Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

Weekly-specific ambient PM1 before and during pregnancy and the risk of gestational diabetes mellitus

BACKGROUND

Exposure to fine or respirable particulate matter has been linked to an elevated risk of gestational diabetes mellitus (GDM). However, the association between exposure to particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) and GDM has not been explored.

METHODS

We conducted a cohort study involving 60,173 pregnant women from nine hospitals in Beijing, China, from February 2015 to April 2021. Daily concentrations of PM1 and ozone were obtained from a validated spatiotemporal artificial intelligence model. We used a modified Poisson regression combined with distributed lag models to estimate the association between weekly-specific PM1 exposure and the risk of GDM after adjusting for individual-level covariates.

RESULTS

Among the 51,299 pregnant women included in the final analysis, 4008 were diagnosed with GDM. Maternal exposure to PM1 during preconception and gestational periods was generally associated with an increased risk of GDM. The most pronounced associations were identified during the 12th week before pregnancy, the 5th-8th weeks of the first trimester, and the 23rd-24th weeks of the second trimester. Each 10 μg/m3 increase in PM1 was associated with a relative risk of GDM of 1.65 (95 % CI: 1.59, 1.72) during the preconception period, 1.67 (95 % CI: 1.61, 1.73) in the first trimester, 1.52 (95 % CI: 1.47, 1.58) in the second trimester, and 2.54 (95 % CI: 2.45, 2.63) when considering the first and second trimester combined.

CONCLUSIONS

Exposure to PM1 before and during pregnancy was associated with an increased risk of GDM, particularly during the 12 weeks before pregnancy and gestational weeks 5-8 and 23-24.

Associations between long-term ambient PM2.5 exposure and the incidence of cardiopulmonary diseases and diabetes, attributable years lived with disability, and policy implication

Long-term exposure to ambient PM2.5 is known associated with cardiovascular and respiratory health effects. However, the heterogeneous concentrationresponse function (CRF) between PM2.5 exposure across different concentration range and cardiopulmonary disease and diabetes mellitus (DM) incidence, and their implications on attributable years lived with disability (YLD) and regulation policy has not been well-studied. In this retrospective longitudinal cohort study, disease-free participants (approximately 170,000 individuals, aged ≥ 30 years) from the MJ Health Database were followed up (2007-2017) regarding incidents of coronary heart disease (CHD), ischemic stroke, chronic obstructive pulmonary disease (COPD), lower respiratory tract infections (LRIs), and DM. We used a time-dependent nonlinear weight-transformation Cox regression model for the CRF with an address-matched 3-year mean PM2.5 exposure estimate. Town/district-specific PM2.5-attributable YLD were calculated by multiplying the disease incidence rate, population attributable fraction, disability weight, and sex-age group specific subpopulation for each disease separately. The estimated CRFs for cardiopulmonary diseases were heterogeneously with the hazard ratios (HRs) increased rapidly for CHD and ischemic stroke at PM2.5 concentration lower than 10 μg/m3, whereas the HRs for DM (LRIs) increased with PM2.5 higher than 15 (20) μg/m3. Women had higher HRs for ischemic stroke and DM but not CHD. Relative to the lowest observed PM2.5 concentration of 6 μg/m3 of the study population, the PM2.5 level with an extra risk of 0.1 % (comparable to the disease incidence) for CHD, ischemic stroke, DM, and LRIs were 8.59, 11.85, 22.09, and 24.23 μg/m3, respectively. The associated attributable YLD decreased by 51.4 % with LRIs reduced most (83.6 %), followed by DM (63.7 %) as a result of PM2.5 concentration reduction from 26.10 to 16.82 μg/m3 during 2011-2019 in Taiwan. The proportion of YLD due to CHD and ischemic stroke remained dominant (56.4 %-69.9 %). The cost-benefit analysis for the tradeoff between avoidable YLD and mitigation cost suggested an optimal PM2.5 exposure level at 12 μg/m3. CRFs for cardiopulmonary diseases, attributable YLD, and regulation level, may vary depending on the national/regional background and spatial distribution of PM2.5 concentrations, as well as demographic characteristics.

Association between short-term ambient air pollutants and type 2 diabetes outpatient visits: a time series study in Lanzhou, China

Diabetes is a global public health problem, and the impact of air pollutants on type 2 diabetes mellitus (T2DM) has attracted people's attention. This study aimed to assess the association of short-term exposure to six criteria air pollutants with T2DM outpatient visits in Lanzhou, China. We collected data on daily outpatient visits for T2DM, daily meteorological data and hourly concentrations of air pollutants in Lanzhou from 2013 to 2019. An over-dispersed passion generalized addictive model combined with a distributed lag non-linear model was applied to estimate the associations and stratified analyses were performed by gender, age, and season. The models were fitted with different lag structures, including single lag days from the current to the previous seven days (lag0 to lag7) and moving average concentrations over seven lag days (lag01 to lag07). A positive association between multiple air pollutants, especially PM2.5, NO2, O38h and CO and hospital outpatient visits for T2DM was observed. The largest association between T2DM outpatient visits and PM2.5 was observed at lag06 (RR 1.013, 95% CI: 1.001, 1.027), NO2 at lag03 (RR 1.034, 95% CI: 1.018, 1.050), O38h at lag05 (RR 1.012, 95% CI: 1.001, 1.023) for an increase of 10 μg m-3 and CO at lag03 (RR 1.084, 95% CI: 1.029, 1.142) for an increase of 1 mg m-3 in the concentrations. In addition, people aged <65 and males are more susceptible, and air pollutants have a greater impact on the cold season. This study showed that although the air pollution in Lanzhou was improved, there was still a statistical correlation between air pollution exposure and T2DM outpatient visits. Therefore, the local government still needs to strengthen the control of air pollution and enhance the protection awareness of the diabetic population through education and publicity.

The Effect of Diesel Exhaust Particles on Adipose Tissue Mitochondrial Function and Inflammatory Status

Air pollution poses a significant global health risk, with fine particulate matter (PM2.5) such as diesel exhaust particles (DEPs) being of particular concern due to their potential to drive systemic toxicities through bloodstream infiltration. The association between PM2.5 exposure and an increased prevalence of metabolic disorders, including obesity, metabolic syndrome, and type 2 diabetes mellitus (T2DM), is evident against a backdrop of rising global obesity and poor metabolic health. This paper examines the role of adipose tissue in mediating the effects of PM2.5 on metabolic health. Adipose tissue, beyond its energy storage function, is responsive to inhaled noxious stimuli, thus disrupting metabolic homeostasis and responding to particulate exposure with pro-inflammatory cytokine release, contributing to systemic inflammation. The purpose of this study was to characterize the metabolic response of adipose tissue in mice exposed to either DEPs or room air (RA), exploring both the adipokine profile and mitochondrial bioenergetics. In addition to a slight change in fat mass and a robust shift in adipocyte hypertrophy in the DEP-exposed animals, we found significant changes in adipose mitochondrial bioenergetics. Furthermore, the DEP-exposed animals had a significantly higher expression of adipose inflammatory markers compared with the adipose from RA-exposed mice. Despite the nearly exclusive focus on dietary factors in an effort to better understand metabolic health, these results highlight the novel role of environmental factors that may contribute to the growing global burden of poor metabolic health.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Obesogens: a unifying theory for the global rise in obesity

Despite varied treatment, mitigation, and prevention efforts, the global prevalence and severity of obesity continue to worsen. Here we propose a combined model of obesity, a unifying paradigm that links four general models: the energy balance model (EBM), based on calories as the driver of weight gain; the carbohydrate-insulin model (CIM), based on insulin as a driver of energy storage; the oxidation-reduction model (REDOX), based on reactive oxygen species (ROS) as a driver of altered metabolic signaling; and the obesogens model (OBS), which proposes that environmental chemicals interfere with hormonal signaling leading to adiposity. We propose a combined OBS/REDOX model in which environmental chemicals (in air, food, food packaging, and household products) generate false autocrine and endocrine metabolic signals, including ROS, that subvert standard regulatory energy mechanisms, increase basal and stimulated insulin secretion, disrupt energy efficiency, and influence appetite and energy expenditure leading to weight gain. This combined model incorporates the data supporting the EBM and CIM models, thus creating one integrated model that covers significant aspects of all the mechanisms potentially contributing to the obesity pandemic. Importantly, the OBS/REDOX model provides a rationale and approach for future preventative efforts based on environmental chemical exposure reduction.

Dietary intake changes the associations between long-term exposure to fine particulate matter and the surrogate indicators of insulin resistance

The relationship of fine particulate matter (PM2.5) exposure and insulin resistance remains inclusive. Our study aimed to investigate this association in the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). Specifically, we examined the associations between long-term PM2.5 exposure and three surrogate indicators of insulin resistance: the triglyceride-glucose index (TyG), TyG with waist circumference (TyG-WC) and metabolic score for insulin resistance (METS-IR). Additionally, we explored potential effect modification of dietary intake and components. Generalized estimating equations were used to evaluate the associations between PM2.5 and the indicators with an unbalanced repeated measurement design. Our analysis incorporated a total of 162,060 observations from 99,329 participants. Each 10 μg/m3 increment of PM2.5 was associated with an increase of 0.22 % [95 % confidence interval (CI): 0.20 %, 0.25 %], 1.60 % (95 % CI: 1.53 %, 1.67 %), and 2.05 % (95 % CI: 1.96 %, 2.14 %) in TyG, TyG-WC, and METS-IR, respectively. These associations were attenuated among participants with a healthy diet, particularly those with sufficient intake of fruit and vegetable, fish or tea (pinteraction < 0.0028). For instance, among participants with a healthy diet, TyG increased by 0.11 % (95 % CI: 0.08 %, 0.15 %) per 10 μg/m3 PM2.5 increment, significantly lower than the association observed in those with an unhealthy diet. The findings of this study emphasize the potential of a healthy diet to mitigate these associations, highlighting the urgency for improving air quality and implementing dietary interventions among susceptible populations in China.

Air pollution exposure and cardiometabolic risk

The Global Burden of Disease assessment estimates that 20% of global type 2 diabetes cases are related to chronic exposure to particulate matter (PM) with a diameter of 2·5 μm or less (PM2·5). With 99% of the global population residing in areas where air pollution levels are above current WHO air quality guidelines, and increasing concern in regard to the common drivers of air pollution and climate change, there is a compelling need to understand the connection between air pollution and cardiometabolic disease, and pathways to address this preventable risk factor. This Review provides an up to date summary of the epidemiological evidence and mechanistic underpinnings linking air pollution with cardiometabolic risk. We also outline approaches to improve awareness, and discuss personal-level, community, governmental, and policy interventions to help mitigate the growing global public health risk of air pollution exposure.

The mediation effect of asprosin on the association between ambient air pollution and diabetes mellitus in the elderly population in Taiyuan, China

Evidence around the relationship between air pollution and the development of diabetes mellitus (DM) remains limited and inconsistent. To investigate the potential mediation effect of asprosin on the association between fine particulate matter (PM2.5), tropospheric ozone (O3) and blood glucose homeostasis. A case-control study was conducted on a total of 320 individuals aged over 60 years, including both diabetic and non-diabetic individuals, from six communities in Taiyuan, China, from July to September 2021. Generalized linear models (GLMs) suggested that short-term exposure to PM2.5 was associated with elevated fasting blood glucose (FBG), insulin resistance index (HOMA-IR), as well as reduced pancreatic β-cell function index (HOMA-β), and short-term exposure to O3 was associated with increased FBG and decreased HOMA-β in the total population and elderly diabetic patients. Mediation analysis showed that asprosin played a mediating role in the relationship of PM2.5 and O3 with FBG, with mediating ratios of 10.2% and 18.4%, respectively. Our study provides emerging evidence supporting that asprosin mediates the short-term effects of exposure to PM2.5 and O3 on elevated FBG levels in an elderly population. Additionally, the elderly who are diabetic, over 70 years, and BMI over 24 kg/m2 are more vulnerable to air pollutants and need additional protection to reduce their exposure to air pollution.

Maternal health outcomes associated with ambient air pollution: An umbrella review of systematic reviews and meta-analyses

A growing body of literature demonstrated an association between exposure to ambient air pollution and maternal health outcomes with mixed findings. The objective of this umbrella review was to systematically summarize the global evidence on the effects of air pollutants on maternal health outcomes. We adopted the Joanna Briggs Institute (JBI) methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standards for this umbrella review. We conducted a comprehensive search across six major electronic databases and other sources to identify relevant systematic reviews and meta-analyses (SRMAs) published from the inception of these databases up to June 30, 2023. Out of 2399 records, 20 citations matched all pre-determined eligibility criteria that include SRMAs focusing on exposure to air pollution and its impact on maternal health, reported quantitative measures or summary effects, and published in peer-reviewed journals in the English language. The risk of bias of included SRMAs was evaluated based on the JBI critical appraisal checklist. All SRMAs reported significant positive associations between ambient air pollution and several maternal health outcomes. Specifically, particulate matter (PM), SO2, and NO demonstrated positive associations with gestational diabetes mellitus (GDM). Moreover, PM and NO2 showed a consistent positive relationship with hypertensive disorder of pregnancy (HDP) and preeclampsia (PE). Although limited, available evidence highlighted a positive correlation between PM and gestational hypertension (GH) and spontaneous abortion (SAB). Only one meta-analysis reported the effects of air pollution on maternal postpartum depression (PPD) where only PM10 showed a significant positive relationship. Limited studies were identified from low- and middle-income countries (LMICs), suggesting evidence gap from the global south. This review necessitates further research on underrepresented regions and communities to strengthen evidence on this critical issue. Lastly, interdisciplinary policymaking and multilevel interventions are needed to alleviate ambient air pollution and associated maternal health disparities.

Duration-sensitive association between air pollution exposure and changes in cardiometabolic biomarkers: Evidence from a predominantly African American cohort

BACKGROUND

Ambient fine particulate matter (PM2.5) exposure has been related to cardiometabolic diseases, but the underlying biological pathways remain unclear at the population level.

OBJECTIVE

To investigate the effect of PM2.5 exposure on changes in multiple cardiometabolic biomarkers across different exposure durations.

METHOD

Data from a prospective cohort study were analyzed. Ten cardiometabolic biomarkers were measured, including ghrelin, resistin, leptin, C-peptide, creatine kinase myocardial band (CK-MB), monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor alpha (TNF-alpha), N-terminal pro B-type natriuretic peptide (NT-proBNP), troponin, and interleukin-6 (IL-6). PM2.5 levels across exposure durations from 1 to 36 months were assessed. Mixed effect model was used to estimate changes in biomarker levels against 1 μg/m3 increase in PM2.5 level across different exposure durations.

RESULTS

Totally, 641 participants were included. The average PM2.5 exposure level was 9 μg/m3. PM2.5 exposure was inversely associated with ghrelin, and positively associated with all other biomarkers. The magnitudes of these associations were duration-sensitive and exhibited a U-shaped or inverted-U-shaped trend. For example, the association of resistin were β = 0.05 (95% CI: 0.00, 0.09) for 1-month duration, strengthened to β = 0.27 (95% CI: 0.14, 0.41) for 13-month duration, and weakened to β = 0.12 (95% CI: -0.03, 0.26) for 24-month duration. Similar patterns were observed for other biomarkers except for CK-MB, of which the association direction switched from negative to positive as the duration increased. Resistin, leptin, MCP-1, TNF-alpha, and troponin had a sensitive exposure duration of nearly 12 months. Ghrelin and C-peptide were more sensitive to longer-term exposure (>18 months), while NT-proBNP and IL-6 were more sensitive to shorter-term exposure (<6 months).

CONCLUSION

PM2.5 exposure was associated with elevated levels in cardiometabolic biomarkers related to insulin resistance, inflammation, and heart injury. The magnitudes of these associations depended on the exposure duration. The most sensitive exposure durations of different biomarkers varied.

m6A methylation-mediated PGC-1α contributes to ferroptosis via regulating GSTK1 in arsenic-induced hepatic insulin resistance

Arsenic exposure has been closely linked to hepatic insulin resistance (IR) and ferroptosis with the mechanism elusive. Peroxisome proliferator γ-activated receptor coactivator 1-α (PGC-1α) is essential for glucose metabolism as well as for the production of reactive oxygen species (ROS). However, it was unclear whether there is a regulatory connection between PGC-1α and ferroptosis. Besides, the definitive mechanism of arsenic-induced hepatic IR progression remains to be determined. Here, we found that hepatic insulin sensitivity impaired by sodium arsenite (NaAsO2) could be reversed by inhibiting ferroptosis. Mechanistically, we found that PGC-1α suppression inhibited the protein expression of glutathione s-transferase kappa 1 (GSTK1) via nuclear respiratory factor 1 (NRF1), thereby increasing ROS accumulation and promoting ferroptosis. Furthermore, we showed that NaAsO2 induced hepatic IR and ferroptosis via methyltransferase-like 14 (METTL14) and YTH domain-containing family protein 2 (YTHDF2)-mediated N6-methyladenosine (m6A) of PGC-1α mRNA. In conclusion, NaAsO2-mediated PGC-1α suppression was m6A methylation-dependent and induced ferroptosis via the PGC-1α/NRF1/GSTK1 pathway in hepatic IR. The data might provide insight into potential targets for diabetes prevention and treatment.

Fine particulate matter (PM2.5)-induced pulmonary oxidative stress contributes to increases in glucose intolerance and insulin resistance in a mouse model of circadian dyssynchrony

Results of human and animal studies independently suggest that either ambient fine particulate matter (PM2.5) air pollution exposure or a disturbed circadian rhythm (circadian dyssynchrony) are important contributing factors to the rapidly evolving type-2-diabetes (T2D) epidemic. The objective of this study is to investigate whether circadian dyssynchrony increases the susceptibility to PM2.5 and how PM2.5 affects metabolic health in circadian dyssynchrony. We examined systemic and organ-specific changes in glucose homeostasis and insulin sensitivity in mice maintained on a regular (12/12 h light/dark) or disrupted (18/6 h light/dark, light-induced circadian dyssynchrony, LICD) light cycle exposed to air or concentrated PM2.5 (CAP, 6 h/day, 30 days). Exposures during Zeitgeber ZT3-9 or ZT11-17 (Zeitgeber in circadian time, ZT0 = begin of light cycle) tested for time-of-day PM2.5 sensitivity (chronotoxicity). Mice transgenic for lung-specific overexpression of extracellular superoxide dismutase (ecSOD-Tg) were used to assess the contribution of CAP-induced pulmonary oxidative stress. Both, CAP exposure from ZT3-9 or ZT11-17, decreased glucose tolerance and insulin sensitivity in male mice with LICD, but not in female mice or in mice kept on a regular light cycle. Although changes in glucose homeostasis in CAP-exposed male mice with LICD were not associated with obesity, they were accompanied by white adipose tissue (WAT) inflammation, impaired insulin signaling in skeletal muscle and liver, and systemic and pulmonary oxidative stress. Preventing CAP-induced oxidative stress in the lungs mitigated the CAP-induced decrease in glucose tolerance and insulin sensitivity in LICD. Our results demonstrate that circadian dyssynchrony is a novel susceptibility state for PM2.5 and suggest that PM2.5 by inducing pulmonary oxidative stress increases glucose intolerance and insulin resistance in circadian dyssynchrony.

The effects of fine particulate matter, solid fuel use and greenness on the risks of diabetes in middle-aged and older Chinese

BACKGROUND

Previous studies provided clues that environmental factors were closely related to diabetes incidence. However, the evidence from high-quality and large cohort studies about the effects of PM_2.5, solid fuel use and greenness on the development of diabetes among middle-aged and older adults in China was scarce.

OBJECTIVE

To separately investigate the independent effects of PM_2.5, solid fuel use and greenness on the development of diabetes among middle-aged and older adults.

METHODS

A total of 9242 participants were involved in this study extracted from the China Health and Retirement Longitudinal Study. Time-varying Cox regression was applied to detect the association of diabetes with PM_2.5, solid fuel use and greenness, separately. The potential interactive effect of air pollution and greenness were explored using the relative excess risk due to interaction (RERI).

RESULTS

Per 10 μg/m³ increases in PM_2.5 were associated with 6.0% (95% CI: 1.9, 10.2) increasing risks of diabetes incidence. Females seemed to be more susceptible to PM_2.5. However, the effects of solid fuel use only existed in older and lower BMI populations, with hazard ratios (HRs) of 1.404 (1.116, 1.766) and 1.346 (1.057, 1.715), respectively. In addition, exposure to high-level greenness might reduce the risks of developing diabetes [HR = 0.801 (0.687, 0.934)]. Weak evidence of the interaction effect of PM_2.5/solid fuel use and greenness on diabetes was found.

SIGNIFICANCE

Both PM_2.5 and solid fuel use were associated with the increasing incidence of diabetes. In addition, high-level greenness might be a beneficial environmental factor for reducing the risks of developing diabetes. All in all, our findings might provide valuable references for public health apartments to formulate very fruitful policies to reduce the burden of diabetes.

IMPACT STATEMENT

Both PM_2.5 and solid fuel use were associated with the increasing incidence of diabetes while high-level greenness was not, which might provide valuable references for public health apartments to make policies.

The relationship between air pollutants and gestational diabetes: an updated systematic review and meta-analysis

PURPOSE

Air pollution is an environmental stimulus that may predispose pregnant women to gestational diabetes mellitus (GDM). This systematic review and meta-analysis were conducted to investigate the relationship between air pollutants and GDM.

METHODS

PubMed, Web of Science, and Scopus were systematically searched for retrieving English articles published from January 2020 to September 2021, investigating the relationship of exposure to ambient air pollution or levels of air pollutants with GDM and related parameters, including fasting plasma glucose (FPG), insulin resistance, and impaired glucose tolerance. Heterogeneity and publication bias were evaluated using I-squared (I2), and Begg's statistics, respectively. We also performed the subgroup analysis for particulate matters (PM2.5, PM10), Ozone (O3), and sulfur dioxide (SO2) in the different exposure periods.

RESULTS

A total of 13 studies examining 2,826,544 patients were included in this meta-analysis. Compared to non-exposed women, exposure to PM2.5 increases the odds (likelihood of occurrence outcome) of GDM by 1.09 times (95% CI 1.06, 1.12), whereas exposure to PM10 has more effect by OR of 1.17 (95% CI 1.04, 1.32). Exposure to O3 and SO2 increases the odds of GDM by 1.10 times (95% CI 1.03, 1.18) and 1.10 times (95% CI 1.01, 1.19), respectively.

CONCLUSIONS

The results of the study show a relationship between air pollutants PM2.5, PM10, O3, and SO2 and the risk of GDM. Although evidence from various studies can provide insights into the linkage between maternal exposure to air pollution and GDM, more well-designed longitudinal studies are recommended for precise interpretation of the association between GDM and air pollution by adjusting all potential confounders.

A Review of the GSTM1 Null Genotype Modifies the Association between Air Pollutant Exposure and Health Problems

Air pollution is one of the significant environmental risks known as the cause of premature deaths. It has deleterious effects on human health, including deteriorating respiratory, cardiovascular, nervous, and endocrine functions. Exposure to air pollution stimulates reactive oxygen species (ROS) production in the body, which can further cause oxidative stress. Antioxidant enzymes, such as glutathione S-transferase mu 1 (GSTM1), are essential to prevent oxidative stress development by neutralizing excess oxidants. When the antioxidant enzyme function is lacking, ROS can accumulate and, thus, cause oxidative stress. Genetic variation studies from different countries show that GSTM1 null genotype dominates the GSTM1 genotype in the population. However, the impact of the GSTM1 null genotype in modifying the association between air pollution and health problem is not yet clear. This study will elaborate on GSTM1's null genotype role in modifying the relationship between air pollution and health problems.

PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows

Fine particulate matter (PM_2.5) has been linked to gestational diabetes mellitus (GDM). However, PM_2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24^th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24^th gestation week). We aimed to examine differential impacts of PM_2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM_2.5 and its constituents (i.e., sulfate [SO₄ ^2-], ammonium [NH₄ ⁺], nitrate [NO₃ ^-], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM_2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM_2.5, SO₄ ^2-, NH₄ ⁺, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM_2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM_2.5 in the 1^st and 2^nd trimesters, SO₄ ^2- in the 1^st and 2^nd trimesters, and NO₃ ^- in the preconception and 1^st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM_2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.

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.

PM2.5 and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China

BACKGROUND

Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of <2.5μm (PM2.5)] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM2.5, gut microbiota, and metabolic diseases are unclear.

OBJECTIVES

We investigated the associations between personal exposure to PM2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM2.5 and insulin resistance and the mediating effects between PM2.5 and sphingolipid metabolism.

METHODS

We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures (PM2.5) and featured metabolism outcomes.

RESULTS

Our prospective panel study illustrated that exposure to PM2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism.

DISCUSSION

Our findings demonstrated that PM2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM2.5 and IR. https://doi.org/10.1289/EHP9688.

Exposure to air pollutant mixture and gestational diabetes mellitus in Southern California: Results from electronic health record data of a large pregnancy cohort

BACKGROUND

Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.

OBJECTIVES

To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.

METHODS

Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM_2.5), <10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery.

RESULTS

The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM_2.5, PM₁₀, NO₂ and PM_2.5 constituents. The association was strongest for NO₂ [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO₂, PM_2.5, and PM₁₀, OR = 1.095, 95% CI: 1.082-1.108) and PM_2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO₂ (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM_2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers.

CONCLUSION

This study found that exposure to a mixture of ambient PM_2.5, PM₁₀, NO₂, and PM_2.5 chemical constituents was associated with an increased risk of GDM. NO₂ and black carbon PM_2.5 contributed most to GDM risk.

Serum branched-chain amino acids modifies the associations between air pollutants and insulin resistance

Growing evidence supports that air pollution exposure has become a risk factor of type II diabetes mellitus through the induction of insulin resistance (IR), but the presented findings did not provide a consistent relationship between air pollution exposure and IR in the temporal scale and the magnitude. Reported associated with IR and air pollution exposure, branched-chain amino acids (BCAAs) in blood might modify the association between air pollution exposure and IR. We took advantage of an existing panel study on elderly people who were healthy or with pre-diabetes. Amino acids were analyzed from the serum samples using a UPLC-QQQ-MS, and the homeostasis model assessment of insulin resistance (HOMA-IR) values were calculated to represent the levels of IR in each visit. Exposures to PM_2.5, NO₂, SO₂, CO, O₃, and black carbon (BC) were estimated using data from a monitoring station. Linear mixed-effects models were applied to estimate the associations between the air pollution and HOMA-IR, as well as the modifying effects of BCAAs. We found significantly higher concentrations of BCAAs in the pre-diabetic subjects than healthy ones. The concentrations of BCAAs were all significantly associated with HOMA-IR. For subjects with high-level BCAAs, HOMA-IR was positively associated with an IQR increase in PM_2.5, NO₂, BC, and CO at lag day 2 and in PM_2.5, SO₂, NO₂, BC, and CO at lag day 7. While for subjects with low-level BCAAs, there was no significant association observed at any lag day except for CO at lag day 5. The study provided evidence that circulating BCAAs may modify the relationship between air pollution exposure and the level of insulin resistance in humans.

The mediating role of vascular inflammation in traffic-related air pollution associated changes in insulin resistance in healthy adults

AIM

The precise pathophysiologic pathway linking traffic-related air pollution (TRAP) to diabetes mellitus is not well elucidated. We aimed to investigate whether activation of vascular inflammation can be a mechanistic linkage between ambient TRAP and insulin resistance.

METHODS

Study outcomes were determined by assessing a series of circulating biomarkers indicative of insulin resistance and vascular inflammation among 73 healthy adults who underwent repeated clinical visits in Beijing, China, 2014-2016. Concomitantly, concentrations of ambient TRAP indices, including particulate matter in diameter <2.5 μm (PM_2.5), particles in size fractions of 5-560 nm, black carbon, carbon monoxide, nitrogen dioxide, and oxides of nitrogen, were continuously monitored.

RESULTS

Participants experienced extremely high levels of TRAP exposures, with mean (standard deviation) PM_2.5 concentrations of 91.8 (48.3) μg/m³, throughout the study. We found that interquartile range increases in exposure to moving average concentrations of various TRAP indices at prior up to 7 days were associated with significant elevations of 8.9-49.6% in insulin levels. Higher pollutant levels were also related to worsening metrics of insulin resistance (soluble insulin receptor ectodomain, adipokines, and homeostasis model assessment of insulin resistance) and heightened vascular inflammatory responses, particularly disruptions of the receptor activator of nuclear factor κB ligand/osteoprotegerin system balance and elevations of monocyte/macrophage and T cell activation markers. Mediation analyses showed that activation of vascular inflammation could explain up to 66% of the alterations in metrics of insulin resistance attributable to air pollution.

CONCLUSION

Our results suggest that ambient traffic pollution exposure was capable of promoting insulin resistance possibly via generating vascular inflammation.

Association of PM2.5 with Insulin Resistance Signaling Pathways on a Microfluidic Liver-Kidney Microphysiological System (LK-MPS) Device

Insulin resistance (IR) is a typical sign of metabolic dysregulation caused by fine particulate matter (PM_2.5), but the underlying signaling has not been clearly determined. Herein, a microfluidic liver-kidney microphysiological system (LK-MPS) is presented to assess the signaling pathways of IR generated by PM_2.5 at 200 μg/mL for 24 h. The LK-MPS device consisted of a biomimetic liver-kidney architecture and reconstructed two circulation paths: the liver metabolism-kidney excretion (LM-KE) and kidney excretion-liver metabolism (KE-LM), by which PM_2.5 is feasibly distributed in the two organs. Transmission electron microscopy (TEM) analysis revealed that PM_2.5 can embed in the cytoplasm and nuclei, undergo transport by vesicles, and lead to the destruction of mitochondria. Further comprehensive immunofluorescence, enzyme-linked immunosorbent assays (ELISAs) and untargeted metabolomic analyses confirmed that PM_2.5 disturbed the classic IRS-1/AKT signaling pathway (INSR, IRS-1, PI3K, AKT, GLUT2, GLUT4, and FOXO1 downregulated) and IR-related metabolic pathways: UDP-hexosamine (UDP-GlcNAc), gluconeogenesis (β-d-glucose 6-phosphate), and lipid biosynthesis (ceramide (Cer) and triacylglycerol (TG)) pathways, leading to the disorder of glucose levels. Collectively, these disorders aggravate hepatic and renal IR. Pearson's correlation coefficient test showed that elemental carbon (EC), polycyclic aromatic hydrocarbons (PAHs), and metals (Ca, Co, and V) were negatively correlated to the dysregulated proteins (INSR, IRS-1, AKT, FOXO1, GLUT2, and GLUT4). These findings may partially explain IR-related signaling pathways triggered by PM_2.5.

Exposure to fine particulate matter promotes platelet activation and thrombosis via obesity-related inflammation

Short-term exposure to fine particulate matter (PM_2.5) increases thrombotic risk particularly in obese individuals, but the underlying mechanisms remain unclear. This study aims to compare the effects of PM_2.5 on inflammation and platelet activation in obese versus normal-weight adults, and investigate potential causal pathways. We conducted a panel study measuring blood markers in 44 obese and 53 normal-weight adults on 3 separate occasions in 2017-2018. Associations between PM_2.5/black carbon (BC) and biomarkers were estimated using mixed-effect models. An interaction analysis compared PM_2.5/BC-related effects between subgroups. Biomarker combinations and mediation analysis were performed to elucidate the biological pathways. There was a significant "low-high-low" trend of PM_2.5 levels across the 3 study periods. Increases in pro-inflammatory cytokines and changes of platelet activation and aggregation markers were associated with PM_2.5/BC in obese subgroup only. Among obese subjects, the combination of pro-inflammatory cytokines and that of platelet markers increased 26.8% (95% CI: 16.0%, 37.9%) and 14.7% (95% CI: 1.9%, 27.0%) per IQR increase in PM_2.5 over 5-day and 7-day averages. Inflammation mediated 24.5% of the pathways through which PM_2.5 promoted platelet activation. This study suggested obese people are susceptible to pro-thrombotic impacts of PM_2.5 exposures. PM_2.5 may aggravate thrombosis through obesity-related inflammation.

Particulate matter air pollutants and cardiovascular disease: Strategies for intervention

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

Associations between the chemical composition of PM2.5 and gestational diabetes mellitus

BACKGROUND

Fine particulate matter (PM_2.5) is a complex mixture of fine particulates with large spatiotemporal heterogeneities in chemical compositions. While PM_2.5 has been associated with gestational diabetes mellitus (GDM), little is known about the relationship between specific chemical components of PM_2.5 and GDM. We examined the associations between GDM and pregnancy exposures to PM_2.5 and its compositions, including sulfate (SO₄^2-), ammonium (NH₄⁺), nitrate (NO₃^-), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS), and to identify critical windows of exposure.

METHODS

We used data from the 2005-2015 Florida Vital Statistics Birth Records. A well-validated geoscience-derived model was used to estimate women's pregnancy exposures to PM_2.5 and its compositions. Distributed lag models were used to examine the associations and to identify the critical windows of exposure.

RESULTS

A total of 2,078,669 women were included. In single-pollutant models, after controlling for potential confounders, positive associations between PM_2.5 and GDM were observed during the second trimester of pregnancy. We found positive associations between SO₄^2-, NH₄⁺, NO₃^-, OM and BC, with largest effect sizes observed in the 21-24 weeks of pregnancy. Negative associations were observed for DUST and SS. Consistent results for NH₄⁺, OM, DUST and SS were observed in the multi-pollutant models.

CONCLUSIONS

Exposures to PM_2.5 and its compositions (mainly NH₄⁺, OM) during the second trimester are positively associated with GDM, especially for exposures during the 21-24 weeks of pregnancy. Further studies are needed to confirm the findings and examine the underlying mechanisms.

PM2.5 and Diabetes in the Japanese Population

Growing evidence suggests that PM_2.5 is associated with diabetes mellitus (DM). Although DM is a major public health concern, there has not yet been a study of this association in Japan. We used health examination data from 66,885 individuals in Tokyo, Japan 2005–2019. Cox proportional hazards models were used to evaluate an association between annual exposure to PM_2.5 and glycated hemoglobin A_1c (HbA_1c), or fasting plasma glucose (FPG). An increase of 1 μg/m³ in the annual average of PM_2.5 concentration was associated (HR = 1.029; 95% CI = 1.004–1.055) with an increase in diabetes (incident + prevalent). For incident DM, a greater PM_2.5 level was associated with more DM (HR = 1.029; 95% CI, 1.003–1.055). Compared to HbA_1c, FPG showed a stronger association with the annual exposure to PM_2.5 (HR = 1.065; 95% CI, 1.040–1.091). We found that greater exposure to PM_2.5 in the long-term was associated with an increased risk of diabetes, and that the magnitude of association became stronger as the exposure duration increased. Omorogieva Ojo

Nontraditional Risk Factors for Obesity in Modern Society

Overweight and obesity, which have rapidly increased around the world in recent years, are significant health problems. They can lead to various morbidities, including cardiovascular diseases, cerebrovascular diseases, type 2 diabetes, some types of cancer, and even death. Obesity is caused by an energy imbalance due to excessive calorie intake and insufficient energy consumption, and genetic factors and individual behavioral problems are also known to be major contributing factors. However, these are insufficient to explain the surge in obesity that has occurred in recent decades. Recent studies have suggested that environmental factors arising from the process of socioeconomic development and modernization contribute to this phenomenon. These environmental factors include light pollution due to artificial lighting, air pollution, endocrine-disrupting chemicals, and reduced exposure to green spaces due to urbanization of residential areas. In this manuscript, the findings and mechanisms of these novel risk factors causing overweight and obesity are reviewed.

Endothelial progenitor cells as critical mediators of environmental air pollution-induced cardiovascular toxicity

Environmental air pollution exposure is a leading cause of death worldwide, and with increasing industrialization and urbanization, its disease burden is expected to rise even further. The majority of air pollution exposure-associated deaths are linked to cardiovascular disease (CVD). Although ample research demonstrates a strong correlation between air pollution exposure and CVD risk, the mechanisms by which inhalation of polluted air affects cardiovascular health are not completely understood. Inhalation of environmental air pollution has been associated with endothelial dysfunction, which suggests that air pollution exposure impacts CVD health by inducing endothelial injury. Interestingly, recent studies demonstrate that air pollution exposure affects the number and function of endothelial progenitor cells (EPCs), subpopulations of bone marrow-derived proangiogenic cells that have been shown to play an essential role in maintaining cardiovascular health. In line with their beneficial function, chronically low levels of circulating EPCs and EPC dysfunction (e.g., in diabetic patients) have been associated with vascular dysfunction, poor cardiovascular health, and increases in the severity of cardiovascular outcomes. In contrast, treatments that improve EPC number and function (e.g., exercise) have been found to attenuate cardiovascular dysfunction. Considering the critical, nonredundant role of EPCs in maintaining vascular health, air pollution exposure-induced impairments in EPC number and function could lead to endothelial dysfunction, consequently increasing the risk for CVD. This review article covers novel aspects and new mechanistic insights of the adverse effects of air pollution exposure on cardiovascular health associated with changes in EPC number and function.

Association of fine particulate matter with glucose and lipid metabolism: a longitudinal study in young adults

OBJECTIVES

This study aimed to evaluate whether PM2.5 exposure in a highly polluted area (>100 µg/m3) affects glucose and lipid metabolism in healthy adults.

METHODS

We recruited 110 healthy adults in Baoding city, Hebei, China, and followed them up between 2017 and 2018. Personal air samplers were used to monitor personal PM2.5 levels. Eight glucose and lipid metabolism parameters were quantified. We performed the linear mixed-effect models to investigate the relationships between PM2.5 and glucose and lipid metabolism parameters. Stratified analyses were further performed according to sex and body mass index (BMI).

RESULTS

The concentration of PM2.5 was the highest in spring, with a median of 232 μg/m3 and the lowest in autumn (139 μg/m3). After adjusting for potential confounders, we found that for each twofold increase in PM2.5, the median of insulin concentration decreased by 5.89% (95% CI -10.91% to -0.58%; p<0.05), and ox-LDL increased by 6.43% (95% CI 2.21% to 10.82%; p<0.05). Stratified analyses indicated that the associations were more pronounced in females, overweight and obese participants.

CONCLUSIONS

Exposure to high PM2.5 may have deleterious effects on glucose and lipid metabolism. Females, overweight and obese participants are more vulnerable.

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.

Associations between changes in adipokines and exposure to fine and ultrafine particulate matter in ambient air in Beijing residents with and without pre-diabetes

OBJECTIVE

Exposure to particulate matter (PM) is a risk factor to diabetes, but the underlying mechanism is unclear. Adipokines play important roles in glucose metabolism. This study examined the associations between short-term exposure to ambient PM and adipokine levels and evaluated whether metabolic disorders could enhance susceptibility to PM-induced health effects.

RESEARCH DESIGN AND METHODS

In a panel study (SCOPE, Study Comparing the Cardiometabolic and Respiratory Effects of Air Pollution Exposure on Healthy and Pre-diabetic Individuals) in Beijing, China, 60 pre-diabetic individuals and 60 healthy controls completed two to seven clinical visits. The associations between serum adiponectin, leptin, and resistin levels and the moving average (MA) mass concentration of PM_2.5 and number concentrations of ultrafine particles (UFP) and accumulation-mode particles (AMP) during the 1-14 days prior to clinical visits, and the effects of metabolic disorders on any such associations, were evaluated using a linear mixed-effects model.

RESULTS

Short-term exposure to ambient UFP and AMP was inversely associated with adipokine levels at 1-14 days prior to clinical visits. For example, each IQR increment in 1 day MA UFP exposure (6.0×10³/cm³) was associated with -14.0% (95% CI -20.9%, -6.4%), -6.6% (95% CI -12.4%, -0.4%), and -8.5% (95% CI -14.5%, -2.2%) changes in adiponectin, leptin, and resistin levels, respectively. There was no significant association between adipokine levels and PM_2.5 exposure. UFP and AMP exposure was associated with a greater decrease in adiponectin level and a weaker change in leptin level among participants with high insulin resistance levels. Glucose status did not modify PM-induced changes in adipokine levels.

CONCLUSION

High level of insulin resistance could aggravate the adverse metabolic impact of exposure to UFP and AMP.

Repetitive Ozone Exposures and Evaluation of Pulmonary Inflammation and Remodeling in Diabetic Mouse Strains

BACKGROUND

Epidemiological studies support the hypothesis that diabetes alters pulmonary responses to air pollutants like ozone (O 3 ). The mechanism(s) underlying these associations and potential links among diabetes, O 3 , and lung inflammation and remodeling are currently unknown.

OBJECTIVES

The goal was to determine whether pulmonary responses to repetitive ozone exposures are exacerbated in murine strains that are hyperglycemic and insulin resistant.

METHODS

Normoglycemic and insulin-sensitive C57BL/6J mice; hyperglycemic, but mildly insulin-resistant, KK mice; and hyperglycemic and markedly insulin-resistant KKAy mice were used for ozone exposure studies. All animals were exposed to filtered air (FA) or repetitive ozone (0.5  ppm O 3 , 4 h/d, for 13 consecutive weekdays). Tissue analysis was performed 24 h following the final exposure. This analysis included bronchoalveolar lavage (BAL) for cell and fluid analysis, and tissue for pathology, immunohistology, mRNA, and hydroxyproline.

RESULTS

Following repetitive O 3 exposure, higher bronchoalveolar lavage fluid inflammatory cells were observed in all mice (KKAy > KK > C 57 BL / 6 ), with a notable influx of neutrophils and eosinophils in KK and KKAy mice. Although the lungs of O 3 -exposed C57BL/6J and KK mice had minimal centriacinar histological changes without fibrosis, the lungs of O 3 -exposed KKAy mice contained marked epithelial hyperplasia in proximal alveolar ducts and adjacent alveoli with associated centriacinar fibrosis. Fibrosis in O 3 -exposed KKAy lungs was confirmed with immunohistochemistry, tissue hydroxyproline content, and tissue mRNA expression of fibrosis-associated genes (Ccl11, Il13, and Mmp12). Immunofluorescence staining and confocal microscopy revealed alterations in the structure and composition of the airway and alveolar epithelium in regions of fibrosis.

DISCUSSION

Our results demonstrate that in diabetic animal strains repetitive ambient ozone exposure led to early and exaggerated pulmonary inflammation and remodeling. Changes in distal and interstitial airspaces and the activation of Th2 inflammatory and profibrotic pathways in experimental animals provide a preliminary, mechanistic framework to support the emerging epidemiological associations among air pollution, diabetes, and lung disease. https://doi.org/10.1289/EHP7255.

Effect of ambient air pollution on the incidence of colorectal cancer among a diabetic population: a nationwide nested case-control study in Taiwan

OBJECTIVES

An increasing number of studies had shown that air pollution exposure may aggravate blood glucose control in patients with diabetes, an independent risk factor for colorectal cancer (CRC) proposed by some researchers. This study aimed to investigate the impact of exposure to ambient particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5) on the incidence of CRC among a diabetic population.

DESIGN

A nested case-control study.

SETTING

A subset data retrieved from the Taiwan's National Health Insurance Research Database.

PARTICIPANTS

We identified patients with newly diagnosed diabetes (n=1 164 962) during 1999-2013. Participants who had subsequently developed an incident of CRC were placed into the case group, while controls were matched to the cases at a 4:1 ratio by age, gender, date of diabetes diagnosis and the index date of CRC diagnosis.

METHODS AND OUTCOME MEASURES

All variables associated with the risk of CRC entered into a multinomial logistic regression model. The dose-response relationship between various average concentrations of PM_2.5 exposure and the incidence of CRC was estimated by logistic regression.

RESULTS

The study included a total of 7719 incident CRC cases matched with 30 876 controls of random sampling. The mean annual concentration of PM_2.5 was 35.3 µg/m³. After adjusting for potential confounders, a dose-response relationship was observed between the CRC risks and each interquartile increase of PM_2.5 concentration (Q1-Q2: 1.03 (0.95-1.11), Q2-Q3: 1.06 (0.98-1.15), ≥Q3: 1.19 (1.10-1.28) in model 2. The adjusted ORs (95% CI) of CRC incidence for each 10 µg/m³ increment of PM_2.5 was 1.08 (1.04-1.11). Moreover, a faster growing adapted Diabetes Complications Severity Index (aDCSI) score was noticed in CRC group compared with the controls, which also showed a significant association in our multivariate analysis (adjusted OR=1.28, 95% CI 1.18 to 1.38).

CONCLUSIONS

Long-term exposure to high concentrations of PM_2.5 may contribute to an increased incidence of CRC among diabetic populations.

Cardiovascular adaptations to particle inhalation exposure: molecular mechanisms of the toxicology

Ambient air, occupational settings, and the use and distribution of consumer products all serve as conduits for toxicant exposure through inhalation. While the pulmonary system remains a primary target following inhalation exposure, cardiovascular implications are exceptionally culpable for increased morbidity and mortality. The epidemiological evidence for cardiovascular dysfunction resulting from acute or chronic inhalation exposure to particulate matter has been well documented, but the mechanisms driving the resulting disturbances remain elusive. In the current review, we aim to summarize the cellular and molecular mechanisms that are directly linked to cardiovascular health following exposure to a variety of inhaled toxicants. The purpose of this review is to provide a comprehensive overview of the biochemical changes in the cardiovascular system following particle inhalation exposure and to highlight potential biomarkers that exist across multiple exposure paradigms. We attempt to integrate these molecular signatures in an effort to provide direction for future investigations. This review also characterizes how molecular responses are modified in at-risk populations, specifically the impact of environmental exposure during critical windows of development. Maternal exposure to particulate matter during gestation can lead to fetal epigenetic reprogramming, resulting in long-term deficits to the cardiovascular system. In both direct and indirect (gestational) exposures, connecting the biochemical mechanisms with functional deficits outlines pathways that can be targeted for future therapeutic intervention. Ultimately, future investigations integrating "omics"-based approaches will better elucidate the mechanisms that are altered by xenobiotic inhalation exposure, identify biomarkers, and guide in clinical decision making.

Associations of exposure to fine particulate matter during pregnancy with maternal blood glucose levels and gestational diabetes mellitus: Potential effect modification by ABO blood group

BACKGROUND

Previous studies have examined the relationships between prenatal fine particulate matter (PM_2.5) exposure and gestational diabetes mellitus (GDM), but the results were inconsistent. Furthermore, the possible effect modification by ABO blood group has not been explored.

OBJECTIVES

To assess the associations of PM_2.5 exposures during pregnancy with maternal glucose levels as well as GDM, and further to evaluate the potential effect modification by ABO blood group.

METHODS

Between January 2013 and January 2015, 4783 pregnant women were enrolled in our study based on a birth cohort in Wuhan. Daily PM_2.5 exposure levels for each woman during pregnancy were estimated using a spatial-temporal land-use regression model. Linear regressions with general estimating equations (GEE) were performed to assess the associations between trimester-specific PM_2.5 exposures and maternal glucose levels. Modified Poisson regressions with GEE analyses were used to evaluate the impacts of PM_2.5 exposures during each trimester on the risk of GDM. The associations of PM_2.5 exposure during the whole study period with glucose levels and GDM were estimated using multiple linear regression model and modified Poisson regression model, respectively. We conducted a stratified analysis to explore the potential effect modification by ABO blood group.

RESULTS

Among all the 4783 participants, 394 (8.24%) had GDM. Exposure to PM_2.5 was found to be positively associated with elevated fasting glucose level during the whole study period [0.382 mg/dL, 95% confidence interval (CI): 0.179-0.586, per 10 μg/m³ increase in PM_2.5], the first trimester (0.154 mg/dL ,95% CI: 0.017-0.291) and the second trimester (0.541 mg/dL, 95% CI: 0.390-0.692). No statistically significant results were observed between PM_2.5 and 1-h and 2-h glucose levels during any study period. Increased risks of GDM for each 10 μg/m³ increase in PM_2.5 levels were observed during the whole study period [relative risk (RR): 1.120, 95% CI: 1.021-1.228] and the first trimester (RR: 1.074, 95% CI: 1.012-1.141), but not the second trimester (RR: 1.035, 95% CI: 0.969-1.106). Stratified analysis indicated that the associations of PM_2.5 exposures with GDM were more pronounced among pregnant women with blood group A, but no significant effect modifications were observed.

CONCLUSION

Our study enriched epidemiological evidence linking PM_2.5 exposures during pregnancy to elevated maternal glucose levels and increased risk of GDM. More importantly, we first highlighted that the impact of PM_2.5 on GDM might be greater among pregnant women with blood group A.

Ambient air pollution and gestational diabetes mellitus: A review of evidence from biological mechanisms to population epidemiology

Gestational diabetes mellitus (GDM) is a serious complication of pregnancy that could cause adverse health effects on both mothers and fetuses, and its prevalence has been increasing worldwide. Experimental and epidemiological studies suggest that air pollution may be an important risk factor of GDM, but conclusions are inconsistent. To provide a comprehensive overview of ambient air pollution on GDM, we summarized existing evidence concerning biological linkages between maternal exposure to air pollutants and GDM based on mechanism studies. We also performed a quantitative meta-analysis based on human epidemiological studies by searching English databases (Pubmed, Web of Science and Embase) and Chinese databases (Wanfang, CNKI). As a result, the limited mechanism studies indicated that β-cell dysfunction, neurohormonal disturbance, inflammation, oxidative stress, imbalance of gut microbiome and insulin resistance may be involved in air pollution-GDM relationship, but few studies were performed to explore the direct biological linkage. Additionally, a total of 13 epidemiological studies were included in the meta-analysis, and the air pollutants considered included PM_2.5, PM₁₀, SO₂, NO₂ and O₃. Most studies were retrospective and mainly conducted in developed regions. The results of meta-analysis indicated that maternal first trimester exposure to SO₂ increased the risk of GDM (standardized odds ratio (OR) = 1.392, 95% confidence intervals (CI): 1.010, 1.773), while pre-pregnancy O₃ exposure was inversely associated with GDM risk (standardized OR = 0.981, 95% CI: 0.977, 0.985). No significant effects were observed for PM_2.5, PM₁₀ and NO₂. In conclusion, additional mechanism studies on the molecular level are needed to provide persuasive rationale underlying the air pollution-GDM relationship. Moreover, other important risk factors of GDM, including maternal lifestyle and road traffic noise exposure that may modify the air pollution-GDM relationship should be considered in future epidemiological studies. More prospective cohort studies are also warranted in developing countries with high levels of air pollution.

Relationship betweentemporal distribution of air pollution exposure and glucose homeostasis during pregnancy

BACKGROUND

Mounting evidence has demonstrated that air pollution exposure is associated with the increased prevalence of gestational diabetes mellitus (GDM). However, the long-term exposure effect and the time window of the maximum effect of these air pollutants on GDM and glucose homeostasis during pregnancy are unclear.

METHODS

We conducted this study on 5427 nondiabetic pregnant women who were admitted from three hospitals in Hefei City, China, between 2015 and 2018. The data regarding the average exposure to particulate matter (PM), sulfur dioxide (SO₂), and ozone (O₃) were estimated in a fixed monitoring station in Hefei. We used logistic regression and multiple linear regression to assess the effects of air pollutants on GDM and glucose homeostasis.

RESULTS

Of the 5427 participants, 1119 (20.6%) had GDM. We found prepregnancy exposure to air pollutants was associated with the risk of GDM in the single pollutant model [odds and 95% confidence interval (CI) of GDM for an interquartile range (IQR) increase was 1.24 (1.06-1.45) for PM_2.5, 1.42 (1.26-1.59) for PM₁₀, 1.21 (1.10-1.33) for SO₂ and1.19 (1.08-1.31) for O₃]. The risk of GDM before pregnancy was higher with long-term exposure to high-concentration pollutants compared with the risk in pregnant women who were not exposed to high-concentration pollutants (χ² = 41.52, p for trend <0.0001); the ORs and 95% CI values for the exposure times of 1, 2, and 3 months were 1.28 (0.96-1.72), 1.52 (1.06-2.19), and 1.69 (1.11-2.57), respectively. The results showed a positive effect of exposure to higher-concentration air pollutants 1 year before pregnancy on glucose homeostasis during pregnancy. The time windows of the maximum effect of PM_2.5, PM₁₀, SO₂, and O₃ on GDM were different. The time windows of the maximum effect of PM_2.5, PM₁₀, and SO₂ were 6 months, 5 months, and 1 month before the last menstrual period (LMP) and 3 months after the LMP, respectively. The time windows of the maximum effect of air pollution on glucose homeostasis indicators from the 2-h 75-g oral glucose tolerance test were similar to the abovementioned results.

CONCLUSIONS

Prepregnancy long-term air pollution exposure was associated with a higher risk of developing GDM by affecting glucose metabolism. The time window of the maximum effect of PM on GDM and glucose metabolism indicators was observed earlier than that of SO₂ and O₃.

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 μg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5.

Exposure to ambient fine particulate matter is associated with changes in fasting glucose and lipid profiles: a nationwide cohort study

BACKGROUND

Ambient fine particulate matter is a rising concern for global public health. It was recently suggested that exposure to fine particulate matter may contribute to the development of diabetes and dyslipidaemia. This study aims to examine the potential associations of ambient particulate matter exposure with changes in fasting glucose and lipid profiles in Koreans.

METHOD

We used the data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC), a nationwide database representative of the Korean population. A total of 85,869 individuals aged ≥20 years were included. Multiple regression analyses were conducted to assess the associations between exposure to particulate matter and changes in fasting glucose and lipid profiles at 2-year intervals after adjusting for confounders.

RESULTS

Significant associations were observed between an increase in interquartile range for particulate matter < 2.5 μm in diameter (PM_2.5) and elevated levels of fasting glucose and low-density lipoprotein cholesterol (p for trend = 0.015 and 0.010, respectively), while no association for particulate matter sized 2.5-10 μm in diameter (PM_10-2.5) was noted after adjusting for the other covariates. Sub-group analyses showed stronger associations in individuals who were older (≥60 years) or physically inactive.

CONCLUSIONS

Fine particulate matter exposure affects worsening fasting glucose and low-density lipoprotein cholesterol levels, with no evidence of an association for coarse particulate matter.

The relationship between long-term exposure to PM2.5 and fasting plasma glucose levels in Chinese children and adolescents aged 6-17 years: A national cross-sectional study

BACKGROUND

Previous studies investigating the association between PM_2.5 exposure and fasting plasma glucose levels (FPGLs) are mostly limited to short- and mid-term PM_2.5 exposure and lack adjustments for key confounders in adult research.

OBJECTIVES

Exploring the relationship between seven years long-term PM_2.5 exposure and FPGLs in Chinese children and adolescents aged 6-17 years.

METHODS

Between September 2013 and December 2013, 16,489 participants aged 6-17 years were recruited using a four-staged, stratified, cluster sampling strategy from 7 provinces, autonomous regions and municipalities of mainland China. A generalized linear mixed model (GLMM) was used to estimate the relationship between annual PM_2.5 exposure (2007-2013) and FPGLs stratified by sex and one-year age increments. Sociodemographic characteristics, living with both parents, early-life factors, behaviours, and infection symptoms were gradually adjusted from the crude model to regression model 6, and BMI was adjusted for in model 7.

RESULTS

The annual concentration of PM_2.5 was 56.23 (±12.99) μg/m³. The mean FPGLs in the 8551 boys (4.75 mmol/L ± 0.52) was significantly higher than that in the 8194 girls (4.63 mmol/L ± 0.48) (P < 0.0001). In model 6, for every 10 μg/m3 increase in PM_2.5 exposure, the FPGLs in boys and girls increased by 0.048 (95% CIs 0.031 to 0.065) mmol/L (P < 0.0001) and 0.054 (95% CIs 0.039 to 0.069) mmol/L (P < 0.0001), respectively. The FPGLs were significantly positively associated with long-term PM_2.5 exposure at the ages of 12, 15 and 16 years in both the boys and girls and exhibited age differences in model 7. The prevalence of impaired fasting plasma glucose (IFP) and diabetes decreased by 0.8% when the exposure concentration of PM_2.5 was reduced by 10 μg/m³ in model 6, which assessed the negative effects of PM_2.5 exposure and revealed that 1,298,920 children and adolescents could have been protected from IFP and diabetes in 2013 in China.

CONCLUSIONS

Long-term PM_2.5 exposure may be an independent risk factor of elevated FPGLs. The adverse effect of PM_2.5 exposure on FPGLs in children and adolescents could appear after 10 years of cumulative exposure. The precise intervention time was revealed as approximately 12 and 11 years in boys and girls, respectively. There are great public health implications associated with early prevention strategies for the eradication of the negative effects of long-term exposure to PM_2.5 on FPGLs.

Air pollution and gestational diabetes mellitus: evidence from cohort studies

Exposure to different air pollutants has been linked to type 2 diabetes mellitus, but the evidence for the association between air pollutants and gestational diabetes mellitus (GDM) has not been systematically evaluated. We systematically retrieved relevant studies from PubMed, Embase, and the Web of Science, and performed stratified analyses and regression analyses. Thirteen studies were analyzed, comprising 1 547 154 individuals from nine retrospective studies, three prospective studies, and one case-control study. Increased exposure to particulate matter ≤2.5 µm in diameter (PM_2.5) was not associated with the increased risk of GDM (adjusted OR 1.03, 95% CI 0.99 to 1.06). However, subgroup analysis showed positive correlation of PM_2.5 exposure in the second trimester with an increased risk of GDM (combined OR 1.07, 95% CI 1.00 to 1.13). Among pollutants other than PM_2.5, significant association between GDM and nitrogen dioxide (NO₂) (OR 1.05, 95% CI 1.01 to 1.10), nitrogen oxide (NO_x) (OR 1.03, 95% CI 1.01 to 1.05), and sulfur dioxide (SO₂) (OR 1.09, 95% CI 1.03 to 1.15) was noted. There was no significant association between exposure to black carbon or ozone or carbon monoxide or particulate matter ≤10 µm in diameter and GDM. Thus, systematic review of existing evidence demonstrated association of exposure to NO₂, NO_x, and SO₂, and the second trimester exposure of PM_2.5 with the increased risk of GDM. Caution may be exercised while deriving conclusions from existing evidence base because of the limited number and the observational nature of studies.

Effects of ambient particulate matter on fasting blood glucose: A systematic review and meta-analysis

Studies have found that ambient particulate matter (PM) affects fasting blood glucose. However, the results are not consistent. We conducted a systematic review and meta-analysis to determine the relationship between PM with an aerodynamic diameter of 10 μm or less (PM₁₀) and PM with an aerodynamic diameter of 2.5 μm or less (PM_2.5) and fasting blood glucose. We searched PubMed, Web of Science, the Wanfang Database and the China National Knowledge Infrastructure up to April 1, 2019. A total of 24 papers were included in the review, and 17 studies with complete or convertible quantitative information were included in the meta-analysis. The studies were divided into groups by PM size fractions (PM₁₀ and PM_2.5) and length of exposure. Long-term exposures were based on annual average concentrations, and short-term exposures were those lasting less than 28 days. In the long-term exposure group, fasting blood glucose increased 0.10 mmol/L (95% CI: 0.02, 0.17) per 10 μg/m³ of increased PM₁₀ and 0.23 mmol/L (95% CI: 0.01, 0.45) per 10 μg/m³ of increased PM_2.5. In the short-term exposure group, fasting blood glucose increased 0.02 mmol/L (95% CI: -0.01, 0.04) per 10 μg/m³ of increased PM₁₀ and 0.08 mmol/L (95% CI: 0.04, 0.11) per 10 μg/m³ of increased PM_2.5. Further prospective studies are needed to explore the relationship between ambient PM exposure and fasting blood glucose.

Association between environmental quality and diabetes in the USA

AIMS/INTRODUCTION

Caloric excess and physical inactivity fail to fully account for the rise of diabetes prevalence. Individual environmental pollutants can disrupt glucose homeostasis and promote metabolic dysfunction. However, the impact of cumulative exposures on diabetes risk is unknown.

MATERIALS AND METHODS

The Environmental Quality Index, a county-level index composed of five domains, was developed to capture the multifactorial ambient environmental exposures. The Environmental Quality Index was linked to county-level annual age-adjusted population-based estimates of diabetes prevalence rates. Prevalence differences (PD, annual difference per 100,000 persons) and 95% confidence intervals (CI) were estimated using random intercept mixed effects linear regression models. Associations were assessed for overall environmental quality and domain-specific indices, and all analyses were stratified by four rural-urban strata.

RESULTS

Comparing counties in the highest quintile/poorest environmental quality to those in the lowest quintile/best environmental quality, counties with poor environmental quality demonstrated lower total diabetes prevalence rates. Associations varied by rural-urban strata; overall better environmental quality was associated with lower total diabetes prevalence rates in the less urbanized and thinly populated strata. When considering all counties, good sociodemographic environments were associated with lower total diabetes prevalence rates (prevalence difference 2.77, 95% confidence interval 2.71-2.83), suggesting that counties with poor sociodemographic environments have an annual prevalence rate 2.77 per 100,000 persons higher than counties with good sociodemographic environments.

CONCLUSIONS

Increasing attention has focused on environmental exposures as contributors to diabetes pathogenesis, and the present findings suggest that comprehensive approaches to diabetes prevention must include interventions to improve environmental quality.

Population-Based Study of Traffic-Related Air Pollution and Obesity in Mexican Americans

OBJECTIVE

The purpose of this study was to assess the cross-sectional association between residential exposure to traffic-related air pollution and obesity in Mexican American adults.

METHODS

A total of 7,826 self-reported Mexican Americans aged 20 to 60 years old were selected from the baseline survey of the MD Anderson Mano-a-Mano Mexican American Cohort. Concentrations of traffic-related particulate matter with aerodynamic diameter  < 2.5 μm were modeled at geocoded residential addresses using a dispersion models. The residential proximity to the nearest major road was calculated using a Geographic Information System. Linear and logistic regression models were used to estimate the adjusted associations between exposure and obesity, defined as BMI ≥ 30.

RESULTS

More than half (53.6%) of the study participants had BMI ≥ 30, with a higher prevalence in women (55.0%) than in men (48.8%). Overall higher traffic-related air pollution exposures were associated with lower BMI in men but higher BMI in women. By stratifying for those who lived in a 0- to 1,500-m road buffer, the one-interquartile-range (685.1 m) increase of distance to a major road had a significant association with a 0.58-kg/m² lower BMI (95% CI: -0.92 to -0.24) in women.

CONCLUSIONS

Exposure to intensive traffic is associated with increased risk of obesity in Mexican American women.

Benzene Exposure Induces Insulin Resistance in Mice

Benzene is a ubiquitous pollutant associated with hematotoxicity but its metabolic effects are unknown. We sought to determine if and how exposure to volatile benzene impacted glucose handling. We exposed wild type C57BL/6 mice to volatile benzene (50 ppm × 6 h/day) or HEPA-filtered air for 2 or 6 weeks and measured indices of oxidative stress, inflammation, and insulin signaling. Compared with air controls, we found that mice inhaling benzene demonstrated increased plasma glucose (p = .05), insulin (p = .03), and HOMA-IR (p = .05), establishing a state of insulin and glucose intolerance. Moreover, insulin-stimulated Akt phosphorylation was diminished in the liver (p = .001) and skeletal muscle (p = .001) of benzene-exposed mice, accompanied by increases in oxidative stress and Nf-κb phosphorylation (p = .025). Benzene-exposed mice also demonstrated elevated levels of Mip1-α transcripts and Socs1 (p = .001), but lower levels of Irs-2 tyrosine phosphorylation (p = .0001). Treatment with the superoxide dismutase mimetic, TEMPOL, reversed benzene-induced effects on oxidative stress, Nf-κb phosphorylation, Socs1 expression, Irs-2 tyrosine phosphorylation, and systemic glucose intolerance. These findings suggest that exposure to benzene induces insulin resistance and that this may be a sensitive indicator of inhaled benzene toxicity. Persistent ambient benzene exposure may be a heretofore unrecognized contributor to the global human epidemics of diabetes and cardiovascular disease.

PM2.5 aggravates diabetes via the systemically activated IL-6-mediated STAT3/SOCS3 pathway in rats' liver

PM_2.5 exposure aggravates type 2 diabetes, in which inflammatory factors play an important role. In this study, we aimed to explore the mechanisms responsible for aggravating diabetes after PM_2.5 exposure, and study the roles of inflammatory factors in insulin-resistant type 2 diabetes. Our study indicated that short-time PM_2.5 exposure enhances insulin resistance in type 2 diabetic rats and significantly raises inflammatory factors, including IL-6, TNF-α, and MCP-1, in lungs. However, we found that of these inflammatory factors only IL-6 levels are elevated in blood, liver, adipose tissue, and macrophages, but not in skeletal muscle. IL-6 induced activation of the STAT3/SOCS3 pathway in liver, but not other downstream pathways including STAT1, ERK1/2, and PI3K. Both STAT3 inhibition and IL-6 neutralization effectively alleviated the disorders of glucose metabolism after PM_2.5 exposure. Taken together, this suggests that the systemic increase in IL-6 may play an important role in the deterioration of the type 2 diabetes via IL-6/STAT3/SOCS3 pathway in liver after short-time exposure to PM_2.5. Besides, we unexpectedly found a stronger resistance to the PM_2.5 exposure-induced increase in IL-6 in skeleton muscle than those of many other tissues.

Association of Prenatal and Perinatal Exposures to Particulate Matter With Changes in Hemoglobin A1c Levels in Children Aged 4 to 6 Years

IMPORTANCE

Environmental risk factors for childhood type 2 diabetes, an increasing global problem, are understudied. Air pollution exposure has been reported to be a risk factor for this condition.

OBJECTIVE

To examine the association between prenatal and perinatal exposures to fine particulate matter with a diameter less than 2.5 μm (PM2.5) and changes in hemoglobin A1c (HbA1c), a measure of glycated hemoglobin and marker of glucose dysregulation, in children aged 4 to 7 years.

DESIGN, SETTING, AND PARTICIPANTS

The Programming Research in Obesity, Growth, Environment, and Social Stressors (PROGRESS) study, a birth cohort study conducted in Mexico City, Mexico, recruited pregnant women from July 3, 2007, to February 21, 2011, through public health maternity clinics. The present analysis includes 365 mother-child pairs followed up until the child was approximately 7 years of age. This study included data from only study visits at approximately 4 to 5 years (visit 1) and 6 to 7 years (visit 2) post partum because HbA1c levels were not measured in earlier visits. The data were analyzed from March 11, 2018, to May 3, 2019.

EXPOSURES

Daily PM2.5 exposure estimates at participants' home addresses from 4 weeks prior to mothers' date of last menstrual period (LMP), a marker of the beginning of pregnancy, to 12 weeks after the due date. Exposure was estimated from satellite measurements and calibrated against ground PM2.5 measurements, land use, and meteorological variables.

MAIN OUTCOMES AND MEASURES

Outcomes included HbA1c levels at 4 to 5 years and 6 to 7 years of age, and the change in the level from the former age group to the latter.

RESULTS

The sample included 365 children, of whom 184 (50.4%) were girls. The mean (range) age of the children was 4.8 (4.0-6.4) years at visit 1, and 6.7 (6.0-9.7) years at visit 2. At the time of delivery, the mean (range) age of the mothers was 27.7 (18.3-44.4) years, with a mean (range) prepregnancy body mass index of 26.4 (18.5-43.5). The mean (SD) prenatal PM2.5 exposure (22.4 μg/m3 [2.7 μg/m3]) was associated with an annual increase in HbA1c levels of 0.25% (95% CI, 0.004%-0.50%) from age 4 to 5 years to 6 to 7 years compared with exposure at 12 μg/m3, the national regulatory standard in Mexico. Sex-specific effect estimates were statistically significant for girls (β = 0.21%; 95% CI, 0.10% to 0.32%) but not for boys (β = 0.31%; 95% CI, -0.09% to 0.72%). The statistically significant windows of exposure were from week 28 to 50.6 after the mother's LMP for the overall cohort and from week 11 to the end of the study period for girls. Lower HbA1c levels were observed at age 4 to 5 years in girls (β = -0.72%; 95% CI, -1.31% to -0.13%, exposure window from week 16 to 37.3) and boys (β = -0.98%; 95% CI, -1.70% to -0.26%, exposure window from the beginning of the study period to week 32.7), but no significant association was found in the overall cohort (β = -0.13%; 95% CI, -1.27% to 1.01%). There was no significant association between PM2.5 exposure and HbA1c level at age 6 to 7 years in any group.

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that prenatal and perinatal exposures to PM2.5 are associated with changes in HbA1c, which are indicative of glucose dysregulation, in early childhood. Further research is needed because this finding may represent a risk factor for childhood or adolescent diabetes.

Air Pollution and Cardiovascular Disease: JACC State-of-the-Art Review

Fine particulate matter <2.5 μm (PM_2.5) air pollution is the most important environmental risk factor contributing to global cardiovascular (CV) mortality and disability. Short-term elevations in PM_2.5 increase the relative risk of acute CV events by 1% to 3% within a few days. Longer-term exposures over several years increase this risk by a larger magnitude (∼10%), which is partially attributable to the development of cardiometabolic conditions (e.g., hypertension and diabetes mellitus). As such, ambient PM_2.5 poses a major threat to global public health. In this review, the authors provide an overview of air pollution and health, including assessment of exposure, impact on CV outcomes, mechanistic underpinnings, and impact of air pollution reduction strategies to mitigate CV risk. The review concludes with future challenges, including the inextricable link between air pollution and climate change, and calls for large-scale trials to allow the promulgation of formal evidence-based recommendations to lower air pollution-induced health risks.