Ambient air pollution in relation to diabetes and glucose-homoeostasis markers in China: a cross-sectional study with findings from the 33 Communities Chinese Health Study

Changes and risk factors of adult prediabetes, diabetes prevalence and diabetes control among adult residents in Xinjiang from 2010 to 2018

To analyze the status and related risk factors of prediabetes, diabetes and diabetes control among adult residents in Xinjiang, so as to provide basis and guidance for local diabetes prevention and treatment. A multi-stage stratified sampling method was adopted to conduct preliminary screening of all residents aged 18 years old and above. Personal characteristics, blood glucose, hypertension and blood fat were collected by questionnaire survey, physical measurements and laboratory examinations respectively, and the risk factors of prediabetes, diabetes and blood glucose control were analyzed by binary logistic regression model. The prevalence of prediabetes and diabetes and the control rates of blood glucose in 2010 and 2018 were 17.47% and 20.13%, 12.27% and 15.43%, 35.05% and 38.82%, respectively. The increasing trend was found in prevalence of prediabetes and diabetes. Old age, marriage (including cohabitation), divorce (including separation), overweight or obesity, central obseity and dyslipidemia were risk factors in prediabetes, diabetes was related to old age, family history of diabetes, overweight and obesity, central obesity, hypertension and dyslipidemia, and diabetes blood glucose control was influenced by age, region, central obesity and dyslipidemia. Compared with 2010, the adverse effects on prediabetes of gender and diabetes of region were not significant, and the problem of impaired blood glucose caused by harmful drinking behavior was also alleviated. The prevalence of prediabetes and diabetes in Xinjiang residents is still at a high level, and the control of blood glucose needs to be further strengthened. Meanwhile, the elderly, region, married or divorced, family history of diabetes, overweight and obesity, central obesity, hypertension and dyslipidemia are the key groups for prevention and treatment of diabetes in this area. Active control of weight, blood pressure and blood lipids, screening and publicity of prediabetes and diabetes, and regular monitoring and early intervention are of great significance to reduce the incidence and adverse outcomes of diabetes.

Air pollution, lifestyle, and cardiovascular disease risk in northwestern China: A cohort study of over 5.8 million participants

Evidence on the combined impact of air pollution and lifestyle on cardiovascular disease (CVD) risk is limited. We employed the Space-Time Extra-Trees model, an ensemble learning method for spatiotemporal data, to estimate the annual average concentrations of five air pollutants from 2017 to 2019. Cox proportional hazards models were used to assess the associations between air pollutant exposure and CVD incidence. A lifestyle score, based on body mass index, waist circumference, diet, physical activity, alcohol consumption, and smoking, was developed to examine the moderating effect of lifestyle on the air pollution-CVD relationship. Among 5,838,833 baseline participants without CVD, 414,218 developed CVD during follow-up. Long-term exposure to particulate matter (PM1, PM2.5, PM10), ozone (O3), and carbon monoxide (CO) was significantly associated with increased CVD risk. Stratified analyses revealed that exercise had the most significant impact on this association, with exercisers showing a notable reduction in risk compared to non-exercisers. An interaction between air pollution and lifestyle was observed (P-interaction < 0.001). Compared to individuals with a relatively healthy lifestyle and low air pollution exposure, those with an unhealthy lifestyle and high exposure had the highest risk of developing CVD (PM1: HR = 1.660, PM2.5: HR = 1.891, PM10: HR = 1.755, O3: HR = 1.970, CO: HR = 1.426). Further analysis revealed a synergistic additive interaction between lifestyle and air pollution, leading to relative excess risks of 0.151, 0.154, 0.137, 0.171, and 0.095 in groups with relatively unhealthy lifestyles and high exposure to PM1, PM2.5, PM10, O3, and CO, respectively. Thus, in addition to controlling major air pollutant emissions, promoting healthy lifestyle adoption is crucial.

Inflammation factors mediate the association between heavy metal and Homa-IR index: An integrated approach from the NHANES (2011∼2016)

INTRODUCTION

The interplay between heavy metals exposure and insulin resistance (IR), specifically through the mediation of inflammation factors, is crucial for understanding metabolic disturbances. This study utilizes data from the NHANES (2011∼2016) to investigate these relationships in a large, diverse U.S.

POPULATION

METHODS

The study analyzed the associations between heavy metals (cadmium (Cd), lead (Pb), mercury (Hg), manganese (Mn)) and the Homeostatic Model Assessment for Insulin Resistance (Homa-IR) index. The analyses included descriptive statistics, Pearson's correlations, linear and non-linear regression models, and advanced statistical models such as Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression (BKMR). Inflammation factors were assessed for their mediating role in these associations.

RESULTS

The findings highlighted significant positive correlations between specific heavy metals and the Homa-IR index. Both linear and non-linear associations were evident, with certain metals showing a more pronounced impact in the presence of high inflammation markers. It was found that the Homa-IR index was negatively associated with Pb (β (95 %CI) = -0.0126 (-0.0238 ∼ -0.0015), P = 0.0268) and Hg (β (95 %CI) = -0.0090 (-0.0180 ∼ -0.0001), P = 0.0487). The WQS regression indicated an overall positive relationship between heavy metal mixtures (Estimate: 0.0050, P < 0.05) and the Homa-IR index where Cu had the highest weights (0.7741), while BKMR analyses detailed the varying effects of individual metals at different exposure levels. In the mediation analysis, it can be found that monocyte (Mono) mediated the association between Pb and Homa-IR index (direct effect:0.0546, indirect effect:0.0082) and neutrophil (Neu) (direct effect:0.0521, indirect effect:0.0047) can mediate the association between Hg and Homa-IR index.

CONCLUSIONS

This study confirms that exposure to heavy metals is associated with increased insulin resistance and that inflammation significantly mediates this relationship. Understanding these pathways is essential for developing targeted interventions to mitigate the metabolic consequences of environmental exposures.

Long-term low-level ozone exposure and the incidence of type 2 diabetes mellitus and glycemic levels: A prospective cohort study from Southwest China

BACKGROUND

This study investigated the relationship between long-term low-level ozone (O3) exposure, type 2 diabetes mellitus (T2DM) incidence, and glycemic levels within a prospective cohort in Southwest China, especially in regions with relatively low air pollution levels.

METHOD

Between 2010 and 2020, the Guizhou Population Health Cohort Study (GPHCS) enrolled 9280 participants, who were followed up from 2016 to 2020. A total of 7317 participants (aged 18-95 years, mean 43.70 ± 14.89 years) were included in the final analysis. Time-dependent Cox regression models were used to evaluate the hazard ratios (HRs) between O3 exposure and T2DM incidence and its 95 % confidence intervals (CIs). Generalized linear model (GLM) assessed the association between O3 exposure and fasting blood glucose (FBG) levels.

RESULTS

During a median follow-up period of 6.58 (6.25, 8.42) years, 763 participants were diagnosed with T2DM. For every 1 standard deviation (SD) increase in O3 exposure (Mean ± SD: 67.23 ± 2.16 μg/m³) during the 6 years before baseline, the incidence of T2DM increased by 32.4 % (HR = 1.324, 95 % CI: 1.216, 1.442), while FBG levels rose by 0.081 mmol/L (β = 0.081, 95 % CI: 0.035,0.126). These associations persisted after adjusting for potential confounders, including PM2.5 and temperature. Stratified analyses revealed stronger associations in Han Chinese and urban populations.

CONCLUSION

This study provides robust evidence that even long-term exposure to low-level O3, below the World Health Organization (WHO) guideline value, is significantly associated with increased T2DM incidence and elevated FBG levels. These findings stress the need for stricter air pollution control measures to reduce the incident T2DM caused by long-term low-level O3 exposure and enhance public health protections.

Outdoor air pollution exposure and the risk of type 2 diabetes mellitus: A systematic umbrella review and meta-analysis

The association between different air pollutants and Type 2 Diabetes Mellitus (T2DM) is a growing topic of interest in public health research. This umbrella review and meta-analysis aimed to consolidate current literature on the association between various outdoor air pollutants and T2DM. Subgroups and dose-response relationships were also analyzed to further quantify the association, especially by the factors such as the type of pollutants, duration of exposure, and geographical variation, etc. A thorough literature search of three databases revealed a total of 71 records for umbrella review and 1524 records for meta-analysis where 8 studies were included in the final review of umbrella review and 46 studies for meta-analysis. The evaluation of the study's quality in umbrella review and meta-analysis were conducted using the AMSTAR 2 criteria and the Newcastle-Ottawa Scale (NOS), respectively. Exposure to Particulate Matter (PM) 2.5, PM10, Nitrogen dioxides (NO2) and Ozone (O3) were significantly associated with the risk of T2DM [OR = 1.12 (95% Confidence Interval (CI): 1.09, 1.15), 1.12 (95% CI: 1.06, 1.18), 1.09 (95%CI: 1.07, 1.12), 1.05 (95%CI: 1.03, 1.08), respectively] and subgroup analysis further revealed that PM2.5, PM10, and NO2 associations were confounded by factors such as ages, study design, regions of exposure and air pollution concentration levels. Lastly, only exposure to PM10 had a significant dose-response relationship with the risk of T2DM (p-value = 0.000). These findings further emphasized the need for standardized methods in conducting air pollution research and additional research on other air pollutants to further explore the relationships between these air pollutants and T2DM.

Air Pollution and Diabetes Mellitus: Association and Validation in a Desert Area in China

CONTEXT

Despite the growing evidence pointing to the detrimental effects of air pollution on diabetes mellitus (DM), the relationship remains poorly explored, especially in desert-adjacent areas characterized by high aridity and pollution.

OBJECTIVE

We conducted a cross-sectional study with health examination data from more than 2.9 million adults in 2 regions situated in the southern part of the Taklamakan Desert, China.

METHODS

We assessed 3-year average concentrations (2018-2020) of particulate matter (PM1, PM2.5, and PM10), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) through a space-time extra-trees model. After adjusting for various covariates, we employed generalized linear mixed models to evaluate the association between exposure to air pollutants and DM.

RESULTS

The odds ratios for DM associated with a 10 µg/m3 increase in PM1, PM2.5, PM10, CO, and NO2 were 1.898 (95% CI, 1.741-2.070), 1.07 (95% CI, 1.053-1.086), 1.013 (95% CI, 1.008-1.018), 1.009 (95% CI, 1.007-1.011), and 1.337 (95% CI, 1.234-1.449), respectively. Notably, men, individuals aged 50 years or older, those with lower educational attainment, nonsmokers, and those not engaging in physical exercise appeared to be more susceptible to the adverse effects of air pollution. Multiple sensitivity analyses confirmed the stability of these findings.

CONCLUSION

Our study provides robust evidence of a correlation between prolonged exposure to air pollution and the prevalence of DM among individuals living in desert-adjacent areas. This research contributes to the expanding knowledge on the relationship between air pollution exposure and DM prevalence in desert-adjacent areas.

The role of telomere shortening in ambient ozone exposure-related insulin resistance

BACKGROUND

Ozone (O3) exposure and telomere shortening are associated with insulin resistance (IR). However, the role of telomere shortening in ambient O3 exposure-related IR is largely unclear.

METHODS

The Henan Rural Cohort recruited participants and performed a random forest method to estimate residential O3 concentration. IR was reflected by homeostasis model assessment-IR, quantitative insulin sensitivity check index, triglyceride and glucose index, etc. Generalized linear model, quantile regression model, and mediation effects analysis were utilized to assess the associations of O3 exposure and relative telomere length (RTL) with longitudinal IR markers and their change rates. Furthermore, the role of telomere homeostasis in O3-exposure-induced IR in vivo and in vitro experiments was verified.

RESULTS

O3 exposure was positively associated with longitudinal IR. The proportions of RTL mediated associations between O3 exposure and longitudinal IR markers ranged from 11.92 % to 60.36 %. O3-exposed mice exhibited a higher glucose load, upregulation of GSK-3β and G-6-Pase expression at mRNA levels, glycogen accumulation reduction, telomere shortening, and decreased telomerase reverse transcriptase activity relative to air-exposed mice. In vitro experiments reveal that overexpression of TERT in HepG2 cells up-regulated G-6-Pase mRNA expression level.

CONCLUSIONS

Impaired telomere homeostasis may be involved in O3 exposure-related IR via inhibition of glycogen synthesis and acceleration of gluconeogenesis and the specific mechanisms are still further elucidated.

Classification and identification of risk factors for type 2 diabetes

The risk factors for type 2 diabetes mellitus (T2DM) have been increasingly researched, but the lack of systematic identification and categorization makes it difficult for clinicians to quickly and accurately access and understand all the risk factors, which are categorized in this paper into five categories: Social determinants, lifestyle, checkable/testable risk factors, history of illness and medication, and other factors, which are discussed in a narrative review. Meanwhile, this paper points out the problems of the current research, helps to improve the systematic categorisation and practicality of T2DM risk factors, and provides a professional research basis for clinical practice and industry decision-making.

The burden of type 2 diabetes attributable to air pollution across China and its provinces, 1990-2021: an analysis for the Global Burden of Disease Study 2021

Background

Temporal trends and geographical disparities in type 2 diabetes burden attributable to air pollution, including ambient and household, are not fully understood within China. This study aims to estimate the burden of type 2 diabetes attributable to air pollution at national and provincial levels from 1990 to 2021.

Methods

We assessed air pollution exposure across 33 Chinese provinces, autonomous regions, municipalities, and special administrative regions, focusing on two common forms of air pollution: ambient particulate matter pollution (defined as the annual gridded concentration of PM2.5) and household air pollution (defined as the percentage of households using solid cooking fuels and their corresponding exposure to PM2.5). We employed the methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to estimate the attribution of air pollution on type 2 diabetes deaths and disability-adjusted life years (DALYs) by age, sex, year, and province.

Findings

In 2021, about a fifth of the national type 2 diabetes burden was attributable to air pollution, with an age-standardised estimate of 1.76 deaths and 110.79 DALYs per 100,000 population, higher in males. Ambient PM2.5 contributed to 16.89% of deaths and 16.36% of DALYs, while household air pollution contributed to 3.24% of deaths and 3.07% of DALYs. From 1990 to 2021, type 2 diabetes mortality rates due to ambient PM2.5 pollution increased by 264.23%, whereas those from household air pollution decreased by 80.8%. In 2021, Beijing had the highest population attributable fraction (PAFs) of DALYs due to ambient PM2.5 pollution at 19.63%, while Tibet had the highest PAFs for household air pollution at 13.72%. The age-standardised DALYs rates for type 2 diabetes due to ambient PM2.5 varied widely across provinces, from 143.8 per 100,000 people in Tianjin to 21.6 per 100,000 people in Tibet.

Interpretation

Air pollution, especially ambient PM2.5, is a significant risk factor for type 2 diabetes in China. Urgent action is needed to enhance air pollution control and develop locally adapted preventive strategies to reduce the burden of air pollution-related type 2 diabetes.

Funding

Sanming Project of Medicine in Shenzhen (NO. SZSM202111001).

Effects of Various Heavy Metal Exposures on Insulin Resistance in Non-diabetic Populations: Interpretability Analysis from Machine Learning Modeling Perspective

Increasing and compelling evidence has been proved that heavy metal exposure is involved in the development of insulin resistance (IR). We trained an interpretable predictive machine learning (ML) model for IR in the non-diabetic populations based on levels of heavy metal exposure. A total of 4354 participants from the NHANES (2003-2020) with complete information were randomly divided into a training set and a test set. Twelve ML algorithms, including random forest (RF), XGBoost (XGB), logistic regression (LR), GaussianNB (GNB), ridge regression (RR), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), AdaBoost (AB), Gradient Boosting Decision Tree (GBDT), Voting Classifier (VC), and K-Nearest Neighbour (KNN), were constructed for IR prediction using the training set. Among these models, the RF algorithm had the best predictive performance, showing an accuracy of 80.14%, an AUC of 0.856, and an F1 score of 0.74 in the test set. We embedded three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) in RF model for model interpretation. Urinary Ba, urinary Mo, blood Pb, and blood Cd levels were identified as the main influencers of IR. Within a specific range, urinary Ba (0.56-3.56 µg/L) and urinary Mo (1.06-20.25 µg/L) levels exhibited the most pronounced upwards trend with the risk of IR, while blood Pb (0.05-2.81 µg/dL) and blood Cd (0.24-0.65 µg/L) levels showed a declining trend with IR. The findings on the synergistic effects demonstrated that controlling urinary Ba levels might be more crucial for the management of IR. The SHAP decision plot offered personalized care for IR based on heavy metal control. In conclusion, by utilizing interpretable ML approaches, we emphasize the predictive value of heavy metals for IR, especially Ba, Mo, Pb, and Cd.

Exploring the relationship between air pollution, non-alcoholic fatty liver disease, and liver function indicators: a two-sample Mendelian randomization analysis study

Background and aims

Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder worldwide, with an increasing incidence in recent years. While previous studies have suggested an association between the air pollutant PM2.5 and NAFLD, there is still considerable debate regarding the existence of a clear causal relationship between air pollution and NAFLD. This study aims to employ Mendelian randomization methods to evaluate the causal relationship between major air pollutants and NAFLD.

Method

We conducted Mendelian randomization analyses on a large-scale publicly available genome-wide association study (GWAS) dataset of European populations to dissect the association between air pollutants, NAFLD, and liver function indicators. We used five different analysis methods, including Inverse-variance weighted (IVW), Weighted median, MR-Egger, Simple mode, and Weighted mode, to analyze the data. We also tested for pleiotropy, heterogeneity, and sensitivity of the results.

Results

This study utilized four common exposures related to air pollution and four outcomes related to NAFLD. The results regarding the association between air pollutants and NAFLD (PM2.5: P=0.808, 95% CI=0.37-3.56; PM10: P=0.238, 95% CI=0.33-1.31; nitrogen dioxide: P=0.629, 95% CI=0.40-4.61; nitrogen oxides: P=0.123, 95% CI=0.13-1.28) indicated no statistically significant correlation between them. However, notably, there was a causal relationship between PM10 and serum albumin (ALB) levels (P=0.019, 95% CI=1.02-1.27).

Conclusion

This MR study found no evidence of a causal relationship between air pollution and NAFLD in European populations. However, a statistically significant association was observed between PM10 and ALB levels, suggesting that the air pollutant PM10 may impact the liver's ability to synthesize proteins.

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.

Mutational landscape induced by chronic exposure to environmental PM10 and PM2.5 in A549 lung epithelial cell

Exposure to particulate matter (PM) has been linked to an increased risk of multiple diseases, primarily lung cancer, through various molecular mechanisms. However, the mutagenic potential of PM remains unclear. This study aimed to provide a comprehensive description of genetic mutations and mutagenic signatures resulting from chronic exposure to PM10 or PM2.5. Using whole exome sequencing, we identified driver mutations and mutational signatures in A549 cells, a lung epithelial cell model subjected to weekly exposure to either PM10 or PM2.5, for a period of 28 weeks. The number of single nucleotide variations, insertions, and deletions increased depending on the duration of exposure. PM10 generated the highest number of genomic alterations. Amplifications in SYK (oncogene) and mutations in NCOR1 (tumor suppressor gene) were prevalent in cells exposed to either PM10 or PM2.5; however, other mutations were exclusive, such as TP53 and ANK3 for PM10, and ERCC1 and ERCC2 for PM2.5. Different p53-related signaling pathways were most enriched by driver mutations upon exposure to both PM10 and PM2.5, particularly the glucose deprivation pathway. Exposure to either PM10 or PM2.5 resulted in high frequencies of C > A substitutions and one-base insertions/deletions in microhomology sites. The single-base substitution (SBS) signature SBS05, related to the nucleotide excision DNA repair pathway, contributed the most to both PM10-and PM2.5-exposed cells. The contribution of signature SBS18, related to oxidative stress, was observed in cells exposed to either PM10 or PM2.5, but a greater contribution was observed in PM2.5-exposed cells. In addition, SBS03 and SBS36, which are related to different DNA damage repair mechanisms, were observed more frequently in PM10-exposed cells. We assessed the mutagenic potential of PM10 and PM2.5, as a complete mixture, identifying mutated driver genes and mutational signatures generated by chronic PM exposure, which could contribute to the development of cancer, cardiovascular, and digestive diseases.

Association Between Long-Term Exposure to Ambient Air Pollution and Fasting Blood Glucose: A Systematic Review and Meta-Analysis

Increasing studies are indicating a potential association between ambient air pollution exposure and fasting blood glucose (FBG), an indicator of prediabetes and diabetes. However, there is inconsistency within the existing literature. The aim of this study was to summarize the associations of exposures to particulate matters (PMs) (with aerodynamic diameters of ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), respectively) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) with FBG based on the existing epidemiological research for a better understanding of the relationship between air pollution and diabetes. Up to 2 July 2024, we performed a comprehensive literature retrieval from various electronic databases (PubMed, Web of Science, Scopus, and Embase). Random-effect and fixed-effect models were utilized to estimate the pooled percent changes (%) and 95% confidence intervals (CIs). Then, subgroup meta-analyses and meta-regression analyses were applied to recognize the sources of heterogeneity. There were 33 studies eligible for the meta-analysis. The results showed that for each 10 μg/m3 increase in long-term exposures to PM1, PM2.5, PM10, and SO2, the pooled percent changes in FBG were 2.24% (95% CI: 0.54%, 3.96%), 1.72% (95% CI: 0.93%, 2.25%), 1.19% (95% CI: 0.41%, 1.97%), and 0.52% (95% CI:0.40%, 0.63%), respectively. Long-term exposures to ambient NO2 and O3 were not related to alterations in FBG. In conclusion, our findings support that long-term exposures to PMs of various aerodynamic diameters and SO2 are associated with significantly elevated FBG levels.

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.

Ambient air fine particulate matter (PM10 and PM2.5) and risk of type 2 diabetes mellitus and mechanisms of effects: a global systematic review and meta-analysis

Type 2 diabetes causes early mortality worldwide. Air pollution's relationship with T2DM has been studied. The association between them is unclear because of inconsistent outcomes. Studies on this topic have been published since 2019, but not thoroughly evaluated. We conducted a systematic review and meta-analysis using relevant data. The study protocol was registered in PROSPIRO and conducted according to MOOSE guidelines. In total, 4510 manuscripts were found. After screening, 46 studies were assessed using the OHAT tool. This meta-analysis evaluated fine particles with T2DM using OR and HR effect estimates. Evaluation of publication bias was conducted by Egger's test, Begg's test, and funnel plot analysis. A sensitivity analysis was conducted to evaluate the influence of several studies on the total estimations. Results show a significant association between PM2.5 and PM10 exposure and T2DM. Long-term exposure to fine air particles may increase the prevalence and incidence of T2DM. Fine air pollution increases the chance of developing T2DM mainly via systemic inflammation, oxidative stress, and endoplasmic reticulum stress.

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 PM2.5, 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 PM2.5, 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 PM2.5, 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 PM2.5 were associated with 6.0% (95% CI: 1.9, 10.2) increasing risks of diabetes incidence. Females seemed to be more susceptible to PM2.5. 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 PM2.5/solid fuel use and greenness on diabetes was found.

SIGNIFICANCE

Both PM2.5 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 PM2.5 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.

Long-Term Exposure to Fine Particulate Matter and Fasting Blood Glucose and Diabetes in 20 Million Chinese Women of Reproductive Age

OBJECTIVE

Evidence of the associations between fine particulate matter (PM2.5) and diabetes risk from women of reproductive age, in whom diabetes may have adverse long-term health effects for both themselves and future generations, remains scarce. We therefore examined the associations of long-term PM2.5 exposure with fasting blood glucose (FBG) level and diabetes risk in women of reproductive age in China.

RESEARCH DESIGN AND METHODS

This study included 20,076,032 women age 20-49 years participating in the National Free Preconception Health Examination Project in China between 2010 and 2015. PM2.5 was estimated using a satellite-based model. Multivariate linear and logistic regression models were used to examine the associations of PM2.5 exposure with FBG level and diabetes risk, respectively. Diabetes burden attributable to PM2.5 was estimated using attributable fraction (AF) and attributable number.

RESULTS

PM2.5 showed monotonic relationships with elevated FBG level and diabetes risk. Each interquartile range (27 μg/m3) increase in 3-year average PM2.5 concentration was associated with a 0.078 mmol/L (95% CI 0.077, 0.079) increase in FBG and 18% (95% CI 16%, 19%) higher risk of diabetes. The AF attributed to PM2.5 exposure exceeding 5 μg/m3 was 29.0% (95% CI 27.5%, 30.5%), corresponding to an additional 78.6 thousand (95% CI 74.5, 82.6) diabetes cases. Subgroup analyses showed more pronounced diabetes risks in those who were overweight or obese, age >35 years, less educated, of minority ethnicity, registered as a rural household, and residing in western China.

CONCLUSIONS

We found long-term PM2.5 exposure was associated with higher diabetes risk in women of reproductive age in China.

A systematic review on the level of risk perception of diabetes mellitus: The role of environmental factor

BACKGROUND

Risk perception plays important role in motivating preventive health behaviours. The objective of this systematic review was to explore the level of diabetes risk perception among individuals with and without apparent risk for diabetes, and to consider the effect of environmental factors on the level of diabetes risk perception.

METHODS

This systematic review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The literature search was carried out through PubMed, Web of Science, and Scopus. Original articles written in English and published between 2013 and 2023 were considered. Study quality was appraised using the Mixed Methods Appraisal Tool. Narrative synthesis was undertaken due to methodological heterogeneity in the included studies.

RESULTS

A total of 13 cross-sectional studies, two randomized controlled trials, two cohort studies, two mixed methods studies and one quasi-experiment with a control group were included. An overall low level of diabetes risk perception was reported particularly in those without apparent risk for diabetes. The 20 included studies reported widely varied measures for calculating diabetes risk perception. The influence of environmental factors on the risk perception of diabetes was highlighted.

LIMITATIONS

The use of study-specific and non-validated measures in the included studies weakens the authors' ability to compare across studies. The role of language and publication bias within this systematic review should be acknowledged as we included only English-language studies published in peer-reviewed journals. Another limitation is the exclusion of dimensions of risk perception such as optimistic bias as search terms.

CONCLUSION

The overall low risk perception of diabetes calls for urgent need of public health interventions to increase the risk perception of diabetes. In the future, researchers should ensure the validity and reliability of the measures being used. The influence of environmental factors on the diabetes risk perception indicates that diabetes preventive interventions targeting environmental factors may be effective in increasing the risk perception of diabetes.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

Insulin resistance and its relationship with long-term exposure to ozone: Data based on a national population cohort

The relationship of ozone (O3), particularly the long-term exposure, with impacting metabolic homeostasis in population was understudied and under-recognised. Here, we used data from ChinaHEART, a nationwide, population-based cohort study, combined with O3 and PM2.5 concentration data with high spatiotemporal resolution, to explore the independent association of exposure to O3 with the prevalence of insulin resistance (IR). Among the 271 540 participants included, the crude prevalence of IR was 39.1%, while the age and sex standardized prevalence stood at 33.0%. Higher IR prevalence was observed with each increase of 10.0 μg/m3 in long-term O3 exposure, yielding adjusted odds ratios (OR) of 1.084 (95% CI: 1.079-1.089) in the one-pollutant model and 1.073 (95% CI: 1.067-1.079) in the two-pollutant model. Notably, a significant additive interaction between O3 and PM2.5 on the prevalence of IR was observed (P for additive interaction < 0.001). Our main findings remained consistent and robust in the sensitivity analyses. Our study suggests long-term exposure to O3 was independently and positively associated with prevalence of IR. It emphasized the benefits of policy interventions to reduce O3 and PM2.5 exposure jointly, which could ultimately alleviate the health and economic burden related to DM.

Changes in PM2.5-related diabetes risk under the implementation of the clean air act in Shanghai

OBJECTIVES

We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai.

METHODS

A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods.

RESULTS

In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders.

CONCLUSION

Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.

Associations between long-term exposure to air pollution, diabetes, and hypertension in metropolitan Iran: an ecologic study

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

The role of liver enzymes in the association between ozone exposure and diabetes risk: a cross-sectional study of Zhuang adults in China

Background: Growing evidence has demonstrated the role of ambient air pollutants in driving diabetes incidence. However, epidemiological evidence linking ozone (O3) exposure to diabetes risk has been scarcely studied in Zhuang adults in China. We aimed to investigate the associations of long-term exposure to O3 with diabetes prevalence and fasting plasma glucose (FPG) and estimate the mediating role of liver enzymes in Zhuang adults. Methods: We recruited 13 843 ethnic minority adults during 2018-2019 based on a cross-sectional study covering nine districts/counties in Guangxi. Generalized linear mixed models were implemented to estimate the relationships between O3 exposure and diabetes prevalence and FPG. Mediation effect models were constructed to investigate the roles of liver enzymes in the associations of O3 exposure with diabetes prevalence and FPG. Subgroup analyses were conducted to identify potential effect modifications. Results: Long-term exposure to O3 was positively associated with diabetes prevalence and FPG levels in Zhuang adults, with an excess risk of 7.32% (95% confidence interval [CI]: 2.56%, 12.30%) and an increase of 0.047 mmol L-1 (95% CI: 0.032, 0.063) for diabetes prevalence and FPG levels, respectively, for each interquartile range (IQR, 1.18 μg m-3) increment in O3 concentrations. Alanine aminotransferase (ALT) significantly mediated 8.10% and 29.89% of the associations of O3 with FPG and diabetes prevalence, respectively, and the corresponding mediation proportions of alkaline phosphatase (ALP) were 8.48% and 30.00%. Greater adverse effects were observed in females, obese subjects, people with a low education level, rural residents, non-clean fuel users, and people with a history of stroke and hypertension in the associations of O3 exposure with diabetes prevalence and/or FPG levels (all P values for interaction < 0.05). Conclusion: Long-term exposure to O3 is related to an increased risk of diabetes, which is partially mediated by liver enzymes in Chinese Zhuang adults. Promoting clean air policies and reducing exposure to environmental pollutants should be a priority for public health policies geared toward preventing diabetes.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

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.

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.

The association between outdoor light at night exposure and adult obesity in Northeastern China

Previous studies have linked exposure to light at night (LAN) with various health outcomes, but evidence is limited for the LAN-obesity association. Thestudy analysed data from 24,845 participants of the 33 Communities Chinese Health Study and obesity (BMI ≥28 kg/m2) was defined according to the Working Group on Obesity in China. The Global Radiance Calibrated Nighttime Lights data were used to estimate participants' LAN exposure. The mixed-effect regression models examined the LAN-BMI and LAN-obesity association. We found that higher LAN exposure was significantly associated with greater BMI and higher risk of obesity. Changes of BMI and the odds ratios (ORs) of obesity and 95% confidence intervals (CIs) for 2nd, 3rd, and 4th against the 1st quartile of LAN exposure were 0.363 (0.208, 0.519), 0.364 (0.211, 0.516) and 0.217 (0.051, 0.383); 1.228 (1.099, 1.371), 1.356 (1.196, 1.538) and 1.269 (1.124, 1.433), respectively. Age and regular exercise showed significant modification effects on the LAN-obesity association.

Adverse effects of exposure to fine particles and ultrafine particles in the environment on different organs of organisms

Particulate pollution is a global risk factor that seriously threatens human health. Fine particles (FPs) and ultrafine particles (UFPs) have small particle diameters and large specific surface areas, which can easily adsorb metals, microorganisms and other pollutants. FPs and UFPs can enter the human body in multiple ways and can be easily and quickly absorbed by the cells, tissues and organs. In the body, the particles can induce oxidative stress, inflammatory response and apoptosis, furthermore causing great adverse effects. Epidemiological studies mainly take the population as the research object to study the distribution of diseases and health conditions in a specific population and to focus on the identification of influencing factors. However, the mechanism by which a substance harms the health of organisms is mainly demonstrated through toxicological studies. Combining epidemiological studies with toxicological studies will provide a more systematic and comprehensive understanding of the impact of PM on the health of organisms. In this review, the sources, compositions, and morphologies of FPs and UFPs are briefly introduced in the first part. The effects and action mechanisms of exposure to FPs and UFPs on the heart, lungs, brain, liver, spleen, kidneys, pancreas, gastrointestinal tract, joints and reproductive system are systematically summarized. In addition, challenges are further pointed out at the end of the paper. This work provides useful theoretical guidance and a strong experimental foundation for investigating and preventing the adverse effects of FPs and UFPs on human health.

Long-term exposure to PM1 is associated with increased prevalence of metabolic diseases: evidence from a nationwide study in 123 Chinese cities

Exposure to particulate matter (PM) has been linked to metabolic diseases. However, the effects of PM with an aerodynamic diameter ≤ 1.0 µm (PM1) on metabolic diseases remain unclear. This study is aimed at assessing the associations of PM1 with metabolic disease risk and quantifying the concentration-response (C-R) relationship of PM1 with metabolic disease risk. A national cross-sectional study was conducted, including 12,495 middle-aged and older adults in 123 Chinese cities. The two-year average concentration of PM1 was evaluated using satellite-based spatiotemporal models. Metabolic diseases, including abdominal obesity, diabetes, hypertension, dyslipidemia, and metabolic syndrome, were identified based on physical examination, blood standard biochemistry examination, and self-reported disease histories. Generalized linear models and C-R curves were used to evaluate the associations of PM1 with metabolic diseases. A total of 12,495 participants were included in this study, with a prevalence of 45.73% for abdominal obesity, 20.22% for diabetes, 42.46% for hypertension, 41.01% for dyslipidemia, and 33.78% for metabolic syndrome. The mean ± standard deviation age of participants was 58.79 ± 13.14 years. In addition to dyslipidemia, exposure to PM1 was associated with increased risks of abdominal obesity, diabetes, hypertension, and metabolic syndrome. Each 10 μg/m3 increase in PM1 concentrations was associated with 39% (odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.33, 1.46) increase in abdominal obesity, 18% (OR = 1.18, 95%CI 1.12, 1.25) increase in diabetes, 11% (OR = 1.11, 95%CI 1.06, 1.16) increase in hypertension, and 25% (OR = 1.25, 95%CI 1.19, 1.31) in metabolic syndrome, respectively. C-R curves showed that the OR values of abdominal obesity, diabetes, hypertension, and metabolic syndrome were increased gradually with the increase of PM1 concentrations. Subgroup analysis indicated that exposure to PM1 was associated with increased metabolic disease risks among participants with different lifestyles and found that solid fuel users were more susceptible to PM1 than clean fuel users. This national cross-sectional study indicated that exposure to higher PM1 might increase abdominal obesity, diabetes, hypertension, and metabolic syndrome risk, and solid fuel use might accelerate the adverse effects of PM1 on metabolic syndrome risk. Further longitudinal cohort studies are warranted to establish a causal inference between PM1 exposure and metabolic disease risk.

Beneficial associations between outdoor visible greenness at the workplace and metabolic syndrome in Chinese adults

BACKGROUND

Greenness surrounding residential places has been found to significantly reduce the risk of diseases such as hypertension, obesity, and metabolic syndrome (MetS). However, it is unclear whether visible greenness exposure at the workplace has any impact on the risk of MetS.

METHODS

Visible greenness exposure was assessed using a Green View Index (GVI) based on street view images through a convolutional neural network model. We utilized logistic regression to examine the cross-sectional association between GVI and MetS as well as its components among 51,552 adults aged 18-60 in the city of Hangzhou, China, from January 2018 to December 2021. Stratified analyses were conducted by age and sex groups. Furthermore, a scenario analysis was conducted to investigate the risks of having MetS among adults in different GVI scenarios.

RESULTS

The mean age of the participants was 40.1, and 38.5% were women. We found a statistically significant association between GVI and having MetS. Compared to the lowest quartile of GVI, participants in the highest quartile of GVI had a 17% (95% CI: 11-23%) lower odds of having MetS. The protective association was stronger in the males, but we did not observe such differences in different age groups. Furthermore, we found inverse associations between GVI and the odds of hypertension, low high-density lipoprotein cholesterol, obesity, and high levels of FPG.

CONCLUSIONS

Higher exposure to outdoor visible greenness in the workplace environment might have a protective effect against MetS.

Fine particulate matter and its constituent on ovarian reserve: Identifying susceptible windows of exposure

BACKGROUND

Little is known about the associations of exposure to fine particulate matter (PM2.5) and its constituents with ovarian reserve, and the potential susceptible window of exposure remains unclear.

METHODS

We performed a retrospective cohort study of 5189 women who attended a fertility center in Hubei, China, during 2019-2022, and estimated concentrations of PM2.5 and its major constituents during the development of follicles (4th-6th month [W1], 0-4th month [W2], 0-6th month [W3]) and 1-year before measurement (W4) based on Tracking Air Pollution in China database. We used multivariable linear regression and logistic regression models to examine the associations of PM2.5 and its constituent exposures with anti-Müllerian hormone (AMH), the preferred indicator of ovarian reserve.

RESULTS

We observed significantly decreased AMH levels associated with increasing PM2.5 concentrations, with the percent changes (95 % confidence intervals [CIs]) of 1.99 % (0.24 %-3.71 %) during W1 and 3.99 % (0.74 %-7.15 %) during W4 for per 10 μg/m3 increases in PM2.5.When PM2.5 exposure levels were equal to 50th percentile (32.6-42.3 μg/m3) or more, monotonically decreased AMH levels and increased risks of low AMH were seen with increasing PM2.5 concentrations during W1 and W4 (P < 0.05). Black carbon (BC), ammonium (NH4+), nitrate (NO3-), and organic matter (OM) during W1, and NH4+, NO3-, as well as sulfate (SO42-) during W4 were significantly associated with decreased AMH. Moreover, PM2.5 and SO42- exposures during W4 were positively associated with low AMH. Additionally, the associations were stronger among women aged <35 years, lived in urban regions, or measured AMH in cold-season (P for interaction <0.05).

CONCLUSION

PM2.5 and specific chemical components (particularly NH4+, NO3-, and SO42-) exposure during the secondary to antral follicle stage and 1-year before measurement were associated with diminished ovarian reserve (DOR), indicating the adverse impact of PM2.5 and its constituent exposures on female reproductive potential.

Association of land urbanization and type 2 diabetes mellitus prevalence and mediation of greenness and physical activity in Chinese adults

The prevalence of type 2 diabetes (T2D) is higher in urban than in rural areas. Limited information is available on the association between T2D and Land urbanization (LU) while LU influences not only greenness and Particulate Matter 2.5 (PM2.5) but also inhabitant behavior. We aimed to explore the association between the LU level and T2D prevalence, as well as whether greenness, PM2.5, or conscious physical activity mediated any of the observed associations. This study encompassed 27,633 adult participants from Shandong Province who completed the sixth National Health Service Survey in 2018. Ambient LU exposure was estimated by spatial characteristics, including the existing impervious surface area (ISA), road density (RD), and annual night light (NL). Exposures were estimated using satellite images and OpenStreetMap, with 1000 m used as the main analysis buffer. Two-level logistic regression models were used to investigate the association between the LU metrics and T2D. Additionally, we explored potential mechanisms of the association through mediation analysis. The prevalence of T2D among participants was 5.14%, with average exposures to ISA_1000m of 1.441 km2, RD_1000m of 3.856 km/km2, and NL_1000m of 9.821 nW/cm2/sr. Higher levels of LU exposure were associated with higher T2D ORs [for each interquartile of ISA_1000m, RD_1000m, and NL_1000m, the adjusted OR (95% CI) for the T2D prevalence were 1.29 (1.19-1.4), 1.25 (1.15-1.36), and 1.25 (1.15-1.36), respectively]. This relationship persisted in several sensitivity analyses including use of different buffer sizes. We observed stronger associations among participants younger than 65 years or in men. Greenness mediated a 20.78%-65.36% of the estimated associations, conscious physical activity mediated a 10.35%-15.85%, while PM2.5 mediated insignificantly. These results suggest a deleterious association between higher levels of LU and T2D among adult residents in a developing country. Greenness and conscious physical activity mediate the association.

Metabolomic alterations in healthy adults traveling to low-pollution areas: A natural experiment with ozone exposure

Numerous epidemiological studies have demonstrated links between short-term ozone exposure to various adverse health outcomes, but some ozone-induced pathological mechanisms remain unclear. To fill this knowledge gap, we enrolled 36 healthy young adults living in high-ozone areas and performed an untargeted metabolomic analysis in serum collected before, during, and after their travel to a low-ozone scenic area. Reviewing the literature, we found 16 metabolites significantly associated with ozone, pointing to neurological health, type 2 diabetes (T2D) risk, and cardiovascular health. Notably, we observed significant changes in these 16 metabolites from the ozone reduction when participants traveled from the campus to the scenic area (adjusted p-value < 0.05). However, when ozone increased after participants returned to campus from the scenic area, we observed that T2D risk and cardiovascular health-related metabolites returned to their original state (adjusted p-value < 0.05), but neurological health-related metabolites did not change significantly with ozone exposure. Our study showed that ozone exposure was linked to prompt alterations in serum metabolites related to cardiovascular health and T2D risk but less sensitive changes in neurological health-related metabolites. Among many lipids, free fatty acids and acylcarnitines were the most sensitive compounds positively associated with changes in ozone exposure.

Short-term exposure to ozone and mortality from AIDS-related diseases: A case-crossover study in the middle Yangtze River region, China

BACKGROUND

Previous investigations have predominantly concentrated on the influence of ozone (O3) on general population mortality. However, a noticeable gap exists regarding the attention directed towards susceptible demographics, specifically individuals afflicted by human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS).

METHODS

A dataset comprising 1467 AIDS-related fatalities from 2013 to 2020 was amassed from the Hubei Provincial Center for Disease Control and Prevention. Daily maximum 8-h average O3 levels and meteorological parameters were extracted from the ChinaHighAirPollutants dataset and the National Meteorological Science Data Center, respectively. A time-stratified case-crossover methodology was employed to scrutinize the connection between short-term exposure to O3 and AIDS-related deaths.

RESULTS

A rise of one interquartile (IQR) in O3 concentration, lagged by 4 days, was associated with a 15% [95% confidence intervals (CIs): 2, 31] increase in AIDS-related deaths. Notably, males demonstrated heightened susceptibility to the adverse consequences of O3, marked by an odds ratio of 1.20 (95% CIs: 1.05, 1.37) at lag 4 day. Additionally, patients aged over 65 years exhibited escalated vulnerability to brief O3 exposure. Marriage status and educational attainment emerged as influential factors modifying the interplay between O3 and AIDS-related mortality.

CONCLUSIONS

Our study presents novel evidence spotlighting the deleterious repercussions of O3 on mortality in the HIV/AIDS population.

Dilemma of Epigenetic Changes Causing or Reducing Metabolic Disorders in Offsprings of Obese Mothers

Maternal obesity is associated with fetal complications predisposing later to the development of metabolic syndrome during childhood and adult stages. High-fat diet seems to influence individuals and their subsequent generations in mediating weight gain, insulin resistance, obesity, high cholesterol, diabetes, and cardiovascular disorder. Research evidence strongly suggests that epigenetic alteration is the major contributor to the development of metabolic syndrome through DNA methylation, histone modifications, and microRNA expression. In this review, we have discussed the outcome of recent studies on the adverse and beneficial effects of nutrients and vitamins through epigenetics during pregnancy. We have further discussed about the miRNAs altered during maternal obesity. Identification of new epigenetic modifiers such as mesenchymal stem cells condition media (MSCs-CM)/exosomes for accelerating the reversal of epigenetic abnormalities for the development of new treatments is yet another aspect of the present review.

PM2.5 exposure, glycemic markers and incidence of type 2 diabetes in two large Indian cities

INTRODUCTION

Exposure to fine particulate matter has been associated with several cardiovascular and cardiometabolic diseases. However, such evidence mostly originates from low-pollution settings or cross-sectional studies, thus necessitating evidence from regions with high air pollution levels, such as India, where the burden of non-communicable diseases is high.

RESEARCH DESIGN AND METHODS

We studied the associations between ambient PM2.5 levels and fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c) and incident type 2 diabetes mellitus (T2DM) among 12 064 participants in an adult cohort from urban Chennai and Delhi, India. A meta-analytic approach was used to combine estimates, obtained from mixed-effects models and proportional hazards models, from the two cities.

RESULTS

We observed that 10 μg/m3 differences in monthly average exposure to PM2.5 was associated with a 0.40 mg/dL increase in FPG (95% CI 0.22 to 0.58) and 0.021 unit increase in HbA1c (95% CI 0.009 to 0.032). Further, 10 μg/m3 differences in annual average PM2.5 was associated with 1.22 (95% CI 1.09 to 1.36) times increased risk of incident T2DM, with non-linear exposure response.

CONCLUSIONS

We observed evidence of temporal association between PM2.5 exposure, and higher FPG and incident T2DM in two urban environments in India, thus highlighting the potential for population-based mitigation policies to reduce the growing burden of diabetes.

Does PM1 exposure during pregnancy impact the gut microbiota of mothers and neonates?

BACKGROUND

Ambient air pollutant exposure can change the composition of gut microbiota at 6-months of age, but there is no epidemiological evidence on the impacts of exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during pregnancy on gut microbiota in mothers and neonates. We aimed to determine if gestational PM1 exposure is associated with the gut microbiota of mothers and neonates.

METHODS

Leveraging a mother-infant cohort from the central region of China, we estimated the exposure concentrations of PM1 during pregnancy based on residential address records. The gut microbiota of mothers and neonates was analyzed using 16 S rRNA V3-V4 gene sequences. Functional pathway analyses of 16 S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The impact of PM1 exposure on α-diversity, composition, and function of gut microbiota in mothers and neonates was evaluated using multiple linear regression, controlling for nitrogen dioxide (NO2) and ozone (O3). Permutation multivariate analysis of variance (PERMANOVA) was used to analyze the interpretation degree of PM1 on the sample differences at the OTU level using the Bray-Curtis distance algorithm.

RESULTS

Gestational PM1 exposure was positively associated with the α-diversity of gut microbiota in neonates and explained 14.8% (adj. P = 0.026) of the differences in community composition among neonatal samples. In contrast, gestational PM1 exposure had no impact on the α- and β-diversity of gut microbiota in mothers. Gestational PM1 exposure was positively associated with phylum Actinobacteria of gut microbiota in mothers, and genera Clostridium_sensu_stricto_1, Streptococcus, Faecalibacterium of gut microbiota in neonates. At Kyoto Encyclopedia of Genes and Genomes pathway level 3, the functional analysis results showed that gestational PM1 exposure significantly down-regulated Nitrogen metabolism in mothers, as well as Two-component system and Pyruvate metabolism in neonates. While Purine metabolism, Aminoacyl-tRNA biosynthesis, Pyrimidine metabolism, and Ribosome in neonates were significantly up-regulated.

CONCLUSIONS

Our study provides the first evidence that exposure to PM1 has a significant impact on the gut microbiota of mothers and neonates, especially on the diversity, composition, and function of neonatal meconium microbiota, which may have important significance for maternal health management in the future.

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.

Cross-sectional and longitudinal relationships between ozone exposure and glucose homeostasis: Exploring the role of systemic inflammation and oxidative stress in a general Chinese urban population

The adverse health effects of ozone pollution have been a globally concerned public health issue. Herein we aim to investigate the association between ozone exposure and glucose homeostasis, and to explore the potential role of systemic inflammation and oxidative stress in this association. A total of 6578 observations from the Wuhan-Zhuhai cohort (baseline and two follow-ups) were included in this study. Fasting plasma glucose (FPG) and insulin (FPI), plasma C-reactive protein (CRP, biomarker for systemic inflammation), urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG, biomarker for oxidative DNA damage), and urinary 8-isoprostane (biomarker for lipid peroxidation) were repeatedly measured. After adjusting for potential confounders, ozone exposure was positively associated with FPG, FPI, and homeostasis model assessment of insulin resistance (HOMA-IR), and negatively associated with HOMA of beta cell function (HOMA-β) in cross-sectional analyses. Each 10 ppb increase in cumulative 7-days moving average ozone was associated with a 13.19%, 8.31%, and 12.77% increase in FPG, FPI, and HOMA-IR, respectively, whereas a 6.63% decrease in HOMA-β (all P < 0.05). BMI modified the associations of 7-days ozone exposure with FPI and HOMA-IR, and the effects were stronger in subgroup whose BMI ≥24 kg/m². Consistently high exposure to annual average ozone was associated with increased FPG and FPI in longitudinal analyses. Furthermore, ozone exposure was positively related to CRP, 8-OHdG, and 8-isoprostane in dose-response manner. Increased CRP, 8-OHdG, and 8-isoprostane could dose-dependently aggravate glucose homeostasis indices elevations related to ozone exposure. Increased CRP and 8-isoprostane mediated 2.11-14.96% of ozone-associated glucose homeostasis indices increment. Our findings suggested that ozone exposure could cause glucose homeostasis damage and obese people were more susceptible. Systemic inflammation and oxidative stress might be potential pathways in glucose homeostasis damage induced by ozone exposure.

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.

Association of ambient PM1 exposure with maternal blood pressure and hypertensive disorders of pregnancy in China

Evidence concerning PM1 exposure, maternal blood pressure (BP), and hypertensive disorders of pregnancy (HDP) is sparse. We evaluated the associations using 105,063 participants from a nationwide cohort. PM1 concentrations were evaluated using generalized additive model. BP was measured according to the American Heart Association recommendations. Generalized linear mixed models were used to assess the PM1-BP/HDP associations. Each 10 μg/m3 higher first-trimester PM1 was significantly associated with 1.696 mmHg and 1.056 mmHg higher first-trimester SBP and DBP, and with 11.4% higher odds for HDP, respectively. The above associations were stronger among older participants (> 35 years) or those educated longer than 17 years or those with higher household annual income (> 400,000 CNY). To conclude, first-trimester PM1 were positively associated with BP/HDP, which may be modified by maternal age, education level, and household annual income. Further research is warranted to provide more information for both health management of HDP and environmental policies enactment.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Transportation-related Environmental Mixtures and Diabetes Prevalence and Control in Urban/Metropolitan Counties in the United States

Diabetes rates in the United States are staggering and climbing. Importantly, traditional risk factors fail to completely account for the magnitude of the diabetes epidemic. Environmental exposures, including urban and metropolitan transportation quality, are implicated as contributors to disease. Using data from the county-level Environmental Quality Index (EQI) developed for the United States, we analyzed associations between transportation and air quality environmental metrics with overall diabetes prevalence and control within urban/metropolitan counties in the United States from 2006 to 2012. Additionally, we examined effect modification by race/ethnicity through stratification based on the county-level proportion of minority residents. Last, we applied mixture methods to evaluate the effect of simultaneous poor transportation factors and worse air quality on the same outcomes. We found that increased county-level particulate matter air pollution and nitrogen dioxide along with reduced public transportation usage and lower walkability were all associated with increased diabetes prevalence. The minority proportion of the population influences some of these relationships as some of the effects of air pollution and the transportation-related environment are worse among counties with more minority residents. Furthermore, the transportation and air quality mixtures were found to be associated with increased diabetes prevalence and reduced diabetes control. These data further support the burgeoning evidence that poor environments amplify diabetes risk. Future cohort studies should explore the utility of environmental policies and urban planning as tools for improving metabolic health.

The effect of ambient ozone exposure on three types of diabetes: a meta-analysis

BACKGROUND

Ozone as an air pollutant is gradually becoming a threat to people's health. However, the effect of ozone exposure on risk of developing diabetes, a fast-growing global metabolic disease, remains controversial.

OBJECTIVE

To evaluate the impact of ambient ozone exposure on the incidence rate of type 1, type 2 and gestational diabetes mellitus.

METHOD

We systematically searched PubMed, Web of Science, and Cochrane Library databases before July 9, 2022, to determine relevant literature. Data were extracted after quality evaluation according to the Newcastle Ottawa Scale (NOS) and the agency for healthcare research and quality (AHRQ) standards, and a meta-analysis was used to evaluate the correlation between ozone exposure and type 1 diabetes mellitus (T1D), type 2 diabetes mellitus (T2D), and gestational diabetes mellitus (GDM). The heterogeneity test, sensitivity analysis, and publication bias were performed using Stata 16.0.

RESULTS

Our search identified 667 studies from three databases, 19 of which were included in our analysis after removing duplicate and ineligible studies. Among the remaining studies, three were on T1D, five were on T2D, and eleven were on GDM. The result showed that ozone exposure was positively correlated with T2D [effect size (ES) = 1.06, 95% CI: 1.02, 1.11] and GDM [pooled odds ratio (OR) = 1.01, 95% CI: 1.00, 1.03]. Subgroup analysis demonstrated that ozone exposure in the first trimester of pregnancy might raise the risk of GDM. However, no significant association was observed between ozone exposure and T1D.

CONCLUSION

Long-term exposure to ozone may increase the risk of T2D, and daily ozone exposure during pregnancy was a hazard factor for developing GDM. Decreasing ambient ozone pollution may reduce the burden of both diseases.

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.

The long-term and short-term effects of ambient air pollutants on sleep characteristics in the Chinese population: big data analysis from real world by sleep records of consumer wearable devices

Several studies on long-term air pollution exposure and sleep have reported inconsistent results. Large-scale studies on short-term air pollution exposures and sleep have not been conducted. We investigated the associations of long- and short-term exposure to ambient air pollutants with sleep in a Chinese population based on over 1 million nights of sleep data from consumer wearable devices. Air pollution data including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected from the Ministry of Ecology and Environment. Short-term exposure was defined as a moving average of the exposure level for different lag days from Lag0 to Lag0-6. A 365-day moving average of air pollution was regarded as long-term exposure. Sleep data were recorded using wearable devices from 2017 to 2019. The mixed-effects model was used to evaluate the associations. We observed that sleep parameters were associated with long-term exposure to all air pollutants. Higher levels of air pollutant concentrations were associated with longer total sleep and light sleep duration, shorter deep sleep duration, and decreases in wake after sleep onset (WASO), with stronger associations of exposures to NO2 and CO [a 1-interquartile range (IQR) increased NO2 (10.3 μg/m3) was associated with 8.7 min (95% CI: 8.08 to 9.32) longer sleep duration, a 1-IQR increased CO (0.3 mg/m3) was associated with 5.0 min (95% CI: - 5.13 to - 4.89) shorter deep sleep duration, 7.7 min (95% CI: 7.46 to 7.85) longer light sleep duration, and 0.5% (95% CI: - 0.5 to - 0.4%) lower proportion of WASO duration to total sleep]. The cumulative effect of short-term exposure on Lag0-6 is similar to long-term exposure but relatively less. Subgroup analyses indicated generally greater effects on individuals who were female, younger (< 45 years), slept longer (≥ 7 h), and during cold seasons, but the pattern of effects was mixed. We supplemented two additional types of stratified analyses to reduce repeated measures of outcomes and exposures while accounting for individual variation. The results were consistent with the overall results, proving the robustness of the overall results. In summary, both short- and long-term exposure to air pollution affect sleep, and the effects are comparable. Although people tend to have prolonged total sleep duration with increasing air pollutant concentrations, their sleep quality might remain poor because of the reduction in deep sleep.

Associations of ozone exposure with gestational diabetes mellitus and glucose homeostasis: Evidence from a birth cohort in Shanghai, China

BACKGROUND

Associations between individual exposure to ozone (O₃) and gestational diabetes mellitus (GDM) have rarely been investigated, and critical windows of O₃ exposure for GDM have not been identified.

OBJECTIVES

We aimed to explore the associations of gestational O₃ exposure with GDM and glucose homeostasis as well as to identify the potential critical windows.

METHODS

A total of 7834 pregnant women were included. Individual O₃ exposure concentrations were evaluated using a high temporal-spatial resolution model. Each participant underwent an oral glucose tolerance test (OGTT) to screen for GDM between 24 and 28 gestational weeks. Multiple logistic and multiple linear regression models were used to estimate the associations of O₃ with GDM risks and with blood glucose levels of OGTT, respectively. Distributed lag nonlinear models (DLNMs) were used to estimate the critical windows of O₃ exposure for GDM.

RESULTS

Nearly 13.29 % of participants developed GDM. After controlling for covariates, we observed increased GDM risks per IQR increment of O₃ exposure in the first trimester (OR = 1.738, 95 % CI: 1.002-3.016) and the first two trimesters (OR = 1.576, 95 % CI: 1.005-2.473). Gestational O₃ exposure was positively associated with increased fasting blood glucose (the first trimester: β = 2.964, 95 % CI: 1.529-4.398; the first two trimesters: β = 1.620, 95 % CI: 0.436-2.804) and 2 h blood glucose (the first trimester: β = 6.569, 95 % CI: 1.775-11.363; the first two trimesters: β = 6.839, 95 % CI: 2.896-10.782). We also observed a concentration-response relationship of gestational O₃ exposure with GDM risk, as well as fasting and 2 h blood glucose levels. Additionally, 5-10 gestational weeks was identified as a critical window of O₃ exposure for GDM development.

CONCLUSION

In summary, we found that gestational O₃ exposure disrupts glucose homeostasis and increases the risk of GDM in pregnant women. Furthermore, 5-10 gestational weeks could be a critical window for the effects of O₃ exposure on GDM.