Association between air pollution and type 2 diabetes: an updated review of the literature

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

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

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

BACKGROUND

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

METHODS AND FINDINGS

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

CONCLUSIONS

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

Ambient air pollution and the risk of ischaemic and haemorrhagic stroke

Stroke is a leading cause of disability and the second most common cause of death worldwide. Increasing evidence suggests that air pollution is an emerging risk factor for stroke. Over the past decades, air pollution levels have continuously increased and are now estimated to be responsible for 14% of all stroke-associated deaths. Interpretation of previous literature is difficult because stroke was usually not distinguished as ischaemic or haemorrhagic, nor by cause. This Review summarises the evidence on the association between air pollution and the different causes of ischaemic stroke and haemorrhagic stroke, to clarify which people are most at risk. The risk for ischaemic stroke is increased after short-term or long-term exposure to air pollution. This effect is most pronounced in people with cardiovascular burden and stroke due to large artery disease or small vessel disease. Short-term exposure to air pollution increases the risk of intracerebral haemorrhage, a subtype of haemorrhagic stroke, whereas the effects of long-term exposure are less clear. Limitations of the current evidence are that studies are prone to misclassification of exposure, often rely on administrative data, and have insufficient clinical detail. In this Review, we provide an outlook on new research opportunities, such as those provided by the decreased levels of air pollution due to the current COVID-19 pandemic.

Associations of residing greenness and long-term exposure to air pollution with glucose homeostasis markers

BACKGROUND

Although long-term exposure to higher air pollutants and lower residing greenness related to disorders of glucose homeostasis have been reported, their interaction effects on glucose homeostasis in developing countries remained unclear.

METHODS

A total of 35, 482 participants were obtained from the Henan Rural Cohort (n = 39, 259). Exposure to air pollutants (PM₁, PM_2.5, PM₁₀ and NO₂) were predicted by using a spatiotemporal model-based on satellites data. Residing greenness was reflected by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which were derived from satellites data. Independent associations of single or mixture of air pollutant or residing greenness with glucose homeostasis markers were analyzed by quantile regression models and quantile g (qg)-computation method, respectively. Furthermore, interaction effects of residing greenness and air pollution on glucose homeostasis markers were analyzed by generalized additive models.

RESULTS

Positive associations of single or mixture of air pollutants (PM₁, PM_2.5, PM₁₀ or NO₂) with fasting plasma glucose (FPG) were observed, while negative associations of single or mixture of air pollutants with insulin or HOMA-β were observed. Residing greenness was negatively associated with FPG but positively related to insulin or HOMA-β. Quantile regression revealed the heterogeneity were observed in the associations the residing greenness or air pollutants with glucose homeostasis markers (insulin or HOMA-β) across deciles of the glucose homeostasis markers distributions. Furthermore, joint associations of single air pollutant and residing greenness on glucose homeostasis markers were found.

CONCLUSIONS

The results indicated that exposure to air pollution had negative effect on glucose homeostasis markers and these effects may be modified by living in higher green space. These findings suggest that increased residing greenness and air pollution control may have joint effect on decreased the risk of diabetes.

CLINICAL TRIAL REGISTRATION

The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).

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

Background

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

Methods

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

Results

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

Conclusions

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

Particle air pollution and gestational diabetes mellitus in Houston, Texas

BACKGROUND

There is mixed evidence implicating prenatal exposure to particulate matter <2.5 μm in aerodynamic diameter (PM_2.5) in the risk of gestational diabetes mellitus (GDM) and only one study has examined exposure to PM_2.5 constituents, which vary with location because of different emission sources.

METHODS

We conducted a retrospective cohort study of singleton live births in Harris County, Texas from 2008 to 2013. With data from the Texas Commission on Environmental Quality (TCEQ), we spatially interpolated maternal exposures to total and speciated PM_2.5, nitrogen dioxide (NO₂) and ozone (O₃) over the 12-week preconception period and trimesters 1 and 2. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between pre-conception and pregnancy exposures to total and speciated PM_2.5 and odds of GDM, adjusted for temperature and maternal covariates. We also evaluated confounding from NO₂ and O₃ exposures in multi-pollutant models.

RESULTS

An interquartile range (IQR) increase in total PM_2.5 exposure was associated with elevated odds for developing GDM over the preconception (adjusted OR = 1.09, 95% CI: 1.06, 1.12), first trimester (OR = 1.13, 95% CI: 1.10, 1.17) and second trimester (OR = 1.13, 95% CI: 1.09, 1.17) periods. Effect estimates increased with adjustment for NO₂ and O₃. We observed modest increases in odds of GDM for IQR increases in first trimester ammonium ion PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) and sulfate PM_2.5 (OR = 1.03, 95% CI: 1.00, 1.05) exposures, as well as preconception Cr PM_2.5 exposures (OR = 1.05, 95% CI: 1.02, 1.07).

CONCLUSION

Exposures to PM_2.5, before and during pregnancy were associated with elevated odds of GDM. Mitigating air pollution exposures may reduce the risk of GDM and its long-term implications for maternal and child health.

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

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

Role of Air Pollution and rs10830963 Polymorphism on the Incidence of Type 2 Diabetes: Tehran Cardiometabolic Genetic Study

Diabetes mellitus (DM) is considered one of the leading health issues that are egregiously threatening human life throughout the world. Several epidemiological studies have examined the relationship of a particular matter < 10 μm (PM10) exposure and with type 2 diabetes mellitus (T2DM) prevalence and incidence. Accordingly, the current study is a study investigating the independent influence of air pollution (AP) and rs10830963 on the incidence of T2DM. A total number of 2428 adults over 20 years of age participated in a prospective cohort (TCGS) during a 9-year follow-up phase. The concentration of AP was measured, and the obtained values were considered the mean level in three previous years since the exposure concentration took the people living in that location. The COX regression model was employed to determine the influence of AP and rs10830963 on the incidence of T2DM in adjustment with covariate factors. Among the 392 T2DM, 230 cases (58.7%) were female diabetics, and 162 (41.3%) were male diabetics. According to the multivariable-adjusted model, exposure to PM10 (per 10 μm/m3), associated with the risk of T2DM, although just a borderline (p = 0.07) was found in the multivariable model (HR; 1.50, 95% CI; 1-2.32). The rs10830963 was directly associated with the incidence of diabetes, and the GG genotype increased the T2DM rate by 113% (more than two times) (HR; 2.134, 95% CI; 1.42-3.21, p ≤ 0.001) and GC increased it by 65% (HR; 1.65, 95% CI; 1.24-2.21, p ≤ 0.001). Long-term exposure to PM10 was associated with an increased risk of diabetes. Thus, it is suggested that the individuals with variant rs10830963 genotypes fall within a group susceptible to an increased risk of T2DM arising from AP.