Epidemiological and experimental links between air pollution and type 2 diabetes

Disease types and pathogenic mechanisms induced by PM2.5 in five human systems: An analysis using omics and human disease databases

Atmospheric fine particulate matter (PM2.5) can harm various systems in the human body. Due to limitations in the current understanding of epidemiology and toxicology, the disease types and pathogenic mechanisms induced by PM2.5 in various human systems remain unclear. In this study, the disease types induced by PM2.5 in the respiratory, circulatory, endocrine, and female and male urogenital systems have been investigated and the pathogenic mechanisms identified at molecular level. The results reveal that PM2.5 is highly likely to induce pulmonary emphysema, reperfusion injury, malignant thyroid neoplasm, ovarian endometriosis, and nephritis in each of the above systems respectively. The most important co-existing gene, cellular component, biological process, molecular function, and pathway in the five systems targeted by PM2.5 are Fos proto-oncogene (FOS), extracellular matrix, urogenital system development, extracellular matrix structural constituent conferring tensile strength, and ferroptosis respectively. Differentially expressed genes that are significantly and uniquely targeted by PM2.5 in each system are BTG2 (respiratory), BIRC5 (circulatory), NFE2L2 (endocrine), TBK1 (female urogenital) and STAT1 (male urogenital). Important disease-related cellular components, biological processes, and molecular functions are specifically induced by PM2.5. For example, response to wounding, blood vessel morphogenesis, body morphogenesis, negative regulation of response to endoplasmic reticulum stress, and response to type I interferon are the top uniquely existing biological processes in each system respectively. PM2.5 mainly acts on key disease-related pathways such as the PD-L1 expression and PD-1 checkpoint pathway in cancer (respiratory), cell cycle (circulatory), apoptosis (endocrine), antigen processing and presentation (female urogenital), and neuroactive ligand-receptor interaction (male urogenital). This study provides a novel analysis strategy for elucidating PM2.5-related disease types and is an important supplement to epidemiological investigation. It clarifies the risks of PM2.5 exposure, elucidates the pathogenic mechanisms, and provides scientific support for promoting the precise prevention and treatment of PM2.5-related diseases.

Public Health Impacts of Ambient Particulate Matter Pollution in Libya from 1990 to 2019: An Analysis of the 2019 Global Burden of Disease (GBD) Study

Air pollution is recognized as a critical global health risk, yet there has been no comprehensive assessment of its impact on public health in Libya until now. This study evaluates the burden of disease associated with ambient particulate matter (PM2.5) in Libya, drawing on data from the Global Burden of Disease Study 2019. By integrating satellite-based estimates, chemical transport models, and ground-level measurements, PM2.5 exposure and its effects on mortality and disability-adjusted life years (DALYs) across the different sexes and all age groups from 1990 to 2019 are estimated. Our findings reveal that the annual population-weighted mean PM2.5 concentration in Libya was 38.6 μg/m3 in 2019, marking a 3% increase since 1990. In the same year, PM2.5 was responsible for approximately 3368 deaths, accounting for 11% of all annual deaths in the country. Moreover, a total of 107,207 DALYs were attributable to PM2.5, with ischemic heart disease being the leading cause, representing 46% of these DALYs. The analysis also highlights a significant burden of years of life lost (YLLs) at 89,113 and years lived with disability (YLDs) at 18,094, due to PM2.5. Given the substantial health risks associated with air pollution, particularly from ambient particulate matter, Libyan authorities must implement effective policies aimed at reducing air pollution to enhance healthcare outcomes and preventive services.

DNA methylation mediates the effects of PM2.5 and O3 on ceramide metabolism: A novel mechanistic link between air pollution and insulin resistance

Insulin resistance (IR), linked to air pollution, is an initial stage of early-onset Type 2 diabetes mellitus (T2DM). While ceramide metabolism plays an important role in IR pathogenesis, the effects of air pollution on this process and its mechanisms remain unclear. We recruited young adults aged 18-30 years to a panel study in Wuhan, China. Using personal portable devices and stationary monitoring stations, we tracked particulate matter with aerodynamic diameters≤ 2.5 µm (PM2.5) and Ozone (O3) levels. Liquid chromatography/mass spectrometry (LC-MS) based metabolomics quantified ceramide metabolism, and Illumina Infinium Human Methylation 850 kBeadChip assay measured deoxyribonucleic acid (DNA) methylation. Linear mixed-effects models assessed relationships of air pollution with i) IR indexes, ii) ceramide metabolism, and iii) DNA methylation. Mediation analysis was subsequently performed to evaluate the potential mediating effect of DNA methylation in the association between air pollution and ceramide metabolism. PM2.5 and O3 were associated with elevated IR. Specifically, each 10 μg/m3 increase in PM2.5 and O3 at lag0-12 h significantly increased triglyceride‑glucose index (TyG index) and TyG-BMI (TyG - Body mass index) by 0.88%, 0.89% and 0.26%, 0.26%, respectively. Furthermore, levels of eight ceramides were altered by air pollution exposure, and nine methylated CpG sites in inflammation genes mediated the effects of air pollution on ceramide metabolism. Our findings imply the existence of a novel mechanism connecting air pollution to IR.

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.

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.

Secular trends in type 2 diabetes mellitus attributable to PM2.5 exposure in China from 1990 to 2019: an age-period-cohort analysis

Secular trends of mortality and disability-adjusted life years (DALY) in type 2 diabetes mellitus (T2DM) attributable to PM2.5 exposure in China remain unclear. This study applied the joinpoint regression analysis and age-period-cohort model to assess the secular trends. There was a slight alternation in age-standardized rate of mortality and DALY in the total population, while the changes were increased in males and decreased in females from 1990 to 2019. Meanwhile, the changes attributable to ambient particular matter pollution exposure (APE) increased significantly and reduced household air pollution from solid fuels exposure (HPE). Longitudinal age curves showed that T2DM mortality and DALY increased with age. Period rate ratios (RR) attributable to APE increased but fell to HPE. Similar trends were observed in the cohort RR. PM2.5 exposure is more harmful to males and older people. The type of air pollution responsible for T2DM has changed from HPE to APE.

The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China

Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.

Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

Background

Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the causality of PM on CVDs and cardiovascular biomarkers, we conducted a Mendelian randomization (MR) analysis.

Method

In this study, we obtained summary-level data for CVDs and cardiovascular biomarkers including atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), ischemic stroke (IS), stroke subtypes, body mass index (BMI), lipid traits, fasting glucose, fasting insulin, and blood pressure from several large genome-wide association studies (GWASs). Then we used two-sample MR to assess the causality of PM on CVDs and cardiovascular biomarkers, 16 single nucleotide polymorphisms (SNPs) for PM2.5 and 6 SNPs for PM10 were obtained from UK Biobank participants. Inverse variance weighting (IVW) analyses under the fixed effects model were used as the main analytical method to calculate MR Estimates, followed by multiple sensitivity analyses to confirm the robustness of the results.

Results

Our study revealed increases in PM2.5 concentration were significantly related to a higher risk of MI (odds ratio (OR), 2.578; 95% confidence interval (CI), 1.611-4.127; p = 7.920 × 10-5). Suggestive evidence was found between PM10 concentration and HF (OR, 2.015; 95% CI, 1.082-3.753; p = 0.027) and IS (OR, 2.279; 95% CI,1.099-4.723; p = 0.027). There was no evidence for an effect of PM concentration on other CVDs. Furthermore, PM2.5 concentration increases were significantly associated with increases in triglyceride (TG) (OR, 1.426; 95% CI, 1.133-1.795; p = 2.469 × 10-3) and decreases in high-density lipoprotein cholesterol (HDL-C) (OR, 0.779; 95% CI, 0.615-0.986; p = 0.038). The PM10 concentration increases were also closely related to the decreases in HDL-C (OR, 0.563; 95% CI, 0.366-0.865; p = 8.756 × 10-3). We observed no causal effect of PM on other cardiovascular biomarkers.

Conclusion

At the genetic level, our study suggested the causality of PM2.5 on MI, TG, as well HDL-C, and revealed the causality of PM10 on HF, IS, and HDL-C. Our findings indicated the need for continued improvements in air pollution abatement for CVDs prevention.

Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization

Backgrounds

Many studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between particulate matter 2.5 (PM2.5) and diabetes based on genetic approaches are scarce. The study estimated the causal relationship between diabetes and PM2.5 using two sample mendelian randomization (TSMR).

Methods

We collected genetic data from European ancestry publicly available genome wide association studies (GWAS) summary data through the MR-BASE repository. The IEU GWAS information output PM2.5 from the Single nucleotide polymorphisms (SNPs) GWAS pipeline using pheasant-derived variables (Consortium = MRC-IEU, sample size: 423,796). The annual relationship of PM2.5 (2010) were modeled for each address using a Land Use Regression model developed as part of the European Study of Cohorts for Air Pollution Effects. Diabetes GWAS information (Consortium = MRC-IEU, sample size: 461,578) were used, and the genetic variants were used as the instrumental variables (IVs). We performed three representative Mendelian Randomization (MR) methods: Inverse Variance Weighted regression (IVW), Egger, and weighted median for causal relationship using genetic variants. Furthermore, we used a novel method called MR Mixture to identify outlier SNPs.

Results

From the IVW method, we revealed the causal relationship between PM2.5 and diabetes (Odds ratio [OR]: 1.041, 95% CI: 1.008-1.076, P = 0.016), and the finding was substantiated by the absence of any directional horizontal pleiotropy through MR-Egger regression (β = 0.016, P = 0.687). From the IVW fixed-effect method (i.e., one of the MR machine learning mixture methods), we excluded outlier SNP (rs1537371) and showed the best predictive model (AUC = 0.72) with a causal relationship between PM2.5 and diabetes (OR: 1.028, 95% CI: 1.006-1.049, P = 0.012).

Conclusion

We identified the hypothesis that there is a causal relationship between PM2.5 and diabetes in the European population, using MR methods.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Lanzhou, China

Studies on the effects of short-term air pollution exposure on hospitalization for type 2 diabetes mellitus (T2DM) are relatively scarce in developing regions. The time-series study was used to explore the acute effects of air pollutants on hospitalization for T2DM in Lanzhou, China. A distribution lag nonlinear model based on the generalized additive model was used to analyze the hospitalization impact of air pollution on T2DM. Stratified analysis by gender, age and season was obtained. The results were indicated as the relative risk (RR) with 95% confidence interval (CI) for single-day lags (from lag0 to lag7) and cumulative lag days (from lag0-1 to lag0-7). The strongest correlations (RR, 95% CI) of hospitalization for T2DM and PM10 (RR = 1.003, 95% CI 1.000, 1.001) at lag7 and NO2 (RR = 1.022, 95% CI 1.000, 1.045) at lag0-4 were observed for an increase of 10 µg/m3 in the concentrations and CO (RR = 1.091, 95% CI 1.017, 1.170) at lag0-4 for an increase of 1 mg/m3 in the concentration. The hazardous impacts of PM10, NO2 and CO were greater for females, people aged ≥ 65 years and in the cold season. However, there was no significant association between PM2.5, SO2 and O38h and the number of hospitalizations for T2DM.

Diesel Exhaust Particle (DEP)-induced glucose intolerance is driven by an intestinal innate immune response and NLRP3 activation in mice

BACKGROUND

We previously found that air pollution particles reaching the gastrointestinal tract elicit gut inflammation as shown by up-regulated gene expression of pro-inflammatory cytokines and monocyte/macrophage markers. This inflammatory response was associated with beta-cell dysfunction and glucose intolerance. So far, it remains unclear whether gut inflammatory changes upon oral air pollution exposure are causally linked to the development of diabetes. Hence, our aim was to assess the role of immune cells in mediating glucose intolerance instigated by orally administered air pollutants.

METHODS

To assess immune-mediated mechanisms underlying air pollution-induced glucose intolerance, we administered diesel exhaust particles (DEP; NIST 1650b, 12 µg five days/week) or phosphate-buffered saline (PBS) via gavage for up to 10 months to wild-type mice and mice with genetic or pharmacological depletion of innate or adaptive immune cells. We performed unbiased RNA-sequencing of intestinal macrophages to elucidate signaling pathways that could be pharmacologically targeted and applied an in vitro approach to confirm these pathways.

RESULTS

Oral exposure to air pollution particles induced an interferon and inflammatory signature in colon macrophages together with a decrease of CCR2^- anti-inflammatory/resident macrophages. Depletion of macrophages, NLRP3 or IL-1β protected mice from air pollution-induced glucose intolerance. On the contrary, Rag2-/- mice lacking adaptive immune cells developed pronounced gut inflammation and glucose intolerance upon oral DEP exposure.

CONCLUSION

In mice, oral exposure to air pollution particles triggers an immune-mediated response in intestinal macrophages that contributes to the development of a diabetes-like phenotype. These findings point towards new pharmacologic targets in diabetes instigated by air pollution particles.

Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey

INTRODUCTION

Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.

METHODS

This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.

RESULTS

A total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.

CONCLUSION

Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions.

Effect of the Combination of Probiotics and Korean Red Ginseng on Diabetic Wound Healing Exposed to Diesel Exhaust Particles(DEPs)

Background and Objectives: Diesel exhaust particles (DEPs) are a major component of air pollution and adversely affect respiratory and cardiovascular disease and diabetic foot ulcers if diabetic patients are exposed to them. There are currently no studies on treating diabetic wounds exposed to DEPs. So, the effect of a combination of probiotics and Korean red ginseng on a diabetic wound model exposed to DEPs was confirmed. Materials and Methods: Rats were randomly divided into three groups according to DEP inhalation concentration and whether they underwent applications of probiotics (PB) and Korean red ginseng (KRG). Wound tissue was collected from all rats, and wound healing was evaluated using molecular biology and histology methods. Results: The wound size of all groups decreased over time, but there was no significant difference. As a result of the molecular biology experiment, the expression of NF-κB p65 on day 7 was significantly higher in group 2 than in the normal control group. As a result of histological analysis, unlike the primary control group, it was confirmed that granule tissue was formed on the 14th day in the normal control group and group 2. Conclusions: The findings in this study suggest that combined treatment with PB and KRG can promote the healing of DEP-exposed diabetic wounds.

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.

Lung versus gut exposure to air pollution particles differentially affect metabolic health in mice

BACKGROUND

Air pollution has emerged as an unexpected risk factor for diabetes. However, the mechanism behind remains ill-defined. So far, the lung has been considered as the main target organ of air pollution. In contrast, the gut has received little scientific attention. Since air pollution particles can reach the gut after mucociliary clearance from the lungs and through contaminated food, our aim was to assess whether exposure deposition of air pollution particles in the lung or the gut drive metabolic dysfunction in mice.

METHODS

To study the effects of gut versus lung exposure, we exposed mice on standard diet to diesel exhaust particles (DEP; NIST 1650b), particulate matter (PM; NIST 1649b) or phosphate-buffered saline by either intratracheal instillation (30 µg 2 days/week) or gavage (12 µg 5 days/week) over at least 3 months (total dose of 60 µg/week for both administration routes, equivalent to a daily inhalation exposure in humans of 160 µg/m³ PM_2.5) and monitored metabolic parameters and tissue changes. Additionally, we tested the impact of the exposure route in a "prestressed" condition (high-fat diet (HFD) and streptozotocin (STZ)).

RESULTS

Mice on standard diet exposed to particulate air pollutants by intratracheal instillation developed lung inflammation. While both lung and gut exposure resulted in increased liver lipids, glucose intolerance and impaired insulin secretion was only observed in mice exposed to particles by gavage. Gavage with DEP created an inflammatory milieu in the gut as shown by up-regulated gene expression of pro-inflammatory cytokines and monocyte/macrophage markers. In contrast, liver and adipose inflammation markers were not increased. Beta-cell secretory capacity was impaired on a functional level, most likely induced by the inflammatory milieu in the gut, and not due to beta-cell loss. The differential metabolic effects of lung and gut exposures were confirmed in a "prestressed" HFD/STZ model.

CONCLUSIONS

We conclude that separate lung and gut exposures to air pollution particles lead to distinct metabolic outcomes in mice. Both exposure routes elevate liver lipids, while gut exposure to particulate air pollutants specifically impairs beta-cell secretory capacity, potentially instigated by an inflammatory milieu in the gut.

Association of long-term exposure to PM2.5 constituents with glucose metabolism in Chinese rural population

BACKGROUND

Evidence on the associations of fine particulate matter (PM_2.5) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM_2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent.

METHODS

A total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015-2017. Three-year averaged concentrations of PM_2.5 mass and its constituents (black carbon (BC), ammonium (NH₄⁺), nitrate (NO₃^-), organic matter (OM), inorganic sulfate (SO₄^2-), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM_2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent.

RESULTS

The adjusted odds ratio (OR) for T2DM associated with 1 μg/m³ increase was 1.02 for PM_2.5 mass, 1.28 for BC, 1.15 for NH₄⁺, 1.08 for NO₃^-, 1.10 for OM, 1.11 for SO₄^2-, and 1.12 for SOIL. Significant associations of PM_2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM_2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m³ increment in the PM_2.5-adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β.

CONCLUSIONS

PM_2.5 mass and its constituents (BC, NH₄⁺, NO₃^-, OM, SO₄^2-, SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Chronic Exposure to Low-Molecular-Weight Polycyclic Aromatic Hydrocarbons Promotes Lipid Accumulation and Metabolic Inflammation

2-naphthol is a low-molecular-weight (LMW) polycyclic aromatic hydrocarbon (PAH) and air pollutant associated with childhood obesity. There has been a recent emergence of studies on the consequences of PAHs on human health. Current epidemiological reports suggest LMW-PAHs may contribute to obesity incidences in children, yet most studies focus on high-molecular-weight PAHs. This study explores 2-naphthol's impact on obesity and obesity-associated metabolic disorders. To investigate 2-naphthol's effect on lipid metabolism and inflammation, we employed 3T3-L1 and BAT1 cell lines to model white and brown adipocytes, respectively, alongside a murine macrophage cell line (RAW264.7). We found that 2-naphthol increased the expression of key adipogenic and lipogenic genes while decreasing lipolytic gene expression in chronically treated 3T3-L1 and BAT1 adipocytes. In addition, chronic 2-naphthol treatment also suppressed adrenergic-stimulated thermogenic gene expression in BAT1 brown adipocytes. In consistence, an increase in lipid accumulation was demonstrated in BODIPY and Oil Red O-stained adipocytes. Additionally, 3T3-L1 adipocytes and RAW264.7 macrophages chronically exposed to 2-naphthol showed upregulated mRNA expression of major inflammatory cytokines (e.g., tumor necrosis factor α (Tnfα), interleukin-1β (Il-1β), and Il-6). In summary, chronic exposure to 2-naphthol stimulates lipid accumulation in adipocytes and inflammation in adipocytes and macrophages. These findings support previous research that demonstrates 2-naphthol has obesogenic potential.

Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus - A cohort study in northern Sweden

Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1-5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM₁₀ (4% [95% CI: -54-137%] per 10 μg/m³), PM₁₀-traffic (2% [95% CI: -6-11%] per 1 μg/m³) and PM_2.5-exhaust (11% [95% CI: -39-103%] per 1 μg/m³). A negative association was found for both PM_2.5 (-18% [95% CI: -99-66%] per 5 μg/m³), but only in the 2nd exposure tertile (-10% [95% CI: -25-9%] compared to the first tertile), and PM_2.5-woodburning (-30% [95% CI: -49-4%] per 1 μg/m³). In two-pollutant models including PM_2.5-woodburning, there was an 11% [95% CI: -11-38%], 6% [95% CI: -16-34%], 13% [95% CI: -7-36%] and 17% [95% CI: 4-41%] higher risk in the 3rd tertile of PM₁₀, PM_2.5, PM₁₀-traffic and PM_2.5-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.

Maternal exposure to air pollution alters energy balance transiently according to gender and changes gut microbiota

Introduction

The timing of maternal exposure to air pollution is crucial to define metabolic changes in the offspring. Here we aimed to determine the most critical period of maternal exposure to particulate matter (PM_2.5) that impairs offspring's energy metabolism and gut microbiota composition.

Methods

Unexposed female and male C57BL/6J mice were mated. PM_2.5 or filtered air (FA) exposure occurred only in gestation (PM_2.5/FA) or lactation (FA/PM_2.5). We studied the offspring of both genders.

Results

PM_2.5 exposure during gestation increased body weight (BW) at birth and from weaning to young in male adulthood. Leptin levels, food intake, Agrp, and Npy levels in the hypothalamus were also increased in young male offspring. Ikbke, Tnf increased in male PM_2.5/FA. Males from FA/PM_2.5 group were protected from these phenotypes showing higher O₂ consumption and Ucp1 in the brown adipose tissue. In female offspring, we did not see changes in BW at weaning. However, adult females from PM_2.5/FA displayed higher BW and leptin levels, despite increased energy expenditure and thermogenesis. This group showed a slight increase in food intake. In female offspring from FA/PM_2.5, BW, and leptin levels were elevated. This group displayed higher energy expenditure and a mild increase in food intake. To determine if maternal exposure to PM_2.5 could affect the offspring's gut microbiota, we analyzed alpha diversity by Shannon and Simpson indexes and beta diversity by the Linear Discriminant Analysis (LDA) in offspring at 30 weeks. Unlike males, exposure during gestation led to higher adiposity and leptin maintenance in female offspring at this age. Gestation exposure was associated with decreased alpha diversity in the gut microbiota in both genders.

Discussion

Our data support that exposure to air pollution during gestation is more harmful to metabolism than exposure during lactation. Male offspring had an unfavorable metabolic phenotype at a young age. However, at an older age, only females kept more adiposity. Ultimately, our data highlight the importance of controlling air pollution, especially during gestation.

Association of long-term air pollution exposure with the risk of prediabetes and diabetes: Systematic perspective from inflammatory mechanisms, glucose homeostasis pathway to preventive strategies

BACKGROUND

Limited evidence suggests the association of air pollutants with a series of diabetic cascades including inflammatory pathways, glucose homeostasis disorder, and prediabetes and diabetes. Subclinical strategies for preventing such pollutants-induced effects remain unknown.

METHODS

We conducted a cross-sectional study in two typically air-polluted Chinese cities in 2018-2020. One-year average PM₁, PM_2.5, PM₁₀, SO₂, NO₂, and O₃ were calculated according to participants' residence. GAM multinomial logistic regression was performed to investigate the association of air pollutants with diabetes status. GAM and quantile g-computation were respectively performed to investigate individual and joint effects of air pollutants on glucose homeostasis markers (glucose, insulin, HbA1c, HOMA-IR, HOMA-B and HOMA-S). Complement C3 and hsCRP were analyzed as potential mediators. The ABCS criteria and hemoglobin glycation index (HGI) were examined for their potential in preventive strategy.

RESULTS

Long-term air pollutants exposure was associated with the risk of prediabetes [Prevalence ratio for O₃ (PR_O₃) = 1.96 (95% CI: 1.24, 3.03)] and diabetes [PR_PM₁ = 1.18 (95% CI: 1.05, 1.32); PR_PM_2.5 = 1.08 (95% CI: 1.00, 1.16); PR_O₃ = 1.35 (95% CI: 1.03, 1.74)]. PM₁, PM₁₀, SO₂ or O₃ exposure was associated with glucose-homeostasis disorder. For example, O₃ exposure was associated with increased levels of glucose [7.67% (95% CI: 1.75, 13.92)], insulin [19.98% (95% CI: 4.53, 37.72)], HOMA-IR [34.88% (95% CI: 13.81, 59.84)], and decreased levels of HOMA-S [-25.88% (95% CI: -37.46, -12.16)]. Complement C3 and hsCRP played mediating roles in these relationships with proportion mediated ranging from 6.95% to 60.64%. Participants with HGI ≤ -0.53 were protected from the adverse effects of air pollutants.

CONCLUSION

Our study provides comprehensive insights into air pollutant-associated diabetic cascade and suggests subclinical preventive strategies.

Association between long-term air pollution exposure and insulin resistance independent of abdominal adiposity in Korean adults

Significant associations between air pollution (AP) and insulin resistance (IR) have been reported in limited populations or certain patient groups, but few studies have addressed this association in the general population, especially in Asians. Although abdominal fat is a major contributor to IR, previous studies have not fully controlled for its effect in the association between AP and IR. We investigated the association between exposure to AP and IR in Korean adults in the general population and whether this association is maintained even after controlling for the effects of abdominal fat, particularly visceral fat. This was a cross-sectional study. Data were obtained for Korean adults who participated in screening health checkups at Seoul National University Health Examination Center from 2006 to 2014. A total of 4251 men and women aged 22-84 years were included. IR was represented by the homeostasis model assessment of insulin resistance (HOMA-IR). Adiposity traits such as visceral adipose tissue (VAT) and subcutaneous adipose tissue areas were measured by computed tomography. We assessed the annual mean concentrations of air pollutants, including particulate matter with an aerodynamic diameter of 10 µm or less (PM₁₀), nitrogen dioxide, sulfur dioxide, and carbon monoxide. HOMA-IR was significantly associated with increased annual mean exposure to PM₁₀ in both men (β = 0.15; 95% CI 0.09, 0.22) and women (β = 0.16; 95% CI 0.09, 0.23), and these associations were maintained even after controlling for VAT area (both p < 0.05). The adjusted mean HOMA-IR increased gradually with the level of long-term PM₁₀ exposure (low, intermediate, and high exposure) (all p for trend < 0.001) in the subgroup analysis. After adjusting for possible confounding factors, including VAT area, the annual mean exposure to PM₁₀ was significantly associated with the presence of IR in both men (OR 1.18; 95% CI 1.03, 1.35) and women (OR 1.44; 95% CI 1.18, 1.76). Other air pollutants, such as NO₂, SO₂ and CO, did not show any significant associations with HOMA-IR or the presence of IR. Persistent exposure to PM₁₀ is the main independent risk factor for IR and exhibits a dose-dependent association regardless of visceral fatness in both men and women.

Acute exposure to air pollutants increase the risk of acute glaucoma

Background

Ambient air pollution is related to the onset and progression of ocular disease. However, the effect of air pollutants on the acute glaucoma remains unclear.

Objective

To investigate the effect of air pollutants on the incidence of acute glaucoma (acute angle closure glaucoma and glaucomatocyclitic crisis) among adults.

Methods

We conducted a time-stratified case-crossover study based on the data of glaucoma outpatients from January, 2015 to Dec, 2021 in Shanghai, China. A conditional logistic regression model combined with a polynomial distributed lag model was applied for the statistical analysis. Each case serves as its own referent by comparing exposures on the day of the outpatient visit to the exposures on the other 3–4 control days on the same week, month and year. To fully capture the delayed effect of air pollution, we used a maximum lag of 7 days in main model.

Results

A total of 14,385 acute glaucoma outpatients were included in this study. We found exposure to PM_2.5, PM₁₀, nitrogen dioxide (NO₂) and carbon monoxide (CO) significantly increased the odds of outpatient visit for acute glaucoma. Wherein the odds of acute glaucoma related to PM_2.5 and NO₂ were higher and more sustained, with OR of 1.07 (95%CI: 1.03–1.11) and 1.12 (95% CI: 1.08–1.17) for an IQR increase over lag 0–3 days, than PM₁₀ and CO over lag 0–1 days (OR:1.03; 95% CI: 1.01–1.05; OR: 1.04; 95% CI: 1.01–1.07).

Conclusions

This case-crossover study provided first-hand evidence that air pollutants, especially PM_2.5 and NO₂, significantly increased risk of acute glaucoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14078-9.

Modification Effect of PARP4 and ERCC1 Gene Polymorphisms on the Relationship between Particulate Matter Exposure and Fasting Glucose Level

Particulate matter (PM) has been linked to adverse health outcomes, including insulin resistance (IR). To evaluate the relationships between exposures to PM₁₀, PM_2.5–10, and PM_2.5; the serum level of fasting glucose, a key IR indicator; and effects of polymorphisms of two repair genes (PARP4 and ERCC1) on these relations, PMs exposure data and blood samples for glucose measurement and genotyping were collected from 527 Korean elders. Daily average levels of PMs during 8 days, from 7 days before examination to the health examination day (from lag day 7 to lag day 0), were used for association analyses, and mean concentrations of PM₁₀, PM_2.5–10, and PM_2.5 during the study period were 43.4 µg/m³, 19.9 µg/m³, and 23.6 µg/m³, respectively. All three PMs on lag day 4 (mean, 44.5 µg/m³ for PM₁₀, 19.9 µg/m³ for PM_2.5–10, and 24.3 µg/m³ for PM_2.5) were most strongly associated with an increase in glucose level (percent change by inter-quartile range-change of PM: (β) = 1.4 and p = 0.0023 for PM₁₀; β = 3.0 and p = 0.0010 for PM_2.5–10; and β = 2.0 and p = 0.0134 for PM_2.5). In particular, elders with PARP4 G-C-G or ERCC1 T-C haplotype were susceptible to PMs exposure in relation to glucose levels (PARP4 G-C-G: β = 2.6 and p = 0.0006 for PM₁₀, β = 3.5 and p = 0.0009 for PM_2.5–10, and β = 1.6 and p = 0.0020 for PM_2.5; ERCC1 T-C: β = 2.2 and p = 0.0016 for PM₁₀, β = 3.5 and p = 0.0003 for PM_2.5–10, and β = 1.2 and p = 0.0158 for PM_2.5). Our results indicated that genetic polymorphisms of PARP4 and ERCC1 could modify the relationship between PMs exposure and fasting glucose level in the elderly.

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.

Air pollution and endocrine disruptors induce human microbiome imbalances: A systematic review of recent evidence and possible biological mechanisms

A rich body of literature indicates that environmental factors interact with the human microbiome and influence its composition and functions contributing to the pathogenesis of diseases in distal sites of the body. This systematic review examines the scientific evidence on the effect of environmental toxicants, air pollutants and endocrine disruptors (EDCs), on compositional and diversity of human microbiota. Articles from PubMed, Embase, WoS and Google Scholar where included if they focused on human populations or the SHIME® model, and assessed the effects of air pollutants and EDCs on human microbiome. Non-human studies, not written in English and not displaying original research were excluded. The Newcastle-Ottawa Scale was used to assess the quality of individual studies. Results were extracted and presented in tables. 31 studies were selected, including 24 related to air pollutants, 5 related to EDCs, and 2 related to EDC using the SHIME® model. 19 studies focussed on the respiratory system (19), gut (8), skin (2), vaginal (1) and mammary (1) microbiomes. No sufficient number of studies are available to observe a consistent trend for most of the microbiota, except for streptococcus and veillionellales for which 9 out of 10, and 3 out of 4 studies suggest an increase of abundance with exposure to air pollution. A limitation of the evidence reviewed is the scarcity of existing studies assessing microbiomes from individual systems. Growing evidence suggests that exposure to environmental contaminants could change the diversity and abundance of resident microbiota, e.g. in the upper and lower respiratory, gastrointestinal, and female reproductive system. Microbial dysbiosis might lead to colonization of pathogens and outgrowth of pathobionts facilitating infectious diseases. It also might prime metabolic dysfunctions disrupting the production of beneficial metabolites. Further studies should elucidate the role of environmental pollutants in the development of dysbiosis and dysregulation of microbiota-related immunological processes.

Environmental Factors as Diabetic Mediators: A Mechanistic Approach

Despite substantial investment in research and treatment options, diabetes mellitus remains a pressing public health concern with potential epidemic proportions globally. There are reports that by the end of 2040, 642 million people will be suffering from diabetes. Also, according to an estimation, 1.6 million deaths were caused directly by diabetes in 2016. Diabetes is a metabolic disorder characterized by impaired glucose regulation in the body due to the destruction of pancreatic β-cells or insulin resistance. Genetic propensity, unhealthy and imbalanced diet, obesity and increasing urbanization are the common risk factors for diabetes. Besides this, it has been reported that environmental pollutants like organic pesticides, heavy metals, and air pollutants act as strong predisposing factors for diabetes owing to their highly bio-accumulative nature. These pollutants disturb glucose homeostasis either by up-regulating or down-regulating the expression of diabetic marker genes like insulin (INS) and glucokinase (GCK). Unfortunately, the molecular mechanism of the role of pollutants in causing diabetes is not very clear. This mechanistic review provides evidence of different environmental determinants, including persistent organic pollutants (POPs), air pollutants, toxic metals, etc., in inducing diabetes and proposes a framework for the possible mechanisms involved. It also illuminates the current status and future challenges, which will not only broaden our understanding but can also be a reasonable platform for further investigation.

Reducing particulates in indoor air can improve the circulation and cardiorespiratory health of old people: A randomized, double-blind crossover trial of air filtration

Exposure to indoor air particulate pollution increases respiratory and cardiovascular morbidity and mortality, especially in the elderly. To assess a short-term, indoor air filtration's potential benefit on circulatory and cardiopulmonary health among healthy older people, a randomized, double-blind crossover trial was conducted with 24 healthy residents of an aged-care center in Chongqing, China in 2020. Each room received a high-efficiency particulate air filter air purifier and a placebo air purifier for two days. Fifteen circulatory system biomarkers of inflammation, coagulation, and oxidative stress; lung function; blood pressure (BP); heart rate (HR) and fractional exhaled nitric oxide (FeNO) were measured end of each two days. Indoor air particulate pollution was monitored throughout the study period. Linear mixed-effect models were used to associate health outcome variables with indoor particles. This intervention study demonstrated that air filtration was associated with significantly decreased concentrations of inflammatory and coagulation biomarkers, but not of biomarkers of oxidative stress and lung function. Just 48 h of air filtration can improve the cardiopulmonary health of the elderly. Air purifiers may be a public health measure that can be taken to improve circulatory and cardiopulmonary health among older people.

Physical Activity in Polluted Air-Net Benefit or Harm to Cardiovascular Health? A Comprehensive Review

Both exposure to higher levels of polluted air and physical inactivity are crucial risk factors for the development and progression of major noncommunicable diseases and, in particular, of cardiovascular disease. In this context, the World Health Organization estimated 4.2 and 3.2 million global deaths per year in response to ambient air pollution and insufficient physical activity, respectively. While regular physical activity is well known to improve general health, it may also increase the uptake and deposit of air pollutants in the lungs/airways and circulation, due to increased breathing frequency and minute ventilation, thus increasing the risk of cardiovascular disease. Thus, determining the tradeoff between the health benefits of physical activity and the potential harmful effects of increased exposure to air pollution during physical activity has important public health consequences. In the present comprehensive review, we analyzed evidence from human and animal studies on the combined effects of physical activity and air pollution on cardiovascular and other health outcomes. We further report on pathophysiological mechanisms underlying air pollution exposure, as well as the protective effects of physical activity with a focus on oxidative stress and inflammation. Lastly, we provide mitigation strategies and practical recommendations for physical activity in areas with polluted air.

Environmental risk factors and cardiovascular diseases: a comprehensive review

Noncommunicable diseases (NCDs) are fatal for more than 38 million people each year and are thus the main contributors to the global burden of disease accounting for 70% of mortality. The majority of these deaths are caused by cardiovascular disease. The risk of NCDs is strongly associated with exposure to environmental stressors such as pollutants in the air, noise exposure, artificial light at night and climate change, including heat extremes, desert storms and wildfires. In addition to the traditional risk factors for cardiovascular disease such as diabetes, arterial hypertension, smoking, hypercholesterolemia and genetic predisposition, there is a growing body of evidence showing that physicochemical factors in the environment contribute significantly to the high NCD numbers. Furthermore, urbanization is associated with accumulation and intensification of these stressors. This comprehensive expert review will summarize the epidemiology and pathophysiology of environmental stressors with a focus on cardiovascular NCDs. We will also discuss solutions and mitigation measures to lower the impact of environmental risk factors with focus on cardiovascular disease.

Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study

It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.

PM2.5 promotes β cell damage by increasing inflammatory factors in mice with streptozotocin

Emerging evidence indicates that exposure to fine particulate matter contributes to the onset of diabetes. The present study aimed to investigate the mechanism of particulate matters (PM)2.5 affecting glucose homeostasis in mice with type 1 diabetes mellitus. Male C57BL/6 mice were housed under filtered air (FA) or PM2.5 for 12 weeks and then received intraperitoneal injection of streptozotocin (STZ; 40 mg/kg) or acetic buffer daily for 5 days. At 4 weeks after the last injection, fasting glucose was tested. In the plasma and liver, cholesterol levels were determined by cholesterol oxidase-peroxidase and triglyceride levels were determined by triglycerophosphate oxidase-peroxidase. Homeostasis model assessment of β cell function (Homa-β) was computed based on fasting insulin and glucose levels. Interleukin-1β (IL-1β) and tumor necrosis factor-α (TNFα) levels in plasma, visceral adipose tissues, RAW264.7 macrophages and MIN6 pancreatic β cells treated with PM2.5 (0-50 µg/ml) were quantified via ELISA. Before STZ injection, fasting blood glucose (FBG) levels were similar between FA and PM2.5 groups. After STZ injection, FBG levels were higher in mice pre-exposed to PM2.5 compared with those pre-exposed to FA. When taking FBG levels ≥7 mmol/l as the criteria for impaired glucose level, its incidence was 53.3% and 77.8% in FA and PM2.5 groups, respectively. Independent of STZ injection, IL-1β levels in the adipose tissue were upregulated in mice pre-exposed to PM2.5 compared with FA. The addition of PM2.5 stimulated IL-1β and TNFα production in macrophages and pancreatic β cells, and inhibited the secretion of insulin from MIN6 cells in a dose-dependent manner. In conclusion, pre-exposure of PM2.5 impaired pancreatic β cells in mice upon STZ injection, partially via enhanced inflammation, and suppressed the secretion of insulin.

Oxidative Stress Biomarkers in the Relationship between Type 2 Diabetes and Air Pollution

The incidence and prevalence of type 2 diabetes have increased in the last decades and are expected to further grow in the coming years. Chronic hyperglycemia triggers free radical generation and causes increased oxidative stress, affecting a number of molecular mechanisms and cellular pathways, including the generation of advanced glycation end products, proinflammatory and procoagulant effects, induction of apoptosis, vascular smooth-muscle cell proliferation, endothelial and mitochondrial dysfunction, reduction of nitric oxide release, and activation of protein kinase C. Among type 2 diabetes determinants, many data have documented the adverse effects of environmental factors (e.g., air pollutants) through multiple exposure-induced mechanisms (e.g., systemic inflammation and oxidative stress, hypercoagulability, and endothelial and immune responses). Therefore, here we discuss the role of air pollution in oxidative stress-related damage to glycemic metabolism homeostasis, with a particular focus on its impact on health. In this context, the improvement of new advanced tools (e.g., omic techniques and the study of epigenetic changes) may provide a substantial contribution, helping in the evaluation of the individual in his biological totality, and offer a comprehensive assessment of the molecular, clinical, environmental, and epidemiological aspects.

Particulate Air Pollution and Osteoporosis: A Systematic Review

Air pollution is associated with inflammation and oxidative stress, which predispose to several chronic diseases in human. Emerging evidence suggests that the severity and progression of osteoporosis are directly associated with inflammation induced by air pollutants like particulate matter (PM). This systematic review examined the relationship between PM and bone health or fractures. A comprehensive literature search was conducted from January until February 2021 using the PubMed, Scopus, Web of Science, Google Scholar and Cochrane Library databases. Human cross-sectional, cohort and case-control studies were considered. Of the 1500 papers identified, 14 articles were included based on the inclusion and exclusion criteria. The air pollution index investigated by most studies were PM2.5 and PM10. Current studies demonstrated inconsistent associations between PM and osteoporosis risk or fractures, which may partly due to the heterogeneity in subjects' characteristics, study design and analysis. In conclusion, there is an inconclusive relationship between osteoporosis risk and fracture and PM exposures which require further validation.

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

Emerging role of air pollution and meteorological parameters in COVID-19

Exposure to air pollutants has been associated with respiratory viral infections. Epidemiological studies have shown that air pollution exposure is related to increased cases of SARS-COV-2 infection and COVID-19-associated mortality. In addition, the changes of meteorological parameters have also been implicated in the occurrence and development of COVID-19. However, the molecular mechanisms by which pollutant exposure and changes of meteorological parameters affects COVID-19 remains unknown. This review summarizes the biology of COVID-19 and the route of viral transmission, and elaborates on the relationship between air pollution and climate indicators and COVID-19. Finally, we envisaged the potential roles of air pollution and meteorological parameters in COVID-19.

Estimates of Type 2 Diabetes Mellitus Burden Attributable to Particulate Matter Pollution and Its 30-Year Change Patterns: A Systematic Analysis of Data From the Global Burden of Disease Study 2019

BACKGROUND

Epidemiological trends of type 2 diabetes mellitus attributable to fine particulate matter (PM_2.5) pollution remain unclear. Here, we estimated spatiotemporal trends of type 2 diabetes mellitus burden attributable to PM_2.5 pollution, including ambient particulate matter pollution (APMP) and household air pollution (HAP), from 1990-2019.

METHODS

Data were obtained from the Global Burden of Disease Study 2019 and were analyzed by age, sex, year, and location. Joinpoint regression analysis was applied in the analysis of temporal trends in type 2 diabetes mellitus burden over the 30 years.

RESULTS

Globally, PM_2.5 pollution contributed to 292.5 thousand deaths and 13 million disability-adjusted life-years (DALYs) in 2019. APMP ranked third among all risk factors, causing an increase in type 2 diabetes mellitus burden from 1990, whereas the impact of HAP significantly fell during the same period. Both APMP and HAP contributed the most to deaths and DALYs of type 2 diabetes mellitus among older people. However, the age-standardized death and DALY rates of type 2 diabetes mellitus attributable to APMP were greater among males and people in the middle socio-demographic index countries, especially in Southern Sub-Saharan Africa. For HAP, type 2 diabetes mellitus burden was modestly higher in females and was highest in Oceania, which was the only region with an increase from 1990.

CONCLUSIONS

PM_2.5 pollution resulted in substantial and increasing type 2 diabetes mellitus burden worldwide. Hence, governments and health systems should take steps to reduce air pollution to mitigate this increasing burden.

Long-term air pollution exposure and self-reported morbidity: A longitudinal analysis from the Thai cohort study (TCS)

BACKGROUND

Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.

METHODS

This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO.

RESULTS

After controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2.

CONCLUSIONS

Long-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.

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.

Immune biomarkers link air pollution exposure to blood pressure in adolescents

BACKGROUND

Childhood exposure to air pollution contributes to cardiovascular disease in adulthood. Immune and oxidative stress disturbances might mediate the effects of air pollution on the cardiovascular system, but the underlying mechanisms are poorly understood in adolescents. Therefore, we aimed to identify immune biomarkers linking air pollution exposure and blood pressure levels in adolescents.

METHODS

We randomly recruited 100 adolescents (mean age, 16 years) from Fresno, California. Using central-site data, spatial-temporal modeling, and distance weighting exposures to the participant's home, we estimated average pollutant levels [particulate matter (PM), polyaromatic hydrocarbons (PAH), ozone (O₃), carbon monoxide (CO) and nitrogen oxides (NO_x)]. We collected blood samples and vital signs on health visits. Using proteomic platforms, we quantitated markers of inflammation, oxidative stress, coagulation, and endothelial function. Immune cellular characterization was performed via mass cytometry (CyTOF). We investigated associations between pollutant levels, cytokines, immune cell types, and blood pressure (BP) using partial least squares (PLS) and linear regression, while adjusting for important confounders.

RESULTS

Using PLS, biomarkers explaining most of the variance in air pollution exposure included markers of oxidative stress (GDF-15 and myeloperoxidase), acute inflammation (C-reactive protein), hemostasis (ADAMTS, D-dimer) and immune cell types such as monocytes. Most of these biomarkers were independently associated with the air pollution levels in fully adjusted regression models. In CyTOF analyses, monocytes were enriched in participants with the highest versus the lowest PM_2.5 exposure. In both PLS and linear regression, diastolic BP was independently associated with PM_2.5, NO, NO₂, CO and PAH₄₅₆ pollution levels (P ≤ 0.009). Moreover, monocyte levels were independently related to both air pollution and diastolic BP levels (P ≤ 0.010). In in vitro cell assays, plasma of participants with high PM_2.5 exposure induced endothelial dysfunction as evaluated by eNOS and ICAM-1 expression and tube formation.

CONCLUSIONS

For the first time in adolescents, we found that ambient air pollution levels were associated with oxidative stress, acute inflammation, altered hemostasis, endothelial dysfunction, monocyte enrichment and diastolic blood pressure. Our findings provide new insights on pollution-related immunological and cardiovascular disturbances and advocate preventative measures of air pollution exposure.

Effects of Ultrafine Particles in Ambient Air on Primary Health Care Consultations for Diabetes in Children and Elderly Population in Ljubljana, Slovenia: A 5-Year Time-Trend Study

Epidemiological studies indicate that exposure to ultrafine particles (UFP) in ambient air represents an important environmental public health issue. The aim of this study was to determine the association between UFP in ambient air and the daily number of consultations in the primary health care unit due to diabetes mellitus in children and elderly population of the Municipality of Ljubljana. A 5-year time-trend ecological study was carried out for the period between 1 January 2013 and 31 December 2017. The daily number of primary health care consultations due to diabetes mellitus among children and elderly population was observed as the health outcome. Daily mean UFP concentrations (different size from 10 to 100 nm) were measured and calculated. Poisson regression analysis was used to investigate the association between the observed outcome and the daily UFP, particulate matter fine fraction (PM_2.5), and particulate matter coarse fraction (PM₁₀) concentrations, adjusted to other covariates. The results show that the daily number of consultations due to diabetes mellitus were highly significantly associated with the daily concentrations of UFP (10 to 20 nm; p ≤ 0.001 and 20 to 30 nm; p ≤ 0.001) in all age groups and in the elderly population. In observed the population of children, we did not confirm the association. Findings indicate that specified environmental challenges should be addressed by comprehensive public health strategies leading to the coordinated cross-sectoral measures for the reduction of UFP in ambient air and the mitigation of adverse health effects.

Exposure to particulate matter (PM2.5) and prevalence of diabetes mellitus in Indonesia

BACKGROUND

Recently emerging evidence suggests an association between particulate matter less than 2.5 µm in diameter (PM_2.5) exposure and diabetes risk. However, evidence from Asia is limited. Here, we evaluated the association between PM_2.5 exposure and the prevalence of diabetes mellitus in one of the most populated countries in Asia, Indonesia.

METHODS

We used the 2013 Indonesia Basic Health Research, which surveyed households in 487 regencies/municipalities in all 33 provinces in Indonesia (n = 647,947). We assigned individual exposure to PM_2.5 using QGIS software. Multilevel logistic regression with a random intercept based on village and cubic spline analysis were used to assess the association between PM_2.5 exposure and the prevalence of diabetes mellitus. We also assessed the lower exposure at which PM_2.5 has potential adverse effects.

RESULTS

We included 647,947 subjects with a mean age of 41.9 years in our study. Exposure to PM_2.5 levels was associated with a 10-unit increase in PM_2.5 (fully adjusted odds ratio: 1.09; 95% confidence interval: 1.05-1.14). The findings were consistent for quartile increases in PM_2.5 levels and the cubic spline function. Even when we restricted to those exposed to PM_2.5 concentrations of less than 10.0 µg/m³ in accordance with the recommended guidelines for annual exposure to PM_2.5 made by the World Health Organization, the association remained elevated, especially among subjects living in the urban areas. Hence, we were unable to establish a safe threshold for PM_2.5 and the risk of diabetes.

CONCLUSIONS

Our findings suggest a positive association between PM_2.5 exposure and prevalence of diabetes mellitus, which is possibly below the current recommended guidelines. Further studies are needed to ascertain the causal association of this finding.

Short-term exposure to air pollution (PM2.5) induces hypothalamic inflammation, and long-term leads to leptin resistance and obesity via Tlr4/Ikbke in mice

A previous study demonstrated that a high-fat diet (HFD), administered for one-three-days, induces hypothalamic inflammation before obesity’s established, and the long term affects leptin signaling/action due to inflammation. We investigate whether exposure to particulate matter of a diameter of ≤2.5 μm (PM_2.5) in mice fed with a chow diet leads to similar metabolic effects caused by high-fat feeding. Compared to the filtered air group (FA), one-day-exposure-PM_2.5 did not affect adiposity. However, five-days-exposure-PM_2.5 increased hypothalamic microglia density, toll-like-receptor-4 (Tlr4), and the inhibitor-NF-kappa-B-kinase-epsilon (Ikbke) expression. Concurrently, fat mass, food intake (FI), and ucp1 expression in brown adipose tissue were also increased. Besides, decreased hypothalamic STAT3-phosphorylation and Pomc expression were found after twelve-weeks-exposure-PM_2.5. These were accompanied by increased FI and lower energy expenditure (EE), leading to obesity, along with increased leptin and insulin levels and HOMA. Mechanistically, the deletion of Tlr4 or knockdown of the Ikbke gene in the hypothalamus was sufficient to reverse the metabolic outcomes of twelve-weeks-exposure-PM_2.5. These data demonstrated that short-term exposure-PM_2.5 increases hypothalamic inflammation, similar to a HFD. Long-term exposure-PM_2.5 is even worse, leading to leptin resistance, hyperphagia, and decreased EE. These effects are most likely due to chronic hypothalamic inflammation, which is regulated by Tlr4 and Ikbke signaling.

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.

Diabetes mortality burden attributable to short-term effect of PM10 in China

Ambient air pollution may be associated with diabetes mellitus. However, evidence from developing countries is limited although the concentrations of air pollution are disproportionably higher in these countries. We collected daily data on diabetes mortality, air pollution, and weather conditions from 16 Chinese provincial cities during 2007-2013. A quasi-Poisson regression combined with a distributed lag model was used to quantify the city-specific mortality risk of PM₁₀ (particulate matter with aerodynamic diameter < 10 μm). Then, a random-effect meta-analysis was conducted to pool effect estimates from 16 cities. We also calculated the attributable fraction and attributable number of diabetes mortality due to PM₁₀. Effects of PM₁₀ were found to be acute and limited to 3 days. Harvesting effect of PM₁₀ was found during lag 4-10 days on diabetes mortality. An increase of 0.17% (95%CI: 0.01-0.34), 0.48% (95%CI: 0.22-0.73), and 0.53% (95%CI: 0.27-0.80) in diabetes mortality was associated with per 10 μg/m³ increase in PM₁₀ at lag 0, 0-4 and 0-10 days, respectively. Totally, 5.76% (95%CI: 2.59-8.00%) and 5878 (95%CI: 2639-8163) deaths due to diabetes could be attributable to PM₁₀. If the concentration of PM₁₀ attained the Chinese government and WHO targets, the reduction in number of PM_2.5-attributed diabetes deaths was 2016 and 5528, respectively. Higher effect estimates of PM₁₀ were observed among females and those aged 0-64 years old at lag 0 day, while greater cumulative effects of PM₁₀ were among males, the elderly aged 75 or over, and the illiterate at lag 0-10 days. However, the between-group differences were not statistically significant. It is one of the few studies on examining the attributable burden of diabetes mortality caused by particulate matter. Our findings indicated that effective efforts on controlling air pollution could reduce a prominent number of air pollution-related diabetes deaths.

All-source and source-specific air pollution and 10-year diabetes Incidence: Total effect and mediation analyses in the Heinz Nixdorf recall study

BACKGROUND

An increasing number of studies have been published recently on the association between ambient air pollution (AP) and incident diabetes mellitus (DM), but studies investigating source-specific AP toxicity and potential mediating pathways are rare. We investigated the associations of all-source, traffic-specific, and industry-specific outdoor AP exposure with 10-year incidence of DM and potential mediation via inflammation-associated biomarkers.

METHODS

Data from participants of the prospective Heinz Nixdorf Recall cohort study who attended the baseline (t₀; 2000-2003), 5-year follow-up (t₁; 2006-2008), and 10-year follow-up (t₂; 2011-2015) examinations was used. For participants without DM at baseline (determined using information on physician diagnosis and glucose-lowering medication), residential long-term exposure (total, traffic-specific, and industry-specific) to particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), and accumulation mode particle number concentration (PN_AM) were estimated using a chemistry transport model. Covariate-adjusted modified Poisson regression models with robust standard errors were applied to estimate relative risks (RR) for the associations between baseline AP and incident DM at t₂. Mediation analyses for adiponectin, high-sensitivity C-reactive protein (hsCRP), and interleukin-1 receptor antagonist (IL-1RA) were conducted to estimate natural direct and indirect effects.

RESULTS

Of the 4,814 participants at t₀, 2,451 participants (mean baseline age: 58.2 years) were included in the main analysis. Interquartile range (IQR) increases in total PM₁₀ and PN_AM were associated with increased risk of DM (e.g., RR: 1.25 [95% Confidence Interval (CI): 1.02, 1.53] per 3.8 µg/m³ PM₁₀). Whereas traffic-specific exposures were associated with DM risk for all air pollutants (e.g., RR: 1.24 [95% CI: 1.06, 1.46] per 0.3 µg/m³ PM₁₀), significant associations for industry exposures were limited to NO₂ and PN_AM (e.g., RR: 1.24 [95% CI: 1.03, 1.49] per 230 particles/mL PN_AM). Potential mediation of the association between AP and DM was observed for adiponectin but not for hsCRP and IL-1RA.

CONCLUSION

Our study shows that long-term exposure to total and source-specific ambient AP may increase DM risk, with consistent results observed across traffic-specific exposures. Decreases in adiponectin may play a potential role along the causal pathway.

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.

Ambient air pollution and diabetes: A systematic review and meta-analysis

BACKGROUND

Air pollutants are suggested to be related to type 2 diabetes (T2D). Since several high quality papers on air pollutants and T2D have been published beyond the last reviews, an extended systematic review is highly warranted. We review epidemiological studies to quantify the association between air pollutants and T2D, and to answer if diabetes patients are more vulnerable to air pollutants.

METHODS

We systematically reviewed the databases of PubMed and Web of Science based on the guidelines of the Preferred Reporting Items for Systematic review and Meta-analysis (PRISMA). We calculated odds ratios (OR) or hazard ratios (HR) and their 95% confidence intervals (CI) to assess the strength of the associations between air pollutants [e.g., particulate matter with diameter ≤ 2.5 μm (PM_2.5), particulate matter with diameter ≤ 10 μm (PM₁₀), and nitrogen dioxide (NO₂)] and T2D. We evaluated the quality and risk of bias of the included studies and graded the credibility of the pooled evidence using several recommended tools. We also performed sensitivity analysis, meta-regression analysis, and publication bias test.

RESULTS

Out of 716 articles identified, 86 were used for this review and meta-analysis. Meta-analyses showed significant associations of PM_2.5 with T2D incidence (11 studies; HR = 1.10, 95% CI = 1.04-1.17 per 10 μg/m³ increment; I² = 74.4%) and prevalence (11 studies; OR = 1.08; 95% CI = 1.04-1.12 per 10 μg/m³ increment; I² = 84.3%), of PM₁₀ with T2D prevalence (6 studies; OR = 1.10; 95% CI = 1.03-1.17 per 10 μg/m³ increment; I² = 89.5%) and incidence (6 studies; HR = 1.11; 95% CI = 1.00-1.22 per μg/m³ increment; I² = 70.6%), and of NO₂ with T2D prevalence (11 studies; OR = 1.07; 95% CI = 1.04-1.11 per 10 μg/m³ increment; I² = 91.1%). The majority of studies on glucose-homoeostasis markers also showed increased risks with higher air pollutants levels, but the studies were too heterogeneous for meta-analysis. Overall, patients with diabetes might be more vulnerable to PM.

CONCLUSIONS

Recent publications strengthened the evidence for adverse effects of ambient air pollutants exposure (especially for PM) on T2D and that diabetic patients might be more vulnerable to air pollutants exposure.

Risk Analysis of Air Pollution and Meteorological Factors Affecting the Incidence of Diabetes in the Elderly Population in Northern China

BACKGROUND

Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence.

METHODS

Our study included 19,000 people aged ≥60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI).

RESULTS

We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10 μg/m³ increase in PM_2.5, PM₁₀, and NO₂, respectively, as well as 1.156 (1.058-1.264) per 1 mg/m³ increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10 μg/m³ increase in PM_2.5. We also found that women, the elderly (≥75 years), and obese subjects were more susceptible to the effect of PM_2.5.

CONCLUSION

Our data suggest that PM_2.5 is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.