conclusions are still inconsistent.

METHODS

We conducted a systematic review and meta-analysis to pool the effect of PM exposure on obesity. Five databases (including PubMed, Web of Science, Scopus, Embase, and Cochrane) were searched for relevant studies up to Jan 2022. Adjusted risk ratio (RR) with corresponding 95% confidence interval (CI) were retrieved from individual studies and pooled with random effect models by STATA software. Besides, we tested the stability of results by Egger's test, Begg's test, funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. The NTP-OHAT guidelines were followed to assess the risk of bias. Then the GRADE was used to evaluate the certainty of evidence.

RESULTS

26 studies were included in this meta-analysis. 19 studies have shown that PM_2.5 can increase the risk of obesity per 10 μg/m³ increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM₁₀ increase the risk of obesity per 10 μg/m³ increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM_2.5 increases the risk of obesity in children (RR: 1.06, 95% CI: 1.02-1.11). And we explored the source of heterogeneity by subgroup analysis, which suggested associations between PM and obesity tended to vary by region, age group, participants number, etc. The analysis results showed publication bias and other biases are well controlled, but most certainties of the evidence were low, and more research is required to reduce these uncertainties.

CONCLUSION

Exposure to PM_2.5 and PM₁₀ with per 10 μg/m³ increment could increase the risk of obesity in the global population.

Air pollution, residential greenness, and metabolic dysfunction biomarkers: analyses in the Chinese Longitudinal Healthy Longevity Survey

BACKGROUND

We hypothesize higher air pollution and fewer greenness exposures jointly contribute to metabolic syndrome (MetS), as mechanisms on cardiometabolic mortality.

METHODS

We studied the samples in the Chinese Longitudinal Healthy Longevity Survey. We included 1755 participants in 2012, among which 1073 were followed up in 2014 and 561 in 2017. We used cross-sectional analysis for baseline data and the generalized estimating equations (GEE) model in a longitudinal analysis. We examined the independent and interactive effects of fine particulate matter (PM_2.5) and Normalized Difference Vegetation Index (NDVI) on MetS. Adjustment covariates included biomarker measurement year, baseline age, sex, ethnicity, education, marriage, residence, exercise, smoking, alcohol drinking, and GDP per capita.

RESULTS

At baseline, the average age of participants was 85.6 (SD: 12.2; range: 65-112). Greenness was slightly higher in rural areas than urban areas (NDVI mean: 0.496 vs. 0.444; range: 0.151-0.698 vs. 0.133-0.644). Ambient air pollution was similar between rural and urban areas (PM_2.5 mean: 49.0 vs. 49.1; range: 16.2-65.3 vs. 18.3-64.2). Both the cross-sectional and longitudinal analysis showed positive associations of PM_2.5 with prevalent abdominal obesity (AO) and MetS, and a negative association of NDVI with prevalent AO. In the longitudinal data, the odds ratio (OR, 95% confidence interval-CI) of PM_2.5 (per 10 μg/m³ increase) were 1.19 (1.12, 1.27), 1.16 (1.08, 1.24), and 1.14 (1.07, 1.21) for AO, MetS and reduced high-density lipoprotein cholesterol (HDL-C), respectively. NDVI (per 0.1 unit increase) was associated with lower AO prevalence [OR (95% CI): 0.79 (0.71, 0.88)], but not significantly associated with MetS [OR (95% CI): 0.93 (0.84, 1.04)]. PM_2.5 and NDVI had a statistically significant interaction on AO prevalence (p_interaction: 0.025). The association between PM_2.5 and MetS, AO, elevated fasting glucose and reduced HDL-C were only significant in rural areas, not in urban areas. The association between NDVI and AO was only significant in areas with low PM_2.5, not under high PM_2.5.

CONCLUSIONS

We found air pollution and greenness had independent and interactive effect on MetS components, which may ultimately manifest in pre-mature mortality. These study findings call for green space planning in urban areas and air pollution mitigation in rural areas.

Exposure to concentrated ambient PM2.5 (CAPM) induces intestinal disturbance via inflammation and alternation of gut microbiome

Air pollution causes a great disease burden worldwide. Recent evidences suggested that PM_2.5 contributes to intestinal disease. The objective of present study was to investigate the influence of ambient PM_2.5 on intestinal tissue and microbiome via whole-body inhalation exposure. The results showed that high levels and prolonged periods exposure to concentrated ambient PM_2.5 (CAPM) could destroy the mucous layer of the colon, and significantly alter the mRNA expression of tight junction (Occludin and ZO-1) and inflammation-related (IL-6, IL-10 and IL-1β) genes in the colon, comparing with exposure to the filtered air (FA). The composition of intestinal microbiome at the phylum and genus levels also varied along with the exposure time and PM_2.5 levels. At the phylum level, Bacteroidetes was greatly decreased, while Proteobacteria was increased after exposure to CAPM, comparing with exposure to FA. At the genus level, Clostridium XlVa, Akkermansia and Acetatifactor, were significantly elevated exposure to CAPM, comparing with exposure to FA. Our results also indicated that high levels and prolonged periods exposure to CAPM altered metabolic functional pathways. The correlation analysis showed that the intestinal inflammation was related to the alteration of gut microbiome induced by CAPM exposure, which may be a potential mechanism that elucidates PM_2.5-induced intestinal diseases. These results extend our knowledge on the toxicology and health effects of ambient PM_2.5.

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.

Short-term ozone exposure and metabolic status in metabolically healthy obese and normal-weight young adults: A viewpoint of inflammatory pathways

Unhealthy metabolic status increases risks of cardiovascular and other diseases. This study aims to explore whether there is a link between O₃ and metabolic health indicators through a viewpoint of inflammatory pathways. 49 metabolically healthy normal-weight (MH-NW) and 39 metabolically healthy obese (MHO) young adults aged 18-26 years were recruited from a panel study with three visits. O₃ exposure were estimated based on fixed-site environmental monitoring data and time-activity diary for each participant. Compared to MH-NW people, MHO people were more susceptible to the adverse effects on metabolic status, including blood pressure, glucose, and lipid indicators when exposed to O₃. For instance, O₃ exposure was associated with significant decreases in high-density lipoprotein cholesterol (HDL-C), and increases in C-peptide and low-density lipoprotein cholesterol (LDL-C) among MHO people, while only weaker changes in HDL-C and LDL-C among MH-NW people. Mediation analyses indicated that leptin mediated the metabolic health effects in both groups, while eosinophils and MCP-1 were also important mediating factors for the MHO people. Although both with a metabolically healthy status, compared to normal-weight people, obese people might be more susceptible to the negative effects of O₃ on metabolic status, possibly through inflammatory indicators such as leptin, eosinophils, and MCP-1.

Impacts of Environmental Insults on Cardiovascular Aging

PURPOSE OF REVIEW

With cardiovascular disease (CVD) being the top cause of deaths worldwide, it is important to ensure healthy cardiovascular aging through enhanced understanding and prevention of adverse health effects exerted by external factors. This review aims to provide an updated understanding of environmental influences on cardiovascular aging, by summarizing epidemiological and mechanistic evidence for the cardiovascular health impact of major environmental stressors, including air pollution, endocrine-disrupting chemicals (EDCs), metals, and climate change.

RECENT FINDINGS

Recent studies generally support positive associations of exposure to multiple chemical environmental stressors (air pollution, EDCs, toxic metals) and extreme temperatures with increased risks of cardiovascular mortality and morbidity in the population. Environmental stressors have also been associated with a number of cardiovascular aging-related subclinical changes including biomarkers in the population, which are supported by evidence from relevant experimental studies. The elderly and patients are the most vulnerable demographic groups to majority environmental stressors. Future studies should account for the totality of individuals' exposome in addition to single chemical pollutants or environmental factors. Specific factors most responsible for the observed health effects related to cardiovascular aging remain to be elucidated.

Urban Neighbourhood Environments, Cardiometabolic Health and Cognitive Function: A National Cross-Sectional Study of Middle-Aged and Older Adults in Australia

Population ageing and urbanisation are global phenomena that call for an understanding of the impacts of features of the urban environment on older adults' cognitive function. Because neighbourhood characteristics that can potentially have opposite effects on cognitive function are interdependent, they need to be considered in conjunction. Using data from an Australian national sample of 4141 adult urban dwellers, we examined the extent to which the associations of interrelated built and natural environment features and ambient air pollution with cognitive function are explained by cardiometabolic risk factors relevant to cognitive health. All examined environmental features were directly and/or indirectly related to cognitive function via other environmental features and/or cardiometabolic risk factors. Findings suggest that dense, interconnected urban environments with access to parks, blue spaces and low levels of air pollution may benefit cognitive health through cardiometabolic risk factors and other mechanisms not captured in this study. This study also highlights the need for a particularly fine-grained characterisation of the built environment in research on cognitive function, which would enable the differentiation of the positive effects of destination-rich neighbourhoods on cognition via participation in cognition-enhancing activities from the negative effects of air pollutants typically present in dense, destination-rich urban areas.

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.

PM10 exposure interacts with abdominal obesity to increase blood triglycerides: a cross-sectional linkage study

Background

Blood lipids and glucose levels dysregulation represent potential mechanisms intermediating the adverse cardiovascular effects of ambient particulate matter (PM) exposure. This study aims to estimate the effect of long-term PM₁₀ exposure on blood lipids and glucose levels and to assess the potential mediation and/or modification action of abdominal obesity (AO) (waist-to-height ratio).

Methods

Our study was based on 2,390 participants of the first Portuguese Health Examination Survey (INSEF, 2015) with available data on blood lipids and glucose parameters and living within a 30-km radius of an air quality monitoring station with available PM₁₀ measurements. PM₁₀ concentrations were acquired from the air quality monitoring network of the Portuguese Environment Agency. Generalized linear models were used to assess the effect of 1-year PM₁₀ exposure on blood lipids and glucose levels. An interaction term was introduced in the models to test the modification action of AO.

Results

We found an association between PM₁₀ and non-fasting blood triglycerides (TG) after adjustment for age, sex, education, occupation, lifestyles-related variables and temperature but only in participants with AO. Per each 1 µg/m³ PM₁₀ increment, there was a 1.84% (95% confidence interval: 0.02–3.69) increase in TG. For the remaining blood lipid and glucose parameters, no associations were found.

Conclusions

Our study demonstrates that even at low levels of exposure, long-term PM₁₀ exposure interacts with AO to increase blood TG. Our findings suggest that reducing both AO prevalence and PM₁₀ below current standards would result in additional health benefits for the population.

Air pollution and metabolic syndrome risk: Evidence from nine observational studies

BACKGROUND AND AIMS

Globally, the number of metabolic syndrome (MetS) cases has increased substantially over time. However, the association between air pollution (AP) and MetS risk has been contradictory in observational studies. This is the first reported meta-analysis quantitatively exploring the aforementioned association.

METHODS

We searched PubMed, Embase, and Web of Science database entries up to September 14, 2020, and searches were updated up to December 6, 2020 to identify eligible articles on the AP-MetS risk association. No language restriction was imposed. Random-effects models were applied to estimate summary and subgroup effect sizes with 95% confidence intervals (CIs). PROSPERO registration number: CRD42020210431.

RESULTS

Eight articles (nine studies) were eligible for the meta-analysis. Increased MetS prevalence was not found to be associated with particulate matter less than 1 μm (PM₁), 2.5 μm (PM_2.5), and 10 μm (PM₁₀) in diameter or nitrogen dioxide (NO₂), and the summary effect sizes were 1.33 (95% CI: 0.95-1.85), 1.34 (95% CI: 0.96-1.89), 1.18 (95% CI: 0.98-1.19), and 1.28 (95% CI: 0.89-1.82), respectively, based on cross-sectional studies. The summary results indicated no association between each 10 μg/m³ increase in PM_2.5 and MetS incidence (effect size 2.78 [95% CI: 0.70-11.02]), based on cohort studies. Subgroup analysis demonstrated that MetS incidence in older men increased dramatically by 992% with each 10 μg/m³ increase in PM_2.5.

CONCLUSIONS

The evidence presented here suggests that although exposure to PM₁, PM_2.5, PM₁₀, or NO₂ was not found to have a significant association with the occurrence of MetS, the statistical significance of the relationship between exposure to PM₁, PM_2.5, or PM₁₀ and MetS prevalence was approximately borderline. More studies on AP-MetS risk association in low-/middle-income countries, as well as on the association between other air pollutants and MetS risk, are warranted. A sufficient number of high-quality studies is required to perform a meaningful meta-analysis of the relationship between air pollutants and MetS.

A Co-Twin control study of fine particulate matter and the prevalence of metabolic syndrome risk factors

The relationship between ambient fine particulate matter (PM_2.5) and metabolic syndrome (MetS) is understudied. It also remains unknown whether familial factors play a role in this relationship. In a study of 566 middle-aged twins, we examined the association of PM_2.5 with MetS risk factors, measured by a MetS score as a summation of individual risk factors (range, 0 to 5). High-resolution PM_2.5 estimates were obtained through previously validated models that incorporated monitor and satellite derived data. We estimated two-year average PM_2.5 concentrations based on the ZIP code of each twin's residence. We used ordinal response models adapted for twin studies. When treating twins as individuals, the odds ratio of having 1-point higher MetS score was 1.78 for each 10 μg/m³-increase in exposure to PM_2.5 (confidence interval [CI]: 1.01, 3.15), after adjusting for potential confounders. This association was mainly between pairs; the odds ratio was 1.97 (CI: 1.01, 3.84) for each 10 μg/m³-increase in the average pairwise exposure level. We found no significant difference in MetS scores within pairs who were discordant for PM_2.5 exposure. In conclusion, higher PM_2.5 in residence area is associated with more MetS risk factors. This association, however, is confounded by shared familial factors.

Air Pollution, Residential Greenness and Metabolic Dysfunction during Early Pregnancy in the INfancia y Medio Ambiente (INMA) Cohort

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM_2.5 and NO₂ exposures and the metabolic outcomes. Though not statistically significant, high PM_2.5 exposure (≥25 µg/m³) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO₂ exposure (≥39.8 µg/m³) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

Association between ambient particulate matter exposure and metabolic syndrome risk: A systematic review and meta-analysis

Although the association between ambient particulate matter and metabolic syndrome (MetS) has been investigated, the effect of particulate matter (PM) on MetS is inconclusive. We conducted a systematic review and meta-analysis to study the association between long-term ambient PM exposure and MetS risk. The data from five databases were extracted to analyze the association between ambient PM exposure and MetS risk. A random-effects model was performed to estimate the overall risk effect. The present systematic review and meta-analysis illustrated that an increase of 5 μg/m³ in annual PM_2.5 or PM₁₀ concentration was associated with 14% or 9% increases of MetS risk, respectively (PM_2.5, RR = 1.14, 95%CI [1.03, 1.25]; PM₁₀, RR = 1.09, 95%CI [1.00, 1.19]). The population-attributable risk (PAR) was 12.28% for PM_2.5 exposure or 8.26% for PM₁₀ exposure, respectively. There was statistical association between PM_2.5 exposure and risk of MetS in male proportion ≥50%, Asia, related disease or medication non-adjustment subgroup as well as cohort study subgroups, respectively. The significant association between PM₁₀ exposure and risk of MetS was observed in male proportion ≥50% and calories intake adjustment subgroups, respectively. Sensitivity analyses showed the robustness of our results. No publication bias was detected. In conclusion, there was positive association between long-term PM exposure and MetS risk. 12.28% of MetS risk could be attributable to PM_2.5 exposure.

Dynamic recovery after acute single fine particulate matter exposure in male mice: Effect on lipid deregulation and cardiovascular alterations

Many studies have linked airborne fine particulate matter (PM2.5) exposure to cardiovascular diseases. We performed a time-series analysis to investigate whether the disruption of lipid metabolism recovered or lasted after acute PM2.5 exposure in mice. Targeted lipidomic analysis showed that four major plasma membrane phospholipids along with cholesterol esters (CE) were significantly altered on 7th post-exposure day (PED7), and the alteration reached a peak on PED14. On PED21, the phosphatidylcholine (PC) decrease was more marked than on PED14, and its resurgence was indirectly linked to triglyceride (TG) increase. Homocysteine (HCY), lactate dehydrogenase (LDH), and α-hydroxybutyrate dehydrogenase (α-HBDH) levels increased but glucose levels decreased markedly in a dose- and time-dependent manner throughout the experimental period. Network analysis showed that the lasting lipid deregulation on PED21 correlated to myocardial markers and glucose interruption, during which high-density lipoprotein cholesterol (HDL-C) decreased. The present data implied that the constructional membrane lipids were initially interrupted by PM2.5, and the subsequent rehabilitation resulted in the deregulation of storage lipids; the parallel myocardial and glucose effects may be enhanced by the lasting HDL-C lipid deregulation on PED21. These myocardial and lipidomic events were early indicators of cardiovascular risk, resulting from subsequent exposure to and accumulation of PM2.5.

Foetal 25-hydroxyvitamin D moderates the association of prenatal air pollution exposure with foetal glucolipid metabolism disorder and systemic inflammatory responses

BACKGROUND

Previous studies have indicated that systemic inflammation may play an important role in the association between air pollution exposure and glucolipid metabolism disorders, and vitamin D supplementation was beneficial in improving systemic inflammation and glucolipid metabolism. However, the role of foetal 25-hydroxyvitamin D (25(OH)D) and high-sensitivity C-reactive protein (hs-CRP) in the association between prenatal air pollution exposure and foetal glucolipid metabolism disorders is still not clear.

OBJECTIVE

To verify whether foetal 25(OH)D can improve glucolipid metabolism disorders induced by prenatal air pollution exposure by inhibiting the systemic inflammation.

METHODS

A total of 2,754 mother-newborn pairs were enrolled from three hospitals in Hefei city, China, between 2015 and 2019. We obtained air pollutants (PM_2.5, PM₁₀, SO₂, CO, and NO₂) data from the Hefei City Ecology and Environment Bureau. Cord blood biomarkers (25(OH)D, hs-CRP, C-peptide, HDL-C, LDL-C, TC, and TG) were measured.

RESULTS

We found that prenatal air pollution exposure was positively associated with foetal glucolipid metabolic index levels after adjusting for confounders. Additionally, an IQR increase in exposure to PM_2.5, PM₁₀, SO₂, and CO was associated with 20.0% (95% confidence interval (CI): 16.9, 23.6), 20.1% (16.8, 23.3), 22.9% (20.6, 25.3), and 16.7% (14.4, 19.0) higher cord blood hs-CRP levels, respectively, and an SD increase in hs-CRP was associated with 1.4% (0.1, 2.8), 2.2% (1.6, 2.9), 1.4% (0.9, 2.0), and 3.9% (2.8, 4.9) higher C-peptide, LDL-C, TC, and TG levels in the cord blood, respectively. However, there was a monotonic decrease in βs between cord blood 25(OH)D and biomarkers (P for trend < 0.001). Furthermore, mediation analysis revealed that the association between air pollution exposure and foetal glucolipid metabolic indexes mediated by hs-CRP and 25(OH)D was 19.35%. In stratified analyses, the significant negative association between cord blood 25(OH)D with foetal hs-CRP and glucolipid metabolic indexes was observed only at low-medium levels of air pollution exposure.

CONCLUSIONS

Prenatal air pollution exposure could damage foetal glucolipid metabolic function through systemic inflammation. High foetal 25(OH)D levels may improve foetal systemic inflammation and glucolipid metabolism at low-medium levels of prenatal air pollution exposure.

Association of long-term exposure to ambient air pollutants with blood lipids in Chinese adults: The China Multi-Ethnic Cohort study

BACKGROUND

Dyslipidemia is a crucial risk factor for cardiovascular diseases. Previous studies have suggested that air pollution is associated with blood lipids. However, little evidence exists in low- and middle-income regions. We aimed to investigate the association between air pollution and blood lipids in southwestern China.

METHODS

We included 67,305 participants aged 30-79 years from the baseline data of the China Multi-Ethnic Cohort (CMEC) study. Three-year average concentrations of particles with diameters ≤1 μm (PM₁), particles with diameters ≤ 2.5 μm (PM_2.5), particles with diameters ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) were estimated using satellite-based spatiotemporal models. Individual serum lipids, including cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), were measured. Linear, logistic, and quantile regression models were used to evaluate the association between ambient air pollution and blood lipids.

RESULTS

All five air pollutants in our study were associated with lipid levels. Increased air pollution exposure was associated with a high risk of dyslipidemia. Each 10 μg/m³ increase in PM_2.5 was associated with 0.92% (95% confidence interval (CI): 0.64%, 1.20%), 2.23% (95% CI: 1.44%, 3.02%), and 3.04% (95% CI: 2.61%, 3.47%) increases in TC, TG, and LDL-C levels, respectively, and a 2.03% (95% CI: 1.69%, 2.37%) decrease in HDL-C levels, and high risks of dyslipidemia (OR = 1.14, 95% CI: 1.10, 1.18). Stronger associations of air pollution with blood lipids were found in participants with high lipid levels than in those with low lipid levels.

CONCLUSION

Long-term exposure to air pollutants was associated with blood lipid levels and the risk of dyslipidemia. People with high lipid levels were more susceptible to air pollution. Therefore, air pollution prevention and control may help reduce the incidence of dyslipidemia and the burden of CVDs.

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.

Long-term exposure to ambient air pollution and metabolic syndrome in children and adolescents: A national cross-sectional study in China

BACKGROUND

The prevalence of metabolic syndrome (MetS) rapidly increased over the past decades. However, little evidence exists about the effects of long-term exposure to ambient air pollution on MetS in children and adolescents.

OBJECTIVE

This study aims to assess the association between long-term ambient air pollution and the prevalence of MetS in a large population of Chinese children and adolescents.

METHODS

In 2013, a total of 9,897 children and adolescents aged 10 to 18 years were recruited from seven provinces/municipalities in China. MetS was defined based on the recommendation by the International Diabetes Federation (IDF). Satellite based spatio-temporal models were used to estimate exposure to ambient air pollution (including particles with diameters ≤1.0 µm (PM₁), ≤2.5 µm (PM_2.5), and ≤10 µm (PM₁₀), and nitrogen dioxide (NO₂)). Individual exposure was calculated according to 94 schools addresses. After adjustment for a range of covariates, generalized linear mixed-effects models were utilized to evaluate the associations between air pollutants and the prevalence of MetS and its components. In addition, several stratified analyses were examined according to sex, weight status, outdoor physical activity time, and sugar-sweetened beverages (SSBs) intake.

RESULTS

The prevalence of MetS was 2.8%. The odds ratio of MetS associated with a 10 μg/m³ increase in PM₁, PM_2.5, PM₁₀ and NO₂ was 1.20 (95%CI: 0.99, 1.46), 1.31 (95%CI: 1.05, 1.64), 1.32 (95%CI: 1.08, 1.62), and 1.33 (95%CI: 1.03, 1.72), respectively. Regarding the MetS components, we observed associations between all pollutants and abdominal obesity. In addition, long-term PM₁ and NO₂ exposures were associated with the prevalence of elevated fasting blood glucose. Stratified analyses detected that the associations between air pollutants and the prevalence of MetS were stronger in boys (P_interaction < 0.05).

CONCLUSIONS

We found that long-term exposure to PM_2.5, PM₁₀, and NO₂ were positively associated with the prevalence of MetS in children and adolescents. Our findings may have certain public health implications for some comprehensive strategy of environment improvement and lifestyles changes in order to reduce the burden of non-communicable disease.

The association between ambient air pollution and blood lipids: A longitudinal study in Shijiazhuang, China

BACKGROUND

Few studies have explored the associations between ambient air pollution and blood lipid levels. This study aimed to fill this knowledge gap based on a routine health examination cohort in Shijiazhuang, China.

METHODS

We included 7063 participants who took the routine health examination for 2-3 times at Hebei General Hospital from January 2016 to December 2018. Individual serum levels of cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were measured. Their three-month average exposure to air pollution prior to the routine health examinations was estimated using inverse distance weighted method. We used linear mixed-effects regression models to examine the associations between air pollution and levels of blood lipids while controlling for age, gender, body mass index (BMI), smoking, alcohol drinking, temperature, humidity, with a random effect for each individual.

RESULTS

Particles with diameters ≤2.5 μm and ≤10 μm (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and ozone (O₃) were all positively associated with TC, TG, and LDL-C and negatively associated with HDL-C, in single pollutant models. Each 10 μg/m³ increment of 3-month average PM_2.5 was associated with 0.65% [95% confidence interval (CI): 0.03%-1.28%], 0.56% (95%CI: 0.33%-0.79%) and 0.63% (95%CI: 0.35%-0.91%) increment in TG, TC, and LDL-C, and 0.91% (95%CI: 0.68%-1.13%) decrease in HDL-C. In two-pollutant models, the effects of gaseous pollutants on blood lipids were weakened, while those of PMs were strengthened. Stronger associations were presented in the elderly (≥60 years) and overweight/obese (BMI ≥ 24) participants.

CONCLUSIONS

Ambient air pollution had significantly adverse effects on blood lipid levels, especially in overweight/obese and elderly individuals.

CAPSULE

Significant associations between increased air pollution and worse blood lipid levels were found, especially in overweight/obese and elderly individuals.