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

Long-term exposure to ambient particulate matter is associated with prognosis in people living with HIV/AIDS: Evidence from a longitudinal study

BACKGROUND

Evidence on the association between particulate matter (PM) exposure and prognosis in people living with HIV/AIDS (PWHA) is scarce. We aim to investigate the associations of long-term exposure to PM with AIDS-related deaths and complications.

METHODS

We collected follow-up information on 7444 PWHAs from 2000 to 2021 from the HIV/AIDS Comprehensive Response Information Management System of the Wuhan Center for Disease Control and Prevention. The AIDS-related deaths and complications were assessed by physicians every 3 to 6 months, and the monthly average PM concentrations for each PWHA were extracted from the China High Air Pollutants dataset. We employed time-varying Cox regression models to evaluate the associations of the average cumulative PM exposure concentrations with AIDS-related deaths and complications, as well as the mediating effects of AIDS-related complications in PM-induced AIDS-related deaths.

RESULTS

For each 1 μg/m3 increase in PM1, PM2.5, and PM10, the adjusted hazard ratios (HRs) for AIDS-related deaths were 1.021 (1.009, 1.033), 1.012 (1.005, 1.020), and 1.010 (1.005, 1.015), respectively; and the HRs for AIDS-related complications were 1.049 (1.034, 1.064), 1.029 (1.020, 1.038), and 1.031 (1.024, 1.037), respectively. AIDS-related complications mediated 18.38 % and 18.68 % of the association of exposure to PM1 and PM2.5 with AIDS-related deaths, respectively. The association of PM exposure with AIDS-related deaths was more significant in older PWHA. Meanwhile, the association between PM exposure and AIDS-related complications was stronger in PWHA with a BMI ≥ 24 kg/m2.

CONCLUSION

Long-term exposure to PM is positively associated with AIDS-related deaths and complications, and AIDS-related complications have mediating effects in PM-induced AIDS-related deaths. Our evidence emphasizes that enhanced protection against PM exposure for PWHAs is an additional mitigation strategy to reduce AIDS-related deaths and complications.

Ambient particulate matter and renal function decline in people with HIV/AIDS

OBJECTIVE

We aimed to explore the effect of particulate matter exposure on renal function in people with HIV/AIDS (PWHA).

METHODS

A total of 37 739 repeated measurements were conducted on eGFR levels, serum creatinine (Scr), and the triglyceride-glucose (TyG) index in 6958 PWHAs. The relationship between 1 and 28 day moving averages of particulate matter concentrations with Scr and eGFR was assessed using linear mixed-effects models. Modified Poisson regression models were employed to assess the associations of cumulative particulate matter exposure with the incidence of chronic kidney disease (CKD). Mediation analyses were used to examine the role of TyG index.

RESULTS

Short-term exposure to particulate matter was related to reduced renal function. The strongest associations between exposure to particulate matter (PM) 1 , PM 2.5 , and PM 10 and percentage changes in eGFR were observed at 7-day moving average exposure windows, with a respective decrease of 0.697% (-1.008%, -0.386%), 0.429% (-0.637%, -0.220%), and 0.373% (-0.581%, -0.164%) per IQR increment. Long-term exposure to PM 1 , PM 2.5 , and PM 10 was positively linked with the incidence of CKD, with each IQR increment corresponding to fully adjusted RRs (95% CIs) of 1.631 (1.446-1.839), 1.599 (1.431-1.787), and 1.903 (1.665-2.175), respectively. TyG index-mediated 8.87, 8.88, and 7.58% of the relationship between cumulative exposure to PM 1 , PM 2.5 , and PM 10 and increased risk of CKD, respectively.

CONCLUSION

Exposure to particulate matter among PWHAs is linked to reduced renal function, potentially contributing to increased CKD incidence, where the TyG index might serve as a partial mediator.

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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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.

Long-term influence of air pollutants on morbidity and all-cause mortality of cardiometabolic multi-morbidity: A cohort analysis of the UK Biobank participants

BACKGROUND

The effects of air pollutants on cardiometabolic diseases (CMDs) have been widely explored, whereas their influences on cardiometabolic multi-morbidity (CMM) were not clear.

METHODS

We employed the UK Biobank cohort (N = 317,160) to study the association between six air pollutants (PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx) and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. CMM was defined as occurrence of two or more of the four diseases. Multi-state Cox models were performed to estimate hazard ratio (HR) and its 95% confidence interval (95%CI).

RESULTS

During a median follow-up of 12.8 years, 52,211 participants developed only one CMD, 15,446 further developed CMM, and 16,861 ultimately died. It was demonstrated that per interquartile range increase (IQR) increases in PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx would increase 12% (9%-15%), 4% (1%-7%), 3% (1%-6%), 7% (4%-10%), 11% (8%-15%) and 10% (7%-13%) higher risk of developing one CMD from health baseline; 7% (2%-12%), 8% (3%-13%), 6% (2%-11%), 10% (5%-15%), 13% (7%-18%) and 10% (5%-15%) greater risk of occurring CMM from one CMD baseline; and 11% (-2%∼26%), 22% (7%-38%), 17% (3%-32%), 31% (16%-49%), 33% (17%-51%) and 32% (17%-50%) larger risk of causing death from CMM baseline, respectively.

CONCLUSIONS

We revealed that people living in areas with high air pollution suffered from higher hazard of CMD, CMM and all-cause mortality; our findings implied keeping clean air was an effective approach to prevent or mitigate initiation, progression, and death from healthy to CMDs and from CMDs to CMM.

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.

Independent and interactive associations between greenness and ambient pollutants on novel glycolipid metabolism biomarkers: A national repeated measurement study

This study aims to investigate the independent and interactive effects of greenness and ambient pollutants on novel glycolipid metabolism biomarkers. A repeated national cohort study was conducted among 5085 adults from 150 counties/districts across China, with levels of novel glycolipid metabolism biomarkers of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c measured. Exposure levels of greenness and ambient pollutants (including PM1, PM2.5, PM10, and NO2) for each participant were determined based on their residential location. Linear mixed-effect and interactive models were used to evaluate the independent and interactive effects between greenness and ambient pollutants on the four novel glycolipid metabolism biomarkers. In the main models, the changes [β (95% CIs)] of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c were -0.021 (-0.036, -0.007), -0.120 (-0.175, -0.066), -0.092 (-0.122, -0.062), and -0.445 (-1.370, 0.480) for every 0.1 increase in NDVI, and were 0.004 (0.003, 0.005), 0.014 (0.009, 0.019), 0.009 (0.006, 0.011), and 0.067 (-0.019, 0.154) for every 1 μg/m3 increase in PM1. Results of interactive analyses demonstrated that individuals living in low-polluted areas could get greater benefits from greenness than those living in highly-polluted areas. Additionally, the results of mediation analyses revealed that PM2.5 mediated 14.40% of the association between greenness and the TyG index. Further research is needed to validate our findings.

Synergistic association of long-term ozone exposure and solid fuel use with biomarkers of advanced fibrosis

This study aims to explore the association of combined exposure to cooking fuel type and ambient ozone (O3) levels with hepatic fibrosis indices among rural adults. A total of 21,010 participants were derived from the Henan Rural Cohort. Information regarding cooking fuel type was collected through a questionnaire, and the concentration of ground-level O3 for each subject was obtained from the Tracking Air Pollution in China (TAP) dataset. A generalized linear model was used to examine the independent association of cooking fuel type or O3 exposure with hepatic fibrosis indices (FIB-4, APRI, and AST/ALT), and their possible interactions with advanced fibrosis were conducted. Compared to clean fuel users, solid fuel users had increased the risk of advanced fibrosis, the adjusted odds ratio (OR) of its assessment by FIB-4 1.240 (1.151, 1.336), by APRI 1.298 (1.185, 1.422), and by AST/ALT 1.135 (1.049, 1.227), respectively. Compared to low O3 exposure, the adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT in women with high O3 exposure were correspondingly 1.219 (1.138, 1.305), 1.110 (1.017, 1.212), and 0.883 (0.822, 0.949). The adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT for solid fuel users with high O3 exposure relative to clean fuel users with low O3 exposure in women were 1.557 (1.381, 1.755), 1.427 (1.237, 1.644), and 0.979 (0.863, 1.108), respectively. Significant additive effect of O3 exposure and solid fuel use on FIB-4-defined advanced fibrosis was observed in women, which was quantified by RERI (0.265, 95%CI: 0.052, 0.477), AP (0.170 95%CI: 0.045, 0.295), and SI (1.906, 95%CI: 1.058, 3.432). Solid fuel users with high O3 exposure were significantly associated with elevated hepatic fibrosis indices among rural women, suggesting that poor air quality may induce hepatocellular injury, and women might be more vulnerable to air pollution. The findings indicate that using cleaner fuels in cooking is an effective measure to maintain sustainable development of the environment and gain beneficial effect on human health. Clinical trial registration: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

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.

Joint effect of multiple air pollutants on cardiometabolic health in normal-weight and obese adults: A novel insight into the role of circulating free fatty acids

The cardiometabolic effects of air pollution in the context of mixtures and the underlying mechanisms remain not fully understood. This study aims to investigate the joint effect of air pollutant mixtures on a broad range of cardiometabolic parameters, examine the susceptibility of obese individuals, and determine the role of circulating fatty acids. In this panel study, metabolically healthy normal-weight (MH-NW, n = 49) and obese (MHO, n = 39) adults completed three longitudinal visits (257 person-visits in total). Personal exposure levels of PM_2.5, PM₁₀, O₃, NO₂, SO₂, CO and BC were estimated based on fixed-site monitoring data, time-activity logs and infiltration factor method. Blood pressure, glycemic homeostasis, lipid profiles, systematic inflammation and coagulation biomarkers were measured. Targeted metabolomics was used to quantify twenty-eight plasma free fatty acids (FFAs). Bayesian kernel machine regression models were applied to establish the exposure-response relationships and identify key pollutants. Significant joint effects of measured air pollutants on systematic inflammation and coagulation biomarkers were observed in the MHO group, instead of the MH-NW group. Lipid profiles showed the most significant changes in both groups and O₃ contributed the most to the total effect. Specific FFA patterns were identified, and de novo lipogenesis (DNL)-related pattern was most closely related to blood lipid profiles. In particular, interaction analysis suggested that DNL-related FFA pattern augmented the effects of O₃ on triglyceride (TG, P_interaction = 0.040), high-density lipoprotein cholesterol (HDL-C, P_interaction = 0.106) and TG/HDL-C (P_interaction = 0.020) in the MHO group but not MH-NW group. This modification was further confirmed by interaction analysis with estimated activity of SCD1, a key enzyme in the DNL pathway. Therefore, despite being metabolically healthy, obese subjects have a higher cardiometabolic susceptibility to air pollution, especially O₃, and the DNL pathway may represent an intrinsic driver of lipid susceptibility. This study provides new insights into the cardiometabolic susceptibility of obese individuals to air pollution.

Are there joint effects of different air pollutants and meteorological factors on mental disorders? A machine learning approach

Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM_2.5, PM₁₀, O₃, SO₂, and NO₂), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients' average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m³ increase in O₃, PM_2.5 and PM₁₀ exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O₃ and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O₃ and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.

Body Mass Index Modulates the Impact of Short-Term Exposure to Air Particulate Matter on High-Density Lipoprotein Function

Air particulate matter (PM) exposure has been associated with increased cardiovascular risk, especially in obesity. By triggering inflammation and oxidative stress, PM could impact atheroprotection by high-density lipoproteins (HDL). The aim of the study was to assess the relationship between short-term exposure to PM and HDL function, and the modifying effect of body mass index (BMI). Daily exposures to PM10 and PM2.5 of 50 subjects with overweight/obesity and 41 healthy volunteers with BMI < 30 kg/m2 were obtained from fixed monitoring stations. HDL function was assessed as promotion of nitric oxide (NO) release by endothelial cells and reduction in cholesterol in macrophages. HDL-induced NO release progressively declined with the increase in BMI. No association was found between HDL function and PM exposure, but a modifying effect of BMI was observed. The positive association between PM10 exposure at day −1 and NO production found at normal BMI values was lost in participants with higher BMI. Similar results were obtained for the reduction in macrophage cholesterol. The loss of the compensatory response of HDL function to PM exposure at increasing BMI levels could contribute to the endothelial dysfunction induced by PM and help to explain the susceptibility of subjects with obesity to air pollution.

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

Ambient particles with aerodynamic diameter <0.1 μm (PM_0.1) have been suggested to have significant health impact. However, studies on the association between long-term PM_0.1 exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006-2009 average PM_0.1 concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM_0.1 concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM_0.1 concentration was associated with a 5.75 (95% Confidence interval, 3.24-8.25) mg/dl and a 6.05 (2.85-9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10-1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM_0.1 exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

Urban heat: an increasing threat to global health

Shilu Tong and colleagues describe the health consequences of extreme urban heat and the priorities for action and research to mitigate the harms