Fine particulate matter and incidence of metabolic syndrome in non-CVD patients: A nationwide population-based cohort study

Impaired thyroid hormone sensitivity exacerbates the effect of PM2.5 and its components on dyslipidemia in schizophrenia

BACKGROUND

Dyslipidemia in schizophrenia causes a serious loss of healthy life expectancy, making it imperative to explore key environmental risk factors. We aimed to assess the effect of PM2.5 and its constituents on dyslipidemia in schizophrenia, identify the critical hazardous components, and investigate the role of impaired thyroid hormones (THs) sensitivity in this association.

METHODS

We collected disease data on schizophrenia from the Anhui Mental Health Center from 2019 to 2022. Logistic regression was constructed to explore the effect of average annual exposure to PM2.5 and its components [black carbon (BC), organic matter (OM), sulfate (SO42-), ammonium (NH4+), and nitrate (NO3-)] on dyslipidemia, with subgroup analyses for age and gender. The degree of impaired THs sensitivity in participants was reflected by the Thyroid Feedback Quantile-based Index (TFQI), and its role in the association of PM2.5 components with dyslipidemia was explored.

RESULTS

A total of 5125 patients with schizophrenia were included in this study. Exposure to PM2.5 and its components (BC, OM, SO42-, NH4+, and NO3-) were associated with dyslipidemia with the odds ratios and 95 % confidence interval of 1.13 (1.04, 1.23), 1.16 (1.07, 1.26), 1.15 (1.06, 1.25), 1.11 (1.03, 1.20), 1.09 (1.00, 1.18), 1.12 (1.04, 1.20), respectively. Mixed exposure modeling indicated that BC played a major role in the effects of the mixture. More significant associations were observed in males and groups <45 years. In addition, we found that the effect of PM2.5 and its components on dyslipidemia was exacerbated as impaired THs sensitivity in the patients.

CONCLUSIONS

Exposure to PM2.5 and its components is associated with an increased risk of dyslipidemia in schizophrenia, which may be exacerbated by impaired THs sensitivity. Our results suggest a new perspective for the management of ambient particulate pollution and the protection of thyroid function in schizophrenia.

Air pollution and risk of 32 health conditions: outcome-wide analyses in a population-based prospective cohort in Southwest China

BACKGROUND

Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions.

METHODS

A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD.

RESULTS

Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions.

CONCLUSIONS

Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Associations between exposure to various air pollutants and risk of metabolic syndrome: a systematic review and meta-analysis

BACKGROUND

Metabolic Syndrome (MetS) is a widely observed metabolic disorder that is increasingly prevalent worldwide, leading to substantial societal consequences. Previous studies have conducted two separate meta-analyses to investigate the relationship between MetS and air pollutants. However, these studies yielded conflicting results, necessitating a thorough systematic review and meta-analysis to reassess the link between different air pollutants and the risk of developing MetS.

METHODS

We conducted a comprehensive search of relevant literature in databases including PubMed, Embase, Cochrane Library, and Web of Science up to October 9, 2023. The search was specifically restricted to publications in the English language. Following the screening of studies investigating the correlation between air pollution and MetS, we utilized random-effects models to calculate pooled effect sizes along with their respective 95% confidence intervals (CIs). We would like to highlight that this study has been registered with PROSPERO, and it can be identified by the registration number CRD42023484421.

RESULTS

The study included twenty-four eligible studies. The results revealed that an increase of 10 μg/m3 in annual concentrations of PM1, PM2.5, PM10, NO2, SO2, and O3 was associated with a 29% increase in metabolic syndrome (MetS) risk for PM1 (OR = 1.29 [CI 1.07-1.54]), an 8% increase for PM2.5 (OR = 1.08 [CI 1.06-1.10]), a 17% increase for PM10 (OR = 1.17 [CI 1.08-1.27]), a 24% increase for NO2 (OR = 1.24 [CI 1.01-1.51]), a 19% increase for SO2 (OR = 1.19 [CI 1.04-1.36]), and a 10% increase for O3 (OR = 1.10 [CI 1.07-1.13]).

CONCLUSION

The findings of this study demonstrate a significant association between exposure to fine particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and the incidence of metabolic syndrome (MetS). Moreover, the results suggest that air pollution exposure could potentially contribute to the development of MetS in humans.

Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

Mortality Burden Due to Short-term Exposure to Fine Particulate Matter in Korea

OBJECTIVES

Excess mortality associated with long-term exposure to fine particulate matter (PM2.5) has been documented. However, research on the disease burden following short-term exposure is scarce. We investigated the cause-specific mortality burden of short-term exposure to PM2.5 by considering the potential non-linear concentration-response relationship in Korea.

METHODS

Daily cause-specific mortality rates and PM2.5 exposure levels from 2010 to 2019 were collected for 8 Korean cities and 9 provinces. A generalized additive mixed model was employed to estimate the non-linear relationship between PM2.5 exposure and cause-specific mortality levels. We assumed no detrimental health effects of PM2.5 concentrations below 15 μg/m3. Overall deaths attributable to short-term PM2.5 exposure were estimated by summing the daily numbers of excess deaths associated with ambient PM2.5 exposure.

RESULTS

Of the 2 749 704 recorded deaths, 2 453 686 (89.2%) were non-accidental, 591 267 (21.5%) were cardiovascular, and 141 066 (5.1%) were respiratory in nature. A non-linear relationship was observed between all-cause mortality and exposure to PM2.5 at lag0, whereas linear associations were evident for cause-specific mortalities. Overall, 10 814 all-cause, 7855 non-accidental, 1642 cardiovascular, and 708 respiratory deaths were attributed to short-term exposure to PM2.5. The estimated number of all-cause excess deaths due to short-term PM2.5 exposure in 2019 was 1039 (95% confidence interval, 604 to 1472).

CONCLUSIONS

Our findings indicate an association between short-term PM2.5 exposure and various mortality rates (all-cause, non-accidental, cardiovascular, and respiratory) in Korea over the period from 2010 to 2019. Consequently, action plans should be developed to reduce deaths attributable to short-term exposure to PM2.5.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network

BACKGROUND

Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes.

METHODS

After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China.

RESULTS

Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO.

CONCLUSIONS

Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

Cigarette smoking and PM2.5 might jointly exacerbate the risk of metabolic syndrome

Background

Cigarette smoking and particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) are major preventable cardiovascular mortality and morbidity promoters. Their joint role in metabolic syndrome (MS) pathogenesis is unknown. We determined the risk of MS based on PM2.5 and cigarette smoking in Taiwanese adults.

Methods

The study included 126,366 Taiwanese between 30 and 70 years old with no personal history of cancer. The Taiwan Biobank (TWB) contained information on MS, cigarette smoking, and covariates, while the Environmental Protection Administration (EPA), Taiwan, contained the PM2.5 information. Individuals were categorized as current, former, and nonsmokers. PM2.5 levels were categorized into quartiles: PM2.5 ≤ Q1, Q1 < PM2.5 ≤ Q2, Q2 < PM2.5 ≤ Q3, and PM2.5 > Q3, corresponding to PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3.

Results

The prevalence of MS was significantly different according to PM2.5 exposure (p-value = 0.0280) and cigarette smoking (p-value < 0.0001). Higher PM2.5 levels were significantly associated with a higher risk of MS: odds ratio (OR); 95% confidence interval (CI) = 1.058; 1.014-1.104, 1.185; 1.134-1.238, and 1.149; 1.101-1.200 for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. The risk of MS was significantly higher among former and current smokers with OR; 95% CI = 1.062; 1.008-1.118 and 1.531; 1.450-1.616, respectively, and a dose-dependent p-value < 0.0001. The interaction between both exposures regarding MS was significant (p-value = 0.0157). Stratification by cigarette smoking revealed a significant risk of MS due to PM2.5 exposure among nonsmokers: OR (95% CI) = 1.074 (1.022-1.128), 1.226 (1.166-1.290), and 1.187 (1.129-1.247) for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. According to PM2.5 quartiles, current smokers had a higher risk of MS, regardless of PM2.5 levels (OR); 95% CI = 1.605; 1.444-1.785, 1.561; 1.409-1.728, 1.359; 1.211-1.524, and 1.585; 1.418-1.772 for PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. After combining both exposures, the group, current smokers; PM2.5 > 38.205 μg/m3 had the highest odds (1.801; 95% CI =1.625-1.995).

Conclusion

PM2.5 and cigarette smoking were independently and jointly associated with a higher risk of MS. Stratified analyses revealed that cigarette smoking might have a much higher effect on MS than PM2.5. Nonetheless, exposure to both PM2.5 and cigarette smoking could compound the risk of MS.

Loliolide in Sargassum horneri Alleviates Ultrafine Urban Particulate Matter (PM 0.1)-Induced Inflammation in Human RPE Cells

Owing to increasing air pollution due to industrial development, fine dust has been associated with threatening public health. In particular, ultrafine urban particulate matter (uf-UP, PM 0.1) can easily enter our bodies, causing inflammation-related diseases. Therefore, in the present study, we evaluated the effects of hydrothermal extracts of Sargassum horneri and its bioactive compound, loliolide, on uf-UP-induced inflammation as a potential treatment strategy for retinal disorders. Human retinal pigment epithelial cells (ARPE-19) stimulated with TNF-α or uf-UPs were treated with S. horneri extract and loliolide. S. horneri extracts exhibited anti-inflammatory effects on uf-UP-induced inflammation without cell toxicity through downregulating the mRNA expression of MCP-1, IL-8, IL-6, and TNF-α. UPLC-QTOF/MS analysis confirmed that the hydrothermal extract of S. horneri contained loliolide, which has anti-inflammatory effects. Loliolide effectively reduced the mRNA expression and production of proinflammatory chemokines (IL-8) and cytokines (IL-1β and IL-6) by downregulating the MAPK/NF-ĸB signaling pathway on TNF-α-stimulated inflammatory ARPE-19 cells. These effects were further confirmed in inflammatory ARPE-19 cells after stimulation with uf-UPs. Collectively, these results suggested the application of S. horneri as a functional ingredient for treating ocular disorders caused by particular matters.

Associations between residential greenness and air pollution and the incident metabolic syndrome in a Thai worker cohort

Increasing air pollution and decreasing exposure to greenness may contribute to the metabolic syndrome (MetS). We examined associations between long-term exposure to residential greenness and air pollution and MetS incidence in the Bangkok Metropolitan Region, Thailand. Data from 1369 employees (aged 52-71 years) from the Electricity Generating Authority of Thailand cohort from 2002 to 2017 were analyzed. The greenness level within 500 m of each participant's residence was measured using the satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The kriging approach was used to generate the average concentration of each air pollutant (PM10, CO, SO2, NO2, and O3) at the sub-district level. The average long-term exposure to air pollution and greenness for each participant was calculated over the same period of person-time. Cox proportional hazards models were used to analyze the greenness-air pollution-MetS associations. The adjusted hazard ratio of MetS was 1.42 (95% confidence interval (CI): 1.32, 1.53), 1.22 (95% CI: 1.15, 1.30), and 2.0 (95% CI: 1.82, 2.20), per interquartile range increase in PM10 (9.5 μg/m3), SO2 (0.9 ppb), and CO (0.3 ppm), respectively. We found no clear association between NDVI or EVI and the incidence of MetS. On the contrary, the incident MetS was positively associated with NDVI and EVI for participants exposed to PM10 at concentrations more than 50 μg/m3. In summary, the incidence of MetS was positively associated with long-term exposure to air pollution. In areas with high levels of air pollution, green spaces may not benefit health outcomes.

Personal exposure of PM2.5 and metabolic syndrome markers of pregnant women in South Korea: APPO study

We examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234-7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255-11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206-9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712-10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.

Subchronic exposure to 1,2-naphthoquinone induces adipose tissue inflammation and changes the energy homeostasis of mice, partially due to TNFR1 and TLR4

Air pollution affects energy homeostasis detrimentally. Yet, knowledge of how each isolated pollutant can impact energy metabolism remains incomplete. The present study was designed to investigate the distinct effects of 1,2-naphthoquinone (1,2-NQ) on energy metabolism since this pollutant increases at the same rate as diesel combustion. In particular, we aimed to determine in vivo effects of subchronic exposure to 1,2-NQ on metabolic and inflammatory parameters of wild-type mice (WT) and to explore the involvement of tumor necrosis factor receptor 1 (TNFR1) and toll-like receptor 4 (TLR4) in this process. Males WT, TNFR1KO, and TLR4KO mice at eight weeks of age received 1,2-NQ or vehicle via nebulization five days a week for 17 weeks. In WT mice, 1,2-NQ slightly decreased the body mass compared to vehicle-WT. This effect was likely due to a mild food intake reduction and increased energy expenditure (EE) observed after six weeks of exposure. After nine weeks of exposure, we observed higher fasting blood glucose and impaired glucose tolerance, whereas insulin sensitivity was slightly improved compared to vehicle-WT. After 17 weeks of 1,2-NQ exposure, WT mice displayed an increased percentage of M1 and a decreased (p = 0.057) percentage of M2 macrophages in adipose tissue. The deletion of TNFR1 and TLR4 abolished most of the metabolic impacts caused by 1,2-NQ exposure, except for the EE and insulin sensitivity, which remained high in these mice under 1,2-NQ exposure. Our study demonstrates for the first time that subchronic exposure to 1,2-NQ affects energy metabolism in vivo. Although 1,2-NQ increased EE and slightly reduced feeding and body mass, the WT mice displayed higher inflammation in adipose tissue and impaired fasting blood glucose and glucose tolerance. Thus, in vivo subchronic exposure to 1,2-NQ is harmful, and TNFR1 and TLR4 are partially involved in these outcomes.

Exposure to air pollution and gains in body weight and waist circumference among middle-aged and older adults

INTRODUCTION

Emerging research suggested a nexus between air pollution exposure and risks of overweight and obesity, while existing longitudinal evidence was extensively sparse, particularly in densely populated regions. This study aimed to quantify concentration-response associations of changes in weight and waist circumference (WC) related to air pollution in Chinese adults.

METHODS

We conceived a nationally representative longitudinal study from 2011 to 2015, by collecting 34,854 observations from 13,757 middle-aged and older adults in 28 provincial regions of China. Participants' height, weight and WC were measured by interviewers using standardized devices. Concentrations of major air pollutants including fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ozone (O₃) predicted by well-validated spatiotemporal models were assigned to participants according to their residential cities. Possible exposure biases were checked through 1000 random simulated exposure at individual level, using a Monte Carlo simulation approach. Linear mixed-effects models were applied to estimate the relationships of air pollution with weight and WC changes, and restricted cubic spline functions were adopted to smooth concentration-response (C-R) curves.

RESULTS

Each 10-μg/m³ rise in PM_2.5, NO₂ and O₃ was associated with an increase of 0.825 (95% confidence interval: 0.740, 0.910), 0.921 (0.811, 1.032) and 1.379 (1.141, 1.616) kg in weight, respectively, corresponding to WC gains of 0.688 (0.592, 0.784), 1.189 (1.040, 1.337) and 0.740 (0.478, 1.002) cm. Non-significant violation for linear C-R relationships was observed with exception of NO₂-weight and PM_2.5/NO₂-WC associations. Sex-stratified analyses revealed elevated vulnerability in women to gain of weight in exposure to PM_2.5 and NO₂. Sensitive analyses largely supported our primary findings via assessing exposure estimates from 1000 random simulations, and performing reanalysis based on non-imputed covariates and non-obese participants, as well as alternative indicators (i.e., body mass index and waist-to-height ratio).

CONCLUSIONS

We found positively robust associations of later-life exposure to air pollutants with gains in weight and WC based on a national sample of Chinese adult men and women. Our findings suggested that mitigation of air pollution may be an efficient intervention to relieve obesity burden.

Association between long-term exposure to ambient particulate matter and blood pressure, hypertension: an updated systematic review and meta-analysis

Evidence of more recent studies should be updated to evaluate the effect of long-term exposure to particulate matter (PM) on blood pressure and hypertension.        Studies of long-term effects of PM₁, PM_2.5 and PM₁₀ on blood pressure (SBP, DBP, MAP), hypertension were searched in Pubmed, Web of Science and Embase before May, 2021. Meta-analysis of 41 studies showed that exposure to PM₁, PM_2.5 was associated with SBP (1.76 mmHg (95%CI:0.71, 2.80) and 0.63 mmHg (95%CI:0.40, 0.85), per 10 μg/m³ increase in PM), all three air pollutants (PM₁, PM_2.5, PM₁₀) was associated with DBP (1.16 mmHg (95%CI:0.34, 1.99), 0.31 mmHg (95%CI:0.16, 0.47), 1.17 mmHg (95%CI:0.24, 2.09), respectively. As for hypertension, PM₁, PM_2.5 and PM₁₀ were all significantly associated with higher risk of hypertension (OR=1.27 (95%CI:1.06, 1.52), 1.15 (95%CI:1.10, 1.20) and 1.11 (95%CI:1.07, 1.16). In conclusion, our study indicated a positive association between long-term exposure to particulate matter and increased blood pressure, hypertension.

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.

Exposure to air pollution and prevalence of metabolic syndrome: A nationwide study in China from 2011 to 2015

BACKGROUND

Evidence concerning the influence of air pollution on metabolic syndrome (MetS) is still limited. We aimed to investigate whether sustained exposure to air pollutants are associated with increased prevalence of MetS and its individual components.

METHODS

We conducted a cross-sectional study comprised of 14,097 individuals participated in the first or third survey of the CHARLS. The personal cumulative (3-year averaged) exposure concentrations of nitrogen dioxide (NO₂), particulate matter (PM) with a diameter of 1.0 μm or less (PM₁), PM with a diameter of 10 μm or less (PM₁₀) and PM with a diameter of 2.5 μm or less (PM_2.5) were estimated using a spatiotemporal random forest model at 0.1° × 0.1° spatial resolution based on residential address of each participant provided. We utilized logistic regression models to estimate the associations of the four air pollutants with the prevalence of MetS and its individual components, and performed interaction analyses to evaluate potential effect modifications by gender, health status, age and drinking status.

RESULTS

Sustained exposure to air pollutants is associated with increased prevalence of MetS. For every 10 μg/m³ increase in NO₂, PM₁, PM₁₀ and PM_2.5, the adjusted odds ratio (OR) of MetS was 2.276 (95 % CI: 2.148, 2.412), 1.207 (95 % CI: 1.155, 1.263), 1.027 (95 % CI: 1.006, 1.048) and 1.027 (95 % CI: 0.989, 1.066), respectively. For MetS components, we observed significant associations between NO₂, PM₁, PM₁₀ and central obesity, high blood pressure, elevated fasting glucose and low high-density lipoprotein cholesterol. For example, the adjusted OR of low high-density lipoprotein cholesterol for every 10 μg/m³ increase in NO₂ was 1.855 (95 % CI: 1.764, 1.952). We also identified that age could significantly modified the association between NO₂ and prevalence of MetS.

CONCLUSIONS

Chinese adults sustained exposure to higher concentrations of air pollutants are associated with increased prevalence of MetS and its components.

Long-Term Exposure to Air Pollution and the Occurrence of Metabolic Syndrome and Its Components in Taiwan

BACKGROUND

Metabolic syndrome (MetS), a major contributor to cardiovascular and metabolic diseases, has been linked with exposure to air pollution. However, the relationship between air pollutants and the five components of MetS [abdominal obesity, elevated triglyceride, decreased high-density lipoprotein cholesterol (HDL-C), elevated blood pressure, and elevated fasting blood glucose levels], has not been clearly described.

OBJECTIVE

We examined the association between long-term exposure to air pollutants and the occurrence of MetS and its components by using a longitudinal cohort in Taiwan.

METHODS

The MJ Health Research Foundation is a medical institute that conducts regular physical examinations. The development of MetS, based on a health examination and the medical history of an MJ cohort of 93,771 participants who were enrolled between 2006 and 2016 and had two or more examinations, was compared with estimated exposure to air pollutants in the year prior to health examination. The exposure levels to fine particulate matter [PM with an aerodynamic diameter of ≤2.5μm (PM2.5)] and nitrogen dioxide (NO2) in the participants' residential areas were estimated using a hybrid Kriging/land-use regression (LUR) model executed using the XGBoost algorithm and a hybrid Kriging/LUR model, respectively. Cox regression with time-dependent covariates was conducted to estimate the effects of annual air pollutant exposure on the risk of MetS and its components.

RESULTS

During the average follow-up period of 3.4 y, the incidence of MetS was 38.1/1,000 person-years. After mutual adjustment and adjustments for potential covariates, the results indicated that every 10-μg/m3 increase in annual PM2.5 concentration was associated with an increased risk of abdominal obesity [adjusted hazard ratio (aHR)=1.07; 95% confidence interval (CI): 1.01, 1.14], hypertriglyceridemia (aHR=1.17; 95% CI: 1.11, 1.23), low HDL-C (aHR=1.09; 95% CI: 1.02, 1.17), hypertension (aHR=1.15; 95% CI: 1.09, 1.21), and elevated fasting blood glucose (aHR=1.15; 95% CI: 1.10, 1.20). Furthermore, PM2.5 and NO2  may increase the risk of developing MetS among people who already "have" some components of MetS.

DISCUSSION

Our findings suggest that in apparently healthy adults undergoing physical examination, exposure to PM2.5 and NO2 might be associated with the occurrence of MetS and its components. https://doi.org/10.1289/EHP10611.

Association of PM2.5 and Its Chemical Compositions with Metabolic Syndrome: A Nationwide Study in Middle-Aged and Older Chinese Adults

Studies on the association of PM_2.5 and its compositions with metabolic syndrome (MetS) were limited, and it was unclear which was the most hazardous composition. In this study, we aimed to investigate the association between PM_2.5 and its compositions with MetS and identified the most hazardous composition. In this study, we included 13,418 adults over 45 years across 446 communities from 150 counties of 28 provinces in nationwide China in 2015. MetS was defined based on the five indicators of the Joint Interim Societies, including: blood pressure (SBP (systolic blood pressure) and DBP (diastolic blood pressure)); fasting blood glucose (FBG); fasting triglyceride (FTG); high density lipoprotein cholesterol (HDL-C); and waist circumference (WC). We used chemical transport models to estimate the concentration of PM_2.5 and its compositions, including black carbon, ammonium, nitrate, organic matter, and sulfate. We used a generalized linear regression model to examine the association of PM_2.5 and its compositions with MetS. In this study, we observed that the average age was 61.40 (standard deviation (SD): 9.59). Each IQR (29.76 μg/m³) increase in PM_2.5 was associated with a 1.27 (95% CI: 1.17, 1.37) increase in the odds for MetS. We indicated that black carbon showed stronger associations than other compositions. The higher associations were observed among women, participants aged less than 60 years, who lived in urban areas and in the Northeast, smokers, drinkers, and the obese populations. In conclusion, our findings identified the most harmful composition and sensitive populations and regions that required attention, which would be helpful for policymakers.

Effects of long-term PM2.5 exposure on metabolic syndrome among adults and elderly in Guangdong, China

BACKGROUND

We aimed to explore the association between long-term exposure to particulate matter ≤ 2.5 µm (PM_2.5) and metabolic syndrome (MetS) and its components including fasting blood glucose (FBG), blood pressure, triglyceride (TG), high-density lipoprotein cholesterol (HDL-c) and waist circumference among adults and elderly in south China.

METHODS

We surveyed 6628 participants in the chronic disease and risk factors surveillance conducted in 14 districts of Guangdong province in 2015. MetS was defined based on the recommendation by the Joint Interim Societies' criteria. We used the spatiotemporal land-use regression (LUR) model to estimate the two-year average exposure of ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and O₃) at individual levels. We recorded other covariates by using a structured questionnaire. Generalized linear mixed model was used for analysis.

RESULTS

A 10-μg/m³ increase in the two-year mean PM_2.5 exposure was associated with a higher risk of developing MetS [odd ratio (OR): 1.17, 95% confidence interval (CI): 1.01, 1.35], increased risk of fasting blood glucose level. (OR: 1.18, 95% CI: 1.02, 1.36), and hypertriglyceridemia (OR: 1.36, 95% CI: 1.18, 1.58) in the adjusted/unadjusted models (all P < 0.05). We found significant interaction between PM_2.5 and the region, exercise on the high TG levels, and an interaction with the region, age, exercise and grain consumption on FBG (P _interaction < 0.05).

CONCLUSIONS

Long-term exposure to PM_2.5 was associated with MetS, dyslipidemia and FBG impairment. Efforts should be made for environment improvement to reduce the burden of MetS-associated non-communicable disease.

Associations of Fine Particulate Matter Constituents with Metabolic Syndrome and the Mediating Role of Apolipoprotein B: A Multicenter Study in Middle-Aged and Elderly Chinese Adults

Fine particulate matter (PM_2.5) was reported to be associated with metabolic syndrome (MetS), but how PM_2.5 constituents affect MetS and the underlying mediators remains unclear. We aimed to investigate the associations of long-term exposure to 24 kinds of PM_2.5 constituents with MetS (defined by five indicators) in middle-aged and elderly adults and to further explore the potential mediating role of apolipoprotein B (ApoB). A multicenter study was conducted by recruiting subjects (n = 2045) in the Beijing-Tianjin-Hebei region from the cohort of Sub-Clinical Outcomes of Polluted Air in China (SCOPA-China Cohort). Relationships among PM_2.5 constituents, serum ApoB levels, and MetS were estimated by multiple logistic/linear regression models. Mediation analysis quantified the role of ApoB in "PM_2.5 constituents-MetS" associations. Results indicated PM_2.5 was significantly related to elevated MetS prevalence. The MetS odds increased after exposure to sulfate (SO₄^2-), calcium ion (Ca²⁺), magnesium ion (Mg²⁺), Si, Zn, Ca, Mn, Ba, Cu, As, Cr, Ni, or Se (odds ratios ranged from 1.103 to 3.025 per interquartile range increase in each constituent). PM_2.5 and some constituents (SO₄^2-, Ca²⁺, Mg²⁺, Ca, and As) were positively related to serum ApoB levels. ApoB mediated 22.10% of the association between PM_2.5 and MetS. Besides, ApoB mediated 24.59%, 50.17%, 12.70%, and 9.63% of the associations of SO₄^2-, Ca²⁺, Ca, and As with MetS, respectively. Our findings suggest that ApoB partially mediates relationships between PM_2.5 constituents and MetS risk in China.

Obesity II: Establishing causal links between chemical exposures and obesity

Obesity is a multifactorial disease with both genetic and environmental components. The prevailing view is that obesity results from an imbalance between energy intake and expenditure caused by overeating and insufficient exercise. We describe another environmental element that can alter the balance between energy intake and energy expenditure: obesogens. Obesogens are a subset of environmental chemicals that act as endocrine disruptors affecting metabolic endpoints. The obesogen hypothesis posits that exposure to endocrine disruptors and other chemicals can alter the development and function of the adipose tissue, liver, pancreas, gastrointestinal tract, and brain, thus changing the set point for control of metabolism. Obesogens can determine how much food is needed to maintain homeostasis and thereby increase the susceptibility to obesity. The most sensitive time for obesogen action is in utero and early childhood, in part via epigenetic programming that can be transmitted to future generations. This review explores the evidence supporting the obesogen hypothesis and highlights knowledge gaps that have prevented widespread acceptance as a contributor to the obesity pandemic. Critically, the obesogen hypothesis changes the narrative from curing obesity to preventing obesity.

Health Effects of Long-Term Exposure to Ambient PM2.5 in Asia-Pacific: a Systematic Review of Cohort Studies

Abstract

Purpose of Review

Health effects of long-term exposure to ambient PM_2.5 vary with regions, and 75% of the deaths attributable to PM_2.5 were estimated in Asia-Pacific in 2017. This systematic review aims to summarize the existing evidence from cohort studies on health effects of long-term exposure to ambient PM_2.5 in Asia-Pacific.

Recent Findings

In Asia-Pacific, 60 cohort studies were conducted in Australia, Mainland China, Hong Kong, Taiwan, and South Korea. They consistently supported associations of long-term exposure to PM_2.5 with increased all-cause/non-accidental and cardiovascular mortality as well as with incidence of cardiovascular diseases, type 2 diabetes mellitus, kidney diseases, and chronic obstructive pulmonary disease. Evidence for other health effects was limited. Inequalities were identified in PM_2.5-health associations.

Summary

To optimize air pollution control and public health prevention, further studies need to assess the health effects of long-term PM_2.5 exposure in understudied regions, the health effects of long-term PM_2.5 exposure on mortality and risk of type 2 diabetes mellitus, renal diseases, dementia and lung cancer, and inequalities in PM_2.5-health associations. Study design, especially exposure assessment methods, should be improved.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40572-022-00344-w.

Association between long-term exposure to PM2.5 and hypertension: A systematic review and meta-analysis of observational studies

BACKGROUND

Numerous studies have examined the association between long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5) and hypertension. However, the results are inconsistent.

OBJECTIVES

Considering the limitations of previous meta-analyses and the publication of many new studies in recent years, we conducted this meta-analysis to assess the relationship between long-term PM_2.5 exposure and the incidence and prevalence of hypertension in a healthy population.

METHODS

We searched PubMed, Web of Science, Embase, and Scopus for relevant studies published until April 2, 2021 and reviewed the reference lists of previous reviews. A total of 28 observational studies reporting RR or OR with 95% CI for the association between long-term PM_2.5 exposure and the risk of hypertension were included.

RESULTS

After the sensitivity analysis, we excluded one study with a high degree of heterogeneity, resulting in 27 studies and 28 independent reports. Approximately 42 million participants were involved, and the cases of hypertension in cohort and cross-sectional studies were 508,749 and 1,793,003, respectively. The meta-analysis showed that each 10 μg/m³ increment in PM_2.5 was significantly associated with the risks of hypertension incidence (RR = 1.21, 95% CI: 1.07, 1.35) and prevalence (OR = 1.06, 95% CI: 1.03, 1.09). Subgroup analyses showed that occupational exposure had a significant effect on the association of PM_2.5 and hypertension incidence (p for interaction = 0.042) and that the PM_2.5 concentration level and physical activity had a noticeable effect on the association of PM_2.5 and hypertension prevalence (p for interaction = 0.005; p for interaction = 0.022).

CONCLUSIONS

A significantly positive correlation was observed between long-term PM_2.5 exposure and risks of hypertension incidence and prevalence, and a high PM_2.5 concentration resulted in an increased risk of hypertension.

Assessing short-term impacts of PM2.5 constituents on cardiorespiratory hospitalizations: Multi-city evidence from China

Apart from concentrations of particulate mass, PM_2.5-associated effects on health may largely depend on its chemical components. However, little is known regarding the underlying effects of specific PM_2.5 constituents. The study included nearly 1 million hospital admissions from five Chinese cities during 2015-2017. Based on the modified Community Multiscale Air Quality model, our study simulated daily concentrations of PM_2.5 and five main components. We used a time-stratified case-crossover design with conditional logistic regression models to estimate short-term effects of PM_2.5 constituents on cause-specific hospital admissions. Per interquartile range increase in exposure to PM_2.5, elemental carbon, organic carbon, nitrate, sulfate and ammonium at lag 04-day was related to an excess risk (ER%) for non-accidental admissions of 1.6% [95% confidence interval: 1.1-2.0], 1.9% [1.3-2.4], 1.0% [0.5-1.6], 1.2% [0.4-2.0], 1.2% [0.9-1.5] and 1.4% [0.9-1.9], respectively. Great heterogeneities of constituents-admission associations existed in diverse causes and constituents. This study provided multi-center high-quality evidence that hospital admissions, particularly those for ischemic heart disease (ER% ranging from 2.3 to 5.4% at lag 04-day) and pneumonia (1.9-5.1% at lag 4-day), could be triggered by short-term exposures to ambient PM_2.5 constituents. Relatively stronger constituents-admission associations were found among females for respiratory causes and the elderly for cardiovascular causes.

Long-term ambient PM2.5 exposure associated with cardiovascular risk factors in Chinese less educated population

INTRODUCTION

Long-term exposure to ambient air pollution is related to major cardiovascular risk factors including diabetes, hypertension, hyperlipidemia and overweight, but with few studies in high-concentration nations like China so far. We aimed to investigate the association between long-term exposure to ambient fine particulate matter (particles with an aerodynamic diameter ≤ 2.5 μm, PM_2.5) and major cardiovascular risk factors in China.

METHODS

Adult participants with selected biochemical tests were recruited from the Chinese Physiological Constant and Health Condition (CPCHC) survey conducted from 2007 to 2011. Gridded PM_2.5 data used were derived from satellite-observed data with adjustment of ground-observed data. District-level PM_2.5 data were generated to estimate the association using multivariate logistic regression model and generalized additive model.

RESULTS

A total of 19,236 participants from the CPCHC survey were included with an average age of 42.8 ± 16.1 years, of which nearly half were male (47.0%). The annual average PM_2.5 exposure before the CPCHC survey was 33.4 (14.8-53.4) μg/m³, ranging from 8.0 μg/m³ (Xiwuqi) to 94.7 μg/m³ (Chengdu). Elevated PM_2.5 was associated with increased prevalence of hypertension (odds ratio (OR) =1.022, 95% confidence interval (95%CI): 1.001, 1.043) and decreased prevalence of overweight (OR = 0.926, 95%CI: 0.910, 0.942). Education significantly interacted with PM_2.5 in association with all the interesting risk factors. Each 10 μg/m³ increment of PM_2.5 was associated with increased prevalence of diabetes (OR = 1.118, 95%CI: 1.037, 1.206), hypertension (OR = 1.101, 95%CI: 1.056, 1.147), overweight (OR = 1.071, 95%CI: 1.030, 1.114) in participants with poor education, but not in well-educated population. PM_2.5 exposure was negatively associated with hyperlipidemia in all participants (OR = 0.939, 95%CI: 0.921, 0.957). The results were robust in all the sensitivity analyses.

CONCLUSION

Association between long-term PM_2.5 exposure and cardiovascular risk factors might be modified by education. PM_2.5 was associated with a higher prevalence of diabetes, hypertension, and overweight in a less-educated population with time-expose dependency. Long-term exposure to PM_2.5 might be associated with a lower prevalence of hyperlipidemia.

Long-term association of ambient air pollution and hypertension in adults and in children: A systematic review and meta-analysis

AIMS

The association of long-term ambient air pollution and hypertension has been inconsistently reported. We performed an updated systematic review and meta-analysis to assess the association between long-term exposure to ambient air pollution and risk of hypertension in adults and in children.

METHODS

PubMed, EMBASE, and Web of Science were searched up to August 7, 2020 for published articles examining the association of long-term exposure to ambient air pollution, including particulate matter (PM; ultrafine particles, PM₁, PM_1-2.5, PM_2.5, PM_2.5-10 and PM₁₀), nitrogen dioxide (NO₂), nitrogen oxides (NO_x), sulfur dioxide (SO₂), ozone (O₃), carbon monoxide (CO) and hypertension. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension with each 10-μg/m³ increase in air pollutants were calculated by random-effects models.

RESULTS

We included 57 studies (53 of adults and 4 of children) in the meta-analysis. Risk of hypertension was significantly increased in adults with each 10-μg/m³ increase in exposure to PM_2.5 (OR 1.10, 95% CI 1.07-1.14; I² = 93.1%; n = 37), PM₁₀ (1.04, 1.02-1.07; I² = 44.8%; n = 22), and SO₂ (1.21, 1.08-1.36; I² = 96.6%; n = 3). Hypertension was not significantly associated with PM₁ (n = 2), PM_2.5-10 (n = 16), NO₂ (n = 27), or NO_x (n = 17). In children, the summary ORs (95% CIs) for each 10-μg/m³ increase in PM_2.5, PM₁₀, SO₂ and O₃ were 2.82 (0.51-15.68; I² = 83.8%; n = 2), 1.15 (1.01-1.32; I² = 0; n = 2), 8.57 (0.13-575.58; I² = 94.2%; n = 2), and 1.26 (0.81-1.09, I² = 91.6%; n = 2), respectively.

CONCLUSIONS

Long-term ambient air pollution is a potential risk factor for hypertension in adults. More studies are needed to explore the effects of long-term air pollution on hypertension in children.

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.

Associations of ambient air pollution with overnight changes in body composition and sleep-related parameters

This study aims to investigate the association of air pollution with overnight change in 4body composition and sleep-related parameters. Body composition of 197 subjects in New Taipei city was measured before and after sleep by bioelectric impedance analysis. Air pollutant data were collected from Taiwan Environmental Protection Administration. Sleep parameters were examined by polysomnography. We observed fine particulate matter (PM_2.5) decreased arterial oxygen saturation (SaO₂) and increased apnea-hypopnea index (AHI); NO₂ increased arousal, AHI, and decreased mean SaO₂; and O₃ inmcreased mean SaO₂. We observed 0.99-μg/m³ increase in PM_2.5 was associated with 18.8% increase in changes of right arm fat percentage (95% confidence interval (CI): 0.004, 0.375) and 0.011-kg increase in changes of right arm fat mass (95% CI: 0.000, 0.021). 2.45-ppb increase in NO₂ was associated with 0.181-kg decrease in changes of muscle mass (95% CI: -0.147, -0.001), 0.192-kg decrease in changes of fat free mass (95% CI: -0.155, -0.001), 21.1% increase in changes of right leg fat percentage (95% CI: 0.012, 0.160), and 21.3% increase in changes of left leg fat percentage (95% CI: 0.006, 0.168). 1.56-ppb increase in O₃ was associated with 29.3% decrease in changes of right leg fat percentage (95% CI: -0.363, -0.013), 0.058-kg increase in changes of right leg fat free mass (95% CI: 0.008, 0.066), and 0.059-kg increase in changes of right leg muscle mass (95% CI: 0.010, 0.066). We observed AHI was associated with overnight changes in fat percentage, total fat mass, muscle mass, bone mass, fat free mass, extracellular water, basal metabolic rate, leg fat percentage, leg fat mass, and trunk fat percentage (p < 0.05). In conclusion, exposure to air pollutants was associated with overnight body composition changes and sleep-related parameters. Nocturnal changes in total muscle mass and leg fat percentage likely contribute to the relationship between air pollution and obstructive sleep apnea.

Long-term impacts of ambient fine particulate matter exposure on overweight or obesity in Chinese adults: The China-PAR project

Although emerging researches have linked ambient fine particulate matter (PM2.5) to obesity, evidence from high-polluted regions is still lacking. We thus assessed the long-term impacts of PM2.5 on body mass index (BMI) and the risk of the prevalence of overweight/obesity (BMI≥25 kg/m2), by incorporating the well-established Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project comprising 77,609 participants with satellite-based PM2.5 estimates at 1-km spatial resolution. The average of long-term PM2.5 level was 70.4 μg/m3, with the range of 32.1-94.2 μg/m3. Each 10 μg/m3 increment of PM2.5 was associated with 0.421 kg/m2 (95% confidence interval [CI]: 0.402, 0.439) and 13.5% (95% CI: 12.8%, 14.3%) increased BMI and overweight/obesity risk, respectively. Moreover, compared with the lowest quartile of PM2.5 (≤57.5 μg/m3), the relative risk of the prevalence of overweight/obesity from the highest quartile (>85.9 μg/m3) was 1.611 (95% CI: 1.566, 1.657). The exposure-response curve suggested a non-linear relationship between PM2.5 exposure and overweight/obesity. Besides, the association was modified by age, diabetes mellitus, hypertension and dyslipidemia status. Our study provides the evidence for the adverse impacts of long-term PM2.5 on BMI and overweight/obesity in China, and the findings are important for policy development on air quality, especially in severely polluted areas.

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.

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.

Roles of Anxiety and Depression in Predicting Cardiovascular Disease Among Patients With Type 2 Diabetes Mellitus: A Machine Learning Approach

Cardiovascular disease (CVD) is a major complication of type 2 diabetes mellitus (T2DM). In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network (DNN) to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve (ROC) analysis was used to evaluate the model performance. Of participants, 272 (32.6%) were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion.

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.

ENVINT-D-20-01309: Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany

BACKGROUND

A growing number of epidemiological studies show associations between environmental factors and impaired cardiometabolic health. However, evidence is scarce concerning these risk factors and their impact on metabolic syndrome (MetS). This analysis aims to investigate associations between long-term exposure to air pollution, road traffic noise, residential greenness, and MetS.

METHODS

We used data of the first (F4, 2006-2008) and second (FF4, 2013-2014) follow-up of the population-based KORA S4 survey in the region of Augsburg, Germany, to investigate associations between exposures and MetS prevalence at F4 (N = 2883) and MetS incidence at FF4 (N = 1192; average follow-up: 6.5 years). Residential long-term exposures to air pollution - including particulate matter (PM) with a diameter < 10 µm (PM₁₀), PM < 2.5 µm (PM_2.5), PM between 2.5 and 10 µm (PM_coarse), absorbance of PM_2.5 (PM2.5_abs), particle number concentration (PNC), nitrogen dioxide (NO₂), ozone (O₃) - and road traffic noise were modeled by land-use regression models and noise maps. For greenness, the Normalized Difference Vegetation Index (NDVI) was obtained. We estimated Odds Ratios (OR) for single and multi-exposure models using logistic regression and generalized estimating equations adjusted for confounders. Joint Odds Ratios were calculated based on the Cumulative Risk Index. Effect modifiers were examined with interaction terms.

RESULTS

We found positive associations between prevalent MetS and interquartile range (IQR) increases in PM₁₀ (OR: 1.15; 95% confidence interval [95% CI]: 1.02, 1.29), PM_2.5 (OR: 1.14; 95% CI: 1.02, 1.28), PM_coarse (OR: 1.14; 95% CI: 1.02, 1.27), and PM_2.5abs (OR: 1.17; 95% CI: 1.03, 1.32). Results further showed negative, but non-significant associations between exposure to greenness and prevalent and incident MetS. No effects were seen for exposure to road traffic noise. Joint Odds Ratios from multi-exposure models were higher than ORs from models with only one exposure.

Particulate matter inhalation and the exacerbation of cardiopulmonary toxicity due to metabolic disease

Particulate matter is a significant public health issue in the United States and globally. Inhalation of particulate matter is associated with a number of systemic and organ-specific adverse health outcomes, with the pulmonary and cardiovascular systems being particularly vulnerable. Certain subpopulations are well-recognized as being more susceptible to inhalation exposures, such as the elderly and those with pre-existing respiratory disease. Metabolic syndrome is becoming increasingly prevalent in our society and has known adverse effects on the heart, lungs, and vascular systems. The limited evaluations of individuals with metabolic syndromehave demonstrated that theymay compose a sensitive subpopulation to particulate exposures. However, the toxicological mechanisms responsible for this increased vulnerability are not fully understood. This review evaluates the currently available literature regarding how the response of an individual's pulmonary and cardiovascular systems is influenced by metabolic syndrome and metabolic syndrome-associated conditions such as hypertension, dyslipidemia, and diabetes. Further, we will discuss potential therapeutic agents and targets for the alleviation and treatment of particulate-matter induced metabolic illness. The information reviewed here may contribute to the understanding of metabolic illness as a risk factor for particulate matter exposure and further the development of therapeutic approaches to treat vulnerable subpopulations, such as those with metabolic diseases.

Association between prenatal exposure to PM2.5 and the increased risk of specified infant mortality in South Korea

BACKGROUND

Findings from previous studies on the association between exposure to fine particulate matter (PM_2.5) and the risk of infant mortality were inconsistent. Thus, two main objectives of our study were to examine the association between exposure to PM_2.5 and specified infant mortality and to identify critical trimesters.

METHODS

We retrospectively created a birth cohort of singleton full-term infants born in South Korea between 2010 and 2015 using national birth and infant mortality data. The specified causes of infant mortality were circulatory and respiratory diseases, perinatal conditions, congenital anomalies, and sudden infant death syndrome. We performed 1:10 propensity score matching for various exposure windows: each trimester, prenatal, and postnatal (up to age 1). Conditional logistic regression was applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs), while accounting for gestational age, birth weight, maternal education level, season of birth, and regions (metropolitan areas/provinces). We also conducted sex-stratified analyses and used different matching ratios for sensitivity analyses.

RESULTS

A total of 2,501,836 births and 761 deaths (0.03%) were identified in the birth cohort. We found an increased risk of infant mortality per 10 µg/m³ increase in PM_2.5 exposure during the prenatal period (OR: 1.29, 95% CI: 1.07-1.55). Exposure in the 1st and 2nd trimesters was linked to an elevated risk (OR: 1.19, 95% CI: 1.02-1.37; OR: 1.21, 95% CI: 1.04-1.40). However, no association was shown in the third trimester. PM_2.5 exposure in the 1st and 2nd trimesters was associated with elevated male infant mortality, but did not reach statistical significance in female infants. The use of different matching ratios did not significantly affect the results.

CONCLUSION

The study findings suggest that exposure to PM_2.5 could affect infant mortality differently by the timing of exposure and sex, which suggests a relation to fetal development. However, further investigations are warranted.

Ambient air pollution and body weight status in adults: A systematic review and meta-analysis

Overweight and obesity have become a global epidemic and concern, and contributed to at least 4.0 million deaths each year worldwide. However, current evidence regarding the impact of air pollution on body weight status remains inconsistent. We therefore conducted a systematic review and meta-analysis to evaluate the effect of long-term exposure to ambient air pollutants on body weight status in adults. Three databases were searched up to Dec 31, 2019 for articles investigating the association of gaseous (sulfur dioxide, nitrogen dioxide, ozone) and particulate (diameter ≤ 10 μm or ≤ 2.5 μm) air pollutants with body weight status. Random effect models were used to estimate the pooled odds ratios (ORs), regression coefficients (β) and their 95% confidence intervals (95% CIs) associated with air pollution. Among twelve studies that were eligible in the systematic review, ten were used to estimate the pooled effect size, and most of them were cross-sectional studies. We identified that ambient air pollution had adverse effects on body weight status. For example, elevated PM_2.5 and O₃ were associated with higher level of body mass index, with the pooled β (95% CIs) of 0.34 (0.30-0.38) and 0.21 (0.17-0.24) per 10 μg/m³ increment, respectively. In addition, increased NO₂, SO₂ and O₃ were associated with higher risk of having overweight/obesity, with the corresponding pooled OR (95% CI) of 1.13 (1.01-1.26), 1.04 (1.01-1.06) and 1.07 (1.02-1.13) per 10 μg/m³ increment. Overall, air pollution is a potential risk factor for body weight status in adults, and more high-quality studies, especially prospective studies from severely polluted regions, are warranted for comprehensive understanding of its health effects.

Effects of particulate matter on atherosclerosis: a link via high-density lipoprotein (HDL) functionality?

BACKGROUND

Exposure to air pollution has been associated with adverse effects on human health, and ultimately increased morbidity and mortality. This is predominantly due to hazardous effects on the cardiovascular system. Exposure to particulate matter (PM) is considered to be responsible for the most severe effects.

MAIN BODY

Here we summarize current knowledge from existing epidemiological, clinical and animal studies on the influence of PM exposure on high-density lipoprotein (HDL) functionality and the potential initiation and progression of atherosclerosis. We highlight experimental studies that bring support to the causality and point to possible mechanistic links. Recent studies indicate that the functional properties of HDL are more important than the levels per se. Fine (PM_2.5-0.1) and ultrafine (UFP) PM are composed of chemicals as well as biological elements that are redox-active and may trigger pro-inflammatory responses. Experimental studies indicate that these properties and responses may promote HDL dysfunction via oxidative pathways. By affecting protein and lipid components of the HDL particle, its anti-atherosclerotic characteristics including cholesterol efflux capacity, as well as other anti-oxidative and anti-inflammatory features might be impaired.

CONCLUSION

Current literature suggests that PM promotes HDL dysfunction via oxidative pathways. However, as relatively few studies so far have evaluated the impact of particulate air pollution on HDL functionality, more human epidemiological as well as experimental studies are needed to strengthen any possible causal relationship and determine any relevance to atherosclerosis.

Design and Rationale of the Biomarker Center of the Household Air Pollution Intervention Network (HAPIN) Trial

BACKGROUND

Biomarkers of exposure, susceptibility, and effect are fundamental for understanding environmental exposures, mechanistic pathways of effect, and monitoring early adverse outcomes. To date, no study has comprehensively evaluated a large suite and variety of biomarkers in household air pollution (HAP) studies in concert with exposure and outcome data. The Household Air Pollution Intervention Network (HAPIN) trial is a liquified petroleum gas (LPG) fuel/stove randomized intervention trial enrolling 800 pregnant women in each of four countries (i.e., Peru, Guatemala, Rwanda, and India). Their offspring will be followed from birth through 12 months of age to evaluate the role of pre- and postnatal exposure to HAP from biomass burning cookstoves in the control arm and LPG stoves in the intervention arm on growth and respiratory outcomes. In addition, up to 200 older adult women per site are being recruited in the same households to evaluate indicators of cardiopulmonary, metabolic, and cancer outcomes.

OBJECTIVES

Here we describe the rationale and ultimate design of a comprehensive biomarker plan to enable us to explore more fully how exposure is related to disease outcome.

METHODS

HAPIN enrollment and data collection began in May 2018 and will continue through August 2021. As a part of data collection, dried blood spot (DBS) and urine samples are being collected three times during pregnancy in pregnant women and older adult women. DBS are collected at birth for the child. DBS and urine samples are being collected from the older adult women and children three times throughout the child's first year of life. Exposure biomarkers that will be longitudinally measured in all participants include urinary hydroxy-polycyclic aromatic hydrocarbons, volatile organic chemical metabolites, metals/metalloids, levoglucosan, and cotinine. Biomarkers of effect, including inflammation, endothelial and oxidative stress biomarkers, lung cancer markers, and other clinically relevant measures will be analyzed in urine, DBS, or blood products from the older adult women. Similarly, genomic/epigenetic markers, microbiome, and metabolomics will be measured in older adult women samples.

DISCUSSION

Our study design will yield a wealth of biomarker data to evaluate, in great detail, the link between exposures and health outcomes. In addition, our design is comprehensive and innovative by including cutting-edge measures such as metabolomics and epigenetics. https://doi.org/10.1289/EHP5751.

Long-term exposure to PM2.5 and fasting plasma glucose in non-diabetic adolescents in Yogyakarta, Indonesia

BACKGROUND

Indonesia is facing serious air pollution. However, very few studies have been conducted to examine the health risks of air pollution in Indonesia, particularly for adolescents.

OBJECTIVE

To assess the association between long-term exposure to ambient particles with a diameter of <2.5 μm (PM_2.5) and fasting plasma glucose (FPG) in adolescents.

METHODS

A cross-sectional study was conducted in 482 adolescents aged 14-18 years in Yogyakarta, Indonesia in 2016. We finally included 469 (97.30%) participants who had no missing data for data analysis. We collected individual data on socio-demographics, behavioral habits, and health information through standardized questionnaires. Satellite-based PM_2.5 concentrations from 2013 to 2016 were assigned based on participants' residential addresses. The association between PM_2.5 and FPG was examined using a generalized linear regression model while FPG was modeled as a continuous variable. An ordered logistic regression model was used to assess the relationship between PM_2.5 and FPG categories.

RESULTS

Every 1 μg/m³ increase in PM_2.5 was associated with a 0.34 mg/dL [95 confidence interval (95% CI): 0.08 mg/dL, 0.59 mg/dL] increase in FPG levels. Comparing with the low FPG level (under 86 mg/dL), every 1 μg/m³ increase in PM_2.5 was associated with a 10.20% (95% CI: 1.60%, 19.80%) increase in the odds of impaired fasting glucose (IFG) (100-125 mg/dL). Stratified analyses indicated greater effects on participants with hypertension [odds ratio (OR) = 1.30, 95% CI: 1.09, 1.57] and those had higher physical activities (OR = 1.36, 95% CI: 1.09, 1.57). Adolescents' sex, obesity status and different cutoff points of FPG did not modify the association between the exposure to PM_2.5 and FPG levels.

CONCLUSION

Long-term exposure to PM_2.5 was associated with increased FPG levels in Indonesian non-diabetic adolescents.

Association Between Metabolic and Hormonal Derangements and Professional Exposure to Urban Pollution in a High Intensity Traffic Area

Rationale: Studies suggest a relation between exposure to air particulate matter (PM)_2.5 pollution and greater cardiovascular morbidity, as well as increased risk for obesity and diabetes. We aimed to identify association(s) between nutritional and metabolic status and exposure to environmental pollution in a cohort of policemen exposed to high levels of air pollution. Methods: We considered adult municipal policemen, working in an urban area at high-traffic density with documented high levels of air PM_2.5 (exposed group) compared to non-exposed policemen. Clinical characteristics, including the presence/absence of metabolic syndrome, were recorded, and serum biomarkers, including adiponectin, leptin, and ghrelin, were assessed. Results: One hundred ninety-nine participants were enrolled, 100 in the exposed group and 99 in the non-exposed group. Metabolic syndrome was documented in 32% of exposed group and in 52.5% of non-exposed group (P = 0.008). In the exposed group, we found a positive correlation between body mass index and serum leptin as well as in the non-exposed group (P < 0.0001). Within the exposed group, subjects with metabolic syndrome showed lower serum adiponectin (P < 0.0001) and higher leptin (P = 0.002) levels with respect to those without metabolic syndrome, whereas in the non-exposed group, subjects with metabolic syndrome showed only higher leptin levels when compared to those without metabolic syndrome (P = 0.01). Among the participants with metabolic syndrome, we found lower adiponectin levels in those of the exposed group with respect to the non-exposed ones (P = 0.007). When comparing the exposed and non-exposed groups, after stratifying participants for Homeostatic Model Assessment for Insulin Resistance >2.5, we found lower adiponectin levels in those of the exposed group with respect to the non-exposed ones (P = 0.038). Conclusions: Exposure to air PM pollution was associated with lower levels of adiponectin in adult males with metabolic syndrome.

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

Ambient air pollution (AAP) is recognized a cardiovascular risk factor and lipid profile dysregulation seems to be one of the potential mediators involved. However, results from epidemiologic research on the association between exposure to AAP and altered lipid profile have been inconsistent. This study aims to systematically review and meta-analyse epidemiologic evidence on the association between exposure to ambient air pollutants (particulate matter, nitrogen oxides, sulphur dioxide, ozone, carbon monoxide, back carbon) and lipid profile parameters (Total cholesterol; High-Density Lipoprotein Cholesterol; Low-Density Lipoprotein Cholesterol; TG-Triglycerides) or dyslipidaemia. Systematic electronic literature search was performed in PubMed, Web of Science and Scopus databases (last search on 24th May 2019) using keywords related to the exposure (ambient air pollutants) and to the outcomes (lipid profile parameters/dyslipidaemia). Qualitative and quantitative information of the studies were extracted and fixed or random-effects models were used to obtain a pooled effect estimate per each pollutant/outcome combination. 22 studies were qualitatively analysed and, from those, 3 studies were quantitatively analysed. Particulate matters were the most studied pollutants and a considerable heterogeneity in air pollution assessment methods and outcomes definitions was detected. Age, obesity related measures, tobacco consumption, sex and socioeconomic factors were the most frequent considered variables for confounding adjustment in the models. In a long-term exposure scenario, we found a 3.14% (1.36%-4.95%) increase in TG levels per 10 μg/m³ PM₁₀ increment and a 4.24% (1.37%-7.19%) increase in TG levels per 10 μg/m³ NO₂ increment. No significant associations were detected for the remaining pollutant/outcome combinations. Despite the few studies included in the meta-analysis, our study suggests some epidemiologic evidence supporting the association between PM₁₀ and NO₂ exposures and increased TG levels. Due to the very low level of evidence, more studies are needed to clarify the role of lipid profile dysregulation as a mediator on the AAP adverse cardiovascular effects.

The Alzheimer's Disease Exposome

INTRODUCTION

Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants.

RESULTS AND DISCUSSION

We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.