Traffic-related air pollution and incident type 2 diabetes: results from the SALIA cohort study

Social determinants of inflammatory markers linking depression and type 2 diabetes among women: A scoping review

OBJECTIVE

Inflammation is implicated in the pathophysiology of depression and type 2 diabetes (T2D) and is linked to social determinants of health (SDoH) associated with socioeconomic disadvantage. The objective of this review is to identify and map the range of SDoHs associated with inflammation in depression, T2D, or their co-occurrence among women.

METHODS

PubMed, CINAHL, PsychINFO, and Web of Science were searched March-July 2023 to identify studies where 1) an SDoH was a predictor or independent variable, 2) depression or T2D was a clinical focus, 3) inflammatory markers were collected, and 4) analysis was specific to women. We used the National Institute on Minority Health and Health Disparities research framework to guide searching SDoHs, organize findings, and identify gaps.

RESULTS

Of the 1135 studies retrieved, 46 met criteria. Within the reviewed studies, the most used inflammatory measures were C-reactive protein, interleukin-6, and tumor necrosis factor-α, and the most studied SDoHs were early life stress and socioeconomic status. Individual and interpersonal-level variables comprised the bulk of SDoHs in the included studies, while few to no studies examined built environment (n = 6) or health system level (n = 0) factors. Disadvantageous SDoHs were associated with higher levels of inflammation across the included studies.

CONCLUSION

The scope and intersection of depression and T2D represent a syndemic that contributes to and results from socioeconomic inequities and disproportionately affects women. Simultaneous inclusion of social and inflammatory measures, particularly understudied SDoHs, is needed to clarify potent targets aimed at advancing health and equity.

Investigating the temporal trends of diabetes disease burden in China during 1990-2019 from a global perspective

Introduction

Diabetes poses a global public health challenge and our understanding of its temporal evolution in China relative to the rest of the world is limited. Our study aims to comprehensively examine the temporal trend of diabetes DALYs in China from a global perspective.

Methods

We analyzed data on diabetes incidence, prevalence, and mortality for individuals aged ≥20 years in China and globally from the Global Burden of Disease (GBD) 2019 study. We assessed trends in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of diabetes in China and globally by estimating annual percentage changes (EAPCs). We employed decomposition analysis to reveal factors driving the trend of diabetes DALYs in China.

Results

During 1990-2019, the number of diabetes patients increased by 160% from 35.14 million to 91.70 million in China. The ASIR of diabetes increased from 249 per 100,000 to 329 per 100,000 in China, which was lower than the global rate (419 per 100,000 in 2019). The EAPC of diabetes incidence was also lower in China compared to the global rate (1.02% vs. 1.57%). Consistently, the age-standardized prevalence rate of diabetes increased from 4788 per 100,000 to 8170 per 100,000 during 1990-2019 in China, which remained lower than the corresponding global rate (8827 per 100,000 in 2019). Further, the ASMR of diabetes increased from 9 per 100,000 to 15 per 100,000 during 1990-2019 in China, which was lower than the corresponding global rate (30 per 100,000 in 2019). However, EAPC of diabetes mortality in China was much higher than the global level (1.75% vs. 1.07%). Globally, the rising diabetes DALYs was predominantly attributed to population growth (55.2%) and epidemiologic changes (24.6%). In comparison, population growth (48.9%) also played an important role in the increasing diabetes DALYs in China, but aging (43.7%) was second major contributor.

Conclusion

Our findings show that diabetes DALYs in China followed a global increasing trend during 1990-2019. Notably, aging has a very substantial contribution to the increase in diabetes DALYs in China in addition to population growth. .

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Environmental PM2.5-triggered stress responses in digestive diseases

Airborne particulate matter in fine and ultrafine ranges (aerodynamic diameter less than 2.5 μm, PM2.5) is a primary air pollutant that poses a serious threat to public health. Accumulating evidence has pointed to a close association between inhalation exposure to PM2.5 and increased morbidity and mortality associated with modern human complex diseases. The adverse health effect of inhalation exposure to PM2.5 pollutants is systemic, involving multiple organs, different cell types and various molecular mediators. Organelle damages and oxidative stress appear to play a major role in the cytotoxic effects of PM2.5 by mediating stress response pathways related to inflammation, metabolic alteration and cell death programmes. The organs or tissues in the digestive tract, such as the liver, pancreas and small intestines, are susceptible to PM2.5 exposure. This review underscores PM2.5-induced inflammatory stress responses and their involvement in digestive diseases caused by PM2.5 exposure.

Association between residential proximity to major roadways and chronic multimorbidity among Chinese older adults: a nationwide cross-sectional study

BACKGROUND

Multiple negative health outcomes were linked to residential proximity to major roadways. Nevertheless, there is limited knowledge regarding the association between residential proximity to major roadways and chronic multimorbidity.

METHODS

We used data from the 2018 wave of the Chinese Longitudinal Healthy Longevity Survey, which included 12,214 individuals aged ≥ 60. We derived the residential proximity to major roadways from self-reported data, defining chronic multimorbidity as the presence of two or more concurrent chronic diseases. A binary logistic regression model was utilized to investigate the association between residential proximity to major roadways and chronic multimorbidity. The model accounted for some demographic features, socioeconomic conditions, social participation, and health conditions. Subsequently, we conducted subgroup analyses to examine potential interaction effects.

RESULTS

Residential proximity to major roadways was associated with chronic multimorbidity, even after adjusting for confounding factors. Compared with those living > 300 m from major roadways, the OR for those living 201-300 m, 101-200 m, 50-100 m, and < 50 m were increased. When subgroup analyses were conducted using a cutoff point of 200 m, the risk of chronic multimorbidity associated with residential proximity to major roadways was stronger in participants with education levels > 6 years (P = 0.017).

CONCLUSION

Our findings provide important implications for improving residential area siting, transportation policies, and environmental regulations to reduce the risk of chronic multimorbidity caused by traffic-related exposure.

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.

Particulate air pollution exaggerates diet-induced insulin resistance through NLRP3 inflammasome in mice

Air particulate matter 2.5 (PM2.5) has been demonstrated to exaggerate insulin resistance in both human and animal studies. However, the exact molecular mechanisms remain elusive. This study sought to assess the role of NLRP3 inflammasome in PM2.5 exposure-induced insulin resistance and explore the underlying mechanisms. Wild-type (WT), Nlrp3-/-, Tlr4Lps-d, or Nrf2-/- mice, on a normal diet or high-fat diet (HFD), were exposed to PM2.5 or filtered air (FA) in a whole-body exposure facility. Priming (first signal) and assembly (second signal) of NLRP3 inflammasome activation were assessed by measuring the transcription of Nlrp3/Il-1β and detecting the activity of caspase-1 and secretion of IL-1β. We found PM2.5 exposure exaggerated insulin resistance and increased IL-1β production in the HFD-fed WT mice, but not Nlrp3-/- mice. Gene expressions of Nlrp3 and Il-1β in the lungs and peritoneal macrophages were upregulated in WT mice exposed to PM2.5. When stimulated with LPS (first signal) or monosodium urate (second signal), PM2.5 exposure was able to enhance the activity of caspase-1 and IL-1β secretion, suggesting that PM2.5 may serve as a stimulus of either the first or second signal for NLRP3 inflammasome activation. Effects of PM2.5 on caspase-1 activation and IL-1β secretion were partially blocked in Tlr4Lps-d mice. Reactive oxygen species (ROS), co-localization of NLRP3 and mitochondria, and secondary lysosomes in macrophages were increased after PM2.5 exposure, while deficiency of antioxidant gene Nrf2 in mice significantly enhanced PM2.5-induced secretion of IL-1β. Imaging flow cytometry and transmission electron microscopy demonstrated an engulfment of PM2.5 particles by macrophages, while suppression of phagocytosis by cytochalasin D abolished PM2.5-induced transcription of Nlrp3/Il-1β. Our results demonstrated a critical role of NLRP3 inflammasome in PM2.5 exaggerated insulin resistance, and multiple pathways in the first and second signals of NLRP3 inflammasome activation may be involved.

Fine particulate matter (PM2.5)-induced pulmonary oxidative stress contributes to increases in glucose intolerance and insulin resistance in a mouse model of circadian dyssynchrony

Results of human and animal studies independently suggest that either ambient fine particulate matter (PM2.5) air pollution exposure or a disturbed circadian rhythm (circadian dyssynchrony) are important contributing factors to the rapidly evolving type-2-diabetes (T2D) epidemic. The objective of this study is to investigate whether circadian dyssynchrony increases the susceptibility to PM2.5 and how PM2.5 affects metabolic health in circadian dyssynchrony. We examined systemic and organ-specific changes in glucose homeostasis and insulin sensitivity in mice maintained on a regular (12/12 h light/dark) or disrupted (18/6 h light/dark, light-induced circadian dyssynchrony, LICD) light cycle exposed to air or concentrated PM2.5 (CAP, 6 h/day, 30 days). Exposures during Zeitgeber ZT3-9 or ZT11-17 (Zeitgeber in circadian time, ZT0 = begin of light cycle) tested for time-of-day PM2.5 sensitivity (chronotoxicity). Mice transgenic for lung-specific overexpression of extracellular superoxide dismutase (ecSOD-Tg) were used to assess the contribution of CAP-induced pulmonary oxidative stress. Both, CAP exposure from ZT3-9 or ZT11-17, decreased glucose tolerance and insulin sensitivity in male mice with LICD, but not in female mice or in mice kept on a regular light cycle. Although changes in glucose homeostasis in CAP-exposed male mice with LICD were not associated with obesity, they were accompanied by white adipose tissue (WAT) inflammation, impaired insulin signaling in skeletal muscle and liver, and systemic and pulmonary oxidative stress. Preventing CAP-induced oxidative stress in the lungs mitigated the CAP-induced decrease in glucose tolerance and insulin sensitivity in LICD. Our results demonstrate that circadian dyssynchrony is a novel susceptibility state for PM2.5 and suggest that PM2.5 by inducing pulmonary oxidative stress increases glucose intolerance and insulin resistance in circadian dyssynchrony.

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

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

Environmental Pollution and the Risk of Developing Metabolic Disorders: Obesity and Diabetes

To meet the increased need for food and energy because of the economic shift brought about by the Industrial Revolution in the 19th century, there has been an increase in persistent organic pollutants (POPs), atmospheric emissions and metals in the environment. Several studies have reported a relationship between these pollutants and obesity, and diabetes (type 1, type 2 and gestational). All of the major pollutants are considered to be endocrine disruptors because of their interactions with various transcription factors, receptors and tissues that result in alterations of metabolic function. POPs impact adipogenesis, thereby increasing the prevalence of obesity in exposed individuals. Metals impact glucose regulation by disrupting pancreatic β-cells, causing hyperglycemia and impaired insulin signaling. Additionally, a positive association has been observed between the concentration of endocrine disrupting chemicals (EDCs) in the 12 weeks prior to conception and fasting glucose levels. Here, we evaluate what is currently known regarding the link between environmental pollutants and metabolic disorders. In addition, we indicate where further research is required to improve our understanding of the specific effects of pollutants on these metabolic disorders which would enable implementation of changes to enable their prevention.

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.

Associations of the built environment with type 2 diabetes in Asia: a systematic review

OBJECTIVES

Our study aimed to systematically review the literature and synthesise findings on potential associations of built environment characteristics with type 2 diabetes (T2D) in Asia.

DESIGN

Systematic review of the literature.

DATA SOURCES

Online databases Medline, Embase and Global Health were used to identify peer-reviewed journal articles published from inception to 23 January 2023.

ELIGIBILITY CRITERIA

Eligible studies included cohort, cross-sectional and case-control studies that explored associations of built environment characteristics with T2D among adults 18 years and older in Asia.

DATA EXTRACTION AND SYNTHESIS

Covidence online was used to remove duplicates and perform title, abstract and full-text screening. Data extraction was carried out by two independent reviewers using the OVID database and data were imported into MS Excel. Out of 5208 identified studies, 28 studies were included in this systematic review. Due to heterogeneity in study design, built environment and outcome definitions, a semiqualitative analysis was conducted, which synthesised results using weighted z-scores.

RESULTS

Five broad categories of built environment characteristics were associated with T2D in Asia. These included urban green space, walkability, food environment, availability and accessibility of services such as recreational and healthcare facilities and air pollution. We found very strong evidence of a positive association of particulate matter (PM_2.5, PM₁₀), nitrogen dioxide and sulfur dioxide (p<0.001) with T2D risk.

CONCLUSION

Several built environment attributes were significantly related to T2D in Asia. When compared with Western countries, very few studies have been conducted in Asia. Further research is, therefore, warranted to establish the importance of the built environment on T2D. Such evidence is essential for public health and planning policies to (re)design neighbourhoods and help improve public health across Asian countries.

PROSPERO REGISTRATION NUMBER

CRD42020214852.

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.

Early pregnancy particulate matter exposure, pre-pregnancy adiposity and risk of gestational diabetes mellitus in Finnish primiparous women: An observational cohort study

AIMS

To evaluate the association between the exposure of particulate matter with an aerodynamic diameter of ≤ 2.5μm (PM_2.5) and with an aerodynamic diameter of ≤ 10μm (PM₁₀) over the first trimester and the risk of gestational diabetes mellitus (GDM), and to assess whether maternal pre-pregnancy body mass index (BMI) modified the GDM risk.

METHODS

All Finnish primiparous women without previously diagnosed diabetes who delivered between 2009 and 2015 in the city of Vantaa, Finland, composed the study cohort (N = 6189). Diagnosis of GDM was based on a standard 75 g 2-hour oral glucose tolerance test. The average daily concentration of PM_2.5 and PM₁₀ over the first trimester was calculated individually for each woman. The relationship between exposure of PM_2.5 and PM₁₀ and GDM was analyzed with logistic models.

RESULTS

No association was observed between the average daily concentrations of PM_2.5 and PM₁₀ over the first trimester and the GDM risk. When simultaneously taking BMI and PM₁₀ into account both mean daily PM₁₀ concentration (p = 0.047) and pre-pregnancy BMI (p = 0.016) increased GDM risk independently and an interaction (p = 0.013) was observed between PM₁₀ concentration and pre-pregnancy BMI.

CONCLUSIONS

Even globally low PM₁₀ exposure level together with elevated maternal pre-pregnancy BMI seems to increase the GDM risk.

Efficient gene-environment interaction testing through bootstrap aggregating

Gene-environment (GxE) interactions are an important and sophisticated component in the manifestation of complex phenotypes. Simple univariate tests lack statistical power due to the need for multiple testing adjustment and not incorporating potential interplay between several genetic loci. Approaches based on internally constructed genetic risk scores (GRS) require the partitioning of the available sample into training and testing data sets, thus, lowering the effective sample size for testing the GxE interaction itself. To overcome these issues, we propose a statistical test that employs bagging (bootstrap aggregating) in the GRS construction step and utilizes its out-of-bag prediction mechanism. This approach has the key advantage that the full available data set can be used for both constructing the GRS and testing the GxE interaction. To also incorporate interactions between genetic loci, we, furthermore, investigate if using random forests as the GRS construction method in GxE interaction testing further increases the statistical power. In a simulation study, we show that both novel procedures lead to a higher statistical power for detecting GxE interactions, while still controlling the type I error. The random-forests-based test outperforms a bagging-based test that uses the elastic net as its base learner in most scenarios. An application of the testing procedures to a real data set from a German cohort study suggests that there might be a GxE interaction involving exposure to air pollution regarding rheumatoid arthritis.

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

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

Traffic-related air pollution is a risk factor in the development of chronic obstructive pulmonary disease

Background

Outdoor traffic-related air pollution has negative effects on respiratory health. In this study, we aimed to explore the effect of outdoor traffic-related air pollution on chronic obstructive pulmonary disease (COPD) in Guangzhou.

Methods

We enrolled 1,460 residents aged 40 years or older between 21 January 2014 and 31 January 2018. We administered questionnaires and spirometry tests. The distance of participants' residences or locations of outdoor activities from busy roads (as indicators of outdoor traffic-related air pollution), indoor air pollution, and smoking history were queried in the questionnaires.

Results

Of the 1,460 residents with valid survey and test results, 292 were diagnosed with COPD, with a detection rate of 20%. Participants who lived and did their outdoor activities near busy roads had a higher detection rate of COPD. Among residents living at distances of <50 meters, 50-199 meters, and more than 200 meters from busy roads, the detection rates were 20.6, 21.2, and 14.8%, respectively; the rates for outdoor activities at these distances were 23.8, 24.5, and 13.7%, respectively (p < 0.05). After adjusting for sex, age, smoking status, family history, and smoking index, the distance of outdoor activities from busy roads was an independent risk factor for COPD. Participants whose outdoor activities were conducted <50 meters and 50-199 meters of main roads had odds ratios of 1.54 (95% confidence interval 1.01-2.36) and 1.84 (95% interval 1.23-2.76) for the risk of COPD in comparison with a distance of more than 200 meters from busy roads.

Conclusions

Residents of Guangzhou whose outdoor activities were close to busy roads had a high risk of COPD. Traffic-related air pollution presents a risk to human health and a risk of COPD.

Sex-Dependent Responses to Maternal Exposure to PM2.5 in the Offspring

Objective: Particulate matter (PM) with a diameter of 2.5 μm or less (PM_2.5) can cross the blood-placental barrier causing adverse foetal outcomes. However, the impact of maternal exposure to low-levels of PM_2.5 on liver health and the metabolic profile is unclear. This study aimed to investigate hepatic responses to long-term gestational low-dose PM_2.5 exposure, and whether the removal of PM after conception can prevent such effects. Method: Female Balb/c mice (8 weeks) were exposed to PM_2.5 (5 μg/day) for 6 weeks prior to mating, during gestation and lactation to model living in a polluted environment (PM group). In a sub-group, PM_2.5 exposure was stopped post-conception to model mothers moving to areas with clean air (pre-gestation, Pre) group. Livers were studied in 13-week old offspring. Results: Female offspring in both PM and Pre groups had increased liver triglyceride and glycogen levels, glucose intolerance, but reduced serum insulin and insulin resistance. Male offspring from only the Pre group had increased liver and serum triglycerides, increased liver glycogen, glucose intolerance and higher fasting glucose level. Markers of oxidative stress and inflammation were increased in females from PM and Pre groups. There was also a significant sex difference in the hepatic response to PM_2.5 with differential changes in several metabolic markers identified by proteomic analysis. Conclusions: Maternal PM exposure exerted sex-dependent effects on liver health with more severe impacts on females. The removal of PM_2.5 during gestation provided limited protection in the offspring’s metabolism regardless of sex.

A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases

Age-related diseases account for almost half of all diseases among adults worldwide, and their incidence is substantially affected by the exposome, which is the sum of all exogenous and endogenous environmental exposures and the human body’s response to these exposures throughout the entire lifespan. Herein, we perform a comprehensive review of the epidemiological literature to determine the key elements of the exposome that affect the development of age-related diseases and the roles of aging hallmarks in this process. We find that most exposure assessments in previous aging studies have used a reductionist approach, whereby the effect of only a single environmental factor or a specific class of environmental factors on the development of age-related diseases has been examined. As such, there is a lack of a holistic and unbiased understanding of the effect of multiple environmental factors on the development of age-related diseases. To address this, we propose several research strategies based on an exposomic framework that could advance our understanding—in particular, from a mechanistic perspective—of how environmental factors affect the development of age-related diseases. We discuss the statistical methods and other methods that have been used in exposome-wide association studies, with a particular focus on multiomics technologies. We also address future challenges and opportunities in the realm of multidisciplinary approaches and genome–exposome epidemiology. Furthermore, we provide perspectives on precise public health services for vulnerable populations, public communications, the integration of risk exposure information, and the bench-to-bedside translation of research on age-related diseases.

Nonlinear associations between environmental factors and lipid levels in middle-aged and elderly population in China: A national cross-sectional study

BACKGROUND

Blood lipid is an important factor affecting cardiovascular disease in middle-aged and elderly people. At present, the associations between environmental factors and blood lipid level in elderly people has been controversial, and the nonlinear effect of their relationship is lack of research.

METHODS

This study used data from a national cross-sectional survey of blood lipid levels in 13,354 subjects and data from environmental monitoring sites. Logistic regression was used to measure the relationship between the basic characteristics of the study population and blood lipid levels. After controlling the confounding factors, the nonlinear associations between environmental factors and blood lipid levels of middle-aged and elderly people in different geographical regions were studied by random forest model.

RESULTS

The risk of dyslipidemia is significantly higher in middle-aged women, obese people, elderly people, and urban people. Smoking and alcohol consumption increase the risk. The associations between environmental factors and lipid levels of middle-aged and elderly people are nonlinear, the correlation effect between air pollutants and blood lipid level is mainly shown in northern China, and the correlation between meteorological factors and blood lipid level is more obvious in southern China.

CONCLUSIONS

This study shows that the associations between environmental factors and lipid levels in middle-aged and elderly population are nonlinear and have regional differences. Therefore it should be considered in optimizing the allocation of public health resources and preventing and controlling environmental exposure of middle-aged and elderly population.

Effects of air pollution on human health - Mechanistic evidence suggested by in vitro and in vivo modelling

Airborne particulate matter (PM) comprises both solid and liquid particles, including carbon, sulphates, nitrate, and toxic heavy metals, which can induce oxidative stress and inflammation after inhalation. These changes occur both in the lung and systemically, due to the ability of the small-sized PM (i.e. diameters ≤2.5 μm, PM_2.5) to enter and circulate in the bloodstream. As such, in 2016, airborne PM caused ∼4.2 million premature deaths worldwide. Acute exposure to high levels of airborne PM (eg. during wildfires) can exacerbate pre-existing illnesses leading to hospitalisation, such as in those with asthma and coronary heart disease. Prolonged exposure to PM can increase the risk of non-communicable chronic diseases affecting the brain, lung, heart, liver, and kidney, although the latter is less well studied. Given the breadth of potential disease, it is critical to understand the mechanisms underlying airborne PM exposure-induced disorders. Establishing aetiology in humans is difficult, therefore, in-vitro and in-vivo studies can provide mechanistic insights. We describe acute health effects (e.g. exacerbations of asthma) and long term health effects such as the induction of chronic inflammatory lung disease, and effects outside the lung (e.g. liver and renal change). We will focus on oxidative stress and inflammation as this is the common mechanism of PM-induced disease, which may be used to develop effective treatments to mitigate the adverse health effect of PM exposure.

Trends in the prevalence and associated factors of prediabetes and diabetes in Bangladesh: Evidence from population-based cross-sectional surveys

AIMS

Diabetes is a major health problem in Bangladesh, but nationally representative studies on its trends and associated factors are scarce to guide policy formulation. Therefore, the study aims to determine trends in the prevalence and associated factors of prediabetes and diabetes in Bangladesh.

METHODS

The study included two population-based cross-sectional surveys from Bangladesh Demographic and Health Survey (n = 7,505 in 2011 and n = 11,959 in 2017-18). Chi-square association tests were performed to determine the associated factors. Logistic regression models (univariate and multivariable) were used to estimate unadjusted and adjusted relative risks of having diabetes, reported with odds ratios. Age-adjusted prevalence was also reported for both surveys.

RESULTS

The overall age-adjusted prevalence of prediabetes and diabetes decreased from 52.77% (95% CI: 52.61-52.92) and 10.43% (95% CI: 10.33-10.53) in 2011 to 34.10% (95% CI: 33.43-34.78) and 8.50% (95% CI: 8.11-8.90) in 2017-18. Compared to males, females had a higher odds of diabetes in 2011, but in 2017-18 a significant inverse result was observed. In both surveys, the odds of prediabetes and diabetes increased with advancing age, obesity, better wealth status, and hypertension.

CONCLUSION

The study shows that the prevalence of prediabetes and diabetes is high in Bangladesh despite decreasing trends. Therefore, the study recommends promoting healthy lifestyles and regular screening for non-communicable diseases.

Indoor and outdoor air pollution and couple fecundability: a systematic review

BACKGROUND

Air pollution is both a sensory blight and a threat to human health. Inhaled environmental pollutants can be naturally occurring or human-made, and include traffic-related air pollution (TRAP), ozone, particulate matter (PM) and volatile organic compounds, among other substances, including those from secondhand smoking. Studies of air pollution on reproductive and endocrine systems have reported associations of TRAP, secondhand smoke (SHS), organic solvents and biomass fueled-cooking with adverse birth outcomes. While some evidence suggests that air pollution contributes to infertility, the extant literature is mixed, and varying effects of pollutants have been reported.

OBJECTIVE AND RATIONALE

Although some reviews have studied the association between common outdoor air pollutants and time to pregnancy (TTP), there are no comprehensive reviews that also include exposure to indoor inhaled pollutants, such as airborne occupational toxicants and SHS. The current systematic review summarizes the strength of evidence for associations of outdoor air pollution, SHS and indoor inhaled air pollution with couple fecundability and identifies gaps and limitations in the literature to inform policy decisions and future research.

SEARCH METHODS

We performed an electronic search of six databases for original research articles in English published since 1990 on TTP or fecundability and a number of chemicals in the context of air pollution, inhalation and aerosolization. Standardized forms for screening, data extraction and study quality were developed using DistillerSR software and completed in duplicate. We used the Newcastle-Ottawa Scale to assess risk of bias and devised additional quality metrics based on specific methodological features of both air pollution and fecundability studies.

OUTCOMES

The search returned 5200 articles, 4994 of which were excluded at the level of title and abstract screening. After full-text screening, 35 papers remained for data extraction and synthesis. An additional 3 papers were identified independently that fit criteria, and 5 papers involving multiple routes of exposure were removed, yielding 33 articles from 28 studies for analysis. There were 8 papers that examined outdoor air quality, while 6 papers examined SHS exposure and 19 papers examined indoor air quality. The results indicated an association between outdoor air pollution and reduced fecundability, including TRAP and specifically nitrogen oxides and PM with a diameter of ≤2.5 µm, as well as exposure to SHS and formaldehyde. However, exposure windows differed greatly between studies as did the method of exposure assessment. There was little evidence that exposure to volatile solvents is associated with reduced fecundability.

WIDER IMPLICATIONS

The evidence suggests that exposure to outdoor air pollutants, SHS and some occupational inhaled pollutants may reduce fecundability. Future studies of SHS should use indoor air monitors and biomarkers to improve exposure assessment. Air monitors that capture real-time exposure can provide valuable insight about the role of indoor air pollution and are helpful in assessing the short-term acute effects of pollutants on TTP.

The Physiological Effects of Air Pollution: Particulate Matter, Physiology and Disease

Nine out of 10 people breathe air that does not meet World Health Organization pollution limits. Air pollutants include gasses and particulate matter and collectively are responsible for ~8 million annual deaths. Particulate matter is the most dangerous form of air pollution, causing inflammatory and oxidative tissue damage. A deeper understanding of the physiological effects of particulate matter is needed for effective disease prevention and treatment. This review will summarize the impact of particulate matter on physiological systems, and where possible will refer to apposite epidemiological and toxicological studies. By discussing a broad cross-section of available data, we hope this review appeals to a wide readership and provides some insight on the impacts of particulate matter on human health.

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2·5 air pollution, 1990-2019: an analysis of data from the Global Burden of Disease Study 2019

BACKGROUND

Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution.

METHODS

We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.

FINDINGS

In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68-4·83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49-17·5) of deaths and 13·6% (9·73-17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22-9·53) of deaths and 5·92% (3·81-8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5.

INTERPRETATION

Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes.

FUNDING

Bill & Melinda Gates Foundation.

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

BACKGROUND

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

Exploring Environmental Health Inequalities: A Scientometric Analysis of Global Research Trends (1970-2020)

Environmental health inequalities (EHI), understood as differences in environmental health factors and in health outcomes caused by environmental conditions, are studied by a wide range of disciplines. This results in challenges to both synthesizing key knowledge domains of the field. This study aims to uncover the global research status and trends in EHI research, and to derive a conceptual framework for the underlying mechanisms of EHI. In total, 12,320 EHI publications were compiled from the Web of Science core collection from 1970 to 2020. Scientometric analysis was adopted to characterize the research activity, distribution, focus, and trends. Content analysis was conducted for the highlight work identified from network analysis. Keyword co-occurrence and cluster analysis were applied to identify the knowledge domain and develop the EHI framework. The results show that there has been a steady increase in numbers of EHI publications, active journals, and involved disciplines, countries, and institutions since the 2000s, with marked differences between countries in the number of published articles and active institutions. In the recent decade, environment-related disciplines have gained importance in addition to social and health sciences. This study proposes a framework to conceptualize the multi-facetted issues in EHI research referring to existing key concepts.

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics

INTRODUCTION

Exposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures.

METHODS

Among the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM_2.5, NO₂, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data.

RESULTS

Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM_2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM_2.5 using dynamic measures. For all participants, higher dynamic exposure to PM_2.5 and NO₂ was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM_2.5 exposure and MetS differed by Hispanic/Latino ethnicity.

CONCLUSION

These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

Air pollution exposure and incidence of type 2 diabetes in women: A prospective analysis from the Mexican Teachers' Cohort

BACKGROUND

Air pollution is a risk factor for type 2 diabetes (T2D). However, scarse longitudinal studies have evaluated this association in low- and middle-income countries, where 80% of the worldwide cases of T2D occur.

OBJECTIVE

Our aim was to estimate the association between PM_2.5 and NO₂ exposure and incident T2D, in the Mexican Teachers' Cohort (MTC).

METHODS

We selected a subsample of female teachers from the MTC from Mexico City metropolitan area (MCMA), recruited in 2008 and with active follow-up every three years. We assigned the monthly time-weighted exposures (PM_2.5 and NO₂) using home and work addresses, until failure, censoring or death. We developed two high resolution (1 × 1-km) spatiotemporal predictive generalized additive models of PM_2.5 and NO₂. Incident diabetes was identified through self-report and two administrative databases of registered diabetes patients. We fitted time-varying Cox models to estimate hazard ratios of the relation between PM_2.5 and NO₂ and incident T2D, adjusting for confounding variables that were identified using a causal model.

RESULTS

A total of 13,669 teachers were followed-up for a maximum of 11.5 years, over which 996 incident T2D cases (88 cases per 100,000 person-months) occurred. Incident T2D increased by 72% (HR = 1.72 [1.47-2.01]) for each 10 μg/m³ increase of PM_2.5, and 52% for each 10 ppb of NO₂ (HR = 1.52 [1.37-1.68]).

DISCUSSION

Mid-term exposure to PM_2.5 and NO₂ was associated with a higher risk of T2D after adjusting for indoor wood smoke, socioeconomic status, and physical activity. These associations were attenuated in two-pollutant models but remained positive when evaluated long-term exposure. This is the first prospective study to evaluate T2D risk by exposure to both pollutants, PM_2.5 and NO₂ in a population from an upper middle-income country in the Americas.

Evaluation of tree-based statistical learning methods for constructing genetic risk scores

Background

Genetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized extensions. However, these linear methods are usually not able to incorporate gene-gene interactions or non-linear SNP-response relationships. Tree-based statistical learning methods such as random forests and logic regression may be an alternative to such regularized-regression-based methods and are investigated in this article. Moreover, we consider modifications of random forests and logic regression for the construction of GRS.

Results

In an extensive simulation study and an application to a real data set from a German cohort study, we show that both tree-based approaches can outperform elastic net when constructing GRS for binary traits. Especially a modification of logic regression called logic bagging could induce comparatively high predictive power as measured by the area under the curve and the statistical power. Even when considering no epistatic interaction effects but only marginal genetic effects, the regularized regression method lead in most cases to inferior results.

Conclusions

When constructing GRS, we recommend taking random forests and logic bagging into account, in particular, if it can be assumed that possibly unknown epistasis between SNPs is present. To develop the best possible prediction models, extensive joint hyperparameter optimizations should be conducted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04634-w.

Physical Exercise in the Context of Air Pollution: An Emerging Research Topic

Physical exercise (PE) brings physiological benefits to human health; paradoxically, exposure to air pollution (AP) is harmful. Hence, the combined effects of AP and PE are interesting issues worth exploring. The objective of this study is to review literature involved in AP-PE fields to perform a knowledge-map analysis and explore the collaborations, current hotspots, physiological applications, and future perspectives. Herein, cluster, co-citation, and co-occurrence analysis were applied using CiteSpace and VOSviewer software. The results demonstrated that AP-PE domains have been springing up and in rapid growth since the 21st century. Subsequently, active countries and institutions were identified, and the productive institutions were mainly located in USA, China, UK, Spain, and Canada. Developed countries seemed to be the major promoters. Additionally, subject analysis found that environmental science, public health, and sports medicine were the core subjects, and multidimensional communications were forming. Thereafter, a holistic presentation of reference co-citation clusters was conducted to discover the research topics and trace the development focuses. Youth, elite athletes, and rural population were regarded as the noteworthy subjects. Commuter exposure and moderate aerobic exercise represented the common research context and exercise strategy, respectively. Simultaneously, the research hotspots and application fields were elaborated by keyword co-occurrence distribution. It was noted that physiological adaptations including respiratory, cardiovascular, metabolic, and mental health were the major themes; oxidative stress and inflammatory response were the mostly referred mechanisms. Finally, several challenges were proposed, which are beneficial to promote the development of the research field. Molecular mechanisms and specific pathways are still unknown and the equilibrium points and dose-effect relationships remain to be further explored. We are highly confident that this study provides a unique perspective to systematically and comprehensively review the pieces of AP-PE research and its related physiological mechanisms for future investigations.

Sex Difference and Benzene Exposure: Does It Matter?

Sex-related biological differences might lead to different effects in women and men when they are exposed to risk factors. A scoping review was carried out to understand if sex could be a discriminant in health outcomes due to benzene. Studies on both animals and humans were collected. In vivo surveys, focusing on genotoxicity, hematotoxicity and effects on metabolism suggested a higher involvement of male animals (mice or rats) in adverse health effects. Conversely, the studies on humans, focused on the alteration of blood parameters, myeloid leukemia incidence and biomarker rates, highlighted that, overall, women had significantly higher risk for blood system effects and a metabolization of benzene 23-26% higher than men, considering a similar exposure situation. This opposite trend highlights that the extrapolation of in vivo findings to human risk assessment should be taken with caution. However, it is clear that sex is a physiological parameter to consider in benzene exposure and its health effects. The topic of sex difference linked to benzene in human exposure needs further research, with more numerous samples, to obtain a higher strength of data and more indicative findings. Sex factor, and gender, could have significant impacts on occupational exposures and their health effects, even if there are still uncertainties and gaps that need to be filled.

In-line measurement of exhaust mercury emissions by an instrumented light-duty vehicle using both on-road and test track experiments

The initial purpose of this study has been to develop an instrumental platform for monitoring mercury (Hg) emissions from vehicle exhausts under actual traffic conditions. The platform was then mounted onto a fully-instrumented passenger car to identify emission proxies and factors governing the emissions of gaseous elemental Hg (GeM) and its complementary fraction (GdPM). Data obtained from the road were complemented by data acquired on a test track at either stabilized speeds or well-characterized speed variations. GeM emissions increased overall with both driving speed and fuel consumption; nonetheless, they were influenced by the sequence of accelerations and duration associated with the preceding idling or low-speed driving situations. GdPM emissions varied considerably over the course of trips or track tests, with medians ranging from 7% to 70% of the total Hg emissions stemming from fuel. Such high percentages could be explained by a series of redox reactions, whose kinetics and yield were influenced as much by exhaust gas temperature as by driving conditions or the exhaust system structural configuration. Lastly, an analysis of the GeM and GdPM signals showed that urban cores constitute emission hotspots during rush hour when handling low-speed driving and stop-and-go traffic.

Urban Neighbourhood Environments, Cardiometabolic Health and Cognitive Function: A National Cross-Sectional Study of Middle-Aged and Older Adults in Australia

Population ageing and urbanisation are global phenomena that call for an understanding of the impacts of features of the urban environment on older adults' cognitive function. Because neighbourhood characteristics that can potentially have opposite effects on cognitive function are interdependent, they need to be considered in conjunction. Using data from an Australian national sample of 4141 adult urban dwellers, we examined the extent to which the associations of interrelated built and natural environment features and ambient air pollution with cognitive function are explained by cardiometabolic risk factors relevant to cognitive health. All examined environmental features were directly and/or indirectly related to cognitive function via other environmental features and/or cardiometabolic risk factors. Findings suggest that dense, interconnected urban environments with access to parks, blue spaces and low levels of air pollution may benefit cognitive health through cardiometabolic risk factors and other mechanisms not captured in this study. This study also highlights the need for a particularly fine-grained characterisation of the built environment in research on cognitive function, which would enable the differentiation of the positive effects of destination-rich neighbourhoods on cognition via participation in cognition-enhancing activities from the negative effects of air pollutants typically present in dense, destination-rich urban areas.

Environmental Factors as Diabetic Mediators: A Mechanistic Approach

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

Serum branched-chain amino acids modifies the associations between air pollutants and insulin resistance

Growing evidence supports that air pollution exposure has become a risk factor of type II diabetes mellitus through the induction of insulin resistance (IR), but the presented findings did not provide a consistent relationship between air pollution exposure and IR in the temporal scale and the magnitude. Reported associated with IR and air pollution exposure, branched-chain amino acids (BCAAs) in blood might modify the association between air pollution exposure and IR. We took advantage of an existing panel study on elderly people who were healthy or with pre-diabetes. Amino acids were analyzed from the serum samples using a UPLC-QQQ-MS, and the homeostasis model assessment of insulin resistance (HOMA-IR) values were calculated to represent the levels of IR in each visit. Exposures to PM_2.5, NO₂, SO₂, CO, O₃, and black carbon (BC) were estimated using data from a monitoring station. Linear mixed-effects models were applied to estimate the associations between the air pollution and HOMA-IR, as well as the modifying effects of BCAAs. We found significantly higher concentrations of BCAAs in the pre-diabetic subjects than healthy ones. The concentrations of BCAAs were all significantly associated with HOMA-IR. For subjects with high-level BCAAs, HOMA-IR was positively associated with an IQR increase in PM_2.5, NO₂, BC, and CO at lag day 2 and in PM_2.5, SO₂, NO₂, BC, and CO at lag day 7. While for subjects with low-level BCAAs, there was no significant association observed at any lag day except for CO at lag day 5. The study provided evidence that circulating BCAAs may modify the relationship between air pollution exposure and the level of insulin resistance in humans.

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.

Effect of COVID-19-restrictive measures on ambient particulate matter pollution in Yangon, Myanmar

Background

Particulate matter (PM) is recognized as the most harmful air pollutant to the human health. The Yangon city indeed suffers much from PM-related air pollution. Recent research has interestingly been focused on the novel subject of changes in the air quality associated with the restrictive measures in place during the current coronavirus disease-2019 (COVID-19) pandemic. The first case of COVID-19 in Myanmar was diagnosed on March 23, 2020. In this article, we report on our attempt to evaluate any effects of the COVID-19-restrictive measures on the ambient PM pollution in Yangon.

Methods

We measured the PM concentrations every second for 1 week on four occasions at three study sites with different characteristics; the first occasion was before the start of the COVID-19 pandemic and the remaining three occasions were while the COVID-19-restrictive measures were in place, including Stay-At-Home and Work-From-Home orders. The Pocket PM_2.5 Sensor [PRO] designed by the National Institute for Environmental Studies (NIES), Japan, in cooperation with Yaguchi Electric Co., Ltd., (Miyagi, Japan) was used for the measurement of the ambient PM_2.5 and PM₁₀ concentrations.

Results

The results showed that there was a significant reduction (P < 0.001) in both the PM_2.5 and PM₁₀ concentrations while the COVID-19-restrictive measures were in place as compared to the measured values prior to the pandemic. The city experienced a profound improvement in the PM-related air quality from the “unhealthy” category prior to the onset of the COVID-19 pandemic to the “good” category during the pandemic, when the restrictive measures were in place. The percent changes in the PM concentrations varied among the three study sites, with the highest percent reduction noted in a semi-commercial crowded area (84.8% for PM_2.5; 88.6% for PM₁₀) and the lowest percent reduction noted in a residential quiet area (15.6% for PM_2.5; 12.0% for PM₁₀); the percent reductions also varied among the different occasions during the COVID-19 pandemic that the measurements were made.

Conclusions

We concluded that the restrictive measures which were in effect to combat the COVID-19 pandemic had a positive impact on the ambient PM concentrations. The changes in the PM concentrations are considered to be largely attributable to reduction in anthropogenic emissions as a result of the restrictive measures, although seasonal influences could also have contributed in part. Thus, frequent, once- or twice-weekly Stay-At-Home or Telework campaigns, may be feasible measures to reduce PM-related air pollution. When devising such an action plan, it would be essential to raise the awareness of public about the health risks associated with air pollution and create a social environment in which Telework can be carried out, in order to ensure active compliance by the citizens.

Lycopene ameliorates insulin resistance and increases muscle capillary density in aging via activation of SIRT1

Lycopene (Ly) is a kind of hydrocarbon, which belongs to the family of tetraterpene carotene and exists in red fruits and vegetables. The decrease of capillary density and blood flow with age is a significant reason for the increase of mortality and morbidity. Herein, our study aims to explore the effects of Ly (a bioactive food compound) on vascular aging in vitro and in vivo and its potential mechanisms. The cytological results showed that Ly could promote the proliferation of human umbilical vein endothelial cell (HUVECs) and enhance the ability of HUVECs to form capillary-like structures. Furthermore, the expression of SIRT1 in aged HUVECs was up-regulated. In vivo, aging rats showed signs of insulin resistance and blood vessel damage. Additionally, the capillary density and blood flow were reduced during the vascular aging process in both D-gal-induced and naturally aging muscle. However, when Ly was given, these conditions could be reversed. Simultaneously, the contents of ATP, lactic acid and pyruvic acid were determined, and it was found that Ly could promote angiogenesis by increasing the utilization rate of glucose and promoting energy metabolism. Finally, in the insulin resistance cell model, we knocked down the SIRT1 and administrated with Ly, and found that it couldn't restore insulin transdution. In conclusion, all the data in this study demonstrate that Ly could reactivate SIRT1 and improve insulin resistance, which was a reversible cause of vascular aging.

Ozone Exposure, Outdoor Physical Activity, and Incident Type 2 Diabetes in the SALSA Cohort of Older Mexican Americans

BACKGROUND

Type 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes.

OBJECTIVE

We studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association.

METHODS

We selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O3 exposure and diabetes.

RESULTS

In total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [hazard ratio (HR)=0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O3 exposure; also, this association was stronger among those physically active outdoors [HR=1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [HR=1.04 (95% CI: 0.90, 1.20), pinteraction=0.01].

CONCLUSIONS

Our findings suggest that ambient O3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.

Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

BACKGROUND

Air pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship.

METHODS AND FINDINGS

A total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m2. Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM2.5), between 2.5 μm and 10 μm (PM2.5-10), nitrogen dioxide (NO2), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants.

CONCLUSIONS

We found that various air pollutants PM2.5, PM2.5-10, NO2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

Design of a Spark Big Data Framework for PM2.5 Air Pollution Forecasting

In recent years, with rapid economic development, air pollution has become extremely serious, causing many negative effects on health, environment and medical costs. PM_2.5 is one of the main components of air pollution. Therefore, it is necessary to know the PM_2.5 air quality in advance for health. Many studies on air quality are based on the government’s official air quality monitoring stations, which cannot be widely deployed due to high cost constraints. Furthermore, the update frequency of government monitoring stations is once an hour, and it is hard to capture short-term PM_2.5 concentration peaks with little warning. Nevertheless, dealing with short-term data with many stations, the volume of data is huge and is calculated, analyzed and predicted in a complex way. This alleviates the high computational requirements of the original predictor, thus making Spark suitable for the considered problem. This study proposes a PM_2.5 instant prediction architecture based on the Spark big data framework to handle the huge data from the LASS community. The Spark big data framework proposed in this study is divided into three modules. It collects real time PM_2.5 data and performs ensemble learning through three machine learning algorithms (Linear Regression, Random Forest, Gradient Boosting Decision Tree) to predict the PM_2.5 concentration value in the next 30 to 180 min with accompanying visualization graph. The experimental results show that our proposed Spark big data ensemble prediction model in next 30-min prediction has the best performance (R² up to 0.96), and the ensemble model has better performance than any single machine learning model. Taiwan has been suffering from a situation of relatively poor air pollution quality for a long time. Air pollutant monitoring data from LASS community can provide a wide broader monitoring, however the data is large and difficult to integrate or analyze. The proposed Spark big data framework system can provide short-term PM_2.5 forecasts and help the decision-maker to take proper action immediately.

Particulate matter air pollutants and cardiovascular disease: Strategies for intervention

Air pollution is consistently linked with elevations in cardiovascular disease (CVD) and CVD-related mortality. Particulate matter (PM) is a critical factor in air pollution-associated CVD. PM forms in the air during the combustion of fuels as solid particles and liquid droplets and the sources of airborne PM range from dust and dirt to soot and smoke. The health impacts of PM inhalation are well documented. In the US, where CVD is already the leading cause of death, it is estimated that PM2.5 (PM < 2.5 μm in size) is responsible for nearly 200,000 premature deaths annually. Despite the public health data, definitive mechanisms underlying PM-associated CVD are elusive. However, evidence to-date implicates mechanisms involving oxidative stress, inflammation, metabolic dysfunction and dyslipidemia, contributing to vascular dysfunction and atherosclerosis, along with autonomic dysfunction and hypertension. For the benefit of susceptible individuals and individuals who live in areas where PM levels exceed the National Ambient Air Quality Standard, interventional strategies for mitigating PM-associated CVD are necessary. This review will highlight current state of knowledge with respect to mechanisms for PM-dependent CVD. Based upon these mechanisms, strategies for intervention will be outlined. Citing data from animal models and human subjects, these highlighted strategies include: 1) antioxidants, such as vitamins E and C, carnosine, sulforaphane and resveratrol, to reduce oxidative stress and systemic inflammation; 2) omega-3 fatty acids, to inhibit inflammation and autonomic dysfunction; 3) statins, to decrease cholesterol accumulation and inflammation; 4) melatonin, to regulate the immune-pineal axis and 5) metformin, to address PM-associated metabolic dysfunction. Each of these will be discussed with respect to its potential role in limiting PM-associated CVD.

Personal exposures to traffic-related air pollution in three Canadian bus transit systems: the Urban Transportation Exposure Study

BACKGROUND

Exposure to traffic-related air pollution (TRAP) is associated with increased incidence of several cardiopulmonary diseases. The elevated TRAP exposures of commuting environments can result in significant contributions to daily exposures.

OBJECTIVES

To assess the personal TRAP exposures (UFPs, BC, PM_2.5, and PM₁₀) of the bus transit systems of Toronto, Ottawa, and Vancouver, Canada. Personal exposure models estimated the contribution of bus commuting to daily TRAP exposures. Associations between bus type and riding exposures and bus stop/station type and waiting exposures were estimated.

RESULTS

Bus commuting (4.6% of the day) contributed ~59%(SD = 15%), 60%(SD = 20%), and 57%(SD = 18%) of daily PM_2.5-Ba and 70%(SD = 19%), 64%(SD = 15%), and 70%(SD = 15%) of daily PM_2.5-Fe, in Toronto, Ottawa, and Vancouver, respectively. Enclosed bus stations were found to be hotspots of PM_2.5 and BC. Buses with diesel particulate filters (DPFs) and hybrid diesel/electric propulsion were found to have significantly lower in-bus PM_2.5, UFP, and BC relative to 1983-2003 diesel buses in each city with the exception of UFP in Vancouver.

SIGNIFICANCE

Personal exposures for traffic-related air pollutants were assessed for three Canadian bus transit systems. In each system, bus commuting was estimated to contribute significantly toward daily exposures of fine-fraction Ba and Fe as well as BC. Exposures while riding were associated with bus type for several pollutants in each city. These associations suggest the use of hybrid diesel/electric buses equipped with diesel particulate filters have improved air quality for riders.

Exposure to heavy metals from point pollution sources and risk of incident type 2 diabetes among women: a prospective cohort analysis

Heavy metal exposures may contribute to diabetes risk but prospective studies are uncommon. We analyzed the Australian Longitudinal Study on Women's Health (three cohorts aged 18-23, 45-50, or 70-75 at baseline in 1996, N = 34,191) merged with emissions data for 10 heavy metals (As, Be, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) from the National Pollutant Inventory. Over 20-year follow-up, 2,584 women (7.6%) reported incident diabetes. Cox proportional hazards regression models showed that women aged 45-50 at baseline had higher diabetes risk in association with exposure to total air emissions, total water emissions, all individual metals air emissions, and six individual water emissions. After correction for false discovery rate, nine of 11 air emissions and five water emissions remained significant. Associations were not observed for land-based emissions, or for younger or older cohorts. Emissions were dominated by mining, electricity generation and other metals-related industrial processes.

Particulate Matter, an Intrauterine Toxin Affecting Foetal Development and Beyond

Air pollution is the 9th cause of the overall disease burden globally. The solid component in the polluted air, particulate matters (PMs) with a diameter of 2.5 μm or smaller (PM_2.5) possess a significant health risk to several organ systems. PM_2.5 has also been shown to cross the blood–placental barrier and circulate in foetal blood. Therefore, it is considered an intrauterine environmental toxin. Exposure to PM_2.5 during the perinatal period, when the foetus is particularly susceptible to developmental defects, has been shown to reduce birth weight and cause preterm birth, with an increase in adult disease susceptibility in the offspring. However, few studies have thoroughly studied the health outcome of foetuses due to intrauterine exposure and the underlying mechanisms. This perspective summarises currently available evidence, which suggests that intrauterine exposure to PM_2.5 promotes oxidative stress and inflammation in a similar manner as occurs in response to direct PM exposure. Oxidative stress and inflammation are likely to be the common mechanisms underlying the dysfunction of multiple systems, offering potential targets for preventative strategies in pregnant mothers for an optimal foetal outcome.

Associations between air pollution indicators and prevalent and incident diabetes in an African American cohort, the Jackson Heart Study

Background

Diabetes is especially prevalent among African Americans. Prior studies suggest that long-term exposure to ambient air pollution may be associated with greater incidence of diabetes, but results remain heterogeneous. Few studies have included large numbers of African Americans.

Methods

We assessed diabetes status and concentrations of 1- and 3-year fine particulate matter (PM_2.5) and ozone (O₃) among African American participants of the Jackson Heart Study at visits 1 (2000-2004, N = 5128) and 2 (2005-2008, N = 2839). We used mixed-effect modified Poisson regression to estimate risk ratios (RRs) and 95% confidence intervals (CIs) of incidence of diabetes by visit 2 and prevalence ratios (PRs) of the association between air pollution exposure and prevalent diabetes at visits 1 and 2. We adjusted for potential confounding by patient characteristics, as well as inverse probability weights of diabetes at visit 2, accounting for clustering by census tract.

Results

We observed associations between incident diabetes and interquartile range increase in 1-year O₃ (RR 1.34, 95% CI = 1.11, 1.61) and 3-year O₃ (RR 0.88, 95% CI = 0.76, 1.02). We observed associations between prevalent diabetes and 1-year PM_2.5 (PR 1.08, 95% CI = 1.00, 1.17), 1-year O₃ (PR 1.18, 95% CI = 1.10, 1.27), and 3-year O₃ (PR 0.95, 95% CI = 0.90, 1.01) at visit 2.

Conclusions

Our results provide some evidence of positive associations between indicators of long-term PM_2.5 and O₃ exposure and diabetes. This study is particularly relevant to African Americans, who have higher prevalence of diabetes but relatively few studies of environmental pollution risk factors.

Racial Difference in the Association of Long-Term Exposure to Fine Particulate Matter (PM2.5) and Cardiovascular Disease Mortality among Renal Transplant Recipients

Ambient air pollutants are known risk factors for cardiovascular disease (CVD) morbidity and mortality with significant racial disparities. However, few studies have explored racial differences among highly susceptible subpopulations, such as renal transplant recipients (RTRs). Despite improvements in quality of life after transplantation, CVD remains the major cause of mortality, especially among Black recipients. This study aimed to evaluate potential racial differences in the association between long-term levels of PM2.5 and the risk of all-cause, total CVD, and coronary heart disease (CHD) mortality among RTRs. This retrospective study consists of 93,857 non-smoking adults who received a renal transplant between 2001 and 2015. Time-dependent Cox regression was used to assess the association between annual concentrations of PM2.5 and mortality risk. In the multivariable-adjusted models, a 10 μg/m3 increase in ambient PM2.5 levels found increased risk of all-cause (HR = 3.45, 95% CI: 3.08-3.78), CVD (HR = 2.38, 95% CI: 1.94-2.92), and CHD mortality (HR = 3.10, 95% CI: 1.96-4.90). Black recipients had higher risks of all-cause (HR = 4.09, 95% CI: 3.43-4.88) and CHD mortality (HR = 6.73, 95% CI: 2.96-15.32). High levels of ambient PM2.5 were associated with all-cause, CVD, and CHD mortality. The association tended to be higher among Black recipients than non-Blacks.