Effect of long-term exposure to air pollution on type 2 diabetes mellitus risk: a systemic review and meta-analysis of cohort studies

Inhalation exposure to chemicals, microbiota dysbiosis and adverse effects on humans

As revealed by culture-independent methodologies, disruption of the normal lung microbiota (LM) configuration (LM dysbiosis) is a potential mediator of adverse effects from inhaled chemicals. LM, which consists of microbiota in the upper and lower respiratory tract, is influenced by various factors, including inter alia environmental exposures. LM dysbiosis has been associated with multiple respiratory pathologies such as asthma, lung cancer, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF). Chemically-induced LM dysbiosis appears to play significant roles in human respiratory diseases, as has been shown for some air pollutants, cigarette smoke and some inhalable chemical antibiotics. Lung microbiota are also linked with the central nervous system (CNS) in the so-called lung-brain axis. Inhaled chemicals that undergo mucociliary clearance may be linked to respiratory conditions through gut microbiota (GM) dysbiosis in the so-called Gut-Lung axis. However, current linkages of various disease states to LM appears to be associative, with causal linkages requiring further studies using more robust approaches, methods and techniques that are different from those applied in studies involving (GM). Most importantly, the sampling techniques determine the level of risk of cross contamination. Furthermore, the development of continuous or semi-continuous systems designed to replicate the lung microbiome will go a long way to further LM dysbiosis studies. These challenges notwithstanding, the preponderance of evidence points to the significant role of LM-mediated chemical toxicity in human disease and conditions.

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.

e-Health and environmental sustainability in vascular surgery

e-Health technology holds great promise for improving the management of patients with vascular diseases and offers a unique opportunity to mitigate the environmental impact of vascular care, which remains an under-investigated field. The innovative potential of e-Health operates in a complex environment with finite resources. As the expansion of digital health will increase demand for devices, contributing to the environmental burden of electronics and energy use, the sustainability of e-Health technology is of crucial importance, especially in the context of increasing prevalence of cardiovascular diseases. This review discusses the environmental impact of care related to vascular surgery and e-Health innovation, the potential of e-Health technology to mitigate greenhouse gas emissions generated by the health care sector, and to provide leads to research promoting e-Heath technology sustainability. A multifaceted approach, including ethical design, validated eco-audits methodology and reporting standards, technological refinement, electronic and medical devices reuse and recycling, and effective policies is required to provide a sustainable and optimal level of care to vascular patients.

Combined impact of heat and dust on diabetes hospitalization in Kuwait

INTRODUCTION

In Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health problem, the empirical understanding of the actual risks remains limited. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.

RESEARCH DESIGN AND METHODS

We placed custom-designed particle samplers in Kuwait to collect daily dust samples for 2 years from 2017 to 2019. Samples were analyzed for elemental concentrations to identify and quantify dust pollution days. Temperature data were collected from meteorological stations. We then collected hospitalization data for unplanned diabetic admissions in all public hospitals in Kuwait. We used a case-crossover study design and conditional quasi-Poisson models to compare hospitalization days to control days within the same subject. Finally, we fitted generalized additive models to explore the smoothed interaction between temperature and dust days on diabetes hospitalization.

RESULTS

There were 11 155 unplanned diabetes hospitalizations over the study period. We found that each year, there was an excess of 282 diabetic admissions attributed to hot days (95% CI: -14 to 473). Additionally, for every 10 µg/m3 increase in dust levels, there were about 114 excess diabetic admissions annually (95% CI: 11 to 219). Compared with mild non-dusty days (33°C (0 µg/m3)), hot-dusty days jointly increased the relative risk of diabetic admissions from 1.11 at 42°C (85 µg/m3) to 1.36 at 42°C (150 µg/m3).

CONCLUSIONS

Both heat and dust seem to contribute to the increased diabetes morbidity, with combined hot-dusty conditions exacerbating these risks even further.

Is it time to revise the fighting strategy toward type 2 diabetes? Sex and pollution as new risk factors

Diabetes mellitus, a metabolic condition affecting around 537 million individuals worldwide, poses significant challenges, particularly among the elderly population. The etiopathogenesis of type 2 diabetes (T2D) depends on a combination of the effects driven by advancing age, genetic background, and lifestyle habits, e.g. overnutrition. These factors influence the development of T2D differently in men and women, with an obvious sexual dimorphism possibly underlying the diverse clinical features of the disease in different sexes. More recently, environmental pollution, estimated to cause 9 million deaths every year, is emerging as a novel risk factor for the development of T2D. Indeed, exposure to atmospheric pollutants such as PM2.5, O3, NO2, and Persistent Organic Pollutants (POP)s, along with their combination and bioaccumulation, is associated with the development of T2D and obesity, with a 15 % excess risk in case of exposure to very high levels of PM2.5. Similar data are available for plasticizer molecules, e.g. bisphenol A and phthalates, emerging endocrine-disrupting chemicals. Even though causality is still debated at this stage, preclinical evidence sustains the ability of multiple pollutants to affect pancreatic function, promote insulin resistance, and alter lipid metabolism, possibly contributing to T2D onset and progression. In addition, preclinical findings suggest a possible role also for plastic itself in the development of T2D. Indeed, pioneeristic studies evidenced that micro- or nanoplastics (MNP)s, particles in the micro- or nano- range, promote cellular damage, senescence, inflammation, and metabolic disturbances, leading to insulin resistance and impaired glucose metabolism in animal and/or in vitro models. Here we synthesize recent knowledge relative to the association between air-related or plastic-derived pollutants and the incidence of T2D, discussing also the possible mechanistic links suggested by the available literature. We then anticipate the need for future studies in the field of candidate therapeutic strategies limiting pollution-induced damage in preclinical models, such as SGLT-2 inhibitors. We finally postulate that future guidelines for T2D prevention should consider pollution and sex an additional risk factors to limit the diabetes pandemic.

Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study

Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

Source-Specific Air Pollution and Loss of Independence in Older Adults Across the US

Importance

Air pollution is a recognized risk factor associated with chronic diseases, including respiratory and cardiovascular conditions, which can lead to physical and cognitive impairments in later life. Although these losses of function, individually or in combination, reduce individuals' likelihood of living independently, little is known about the association of air pollution with this critical outcome.

Objective

To investigate associations between air pollution and loss of independence in later life.

Design, Setting, and Participants

This cohort study was conducted as part of the Environmental Predictors Of Cognitive Health and Aging study and used 1998 to 2016 data from the Health and Retirement Study. Participants included respondents from this nationally representative, population-based cohort who were older than 50 years and had not previously reported a loss of independence. Analyses were performed from August 31 to October 15, 2023.

Exposures

Mean 10-year pollutant concentrations (particulate matter less than 2.5 μm in diameter [PM2.5] or ranging from 2.5 μm to 10 μm in diameter [PM10-2.5], nitrogen dioxide [NO2], and ozone [O3]) were estimated at respondent addresses using spatiotemporal models along with PM2.5 levels from 9 emission sources.

Main Outcomes and Measures

Loss of independence was defined as newly receiving care for at least 1 activity of daily living or instrumental activity of daily living due to health and memory problems or moving to a nursing home. Associations were estimated with generalized estimating equation regression adjusting for potential confounders.

Results

Among 25 314 respondents older than 50 years (mean [SD] baseline age, 61.1 [9.4] years; 11 208 male [44.3%]), 9985 individuals (39.4%) experienced lost independence during a mean (SD) follow-up of 10.2 (5.5) years. Higher exposure levels of mean concentration were associated with increased risks of lost independence for total PM2.5 levels (risk ratio [RR] per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.10), PM2.5 levels from road traffic (RR per 1-IQR of 10-year mean, 1.09; 95% CI, 1.03-1.16) and nonroad traffic (RR per 1-IQR of 10-year mean, 1.13; 95% CI, 1.03-1.24), and NO2 levels (RR per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.08). Compared with other sources, traffic-generated pollutants were most consistently and robustly associated with loss of independence; only road traffic-related PM2.5 levels remained associated with increased risk after adjustment for PM2.5 from other sources (RR per 1-IQR increase in 10-year mean concentration, 1.10; 95% CI, 1.00-1.21). Other pollutant-outcome associations were null, except for O3 levels, which were associated with lower risks of lost independence (RR per 1-IQR increase in 10-year mean concentration, 0.94; 95% CI, 0.92-0.97).

Conclusions and Relevance

This study found that long-term exposure to air pollution was associated with the need for help for lost independence in later life, with especially large and consistent increases in risk for pollution generated by traffic-related sources. These findings suggest that controlling air pollution could be associated with diversion or delay of the need for care and prolonged ability to live independently.

Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study

Introduction

Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort.

Methods

We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders.

Results

Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants.

Conclusion

Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.

Effects of inhaled fine particulate matter on the lung injury as well as gut microbiota in broilers

Fine particulate matter (PM2.5) has been widely regarded as an important environmental risk factor that has widely influenced health of both animals and humans. Lung injury is the main cause of PM2.5 affecting respiratory tract health. Gut microbiota participates in the development of lung injury in many pathological processes. However, there is still unknown the specific effects of PM2.5 on the gut-lung axis in broilers. Thus, we conducted a broiler model based on 3-wk-old male Arbor Acres broiler to explore the underlying mechanism. Our results showed that PM2.5 exposure triggered TLR4 signaling pathway and induced the increase of IL-6, IFN-γ, TNF-α expression as well as the decrease of IL-10 expression in the lung. Inhaled PM2.5 exposure significantly altered the gut microbiota diversity and community. Specifically, PM2.5 exposure decreased α diversity and altered β diversity of gut microbiota, and reduced the abundance of DTU089, Oscillospirales, Staphylococcus, and increased the Escherichia-Shigella abundance, leading to the increase of gut-derived lipopolysaccharides (LPS). Moreover, PM2.5 significantly disrupted the intestinal epithelial barrier by reducing the expression of muc2 and claudin-1 to increase intestinal permeability, which possibly facilitated the LPS translocation into the blood. Spearman analysis revealed that gut microbiota dysbiosis was positively related to TLR4, TNF-α, and IFN-γ expression in the lung. In summary, our results showed that PM2.5 exposure induced lung injury by causing inflammation and triggering TLR4 signaling pathway, and also induced gut microbiota dysbiosis resulting in the overproduction of gut-derived LPS. And gut microbiota dysbiosis may be associated with lung injury. The above results provide basis data to comprehend the potential role of gut microbiota dysbiosis in the lung injury as well as providing a new regulatory target for alleviating lung injury associated with environmental pollutants.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

Long-term ambient air pollution exposure and prospective change in sedentary behaviour and physical activity in individuals at risk of type 2 diabetes in the UK

BACKGROUND

Air pollution may be a risk factor for physical inactivity and sedentary behaviour (SED) through discouraging active lifestyles, impairing fitness and contributing to chronic diseases with potentially important consequences for population health.

METHODS

Using generalized estimating equations, we examined the associations between long-term particulate matter with diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2) and annual change in accelerometer-measured SED, moderate-to-vigorous physical activity (MVPA) and steps in adults at risk of type 2 diabetes within the Walking Away from Type 2 Diabetes trial. We adjusted for important confounders including social deprivation and measures of the built environment.

RESULTS

From 808 participants, 644 had complete data (1605 observations; 64.7% men; mean age 63.86 years). PM2.5, NO2 and PM10 were not associated with change in MVPA/steps but were associated with change in SED, with a 1 ugm-3 increase associated with 6.38 (95% confidence interval: 0.77, 12.00), 1.52 (0.49, 2.54) and 4.48 (0.63, 8.34) adjusted annual change in daily minutes, respectively.

CONCLUSIONS

Long-term PM2.5, NO2 and PM10 exposures were associated with an annual increase in SED: ~11-22 min/day per year across the sample range of exposure (three standard deviations). Future research should investigate whether interventions to reduce pollution may influence SED.

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.

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.

Cigarette smoking and air pollution exposure and their effects on cardiovascular diseases

Cardiovascular disease (CVD) has no socioeconomic, topographical, or sex limitations as reported by the World Health Organization (WHO). The significant drivers of CVD are cardio-metabolic, behavioral, environmental, and social risk factors. However, some significant risk factors for CVD (e.g., a pitiable diet, tobacco smoking, and a lack of physical activities), have also been linked to an elevated risk of cardiovascular disease. Lifestyles and environmental factors are known key variables in cardiovascular disease. The familiarity with smoke goes along with the contact with the environment: air pollution is considered a source of toxins that contribute to the CVD burden. The incidence of myocardial infarction increases in males and females and may lead to fatal coronary artery disease, as confirmed by epidemiological studies. Lipid modification, inflammation, and vasomotor dysfunction are integral components of atherosclerosis development and advancement. These aspects are essential for the identification of atherosclerosis in clinical investigations. This article aims to show the findings on the influence of CVD on the health of individuals and human populations, as well as possible pathology and their involvement in smoking-related cardiovascular diseases. This review also explains lifestyle and environmental factors that are known to contribute to CVD, with indications suggesting an affiliation between cigarette smoking, air pollution, and CVD.

Ambient air pollution exposure, plasma metabolomic markers, and risk of type 2 diabetes: A prospective cohort study

BACKGROUND

Both air pollution (AP) and impaired lipid metabolism contribute to type 2 diabetes (T2D). However, little is known about the detailed associations of AP to lipidomic markers and the specific lipid metabolomic profile that mediates the impact of AP on incident T2D. We aimed to examine the associations between long-term AP exposure, plasma metabolomic markers, and incident T2D, and subsequently determine the lipid metabolomic profile that mediates the relationship between AP and T2D.

METHODS

This prospective study included 82,548 participants from the UK Biobank without a history of T2D at baseline. Baseline plasma samples were analyzed using the nuclear magnetic resonance (NMR) metabolomic platform, which measured 168 metabolomic markers, including lipids, lipoprotein subclasses, and other circulating metabolites. Land Use Regression models were utilized to estimate annual average concentrations of PM2.5 and NO2. The associations among AP, metabolomic markers, and T2D were investigated using multivariable linear regressions and Cox proportional hazards models. Mediation analyses were performed to assess the role of each metabolomic marker in the AP-T2D relationship. Furthermore, principal component (PC) analysis was conducted on 168 metabolomic markers to extract metabolic patterns. These patterns were utilized to determine their associations with AP and T2D, as well as their mediating role in the AP-T2D relationship.

RESULTS

We found that long-term AP exposure was associated with some lipid metabolites, including ApoA1, HDL concentration, HDL size, and lipid components within HDL, especially in very large, large, and medium HDL, as well as some other lipids, fatty acids, amino acids, glucose, and glycoprotein acetyls. In pairwise mediation analysis, these metabolites exhibited significant mediation effects in the AP-T2D relationship. We identified six PCS representing distinct metabolic patterns. Long-term exposure to PM2.5 and NO2 showed significantly negative associations with PC2 (characterized by high levels of ApoA1, larger HDL, other lipids, and low levels of larger VLDL). PC2 mediated 12.3% and 10.3% of the associations of PM2.5 and NO2 with incident T2D, respectively.

CONCLUSIONS

This study revealed the associations of AP with various lipid metabolites. A lipid metabolomic profile characterized by ApoA1 and larger HDL may mediate the association between AP and incident T2D.

PM10 and Pseudomonas aeruginosa: effects on corneal epithelium

Purpose

In vivo data indicate that mouse corneas exposed to PM10 showed early perforation and thinning after infection with Pseudomonas aeruginosa. To understand the mechanisms underlying this finding, we tested the effects of PM10 and the mitochondria targeted anti-oxidant SKQ1 in immortalized human corneal epithelial cells (HCET) that were challenged with Pseudomonas aeruginosa strain 19660.

Methods

Mouse corneas were infected with strain 19660 after a 2 week whole-body exposure to PM10 or control air and assessed by clinical scores, slit lamp photography and western blot. HCET were exposed to 100μg/ml PM10 for 24h before challenge with strain 19660 (MOI 20). A subset of cells were pre-treated with 50nM SKQ1 for 1h before PM10 exposure. Phase contrast microscopy was used to study cell morphology, cell viability was measured by an MTT assay, and ROS by DCFH-DA. Levels of pro-inflammatory markers and anti-oxidant enzymes were evaluated by RT-PCR, western blot and ELISA. Reduced glutathione (GSH) and malondialdehyde (MDA) levels were evaluated by assay kits.

Results

In vivo, whole body exposure to PM10 vs. control air exposed mouse corneas showed early perforation and/or corneal thinning at 3 days post infection, accompanied by increased TNF-α and decreased SOD2 protein levels. In vitro, PM10 induced a dose dependent reduction in cell viability of HCET and significantly increased mRNA levels of pro-inflammatory molecules compared to control. Exposure to PM10 before bacterial challenge further amplified the reduction in cell viability and GSH levels. Furthermore, PM10 exposure also exacerbated the increase in MDA and ROS levels and phase contrast microscopy revealed more rounded cells after strain 19660 challenge. PM10 exposure also further increased the mRNA and protein levels of pro-inflammatory molecules, while anti-inflammatory IL-10 was decreased. SKQ1 reversed the rounded cell morphology observed by phase contrast microscopy, increased levels of MDA, ROS and pro-inflammatory molecules, and restored IL-10.

Conclusions

PM10 induces decreased cell viability, oxidative stress and inflammation in HCET and has an additive effect upon bacterial challenge. SKQ1 protects against oxidative stress and inflammation induced by PM10 after bacterial challenge by reversing these effects. The findings provide insight into mechanisms underlying early perforation and thinning observed in infected corneas of PM10 exposed mice.

Ambient Air Pollution Exposure and Cerebral White Matter Hyperintensities in Older Adults: A Cross-Sectional Analysis in the Three-City Montpellier Study

BACKGROUND

Growing epidemiological evidence suggests an adverse relationship between exposure to air pollutants and cognitive health, and this could be related to the effect of air pollution on vascular health.

OBJECTIVE

We aim to evaluate the association between air pollution exposure and a magnetic resonance imaging (MRI) marker of cerebral vascular burden, white matter hyperintensities (WMH).

METHODS

This cross-sectional analysis used data from the French Three-City Montpellier study. Randomly selected participants 65-80 years of age underwent an MRI examination to estimate their total and regional cerebral WMH volumes. Exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and black carbon (BC) at the participants' residential address during the 5 years before the MRI examination was estimated with land use regression models. Multinomial and binomial logistic regression assessed the associations between exposure to each of the three pollutants and categories of total and lobar WMH volumes.

RESULTS

Participants' (n = 582 ) median age at MRI was 70.7 years [interquartile range (IQR): 6.1], and 52% (n = 300 ) were women. Median exposure to air pollution over the 5 years before MRI acquisition was 24.3 (IQR: 1.7) μ g / m 3 for PM 2.5 , 48.9 (14.6) μ g / m 3 for NO 2 , and 2.66 (0.60) 10 - 5 / m for BC. We found no significant association between exposure to the three air pollutants and total WMH volume. We found that PM 2.5 exposure was significantly associated with higher risk of temporal lobe WMH burden [odds ratio (OR) for an IQR increase = 1.82 (95% confidence interval: 1.41, 2.36) for the second volume tercile, 2.04 (1.59, 2.61) for the third volume tercile, reference: first volume tercile]. Associations for other regional WMH volumes were inconsistent.

CONCLUSION

In this population-based study in older adults, PM 2.5 exposure was associated with increased risk of high WMH volume in the temporal lobe, strengthening the evidence on PM 2.5 adverse effect on the brain. Further studies looking at different markers of cerebrovascular damage are still needed to document the potential vascular effects of air pollution. https://doi.org/10.1289/EHP12231.

Ecological study on household air pollution exposure and prevalent chronic disease in the elderly

Older people spend most of their time indoors. Limited evidence demonstrates that exposure to indoor air pollutants might be related to chronic complications. This study aimed to estimate the correlation between household air pollution (HAP)'s long-term exposure and the prevalence of elevated hypertension, diabetes mellitus (DM), obesity, and low-density lipoprotein (LDL) cholesterol. From the Global Burden disease dataset, we extracted HAP, hypertension, DM, body mass index, and LDL cholesterol data from Iran from 1990 to 2019 to males and females in people over 50 years. We present APC and AAPC and their confidence intervals using Joinpoint Software statistical software. R software examined the correlation between HAP and hypertension, DM2, Obesity, and high LDL cholesterol. Our finding showed a significant and positive correlation between HAP exposure and prevalence of high low-density lipoprotein cholesterol (p ≤ 0.001, r = 0.70), high systolic blood pressure (p ≤ 0.001, r = 0.63), and high body mass index (p ≤ 0.001, r = 0.57), and DM2 (p ≤ 0.001, r = 0.38). The analysis results also illustrated a positive correlation between indoor air pollution and smoking (p ≤ 0.001, r = 0.92). HAP exposure might be a risk factor for elevated blood pressure, DM, obesity, and LDL cholesterol and, consequently, more serious health problems. According to our results, smoking is one of the sources of HAP. However, ecological studies cannot fully support causal relationships, and this article deals only with Iran. Our findings should be corroborated in personal exposure and biomonitoring approach studies.

Association between long-term air pollution exposure and development of diabetes among community-dwelling adults: Modification of the associations by dietary nutrients

BACKGROUND

Studies on the modifying effects of dietary factors on the association between air pollution and diabetes-related outcomes are limited. We examined whether dietary nutrients could modify the association between long-term air pollution exposure and the development of diabetes.

METHODS

We used data from the Cardiovascular Disease Association Study, which enrolled adults aged 40-69 years in Korea between 2005 and 2011 and followed them up until 2016 (n = 14,667). Annual concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) at each participant's residence(s) were estimated using community multiscale air quality models. Intake of 22 dietary nutrients was assessed using a validated food frequency questionnaire during the baseline survey. We examined the product terms between air pollution levels (continuous) and each dietary nutrient (quartile) using Cox regression models, adjusted for potential confounders.

RESULTS

PM_2.5 [hazard ratio (HR) = 1.49, 95 % confidence interval (CI): 1.11, 2.00] and NO₂ (HR = 1.29, 95 % CI: 1.12, 1.49) concentrations were found to be associated with incident diabetes. NO₂ levels interacted with dietary intake of retinol, vitamin A, and cholesterol (p-values for interaction < 0.05). Stronger associations were observed between NO₂ levels and the occurrence of diabetes among individuals with a lower intake of these nutrients compared to those with a higher intake. No interaction was found between PM_2.5 and the 22 investigated dietary nutrients.

CONCLUSIONS

Adequate intake of dietary nutrients, such as retinol, vitamin A, and cholesterol, from various food items in a balanced diet may prevent the occurrence of diabetes in a setting wherein reduction of air pollution levels cannot be achieved in a short time frame.

Diabetes and climate change

It is widely accepted that climate change is the biggest threat to human health. The pandemic of diabetes is also a major threat to human health, especially in rapidly developing nations. Climate change and diabetes appear to have common global vectors, including increased urbanisation, increased use of transportation, and production and ingestion of ultra-processed foods. People with diabetes appear to be at higher risk of threats to health from climate change, including effects from extreme heat or extreme cold, and natural disasters. Solutions to climate change offer some benefits for the prevention of diabetes and diabetes-related complications. Moving towards lower carbon economies is likely to help reduce reliance on intensive agriculture, reduce physical inactivity, reduce air pollution and enhance quality of life. It may enable a reduction in the prevalence of diabetes and reduced morbidity from the condition.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The changing food environment and neighborhood prevalence of type 2 diabetes

In this ecological study, we used longitudinal data to assess if changes in neighborhood food environments were associated with type 2 diabetes mellitus (T2DM) prevalence, controlling for a host of neighborhood characteristics and spatial error correlation. We found that the population-adjusted prevalence of fast-food and pizza restaurants, grocery stores, and full-service restaurants along with changes in their numbers from 1990 to 2010 were associated with 2015 T2DM prevalence. The results suggested that neighborhoods where fast-food restaurants have increased and neighborhoods where full-service restaurants have decreased over time may be especially important targets for educational campaigns or other public health-related T2DM interventions.

Ambient air pollution, lifestyle, and genetic predisposition associated with type 2 diabetes: findings from a national prospective cohort study

BACKGROUND

The combined effects of ambient air pollution, lifestyle, and genetic predisposition on incident Type 2 Diabetes (T2D) have not been well documented.

METHODS

A total of 263,733 participants without T2D at baseline were identified from the UK Biobank. Annual concentrations of five air pollutants were estimated using Land Use Regression, while a healthy lifestyle score (HLS) was constructed using 7 major lifestyle factors, and polygenic risk score (PRS) was generated using 73 genetic variants. Cox regression was used to determine the association between air pollution and incident T2D for different HLS/PRS categories. Potential HLS/PRS interactions and population attributable fraction (PAF) were also examined.

RESULTS

During a median follow-up of 11.94 years, 7827 (2.97 %) incident T2D cases were identified. Association between air pollution and incident T2D was stronger among those with higher HLS/PRS in a dose-response fashion. In addition, synergistic interactions between lifestyles and air pollution were observed. Lifestyle was the leading risk factor of T2D with a weighted PAF of 25.54 % (95 % CI: 19.22 %, 27.77 %) for intermediate HLS and 24.24 % (18.24 %, 26.36 %) due to unhealthy HLS. Overall, we estimated that about 25 % of T2D cases could be attributable to air pollution and associated interactions.

CONCLUSIONS

Associations between air pollution and T2D were stronger among individuals with unhealthier lifestyle on an additive interaction scale. Public health interventions that address both reduction of exposure to high levels of air pollution in addition to lifestyle changes may have more benefit on reducing T2D risk than focusing on lifestyle changes alone.

Pollution and coronary risk: how much does it matter?

Air pollutants are a complex mixture of gaseous substances and particulate matter (PM). Each component potentially has specific harmful effects on human health, but several experimental and clinical studies have shown a strong impact of fine particles on major adverse cardiovascular events. Most of the available evidence concerns the effects of exposure to PM with a diameter of <2.5 µm (PM2.5) and the risk of developing coronary heart disease through inflammation and oxidative stress. While prolonged exposure to PM2.5 has been shown to be associated with the development of atherosclerosis and cardio-metabolic risk factors, short-term exposure has instead proved to be a trigger for acute coronary events, and especially in subjects with pre-existing coronary artery disease. As such, environmental PM2.5 is a major risk element for global public health. This underlines on the one hand not only the need to adopt and encourage preventive measures especially for individuals with a higher risk profile but also to practice environmental policies that are effective in promoting the reduction of exposure to pollutants.

Role of Liver Enzymes in the Relationship Between Particulate Matter Exposure and Diabetes Risk: A Longitudinal Cohort Study

CONTEXT

Particulate matter (PM) is an important risk factor for diabetes. However, its underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in the pathophysiology of diabetes, few studies have explored this in the association between PM and diabetes.

OBJECTIVE

We investigated the role of liver enzymes in mediating the relationship between PM exposure and diabetes.

METHODS

We included a total of 7963 participants from the China Multi-Ethnic Cohort. Residential exposure to PM was assessed using a validated spatial-temporal assessment method. Diabetes was diagnosed according to the criteria from American Diabetes Association. Associations between PM, liver enzyme [including alanine aminotransferase (ALT), aspartate aminotransferase, alkaline phosphatase, and γ-glutamyl transpeptidase (GGT)], and diabetes were estimated using multivariable regression models. The function of liver enzymes in the relationship between PM and diabetes was assessed using mediation analysis.

RESULTS

PM exposure was positively associated with the odds of diabetes, with odds ratios of 1.32 (95% CI 0.83, 2.09), 1.33 (95% CI 1.07, 1.65), and 1.18 (95% CI 1.02, 1.36) for every 10-μg/m3 increment in ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10) PM, respectively. ALT (4.47%) and GGT (4.78%) exhibited statistically significant mediation effects on the association between PM2.5 and diabetes, and the ALT (4.30%) also had a mediating role on PM10. However, none of the liver enzymes had a significant mediating effect on PM1.

CONCLUSION

The relationship between PM and diabetes is partially mediated by liver enzymes, suggesting that lipid accumulation, oxidative stress, and chronic inflammation in the liver may be involved in its pathogenesis.

K-means cluster analysis of cooperative effects of CO, NO2, O3, PM2.5, PM10, and SO2 on incidence of type 2 diabetes mellitus in the US

Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex mixture of components for which the composition depends on sources and metrological factors. The US Environmental Protection Agency (EPA) monitors and regulates certain components of air pollution known to have negative consequences for human health. Research assessing the health effects of these components of AP often uses traditional regression models, which might not capture more complex and interdependent relationships. Machine learning has the capability to simultaneously assess multiple components and find complex, non-linear patterns that may not be apparent and could not be modeled by other techniques. Here we use k-means clustering to assess the patterns associating PM2.5, PM10, CO, NO2, O3, and SO2 measurements and changes in annual diabetes incidence at a US county level. The average age adjusted annual decrease in diabetes incidence for the entire US populations is -0.25 per 1000 but the change shows a significant geographic variation (range: -17.2 to 5.30 per 1000). In this paper these variations were compared with the local daily AP concentrations of the pollutants listed above from 2005 to 2015, which were matched to the annual change in diabetes incidence for the following year. A total of 134,925 daily air quality observations were included in the cluster analysis, representing 125 US counties and the District of Columbia. K-means successfully clustered AP components and indicated an association between exposure to certain AP mixtures with lower decreases on T2D incidence.

Effects of ambient air pollution on glycosylated hemoglobin: a systematic review and meta-analysis

Air pollution is one of the biggest environmental health problems in the world; accumulative studies have shown that air pollution was closely related to metabolism disorders. HbA1c is a stable indicator for blood glucose level monitoring. However, studies on the impact of ambient air pollution on HbA1c have inconsistent conclusions. The objective of the study is to explore the influence of ambient air pollution on HbA1c. By searching keywords, a systematic literature retrieval was carried out on PubMed, Cochrane Library, Web of Science, and Embase databases up to April 2022. Pooled percentage change (%-change) and 95% confidence intervals (95% CI) were estimated using random effect models for particulate matter (PM) and nitrogen dioxide (NO₂). A subgroup analysis of body mass index (BMI), study region, exposure period, sample size, sensitivity analysis, and publication bias detection was also performed. There were 8, 12, and 6 studies included in this meta-analysis to explore the association between PM₁₀, PM_2.5, NO₂, and HbA1c, respectively. The results showed that for every increase of 10 μg/m³ in PM₁₀, PM_2.5, and NO₂, the %-changes in HbA1c were 0.13%, 0.814%, and 0.02%, respectively. The subgroup analysis showed that exposure period, sample size, and BMI were associated with HbA1c in response to air pollution. PM₁₀, PM_2.5, and NO₂ exposure were significantly associated with increased HbA1c levels.

Diabetogene Umweltfaktoren

Das Risiko, an einem Diabetes mellitus Typ 2 zu erkranken, wird maßgeblich von Merkmalen unserer physischen und sozialen Umwelt beeinflusst. Diese Umweltfaktoren wirken sich insbesondere auf das Ausmaß individueller körperlicher Aktivität sowie das Ernährungsverhalten aus. Weiterhin zählen die Exposition gegenüber Tabakrauch sowie Luftverschmutzung zu den etablierten Risikofaktoren. In den letzten Jahren rückten darüber hinaus weitere mögliche diabetogene Umweltaspekte in den Fokus der Forschung, darunter Umgebungslärm und andere stressfördernde Einflüsse sowie Chemikalien mit endokriner Wirkung. Im folgenden Beitrag wird der Forschungsstand zur Rolle von Umweltfaktoren bei der Entstehung eines Typ-2-Diabetes vorgestellt. Zudem wird diskutiert, wie diese Umweltfaktoren günstig beeinflusst werden können und was DiabetologInnen und andere Diabetesfachkräfte sowie PatientInnen mit Diabetes hierzu beitragen können.

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.

Combined effects of air pollution in adulthood and famine exposure in early life on type 2 diabetes

Famine exposure or air pollution is linked to type 2 diabetes mellitus (T2DM). However, their combined effects on T2DM remain largely unknown. A total of 11,640 individuals were obtained from the Henan Rural Cohort Study. According to their birthdate, participants were divided into three famine exposure subgroups: fetal exposed, childhood exposed, and unexposed groups. The air pollutants (particles with aerodynamics diameters ≤ 1.0 µm (PM₁), ≤ 2.5 µm, and ≤ 10 µm, and nitrogen dioxide) concentrations of each individual were estimated by a spatiotemporal model. Participants were divided into low or high air pollution exposure groups taking the 1st quartile value of air pollutants as the cut-off point. Logistic regression model was used to analyze independent and joint associations between air pollution exposure, famine exposure, and T2DM. Positive associations of air pollution and famine exposure with T2DM were found. Participants who experienced fetal or childhood famine and also were exposed to high concentrations of any kind of the air pollutants had a much higher risk for T2DM than those with no famine and low air pollutants exposure (taking PM_1.0 for example, the odds ratio [OR]: 1.76, 95% confidence interval [CI]: 1.25, 2.47 for fetal famine, and OR: 1.64, 95%CI: 1.13, 2.40 for childhood famine). After stratified analysis, similar results were observed in women. The results indicated that both famine exposure in early life and air pollution exposure in adulthood are related to increased risk for prevalent T2DM, and they have combined effects on T2DM.

Long-term exposure to ozone and diabetes incidence: A longitudinal cohort study in China

BACKGROUND

Ozone (O₃) has become a prominent air pollutant problem as other pollutants concentrations have decreased obviously since China published Air Pollution Action Plan Pollution Prevention Action Plan in 2013. Few studies examined the association between O₃ and diabetes especially in developing countries. This study was designed to investigate the above topic in China.

METHODS

We conducted a prospective cohort study based on a nationwide survey of 13,548 adults from China Health and Retirement Longitudinal Study. City-level exposure to ozone for each participant was matched through ChinaHighO₃ dataset. Time-varying cox proportional hazard regression model was applied to determine the association. Stratification analyses were conducted to explore potential effect modification.

RESULTS

The annual mean concentration of O₃ was 86.6 μg/m³. A 10 μg/m³ increase in 1-year average O₃ concentration was associated with 5.7% (95% CI: 1.004-1.114) relative increment in hazards ratio of diabetes incidence in the fully adjusted model. Results stayed stable when controlling for physical activity, PM_2.5 and mean temperature.

CONCLUSIONS

Our findings provided initial support for a positive and robust association between long-term exposure to O₃ and diabetes incidence in a developing country. More scientific and social attention should be attached to the ozone-induced risks of diabetes occurrence.

Association between exposure to air pollutants and the risk of hospitalization for pulmonary embolism in Beijing, China: A case-crossover design using a distributed lag nonlinear model

BACKGROUND

Pulmonary embolism (PE) is a life-threatening condition. Few studies have evaluated the relationship between air pollution and PE, and these results have been inconsistent. Therefore, our study aimed to investigate the association between air pollutant exposure and the risk of hospitalization due to PE.

MATERIALS AND METHODS

Daily PE admissions, meteorological data, and ambient pollution data from January 1, 2015, to December 31, 2018, were collected in Beijing. A quasi-Poisson regression model combined with time-stratified case-crossover design and a distributed lag nonlinear model was used to determine the effect of air pollutant exposure on PE admission. To examine the stability of air pollutants' effects, multi-pollutant analyses were performed. Stratified analyses by age and sex were further conducted.

RESULTS

There were 5060 PE admissions during the study period, with an estimated incidence of 6.5 per 100,000. PM_2.5, PM₁₀, SO₂, O₃ and CO exposures were significantly associated with elevated risk of PE hospitalization. The highest cumulative risks were observed at a lag of 0-28 days for PM_2.5 (relative risk [RR] = 1.056, 95% confidence intervals [CI]: 1.015-1.098), PM₁₀ (RR = 1.042, 95%CI: 1.010-1.075), and CO (RR = 1.466, 95%CI: 1.127-1.906), at a lag of 0-27 days for SO₂ (RR = 1.674, 95%CI: 1.200-2.335), and at a lag of 0-4 days for O₃ (RR = 1.019, 95%CI: 1.001-1.038). All associations mentioned above except O₃ remained significant in multi-pollutant models. Stratified analyses showed that women and those aged ≥65 years people were more sensitive to PM₁₀ and CO exposure than men and those aged <65 years. The effect of PM_2.5 exposure was statistically significant in all subgroups.

CONCLUSIONS

Exposure to PM_2.5, PM₁₀, SO₂, and CO showed a positive association with PE hospitalization. High-risk PE groups should take special precautions on days with poor air quality.

Short-term exposure to ambient air pollution and type 2 diabetes mortality: A population-based time series study

Acute health effects of air pollution on diabetes risk have not been fully studied in developing countries and the results remain inconsistent. This study aimed to investigate the association between short-term exposure to ambient air pollution and Type 2 diabetes mellitus (T2DM) mortality in China. Data on T2DM mortality from 2013 to 2019 were obtained from the Cause of Death Reporting System (CDRS) of Wuhan Center for Disease Control and Prevention. Air pollution data for the same period were collected from 10 national air quality monitoring stations of Wuhan Ecology and Environment Institute, including daily average PM_2.5, PM₁₀, SO₂, and NO₂. Meteorological data including daily average temperature and relative humidity were collected from Wuhan Meteorological Bureau. Generalized additive models (GAM) based on quasi-Poisson distribution were applied to evaluate the association between short-term exposure to air pollution and daily T2DM deaths. A total of 9837 T2DM deaths were recorded during the study period in Wuhan. We found that short-term exposure to PM_2.5, PM₁₀, SO₂, and NO₂ were positively associated with T2DM mortality, and gaseous pollutants appeared to have greater effects than particulate matter (PM). For the largest effect, per 10 μg/m³ increment in PM_2.5 (lag 02), PM₁₀ (lag 02), SO₂ (lag 03), and NO₂ (lag 02) were significantly associated with 1.099% (95% CI: 0.451, 1.747), 1.016% (95% CI: 0.517, 1.514), 3.835% (95% CI: 1.480, 6.189), and 1.587% (95% CI: 0.646, 2.528) increase of daily T2DM deaths, respectively. Stratified analysis showed that females or elderly population aged 65 and above were more susceptible to air pollution exposure. In conclusion, short-term exposure to air pollution was significantly associated with a higher risk of T2DM mortality. Further research is required to verify our findings and elucidate the underlying mechanisms.

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.

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

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

PM2.5 and Diabetes in the Japanese Population

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

PM2.5 induces intestinal damage by affecting gut microbiota and metabolites of rats fed a high-carbohydrate diet

PM_2.5 has a major impact on the gastrointestinal system, but the specific mechanism behind this action is not fully understood. Current studies have focused on the relationship between PM_2.5 and intestinal flora disorder, while ignoring the important influence of diet on gut microbes. In this study, SD rats were fed either a normal, high-fat, or high-carbohydrate diet for two months and exposed to PM_2.5 (7 mg/kg b.w.) by intratracheal instillation. The results showed that the body and kidney weights of the rats in the high-fat diet group were significantly increased relative to those with a normal diet, and changes in the intestinal microbes and metabolites induced by PM_2.5 were observed. Rats in the high-carbohydrate diet group had a significant response, and the diversity and richness indices of the flora were reduced (p < 0.05); additionally, intestinal Biffidobacterium and Lactobacillus were enriched, while many endogenous metabolites were found. Some amino acids derivatives and long-chain fatty acids were increased (p < 0.05). Both diet structure and PM_2.5 exposure can affect the composition of gut microbiota, and intestinal metabolites may be associated with cell membrane damage when a high-carbohydrate diet interacts with PM_2.5. This study considers multiple dietary factors to further supplement the evidence of intestinal damage via PM_2.5.

[Air pollution and cardiovascular diseases]

Air pollution in the environment and in households is responsible worldwide for almost 9 million preventable premature deaths per year and almost 800,000 such deaths within Europe. Air pollution therefore shortens life expectancy worldwide by almost 3 years. Smoking, a proven cardiovascular risk factor, shortens the mean life expectancy by 2.2 years. Epidemiological studies have shown that air pollution from fine and coarse particulate matter is associated with increased cardiovascular morbidity and mortality. Responsible for this are mainly cardiovascular diseases, such as coronary heart disease, heart attack, heart failure, stroke, hypertension and also diabetes, which are mainly caused or aggravated by fine particulate matter. After inhalation fine particulate matter can reach the brain directly and also reach the bloodstream via a transition process. There, the particles are absorbed by the blood vessels where they stimulate the formation of reactive oxygen species (ROS) in the vascular wall. They therefore promote the formation of atherosclerotic changes and in this way increase the cardiovascular risks, especially an increase in chronic ischemic heart disease and stroke. Recent studies also reported that in coronavirus disease 2019 (COVID-19) patients a high degree of air pollution is correlated with severe disease courses with cardiovascular complications and pulmonary diseases. This necessitates preventive measures, such as lowering of the upper limits for air pollutants. Individual measures to mitigate the health consequences of fine particulate matter are also discussed.

THE ENERGY–POLLUTION–HEALTH NEXUS: A PANEL DATA ANALYSIS OF LOW- AND MIDDLE-INCOME ASIAN COUNTRIES

Increased consumption of nonrenewable energy sources may lead to more air pollution, resulting in negative health impacts in a society. The main purpose of this study is to investigate the relationship between fossil fuel energy consumption and health issues using generalized method of moments estimation technique for data from 18 Asian countries (both low- and middle-income) over the period 1991–2018. The findings demonstrate that fossil fuel energy consumption increases the risk of lung and respiratory diseases. In addition, the results demonstrate the significant effect of CO2 emissions and fossil fuel consumption on undernourishment and death rates. Furthermore, we find that increases in the gross domestic product per capita and healthcare expenditure may help reduce undernourishment and death ratio. The conclusion recommends that diversification of energy in low- and middle-income countries from too much reliance on fossil fuels to more renewable energy sources can improve energy insecurity, at the same time reduce greenhouse gas emissions and minimize the negative impacts on human health.

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.

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

OBJECTIVES

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

DESIGN

A nested case-control study.

SETTING

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

PARTICIPANTS

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

METHODS AND OUTCOME MEASURES

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

RESULTS

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

CONCLUSIONS

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

Environmental determinants of cardiovascular disease: lessons learned from air pollution

Air pollution is well recognized as a major risk factor for chronic non-communicable diseases and has been estimated to contribute more to global morbidity and mortality than all other known environmental risk factors combined. Although air pollution contains a heterogeneous mixture of gases, the most robust evidence for detrimental effects on health is for fine particulate matter (particles ≤2.5 µm in diameter (PM2.5)) and ozone gas and, therefore, these species have been the main focus of environmental health research and regulatory standards. The evidence to date supports a strong link between the risk of cardiovascular events and all-cause mortality with PM2.5 across a range of exposure levels, including to levels below current regulatory standards, with no 'safe' lower exposure levels at the population level. In this comprehensive Review, the empirical evidence supporting the effects of air pollution on cardiovascular health are examined, potential mechanisms that lead to increased cardiovascular risk are described, and measures to reduce this risk and identify key gaps in our knowledge that could help address the increasing cardiovascular morbidity and mortality associated with air pollution are discussed.

Cardiovascular disease burden from ambient air pollution in Europe reassessed using novel hazard ratio functions

Aims

Ambient air pollution is a major health risk, leading to respiratory and cardiovascular mortality. A recent Global Exposure Mortality Model, based on an unmatched number of cohort studies in many countries, provides new hazard ratio functions, calling for re-evaluation of the disease burden. Accordingly, we estimated excess cardiovascular mortality attributed to air pollution in Europe.

Methods and results

The new hazard ratio functions have been combined with ambient air pollution exposure data to estimate the impacts in Europe and the 28 countries of the European Union (EU-28). The annual excess mortality rate from ambient air pollution in Europe is 790 000 [95% confidence interval (95% CI) 645 000–934 000], and 659 000 (95% CI 537 000–775 000) in the EU-28. Between 40% and 80% are due to cardiovascular events, which dominate health outcomes. The upper limit includes events attributed to other non-communicable diseases, which are currently not specified. These estimates exceed recent analyses, such as the Global Burden of Disease for 2015, by more than a factor of two. We estimate that air pollution reduces the mean life expectancy in Europe by about 2.2 years with an annual, attributable per capita mortality rate in Europe of 133/100 000 per year.

Conclusion

We provide new data based on novel hazard ratio functions suggesting that the health impacts attributable to ambient air pollution in Europe are substantially higher than previously assumed, though subject to considerable uncertainty. Our results imply that replacing fossil fuels by clean, renewable energy sources could substantially reduce the loss of life expectancy from air pollution.

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

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

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Associations between the incidence and mortality rates of type 2 diabetes mellitus and long-term exposure to ambient air pollution: A 12-year cohort study in northern China

BACKGROUND

Ambient air pollution has recently been related to type 2 diabetes mellitus (T2DM), a disease that has caused an economic and health burden worldwide. Evidence of an association between air pollution and T2DM was reported in the United States and Europe. However, few studies have focused on the association with high levels of air pollutants in a developing country.

OBJECTIVES

We conducted a 12-year cohort study to assess the incidence and mortality of T2DM associated with long-term exposure to PM₁₀, SO₂, and NO₂.

METHODS

A retrospective cohort with participants from four cities in northern China was conducted to assess mortality and incidence of T2DM from 1998 to 2009. Incidence of T2DM was self-reported, and incident intake of an antidiabetic drug or injection of insulin simultaneously and mortality of T2DM was obtained from a family member and double checked against death certificates provided from the local center for disease control and prevention. Individual pollution exposures were the mean concentrations of pollutants estimated from the local environmental monitoring centers over the survival years. Hazard ratios (HRs) were estimated using Cox regression models after adjusting for potential confounding factors.

RESULTS

A total of 39 054 participants were recruited into the mortality cohort, among which 59 subjects died from T2DM; 38 529 participants were analyzed in the incidence cohort, and 1213 developed new cases of T2DM. For each 10 μg/m³ increase in PM₁₀, SO₂, and NO₂, the adjusted HRs and 95% confidence interval (CI) for diabetic incidence were 1.831 (1.778, 1.886), 1.287 (1.256, 1.318), and 1.472 (1.419, 1.528), respectively. Similar results can be observed in the analysis of diabetic mortality with HRs (95% CI) up to 2.260 (1.732, 2.950), 1.130 (1.042, 1.225), and 1.525 (1.280, 1.816), respectively.

CONCLUSIONS

Our results suggested that long-term exposure to high levels of PM₁₀, SO₂, and NO₂ increase risk of incident and mortality of T2DM in China.

The Nexus between Workplace Exposure for Wood, Welding, Motor Mechanic, and Oil Refinery Workers and the Prevalence of Prediabetes and Type 2 Diabetes Mellitus

Workplace exposure in various occupational and industrial sectors is an emerging health concern worldwide. This study aimed to investigate the nexus between workplace exposure for wood, welding, motor mechanic, and oil refinery workers and the prevalence of prediabetes and type 2 diabetes mellitus. Initially, 2500 male volunteers who were wood, welding, motor mechanic, and oil refinery workers were interviewed. After an examination of their demographics and medical history, 1408 non-smoking wood (158), welding (560), motor mechanic (272), and oil refinery workers (217), along with 201 control subjects, were selected. The participants' mean age was 36.59 ± 0.29 years and the mean body mass index was 26.14 ± 0.11 kg/m². The selected industry workers had been exposed to their respective wood, welding, motor mechanic, and oil refinery workplaces for 8 h per day, six days per week. The American Diabetic Association (ADA)-based glycated hemoglobin (HbA1c) criterion was used to diagnose prediabetes and type 2 diabetes mellitus. Subjects with an HbA1c of less than 5.7% were regarded as non-diabetics, subjects with an HbA1c of 5.7%-6.4% were considered prediabetics, and subjects with an HbA1c of more than 6.4% were considered diabetics. In wood industry workers, the prevalence of prediabetes (PD) was 64 (40.50%) and in type 2 diabetes mellitus (T2DM), it was 21 (13.29%); in welding workers, the prevalence of prediabetes was 261 (46.60%), and for T2DM, it was 90 (16.07%); in motor mechanic workers, the prevalence of prediabetes was 110 (40.44%), and for T2DM, it was 126 (46.32%); and in oil refinery workers, the prevalence of prediabetes was 80 (36.86%), and for T2DM, it was 35 (16.12%). However; the combined prevalence of prediabetes and T2DM among wood, welding, motor mechanic, and oil refinery workers was 421 (34.79%) and 515 (42.66%), respectively. The prevalence of prediabetes and T2DM among workers increased with the duration of working exposure in the wood, welding, motor mechanic, and oil refinery industries. A one-year working exposure in these industries caused an increase of 0.03% in HbA1c. Workplace exposure in wood, welding, motor mechanic, and oil refinery industries increased the risk of prevalence of prediabetes and T2DM among the workers and affected the diabetes etiology.