The Association Between PM2.5 and Ozone and the Prevalence of Diabetes Mellitus in the United States, 2002 to 2008

Spatiotemporal correlations of PM2.5 and O3 variations: A street-scale perspective on synergistic regulation

PM2.5 and O3 are major pollutants affecting air quality and posing serious health risks in China. While many studies focus on their control at urban and regional scales, their co-regulation at the street level-closely tied to traffic emissions and commuting patterns-remains unexplored. This study addressed the gap by using nonlinear statistical methods to analyze the spatiotemporal evolution of PM2.5 and O3 from street-scale mobile measurements in Fuzhou, China. A random forest (RF) model was applied to elucidate factors influencing PM2.5-O3 synchronicity. Key findings revealed that street-scale variations in PM2.5 and O3 exhibited multifractality and long-term persistence. Co-directional changes between PM2.5 and O3 peaked at noon, compared to traffic peak hours and midnight. An 800 m threshold was identified for analyzing PM2.5-O3 synchronicity-below this spatial scale, local factors weaken their concordance, while beyond it, the concordance strengthened. RF models showed that PM2.5 was primarily influenced by precursor substances in winter and meteorological conditions in summer, while O3 was consistently affected by meteorological conditions across both seasons. Road traffic and construction disrupted the co-directional changes of PM2.5 and O3, whereas high humidity partially mitigated high concentrations of both pollutants but enhanced their synchronicity.

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.

Temperature, relative humidity and elderly type 2 diabetes mortality: A spatiotemporal analysis in Shandong, China

BACKGROUND

The mortality of type 2 diabetes mellitus (T2DM) can be affected by environmental factors. However, few studies have explored the effects of environmental factors across diverse regions over time. Given the vulnerability observed in the elderly group in previous research, this research applied Bayesian spatiotemporal models to assess the associations in the elderly group.

METHODS

Data on T2DM death in the elderly group (aged over 60 years old) at the county level were collected from the National Death Surveillance System between 1st January 2013 and 31st December 2019 in Shandong Province, China. A Bayesian spatiotemporal model was employed with the integrated Nested Laplace Approach to explore the associations between socio-environmental factors (i.e., temperatures, relative humidity, the Normalized Difference Vegetation Index (NDVI), particulate matter with a diameter of 2.5 μm or less (PM2.5) and gross domestic product (GDP)) and T2DM mortality.

RESULTS

T2DM mortality in the elderly group was found to be associated with temperature and relative humidity (i.e., temperature: Relative Risk (RR) = 1.41, 95% Credible Interval (CI): 1.27-1.56; relative humidity: RR = 1.05, 95% CI:1.03-1.06), while no significant associations were found with NDVI, PM2.5 and GDP. In winter, significant impacts from temperature (RR = 1.18, 95% CI: 1.06-1.32) and relative humidity (RR = 0.94, 95% CI: 0.89-0.99) were found. Structured and unstructured spatial effects, temporal trends and space-time interactions were considered in the model.

CONCLUSIONS

Higher mean temperatures and relative humidities increased the risk of elderly T2DM mortality in Shandong Province. However, a higher humidity level decreased the T2DM mortality risk in winter in Shandong Province. This research indicated that the spatiotemporal method could be a useful tool to assess the impact of socio-environmental factors on health by combining the spatial and temporal effects.

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.

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.

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.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States

BACKGROUND

Exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment.

METHODS

Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3.

RESULTS

In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type.

CONCLUSIONS

Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

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.

Preliminary study on the effect of ozone exposure on blood glucose level in rats

BACKGROUND

In recent years, people have paid more and more attention to the health hazards caused by O3 exposure, which will become a major problem after fine particulate matter (PM).

OBJECTIVE

To investigate the effects of ozone (O3) exposure on blood glucose levels in rats under different concentrations and times.

METHODS

Eighty rats were divided into control group and three ozone concentration groups. Each group was continuously exposed for 1d, 3d and, 6d, and exposed for 6 hours daily. After exposure, GTT, FBG, and random blood glucose were measured.

RESULTS

The FBG value increased significantly on the 6th day of 0.5 ppm and the 3rd and 6th days of 1.0 ppm exposure compared with the control group (P< 0.05). The random blood glucose value was significantly increased on the 3rd and 6th days of each exposure concentration (P< 0.05). When exposed to 1 ppm concentration, the 120 min GTT value of 1 d, 3 d and, 6 d was significantly higher than that of the control group (P< 0.05).

CONCLUSION

After acute O3 exposure, the blood glucose level of rats was affected by the exposure concentration and time. The concentration of 0.1 ppm had no significant impact on FBG and random blood glucose, and O3 with a concentration of 0.1 ppm and 0.5 ppm had no significant impact on values of GTT at 90 min, and 120 min.

Effect of long-term exposure to PM2.5 on the risk of type 2 diabetes and arthritis in type 2 diabetes patients: Evidence from a national cohort in China

BACKGROUND

It remains unclear whether type 2 diabetes and the complication of arthritis are causally related to the PM_2.5 pollutant. Therefore, we aimed to investigate the associations of long-term PM_2.5 exposure with type 2 diabetes and with arthritis in type 2 diabetes patients.

MATERIALS AND METHODS

This study used data from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011-2018. The associations were analyzed by Cox proportional hazards regression models, and the population-attributable fraction (PAF) was calculated to assess the burden of type 2 diabetes and arthritis-attributable to PM_2.5.

RESULTS

A total of 21,075 participants were finally included, with 19,121 analyzed for PM_2.5 and type 2 diabetes risk and 12,427 analyzed for PM_2.5 and arthritis risk, of which 1,382 with newly-diagnosed type 2 diabetes and 1,328 with arthritis during the follow-up. Overall, each 10 μg/m³ increment in PM_2.5 concentration was significantly associated with an increase in the risk of type 2 diabetes (HR = 1.26, 95 %CI1.22 to 1.31), and the PAF of type 2 diabetes attributable to PM_2.5 was 13.54 %. In type 2 diabetes patients, each 10 μg/m³ increment in PM_2.5 exposure was associated with an increase in arthritis (HR = 1.42, 95 %CI: 1.28 to 1.57), and the association was significantly greater than that (H = 1.23, 95 %CI: 1.19 to 1.28) in adults without type 2 diabetes. The PAFs of arthritis-attributable to PM_2.5 in participants with and without type 2 diabetes were 18.54 % and 10.69 %, respectively.

CONCLUSION

Long-term exposure to PM_2.5 may increase the risk of type 2 diabetes and make type 2 diabetes patients susceptible to arthritis.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Physical activity attenuated the association of ambient ozone with type 2 diabetes mellitus and fasting blood glucose among rural Chinese population

The association of ozone with type 2 diabetes mellitus (T2DM) is uncertain. Moreover, the moderating effect of physical activity on this association is largely unknown. This study aims to evaluate the independent and combined effects of ozone and physical activity on T2DM and fasting blood glucose (FBG) in a Chinese rural adult population. A total of 39,192 participants were enrolled in the Henan Rural Cohort Study. Individual ozone exposure was assessed by using a satellite-based random forest model. The logistic regression and generalized linear models were used to evaluate the associations of ozone and physical activity with T2DM and FBG, respectively. Interaction plots were used to visualize the interaction effects of ozone and physical activity on T2DM or FBG. An interquartile range (IQR) increase in ozone exposure concentration was related to a 53.3% (odds ratio (OR),1.533; 95% confidence interval (CI), 1.426, 1.648) increase in odds of T2DM and a 0.292 mmol/L (95%CI, 0.263, 0.321) higher FBG level, respectively. The effects of ozone on T2DM and FBG generally decreased as physical activity levels increased. Negative additive interactions between ozone and physical activity on T2DM risk were observed (relative excess risk due to interaction (RERI), -0.261; 95%CI, -0.473, -0.048; attributable proportion due to interaction (AP), -0.203; 95%CI, -0.380, -0.027; synergy index (S), 0.520; 95%CI, 0.299, 0.904). The larger effects of ozone were observed among elderly and men on T2DM and FBG than young and women. Long-term exposure to ozone was associated with higher odds of T2DM and higher FBG levels, and these associations might be attenuated by increasing physical activity levels. In addition, there was a negative additive interaction (antagonistic effect) between ozone exposure and physical activity level on T2DM risk, suggesting that physical activity might be an effective method to reduce the burden of T2DM attributed to ozone exposure. Trail registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015, http://www.chictr.org.cn/showproj.aspx?proj=11375.

Insight into the physiological and pathological roles of the aryl hydrocarbon receptor pathway in glucose homeostasis, insulin resistance, and diabetes development

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcriptional factor that mediates the toxicities of several environmental pollutants. Decades of research have been carried out to understand the role of AhR as a novel mechanism for disease development. Its involvement in the pathogenesis of cancer, cardiovascular diseases, rheumatoid arthritis, and systemic lupus erythematosus have long been known. One of the current hot research topics is investigating the role of AhR activation by environmental pollutants on glucose homeostasis and insulin secretion, and hence the pathogenesis of diabetes mellitus. To date, epidemiological studies have suggested that persistent exposure to environmental contaminants such as dioxins, with subsequent AhR activation increases the risk of specific comorbidities such as obesity and diabetes. The importance of AhR signaling in various molecular pathways highlights that the role of this receptor is far beyond just xenobiotic metabolism. The present review aims at providing significant insight into the physiological and pathological role of AhR and its regulated enzymes, such as cytochrome P450 1A1 (CYP1A1) and CYP1B1 in both types of diabetes. It also provides a comprehensive summary of the current findings of recent research studies investigating the role of the AhR/CYP1A1 pathway in insulin secretion and glucose hemostasis in the pancreas, liver, and adipose tissues. This review further highlights the molecular mechanisms involved, such as gluconeogenesis, hypoxia-inducible factor (HIF), oxidative stress, and inflammation.

Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina

Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler ("downscaler") model, which provides spatial predictions of daily concentrations of fine particulate matter (PM2.5) and ozone (O3) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM2.5 and lower levels of O3. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM2.5 and O3, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PEPM2.5 and PEO3) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM2.5 and O3 levels decreased and O3 predictions became more reliable. However, the predictive uncertainty for PM2.5 has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM2.5. In contrast, racial isolation was associated with a greater decline in the reliability of PM2.5 predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O3 within the same time frame.

The links of fine airborne particulate matter exposure to occurrence of cardiovascular and metabolic diseases in Michigan, USA

Air pollutants, particularly airborne particulate matter with aerodynamic diameter < 2.5μm (PM2.5), have been linked to the increase in mortality and morbidity associated with cardiovascular and metabolic diseases. In this study, we investigated the dose-risk relationships between PM2.5 concentrations and occurrences of cardiovascular and metabolic diseases as well as the confounding socioeconomic factors in Michigan, USA, where PM2.5 levels are generally considered acceptable. Multivariate linear regression analyses were performed to investigate the relationship between health outcome and annual ground-level PM2.5 concentrations of 82 counties in Michigan. The analyses revelated significant linear dose-response associations between PM2.5 concentrations and cardiovascular disease (CVD) hospitalization. A 10 μg/m3 increase in PM2.5 exposure was found to be associated with a 3.0% increase in total CVD, 0.45% increase in Stroke, and a 0.3% increase in Hypertension hospitalization rates in Medicare beneficiaries. While the hospitalization rates of Total Stroke, Hemorrhagic Stroke, and Hypertension in urbanized counties were significantly higher than those of rural counties, the death rates of coronary heart disease and ischemic stroke in urbanized counties were significantly lower than those of rural counties. These results were correlated with the facts that PM2.5 levels in urbanized counties were significantly higher than that in rural counties and that the percentage of the population with health insurance and the median household income in rural counties were significantly lower. While obesity prevalence showed evidence of a weak positive correlation (ρ = 0.20, p-value = 0.078) with PM2.5 levels, there was no significant dose-response association between county diabetes prevalence rates and PM2.5 exposure in Michigan. In summary, this study revealed strong dose-response associations between PM2.5 concentrations and CVD incidence in Michigan, USA. The socioeconomic factors, such as access to healthcare resources and median household income, represent important confounding factors that could override the impact of PM2.5 exposure on CVD mortality.

Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China

Ambient PM_2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM_2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM_2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM_2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m³) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM_2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.

Evaluation of associations between estimates of particulate matter exposure and new onset type 2 diabetes in the REGARDS cohort

BACKGROUND

Studies of PM_2.5 and type 2 diabetes employ differing methods for exposure assignment, which could explain inconsistencies in this growing literature. We hypothesized associations between PM_2.5 and new onset type 2 diabetes would differ by PM_2.5 exposure data source, duration, and community type.

METHODS

We identified participants of the US-based REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort who were free of diabetes at baseline (2003-2007); were geocoded at their residence; and had follow-up diabetes information. We assigned PM_2.5 exposure estimates to participants for periods of 1 year prior to baseline using three data sources, and 2 years prior to baseline for two of these data sources. We evaluated adjusted odds of new onset diabetes per 5 µg/m³ increases in PM_2.5 using generalized estimating equations with a binomial distribution and logit link, stratified by community type.

RESULTS

Among 11,208 participants, 1,409 (12.6%) had diabetes at follow-up. We observed no associations between PM_2.5 and diabetes in higher and lower density urban communities, but within suburban/small town and rural communities, increases of 5 µg/m³ PM_2.5 for 2 years (Downscaler model) were associated with diabetes (OR [95% CI] = 1.65 [1.09, 2.51], 1.56 [1.03, 2.36], respectively). Associations were consistent in direction and magnitude for all three PM_2.5 sources evaluated.

SIGNIFICANCE

1- and 2-year durations of PM_2.5 exposure estimates were associated with higher odds of incident diabetes in suburban/small town and rural communities, regardless of exposure data source. Associations within urban communities might be obfuscated by place-based confounding.

The joint effects of physical activity and air pollution on type 2 diabetes in older adults

BACKGROUND

Older adults with type 2 diabetes are at higher risk of developing common geriatric syndromes and have a lower quality of life. To prevent type 2 diabetes in older adults, it's unclear whether the health benefits of physical activity (PA) will be influenced by the harms caused by increased exposure to air pollution during PA, especially in developing countries with severe air pollution problem. We aimed to investigate the joint effects of PA and long-term exposure to air pollution on the type 2 diabetes in older adults from China.

METHODS

This cross-sectional study was based on the China Multi-Ethnic cohort (CMEC) study. The metabolic equivalent of PA was calculated according to the PA scale during the CMEC baseline survey. High resolution air pollution datasets (PM₁₀, PM_2.5 and PM₁) were collected from open products. The joint effects were assessed by the marginal structural mean model with generalized propensity score.

RESULTS

A total of 36,562 participants aged 50 to 79 years were included in the study. The prevalence of type 2 diabetes was 10.88%. The mean (SD) level of PA was 24.93 (18.60) MET-h/d, and the mean (SD) level of PM₁₀, PM_2.5, and PM₁ were 70.00 (23.32) µg/m³, 40.45 (15.66) µg/m³ and 27.62 (6.51) µg/m³, respectively. With PM₁₀ < 92 µg/m³, PM_2.5 < 61 µg/m³, and PM₁ < 36 µg/m³, the benefit effects of PA on type 2 diabetes was significantly greater than the harms due to PMs when PA levels were roughly below 80 MET-h/d. With PM₁₀ ≥ 92 µg/m³, PM_2.5 ≥ 61 µg/m³, and PM₁ ≥ 36 µg/m³, the odds ratio (OR) first decreased and then rose rapidly with confidence intervals progressively greater than 1 and break-even points close to or even below 40 MET-h/d.

CONCLUSIONS

Our findings implied that for the prevention of type 2 diabetes in older adults, the PA health benefits outweighed the harms of air pollution except in extreme air pollution situations, and suggested that when the air quality of residence is severe, the PA levels should ideally not exceed 40 MET-h/d.

PM2.5 exposure as a risk factor for type 2 diabetes mellitus in the Mexico City metropolitan area

BACKGROUND

Exposure to air pollution is the main risk factor for morbidity and mortality in the world. Exposure to particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5) is associated with cardiovascular and respiratory conditions, as well as with lung cancer, and there is evidence to suggest that it is also associated with type II diabetes (DM). The Mexico City Metropolitan Area (MCMA) is home to more than 20 million people, where PM2.5 levels exceed national and international standards every day. Likewise, DM represents a growing public health problem with prevalence around 12%. In this study, the objective was to evaluate the association between exposure to PM2.5 and DM in adults living in the MCMA.

METHODS

Data from the 2006 or 2012 National Health and Nutrition Surveys (ENSANUT) were used to identify subjects with DM and year of diagnosis. We estimated PM2.5 exposure at a residence level, based on information from the air quality monitoring system (monitors), as well as satellite measurements (satellite). We analyzed the relationship through a cross-sectional approach and as a case - control study.

RESULTS

For every 10 μg/m3 increase of PM2.5 we found an OR = 3.09 (95% CI 1.17-8.15) in the 2012 sample. These results were not conclusive for the 2006 data or for the case - control approach.

CONCLUSIONS

Our results add to the evidence linking PM2.5 exposure to DM in Mexican adults. Studies in low- and middle-income countries, where PM2.5 atmospheric concentrations exceed WHO standards, are required to strengthen the evidence.

Does ozone inhalation cause adverse metabolic effects in humans? A systematic review

We utilized a practical, transparent approach for systematically reviewing a chemical-specific evidence base. This approach was used for a case study of ozone inhalation exposure and adverse metabolic effects (overweight/obesity, Type 1 diabetes [T1D], Type 2 diabetes [T2D], and metabolic syndrome). We followed the basic principles of systematic review. Studies were defined as "Suitable" or "Supplemental." The evidence for Suitable studies was characterized as strong or weak. An overall causality judgment for each outcome was then determined as either causal, suggestive, insufficient, or not likely. Fifteen epidemiologic and 33 toxicologic studies were Suitable for evidence synthesis. The strength of the human evidence was weak for all outcomes. The toxicologic evidence was weak for all outcomes except two: body weight, and impaired glucose tolerance/homeostasis and fasting/baseline hyperglycemia. The combined epidemiologic and toxicologic evidence was categorized as weak for overweight/obesity, T1D, and metabolic syndrome,. The association between ozone exposure and T2D was determined to be insufficient or suggestive. The streamlined approach described in this paper is transparent and focuses on key elements. As systematic review guidelines are becoming increasingly complex, it is worth exploring the extent to which related health outcomes should be combined or kept distinct, and the merits of focusing on critical elements to select studies suitable for causal inference. We recommend that systematic review results be used to target discussions around specific research needs for advancing causal determinations.

Air Pollutant Particles, PM2.5, Exposure and Glaucoma in Patients with Diabetes: A National Population-Based Nested Case-Control Study

The global prevalence of diabetes mellitus (DM) has reached 20%. Air pollutants with a particle size of less than 2.5 μm (PM2.5) are a globally recognized risk factor for diabetes and glaucoma. We examined whether the risk of glaucoma would decrease or increase when patients with DM were exposed to different PM2.5 concentrations. Data were obtained from the National Health Insurance Research Database (NHIRD) of Taiwan and the Air Quality Monitoring Network between 2008 and 2013. This nested case-control study involved 197 DM patients with glaucoma and 788 DM patients without glaucoma. Cases and controls were matched (1:4) by gender, age (±5 years), and index date (±6 months), and their data were entered in a logistic regression model adjusted for gender, age, urbanization level, income level, and comorbidities. The odds ratio (OR) of glaucoma at PM2.5 exposure concentration in the fourth quartile (Q4) compared with in the first quartile (Q1) was 1.7 (95% CI: 1.084-2.764). For glaucoma risk, the OR was 1.013 (95% CI: 1.006-1.020) at a PM2.5 exposure concentration in Q1, 1.004 (95% CI: 1.001-1.007) in the third quartile (Q3), and 1.003 (95% CI: 1.001-1.004) in Q4. In the subgroup analysis of patients living in non-emerging towns and non-agricultural towns, the OR for glaucoma in Q4 compared with in Q1 was 2.1 (95% CI: 1.229-3.406) and 1.8 (95% CI: 1.091-2.803), respectively (p trend = 0.001 and 0.011). For patients without migraine, the OR for glaucoma was 1.7 (95% CI: 1.074-2.782; p = 0.006). These results demonstrate that, for patients with DM, PM2.5 increased the risk of glaucoma and PM2.5 was an independent risk factor for glaucoma in patients with DM.

Five Year Trends of Particulate Matter Concentrations in Korean Regions (2015-2019): When to Ventilate?

Indoor air quality becomes more critical as people stay indoors longer, particularly children and the elderly who are vulnerable to air pollution. Natural ventilation has been recognized as the most economical and effective means of improving indoor air quality, but its benefit is questionable when the external air quality is unacceptable. Such risk-risk tradeoffs would require evidence-based guidelines for households and policymakers, but there is a lack of research that examines spatiotemporal long-term air quality trends, leaving us unclear on when to ventilate. This study aims to suggest the appropriate time for ventilation by analyzing the hourly and quarterly concentrations of particulate matter (PM)10 and PM2.5 in seven metropolitan cities and Jeju island in South Korea from January 2015 to September 2019. Both areas’ PM levels decreased until 2018 and rebounded in 2019 but are consistently higher in spring and winter. Overall, the average concentrations of PM10 and PM2.5 peaked in the morning, declined in the afternoon, and rebounded in the evening, but the second peak was more pronounced for PM2.5. This study may suggest ventilation in the afternoon (2–6pm) instead of the morning or late evening, but substantial differences across the regions by season encourage intervention strategies tailored to regional characteristics.

Ambient air pollution exposure association with diabetes prevalence and glycosylated hemoglobin (HbA1c) levels in China. Cross-sectional analysis from the WHO study of AGEing and adult health wave 1

Over the past decades, air pollution has become one of the critical environmental health issues in China. The present study aimed to evaluate links between ambient air pollution and the prevalence of type 2 diabetes mellitus (T2DM) and the levels of glycosylated hemoglobin (HbA1c). A multilevel linear and logistic regression was used to assess these associations among 7,770 participants aged ≥50 years from the WHO Study on global AGEing and adult health (SAGE) in China in 2007-2010. The average exposure to each of pollutants (particulate matter with an aerodynamic diameter of ≤10 μm/≤2.5 μm/≤1 μm [PM₁₀/PM_2.5/PM₁] and nitrogen dioxide [NO₂]) was estimated using a satellite-based spatial statistical model. In logistic models, a 10 µg/m³ increase in PM₁₀ and PM_2.5 was associated with increased T2DM prevalence (Prevalence Odds Ratio, POR: 1.27; 95% CI: 1.11, 1.45 and POR: 1.23; 95% CI: 1.03, 1.46). Similar increments in PM₁₀, PM_2.5, PM₁ and NO₂ were associated with increase in HbA1c levels of 1.8% (95% CI: 1.3, 2.3), 1.3% (95% CI: 1.1, 1.5), 0.7% (95% CI: 0.1, 1.3), and 0.8% (95% CI: 0.4, 1.2), respectively. In a large cohort of older Chinese adults, air pollution was liked to both higher T2DM prevalence and elevated HbA1c levels.

Associations of long-term exposure to PM1, PM2.5, NO2 with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations

OBJECTIVES

To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM1 and PM2.5), nitrogen dioxide (NO2) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations.

MATERIAL AND METHODS

A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM1, PM2.5, NO2 for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM1, PM2.5, NO2 exposure and type 2 diabetes prevalence and fasting blood glucose levels.

RESULTS

The mean 3-year residential exposure concentrations of PM1, PM2.5 and NO2 was 57.4 μg/m3, 73.4 μg/m3 and 39.9 μg/m3, respectively. Higher exposure concentrations of PM1, PM2.5, NO2 by 1 μg/m3 was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m3 increase of PM1, PM2.5 and NO2 was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels.

CONCLUSIONS

Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations.

Associations between long-term exposure to ambient air pollution and risk of type 2 diabetes mellitus: A systematic review and meta-analysis

Previous meta-analyses on associations between air pollution (AP) and type 2 diabetes mellitus (T2DM) were mainly focused on studies conducted in high-income countries. Evidence should be updated by including more recent studies, especially those conducted in low- and middle-income countries. We therefore conducted a systematic review and meta-analysis of epidemiological studies to conclude an updated pooled effect estimates between long-term AP exposure and the prevalence and incidence of T2DM. We searched PubMed, Embase, and Web of Science to identify studies regarding associations of AP with T2DM prevalence and incidence prior to January 2019. A random-effects model was employed to analyze the overall effects. A total of 30 articles were finally included in this meta-analysis. The pooled results showed that higher levels of AP exposure were significantly associated with higher prevalence of T2DM (per 10 μg/m3 increase in concentrations of particles with aerodynamic diameter < 2.5 μm (PM2.5): odds ratio (OR) = 1.09, 95% confidence interval (95%CI): 1.05, 1.13; particles with aerodynamic diameter < 10 μm (PM10): OR = 1.12, 95%CI: 1.06, 1.19; nitrogen dioxide (NO2): OR = 1.05, 95%CI:1.03, 1.08). Besides, higher level of PM2.5 exposure was associated with higher T2DM incidence (per 10 μg/m3 increase in concentration of PM2.5: hazard ratio (HR) = 1.10, 95%CI:1.04, 1.16), while the associations between PM10, NO2 and T2DM incidence were not statistically significant. The associations between AP exposure and T2DM prevalence showed no significant difference between high-income countries and low- and middle-incomes countries. However, different associations were identified between PM2.5 exposure and T2DM prevalence in different geographic areas. No significant differences were found in associations of AP and T2DM prevalence/incidence between females and males, except for the effect of NO2 on T2DM incidence. Overall, AP exposure was positively associated with T2DM. There still remains a need for evidence from low- and middle-income countries on the relationships between AP and T2DM.

Association between air pollution and type 2 diabetes: an updated review of the literature

Air pollution and type 2 diabetes mellitus (T2DM) are critical public health issues worldwide. A large number of epidemiological studies have highlighted the adverse effects of air pollution on diabetes, and include risk profiles for different exposure durations, study design types, subgroup populations, and effects of air pollution components. We researched PubMed, Google Scholar, and Web of Science to identify studies on the association between air pollution and T2DM from January 2009 to January 2019. The aim of this review is to provide a brief overview of epidemiological and experimental studies on air pollution associated with T2DM from the latest research, which may provide practical information about this relationship and possible mechanisms. Current cumulative evidence appears to suggest that T2DM-related biomarkers increase with increasing exposure duration and concentration of air pollutants. The chemical constituents of the air pollutant mixture may affect T2DM to varying degrees. The suggested mechanisms whereby air pollutants induce T2DM include increased inflammation, oxidative stress, and endoplasmic reticulum stress.