All-source and source-specific air pollution and 10-year diabetes Incidence: Total effect and mediation analyses in the Heinz Nixdorf recall study

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.

Association between PM2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation

BACKGROUND

The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear.

METHOD

A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively.

RESULT

PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP.

CONCLUSION

Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

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

Importance

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

Objective

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

Design, Setting, and Participants

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

Exposures

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

Main Outcomes and Measures

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

Results

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

Conclusions and Relevance

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

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 mediation effect of asprosin on the association between ambient air pollution and diabetes mellitus in the elderly population in Taiyuan, China

Evidence around the relationship between air pollution and the development of diabetes mellitus (DM) remains limited and inconsistent. To investigate the potential mediation effect of asprosin on the association between fine particulate matter (PM2.5), tropospheric ozone (O3) and blood glucose homeostasis. A case-control study was conducted on a total of 320 individuals aged over 60 years, including both diabetic and non-diabetic individuals, from six communities in Taiyuan, China, from July to September 2021. Generalized linear models (GLMs) suggested that short-term exposure to PM2.5 was associated with elevated fasting blood glucose (FBG), insulin resistance index (HOMA-IR), as well as reduced pancreatic β-cell function index (HOMA-β), and short-term exposure to O3 was associated with increased FBG and decreased HOMA-β in the total population and elderly diabetic patients. Mediation analysis showed that asprosin played a mediating role in the relationship of PM2.5 and O3 with FBG, with mediating ratios of 10.2% and 18.4%, respectively. Our study provides emerging evidence supporting that asprosin mediates the short-term effects of exposure to PM2.5 and O3 on elevated FBG levels in an elderly population. Additionally, the elderly who are diabetic, over 70 years, and BMI over 24 kg/m2 are more vulnerable to air pollutants and need additional protection to reduce their exposure to air pollution.

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.

Long-term exposure to ambient air pollution and inflammatory response in the KORA study

Previous studies consistently showed an association between fine atmospheric particulate matter (PM2.5) and cardiovascular diseases. Concerns about adverse health effects of ultrafine particles (UFP) are growing but long-term studies are still scarce. In this study, we examined the association between long-term exposure to ambient air pollutants and blood biomarkers of inflammation and coagulation, including fibrinogen, high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA) adiponectin and interleukin-6 (IL-6), measured in the German KORA-S4 cohort study (1999-2001). IL-6 was available for older participants only, who were therefore considered as a subsample. Annual mean concentrations of UFP (as particle number concentration), particulate matter in different particles sizes (PM10, PMcoarse, PM2.5, PM2.5 absorbance), ozone (O3), and nitrogen oxides (NO2, NOX) were estimated by land-use regression models and assigned to participants' home addresses. We performed a multiple linear regression between each pollutant and each biomarker with adjustment for confounders. Per 1 interquartile range (IQR, 1945 particles/cm3) increase of UFP, fibrinogen increased by 0.70 % (0.04; 1.37) and hs-CRP increased by 3.16 % (-0.52; 6.98). Adiponectin decreased by -2.53 % (-4.78; -0.24) per 1 IQR (1.4 μg/m3) increase of PM2.5. Besides, PM2.5 was associated with increased IL-6 in the subsample. In conclusion, we observed that long-term exposure to air pollutants, including both fine and ultrafine particles, was associated with higher concentrations of pro-inflammatory and lower concentrations of an anti-inflammatory blood biomarkers, which is consistent with an increased risk for cardiovascular disease observed for long-term exposure to air pollutants.

Secular trends in type 2 diabetes mellitus attributable to PM2.5 exposure in China from 1990 to 2019: an age-period-cohort analysis

Secular trends of mortality and disability-adjusted life years (DALY) in type 2 diabetes mellitus (T2DM) attributable to PM2.5 exposure in China remain unclear. This study applied the joinpoint regression analysis and age-period-cohort model to assess the secular trends. There was a slight alternation in age-standardized rate of mortality and DALY in the total population, while the changes were increased in males and decreased in females from 1990 to 2019. Meanwhile, the changes attributable to ambient particular matter pollution exposure (APE) increased significantly and reduced household air pollution from solid fuels exposure (HPE). Longitudinal age curves showed that T2DM mortality and DALY increased with age. Period rate ratios (RR) attributable to APE increased but fell to HPE. Similar trends were observed in the cohort RR. PM2.5 exposure is more harmful to males and older people. The type of air pollution responsible for T2DM has changed from HPE to APE.

Aggregation of type-2 diabetes, prediabetes, and metabolic syndrome in German couples

We aimed to examine the concordance of type-2 diabetes, prediabetes and the metabolic syndrome in couples. In cross-sectional analyses, we used data from 1173 couples with index persons from the Heinz Nixdorf Recall Study (2011-2015), a population-based cohort study in Western Germany, and partners from the associated Heinz Nixdorf Multigeneration Study (2013-2016). Mean age (standard deviation) was 67.2 (6.6) years in index persons, and 67.8 (7.7) years in partners. The exposure was the presence of diabetes, prediabetes or metabolic syndrome in index persons, the outcome was the presence of the same health status in partners. Diabetes was defined by either self-reported diagnosis, intake of antidiabetic drugs or insulin, or HbA1c ≥ 6.5%. If the index person had prediabetes or diabetes, the partner was 1.46 (95% CI 1.07-2.00) times more likely to have diabetes than partners of index persons without the condition in the crude model (adjusted model: 1.33 (0.97-1.83)). For self-reported diabetes and for the metabolic syndrome, the corresponding prevalence ratios were 1.33 (0.90-1.97) and 1.17 (1.03-1.32), respectively (adjusted models: 1.23 (0.77-1.94), 1.04 (0.91-1.18)). In German couples, there was weak to moderate concordance of type-2 diabetes, prediabetes and the metabolic syndrome in crude, but poor concordance in adjusted models.

Toxicity and health effects of ultrafine particles: Towards an understanding of the relative impacts of different transport modes

Exposure to particulate matter (PM) has been associated with a wide range of adverse health effects, but it is still unclear how particles from various transport modes differ in terms of toxicity and associations with different human health outcomes. This literature review aims to summarize toxicological and epidemiological studies of the effect of ultrafine particles (UFPs), also called nanoparticles (NPs, <100 nm), from different transport modes with a focus on vehicle exhaust (particularly comparing diesel and biodiesel) and non-exhaust as well as particles from shipping (harbor), aviation (airport) and rail (mainly subway/underground). The review includes both particles collected in laboratory tests and the field (intense traffic environments or collected close to harbor, airport, and in subway). In addition, epidemiological studies on UFPs are reviewed with special attention to studies aimed at distinguishing the effects of different transport modes. Results from toxicological studies indicate that both fossil and biodiesel NPs show toxic effects. Several in vivo studies show that inhalation of NPs collected in traffic environments not only impacts the lung, but also triggers cardiovascular effects as well as negative impacts on the brain, although few studies compared NPs from different sources. Few studies were found on aviation (airport) NPs, but the available results suggest similar toxic effects as traffic-related particles. There is still little data related to the toxic effects linked to several sources (shipping, road and tire wear, subway NPs), but in vitro results highlighted the role of metals in the toxicity of subway and brake wear particles. Finally, the epidemiological studies emphasized the current limited knowledge of the health impacts of source-specific UFPs related to different transport modes. This review discusses the necessity of future research for a better understanding of the relative potencies of NPs from different transport modes and their use in health risk assessment.

Associations of air pollutant concentrations with longitudinal kidney function changes in patients with chronic kidney disease

This longitudinal cohort study investigated the associations of air pollutant exposures, including CO, NO, NO₂, NO_x, O₃, PM₁₀, PM_2.5, and SO₂, with long-term kidney function changes in patients with chronic kidney disease (CKD). We enrolled 447 CKD patients who took part in a universal hospital pre-ESRD care program during 2011-2015. The daily average air pollutant exposures and temperature were estimated for each patient, with different levels of air pollutant concentrations defined by 5-knot and restricted cubic spline function. Predicted annual estimated glomerular filtration (eGFR) slope values by one mixed model were considered as the study outcome. The average age of the study population was 77.1 ± 12.6 years, and the median annual eGFR decreased by 2.1 ml/min/1.73 m² per year from 30 ml/min/1.73 m² at baseline during a mean follow-up time of 3.4 years. The univariable and multivariable analyses revealed no significant linear and non-linear associations between 5-knot air pollutant concentrations and annual eGFR slope. In addition, the visualized spline effect plots show insignificant variation patterns in annual eGFR slope values with increased air pollutant concentrations. These results encourage more extensive studies to clarify the causal relationships and mechanisms of long-term specific air pollutant exposures and longitudinal kidney function change, especially in CKD populations.

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.

Mediation of metabolic syndrome in the association between long-term co-exposure to road traffic noise, air pollution and incident type 2 diabetes

OBJECTIVES

Recent studies have linked exposure to road traffic noise or air pollution with incident type 2 diabetes (T2D), but investigation on their co-exposure was limited and underlying mechanisms remain unclear. We hypothesized that long-term co-exposure to road traffic noise and air pollution increases the risk of incident T2D via the development of metabolic syndrome (MetS).

METHODS

This prospective study included 390,834 participants in UK Biobank. Cumulative risk index (CRI), the health-based weighted levels of multiple exposures, was applied to characterize the co-exposure to 24-hour road traffic noise (L_den), particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5), and nitrogen dioxide (NO₂). L_den was modeled by the Common Noise Assessment Methods in Europe and air pollutant levels were measured by the Land Use Regression model at participants' residential addresses. Incident T2D was ascertained through linkages to inpatient hospital records. MetS was defined by five (central obesity, triglycerides, HDL cholesterol, glucose, and blood pressure) or six factors (C-reactive protein additionally). Cox proportional hazard models were used to assess the association between environmental exposures and incident T2D, and mediation analyses were applied to investigate the role of MetS.

RESULTS

After a median of 10.9 years of follow-up, 13,214 (3.4%) incident T2D cases were ascertained. The exposure to L_den, PM_2.5, and NO₂, as well as their co-exposure, were significantly associated with an elevated risk of incident T2D, with HRs of 1.03 (95%CI: 1.00, 1.05) per 3.5 dB(A) increase in L_den, 1.05 (95%CI: 1.01, 1.10) per 1.3 μg/m³ increase in PM_2.5, 1.07 (95%CI: 1.02, 1.11) per 9.8 μg/m³ increase in NO₂, and 1.06 (95%CI: 1.02, 1.09) per interquartile range increase in CRI. MetS significantly mediated 43.5%- 54.7% of the CRI-T2D relationship.

CONCLUSIONS

Long-term co-exposure to road traffic noise and air pollution is associated with an elevated risk of incident T2D, which may partly be mediated by MetS.

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.

Diabetes and climate change: current evidence and implications for people with diabetes, clinicians and policy stakeholders

Climate change will be a major challenge for the world's health systems in the coming decades. Elevated temperatures and increasing frequencies of heat waves, wildfires, heavy precipitation and other weather extremes can affect health in many ways, especially if chronic diseases are already present. Impaired responses to heat stress, including compromised vasodilation and sweating, diabetes-related comorbidities, insulin resistance and chronic low-grade inflammation make people with diabetes particularly vulnerable to environmental risk factors, such as extreme weather events and air pollution. Additionally, multiple pathogens show an increased rate of transmission under conditions of climate change and people with diabetes have an altered immune system, which increases the risk for a worse course of infectious diseases. In this review, we summarise recent studies on the impact of climate-change-associated risk for people with diabetes and discuss which individuals may be specifically prone to these risk conditions due to their clinical features. Knowledge of such high-risk groups will help to develop and implement tailored prevention and management strategies to mitigate the detrimental effect of climate change on the health of people with diabetes.

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 long-term air pollution exposure with the risk of prediabetes and diabetes: Systematic perspective from inflammatory mechanisms, glucose homeostasis pathway to preventive strategies

BACKGROUND

Limited evidence suggests the association of air pollutants with a series of diabetic cascades including inflammatory pathways, glucose homeostasis disorder, and prediabetes and diabetes. Subclinical strategies for preventing such pollutants-induced effects remain unknown.

METHODS

We conducted a cross-sectional study in two typically air-polluted Chinese cities in 2018-2020. One-year average PM₁, PM_2.5, PM₁₀, SO₂, NO₂, and O₃ were calculated according to participants' residence. GAM multinomial logistic regression was performed to investigate the association of air pollutants with diabetes status. GAM and quantile g-computation were respectively performed to investigate individual and joint effects of air pollutants on glucose homeostasis markers (glucose, insulin, HbA1c, HOMA-IR, HOMA-B and HOMA-S). Complement C3 and hsCRP were analyzed as potential mediators. The ABCS criteria and hemoglobin glycation index (HGI) were examined for their potential in preventive strategy.

RESULTS

Long-term air pollutants exposure was associated with the risk of prediabetes [Prevalence ratio for O₃ (PR_O₃) = 1.96 (95% CI: 1.24, 3.03)] and diabetes [PR_PM₁ = 1.18 (95% CI: 1.05, 1.32); PR_PM_2.5 = 1.08 (95% CI: 1.00, 1.16); PR_O₃ = 1.35 (95% CI: 1.03, 1.74)]. PM₁, PM₁₀, SO₂ or O₃ exposure was associated with glucose-homeostasis disorder. For example, O₃ exposure was associated with increased levels of glucose [7.67% (95% CI: 1.75, 13.92)], insulin [19.98% (95% CI: 4.53, 37.72)], HOMA-IR [34.88% (95% CI: 13.81, 59.84)], and decreased levels of HOMA-S [-25.88% (95% CI: -37.46, -12.16)]. Complement C3 and hsCRP played mediating roles in these relationships with proportion mediated ranging from 6.95% to 60.64%. Participants with HGI ≤ -0.53 were protected from the adverse effects of air pollutants.

CONCLUSION

Our study provides comprehensive insights into air pollutant-associated diabetic cascade and suggests subclinical preventive strategies.

Chronic Exposure to Fine Particulate Matter Increases Mortality Through Pathways of Metabolic and Cardiovascular Disease: Insights From a Large Mediation Analysis

Background Long-term exposure to outdoor fine particulate matter (PM2.5) is the leading environmental risk factor for premature mortality worldwide. Characterizing important pathways through which PM2.5 increases individuals' mortality risk can clarify the PM2.5-mortality relationship and identify possible points of interventions. Recent evidence has linked PM2.5 to the onset of diabetes and cardiovascular disease, but to what extent these associations contribute to the effect of PM2.5 on mortality remains poorly understood. Methods and Results We conducted a population-based cohort study to investigate how the effect of PM2.5 on nonaccidental mortality is mediated by its impacts on incident diabetes, acute myocardial infarction, and stroke. Our study population comprised ≈200 000 individuals aged 20 to 90 years who participated in population-based health surveys in Ontario, Canada, from 1996 to 2014. Follow-up extended until December 2017. Using causal mediation analyses with Aalen additive hazards models, we decomposed the total effect of PM2.5 on mortality into a direct effect and several path-specific indirect effects mediated by diabetes, each cardiovascular event, or both combined. A series of sensitivity analyses were also conducted. After adjusting for various individual- and neighborhood-level covariates, we estimated that for every 1000 adults, each 10 μg/m3 increase in PM2.5 was associated with ≈2 incident cases of diabetes, ≈1 major cardiovascular event (acute myocardial infarction and stroke combined), and ≈2 deaths annually. Among PM2.5-related deaths, 31.7% (95% CI, 17.2%-53.2%) were attributable to diabetes and major cardiovascular events in relation to PM2.5. Specifically, 4.5% were explained by PM2.5-induced diabetes, 22.8% by PM2.5-induced major cardiovascular events, and 4.5% through their interaction. Conclusions This study suggests that a significant portion of the estimated effect of long-term exposure to PM2.5 on deaths can be attributed to its effect on diabetes and cardiovascular diseases, highlighting the significance of PM2.5 on deteriorating cardiovascular health. Our findings should raise awareness among professionals that improving metabolic and cardiovascular health may reduce mortality burden in areas with higher exposure to air pollution.

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

CONTEXT

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The association of specific industry-related air pollution with occurrence of chronic diseases: A register-based study

Air pollution may contribute to onset and progression of chronic diseases such as cardiovascular and respiratory diseases. Most studies have focused on the contribution of traffic-related exposure to PM₁₀ or PM_2.5. Our aim was to investigate the association of different components of industry-related air pollution on the occurrence of chronic diseases. A register-based repeated cross-sectional study was conducted among 89,714 subjects (2012) with 536,599 annual observations (2012-2017) living in the vicinity of a large industrial area in the Netherlands. Information from the dispensed medication registration was linked with a dispersion model to characterize annual individual-level exposure of all subjects at place of residence. Associations between annual exposure (concentration and duration) to particulate matter (PM₁₀), nitrogen oxides (NO_X), sulphur dioxide (SO₂), and volatile organic compounds (VOC) with annual dispensed medication for cardiovascular diseases, respiratory diseases, diabetes mellitus, and inflammatory conditions were investigated by multivariate logistic regression analysis with generalized estimating equations (GEE) while controlling for confounders. Exposure to PM₁₀ and to NO_X (per μg/m³) were significantly associated with medication for cardiovascular diseases (OR 1.06, 95CI% 1.06-1.06 and OR 1.01, 95%CI 1.01-1.01 respectively). Exposures to PM₁₀ and SO₂ (per μg/m³) were significantly associated with medication for inflammatory conditions (OR 1.05, 95%CI 1.00-1.09 and OR 1.07, 95%CI 1.01-1.14 respectively). Exposure to SO₂ was inversely associated with respiratory diseases (OR 0.91, 95%CI 0.86-0.97). Except for inflammatory conditions, exposure duration (years) was significantly associated with the other three chronic diseases (OR varying from 1.01 to 1.03). This study indicates that specific air pollution components caused by industry may contribute to the occurrence of cardiovascular diseases, respiratory diseases, diabetes mellitus, and inflammatory conditions.

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.

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.

Acute effect of particulate matter pollution on hospital admissions for stroke among patients with type 2 diabetes in Beijing, China, from 2014 to 2018

BACKGROUND

The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown.

METHODS

A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends.

RESULTS

A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM_2.5 and PM₁₀ in relation to stroke admissions among T2D patients. A 10 μg/m³ increase in the four-day moving average of PM_2.5 and PM₁₀ was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m³ increase in PM_2.5 in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m³ increase in PM₁₀ in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke.

CONCLUSIONS

High particulate matter might be a risk factor for stroke among patients with T2D. PM_2.5 and PM₁₀ have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.

Dietary Tryptophan and the Risk of Metabolic Syndrome: Total Effect and Mediation Effect of Sleep Duration

PURPOSE

Tryptophan affects energy homeostasis, glucose metabolism, blood pressure, and sleep. However, studies investigating the association between tryptophan and metabolic syndrome (MetSyn) are rare. We aimed to investigate the associations of dietary tryptophan with MetSyn incidence and potential mediation via sleep duration.

METHODS

Data of 7890 participants were obtained from the China Health and Nutrition Survey (1997-2011) (male: 49.9%; mean age=43.43 years;median follow-up=129.76 months; MetSyn incidence: 16.3%). A combination of individual 24-hour recall and household survey was used to assess dietary intake. In total, 6720 and 4474 participants who reported sleep duration and had blood samples taken, respectively, were incorporated into subgroup analyses. MetSyn was defined according to National Cholesterol Education Program Adult Treatment Panel (NCEP ATP) III criteria (2004), and tryptophan consumption and sleep duration were assessed by self-report in each survey. Multivariate Cox regression models were used to assess the associations between tertiles of tryptophan intake and MetSyn. Generalized linear regression models were used to evaluate the effect of tryptophan on sleep duration and plasma biomarkers.

RESULTS

Dietary tryptophan showed a protective effect on the risk of MetSyn. The hazard ratio (95% CI) of MetSyn was 0.77 (0.65-0.90) for individuals with a high tertile of tryptophan. Sleep duration was significantly higher, and HbA_1c, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (APO-B) were lower in the high tertile of tryptophan compared to the low tertile (P<0.05). In addition, mediation effects on the association between tryptophan intake and MetSyn risk were observed for sleep duration (estimated mediation percentage: 26.5%).

CONCLUSION

Our study demonstrated a negative association between dietary tryptophan and MetSyn incidence, and the mediation effect of sleep duration on this association, after adjusting for numerous confounders such as nutrients and food patterns. These findings may have important public health implications for the improvement of cardiometabolic health.

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.