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

Effects of sulfur dioxide inhalation on human health: a review

Sulfur dioxide (SO2) is one of the most important gaseous air pollutants and the chemical index of sulfur oxides (SOx). SO2 is one of the six criteria pollutants in the air quality index (AQI). SO2 can be emitted by natural and anthropogenic sources. Although efforts have been made to reduce sulfur dioxide emissions worldwide, this pollutant and its adverse effects remain a major concern, especially in developing countries. The aim of this study was the investigated the effects of sulfur dioxide inhalation on human health. This narrative review was done based on the literature published from 2000 to 2022 through PubMed, Springer, Web of Science, Science Direct, and Google Scholar databases. In this study, was done screened first based on the abstract and Final assessment done based on the full text of the article. Finally, 38 articles were selected for inclusion in the study. The results of this study showed that sulfur dioxide has adverse health effects on the human respiratory, cardiovascular, and nervous systems and causes type 2 diabetes and non-accidental deaths. Although some evidence suggests that sulfur dioxide in given concentrations has no adverse health effect, its synergistic effects in combination with other air pollutants may be significant. Among the most important practical results of this study can be mentioned to increase the health awareness of the general public, help the politicians of the health sector in making decisions in the health field, creating awareness among polluting producing units and industries and efforts to reduce the emission of Sulfur dioxide.

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

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

The impact of ambient air pollution on hospital admissions, length of stay and hospital costs for patients with diabetes mellitus and comorbid respiratory diseases in Panzhihua, Southwest China

Background

There is limited evidence on association between air pollutants and hospital admissions, hospital cost and length of stay (LOS) among patients with diabetes mellitus (DM) and comorbid respiratory diseases (RD), especially in low- and middle-income countries (LMICs) with low levels of air pollution.

Methods

Daily data on RD-DM patients were collected in Panzhihua from 2016 to 2020. A generalised additive model (GAM) was used to explore the effect of air pollutants on daily hospital admissions, LOS and hospital cost. Attributable risk was employed to estimate RD-DM's burden due to exceeding air pollution exposure, using both 0 microgrammes per cubic metre (μg/m3) and WHO's 2021 air quality guidelines as reference.

Results

For each 10 ug/m3 increase of particles with an aerodynamic diameter <2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter <10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), the admissions of RD-DM patients increased by 7.25% (95% CI = 4.26 to 10.33), 5.59% (95% CI = 3.79 to 7.42), 10.10% (95% CI = 7.29 to 12.98), 12.33% (95% CI = 8.82 to 15.95) and -2.99% (95% CI = -4.08 to -1.90); per 1 milligramme per cubic metre (mg/m3) increase of carbon monoxide (CO) corresponded to a 25.77% (95% CI = 17.88 to 34.19) increment for admissions of RD-DM patients. For LOS and hospital cost, the six air pollutants showed similar effect. Given 0 μg/m3 as the reference, NO2 showed the maximum attributable fraction of 32.68% (95% CI = 25.12 to 39.42%), corresponding to an avoidable burden of 5661 (95% CI = 3611 to 5860) patients with RD-DM.

Conclusions

There is an association between PM2.5, PM10, SO2, NO2, and CO with increased hospital admissions, LOS and hospital cost in patients with RD-DM. Disease burden of RD-DM may be improved by formulating policies related to air pollutants exposure reduction, especially in LMICs with low levels of air pollution.

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

OBJECTIVES

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

DESIGN

Systematic review of the literature.

DATA SOURCES

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

ELIGIBILITY CRITERIA

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

DATA EXTRACTION AND SYNTHESIS

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

RESULTS

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

CONCLUSION

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

PROSPERO REGISTRATION NUMBER

CRD42020214852.

Association of long-term exposure to PM2.5 constituents with glucose metabolism in Chinese rural population

BACKGROUND

Evidence on the associations of fine particulate matter (PM_2.5) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM_2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent.

METHODS

A total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015-2017. Three-year averaged concentrations of PM_2.5 mass and its constituents (black carbon (BC), ammonium (NH₄⁺), nitrate (NO₃^-), organic matter (OM), inorganic sulfate (SO₄^2-), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM_2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent.

RESULTS

The adjusted odds ratio (OR) for T2DM associated with 1 μg/m³ increase was 1.02 for PM_2.5 mass, 1.28 for BC, 1.15 for NH₄⁺, 1.08 for NO₃^-, 1.10 for OM, 1.11 for SO₄^2-, and 1.12 for SOIL. Significant associations of PM_2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM_2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m³ increment in the PM_2.5-adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β.

CONCLUSIONS

PM_2.5 mass and its constituents (BC, NH₄⁺, NO₃^-, OM, SO₄^2-, SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Metabolism toxicity and susceptibility of decabromodiphenyl ether (BDE-209) exposure on BRL cells with insulin resistance

Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance (IR) and has attracted worldwide attention due to its high prevalence. As a typical persistent organic pollutant, decabromodiphenyl ether (BDE-209) has been detected in food and human samples, and the concentration trends increase year by year. In addition, it has been proved to have the potential to increase the risk of IR, but it is rarely reported whether it could aggravate IR in T2DM. Therefore, in this study, the IR-BRL (buffalo rat liver cells with IR) model was applied to study the metabolism toxicity and susceptibility of BDE-209. Results showed that BDE-209 could inhibit glucose absorption and increase the levels of serum total cholesterol (TC) and triglyceride (TG), ultimately leading to the disorder of glucolipid metabolism in IR-BRL cells. Besides, it also could cause cell damage by increasing the levels of aspartate transaminase (AST), alanine aminotransferase (ALT), and malondialdehyde (MDA) in cells. Moreover, its potential mechanisms were to: (1) affect the transport of glucose, synthesis of glycogen and fatty acid via IRS-1/GLUT4 and IRS-1/PI3K/AKT/GSK-3β pathways; (2) impact the proliferation and differentiation by regulating the expression of Mek1/2, Erk1/2, and mTOR proteins and genes. Furthermore, susceptibility analysis showed that there was a significant synergism interaction between IR and BDE-209, which suggested that IR-BRL cells were more susceptible to the metabolism toxicity induced by BDE-209.

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

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

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

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

Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark

OBJECTIVE

Air pollution, road traffic noise and lack of greenness coexist in urban environments and have all been associated with type 2 diabetes. We aimed to investigate how these co-exposures were associated with type 2 diabetes in a multi-exposure perspective.

METHODS

We estimated 5-year residential mean exposure to fine particles (PM_2.5), ultrafine particles (UFP), elemental carbon (EC), nitrogen dioxide (NO₂) and road traffic noise at the most (LdenMax) and least (LdenMin) exposed facade for all persons aged > 50 years living in Denmark in 2005 to 2017. For each air pollutant, we estimated total concentrations and traffic contributions. Based on land use maps, we estimated proportion of green and non-green space within 150 and 1000 m of all residences. In total, 1.9 million persons were included and 128,358 developed type 2 diabetes during follow-up. We performed analyses using Cox proportional hazards models, with adjustment for individual and neighborhood-level sociodemographic co-variates.

RESULTS

In single-pollutant models, all air pollutants, noise and lack of green space were associated with higher risk of diabetes. In two-, three- and four-pollutant analyses of the air pollutants, only UFP and NO₂ remained associated with higher diabetes risk in all models. LdenMax, LdenMin and the two proxies of green space remained associated with diabetes in two-pollutant models of, respectively, noise and green space. In a multi-pollutant analysis, we found hazard ratios (95 % confidence intervals) per interquartile range of 1.021 (1.005; 1.038) for UFP, 1.012 (0.996; 1.028) for NO₂, 1.022 (1.012; 1.033) for LdenMin, 1.013 (1.004; 1.022) for LdenMax, and 1.038 (1.031; 1.044) and 1.018 (1.010; 1.025) for lack of green space within, respectively, 150 m and 1000 m, and a cumulative risk index of 1.131 (1.113; 1.149).

CONCLUSIONS

Air pollution, road traffic noise and lack of green space were independently associated with higher risk of type 2 diabetes.

Ambient air pollution associated with incidence and dynamic progression of type 2 diabetes: a trajectory analysis of a population-based cohort

BACKGROUND

Though the association between air pollution and incident type 2 diabetes (T2D) has been well documented, evidence on the association with development of subsequent diabetes complications and post-diabetes mortality is scarce. We investigate whether air pollution is associated with different progressions and outcomes of T2D.

METHODS

Based on the UK Biobank, 398,993 participants free of diabetes and diabetes-related events at recruitment were included in this analysis. Exposures to particulate matter with a diameter ≤ 10 μm (PM₁₀), PM_2.5, nitrogen oxides (NO_x), and NO₂ for each transition stage were estimated at each participant's residential addresses using data from the UK's Department for Environment, Food and Rural Affairs. The outcomes were incident T2D, diabetes complications (diabetic kidney disease, diabetic eye disease, diabetic neuropathy disease, peripheral vascular disease, cardiovascular events, and metabolic events), all-cause mortality, and cause-specific mortality. Multi-state model was used to analyze the impact of air pollution on different progressions of T2D. Cumulative transition probabilities of different stages of T2D under different air pollution levels were estimated.

RESULTS

During the 12-year follow-up, 13,393 incident T2D patients were identified, of whom, 3791 developed diabetes complications and 1335 died. We observed that air pollution was associated with different progression stages of T2D with different magnitudes. In a multivariate model, the hazard ratios [95% confidence interval (CI)] per interquartile range elevation in PM_2.5 were 1.63 (1.59, 1.67) and 1.08 (1.03, 1.13) for transitions from healthy to T2D and from T2D to complications, and 1.50 (1.47, 1.53), 1.49 (1.36, 1.64), and 1.54 (1.35, 1.76) for mortality risk from baseline, T2D, and diabetes complications, respectively. Generally, we observed stronger estimates of four air pollutants on transition from baseline to incident T2D than those on other transitions. Moreover, we found significant associations between four air pollutants and mortality risk due to cancer and cardiovascular diseases from T2D or diabetes complications. The cumulative transition probability was generally higher among those with higher levels of air pollution exposure.

CONCLUSIONS

This study indicates that ambient air pollution exposure may contribute to increased risk of incidence and progressions of T2D, but to diverse extents for different progressions.

Secular trends in global burden of diabetes attributable to particulate matter pollution from 1990 to 2019

Increasing evidence suggests an association between fine particulate matter (PM2.5) exposure and type 2 diabetes mellitus. However, there is still a lack of comparative evaluation regarding diabetes burden due to ambient and indoor PM2.5 pollution at a global scale. This study attempts to provide a systematic and comprehensive profile for PM2.5-attributable burden of diabetes and its spatiotemporal trends, globally and regionally. Comparative estimates of diabetes attributable to ambient PM2.5 and household air pollution (HAP) from solid fuels for 204 countries and territories were derived from the Global Burden of Disease Study 2019. Globally, 292.5 (95% uncertainty interval: 207.1, 373.4) thousand deaths and 13.0 (9.1, 17.2) million disability-adjusted life years (DALYs) from diabetes were attributed to PM2.5 pollution in 2019, wherein more than two-thirds (67.3% deaths and 69.7% DALYs) were contributed by ambient PM2.5. Compared to 1990, age-standardized DALY rate (ASDR) in 2019 attributable to ambient PM2.5 increased by 85.9% (APC: 2.21% [2.15, 2.27]), while HAP-associated ASDR decreased by 37.9% (APC: - 1.66% [- 1.82, - 1.50]). We observed a negative correlation between SDI and APC in ASMR (rs =  - 0.5, p < 0.001) and ASDR (rs = -0.4, p < 0.001) among 204 countries and territories. HAP-related diabetes experienced a sharp decline during 1990-2019, while global burden of diabetes attributable to ambient PM2.5 was rising rapidly. The elderly and people in low-SDI countries suffered from the greatest burden of diabetes due to PM2.5 pollution. More targeted interventions should be taken by governments to reduce PM2.5 exposure and related diabetes burden.

Adverse associations of different obesity measures and the interactions with long-term exposure to air pollutants with prevalent type 2 diabetes mellitus: The Henan Rural Cohort study

BACKGROUND

Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries.

METHODS

A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015-2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO₂, PM₁, PM_2.5, and PM₁₀ were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S).

RESULTS

Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO₂, PM₁, PM_2.5 and PM₁₀ were related to a 2.96-fold (2.66-3.29), 2.87-fold (2.58-3.20), 2.98-fold (2.67-3.32) and 3.01-fold (2.70-3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found.

CONCLUSIONS

The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions.

Long-term exposure to ambient fine particulate matter (PM2.5) and associations with cardiopulmonary diseases and lung cancer in Taiwan: a nationwide longitudinal cohort study

BACKGROUND

Although a number of studies have reported on the health effects of fine particulate matter (PM2.5) exposure, particularly in North American and European countries as well as China, the evidence about intermediate to high levels of PM2.5 exposures is still limited. We aimed to investigate the associations between long-term exposure to PM2.5 and risk of cardiopulmonary disease incidence in Taiwan with intermediate levels of PM2.5 exposure.

METHODS

A cohort of Taiwanese adults, who participated in the 2001, 2005, 2009 and 2013 National Health Interview Surveys, was followed through 2016 to identify cardiopulmonary disease onset. Exposure to PM2.5 was estimated by incorporating a widespread monitoring network of air quality monitoring stations and microsensors. We used time-dependent Cox regression models to examine the associations between the PM2.5 exposures and health outcomes, adjusting for individual characteristics and ecological covariates. The natural cubic spline functions were used to explore the non-linear effects of the PM2.5 exposure.

RESULTS

A total of 62 694 adults from 353 towns were enrolled. Each 10-μg/m3 increase in 5-year average exposure to PM2.5 was associated with a 4.8% increased risk of incident ischaemic heart disease (95% CI: -3.3, 13.6), 3.9% increased risk of incident stroke (95% CI: -2.9, 11.1), 6.7% increased risk of incident diabetes (95% CI: 1.1, 12.7), 15.7% increased risk of incident lung cancer (95% CI: -0.9, 35.1) and 11.5% increased risk of incident chronic obstructive pulmonary disease (95% CI: -0.8, 25.2). The concentration-response curve showed that there was no statistical evidence of non-linearity for most of the disease outcomes except for ischaemic heart disease (P for non-linearity = 0.014).

CONCLUSIONS

Long-term exposure to intermediate levels of ambient PM2.5 was associated with cardiopulmonary health outcomes. Our study adds value to future application and national burden of disease estimation in evaluating the health co-benefits from ambient air pollution reduction policy in Asian countries.

Exposure to source-specific air pollution and risk for type 2 diabetes: a nationwide study covering Denmark

BACKGROUND

Only few epidemiological studies have investigated whether chronic exposure to air pollution from different sources have different impacts on risk of diabetes. We aimed to investigate associations between air pollution from traffic versus non-traffic sources and risk of type 2 diabetes in the Danish population.

METHODS

We estimated long-term exposure to traffic and non-traffic contributions of particulate matter with a diameter <2.5 µg (PM2.5), elemental carbon (EC), ultrafine particles (UFP) and nitrogen dioxide (NO2) for all persons living in Denmark for the period 2005-17. In total, 2.6 million persons aged >35 years were included, of whom 148 020 developed type 2 diabetes during follow-up. We applied Cox proportional hazards models for analyses, using 5-year time-weighted running means of air pollution and adjustment for individual- and area-level demographic and socioeconomic covariates.

RESULTS

We found that 5-year exposure to all particle measures (PM2.5, UFP and EC) and NO2 were associated with higher type 2 diabetes risk. We observed that for UFP, EC and potentially PM2.5, the pollution originating from traffic was associated with higher risks than the non-traffic contributions, whereas for NO2 similar hazard ratios (HR) were observed. For example, in two-source models, hazard ratios (HRs) per interquartile change in traffic UFP, EC and PM2.5 were 1.025, 1.045 and 1.036, respectively, whereas for non-traffic UFP, EC and PM2.5, the HRs were 1.013, 1.018 and 1.001, respectively.

CONCLUSIONS

Our finding of stronger associations with particulate matter from traffic compared with non-traffic sources implies that prevention strategies should focus on limiting traffic-related particulate matter air pollution.

Environmental risk factors of type 2 diabetes-an exposome approach

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

Mortality and Years of Life Lost in Diabetes Mellitus and Its Subcategories in China and Its Provinces, 2005-2020

OBJECTIVES

To analyze diabetes mellitus (DM) mortality and years of life lost (YLL) in different years and different subgroups at the national and regional levels in China from 2005 to 2020.

METHODS

We estimated mortality and YLL of DM and its subcategories for 31 provinces in China during 2005-2020 using multisource data from the National Mortality Surveillance System (NMSS).

RESULTS

The age standardized mortality rate (ASMR) of DM increased from 12.18 per 100,000 in 2005 to 13.62 per 100,000 in 2020, which was an increase of 11.86%. The ASMR of type 2 diabetes mellitus (T2DM) was much higher than that of type 1 diabetes mellitus (T1DM). The ASMR of T1DM remained stable, but the rate of T2DM increased, and the increase in male patients was higher than that in their female counterparts. At the same time, the burden of premature death was highest in the group ≥ 80 years old, and ASMR increased from 236.02 per 100,000 in 2005 to 358.86 per 100,000 in 2020. In 2005, the eastern region had the highest ASMR of DM, but the western region's ASMR grew faster and eventually became the highest in 2020. In addition, the YLL rate in the eastern region showed a downward trend; however, in the middle and western regions the YLL rate continued to rise, with that of the western region rapidly increasing.

CONCLUSION

A dramatically upward trend in DM deaths can be seen in China from 2005 to 2020. DM remains a chronic disease in urgent need of prevention and control, especially in the elderly and people in less-affluent provinces. We must put forward more targeted policies to effectively allocate medical resources and focus on high-risk groups to reduce the premature-mortality burden of DM and its subcategories.

The lag effect of exposure to PM2.5 on esophageal cancer in urban-rural areas across China

Exposure to PM2.5 pollution is a significant health concern and increases risks for cancers in China. However, the studies regarding the effect of PM2.5 and esophageal cancer incidence (ECI) among urban-rural areas are limited. In this study, we examined the sex- and area-specific association between exposure to PM2.5 and ECI, as well as explored the corresponding lag effects on ECI using a geographical weighted Poisson regression. We found significantly positive effect on ECI for males and females in different models, with the greatest increase of 1.44% (95% CI: 1.30%, 1.59%) and 2.42% (95% CI: 2.17%, 2.66%) in per 10 ug/m3 increase of PM2.5 for males and females at single year lag7 and lag4 after all covariates controlled, respectively. We also found that the long-term effect of PM2.5 on ECI was relatively stable at all moving average year lags. Moreover, rural areas had higher ECI risks for males (0.17%) and females (0.64%) with longer lag period than urban areas. In addition, higher risks for both sexes appeared in north, northwestern, and east China. The findings indicated that long-term exposure to PM2.5 was significantly associated with increased risks for ECI, which reinforce a comprehensive understanding for ECI related to PM2.5.

Investigating the association between long-term exposure to air pollution and greenness with mortality from neurological, cardio-metabolic and chronic obstructive pulmonary diseases in Greece

Long-term exposure to air pollution has been associated with increased natural-cause mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies have examined the potential synergistic effects of exposure to pollutants and greenness. We investigated the association between exposure to air pollution and greenness with nervous system related mortality, cardiometabolic and chronic obstructive pulmonary diseases (COPD) mortality in Greece, using an ecological study design. We collected socioeconomic and mortality data for 1035 municipal units from the 2011 Census. Annual PM_2.5, NO₂, BC and O₃ concentrations for 2010 were predicted at 100 × 100 m grids by hybrid land use regression models. The normalized difference vegetation index (NDVI) was used for greenness. We applied single and two-exposure Poisson regression models on standardized mortality rates accounting for spatial autocorrelation. We assessed interactions between pollutants and greenness. An interquartile range increase in PM_2.5, NO₂ and BC was associated with increased risk in mortality from diseases of the nervous system (relative risk (RR): 1.14, 95% confidence interval (CI): 1.01, 1.28); 1.03 (95% CI: 0.99, 1.07); 1.05 (95% CI: 1.00, 1.10) respectively) and from cerebrovascular disease (RR: 1.14, 95% CI: 1.10, 1.18); 1.02 (95% CI: 1.01, 1.04); 1.02 (95% CI: 1.00, 1.04) respectively). PM_2.5 was associated with ischemic heart disease mortality (RR: 1.05, 95% CI: 1.01, 1.10). We estimated inverse associations for all outcomes with O₃ and for mortality from diseases of the nervous system or COPD with greenness. Estimates were mostly robust to co-exposure adjustment. Interactions were identified between NDVI and O₃ or PM_2.5 on mortality from the diseases of the nervous system, with higher effect estimates in greener areas. Our findings support the adverse effects of air pollution and the beneficial role of greenness on cardiovascular and nervous system related mortality. Further research is needed on diabetes mellitus.

Association between long-term exposure to fine particulate matter and diabetic retinopathy among diabetic patients: A national cross-sectional study in China

BACKGROUND

While the relationship between ambient air pollution and diabetes mellitus has recently been reported, data on the association between fine particulate matter (PM_2.5) and diabetic complications are limited, especially in microvascular diseases such as diabetic retinopathy.

OBJECTIVES

To investigate the associations between long-term exposure to PM_2.5 and the prevalence of diabetic retinopathy in adult diabetic patients in rural China.

METHODS

The study population was based on the Rural Epidemiology for Glaucoma in China (REG-China), a national cross-sectional survey conducted in rural China. This analysis selected diabetic patients with or without diabetic retinopathy. A satellite-based spatiotemporal model was used to estimate personal PM_2.5 exposure. Logistic regression models were used to investigate the effect of long-term PM_2.5 exposure on diabetic retinopathy.

RESULTS

The analysis included 3111 diabetic participants, 329 of whom were diagnosed with diabetic retinopathy. The median level of exposure to PM_2.5 from 2000 to2016 was 59.9 μg/m³. For each 10 μg/m³ increase in PM_2.5, the adjusted odds ratio (95% confidence interval) for diabetic retinopathy was 1.41 (1.27, 1.57). In subgroup analyses, the effect of PM_2.5 on diabetic retinopathy was significantly stronger in participants who self-reported alcohol consumption.

CONCLUSION

These findings suggest that long-term exposure to high PM_2.5 was associated with the risk of diabetic retinopathy among diabetic patients in rural China.

Long-term exposure to particulate matter and residential greenness in relation to androgen and progesterone levels among rural Chinese adults

BACKGROUND

Population-based studies on the associations of long-term exposure to particulate matter (PM) with androgen and progesterone are still scant. Residential greenness is benefits health by promoting physical activity, reducing air pollution, and improving mental health, but it remains unclear whether it is related to androgen and progesterone levels among humans.

AIMS

This study aimed to explore the individual and interactive effects of PM and residential greenness on serum testosterone and progesterone levels among rural Chinese adults.

METHODS

A total of 6017 subjects were recruited from the baseline of the Henan Rural Cohort Study in 2016. Serum testosterone and progesterone were measured with liquid chromatography-tandem mass spectrometry. Particulate matters (PM) (PM₁, PM_2.5, and PM₁₀) were assessed by machine learning algorithms. Residential greenness was assessed using the normalized difference vegetation index (NDVI) within 500-m, 1000-m, and 3000-m buffers around participants' residences. The effects of air pollutants and residential greenness and their interaction on serum testosterone and progesterone levels were assessed using linear mixed-effects models with township as a random intercept.

RESULTS

After adjusting for potential confounding factors, a 1 μg/m³ increase in PM_2.5 or PM₁₀ was associated with a 0.037 or 0.030 ng/ml increase in serum testosterone, respectively, in females and with a 0.111 or 0.182 ng/ml decrease in serum progesterone, respectively, in males. A 1 μg/m³ increase in PM₁, PM_2.5 or PM₁₀ was associated with a 0.222, 0.306, or 0.295 ng/ml decrease in serum progesterone, respectively, among females. Moreover, a 0.1-unit increase in NDVI was associated with a 0.310 ng/ml increase in serum testosterone and a 0.170 ng/ml increased in serum progesterone in males, as well as with a 0.143 ng/ml increase in serum progesterone in females. Interaction effects of PM and residential greenness on serum testosterone and progesterone levels were observed, indicating that the effects of residential greenness on serum testosterone and progesterone were modified by high levels of PM. In addition, physical activity significantly mediated 2.92% of the estimated association between greenness and testosterone levels.

CONCLUSIONS

Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity.

Is industrial pollution detrimental to public health? Evidence from the world's most industrialised countries

BACKGROUND

Industrial pollution is considered to be a detrimental factor for human health. This study, therefore, explores the link between health status and industrial pollution for the top 20 industrialised countries of the world.

METHODS

Crude death rate is used to represent health status and CO2 emissions from manufacturing industries and construction, and nitrous oxide emissions are considered to be indicators of industrial pollution. Using annual data of 60 years (1960-2019), an unbalanced panel data estimation method is followed where (Driscoll, J. C. et al. Rev Econ Stat, 80, 549-560, 1998) standard error technique is employed to deal with heteroscedasticity, autocorrelation and cross-sectional dependence problems.

RESULTS

The research findings indicate that industrial pollution arising from both variables has a detrimental impact on human health and significantly increases the death rate, while an increase in economic growth, number of physicians, urbanisation, sanitation facilities and schooling decreases the death rate.

CONCLUSIONS

Therefore, minimisation of industrial pollution should be the topmost policy agenda in these countries. All the findings are consistent theoretically, and have empirical implications as well. The policy implication of this study is that the mitigation of industrial pollution, considering other pertinent factors, should be addressed appropriately by enunciating effective policies to reduce the human death rate and improve health status in the studied panel countries.

Long-term exposure to PM1 and PM2.5 is associated with serum cortisone level and meat intake plays a moderation role

BACKGROUND

Although short-term exposure to particulate matter (PM) was associated with increased glucocorticoids (GCs) levels, available evidence on associations of long-term exposure to PM and GCs levels is still scant. Previous studies has showed that meat intake is associated with sex hormones levels, but it is unknown whether meat intake is associated with GCs levels. Furthermore, the role of meat intake in the associations between PM and GCs levels remains unclear.

AIMS

The aims of this study were to explore the associations of long-term exposure to PM and GCs levels among Chinese rural adults, and the role of meat intake in these associations.

MATERIALS AND METHODS

A total of 6223 subjects were recruited from the Henan Rural Cohort Study. Serum GCs levels were measured with liquid chromatography-tandem mass spectrometry. The concentrations of PM (PM₁ and PM_2.5) for each subject were assessed with machine learning algorithms. The food frequency questionnaire (FFQ) was used to obtain each participant' information on meat intake. The effects of PM and meat intake on GCs levels were assessed using generalized linear models. In addition, modification analyses were performed to identify the role of meat intake played in the associations of PM with serum GCs levels.

RESULTS

Per 1 μg/m³ increment in PM₁ or PM_2.5 concentration was associated with a 0.364 ng/ml (95% confidence interval (CI): 0.234, 0.494) or 0.227 ng/ml (95%CI: 0.110, 0.343) increase in serum cortisone, respectively. In addition, the moderation effects of total meat intake and red meat intake on the associations of long-term exposure to PM₁ or PM_2.5 with serum cortisone were observed (P < 0.05), indicating that individuals who had high levels of PM₁ or PM_2.5 and meat intake were more susceptible to have a higher state of serum cortisone.

CONCLUSIONS

Our findings suggested that long-term exposure to PM₁ or PM_2.5 was associated with serum cortisone. Moreover, meat intake was found to be a significant moderator in the association of PM₁ or PM_2.5 with serum cortisone levels.

Long-term exposure to ambient PM2.5 and stroke mortality among urban residents in northern China

Evidence is still limited for the role of long-term PM_2.5 exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM_2.5 exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM_2.5-mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM_2.5 derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM_2.5, after adjusting for individual risk factors. The cross-product term of PM_2.5 exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM_2.5 with stroke mortality. Among the study participants, the annual mean level of PM_2.5 concentration was 66.3 μg/m³ ranging from 39.0 μg/m³ to 100.6 μg/m³. For each 10 μg/m³ increment in PM_2.5, the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM_2.5 decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM_2.5 exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change.

The Impact of Air Pollution on Hospitalization for Cardiovascular and Cerebrovascular Disease in Shenyang, China

Background:

The aim of this study was to investigate the overall impact of PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ on the admission of cardiovascular and cerebrovascular disease.

Methods:

We collected data on cardiovascular and cerebrovascular disease admissions from two hospitals in Shenyang Liaoning, China from Jan 2014 to Dec 2017, as well as daily measurements of six pollutants at 11 sites in Shenyang. The generalized additive model was used to assess the association between daily contaminants and admission to cardiovascular and cerebrovascular disease.

Results:

The single-contamination model showed a significant correlation between NO₂, O₃, PM₁₀ and cardiovascular and cerebrovascular diseases at lag0 day. Air pollutants had lag effects on different gender groups. Excess relative risks (ERs) associated with a 10 μg/m³ increase were 1.522(1.057, 1.988) on lag02 for NO₂, 0.547% (0.367%, 0.728%), 0.133% (0.061%, 0.205%) on lag3 for O₃ and PM₁₀. The dual pollutant model showed that the effects of NO₂, O₃, and PM₁₀ after adjusting the influence of other pollutants were still statistically significant.

Conclusion:

Short-term exposure to ambient air pollution (NO₂, O₃, and PM₁₀) may be associated with an increased risk of daily cardiovascular and cerebrovascular admission, which may provide reliable evidence for further understanding of the potential adverse effects of air pollution on cardiovascular and cerebrovascular diseases.