The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: The CHAMPIONS Study

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

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

The role of neighborhood inequalities on diabetes prevention care: a mini-review

An emerging research niche has focused on the link between social determinants of health and diabetes mellitus, one of the most prevalent non-communicable diseases in modern society. The aim of the present mini-review is to explore and summarize current findings in this field targeting high-income countries. In the presence of disadvantaged neighborhood factors (including socioeconomic status, food environment, walkability and neighborhood aesthetics), diabetes prevention and care are affected at a multidimensional level. The vast majority of the included studies suggest that, besides individual risk factors, aggregated neighborhood inequalities should be tackled to implement effective evidence-based policies for diabetes mellitus.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Lanzhou, China

Studies on the effects of short-term air pollution exposure on hospitalization for type 2 diabetes mellitus (T2DM) are relatively scarce in developing regions. The time-series study was used to explore the acute effects of air pollutants on hospitalization for T2DM in Lanzhou, China. A distribution lag nonlinear model based on the generalized additive model was used to analyze the hospitalization impact of air pollution on T2DM. Stratified analysis by gender, age and season was obtained. The results were indicated as the relative risk (RR) with 95% confidence interval (CI) for single-day lags (from lag0 to lag7) and cumulative lag days (from lag0-1 to lag0-7). The strongest correlations (RR, 95% CI) of hospitalization for T2DM and PM10 (RR = 1.003, 95% CI 1.000, 1.001) at lag7 and NO2 (RR = 1.022, 95% CI 1.000, 1.045) at lag0-4 were observed for an increase of 10 µg/m3 in the concentrations and CO (RR = 1.091, 95% CI 1.017, 1.170) at lag0-4 for an increase of 1 mg/m3 in the concentration. The hazardous impacts of PM10, NO2 and CO were greater for females, people aged ≥ 65 years and in the cold season. However, there was no significant association between PM2.5, SO2 and O38h and the number of hospitalizations for T2DM.

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.

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.

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

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

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

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association between long-term exposure to ambient air pollution and prevalence of diabetes mellitus among Malaysian adults

Background

Malaysia has the highest rate of diabetes mellitus (DM) in the Southeast Asian region, and has ongoing air pollution and periodic haze exposure.

Methods

Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NO_x, NO₂, SO₂, O₃ and PM₁₀) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.

Results

The PM₁₀ concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NO_x decreased while O₃ increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM₁₀, 1.553 (95% CI, 1.328, 1.816) for O₃, 1.271 (95% CI, 1.088, 1.486) for SO₂, 1.124 (95% CI, 1.048, 1.207) for NO₂, and 1.087 (95% CI, 1.024, 1.153) for NO_x for NHMS 2006. The adjusted annual average levels of PM₁₀ [1.187 (95% CI, 1.088, 1.294)], O₃ [1.701 (95% CI, 1.387, 2.086)], NO₂ [1.120 (95% CI, 1.026, 1.222)] and NO_x [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO₂, and 0.910 for NO_x].

Conclusion

The findings of this study suggest that long-term exposure to O₃ is an important associated factor of underdiagnosed DM risk in Malaysia. PM₁₀, NO₂ and NO_x may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.

Human epidemiological evidence about the association between air pollution exposure and gestational diabetes mellitus: Systematic review and meta-analysis

BACKGROUND

Previous studies have shown that ambient air pollution exposure can increase the risk of type 2 diabetes mellitus (T2DM) significantly. In consideration of the common underlying pathophysiologic mechanisms, exposure to air pollution may also increase the risk of gestational diabetes mellitus (GDM), but the current evidence was inconsistent and has not well been systematically reviewed. Our goal was to perform a systematic review and meta-analysis assessing the association between air pollution exposure and GDM.

METHODS

An extensive literature search was conducted in selected electronic databases for related human epidemiological studies published in English language. Summary effect estimates were calculated using random-effect models for a) risk per unit increase in continuous air pollutant concentration and b) risk of high versus low exposure level in individual study if each exposure that had been examined in ≥2 studies. We evaluated the heterogeneity using Cochran's Q test and quantified it by I² statistic. Publication bias was also evaluated through the funnel plot when sufficient number of studies are available.

RESULTS

A total of 11 studies evaluating the association between GDM and exposure to air pollution were identified finally. The summary odds ratio (OR) for incidence of GDM following a 10 μg/m³ increase in PM_2.5 exposure during the second trimester was 1.04 (95% Confidence Interval (CI): 1.01, 1.09) and in NO_x during the first trimester was 1.03 (95%CI: 1.00, 1.07) per 10 ppb increase, while for high versus low SO₂ exposure during the second trimester was 1.25 (95%CI: 1.02, 1.53). High heterogeneity among study-specific results in majority of the analyses were observed, and attributed to different exposure assessment methods, populations, study locations, and covariates adjustment. Publication bias cannot be excluded because of the inclusion of small number of studies.

CONCLUSIONS

The present study supports the evidence that air pollution exposure increases the risk the GDM, albeit the existence of high heterogeneity. Further studies are necessary to elaborate the suggestive associations. These results are of public health significance since worsening air pollution in developing countries has been expected to increase the risk of GDM development.

Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India

BACKGROUND

Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM_2.5) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India.

METHODS

We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010-2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM_2.5 and BC levels at residence using land-use regression models and annual personal exposure to PM_2.5 and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex.

RESULTS

Mean (SD) residential PM_2.5 and BC were 32.9 (2.6) μg/m³ and 2.5 (2.6) μg/m³, respectively; personal exposures to PM_2.5 and BC were 54.5 (11.5) μg/m³ and 5.8 (2.5) μg/m³, respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM_2.5 and BC were not associated with higher blood glucose levels. Personal PM_2.5 (20 μg/m³ increase) and BC (1 μg/m³ increase) were negatively associated with blood glucose levels in women (PM_2.5: -1.93, 95%CI: -3.12, -0.73; BC: -0.63, 95%CI: -0.90, -0.37). In men, associations were negative for personal PM_2.5 (-1.99, 95%CI: -3.56, -0.39) and positive for personal BC (0.49, 95%CI: -0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes.

CONCLUSIONS

Our results do not provide evidence that residential exposures to PM_2.5 or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies.

Association of depression and anxiety with clinical, sociodemographic, lifestyle and environmental factors in South Asian and white European individuals at high risk of diabetes

AIM

To investigate the prevalence and correlates of depressive and anxiety symptoms within South Asian and white European populations at high risk of developing Type 2 diabetes.

METHODS

Data were collected at baseline, and at 12, 24 and 36 months from 1429 white European individuals (age 64±7 years, 35.8% women) and 160 South Asian individuals (age 59±9 years, 30.6% women) who were at high risk of Type 2 diabetes and who took part in two Type 2 diabetes prevention trials in Leicestershire, UK. The Hospital Anxiety and Depression Scale was administered during each study visit. Clinical, sociodemographic, lifestyle and environmental data were collected.

RESULTS

At baseline, the burden of depressive symptoms varied by ethnic group and gender, with 9.9% of white European men, 14.9% of white European women, 23.6% of South Asian men and 29.2% of South Asian women exceeding the cut-off score for mild-to-severe depression. During the course of the study and after adjustment for clinical, sociodemographic, lifestyle and environmental factors, depressive symptoms remained higher in the South Asian compared to the white European participants [score higher by 1.5, 95% CI 0.9-2.1]. Levels of anxiety were also higher in the South Asian participants, although associations were attenuated after adjustment. Social deprivation, BMI, proximity to fast-food outlets and physical activity were correlates for depression in both the South Asian and white European participants.

CONCLUSIONS

A higher burden of depressive symptoms was consistently evident among the South Asian individuals, even after adjustment for multiple covariates. It is important to understand both the reasons why these differences are present, to help reduce health inequalities, and whether higher levels of depressive symptoms affect the uptake of and retention rates in diabetes prevention programmes in South Asian communities.

Ambient air pollution and risk of type 2 diabetes in the Chinese

We performed a time series analysis to investigate the potential association between exposure to ambient air pollution and type 2 diabetes (T2D) incidence in the Chinese population. Monthly time series data between 2008 and 2015 on ambient air pollutants and incident T2D (N = 25,130) were obtained from the Environment Monitoring Center of Ningbo and the Chronic Disease Surveillance System of Ningbo. Relative risks (RRs) and 95% confidence intervals (95% CIs) of incident T2D per 10 μg/m³ increases in ambient air pollutants were estimated from Poisson generalized additive models. Exposure to particulate matter < 10 μm (PM₁₀) and sulfur dioxide (SO₂) was associated with increased T2D incidence. The relative risks (RRs) of each increment in 10 μg/m³ of PM₁₀ and SO₂ were 1.62 (95% CI, 1.16-2.28) and 1.63 (95% CI, 1.12-2.38) for overall participants, whereas for ozone (O₃) exposure, the RRs were 0.78 (95% CI, 0.68-0.90) for overall participants, 0.78 (95% CI, 0.69-0.90) for males, and 0.78 (95% CI, 0.67-0.91) for females, respectively. Exposure to PM₁₀ and SO₂ is positively associated with T2D incidence, whereas O₃ is negatively associated with T2D incidence.

Long-term exposure to ambient fine particulate matter (PM2.5) and incident type 2 diabetes: a longitudinal cohort study

AIMS/HYPOTHESIS

Information on the associations of long-term exposure to fine particulate matter (with an aerodynamic diameter less than 2.5 μm; PM_2.5) with the development of type 2 diabetes is scarce, especially for south-east Asia, where most countries are experiencing serious air pollution. This study aimed to investigate the long-term effects of exposure to ambient PM_2.5 on the incidence of type 2 diabetes in a population of Taiwanese adults.

METHODS

A total of 147,908 participants without diabetes, at least 18 years of age, were recruited in a standard medical examination programme between 2001 and 2014. They were encouraged to take medical examinations periodically and underwent at least two measurements of fasting plasma glucose (FPG). Incident type 2 diabetes was identified as FPG ≥7 mmol/l or self-reported physician-diagnosed diabetes in the subsequent medical visits. The PM_2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model with a resolution of 1 × 1 km². The 2 year average of PM_2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM_2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM_2.5 on the incidence of type 2 diabetes. A wide range of covariates were introduced in the models to control for potential effects, including age, sex, education, season, year, smoking status, alcohol drinking, physical activity, vegetable intake, fruit intake, occupational exposure, BMI, hypertension and dyslipidaemia (all were treated as time-dependent covariates except for sex).

RESULTS

Compared with the participants exposed to the first quartile of ambient PM_2.5, participants exposed to the second, third and fourth quartiles of ambient PM_2.5 had HRs of 1.28 (95% CI 1.18, 1.39), 1.27 (95% CI 1.17, 1.38) and 1.16 (95% CI 1.07, 1.26), respectively, for the incidence of type 2 diabetes. Participants who drank occasionally or regularly (more than once per week) or who had a lower BMI (<23 kg/m²) were more sensitive to the long-term effects of exposure to ambient PM_2.5.

CONCLUSIONS/INTERPRETATION

Long-term exposure to ambient PM_2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution.

Ambient fine particulate pollution associated with diabetes mellitus among the elderly aged 50 years and older in China

The linkage between ambient air pollution exposure and occurrence of diabetes mellitus is not well defined. This study examined the association between exposure to fine particles (PM_2.5) and the prevalence of diabetes among Chinese elderly people. We surveyed 11,504 adults aged ≥50 years in China, estimated the annual concentrations of ambient PM_2.5 using a satellite-based model of aerosol optical depth information. We employed a generalized mixed effects model to examine the association between PM_2.5 and the prevalence of diabetes and explored potential effect modifiers. We estimated diabetes burden attributable to ambient PM_2.5 if the observed association is indeed causal. The diabetes prevalence among the participants was 6.5% (n = 745). Our analysis found a statistically significant association between PM_2.5 and diabetes. The adjusted odds ratio was 1.27 (95% confidence interval (CI), 1.12, 1.43) for each 10 μg/m³ increment in ambient PM_2.5. Stratified analyses found a lower association among the participants with higher consumption of fruit. We estimated that 22.02% (95% CI: 8.59%, 43.29%) of the diabetes cases could be ascribable to ambient PM_2.5. Our finding suggests that PM_2.5 exposures could increase the risk of diabetes, and if causal, could be responsible for substantial burden of diabetes among the Chinese elderly; and higher intakes of fruit might reduce the harmful effects of PM_2.5, however, due to the limitation of the cross-sectional study design, more studies are warranted to confirm this observation.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Shijiazhuang, China

Air pollution has been considered as an important contributor to diabetes development. However, the evidence is fewer in developing countries where air pollution concentrations were much higher. In this study, we conduct a time-series study to investigate the acute adverse effect of six air pollutants on type II diabetes mellitus (T2DM) hospitalization in Shijiazhuang, China. An over-dispersed passion generalized addictive model adjusted for weather conditions, day of the week, and long-term and seasonal trends was used. Finally, a 10-μg/m³ increase of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) corresponded to 0.53% (95% confidence interval = 0.22-0.83), 0.32% (95% CI = 0.10-0.55), 0.55% (95% CI = 0.04-1.07), 1.27% (95% CI = 0.33-2.22), and 0.04% (95% CI = 0.02-0.06) increment of T2DM hospitalization, respectively. The effects of PM_2.5, PM₁₀, and CO were robust when adjusted for co-pollutants. The associations appeared to be a little stronger in the cool season than in the warm season. And stronger associations were found in male and elderly (≥ 65 years) than in female and younger people (35-65 years). Our results contribute to the limited data in the scientific literature on acute effects of air pollution on type II diabetes mellitus in developing countries.

MAIN FINDINGS

This is the first adverse effect evidence of air pollution on T2DM in Shijiazhuang, a severely polluted city in China. Males were more vulnerable than females in severe pollution.

Exposure to Environmental and Occupational Particulate Air Pollution as a Potential Contributor to Neurodegeneration and Diabetes: A Systematic Review of Epidemiological Research

It has been hypothesised that environmental air pollution, especially airborne particles, is a risk factor for type 2 diabetes mellitus (T2DM) and neurodegenerative conditions. However, epidemiological evidence is inconsistent and has not been previously evaluated as part of a systematic review. Our objectives were to carry out a systematic review of the epidemiological evidence on the association between long-term exposure to ambient air pollution and T2DM and neurodegenerative diseases in adults and to identify if workplace exposures to particles are associated with an increased risk of T2DM and neurodegenerative diseases. Assessment of the quality of the evidence was carried out using the GRADE system, which considers the quality of the studies, consistency, directness, effect size, and publication bias. Available evidence indicates a consistent positive association between ambient air pollution and both T2DM and neurodegeneration risk, such as dementia and a general decline in cognition. However, corresponding evidence for workplace exposures are lacking. Further research is required to identify the link and mechanisms associated with particulate exposure and disease pathogenesis and to investigate the risks in occupational populations. Additional steps are needed to reduce air pollution levels and possibly also in the workplace environment to decrease the incidence of T2DM and cognitive decline.

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

OBJECTIVE

To examine the association between air pollution and diabetes prevalence in the United States, 2002 to 2008.

METHODS

Annual average particulate matter (PM2.5) and ozone concentrations were calculated using daily county-level data from the CDC's Tracking Network. Individual-level outcome and covariate data were obtained from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System for 862,519 individuals. We used Poisson regression analyses to examine associations between each air pollutant (per 10-unit increase) with diabetes, including regional sub-analyses. Analyses were adjusted for year, age, sex, race, ethnicity, education, income, smoking status, body mass index, exercise, and asthma.

RESULTS

Positive associations between each pollutant and diabetes were found (PM2.5: prevalence ratio [PR] = 1.10; 95% confidence interval [CI] = 1.03, 1.17; ozone: PR = 1.06; 95% CI = 1.03, 1.09). There was limited evidence of effect modification by region.

CONCLUSIONS

Interventions to reduce ambient air pollution may help alleviate the diabetes burden in the US.

Ambient and Traffic-Related Air Pollution Exposures as Novel Risk Factors for Metabolic Dysfunction and Type 2 Diabetes

PURPOSE OF REVIEW

Diabetes mellitus is a top contributor to the global burden of mortality and disability in adults. There has also been a slow, but steady rise in prediabetes and type 2 diabetes in youth. The current review summarizes recent findings regarding the impact of increased exposure to air pollutants on the type 2 diabetes epidemic.

RECENT FINDINGS

Human and animal studies provide strong evidence that exposure to ambient and traffic-related air pollutants such as particulate matter (PM), nitrogen dioxide (NO2), and nitrogen oxides (NOx) play an important role in metabolic dysfunction and type 2 diabetes etiology. This work is supported by recent findings that have observed similar effect sizes for increased exposure to air pollutants on clinical measures of risk for type 2 diabetes in children and adults. Further, studies indicate that these effects may be more pronounced among individuals with existing risk factors, including obesity and prediabetes.

SUMMARY

Current epidemiological evidence suggests that increased air pollution exposure contributes to alterations in insulin signaling, glucose metabolism, and beta (β)-cell function. Future work is needed to identify the specific detrimental pollutants that alter glucose metabolism. Additionally, advanced tools and new areas of investigation present unique opportunities to study the underlying mechanisms, including intermediate pathways, that link increased air pollution exposure with type 2 diabetes onset.

Ambient air pollution, adipokines, and glucose homeostasis: The Framingham Heart Study

OBJECTIVE

To examine associations of proximity to major roadways, sustained exposure to fine particulate matter (PM2.5), and acute exposure to ambient air pollutants with adipokines and measures of glucose homeostasis among participants living in the northeastern United States.

METHODS

We included 5958 participants from the Framingham Offspring cohort examination cycle 7 (1998-2001) and 8 (2005-2008) and Third Generation cohort examination cycle 1 (2002-2005) and 2 (2008-2011), who did not have type 2 diabetes at the time of examination visit. We calculated 2003 annual average PM2.5 at participants' home address, residential distance to the nearest major roadway, and daily PM2.5, black carbon (BC), sulfate, nitrogen oxides (NOx), and ozone concentrations. We used linear mixed effects models for fasting glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) which were measured up to twice, and used linear regression models for adiponectin, resistin, leptin, and hemoglobin A1c (HbA1c) which were measured only once, adjusting for demographics, socioeconomic position, lifestyle, time, and seasonality.

RESULTS

The mean age was 51years and 55% were women. Participants who lived 64m (25th percentile) from a major roadway had 0.28% (95% CI: 0.05%, 0.51%) higher fasting plasma glucose than participants who lived 413m (75th percentile) away, and the association appeared to be driven by participants who lived within 50m from a major roadway. Higher exposures to 3- to 7-day moving averages of BC and NOx were associated with higher glucose whereas the associations for ozone were negative. The associations otherwise were generally null and did not differ by median age, sex, educational attainment, obesity status, or prediabetes status.

CONCLUSIONS

Living closer to a major roadway or acute exposure to traffic-related air pollutants were associated with dysregulated glucose homeostasis but not with adipokines among participants from the Framingham Offspring and Third Generation cohorts.

The health benefits of nature-based solutions to urbanization challenges for children and the elderly - A systematic review

Urban green and blue spaces promote health by offering areas for physical activity, stress relief, and social interaction, which may be considered as cultural ecosystem services. They also provide a number of regulating ecosystem services that can be regarded as nature-based solutions to mitigate impacts from urbanization-induced challenges. Urban trees and other vegetation provide cooling through shade and evapotranspiration, which reduce the impact of the urban heat island on hot summer days. Urban vegetation may improve air quality by removing air pollutants. Open areas in cities, such as parks, gardens, playgrounds and cemeteries, are unsealed spaces that also improve infiltration during extreme precipitation events providing water regulating functions. All these services have the potential to improve the health of urban residents, particularly of specific vulnerable groups such as children and the elderly. The aim of this paper is to provide an overview of the current state of evidence on the relationship between the health of children and the elderly and urban green and blue spaces that can account as nature-based solutions to urbanization-induced challenges. We discuss potential confounding factors and refer to the different green space metrics used to identify associations to health. From the results, we cannot conclude on a universal protective health effect of urban green and blue spaces for children and the elderly. While the association trend is positive, the results remain inconclusive, context dependent and are partly overridden by socioeconomic confounders. However, the research area is consistently increasing, and we advance important prospects for future research on urban green and blue spaces in the face of global challenges such as urbanization.