Air pollution and occurrence of type 2 diabetes in a large cohort study

Outdoor light at night, air pollution and risk of incident type 2 diabetes

BACKGROUND

Air pollution and outdoor light at night (LAN) have been reported to be related to type 2 diabetes (T2D). However, their interaction with risk of T2D remains uncertain. Therefore, our study aimed to explore the relationship between outdoor LAN, air pollution and incident T2D.

METHODS

Our study included a cohort of 24,147 subjects recruited from 2015 to 2018 in Ningbo, China. Land use regression models were used to evaluate particulate matter with a diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2). Satellite images data with a spatial resolution of 500m was used to estimate outdoor LAN levels. T2D new cases were identified by medical records based on health information system. Cox proportional hazards models were used to estimate Hazard ratios (HRs) and 95% confidence intervals (CIs). Moreover, we investigated the multiplicative and additive interactions between air pollution and outdoor LAN.

RESULTS

During 108,908 person-years of follow-up period, 1016 T2D incident cases were identified. The HRs (95% CIs) were 1.22 (1.15, 1.30) for outdoor LAN, 1.20 (1.00, 1.45) for PM2.5, 1.23 (1.11, 1.35) for PM10 and 1.19 (1.04, 1.37) for NO2 in every interquartile range increase, respectively. Furthermore, significant interactions were observed between outdoor LAN and NO2.

CONCLUSIONS

Our findings indicated that air pollution and outdoor LAN were positively associated with T2D. Moreover, we observed an interaction between outdoor LAN and NO2 suggesting that stronger associations for outdoor LAN and T2D in areas with higher levels of NO2, and for NO2 and T2D in areas with higher levels of outdoor LAN.

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.

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

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

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

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

Long-term PM2.5 exposure and early-onset diabetes: Does BMI link this risk?

OBJECTIVE

Limited studies investigated the association between high-level fine particulate matter (PM2.5) pollution and early-onset diabetes, leaving the possible metabolic mechanisms unclear. We assessed the association of cumulative PM2.5 exposure with diabetes, including early-onset, in high-pollution areas of China and explored whether metabolic factors mediated this association.

METHODS

124,204 participants (≥18 years) from 121 counties in Hunan province, China, were enrolled between 2005 and 2020, with follow-up until 2021. The ground-level air pollution concentrations at each participant's residence were calculated using a high-quality dataset in China. The independent association of PM2.5 with incident diabetes and early-onset diabetes was assessed by Cox proportional hazards models. Restricted cubic splines were utilized to establish the exposure-response relationships. The role of metabolism-related mediators was estimated by mediation analysis.

RESULTS

During a median follow-up of 8.47 (IQR, 6.65-9.82) years, there were 3650 patients with new-onset diabetes. Each 1 μg/m3 increase in the level of cumulative PM2.5 exposure was positively related to an increased incidence of diabetes (HR 1.177, 95 % CI 1.172-1.181) among individuals in the PM2.5 > 50 μg/m3 group after adjusting for multiple variables. The relationship of the PM2.5 dose-response curve for diabetes was non-linear. Significant associations between PM2.5 exposure and early-onset diabetes risk were observed, with this risk showing an increase with the earlier age of early diabetes onset. Males, young individuals (≤45 years), and those with a lower body mass index (BMI <24 kg/m2) appeared to be more susceptible to diabetes. Moreover, change in BMI significantly mediated 31.06 % of the PM2.5-diabetes relationship.

CONCLUSIONS

Long-term cumulative PM2.5 exposure increased the risk of early-onset diabetes, which is partially mediated by BMI. Sustained air pollution control measures, priority protection of vulnerable individuals, and effective management of BMI should be taken to reduce the burden of diabetes.

Identifying interactions among air pollutant emissions on diabetes prevalence in Northeast China using a complex network

BACKGROUND

Low air quality related to ambient air pollution is the largest environmental risk to health worldwide. Interactions between air pollution emissions may affect associations between air pollution exposure and chronic diseases. Therefore, this study aimed to quantify interactions among air pollution emissions and assess their effects on the association between air pollution and diabetes.

METHODS

After constructing long-term emission networks for six air pollutants based on data collected from routine monitoring stations in Northeast China, a mutual information network was used to quantify interactions among air pollution emissions. Multiple linear regression analysis was then used to explore the influence of emission interactions on the association between air pollution exposure and the prevalence of diabetes based on data reported from the Northeast Natural Cohort Study in China.

RESULTS

Complex network analysis detected three major emission sources in Northeast China located in Shenyang and Changchun. The effects of particulate matter (PM2.5 and PM10) and ground-level ozone (O3) emissions were limited to certain communities but could spread to other communities through emissions in Inner Mongolia. Emissions of sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) significantly influenced other communities. These results indicated that air pollutants in different geographic areas can interact directly or indirectly. Adjusting for interactions between emissions changed associations between air pollution emissions and diabetes prevalence, especially for PM2.5, NO2, and CO.

CONCLUSIONS

Complex network analysis is suitable for quantifying interactions among air pollution emissions and suggests that the effects of PM2.5 and NO2 emissions on health outcomes may have been overestimated in previous population studies while those of CO may have been underestimated. Further studies examining associations between air pollution and chronic diseases should consider controlling for the effects of interactions among pollution emissions.

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.

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

The Influence of Airborne Particulate Matter on the Risk of Gestational Diabetes Mellitus: A Large Retrospective Study in Chongqing, China

Emerging research findings suggest that airborne particulate matter might be a risk factor for gestational diabetes mellitus (GDM). However, the concentration-response relationships and the susceptible time windows for different types of particulate matter may vary. In this retrospective analysis, we employ a novel robust approach to assess the crucial time windows regarding the prevalence of GDM and to distinguish the susceptibility of three GDM subtypes to air pollution exposure. This study included 16,303 pregnant women who received routine antenatal care in 2018-2021 at the Maternal and Child Health Hospital in Chongqing, China. In total, 2482 women (15.2%) were diagnosed with GDM. We assessed the individual daily average exposure to air pollution, including PM2.5, PM10, O3, NO2, SO2, and CO based on the volunteers' addresses. We used high-accuracy gridded air pollution data generated by machine learning models to assess particulate matter per maternal exposure levels. We further analyzed the association of pre-pregnancy, early, and mid-pregnancy exposure to environmental pollutants using a generalized additive model (GAM) and distributed lag nonlinear models (DLNMs) to analyze the association between exposure at specific gestational weeks and the risk of GDM. We observed that, during the first trimester, per IQR increases for PM10 and PM2.5 exposure were associated with increased GDM risk (PM10: OR = 1.19, 95%CI: 1.07~1.33; PM2.5: OR = 1.32, 95%CI: 1.15~1.50) and isolated post-load hyperglycemia (GDM-IPH) risk (PM10: OR = 1.23, 95%CI: 1.09~1.39; PM2.5: OR = 1.38, 95%CI: 1.18~1.61). Second-trimester O3 exposure was positively correlated with the associated risk of GDM, while pre-pregnancy and first-trimester exposure was negatively associated with the risk of GDM-IPH. Exposure to SO2 in the second trimester was negatively associated with the risk of GDM-IPH. However, there were no observed associations between NO2 and CO exposure and the risk of GDM and its subgroups. Our results suggest that maternal exposure to particulate matter during early pregnancy and exposure to O3 in the second trimester might increase the risk of GDM, and GDM-IPH is the susceptible GDM subtype to airborne particulate matter 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.

In-vehicle exposure to NO2 and PM2.5: A comprehensive assessment of controlling parameters and reduction strategies to minimise personal exposure

Vehicles are the third most occupied microenvironment, other than home and workplace, in developed urban areas. Vehicle cabins are confined spaces where occupants can mitigate their exposure to on-road nitrogen dioxide (NO2) and fine particulate matter (PM2.5) concentrations. Understanding which parameters exert the greatest influence on in-vehicle exposure underpins advice to drivers and vehicle occupants in general. This study assessed the in-vehicle NO2 and PM2.5 levels and developed stepwise general additive mixed models (sGAMM) to investigate comprehensively the combined and individual influences of factors that influence the in-vehicle exposures. The mean in-vehicle levels were 19 ± 18 and 6.4 ± 2.7 μg/m3 for NO2 and PM2.5, respectively. sGAMM model identified significant factors explaining a large fraction of in-vehicle NO2 and PM2.5 variability, R2 = 0.645 and 0.723, respectively. From the model's explained variability on-road air pollution was the most important predictor accounting for 22.3 and 30 % of NO2 and PM2.5 variability, respectively. Vehicle-based predictors included manufacturing year, cabin size, odometer reading, type of cabin filter, ventilation fan speed power, window setting, and use of air recirculation, and together explained 48.7 % and 61.3 % of NO2 and PM2.5 variability, respectively, with 41.4 % and 51.9 %, related to ventilation preference and type of filtration media, respectively. Driving-based parameters included driving speed, traffic conditions, traffic lights, roundabouts, and following high emitters and accounted for 22 and 7.4 % of in-vehicle NO2 and PM2.5 exposure variability, respectively. Vehicle occupants can significantly reduce their in-vehicle exposure by moderating vehicle ventilation settings and by choosing an appropriate cabin air filter.

Analysis of severe ozone-related human health and weather influence over China in 2019 based on a high-resolution dataset

Ozone pollution in 2019 in China is particularly severe posing a tremendous threat to the health of Chinese inhabitants. In this study, we constructed a more reliable and accurate 1-km gridded dataset for 2019 with as many sites as possible using the inverse distance weight interpolation method to analyze spatiotemporal ozone pollution characteristics and health burden attributed to ozone exposure from the perspective of different diseases and weather influence. The accuracy of this new dataset is higher than other public datasets, with the coefficient of determination of 0.84 and root-mean-square error of 8.77 ppb through the validation of 300 external sites which were never used for establishing retrieval methods by the datasets mentioned-above. The averaged MDA8 (the daily maximum 8 h average) ozone concentrations over China was 43.5 ppb, and during April-July, 83.9% of total grids occurred peak-month ozone concentrations. Overall, the highest averaged exceedance days (60 days) and population-weighted ozone concentrations (55.0 ppb) both concentrated in central-eastern China including 9 provinces (only 11.4% of the national territory); meanwhile, all-cause premature deaths attributable to ozone exposure reached up to 142,000 (54.9% of national total deaths) with higher deaths for cardiovascular and respiratory, and the provincial per capita premature mortality was 0.27~0.44‰. The six most polluted weather types in the central-eastern China are in order as follows: westerly (SW and W), cyclonic, northerly, and southerly (NW, N, and S) types, which accounts for approximately 73.2% of health burden attributed to daily ozone exposure and poses the greatest public health risk with mean daily premature deaths ranging from 466 to 610. Our findings could provide an effective support for regional ozone pollution control and public health management in China.

Risk of type 2 diabetes after diagnosed gestational diabetes is enhanced by exposure to PM2.5

BACKGROUND

Air pollution and gestational diabetes mellitus (GDM) are both associated with increased diabetes mellitus (DM) occurrence. However, whether air pollutants modify the effects of GDM on the occurrence of DM has been unknown. This study aims to determine whether the effect of GDM on DM development can be modified by exposure to ambient air pollutants.

METHODS

Women with one singleton birth delivery during 2004-14 according to the Taiwan Birth Certificate Database (TBCD) were included as the study cohort. Those newly diagnosed as having DM 1 year or later after childbirth were identified as DM cases. Controls were selected among women without DM diagnosis during follow-up. Personal residence was geocoded and linked with interpolated concentrations of air pollutants into township levels. Conditional logistic regression was used to determine the odds ratio (OR) of pollutant exposure and GDM, adjusting for age, smoking and meteorological variables.

RESULTS

There were 9846 women who were newly diagnosed as having DM over a mean follow-up period of 10.2 years. We involved them and the 10-fold matching controls involved in our final analysis. The OR (odds ratio) (95% confidence interval, 95% CI) of DM occurrence per interquartile range increased in particulate matter (PM) smaller than or equal to 2.5 µm (PM2.5) and ozone (O3) was 1.31 (1.22-1.41) and 1.20 (1.16-1.25), respectively. The effects of PM exposure on DM development were significantly higher in the GDM group (OR: 2.46, 95% CI: 1.84-3.30) than in the non-GDM group (OR: 1.30, 95% CI: 1.21-1.40).

CONCLUSIONS

Exposure to high levels of PM2.5 and O3 elevates the risk of DM. GDM acted synergistically in DM development with exposure to PM2.5 but not with that to O3.

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

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

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

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

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

BACKGROUND

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

OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSION

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

Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 μg/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 ≤ 36 ppb, PM2.5 ≤ 8.2 μg/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.

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.

Long-term air pollution exposure and diabetes risk in American older adults: A national secondary data-based cohort study

Type 2 diabetes is a major public health concern. Several studies have found an increased diabetes risk associated with long-term air pollution exposure. However, most current studies are limited in their generalizability, exposure assessment, or the ability to differentiate incidence and prevalence cases. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk. We included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264, 869, 458 person-years). We obtained annual estimates of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and warm-months ozone (O₃) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period. We identified 10, 024, 879 diabetes cases of 41, 780, 637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 μg/m³ increase in PM_2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO₂, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O₃. Both for NO₂ and PM_2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO₂ ≤ 36 ppb, PM_2.5 ≤ 8.2 μg/m³). Furthermore, associations remained in the restricted low-level cohorts. The O₃-diabetes exposure-response relationship differed greatly between models and require further investigation. In conclusion, exposures to PM_2.5 and NO₂ are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.

NO2 levels inside vehicle cabins with pollen and activated carbon filters: A real world targeted intervention to estimate NO2 exposure reduction potential

Traffic related nitrogen dioxide (NO₂) poses a serious environmental and health risk factor in the urban environment. Drivers and vehicle occupants in general may have acute exposure to NO₂ levels. In order to identify key controllable measures to reduce vehicle occupant's exposure, this study measures NO₂ exposure inside ten different vehicles under real world driving conditions and applies a targeted intervention by replacing previously used filters with new standard pollen and new activated carbon cabin filters. The study also evaluates the efficiency of the latter as a function of duration of use. The mean in-vehicle NO₂ exposure across the tested vehicles, driving the same route under comparable traffic and ambient air quality conditions, was 50.8 ± 32.7 μg/m³ for the new standard pollen filter tests and 9.2 ± 8.6 μg/m³ for the new activated carbon filter tests. When implementing the new activated carbon filters, overall we observed significant (p < 0.05) reductions by 87 % on average (range 80 - 94.2 %) in the in-vehicle NO₂ levels compared to the on-road concentrations. We further found that the activated carbon filter NO₂ removal efficiency drops by 6.8 ± 0.6 % per month; showing a faster decay in removal efficiency after the first 6 months of use. These results offer novel insights into how the general population can control and reduce their exposure to traffic related NO₂. The use and regular replacement of activated carbon cabin air filters represents a relatively inexpensive method to significantly reduce in-vehicle NO₂ exposure.

Plasma microRNA expression profiles associated with zinc exposure and type 2 diabetes mellitus: Exploring potential role of miR-144-3p in zinc-induced insulin resistance

Zinc exposure has been linked with disordered glucose metabolism and type 2 diabetes mellitus (T2DM) development. However, the underlying mechanism remains unclear. We conducted population-based studies and in vitro experiments to explore potential role of microRNAs (miRNAs) in zinc-related hyperglycemia and T2DM. In the discovery stage, we identified plasma miRNAs expression profile for zinc exposure based on 87 community residents from the Wuhan-Zhuhai cohort through next-generation sequencing. MiRNAs profiling for T2DM was also performed among 9 pairs newly diagnosed T2DM-healthy controls. In the validating stage, plasma miRNA related to both of zinc exposure and T2DM among the discovery population was measured by qRT-PCR in 161 general individuals derived from the same cohort. Furthermore, zinc treated HepG2 cells with mimic or inhibitor were used to verify the regulating role of miR-144-3p. Based on the discovery and validating populations, we observed that miR-144-3p was positively associated with urinary zinc, hyperglycemia, and risk of T2DM. In vitro experiments confirmed that zinc-induced increase in miR-144-3p expression suppressed the target gene Nrf2 and downstream antioxidant enzymes, and aggravated insulin resistance. Our findings provided a novel clue for mechanism underlying zinc-induced glucose dysmetabolism and T2DM development, emphasizing the important role of miR-144-3p dysregulation.

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.

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

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

Sustained air pollution exposures, fasting plasma glucose, glycated haemoglobin, prevalence and incidence of diabetes: a nationwide study in China

BACKGROUND

Evidence remains limited and inconsistent for the associations between sustained air pollution exposures and diabetes development. This study aimed to determine the potential effects of particulate matter with a diameter of ≤10 micrometres (PM10), particulate matter with a diameter of ≤2.5 micrometres (PM2.5) and nitrogen dioxide (NO2) on alterations of fasting plasma glucose (FPG), glycated haemoglobin (HbA1c), in particular, on prevalence and incidence of diabetes.

METHODS

Cross-sectional analyses were conducted based on 9628 participants aged ≥45 years from the baseline survey (2011) of the China Health and Retirement Longitudinal Study (CHARLS), whereas cohort analyses were based on 3510 individuals without diabetes at baseline in the third survey (2015). Residences of participants were geocoded and the air pollution exposures were estimated using a satellite-based spatiotemporal model. Linear, logistic and modified Poisson regression models, adjusting for multiple confounders, were applied to assess the associations between air pollution and FPG, HbA1c, prevalence and incidence of diabetes, respectively.

RESULTS

Associations between PM10, PM2.5 and increased levels of FPG and HbA1c were identified. The levels of FPG and HbA1c increased by 0.025 mmol/L (95% CI: 0.007, 0.044) and 0.011 mmol/L (95% CI: 0.002, 0.019), respectively, for a 10-μg/m3 increase in PM10, and the levels of FPG and HbA1c increased by 0.061 mmol/L (95% CI: 0.028, 0.096) and 0.016 mmol/L (95% CI: 0.000, 0.031), respectively, for a 10-μg/m3 increase in PM2.5. There were also positive associations between diabetes prevalence and PM2.5 and PM10. In the cohort analyses, PM10, PM2.5 and NO2 were associated with a higher incidence of diabetes.

CONCLUSION

Air pollution was allied to diabetes development in elderly Chinese populations. Considering the impact of the dramatic increase in the incidence and prevalence of diabetes in China, interventions to improve air quality are urgently needed.

Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly

As an independent risk factor, ambient air pollution can assume a considerable part in mortality and worsening of cardiovascular disease. We sought to investigate the association between long-term exposure to ambient air pollution and cardiovascular disease mortality and their risk factors in Iranian's elderly population. This inquiry was conducted ecologically utilizing recorded data on cardiovascular disease mortality from 1990 to 2019 for males and females aged 50 years or more from the Global Burden of Disease dataset. Data was interned into Joinpoint software 4.9.0.0 to present Annual Percent Change (APC), Average Annual Percent Change (AAPC), and its confidence intervals. The relationship between recorded data on ambient air pollution and cardiovascular disease' mortality, the prevalence of high systolic blood pressure, high LDL cholesterol levels, high body mass index, and diabetes mellitus type2 was investigated using the Spearman correlation test in R 3.5.0 software. Our finding demonstrated that cardiovascular diseases in elderly males and females in Iran had a general decreasing trend (AAPC = -0.77% and -0.65%, respectively). The results showed a positive correlation between exposure to ambient ozone pollution (p ≤ 0.001, r = 0.94) ambient particulate and air pollution (p < 0.001, r = 0.99) and mortality of cardiovascular disease. Also, ambient air pollution was positively correlated with high systolic blood pressure (p < 0.001, r = 0.98), high LDL cholesterol levels (p < 0.001, r = 0.97), high body mass index (p < 0.001, r = 0.91), diabetes mellitus type2 (p < 0.001, r = 0.77). Evidence from this study indicated that ambient air pollution, directly and indirectly, affects cardiovascular disease mortality in two ways by increasing the prevalence of some traditional cardiovascular disease risk factors. Evidence-based clinical and public health methodologies are necessary to decrease the burden of death and disability associated with cardiovascular disease.

The association between serum cadmium and diabetes in the general population: A cross-sectional study from NHANES (1999-2020)

Background

Associations between serum cadmium and diabetes had been reported in previous studies, however there was still considerable controversy regarding associations. Studies in general population that investigated the effects of serum cadmium on diabetes were currently lacking. We designed this cross-sectional study among U.S. adults under high and low cadmium exposure to assess associations between serum cadmium and diabetes.

Methods

This cross-sectional study analyzed 52,593 adults who aged more than 20 years and participated in the National Health and Nutrition Examination Survey (NHANES), 1999-2020. The missing values and extreme values in the covariables were filled by multiple interpolation. Univariate logistics regression, multivariate logistics regression and smooth fitting curves were used to analyze the association between serum cadmium and diabetes. Simultaneously, sensitivity analysis was carried out by converting the serum cadmium from continuous variable to categorical variable. The stratification logistics regression model was used to analyze whether there were special groups in each subgroup to test the stability of the results.

Results

In this cross-sectional study, serum cadmium levels were negatively correlated with the occurrence of diabetes in the low serum cadmium exposure group (OR = 0.811, 95% CI 0.698, 0.943; P = 0.007). There was no association between serum cadmium level and the occurrence of diabetes in the high serum cadmium exposure group (OR = 1.01, 95% CI 0.982, 1.037; P = 0.511). These results were consistent across all the subgroups (P for interaction >0.05).

Conclusion

Serum cadmium was negatively associated diabetes among the representative samples of the whole population in the United States under the normal level of serum cadmium exposure. However, there was no association between serum cadmium level and the occurrence of diabetes in the high serum cadmium exposure group. This study promoted an update of new preventative strategy targeting environment for the prevention and control of diabetes in the future.

Is city-level travel time by car associated with individual obesity or diabetes in Latin American cities? Evidence from 178 cities in the SALURBAL project

There is growing evidence that longer travel time by private car poses physical and mental risks. Individual-level obesity and diabetes, two of the main public health challenges in low- and middle-income contexts, could be associated to city-level travel times by car. We used individual obesity and diabetes data from national health surveys from individuals in 178 Latin American cities, compiled and harmonized by the SALURBAL project. We calculated city-level travel times by car using the Google Maps Distance Matrix API. We estimated associations between peak hour city-level travel time by car and obesity and diabetes using multilevel logistic regression models, while adjusting for individual characteristics and other city-level covariates. In our study we did not observe a relationship between city-level peak-hour travel time by car and individual obesity and diabetes, as reported in previous research for individual time spent in vehicles in high-income settings. Our results suggest that this relationship may be more complex in Latin America compared to other settings, especially considering that cities in the region are characterized by high degrees of population density and compactness and by a higher prevalence of walking and public transportation use.

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

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

Association between short-term ambient nitrogen dioxide and type 2 diabetes outpatient visits: A large hospital-based study

Type 2 diabetes (T2DM) as a non-communicable disease imposes heavy disease burdens on society. Limited studies have been conducted to assess the effects of short-term air pollution exposure on T2DM, especially in Asian regions. Our research aimed to determine the association between short-term exposure to ambient nitrogen dioxide (NO₂) and outpatient visits for T2DM in Chongqing, the largest city in western China, based on the data collected from November 28, 2013 to December 31, 2019. A generalized additive model (GAM) was applied, and stratified analyses were performed to investigate the potential modifying effects by age, gender, and season. Meanwhile, the disease burden was revealed from attributable risk. Positive associations between short-term NO₂ and daily T2DM outpatient visits were observed. The strongest association was observed at lag 04, with per 10 μg/m³ increase of NO₂ corresponded to increased T2DM outpatient visits at 1.57% [95% confidence interval (CI): 0.48%, 2.65%]. Stronger associations were presented in middle-aged group (35-64 years old), male group, and cool seasons (October to March). Moreover, there were 1.553% (8664.535 cases) of T2DM outpatient visits attributable to NO₂. Middle-aged adults, males, and patients who visited in cool seasons suffered heavier burdens. Conclusively, short-term exposure to NO₂ was associated with increased outpatient visits for T2DM. Attention should be paid to the impact of NO₂ on the burden of T2DM, especially for those vulnerable groups.

The impact of prolonged exposure to air pollution on the incidence of chronic non-communicable disease based on a cohort in Tianjin

Evidence on the associations of prolonged ambient pollutants exposure with chronic non-communicable diseases among middle-aged and elderly residents is still limited. This prospective cohort study intends to investigate the long-term effects of ambient pollution on hypertension and diabetes incidence among relatively older residents in China. Individual particulate matter exposure levels were estimated by satellite-based model. Individual gaseous pollutants exposure levels were estimated by Inverse Distance Weighted model. A Cox regression model was employed to assess the risks of hypertension and diabetes morbidity linked to air pollutants exposures. The cross-product term of ambient pollutants exposure and covariates was further added into the regression model to test whether covariates would modify these air pollution-morbidity associations. During the period from 2014 to 2018, a total of 97,982 subjects completed follow-up. 12,371 incidents of hypertension and 2034 of diabetes occurred. In the multi-covariates model, the hazard ratios (HR) and 95% confidence interval (CI) were 1.49 (1.45-1.52), 1.28 (1.26-1.30), 1.17 (1.15-1.18), 1.21 (1.17-1.25) and 1.33 (1.31-1.35) for hypertension morbidity per 10 μg/m³ increment in PM₁, PM_2.5, PM₁₀, NO₂ and SO₂, respectively. For diabetes onsets, the HR (95% CI) were 1.17 (1.11-1.23), 1.09 (1.04-1.13), 1.06 (1.02-1.09), 1.02 (0.95-1.10), and 1.24 (1.19-1.29), respectively. In addition, for hypertension analyses, the effect estimates were more pronounced in the participants with age <60 years old, BMI ≥24 kg/m², and frequent alcohol drinking. These findings provided the evidence on elevated risks of morbidity of hypertension and diabetes associated with prolonged ambient pollutants exposure at relatively high levels.

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

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

How long-term air pollution and its metal constituents affect type 2 diabetes mellitus prevalence? Results from Wuhan Chronic Disease Cohort

BACKGROUND

Epidemiological evidence linking type 2 diabetes mellitus (T2DM) with air pollution is discrepant and most are restricted to the influences of air-pollutant mass concentration. This study aims to explore the effects of long-term exposure to air pollution and its metal constituents on T2DM prevalence in China.

METHODS

We used data on 10,253 adult residents from the baseline survey of Wuhan Chronic Disease Cohort in 2019. Ambient PM_2.5, PM₁₀ and NO₂ exposure were estimated at residences based on Chinese Air Quality Reanalysis Dataset. Concentrations of 10 metal constituents were measured by 976 PM_2.5 filter samples collected from four monitoring stations. Logistic regression models were employed to examine associations of T2DM prevalence with 3-year mean concentrations of each air pollutant and PM_2.5 metal constituents prior to the baseline investigation.

RESULTS

A total of 673 T2DM cases (6.6%) were identified. The 3-year mean exposures to PM_2.5, PM₁₀ and NO₂ were 50.89 μg/m³, 82.86 μg/m³, and 39.79 μg/m³, respectively. And interquartile range (IQR) of 10 metals in PM_2.5 varied from 0.03 ng/m³ to 78.30 ng/m³. For 1 μg/m³ increment in PM_2.5, PM₁₀ and NO₂, the odds of T2DM increased by 7.2% (95%CI: 1.026, 1.136), 3.1% (95%CI: 1.013, 1.050), and 2.1% (95%CI: 1.005, 1.038) after adjusting for potential confounders. Cd and Sb in PM_2.5 were significant risk factors to T2DM with odds ratios of 1.350 (95%CI: 1.089, 1.673) and 1.389 (95%CI: 1.164, 1.658) for per IQR increase, respectively. Stratification analyses indicated that males and those aged ≥45 years were more susceptive to long-term air pollution.

CONCLUSIONS

Long-term exposure to PM_2.5, PM₁₀ and NO₂ increased T2DM prevalence in a Wuhan population, especially for men and middle-aged and elderly people. Moreover, T2DM was significantly associated with Cd and Sb in PM_2.5. Further research to validate these results and to clarify the underlying mechanisms is warranted.

Comparison of metropolitan cities for mortality rates attributed to ambient air pollution using the AirQ model

In the present study, the air pollution dynamics of the metropolitan cities of Balıkesir, Bursa, Istanbul, Kocaeli, Sakarya and Tekirdağ in the Marmara Region, which is the geographical region with the highest urban and industrial activity in Turkey, were examined for the time period between 2016 and 2019. Annual changes in the cities in terms of air pollution, which was examined with a focus on the PM_2.5 parameter as indicated by United Nations (UN) Sustainable Development Goals (SDGs); differences in the cities by years; and the seasonal changes in air pollution in the cities were investigated. Additionally, mortality rates attributed to air pollution were calculated with the AirQ + software based on integrated exposure-response function recommended by the World Health Organization (WHO) and the UN using city-scale statistics of fatal disease cases that can be attributed to air pollution. It was determined that all cities in the Marmara Region study area exceeded the limit PM_2.5 values specified by the European Union (EU) in the years 2016, 2017 and 2018 while only Kocaeli and Tekirdağ were below the limit values in 2019. The limit values specified by the WHO were exceeded in all cities in each year. A total of 46,920 premature deaths attributed to the exceedance of WHO limit values were calculated for the years 2016, 2017, 2018 and 2019 with 11,895, 13,853, 11,748 and 9,429, respectively. Determining national limit values for the PM_2.5 parameter, which is among the most important factors of air pollution, and monitoring it in a sustainable manner using a sufficient number of well-equipped stations is of great importance. This way, national, regional and urban action plans regarding the impact of air pollution on human health, as indicated by UN SDGs, can be prepared.

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.

Associations of long-term exposure to ambient air pollutants with metabolic syndrome: The Wuhan Chronic Disease Cohort Study (WCDCS)

BACKGROUND

Evidence on the associations between long-term exposure to ambient air pollutants (including particle with aerodynamic diameter ≤10 μm (PM₁₀), particle with aerodynamic diameter ≤2.5 μm (PM_2.5), ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) and prevalence of metabolic syndrome (MetS) remains inconclusive. This study aimed to determine the associations based on a case-control study nested in the Wuhan Chronic Disease Cohort study (WCDCS), a population-based study with baseline survey in 2019.

METHODS

A total of 10,253 residents living in Wuhan were recruited. The 3-year average concentrations of main pollutants (PM₁₀, PM_2.5, O₃, NO₂, and SO₂) at residences prior to the survey date were estimated to evaluate the long-term exposures. The generalized linear mixed models were used to investigate the changes in MetS prevalence by an IQR increases in each air pollutant exposure concentrations. Interaction effects between air pollutants and demographic, lifestyle, and dietary factors on MetS were evaluated by including an interactive item in the main model.

RESULTS

The prevalence of MetS in Wuhan was 9.8%, and the 3-year exposure concentrations of PM₁₀, PM_2.5, O₃, NO₂, and SO₂ were 84.1 μg/m³, 50.5 μg/m³, 55.7 μg/m³, 46.0 μg/m³, and 9.4 μg/m³, respectively. Higher PM₁₀, PM_2.5 and O₃ exposure concentrations were associated with an elevated MetS prevalence (e.g. an IQR increase in PM_2.5, OR = 1.193, 95% confidence intervals (95%CIs): 1.028, 1.385; for O₃, OR = 1.074, 95%CIs: 1.025, 1.124), whereas NO₂, and SO₂ were negatively or insignificant correlated with odds of Mets (e.g. an IQR increase in NO₂, OR = 0.865, 95%CIs: 0.795, 0.941). Males, smokers, alcohol drinkers and individuals who intake fruits occasionally exposure to PM₁₀ and PM_2.5 were found had a higher risk of developing MetS.

CONCLUSIONS

Long-term exposure to higher concentrations of ambient air pollutants may elevate the prevalence of MetS in populations in Central China. Susceptible individuals especially those with unhealthy lifestyles had a higher risk for MetS.

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.

How exposure to chronic stress contributes to the development of type 2 diabetes: A complexity science approach

Chronic stress contributes to the onset of type 2 diabetes (T2D), yet the underlying etiological mechanisms are not fully understood. Responses to stress are influenced by earlier experiences, sex, emotions and cognition, and involve a complex network of neurotransmitters and hormones, that affect multiple biological systems. In addition, the systems activated by stress can be altered by behavioral, metabolic and environmental factors. The impact of stress on metabolic health can thus be considered an emergent process, involving different types of interactions between multiple variables, that are driven by non-linear dynamics at different spatiotemporal scales. To obtain a more comprehensive picture of the links between chronic stress and T2D, we followed a complexity science approach to build a causal loop diagram (CLD) connecting the various mediators and processes involved in stress responses relevant for T2D pathogenesis. This CLD could help develop novel computational models and formulate new hypotheses regarding disease etiology.

Long-term exposure to air pollution and risk of venous thromboembolism in a large administrative cohort

BACKGROUND

Venous thromboembolisms (VTE) are one of the most frequent cause among the cardiovascular diseases. Despite the association between long-term exposure to air pollution and cardiovascular outcomes have been widely explored in epidemiological literature, little is known about the air pollution related effects on VTE. We aimed to evaluate this association in a large administrative cohort in 15 years of follow-up.

METHODS

Air pollution exposure (NO₂, PM₁₀ and PM_2.5) was derived by land use regression models obtained by the ESCAPE framework. Administrative health databases were used to identify VTE cases. To estimate the association between air pollutant exposures and risk of hospitalizations for VTE (in total and divided in deep vein thrombosis (DVT) and pulmonary embolism (PE)), we used Cox regression models, considering individual, environmental (noise and green areas), and contextual characteristics. Finally, we considered potential effect modification for individual covariates and previous comorbidities.

RESULTS

We identified 1,954 prevalent cases at baseline and 20,304 cases during the follow-up period. We found positive associations between PM_2.5 exposures and DVT, PE and VTE with hazard ratios (HRs) up to 1.082 (95% confidence intervals: 0.992, 1.181), 1.136 (0.994, 1.298) and 1.074 (0.996, 1.158) respectively for 10 μg/m³ increases. The association was stronger in younger subjects (< 70 years old compared to > 70 years old) and among those who had cancer.

CONCLUSION

The effect of pollutants on PE and VTE hospitalizations, although marginally non-significant, should be interpreted as suggestive of a health effect that deserves attention in future studies.

Long-term exposure to ambient air pollution and incidence of depression: A population-based cohort study in China

BACKGROUND

Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent.

OBJECTIVES

To investigate the effects of long-term air pollution exposure on depression risk prospectively in China.

METHODS

The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 μm (PM_2.5), ≤10 μm (PM₁₀) and nitrogen dioxide (NO₂) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses.

RESULTS

Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM_2.5, 1.49 (95%CI: 1.35, 1.64) for PM₁₀ and 1.58 (95%CI: 1.42, 1.77) for NO₂. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses.

CONCLUSIONS

Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.

The effect of adjustment to register-based and questionnaire-based covariates on the association between air pollution and cardiometabolic disease

OBJECTIVE

Recent studies on air pollution and disease have been based on millions of participants within a region or country, relying entirely on register-based confounder adjustment. We aimed to investigate the effects of increasing adjustment for register- and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases.

METHODS

In a population-based cohort of 246,766 eligible participants randomly selected across Denmark in 2010 and 2013 and followed up until December 31, 2017, we identified 3,247 myocardial infarction (MI) cases, 4,166 stroke cases and 6,366 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM_2.5 and NO₂ modelled using a validated air pollution model. We used Cox proportional hazards models to calculate hazard ratios (HR) with increasing adjustment for a number of individual- and area-level register-based covariates as well as lifestyle covariates assessed through questionnaires.

RESULTS

We found that a 5 μg/m³ higher PM_2.5 was associated with HRs (95% CI) for MI, stroke and diabetes, of respectively, 1.18 (0.91-1.52), 1.11 (0.88-1.40) and 1.24 (1.03-1.50) in the fully adjusted models. For all three diseases, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in higher HRs compared to HRs adjusted only for age, sex and calendar-year, most marked for MI and diabetes. Further adjustment for lifestyle in models with full register-based individual- and area-level adjustment resulted in only minor changes in HRs for all three diseases.

CONCLUSIONS

Our findings suggest that in studies of air pollution and cardiometabolic disease, which use an adjustment strategy with a broad range of register-based socioeconomic variables, there is no effect on risk estimates from subsequent lifestyle adjustment.

Impact of polluting fuels for cooking on diabetes mellitus and glucose metabolism in south urban China

We hypothesized that exposure to polluting fuels for cooking was associated with abnormality of glucose metabolism and diabetes mellitus (DM) in south urban China. 3414 residents were surveyed in 14 urban areas of Guangdong Province in 2018. We recorded polluting fuels for cooking exposure, different DM status (DM, prediabetes), fasting blood glucose (FBG), oral glucose tolerance test (OGTT), glycated hemoglobin (HbA_1c ), and other covariates by using a structured questionnaire. We conducted logistic regression model and multivariate linear regression model based on propensity-score method (inverse probability of weighting) to examine the effect of polluting fuels for cooking exposure on DM and glucose metabolism. Exposure to polluting fuels for cooking was associated with DM (odds ratio: 2.57, 95% confidence interval: 1.71 to 3.86) and prediabetes (odds ratio: 1.98, 95% confidence interval: 1.52 to 2.58) in both the adjusted and unadjusted models (all p < 0.05). Exposure to polluting fuels for cooking was significantly associated with an increase of FBG (β: 0.30 mmol/L, 95% confidence interval: 0.22 to 0.38 mmol/L). Sensitivity analysis showed that the results were not substantially changed. There was an increased risk of DM, prediabetes and high levels of FBG, OGTT, and HbA_1c among participants aged ≥ 40 years with exposure to polluting fuels for cooking. We demonstrated that exposure to polluting fuels for cooking was associated with higher levels of FBG, which contributed to the increased risk of DM and prediabetes in middle-aged elderly Chinese population living in urban areas.

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.

Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study

It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.

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

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

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.

Ambient air pollution and endocrinologic disorders in childhood

Ambient air pollution has been proposed as an important environmental risk factor that increases global mortality and morbidity. Over the past decade, several human and animal studies have reported an association between exposure to air pollution and altered metabolic and endocrine systems in children. However, the results for these studies were mixed and inconclusive and did not demonstrate causality because different outcomes were observed due to different study designs, exposure periods, and methodologies for exposure measurements. Current proposed mechanisms include altered immune response, oxidative stress, neuroinflammation, inadequate placental development, and epigenetic modulation. In this review, we summarized the results of previous pediatric studies that reported effects of prenatal and postnatal air pollution exposure on childhood type 1 diabetes mellitus, obesity, insulin resistance, thyroid dysfunction, and timing of pubertal onset, along with underlying related mechanisms.

Relationship between Green and Blue Spaces with Mental and Physical Health: A Systematic Review of Longitudinal Observational Studies

There is growing interest in the ways natural environments influence the development and progression of long-term health conditions. Vegetation and water bodies, also known as green and blue spaces, have the potential to affect health and behaviour through the provision of aesthetic spaces for relaxation, socialisation and physical activity. While research has previously assessed how green and blue spaces affect mental and physical wellbeing, little is known about the relationship between these exposures and health outcomes over time. This systematic review summarised the published evidence from longitudinal observational studies on the relationship between exposure to green and blue space with mental and physical health in adults. Included health outcomes were common mental health conditions, severe mental health conditions and noncommunicable diseases (NCDs). An online bibliographic search of six databases was completed in July 2020. After title, abstract and full-text screening, 44 eligible studies were included in the analysis. Depression, diabetes and obesity were the health conditions most frequently studied in longitudinal relationships. The majority of exposures included indicators of green space availability and urban green space accessibility. Few studies addressed the relationship between blue space and health. The narrative synthesis pointed towards mixed evidence of a protective relationship between exposure to green space and health. There was high heterogeneity in exposure measures and adjustment for confounding between studies. Future policy and research should seek a standardised approach towards measuring green and blue space exposures and employ theoretical grounds for confounder adjustment.

Influence of the seasonality and of urban variables in the BTEX and PM2.5 atmospheric levels and risks to human health in a tropical coastal city (Fortaleza, CE, Brazil)

The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM_2.5 and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM_2.5 was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 μg m^-3, with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM_2.5 levels ranged from 4.12 to 33.0 μg m^-3 and 4.18 to 86.58 μg m^-3 in the dry and wet periods, respectively. No seasonal pattern was found for PM_2.5, probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E^-04 to 4.71E^-03 and 1.72E^-04 to 2.01E^-03 for benzene and from 3.07E^-06 to 7.04E^-05 and 3.08E^-06 to 2.85E^-05 for PM_2.5 in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.