Epidemiology of air pollution and diabetes

Short-term Exposure to Wildfire-Specific PM2.5 and Diabetes Hospitalization: A Study in Multiple Countries and Territories

OBJECTIVE

To evaluate associations of wildfire fine particulate matter ≤2.5 mm in diameter (PM2.5) with diabetes across multiple countries and territories.

RESEARCH DESIGN AND METHODS

We collected data on 3,612,135 diabetes hospitalizations from 1,008 locations in Australia, Brazil, Canada, Chile, New Zealand, Thailand, and Taiwan during 2000-2019. Daily wildfire-specific PM2.5 levels were estimated through chemical transport models and machine-learning calibration. Quasi-Poisson regression with distributed lag nonlinear models and random-effects meta-analysis were applied to estimate associations between wildfire-specific PM2.5 and diabetes hospitalization. Subgroup analyses were by age, sex, location income level, and country or territory. Diabetes hospitalizations attributable to wildfire-specific PM2.5 and nonwildfire PM2.5 were compared.

RESULTS

Each 10 µg/m3 increase in wildfire-specific PM2.5 levels over the current day and previous 3 days was associated with relative risks (95% CI) of 1.017 (1.011-1.022), 1.023 (1.011-1.035), 1.023 (1.015-1.032), 0.962 (0.823-1.032), 1.033 (1.001-1.066), and 1.013 (1.004-1.022) for all-cause, type 1, type 2, malnutrition-related, other specified, and unspecified diabetes hospitalization, respectively. Stronger associations were observed for all-cause, type 1, and type 2 diabetes in Thailand, Australia, and Brazil; unspecified diabetes in New Zealand; and type 2 diabetes in high-income locations. An estimate of 0.67% (0.16-1.18%) and 1.02% (0.20-1.81%) for all-cause and type 2 diabetes hospitalizations were attributable to wildfire-specific PM2.5. Compared with nonwildfire PM2.5, wildfire-specific PM2.5 posed greater risks of all-cause, type 1, and type 2 diabetes and were responsible for 38.7% of PM2.5-related diabetes hospitalizations.

CONCLUSIONS

We show the relatively underappreciated links between diabetes and wildfire air pollution, which can lead to a nonnegligible proportion of PM2.5-related diabetes hospitalizations. Precision prevention and mitigation should be developed for those in advantaged communities and in Thailand, Australia, and Brazil.

The Risk of the Aggravation of Diabetic Foot According to Air Quality Factors in the Republic of Korea: A Nationwide Population-Based Study

This study aims to examine the association between the occurrence of diabetic foot and air quality (SO2, CO, NO2, O3). Open data were collected to conduct a big data study. Patient information was gathered from the National Health Insurance Service, and the National Institute of Environmental Science's air quality data were used. A total study population of 347,543 cases were reviewed (case = 13,353, control = 334,190). The lag period from air quality changes to the actual amputation operation was calculated for each factor. The frequency of diabetic foot amputation in each region was identified and analyzed using a distributed lag non-linear model. Gangwon-do showed the highest relative risks (RRs) for SO2 and CO, while Chungcheongnam-do exhibited the highest RR for NO2. Jeju had the highest RR for O3. Regions like Incheon, Busan, and the capital region also showed significant risk increases. These findings emphasize the importance of tailored air quality management to address diabetic foot complications effectively.

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.

Air pollution, life's essential 8, and risk of severe non-alcoholic fatty liver disease among individuals with type 2 diabetes

BACKGROUND

The impacts of long-term exposure to air pollution on the risk of subsequent non-alcoholic fatty liver disease (NAFLD) among participants with type 2 diabetes (T2D) is ambiguous. The modifying role of Life's Essential 8 (LE8) remains unknown.

METHODS

This study included 23,129 participants with T2D at baseline from the UK Biobank. Annual means of nitrogen dioxide (NO2), nitrogen oxides (NOX), and particulate matter (PM2.5, PM2.5-10, PM10) were estimated using the land-use regression model for each participant. The associations between exposure to air pollution and the risk of severe NAFLD were evaluated using Cox proportional hazard models. The effect modification of LE8 was assessed through stratified analyses.

RESULTS

During a median 13.6 years of follow-up, a total of 1,123 severe NAFLD cases occurred. After fully adjusting for potential covariates, higher levels of PM2.5 (hazard ratio [HR] = 1.12, 95%CI:1.02, 1.23 per interquartile range [IQR] increment), NO2 (HR = 1.15, 95%CI:1.04, 1.27), and NOX (HR = 1.08, 95%CI:1.01, 1.17) were associated with an elevated risk of severe NAFLD. In addition, LE8 score was negatively associated with the risk of NAFLD (HR = 0.97, 95% CI: 0.97, 0.98 per point increment). Compared with those who had low air pollution and high LE8, participants with a high air pollution exposure and low LE8 had a significantly higher risk of severe NAFLD.

CONCLUSIONS

Our findings suggest that long-term exposure to air pollution was associated with an elevated risk of severe NAFLD among participants with T2D. A lower LE8 may increase the adverse impacts of air pollution on NAFLD.

Global trends and spatial drivers of diabetes mellitus mortality, 1990-2019: a systematic geographical analysis

Objective

Diabetes mellitus is the leading cause of death worldwide, and multiple risk factors associated with diabetes mortality.

Methods

Employing spatial statistics, we characterized the spatial distribution and patterns of diabetes mortality, and revealed the spatial relationship between diabetes mortality and 11 socioeconomic and environmental risk factors at the country level, from 1990 to 2019.

Results

Globally, significantly high rates of diabetes mortality were primarily clustered in countries with limited land areas or located on islands, such as Fiji, Kiribati, Eswatini, and Trinidad and Tobago. Countries with weaker economic independence are more likely to have higher diabetes mortality rates. In addition, the impact of socioeconomic and environmental factors was significant at the country level, involving health expenditure, number of physicians, household and ambient air pollution, smoking, and alcohol consumption. Notably, the spatial relationship between diabetes mortality and ambient air pollution, as well as alcohol consumption, showed negative correlations. Countries with high diabetes mortality rates generally had lower levels of ambient air pollution and alcohol consumption.

Conclusion

The study highlights the spatial clustering of diabetes mortality and its substantial variation. While many risk factors can influence diabetes mortality, it's also essential to consider the level of these factors at the country level. Tailoring appropriate interventions based on specific national circumstances holds the potential to more effectively mitigate the burden of diabetes mortality.

Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.

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.

Exposure to PM2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.

The effect of haze pollution on rural-to-urban migrants' long-term residence intentions

Severe haze pollution in China threatens human health, and its negative effect hampers rural-to-urban migrants' settlement intentions in destination cities. Using the 2017 China Migrants Dynamic Survey Data (CMDS), the satellite data of PM2.5, and city-level data, this study investigates the impact of haze pollution on rural migrants, long-term residence intentions in Chinese context with IV-probit model, and mediating effect model. Overall, we find an inverted U-shaped relationship between the level of haze pollutants and rural migrants' long-term settlement intentions. Robustness check using multi-measures and thermal inversion as the instrumental variable supports this conclusion. The mediating effect model shows haze pollution plays its role through two opposite mechanisms: signal effect and health effect. When the size of signal effect is larger than health effect, rural migrants are inclined to settle down in their host cities; otherwise, they show lower settlement willingness. The turning point appears when PM2.5 concentration reaches 38.5 μg/m3; migrants have the highest long-term residence intentions. Currently, the national average PM2.5 concentration is 40.98 μg/m3, indicating that China is at the stage where the health effect of haze pollution holds a dominant position. Haze pollution has heterogeneous impacts on migrants' residence intentions. From the individual level, the younger generation, female, and higher-educated migrants have a higher tolerance for polluted air. From the city level, migrants who work in the city with 5 to 10 million dwellers have the highest long-term residence intention and are less sensitive to haze pollution. Thus, we propose stringent environmental regulations and more inclined public service policies to migrants.

Nanocurcumin Reduces High Glucose and Particulate Matter-Induced Endothelial Inflammation: Mitochondrial Function and Involvement of miR-221/222

Purpose

Particulate matter (PM) 2.5, harmful air pollutants, and diabetes are associated with high morbidity and mortality from cardiovascular disease (CVD). However, the molecular mechanisms underlying the combined effects of PM and diabetes on CVD remain unclear.

Methods

Endothelial cells (ECs) treated with high glucose (HG) and PM mimic hyperglycemia and air pollutant exposure in CVD. Endothelial inflammation was evaluated by Western blot and immunofluorescence of ICAM-1 expression and monocyte adhesion. The mechanisms underlying endothelial inflammation were elucidated through MitoSOX Red analysis, JC-1 staining, MitoTracker analysis, and Western blot analysis of mitochondrial fission-related, autophagy-related, and mitophagy-related proteins. Furthermore. nanocurcumin (NCur) pretreatment was used to test if it has a protective effect.

Results

ECs under co-exposure to HG and PM increased ICAM-1 expression and monocyte adhesion, whereas NCur pretreatment attenuated these changes and improved endothelial inflammation. PM exposure increased mitochondrial ROS levels, worsened mitochondrial membrane potential, promoted mitochondrial fission, induced mitophagy, and aggravated inflammation in HG-treated ECs, while NCur reversed these changes. Also, HG and PM-induced endothelial inflammation is through the JNK signaling pathway and miR-221/222 specifically targeting ICAM-1 and BNIP3. PM exposure also aggravated mitochondrial ROS levels, mitochondrial fission, mitophagy, and endothelial inflammation in STZ-induced hyperglycemic mice, whereas NCur attenuated these changes.

Conclusion

This study elucidated the mechanisms underlying HG and PM-induced endothelial inflammation in vitro and in vivo. HG and PM treatment increased mitochondrial ROS, mitochondrial fission, and mitophagy in ECs, whereas NCur reversed these conditions. In addition, miR-221/222 plays a role in the amelioration of endothelial inflammation through targeting Bnip3 and ICAM-1, and NCur pretreatment can modulate miR-221/222 levels. Therefore, NCur may be a promising approach to intervene in diabetes and air pollution-induced CVD.

Serum metabolome and liver transcriptome reveal acrolein inhalation-induced sex-specific homeostatic dysfunction

Acrolein, a respiratory irritant, induces systemic neuroendocrine stress. However, peripheral metabolic effects have not been examined. Male and female WKY rats were exposed to air (0 ppm) or acrolein (3.16 ppm) for 4 h, followed by immediate serum and liver tissue collection. Serum metabolomics in both sexes and liver transcriptomics in males were evaluated to characterize the systemic metabolic response. Of 887 identified metabolites, > 400 differed between sexes at baseline. An acrolein biomarker, 3-hydroxypropyl mercapturic acid, increased 18-fold in males and 33-fold in females, indicating greater metabolic detoxification in females than males. Acrolein exposure changed 174 metabolites in males but only 50 in females. Metabolic process assessment identified higher circulating free-fatty acids, glycerols, and other lipids in male but not female rats exposed to acrolein. In males, acrolein also increased branched-chain amino acids, which was linked with metabolites of nitrogen imbalance within the gut microbiome. The contribution of neuroendocrine stress was evident by increased corticosterone in males but not females. Male liver transcriptomics revealed acrolein-induced over-representation of lipid and protein metabolic processes, and pathway alterations including Sirtuin, insulin-receptor, acute-phase, and glucocorticoid signaling. In sum, acute acrolein inhalation resulted in sex-specific serum metabolomic and liver transcriptomic derangement, which may have connections to chronic metabolic-related diseases.

Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review

PURPOSE OF REVIEW

The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs.

RECENT FINDINGS

CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.

Hair and cord blood element levels and their relationship with air pollution, dietary intake, gestational diabetes mellitus, and infant neurodevelopment

BACKGROUND & AIMS

Exposure to a range of elements, air pollution, and specific dietary components in pregnancy has variously been associated with gestational diabetes mellitus (GDM) risk or infant neurodevelopmental problems. We measured a range of pregnancy exposures in maternal hair and/or infant cord serum and tested their relationship to GDM and infant neurodevelopment.

METHODS

A total of 843 pregnant women (GDM = 224, Non-GDM = 619) were selected from the Complex Lipids in Mothers and Babies cohort study. Forty-eight elements in hair and cord serum were quantified using inductively coupled plasma-mass spectrometry analysis. Binary logistic regression was used to estimate the associations between hair element concentrations and GDM risk, while multiple linear regression was performed to analyze the relationship between hair/cord serum elements and air pollutants, diet exposures, and Bayley Scales of infant neurodevelopment at 12 months of age.

RESULTS

After adjusting for maternal age, BMI, and primiparity, we observed that fourteen elements in maternal hair were associated with a significantly increased risk of GDM, particularly Ta (OR = 9.49, 95% CI: 6.71, 13.42), Re (OR = 5.21, 95% CI: 3.84, 7.07), and Se (OR = 5.37, 95% CI: 3.48, 8.28). In the adjusted linear regression model, three elements (Rb, Er, and Tm) in maternal hair and infant cord serum were negatively associated with Mental Development Index scores. For dietary exposures, elements were positively associated with noodles (Nb), sweetened beverages (Rb), poultry (Cs), oils and condiments (Ca), and other seafood (Gd). In addition, air pollutants PM2.5 (LUR) and PM10 were negatively associated with Ta and Re in maternal hair.

CONCLUSIONS

Our findings highlight the potential influence of maternal element exposure on GDM risk and infant neurodevelopment. We identified links between levels of these elements in both maternal hair and infant cord serum related to air pollutants and dietary factors.

The burden of Noncommunicable Diseases in Portuguese Language Countries

The present study analyzed trends in premature mortality from Noncommunicable diseases (NCDs) between 1990 and 2019, the projections up to 2030, and the risk factors (RFs) attributable to these diseases in the Community of Portuguese Language Countries (CPLP). Estimates from the Global Burden of Disease (GBD) study and the analysis of the burden of premature mortality due to NCDs were used for nine CPLP countries, applying age-standardized rates, using RStudio. Portugal, Brazil, Equatorial Guinea, Angola, and Guinea Bissau showed declining premature mortality rates caused by NCDs, while East Timor, Cape Verde, São Tomé and Príncipe, and Mozambique showed an increase in rates. Projections indicate that none of the countries is expected to achieve the goals of reducing premature mortality due to NCDs by one third by 2030. The attributable burden of disease showed that the most important RFs in 2019 were: high systolic blood pressure (SBP), tobacco, dietary risks, high body mass index (BMI), and air pollution. It can therefore be concluded that there are profound differences in the burden of NCDs among the countries, with better results in Portugal and Brazil, and that no CPLP country is likely to reach the NCD reduction target by 2030.

How heat waves, ozone and sunlight hours affect endocrine and metabolic diseases emergency admissions? A case study in the region of Madrid (Spain)

BACKGROUND

Studies which analyse the joint effect of acoustic or chemical air pollution variables and different meteorological variables on neuroendocrine disease are practically nonexistent. This study therefore sought to analyse the impact of air pollutants and environmental meteorological variables on daily unscheduled admissions due to endocrine and metabolic diseases in the Madrid Region from January 01, 2013 to December 31, 2018.

MATERIAL AND METHODS

We conducted a longitudinal, retrospective, ecological study of daily time series analysed by Poisson regression, with emergency neuroendocrine-disease admissions in the Madrid Region as the dependent variable. The independent variables were: mean daily concentrations of PM₁₀, PM_2.5, NO₂ and O₃; acoustic pollution; maximum and minimum daily temperatures; hours of sunlight; relative humidity; wind speed; and air pressure above sea level. Estimators of the statistically significant variables were used to calculate the relative risks (RRs).

RESULTS

A statistically significant association was found between the increase in temperatures in heat waves, RR: 1.123 95% CI (1.001-1.018), and the number of emergency admissions, making it the main risk factor. An association between a decrease in sunlight and an increase in hospital admissions, RR: 1.005 95% CI (1.002 1.008), was likewise observed. Similarly, ozone, in the form of mean daily concentrations in excess of 44 μg/m³, had an impact on admissions due to neuroendocrine disease, RR: 1.010 95% CI (1.007-1.035). The breakdown by sex showed that in the case of women, NO₂ was also a risk factor, RR: 1.021 95% CI (1.007-1.035).

CONCLUSION

The results obtained in this study serve to identify risk factors for this disease, such as extreme temperatures in heat waves, O₃ or NO₂. The robust association found between the decrease in sunlight and increase in hospital admissions due to neuroendocrine disease serves to spotlight an environmental factor which has received scant attention in public health until now.

Long-term exposure to PM2.5 and O3 with cardiometabolic multimorbidity: Evidence among Chinese elderly population from 462 cities

Cardiometabolic multimorbidity (CMM) refers to the presence of multiple cardiovascular and metabolic diseases (CMDs), such as hypertension, diabetes, and cardio-cerebrovascular diseases (CCVD), in the same individual, and has emerge as a significant global health concern due to population aging. Although previous research has demonstrated the association between cardiovascular and metabolic diseases and air pollutants, evidence on the link between CMM and air pollution exposure among Chinese older adults is limited. To address this research gap, we conducted a national representative survey of 222,179 adults aged 60 and older to investigate the epidemiology of CMM and its association with long-term exposure to PM_2.5 and O₃ in China's elderly population. We found that the prevalence of CMM among Chinese older adults was 16.9%, and hypertension and CCVD were the most common CMM cluster (10.8%). After adjusting for confounding variables, we observed a significant positive association between PM_2.5 exposure and the prevalence of hypertension, diabetes, and CCVD, with a respective excess risk increase of 3.2%, 3.6%, and 5.5% for every 10-unit increase. Moreover, every 10-unit increase in PM_2.5 was linked to a higher risk of hypertension and diabetes (2.2%), hypertension and CCVD (5.4%), diabetes and CCVD (5.6%), and hypertension, diabetes, and CCVD combined (7.6%). We also found a U-shaped curve relationship between O₃ exposure and the occurrence of hypertension, diabetes, and CCVD, as well as different subtypes of CMM, with the lowest risk of O₃ exposure was observed near 75-80 μg/m³. Furthermore, we identified that female and rural residents are more vulnerable to the health risks of air pollution than male and urban residents. Given the increasing aging of the population and rising prevalence of multimorbidity, policymakers should focus more attention on the female and rural elderly population to prevent and control CMM. This study provides compelling evidence that reducing air pollution levels can be an effective strategy to prevent and manage CMM among older adults.

Exposure to various ambient air pollutants and 9 cardiovascular conditions among individuals with diabetes: A prospective analysis of the UK Biobank

BACKGROUND AND AIMS

The adverse effects of air pollutants on the risk of most cardiovascular diseases (CVDs) are well-established, but the risk of CVDs such as deep vein thrombosis, pulmonary embolism, or aortic valve stenosis have been underappreciated, especially in the diabetic population. This study aimed to evaluate associations between long-term air pollutants exposure and the risk of incident CVDs among participants with diabetes.

METHODS

This study included 27,827 participants with baseline diabetes from the UK Biobank. We then estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for CVDs associated with chronic air pollutant exposure in the diabetic population by fitting the Cox proportional hazards model. Moreover, we investigated the cardiovascular effects of air pollutants at concentrations below WHO guideline limits.

RESULTS

After multivariable adjustment, long-term NO₂ and NO_x exposures were positively associated with the development of 8 and 6 types of CVDs in participants with diabetes, respectively. In term of particulate matters, the effect estimates ranged from 1.51 (1.13, 2.03) (coronary artery disease) to 4.65 (2.73, 7.92) (peripheral arterial disease) per 10 μg/m³ increase in PM_2.5. Whereas, the effect estimates ranged from 1.15 (1.04, 1.27) (arterial hypertension) to 2.28 (1.40, 3.69) (pulmonary embolism) per 10 μg/m³ increase in PM₁₀. In addition, our study discovered that for most of the cardiovascular events (8 of 9), the deleterious effects of air pollutants persisted even when participants were exposed to air pollutants concentrations below WHO guideline limits.

CONCLUSIONS

Long-term exposure to ambient NO₂, NO_x, PM_2.5, and PM₁₀, either at normal or low level, increased risk of various cardiovascular outcomes in the diabetic population.

Exercise in the Prevention and Treatment of Type 2 Diabetes

Type 2 diabetes is a systemic, multifactorial disease that is a leading cause of morbidity and mortality globally. Despite a rise in the number of available medications and treatments available for management, exercise remains a first-line prevention and intervention strategy due to established safety, efficacy, and tolerability in the general population. Herein we review the predisposing risk factors for, prevention, pathophysiology, and treatment of type 2 diabetes. We emphasize key cellular and molecular adaptive processes that provide insight into our evolving understanding of how, when, and what types of exercise may improve glycemic control. © 2023 American Physiological Society. Compr Physiol 13:1-27, 2023.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

Association of physical activity and air pollution exposure with the risk of type 2 diabetes: a large population-based prospective cohort study

BACKGROUND

The interplay between physical activity (PA) and air pollution in relation to type 2 diabetes (T2D) remains largely unknown. Based on a large population-based cohort study, this study aimed to examine whether the benefits of PA with respect to the risk of T2D are moderated by exposure to air pollution.

METHODS

UK Biobank participants (n = 359,153) without diabetes at baseline were included. Information on PA was obtained using the International Physical Activity Questionnaire short form. Exposure to air pollution, including PM_2.5, PM_coarse (PM_2.5-10), PM₁₀, and NO_2, was estimated from land use regression models. Cox regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs).

RESULTS

During a median of 8.9 years of follow-up, 13,706 T2D events were recorded. Compared with a low PA level, the HRs for the risk of T2D among individuals with moderate and high PA were 0.82 (95% CI, 0.79-0.86) and 0.73 (95% CI, 0.70-0.77), respectively. Compared with low levels of air pollution, the HRs for risk of T2D for high levels of air pollution (PM_2.5, PM_coarse, PM₁₀, and NO₂) were 1.19 (1.14-1.24), 1.06 (1.02-1.11), 1.13 (1.08-1.18), and 1.19 (1.14-1.24), respectively. There was no effect modification of the associations between PA and T2D by air pollution (all P-interactions > 0.05). The inverse associations between PA and T2D in each air pollution stratum were generally consistent (all P for trend < 0.05).

CONCLUSION

A higher PA and lower air pollution level were independently associated with a lower risk of T2D. The beneficial effects of PA on T2D generally remained stable among participants exposed to different levels of air pollution. Further studies are needed to replicate our findings in moderately and severely polluted areas.

Environmental Stressors and the PINE Network: Can Physical Environmental Stressors Drive Long-Term Physical and Mental Health Risks?

Both psychosocial and physical environmental stressors have been linked to chronic mental health and chronic medical conditions. The psycho-immune-neuroendocrine (PINE) network details metabolomic pathways which are responsive to varied stressors and link chronic medical conditions with mental disorders, such as major depressive disorder via a network of pathophysiological pathways. The primary objective of this review is to explore evidence of relationships between airborne particulate matter (PM, as a concrete example of a physical environmental stressor), the PINE network and chronic non-communicable diseases (NCDs), including mental health sequelae, with a view to supporting the assertion that physical environmental stressors (not only psychosocial stressors) disrupt the PINE network, leading to NCDs. Biological links have been established between PM exposure, key sub-networks of the PINE model and mental health sequelae, suggesting that in theory, long-term mental health impacts of PM exposure may exist, driven by the disruption of these biological networks. This disruption could trans-generationally influence health; however, long-term studies and information on chronic outcomes following acute exposure event are still lacking, limiting what is currently known beyond the acute exposure and all-cause mortality. More empirical evidence is needed, especially to link long-term mental health sequelae to PM exposure, arising from PINE pathophysiology. Relationships between physical and psychosocial stressors, and especially the concept of such stressors acting together to impact on PINE network function, leading to linked NCDs, evokes the concept of syndemics, and these are discussed in the context of the PINE network.

Long-term exposure to air pollution and risk of incident inflammatory bowel disease among middle and old aged adults

BACKGROUND

Epidemiological evidence regarding the associations between long-term exposure to air pollution and risk of incident inflammatory bowel disease (IBD) is scant.

OBJECTIVES

We examined the associations of various specific air pollutants with the risk of incident ulcerative colitis and Crohn's disease, two subtypes of IBD, among middle and old aged adults in the UK. We also explored potential susceptible subgroups.

METHODS

We used data from the UK Biobank study. Information on air pollution, including PM_2.5, PM_2.5-10, PM₁₀ as well as NO₂ and NO_x were estimated using the Land Use Regression model. Multivariable Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

After a median follow-up of 11.7 years, 1872 incident ulcerative colitis and 865 incident Crohn's disease cases were identified among 455,210 IBD-free participants. HRs (95% CIs) of ulcerative colitis associated with each 1 interquartile range (IQR) increase in PM_2.5, PM_2.5-10, PM₁₀, NO₂, and NO_x were 1.06 (1.01, 1.12), 1.03 (0.99, 1.08), 1.09 (1.03, 1.16), 1.12 (1.07, 1.19), and 1.07 (1.02, 1.12), respectively. The associations between all the air pollutants and risk of Crohn's disease were null. Smoking status and sex appeared to respectively modify the associations between some air pollutants and risk of ulcerative colitis and Crohn's disease.

CONCLUSION

Long-term exposure to various air pollutants was associated with the risk of incident ulcerative colitis but not Crohn's disease, highlighting the importance of developing environmental health strategy to reduce the burden of ulcerative colitis.

Adrenal stress hormone regulation of hepatic homeostatic function after an acute ozone exposure in Wistar-Kyoto male rats

Ozone-induced lung injury and inflammation and pulmonary/hypothalamus gene expression changes are diminished in adrenalectomized (AD) rats. Acute ozone exposure induces metabolic alterations concomitant with increases in epinephrine and corticosterone. We hypothesized that adrenal hormones are responsible for observed hepatic ozone effects, and in AD rats, these changes would be diminished. 5-7 days after sham (SH) or AD surgeries, male Wistar-Kyoto rats were exposed to air or 0.8-ppm ozone for 4-hrs. Serum samples were analyzed for metabolites and liver for transcriptional changes immediately post-exposure. Ozone increased circulating triglycerides, cholesterol, free fatty-acids, and leptin in SH but not AD rats. Ozone-induced inhibition of glucose-mediated insulin release was absent in AD rats. Unlike diminution of ozone-induced hypothalamus and lung mRNA expression changes, AD in air-exposed rats (AD-air/SH-air) caused differential hepatic expression of ∼1000 genes. Likewise, ozone in AD rats caused differential expression of ∼1000 genes (AD-ozone/AD-air). Ozone-induced hepatic changes in SH rats reflected enrichment for pathways involving metabolic processes, including acetyl-CoA biosynthesis, TCA cycle, and sirtuins. Upstream predictor analysis identified similarity to responses produced by glucocorticoids and pathways involving forskolin. These changes were absent in AD rats exposed to ozone. However, ozone caused unique changes in AD liver mRNA reflecting activation of synaptogenesis, neurovascular coupling, neuroinflammation, and insulin signaling with inhibition of senescence pathways. In these rats, upstream predictor analysis identified numerous microRNAs involved in glucocorticoid insufficiency. These data demonstrate the critical role of adrenal stress hormones in ozone-induced hepatic homeostasis and necessitate further research elucidating their role in propagating environmentally driven diseases.

Associations between Traffic-Related Air Pollution and Cognitive Function in Australian Urban Settings: The Moderating Role of Diabetes Status

Traffic-related air pollution (TRAP) is associated with lower cognitive function and diabetes in older adults, but little is known about whether diabetes status moderates the impact of TRAP on older adult cognitive function. We analysed cross-sectional data from 4141 adults who participated in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study in 2011-2012. TRAP exposure was estimated using major and minor road density within multiple residential buffers. Cognitive function was assessed with validated psychometric scales, including: California Verbal Learning Test (memory) and Symbol-Digit Modalities Test (processing speed). Diabetes status was measured using oral glucose tolerance tests. We observed positive associations of some total road density measures with memory but not processing speed. Minor road density was not associated with cognitive function, while major road density showed positive associations with memory and processing speed among larger buffers. Within a 300 m buffer, the relationship between TRAP and memory tended to be positive in controls (β = 0.005; p = 0.062), but negative in people with diabetes (β = -0.013; p = 0.026) and negatively associated with processing speed in people with diabetes only (β = -0.047; p = 0.059). Increased TRAP exposure may be positively associated with cognitive function among urban-dwelling people, but this benefit may not extend to those with diabetes.

Long-term exposure to objective and perceived residential greenness and diabetes mortality: A census-based cohort study

BACKGROUND

Residing close to green spaces might reduce diabetes mellitus (DM) risk; however, evidence for diabetes mortality is limited. Moreover, individual and neighbourhood social factors may determine DM risk. Exposure to green spaces may also depend on socioeconomic position (SEP). This study examined the associations between residential greenness and diabetes-related mortality, and the role of the social environment in these associations.

METHODS

We used the 2001 Belgian census linked to mortality register data for the period 2001-2014. We included individuals aged 40-79 years old and residing in the five largest Belgian urban areas at baseline. Exposure to residential greenness was assessed with surrounding greenness using the Normalized Difference Vegetation Index (NDVI) within 500-m of residence (objective indicator), and perceived neighbourhood greenness (subjective indicator). We conducted mixed-effects Cox proportional hazards models to obtain hazard ratios (HR) for diabetes-related mortality per interquartile range (IQR) increments of residential greenness. We assessed effect modification by social factors through stratification.

RESULTS

From 2,309,236 individuals included at baseline, 1.2% died from DM during follow-up. Both residential greenness indicators were inversely associated with diabetes-related mortality after adjustment for individual social factors. After controlling for neighbourhood SEP, the beneficial association with surrounding greenness disappeared [HR 1.02 (95%CI:0.99,1.06)], but persisted with perceived neighbourhood greenness [HR 0.93 (95%CI:0.91,0.95)]. After stratification the inverse associations with perceived neighbourhood greenness were strongest for women, the lowest educated, and individuals residing in least deprived neighbourhoods.

CONCLUSIONS

Our findings suggest that an overall positive perception of neighbourhood green spaces reduces independently the risk of diabetes-related mortality, regardless of the neighbourhood social environment. Nevertheless, neighbourhood SEP may be a strong confounder in the associations between diabetes-related mortality and greenness indicators derived from satellite images. Perception factors not captured by objective measurements of green spaces are potentially relevant in the association with DM, especially among disadvantaged groups.

Mediating effects of gut microbiota in the associations of air pollutants exposure with adverse pregnancy outcomes

BACKGROUND

The aim of this study was to investigate alterations in gut microbiota after exposure to air pollutants during pregnancy and its mediation effect in inducing adverse pregnancy outcomes (APOs).

METHODS

Participants (n = 916) were enrolled between 2017 and 2018 from a prospective cohort study of pregnant women in Guangzhou, China. The relative abundance of fecal microbiota was profiled using 16SrRNA V4 region sequencing. Exposure to air pollutants in each trimester of pregnancy was assessed using measurements from the nearest monitoring station. APOs including pre-term birth (PTB), post-term birth (POTB), low birth weight (LBW), macrosomia fetus (MF), birth defects (BDs), pathological cesarean section (PCS) and postpartum hemorrhage (PPH)) were determined by referring to reliable clinical records and diagnostic criteria. Univariate analysis, multivariate analysis and mediation analysis were performed to estimate the association among air pollutants, gut microbiota and APOs.

RESULTS

Air pollutants exposure during pregnancy was significantly correlated with the alterations in the gut microbiota, and increased risks of various APOs by 1.07-1.36-fold (P < 0.05). The mediation analyses indicated that alterations in Eggerthella, Phascolarctobacterium and Clostridium partially mediated the effects of air pollutants exposure (PM2.5, PM10, O3, NO2 and SO2) on APOs. The relative abundance of f_Micrococcaceae explained 11.39%, 64.90% and 54.80% of the correlation between SO2, PM2.5, PM10 and POTB, respectively; whereas g_Rothia explained 11.97%, 67.80% and 54.50%, respectively. g_Parabacteroides explained 53.0% of the correlation between PM2.5 and PTB.

CONCLUSIONS

Increased air pollutants exposure during pregnancy may induce adverse pregnancy outcomes via alteration of the gut microbiota.

Combined exposure to fine particulate matter and high glucose aggravates endothelial damage by increasing inflammation and mitophagy: the involvement of vitamin D

Background

Cardiovascular diseases (CVDs) are related to particulate matter (PM_2.5) exposure. Researchers have not clearly determined whether hyperglycemia, a hallmark of diabetes, exacerbates PM_2.5-induced endothelial damage. Thus, this study aimed to investigate the combined effects of PM_2.5 and high glucose on endothelial damage.

Results

Here, we treated human umbilical vein endothelial cells (HUVECs) with 30 mM high glucose and 50 μg/mL PM (HG + PM) to simulate endothelial cells exposed to hyperglycemia and air pollution. First, we showed that HUVECs exposed to PM under high glucose conditions exhibited significant increases in cell damage and apoptosis compared with HUVECs exposed to PM or HG alone. In addition, PM significantly increased the production of reactive oxygen species (ROS) in HUVECs and mitochondria treated with HG and decreased the expression of superoxide dismutase 1 (SOD1), a free radical scavenging enzyme. The coexposure group exhibited significantly increased ROS production in cells and mitochondria, a lower mitochondrial membrane potential, and increased levels of the autophagy-related proteins p62, microtubule-associated protein 1 light chain 3β (LC3B), and mitophagy-related protein BCL2 interacting protein 3 (Bnip3). Moreover, autophagosome-like structures were observed in the HG + PM group using transmission electron microscopy. The expression of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) were also increased through the JNK/p38 signaling pathway in the HG + PM group. As a ROS scavenger, vitamin D treatment effectively protected cells under HG and PM conditions by increasing cell viability, reducing mitochondrial ROS production, and suppressing the formation of mitophagy and inflammation. Furthermore, diabetes was induced in mice by administering streptozotocin (STZ). Mice were treated with PM by intratracheal injection. Vitamin D effectively alleviated oxidative stress, mitophagy, and inflammation in the aortas of mice treated with STZ and PM.

Conclusion

Taken together, simultaneous exposure to PM and high glucose exerts significant harmful effects on endothelial cells by inducing ROS production, mitophagy, and inflammation, while vitamin D reverses these effects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12989-022-00462-1.

Long-term exposure to ambient air pollutants and age-related macular degeneration in middle-aged and older adults

Absract In developed countries, age-related macular degeneration (AMD) is a leading cause of irreversible blindness in adults. The key pathways of AMD are suggested to be excessive oxidative stress and inflammation in the central retina. Because air pollution has been found capable of inducing oxidative stress and inflammation, it may play a role in development of AMD. This study investigated the association between ambient air pollution and AMD in 15,115 middle-aged and older adults (≥40 years) from Korean National Health and Nutrition Examination Survey 2008-2012. After controlling for important confounders, ambient NO₂ and CO in current-to-5 prior years and PM₁₀ in 2-to-5 prior years were significantly associated with higher prevalence of early AMD, while O₃ in current-to-5 prior years was significantly associated with lower prevalence of early AMD. When modeled air pollution within administrative division units, its ORs with an IQR increase in NO₂, CO, and O₃ at current year were 1.24 (95% CI: 1.05-1.46), 1.22 (95% CI: 1.09-1.38), and 0.80 (95% CI: 0.70-0.92), respectively. Overall, results from air pollution at local/town units were consistent with those at administrative division units. Long-term exposures to ambient air pollution may play a role in the risk of AMD in middle-aged and older adults.

Research on prediction of daily admissions of respiratory diseases with comorbid diabetes in Beijing based on long short-term memory recurrent neural network

To compare the performance of generalized additive model (GAM) and long short-term memory recurrent neural network (LSTM-RNN) on the prediction of daily admissions of respiratory diseases with comorbid diabetes. Daily data on air pollutants, meteorological factors and hospital admissions for respiratory diseases from Jan 1st, 2014 to Dec 31st, 2019 in Beijing were collected. LSTM-RNN was used to predict the daily admissions of respiratory diseases with comorbid diabetes, and the results were compared with those of GAM. The evaluation indexes were calculated by five-fold cross validation. Compared with the GAM, the prediction errors of LSTM-RNN were significantly lower [root mean squared error (RMSE): 21.21±3.30 vs. 46.13±7.60, <0.01; mean absolute error (MAE): 14.64±1.99 vs. 36.08±6.20, <0.01], and the value was significantly higher (0.79±0.06 vs. 0.57±0.12, <0.01). In gender stratification, RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting female admission (all <0.05), but there were no significant difference in predicting male admission between two models (all >0.05). In seasonal stratification, RMSE and MAE of LSTM-RNN were lower than those of GAM in predicting warm season admission (all <0.05), but there was no significant difference in value (>0.05). There were no significant difference in RMSE, MAE and between the two models in predicting cold season admission (all >0.05). In the stratification of functional areas, the RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting core area admission (all <0.05). has lower prediction errors and better fitting than the GAM, which can provide scientific basis for precise allocation of medical resources in polluted weather in advance.

Longitudinal relationship of particulate matter and metabolic control and severe hypoglycaemia in children and adolescents with type 1 diabetes

BACKGROUND

Evidence for the metabolic impact of long-term exposure to air pollution on diabetes is lacking. We investigated the association of particulate matter <10 μm (PM₁₀) and <2.5 μm (PM_2.5) with yearly averages of HbA1c, daily insulin dose (IU/kg) and rates of severe hypoglycaemia in type 1 diabetes (T1D).

METHODS

We studied data of 44,383 individuals with T1D < 21 years which were documented in 377 German centres within the diabetes prospective follow-up registry (DPV) between 2009 and 2018. Outcomes were aggregated by year and by patient. PM₁₀-and PM_2.5-yearly averages prior to the respective treatment year were linked to individuals via the five-digit postcode areas of residency. Repeated measures linear and negative binomial regression were used to study the association between PM-quartiles (Q1 lowest, Q4 highest concentration) and yearly averages of HbA1c, daily insulin dose and rates of severe hypoglycaemia (confounders: sex, time-dependent age, age at diabetes onset, time-dependent type of treatment, migratory background, degree of urbanisation and socioeconomic index of deprivation).

RESULTS

Adjusted mean HbA1c increased with PM₁₀ (Q1: 7.96% [95%-CI: 7.95-7.98], Q4: 8.03% [8.02-8.05], p-value<0.001) and with PM_2.5 (Q1: 7.97% [7.95-7.99], Q4: 8.02% [8.01-8.04], p < 0.001). Changes in daily insulin dose were inversely related to PM (PM₁₀ and PM_2.5: Q1 0.85 IU/kg [0.84-0.85], Q4: 0.83 IU/kg [0.82-0.83], p < 0.001). Adjusted rates of severe hypoglycaemia increased with PM-quartile groups (PM₁₀ Q1:11.2 events/100 PY [10.9-11.5], PM₁₀ Q4: 15.3 [14.9-15.7], p < 0.001; PM_2.5 Q1: 9.9 events/100 PY [9.6-10.2], PM_2.5 Q4: 14.2 [13.9-14.6], p < 0.001).

DISCUSSION

Air pollution was associated with higher HbA1c levels and increased risk of severe hypoglycaemia in people with T1D, consequently indicating a higher risk of diabetes complications. Further studies are needed to explore causal pathways of the observed associations.

Effect of sulfur dioxide exposure on histopathology and morphometry of pancreatic islet cells and glycemic indices in Wistar rats

Sulfur dioxide (SO₂) is a ubiquitous air pollutant. Recent studies suggest that SO₂ is a momentous risk factor for diabetes mellitus (DM). The present investigation aimed to evaluate the effects of SO₂ exposure on histopathology and morphometry of pancreatic islet cells and serum glycemic indices in rats. Sixteen male Wistar rats were divided equally into SO₂ and control groups. SO₂ group was exposed to 10 parts per million (ppm) SO₂ for 5 weeks (6 days a week, 3 h/day) and control group to filtered air for the same time as SO₂ group. Blood serums were collected and pancreatic tissue isolated. Glycemic indices were measured. Pathological and morphometric changes were studied in the pancreatic tissues. Exposure to SO₂ caused a significant increase in blood glucose but did not significantly change insulin and HbA1c serum levels and HOMA-IR. There were significant differences in vascular congestion (p= 0.02) and insulitis (p= 0.04) between the groups. SO₂ inhalation significantly reduced beta cell number and beta-alpha cell ratio compared with the control group (p=0.03 and p<0.0001, respectively). These findings suggest that SO₂ exposure damages pancreatic tissue which subsequently influences either the incidence of DM or the trend of diabetic complications.

Traffic-related air pollution is associated with glucose dysregulation, blood pressure, and oxidative stress in children

BACKGROUND

Metabolic syndrome increases the risk of cardiovascular disease in adults. Antecedents likely begin in childhood and whether childhood exposure to air pollution plays a contributory role is not well understood.

OBJECTIVES

To assess whether children's exposure to air pollution is associated with markers of risk for metabolic syndrome and oxidative stress, a hypothesized mediator of air pollution-related health effects.

METHODS

We studied 299 children (ages 6-8) living in the Fresno, CA area. At a study center visit, questionnaire and biomarker data were collected. Outcomes included hemoglobin A1c (HbA1c), urinary 8-isoprostane, systolic blood pressure (SBP), and BMI. Individual-level exposure estimates for a set of four pollutants that are constituents of traffic-related air pollution (TRAP) - the sum of 4-, 5-, and 6-ring polycyclic aromatic hydrocarbon compounds (PAH456), NO₂, elemental carbon, and fine particulate matter (PM_2.5) - were modeled at the primary residential location for 1-day lag, and 1-week, 1-month, 3-month, 6-month, and 1-year averages prior to each participant's visit date. Generalized additive models were used to estimate associations between each air pollutant exposure and outcome.

RESULTS

The study population was 53% male, 80% Latinx, 11% Black and largely low-income (6% were White and 3% were Asian/Pacific Islander). HbA1c percentage was associated with longer-term increases in TRAP; for example a 4.42 ng/m³ increase in 6-month average PAH456 was associated with a 0.07% increase (95% CI: 0.01, 0.14) and a 3.62 μg/m³ increase in 6-month average PM_2.5 was associated with a 0.06% increase (95% CI: 0.01, 0.10). The influence of air pollutants on blood pressure was strongest at 3 months; for example, a 6.2 ppb increase in 3-month average NO₂ was associated with a 9.4 mmHg increase in SBP (95% CI: 2.8, 15.9). TRAP concentrations were not significantly associated with anthropometric or adipokine measures. Short-term TRAP exposure averages were significantly associated with creatinine-adjusted urinary 8-isoprostane.

DISCUSSION

Our results suggest that both short- and longer-term estimated individual-level outdoor residential exposures to several traffic-related air pollutants, including ambient PAHs, are associated with biomarkers of risk for metabolic syndrome and oxidative stress in children.

Low emission zones and population health

Air pollution has a detrimental impact on population health, but the effectiveness of policy measures targeting pollution is underexplored. I exploit the natural experiment generated by the staggered implementation of low emission zones in large cities across Germany to assess their impact on health. Using register data on outpatient and inpatient health care, I find that low emission zones reduce the number of patients with cardiovascular disease by 2-3%. This effect is particularly pronounced for those over the age of 65. The findings suggest that low emission zones can be an effective way to reduce air pollution and improve health.

Influencing Indicators and Spatial Variation of Diabetes Mellitus Prevalence in Shandong, China: A Framework for Using Data-Driven and Spatial Methods

To control and prevent the risk of diabetes, diabetes studies have identified the need to better understand and evaluate the associations between influencing indicators and the prevalence of diabetes. One constraint has been that influencing indicators have been selected mainly based on subjective judgment and tested using traditional statistical modeling methods. We proposed a framework new to diabetes studies using data-driven and spatial methods to identify the most significant influential determinants of diabetes automatically and estimated their relationships. We used data from diabetes mellitus patients' health insurance records in Shandong province, China, and collected influencing indicators of diabetes prevalence at the county level in the sociodemographic, economic, education, and geographical environment domains. We specified a framework to identify automatically the most influential determinants of diabetes, and then established the relationship between these selected influencing indicators and diabetes prevalence. Our autocorrelation results showed that the diabetes prevalence in 12 Shandong cities was significantly clustered (Moran's I = 0.328, p < 0.01). In total, 17 significant influencing indicators were selected by executing binary linear regressions and lasso regressions. The spatial error regressions in different subgroups were subject to different diabetes indicators. Some positive indicators existed significantly like per capita fruit production and other indicators correlated with diabetes prevalence negatively like the proportion of green space. Diabetes prevalence was mainly subjected to the joint effects of influencing indicators. This framework can help public health officials to inform the implementation of improved treatment and policies to attenuate diabetes diseases.

Exposure levels to PM2.5 and black carbon for people with disabilities in rural homes of Colombia

Indoor exposure to air pollutants emitted by solid fuels used for cooking or heating homes remains as a problem to solve. The most affected people are newborns, mothers, children, and people with disabilities, due to the time they spend at home. This study is the first in a rural area of South America, which measures indoor air pollutants (PM_2.5 and black carbon) in different environments, inhabited by people with disabilities. The research was supported through a sociodemographic characterization, a methodology useful for future studies, continuous monitoring for 72 h of pollutants, and emission sources, cooking habits, and pre-existing diseases were identified. The primary sources of emissions are improved wood-burning stoves and their chimney. In households where firewood is used, the average concentrations of PM_2.5 were the highest (between 10.9 and 3302.5 μg/m³), as were the average concentrations of BC (average 72 h between 2.6 and 51.2 μg/m³) compared with the houses that use gas (average 72 h between 2.6 and 6 μg/m³). In 57% of the households visited, the World Health Organization (WHO) guidelines for PM_2.5 (25 μg/m³ for 24 h) were exceeded. The results reveal that rural concentrations of BC can be up to 2.5 times higher than those of an urban area with high vehicular traffic and high population density and could be used to establish a baseline that allows the implementation of control mechanisms to reduce pollution of indoor air.

The Prospect for Type 2 Diabetes Mellitus Combined with Exercise and Synbiotics: A Perspective

Change in gut microbiome diversity (the so-called dysbiosis) is correlated with insulin resistance conditions. Exercise is typically the first management for people with type 2 diabetes mellitus (T2DM), which is generally well-known for improving glucose regulation. The new prebiotics and probiotics, like synbiotics, designed to target specific diseases, require additional studies. While the effectiveness of exercise combined with synbiotics seems promising, this review discusses these agents' possibility of increasing the gut microbiota's diversity. Therefore, they could enhance short-chain fatty acids (SCFA). In particular, the synbiotic interaction on gut microbiota, the exercise mechanism in improving gut microbiota, and the prospect of the synergistic effect of the combination of synbiotic and exercise to improve insulin sensitivity are addressed.

Administration of Lactobacillus paracasei HB89 mitigates PM2.5-induced enhancement of inflammation and allergic airway response in murine asthma model

PM2.5 causes abnormal immune response and asthma in animals. In this study, a Balb/c mouse animal model was exposed to PM2.5 to induce asthma. Lactobacillus paracasei HB89 was fed at the same time, in order to observe whether L. paracasei HB89 mitigates respiratory tract allergies stimulated by PM2.5. The results showed that PM2.5 stimulated a significant increase in white blood cells and immunoglobulin (IgE) in OVA-induced allergic Balb/c mice, and IgE in the blood further triggered the release of histamine in the lung immune cells. This not only increased overall immune cell counts, but the lymphocyte counts also increased significantly, resulting in significant inhibitions of cytokines INF-r and TGF-β, and induction of IL-4, IL-5, IL-13 and IL-17a. After feeding with HB89, apart from the absence of observable changes in body weight, the total white blood cell count in the animal blood and IgE response were also be reduced; the proliferation of immune cells in the lungs caused by PM2.5 was slowed down; and histamine and cytokines INF-r and TGF-β were secreted in large quantities, but IL- 4, IL-5, IL-13, IL-17a were inhibited, which effectively reduced the possibility of asthma induction.

Association of combined effects of physical activity and air pollution with diabetes in older adults

BACKGROUND

Physical activity (PA), especially outdoor PA, may have twofold effects on diabetes risk: the health benefits of PA and the potential detrimental effects caused by augmented exposure to air pollution. We examined the association of combined effects of PA and air pollution with diabetes in older adults.

METHODS

The study participants consisted of 1,259,871 older adults aged 58 years or more from the Korean National Health Insurance Service database. The exposure to air pollution was estimated by the average ambient levels of particulate matter (PM) of the participants' residence area. Cox proportional hazards models were used to evaluate the adjusted hazard ratios and 95% confidence intervals of developing diabetes according to the combined effect of moderate to vigorous physical activity (MVPA) and air pollution exposure.

RESULTS

Engaging in 5 or more times of MVPA/week was associated with decreased risk of diabetes within groups with both high and low/moderate levels of exposure to PM10 (low/moderate PM10 aHR 0.91, 95% CI 0.89-0.93; high PM10 aHR 0.97, 95% CI 0.94-0.99) or PM2.5 (low/moderate PM2.5 aHR 0.88, 95% CI 0.85-0.90; high PM10 aHR 0.95, 95% CI 0.91-0.99) exposure. The risk-reducing effects upon MVPA tended to be slightly attenuated, which showed the reverse J-shaped association, but still significant, among those who were exposed to a high level of air pollution. The association was consistent among stratified analyses according to the possible confounders.

CONCLUSION

MVPA may be inversely associated with the risk of diabetes development within groups with both high and low/moderate levels of exposure to PM10 or PM2.5 in older adults. Future studies are necessary to validate whether the positive health effects of MVPA outweigh the potential detrimental effects due to augmented exposure to air pollution during MVPA.

Epidemics and electricity CO2 emissions: a feedback investigation

We examine the short-term and long-term causal effects between epidemics and electricity CO₂ emissions by using panel data from 30 countries over the period of 1990 to 2017. The results show that there is bidirectional relationship between epidemics and electricity CO₂ emissions, especially in OECD and Asian countries.

The Impact of Air Pollution on Healthcare Expenditure for Respiratory Diseases: Evidence from the People's Republic of China

Background

Air pollution is an important factor in health outcomes and health-care expenditure. It has become an important issue of global concern. The objective of this study was to explore the influence of air pollution on the economic burden of respiratory diseases using different levels of PM_2.5.

Methods

Starting from the demand side, we took the 3,546 patients in the Respiratory and Critical Care Department of a tertiary hospital in Beijing between 2013 and 2015 as examples, combining daily air-quality data using a generalized linear regression–analysis model to explore the impact of air pollution on health-care expenditure on a microindividual level.

Results

We found that PM_2.5 had a significant impact on health-care expenditure on respiratory diseases. It had a positive impact on total health-care expenditure, drug expenditure, and antibiotic expenditure. The impact of different levels of air pollution on the health care–expenditure burden of disease was heterogeneous. As the air-pollution index increased, health care–expenditure burden of respiratory diseases also gradually raised. The impact of PM₁₀ and air-quality index had a positive impact on health-care expenditure for respiratory diseases. Air pollution had a significant impact on health care–expenditure burden of respiratory diseases. The effect of length of stay on various health-care expenditure was significantly positive.

Conclusion

The impact of mortality-risk classification on various health-care expenditure is significant. Therefore, policy-making must take into account both the supply side and the demand side of health-care services. Furthermore, the government should strengthen environmental governance, pay attention to the heterogeneity of the health care–expenditure burden affected by environmental pollution, improve the medical insurance system, and improve the health of residents to reduce the health care–expenditure burden.

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.

Association between exposure to ambient fine particulate matter and prevalence of type 2 diabetes in Iran: an ecological study

Epidemiological evidence for the link between long-term exposure to air particulate matter (PM_2.5) and occurrence of type 2 diabetes (T2D) is limited such that little is known about the effect of PM_2.5 exposure and adult T2D prevalence. Thus, the aim of this ecological study is to evaluate the contribution of ambient PM_2.5 exposure to the adult T2D prevalence in the large population of Iran. The study was conducted based on Iran's large-scale cross-sectional surveilling non-communicable diseases (NCDs) risk factors (Timpka et al. 2015b). A total of 31,050 participants were enrolled in three sequential processes of study using cluster random sampling. PM_2.5 data in the urban area of 31 provinces of Iran were acquired from Tehran Air Quality Control Company (AQCC) and the Department of Environment (DoE) of Iran during 2012-2016. Moreover, major and minor diabetes risk factors were considered; the Pearson correlation and a stepwise regression model were performed to estimate associations between risk factors and diabetes and prediabetes prevalence. The results showed T2D prevalence was more frequent among women (10.61%) than men (9.35%). A weak positive correlation was observed between PM_2.5 level and diabetes prevalence with a correlation coefficient of 0.275, although there was no significant association between PM_2.5 value and prediabetes prevalence. Moreover, none of the variables included in the regression model could predict the prevalence of diabetes and prediabetes. According to our study results, it can be suggested that investigating the association between PM_2.5 exposure and T2D prevalence at individual level may provide a better understanding of PM_2.5 exposure and the risk of T2D prevalence.

Association between fine particle exposure and common test items in clinical laboratory: A time-series analysis in Changsha, China

Most studies on the health effects of PM_2.5 (fine particulate matter with diameter smaller than 2.5 μm) use indirect indicators, such as mortality and number of hospital visits. Recent research shows that biomarkers can also be used to evaluate the health effects of PM_2.5; however, these biomarkers are not very common. Clinical laboratories can provide a significant amount of test data that have been proven to have important diagnostic value. Therefore, we use big data analysis methods to find the associations between clinical laboratory common test items and PM_2.5 exposure. Data related to air pollution and meteorological information between 2014 and 2016 were obtained from the China National Environmental Monitoring Centre and the China National Meteorological Information Center. Additionally, data of 27 common test items from the same period were collected from Changsha Central Hospital. Primary analyses included a generalized additive model to analyze the associations between PM_2.5 concentration and common test items; the model was adjusted for time trends, weather conditions (temperature and humidity), and days of the week. Furthermore, we adjusted the effects of other air pollutants, such as PM₁₀, SO₂, NO₂, CO, and O₃. 17 items such as TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, LDL, WBC, K, Cl, Ca, TT, and FIB were significantly positively associated with PM_2.5 concentration (P< 0.05) and have concentration-response relationship. After adjusting the effect of PM₁₀+SO₂+NO₂+CO+O₃, TP, ALB, ALT, AST, TBIL, DBIL, UREA, CREA, UA, GLU, WBC, Cl, and Ca were still significantly associated with PM_2.5 concentration (P< 0.05). This current study suggested that clinical laboratory common test items may be used to assess and predict the health effects of PM_2.5 on the population.

Sub-Daily Exposure to Fine Particulate Matter and Ambulance Dispatches during Wildfire Seasons: A Case-Crossover Study in British Columbia, Canada

BACKGROUND

Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d.

OBJECTIVES

We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia.

METHODS

We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD).

RESULTS

Increased respiratory health outcomes were observed within 1 h of exposure to a 10-μg/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively.

CONCLUSIONS

We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792.

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

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

Novel biomarkers for the evaluation of aging-induced proteinopathies

Proteinopathies are characterized by aging related accumulation of misfolded protein aggregates. Irreversible covalent modifications of aging proteins may significantly affect the native three dimentional conformation of proteins, alter their function and lead to accumulation of misfolded protein as dysfunctional aggregates. Protein misfolding and accumulation of aberrant proteins are known to be associated with aging-induced proteinopathies such as amyloid ß and tau proteins in Alzheimer's disease, α-synuclein in Parkinson's disease and islet amyloid polypeptides in Type 2 diabetes mellitus. Protein oxidation processes such as S-nitrosylation, dityrosine formation and some of the newly elucidated processes such as carbamylation and citrullination recently drew the attention of researchers in the field of Gerontology. Studying over these processes and illuminating their relations between proteinopathies may help to diagnose early and even to treat age related disorders. Therefore, we have chosen to concentrate on aging-induced proteinopathic nature of these novel protein modifications in this review.

Traffic-Related Air Pollution and Carotid Plaque Burden in a Canadian City With Low-Level Ambient Pollution

Background

The association between fine particulate matter and cardiovascular disease has been convincingly demonstrated. The role of traffic‐related air pollutants is less clear. To better understand the role of traffic‐related air pollutants in cardiovascular disease development, we examined associations between NO₂, carotid atherosclerotic plaque, and cardiometabolic disorders associated with cardiovascular disease.

Methods and Results

Cross‐sectional analyses were conducted among 2227 patients (62.9±13.8 years; 49.5% women) from the Stroke Prevention and Atherosclerosis Research Centre (SPARC) in London, Ontario, Canada. Total carotid plaque area measured by ultrasound, cardiometabolic disorders, and residential locations were provided by SPARC medical records. Long‐term outdoor residential NO₂ concentrations were generated by a land use regression model. Associations between NO₂, total carotid plaque area, and cardiometabolic disorders were examined using multiple regression models adjusted for age, sex, smoking, and socioeconomic status. Mean NO₂ was 5.4±1.6 ppb in London, Ontario. NO₂ was associated with a significant increase in plaque (3.4 mm² total carotid plaque area per 1 ppb NO₂), exhibiting a linear dose‐response. NO₂ was also positively associated with triglycerides, total cholesterol, and the ratio of low‐ to high‐density lipoprotein cholesterol (P<0.05). Diabetes mellitus mediated the relationship between NO₂ and total carotid plaque area (P<0.05).

Conclusions

Our results demonstrate that even low levels of traffic‐related air pollutants are linked to atherosclerotic plaque burden, an association that may be partially attributable to pollution‐induced diabetes mellitus. Our findings suggest that reducing ambient concentrations in cities with NO₂ below current standards would result in additional health benefits. Given the billions of people exposed to traffic emissions, our study supports the global public health significance of reducing air pollution.

Ambient air pollution is associated with airway inflammation in older women: a nested cross-sectional analysis

BACKGROUND

Air pollution is a risk factor for chronic obstructive pulmonary disease (COPD). Fraction of exhaled nitric oxide (FeNO) could be a useful biomarker for health effects of air pollutants. However, there were limited data from older populations with higher prevalence of COPD and other inflammatory conditions.

METHODS

We obtained data from the German Study on the influence of Air pollution on Lung function, Inflammation and Ageing. Spirometry and FeNO were measured by standard techniques. Air pollutant exposures were estimated following the European Study of Cohorts for Air Pollution Effects protocols, and ozone (O3) measured at the closest ground level monitoring station. Multiple linear regression models were fitted to FeNO with each pollutant separately and adjusted for potential confounders.

RESULTS

In 236 women (mean age 74.6 years), geometric mean FeNO was 15.2ppb. Almost a third (n=71, 30.1%) of the women had some chronic inflammatory respiratory condition. A higher FeNO concentration was associated with exposures to fine particles (PM2.5), PM2.5absorbance and respirable particles (PM10). There were no significant associations with PMcoarse, NO2, NOx, O3 or length of major roads within a 1 km buffer. Restricting the analysis to participants with a chronic inflammatory respiratory condition, with or without impaired lung function produced similar findings. Adjusting for diabetes did not materially alter the findings. There were no significant interactions between individual pollutants and asthma or current smoking.

CONCLUSIONS

This study adds to the evidence to reduce ambient PM2.5 concentrations as low as possible to protect the health of the general population.