Chemical components of respirable particulate matter associated with emergency hospital admissions for type 2 diabetes mellitus in Hong Kong

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China

BACKGROUND

The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome.

METHODS AND RESULTS

A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05).

CONCLUSIONS

Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

Early-life exposure to ambient air pollution with cardiovascular risk factors in adolescents: Findings from the "Children of 1997" Hong Kong birth cohort

BACKGROUND

Long-term exposure to ambient air pollution is associated with cardiovascular disease (CVD) risk. Little is known about the impact of early-life exposure to air pollutants on CVD risk factors in late adolescence, which may track into adulthood. To clarify, we examined this question in a unique setting with high air pollution and a high level of economic development.

METHODS

This study leveraged the "Children of 1997" Hong Kong birth cohort (N = 8327), including here 3350 participants. We estimated ambient air pollutant exposure including inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and nitrogen monoxide (NO) by growth phase (in utero, infancy, childhood) and overall based on residential address. Generalized linear regression was used to assess the associations of air pollutants exposure by growth phase and sex with CVD risk factors (fasting blood glucose, glycosylated hemoglobin, lipid profile, blood pressure, and body mass index) at 17.6 years. We also assessed whether associations varied by sex.

RESULTS

Early life exposed had little association with glucose metabolism, blood pressure or body mass index, but after considering multiple comparisons early exposure to PM10 was associated with low density lipoprotein (LDL) in boys, with β and 95 % confidence intervals (95 % CI) of 0.184 (0.069 to 0.298) mmol/l, 0.151 (0.056 to 0.248) mmol/l, and 0.157 (0.063 to 0.252) mmol/l by per interquartile range (IQR) increment of PM10 for in utero, infancy, and overall, respectively. No such associations were evident for girls, differences by sex were evident.

CONCLUSIONS

Our study suggested sex-specific associations of early-life PM10 exposure with elevated LDL in adolescence, especially exposure in utero and infancy.

Polychlorinated biphenyls exposure and type 2 diabetes: Molecular mechanism that causes insulin resistance and islet damage

Polychlorinated biphenyls (PCBs) are typical persistent organic pollutants that have been associated with type 2 diabetes (T2DM) in cohort studies. This review aims to comprehensively assess the molecular mechanisms of PCBs-induced T2DM. Recent progress has been made in the research of PCBs in liver tissue, adipose tissue, and other tissues. By influencing the function of nuclear receptors, such as the aryl hydrocarbon receptor (AhR), pregnancy X receptor (PXR), and peroxisome proliferator activated receptor γ (PPARγ), as well as the inflammatory response, PCBs disrupt the balance of hepatic glucose and lipid metabolism. This is associated with insulin resistance (IR) in the target organ of insulin. Through androgen receptor (AR), estrogen receptor α/β (ERα/β), and pancreato-duodenal-homeobox gene-1 (PDX-1), PCBs affect the secretion of insulin and increase blood glucose. Thus, this review is a discussion on the relationship between PCBs exposure and the pathogenesis of T2DM. It is hoped to provide basic concepts for diabetes research and disease treatment.

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

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

The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China

Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study

OBJECTIVES

Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults.

METHODS

We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent.

RESULTS

Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals.

CONCLUSION

Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.

Association between ambient PM1 and semen quality: A cross-sectional study of 27,854 men in China

BACKGROUND

Exposure to ambient fine and respirable particulate matter is associated with poor sperm quality, but evidence for particulate matter with an aerodynamic diameter ≤ 1 μm (PM₁) is scarce. We aimed to estimate the association between PM₁ exposure and sperm concentration, sperm count, sperm total motility, and sperm progressive motility in Chinese men.

METHODS

We conducted a cross-sectional study of 33,221 men attending an infertility clinic in Hubei, China, between 2014 and 2020. Daily concentrations of PM₁ data were estimated from a validated spatiotemporal artificial intelligence model. We used multivariate linear regression to estimate the association between PM₁ exposure and sperm parameters during the spermatogenesis period after adjusting for age, body mass index (BMI), education, ever having fathered a child, and season of semen collection. In addition, we performed stratified analysis to assess whether the association was varied by age, BMI, and educational attainment.

RESULTS

A total of 27,854 participants were included in the final analysis. An interquartile range (17.2 μg/m³) increase in PM₁ during the entire period of semen development was associated with declined semen concentration [-4.39% (95% CI: -7.67%, -1.12%)] and sperm count [-23.56% (95% CI: -28.95%, -18.18%)], reduced total motility [-0.86% (95% CI: -1.66%, -0.06%)] and progressive motility [-2.22% (95% CI: -3.00%, -1.43%)]. The associations were homogeneous across subgroups defined by age and education, but were more pronounced among men with underweight for sperm concentration and sperm count. We identified a critical exposure window of 0-9 lag days, 10-14 lag days, and 70-90 lag days before semen collection for sperm count and progressive motility.

CONCLUSIONS

Among men attending an infertility clinic in China, exposure to PM₁ was associated with poor semen quality, especially during the 70-90 days before ejaculation. These results suggest that exposure to PM₁ might be a novel risk factor for impaired semen quality.

Ambient air pollution and hospitalization for type 2 diabetes in China: A nationwide, individual-level case-crossover study

Scarce evidence is available on the short-term association between air pollution and type 2 diabetes (T2D). We aimed to evaluate the associations between short-term exposure to six criteria air pollutants and hospitalization for T2D based on a national registry. We conducted an individual-level, time-stratified case-crossover study among inpatients with a primary diagnosis of T2D from 153 hospitals across 20 provincial regions in China (2013-2021). Daily concentrations of fine particulate matter (PM_2.5), inhalable particle (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and carbon monoxide (CO), and ozone were collected from the nearest monitoring stations. T2D patients were separated into those admission for T2D with and without complications. Distributed lag non-linear models combined with conditional logistic regressions were used to estimate the associations. A total of 88,904 patients were hospitalized for T2D. Short-term exposures to all six air pollutants above except for ozone were significantly associated with the risk of hospitalization for T2D and both subclasses. An interquartile range increase in the concentrations of PM_2.5, PM₁₀, NO₂, SO₂, and CO at lag 0-2 d was associated with higher hospitalization risk of T2D by 1.71% (95%CI: 0.56%, 2.87%), 2.08% (0.88%, 3.29%), 4.85% (3.29%, 6.44%), 2.44% (1.22%, 3.67%) and 2.55% (1.24%, 3.88%), respectively. The associations of T2D hospitalizations were stronger in cold season than in warm season. Air pollutants had more acute and stronger associations with T2D with complications. The exposure-response relationship curves showed no thresholds, and the slopes were larger for T2D with complications. This nationwide individual-level, case-crossover study provides the first comprehensive evidence that short-term exposure to multiple criteria air pollutants may increase the risk of hospitalizations for T2D, especially for T2D with complications.

Long-term Exposure to Ambient PM2.5 and Its Components Associated With Diabetes: Evidence From a Large Population-Based Cohort From China

OBJECTIVE

Association between particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) components and diabetes remains unclear. We therefore aimed to investigate the associations of long-term exposure to PM2.5 components with diabetes.

RESEARCH DESIGN AND METHODS

This study included 69,210 adults with no history of diabetes from a large-scale epidemiologic survey in Southwest China from 2018 to 2019. The annual average concentrations of PM2.5 and its components were estimated using satellite remote sensing and chemical transport modeling. Diabetes was identified as fasting plasma glucose ≥7.0 mmol/L (126 mg/dL) or hemoglobin A1c ≥48 mmol/mol (6.5%). The logistic regression model and weighted quantile sum method were used to estimate the associations of single and joint exposure to PM2.5 and its components with diabetes, respectively.

RESULTS

Per-SD increases in the 3-year average concentrations of PM2.5 (odds ratio [OR] 1.08, 95% CI 1.01-1.15), black carbon (BC; 1.07, 1.01-1.15), ammonium (1.07, 1.00-1.14), nitrate (1.08, 1.01-1.16), organic matter (OM; 1.09, 1.02-1.16), and soil particles (SOIL; 1.09, 1.02-1.17) were positively associated with diabetes. The associations were stronger in those ≥65 years. Joint exposure to PM2.5 and its components was positively associated with diabetes (OR 1.04, 95% CI 1.01-1.07). The estimated weight of OM was the largest among PM2.5 and its components.

CONCLUSIONS

Long-term exposure to BC, nitrate, ammonium, OM, and SOIL is positively associated with diabetes. Moreover, OM might be the most responsible for the relationship between PM2.5 and diabetes. This study adds to the evidence of a PM2.5-diabetes association and suggests controlling sources of OM to curb the burden of PM2.5-related diabetes.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

K-means cluster analysis of cooperative effects of CO, NO2, O3, PM2.5, PM10, and SO2 on incidence of type 2 diabetes mellitus in the US

Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex mixture of components for which the composition depends on sources and metrological factors. The US Environmental Protection Agency (EPA) monitors and regulates certain components of air pollution known to have negative consequences for human health. Research assessing the health effects of these components of AP often uses traditional regression models, which might not capture more complex and interdependent relationships. Machine learning has the capability to simultaneously assess multiple components and find complex, non-linear patterns that may not be apparent and could not be modeled by other techniques. Here we use k-means clustering to assess the patterns associating PM2.5, PM10, CO, NO2, O3, and SO2 measurements and changes in annual diabetes incidence at a US county level. The average age adjusted annual decrease in diabetes incidence for the entire US populations is -0.25 per 1000 but the change shows a significant geographic variation (range: -17.2 to 5.30 per 1000). In this paper these variations were compared with the local daily AP concentrations of the pollutants listed above from 2005 to 2015, which were matched to the annual change in diabetes incidence for the following year. A total of 134,925 daily air quality observations were included in the cluster analysis, representing 125 US counties and the District of Columbia. K-means successfully clustered AP components and indicated an association between exposure to certain AP mixtures with lower decreases on T2D incidence.

Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China

Ambient PM_2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM_2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM_2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM_2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m³) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM_2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.

Health impacts and spatiotemporal variations of fine particulate and its typical toxic constituents in five urban agglomerations of China

Fine particulate matter (PM_2.5) and its constituents pose great threatens to public health. The spatial-temporal characteristics of some key chemical constituents, such as sulfate, nitrate, and especially toxic trace elements in China has remained unclear, limiting further studies on evaluating the associated public health. Here, we conduct a two-yearlong (2012 and 2015) air quality simulation by coupling localized emission inventory for primary air pollutants and trace elements with a modified CMAQ model in a domain of China and five urban agglomerations. Associated health burdens of PM_2.5 and various toxic trace elements are assessed applying exposure assessment models. The model successfully reproduces air pollution situations. Significant spatial-temporal variations of PM_2.5 and chemical constituents are observed, with higher concentrations mainly occurred in North China Plain (NCP), Fenwei Plain (FWP) and Sichuan-Chongqing Basin (SCB). All chemical constituents in PM_2.5 show higher concentrations in winter except for sulfate. From 2012 to 2015, the annual averaged PM_2.5 concentration and its constituents decreased by 3% -20% nationally and regionally. Smaller reductions of nitrate make PM_2.5 pollution become nitrate-dominated, especially in winter. Approximately 0.28 million deaths related to PM_2.5 in China are avoided, while the population affected by the cancer risks of Cr (VI) and arsenic has slightly increased from 2012 to 2015. Our findings could provide critical insights on the mitigation of air pollution, as well as benefit for epidemiological studies on air pollutants related health effects.

Long-term exposure to PM2.5 major components and mortality in the southeastern United States

BACKGROUND

Long-term exposure to fine particulate matter (PM_2.5) mass has been associated with adverse health effects. However, the health effects of PM_2.5 components have been less studied. There is a pressing need to better understand the relative contribution of components of PM_2.5, which can lay the scientific basis for designing effective policies and targeted interventions.

METHODS

We conducted a population-based cohort study, comprising all Medicare enrollees aged 65 or older in the southeastern United States from 2000 to 2016, to explore the associations between long-term exposure to PM_2.5 major components and all-cause mortality among the elderly. Based on well-validated prediction models, we estimated ZIP code-level annual mean concentrations for five major PM_2.5 components, including black carbon (BC), nitrate (NIT), organic matter (OM), sulfate (SO₄), and soil particles. Data were analyzed using Cox proportional hazards models, adjusting for potential confounders.

RESULTS

The cohort comprised 13,590,387 Medicare enrollees and a total of 107,191,652 person-years. In single-component models, all five major PM_2.5 components were significantly associated with elevated all-cause mortality. The hazard ratios (HR) per interquartile range (IQR) increase in exposure were 1.027 (95% CI: 1.025-1.030), 1.012 (95% CI: 1.010-1.013), 1.018 (95% CI: 1.017-1.020), 1.021 (95% CI: 1.017-1.024), and 1.004 (95% CI: 1.003-1.006) for BC, NIT, OM, SO₄, and soil particles, respectively. While the effect estimate of soil component was statistically significant, it is much smaller than those of combustion-related components.

CONCLUSION

Our study provides epidemiological evidence that long-term exposure to major PM_2.5 components is significantly associated with elevated mortality.

NLRP3 inflammasome is involved in ambient PM2.5-related metabolic disorders in diabetic model mice but not in wild-type mice

AIMS

To explore the role of nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome in ambient fine particulate matter (PM_2.5)-related metabolic disorders.

METHODS

In this study, the C57BL/6 and db/db mice were exposed to concentrated PM_2.5 or filtered air (FA) using Shanghai Meteorological and Environmental Animal Exposure System (Shanghai-METAS) for 12 weeks. Indices of lipid metabolism, glucose metabolism, insulin sensitivity, and protein expression of NLRP3 inflammasome in visceral adipose tissue (VAT) were measured, respectively.

RESULTS

The results showed that PM_2.5 exposure increased circulatory insulin, triglycerides (TG), and total cholesterol (TC), and decreased high-density lipoprotein (HDL) in both C57BL/6 and db/db mice. The levels of NLRP3-related circulatory inflammatory cytokines including both interleukin (IL)-18 and IL-1β in serum were increased in the PM_2.5-exposed mice and accompanied by the elevation in fasting blood glucose and insulin. The results also showed that exposure to PM_2.5 promoted the activation of NLRP3, pro-caspase-1, caspase-1, and apoptosis-associated speck-like protein containing CARD (ASC), simultaneously accompanied by the increase of IL-18 and IL-1β expression in VAT, but the statistically significant difference only found in the db/db mice, not in C57BL/6 mice.

CONCLUSION

The activation of NLRP3 inflammasome might be not the main mechanism of PM_2.5-related metabolic disorders in wide type mice but it partly mediated the exacerbation of metabolic disorders in diabetic model mice.

Meta-analyses of maternal exposure to atmospheric particulate matter and risk of congenital anomalies in offspring

Congenital anomalies are the main causes of infant death and disability. Previous studies have suggested that maternal exposure to particulate matter is related to congenital malformation. However, the conclusions of this study remain controversial. Hence, meta-analyses were performed to assess the relationship between maternal exposure to particulate matter and the risk of congenital anomalies. The Medline, Embase, and Web of Science databases were systemically searched from inception until August 2020 to find articles related to birth defects and particulate matter. The pooled risk estimated for the combination of pollution outcomes was calculated for each study by performing fixed effects or random effects models. The existence of heterogeneity and publication bias in relevant studies was also examined. Thirty studies were included in the analysis. A statistically increased summary risk valuation was found. PM₁₀ exposure was associated with an increased risk of congenital heart disease, neural tube defects, and cleft lip with or without cleft palate (OR per 10 μg/m³ = 1.05, 95% CI, 1.03-1.07; OR per 10 μg/m³ = 1.04, 95% CI, 1.01-1.06; OR per 10 μg/m³ = 1.03, 95% CI, 1.01-1.06). Maternal exposure to particulate matter might be associated with an increased risk of congenital anomalies. Our results indicate the dangers of particulate matter exposure on fetal development and the importance of protection against exposure to such particles during pregnancy. The schematic representation of the association between maternal exposure to PM_2.5/PM₁₀ and congenital anomalies in offspring, and geographic distribution of the included reports in the meta-analyses.

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM_2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China.

METHODS

The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM_2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders.

RESULTS

A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM_2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM_2.5 mass and accounting for multi-collinearity.

CONCLUSIONS

Exposure to PM_2.5 in 2^nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.

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

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

Does the AQHI reduce cardiovascular hospitalization in Hong Kong's elderly population?

BACKGROUND

Air quality alert programs have been introduced around the world to reduce the short term effects of air pollution on health. Hong Kong, a densely populated city in southern China with high levels of air pollution, introduced its first air quality health index (AQHI) on December 30th 2013. However, whether air quality alert program warnings, such as the AQHI, reduces morbidity is uncertain. Using a quasi-experimental design, we conducted the first evaluation of the AQHI in Hong Kong, focusing on cardiovascular morbidity in Hong Kong's elderly population.

METHOD

Interrupted time series with Poisson segmented regression from 2010 to 2016 was used to detect any sudden or gradual changes in emergency hospital admissions for cardiovascular diseases (CVD), after the AQHI policy was implemented. To account for potential confounders, models were adjusted for air pollutants (NO₂, SO₂, PM₁₀, O₃), temperature and humidity. The findings were validated using a negative control and three false policy periods. We also assessed effects on specific subtypes of CVD (hypertensive disease (HPD), acute myocardial infarction (AMI), heart failure, stroke and other CVD) and by sex.

RESULTS

From January 1st 2010 to December 31st, 2016, 375,672 hospital admissions for CVD occurred in Hong Kong's elderly population. Immediately after the policy HPD and AMI dropped by16% (relative risk (RR) 0.84, 95% confidence interval (CI): 0.78-0.91) and 15% (RR 0.85, 95% CI: (0.76-0.97)) respectively. There was no significant change for all CVD or other sub-types and no differences by sex.

CONCLUSION

Hong Kong's AQHI helped reduced hospital admissions in the elderly for HPD and AMI but had no effect on overall emergency hospitalization for CVD. To maximize health benefits of the policy, at risk groups need to be able to follow the behavioral changes recommended by the AQHI warnings.

Respirable Particulate Constituents and Risk of Cause-Specific Mortality in the Hong Kong Population

Emerging studies examined the associations of particulate matter constituents with nonaccidental and cardiorespiratory diseases, but few have investigated more specific causes of cardiorespiratory diseases or other system diseases, especially in Asia. We estimated the association between respirable particulate matter (PM₁₀) constituents and a spectrum of deaths using a quasi-Poisson time-series model in Hong Kong. Positive associations were identified between cause-specific deaths and elemental carbon, organic carbon (OC), nitrate, and potassium ion (K⁺), but only the associations for OC and K⁺ were robust in the two-constituent models adjusting for other constituents. The estimated effects of OC were strongest on mortality from the respiratory system with cumulative percent excess risk (ER%) of 3.82% (95% CI: 0.96%, 6.92%) per interquartile range (6.7 μg/m³) increase over 7 days prior to death (lag_0-7), especially for pneumonia (ER%: 4.32%; 95% CI: 0.70%, 8.26%). The digestive system was most sensitive to K⁺ with cumulative ER% of 6.74% (95% CI: 0.37%, 14.01%) per interquartile range (0.6 μg/m³) increase. This study indicates that PM₁₀ constituents from biomass burning (OC and K⁺) were more toxic than other constituents for deaths in Hong Kong, especially for mortalities from respiratory and digestive systems. These findings should have potential biological and pollution control implications.

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

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

Short-term and long-term exposures to fine particulate matter constituents and health: A systematic review and meta-analysis

BACKGROUND

Fine particulate matter (Particulate matter with diameter ≤ 2.5 μm) is associated with multiple health outcomes, with varying effects across seasons and locations. It remains largely unknown that which components of PM_2.5 are most harmful to human health.

METHODS

We systematically searched all the relevent studies published before August 1, 2018, on the associations of fine particulate matter constituents with mortality and morbidity, using Web of Science, MEDLINE, PubMed and EMBASE. Studies were included if they explored the associations between short term or long term exposure of fine particulate matter constituents and natural, cardiovascular or respiratory health endpoints. The criteria for the risk of bias was adapted from OHAT and New Castle Ottawa. We applied a random-effects model to derive the risk estimates for each constituent. We performed main analyses restricted to studies which adjusted the PM_2.5 mass in their models.

RESULTS

Significant associations were observed between several PM_2.5 constituents and different health endpoints. Among them, black carbon and organic carbon were most robustly and consistently associated with all natural, cardiovascular mortality and morbidity. Other potential toxic constituents including nitrate, sulfate, Zinc, silicon, iron, nickel, vanadium, and potassium were associated with adverse cardiovascular health, while nitrate, sulfate and vanadium were relevant for adverse respiratory health outcomes.

CONCLUSIONS

Our analysis suggests that black carbon and organic carbon are important detrimental components of PM_2.5, while other constituents are probably hazardous to human health. However, more studies are needed to further confirm our results.

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

Air pollution and type 2 diabetes mellitus (T2DM) are critical public health issues worldwide. A large number of epidemiological studies have highlighted the adverse effects of air pollution on diabetes, and include risk profiles for different exposure durations, study design types, subgroup populations, and effects of air pollution components. We researched PubMed, Google Scholar, and Web of Science to identify studies on the association between air pollution and T2DM from January 2009 to January 2019. The aim of this review is to provide a brief overview of epidemiological and experimental studies on air pollution associated with T2DM from the latest research, which may provide practical information about this relationship and possible mechanisms. Current cumulative evidence appears to suggest that T2DM-related biomarkers increase with increasing exposure duration and concentration of air pollutants. The chemical constituents of the air pollutant mixture may affect T2DM to varying degrees. The suggested mechanisms whereby air pollutants induce T2DM include increased inflammation, oxidative stress, and endoplasmic reticulum stress.

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

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

Short-term Effect of Ambient Air Pollution on Emergency Department Visits for Diabetic Coma in Seoul, Korea

Objectives

A positive association between air pollution and both the incidence and prevalence of diabetes mellitus (DM) has been reported in some epidemiologic and animal studies, but little research has evaluated the relationship between air pollution and diabetic coma. Diabetic coma is an acute complication of DM caused by diabetic ketoacidosis or hyperosmolar hyperglycemic state, which is characterized by extreme hyperglycemia accompanied by coma. We conducted a time-series study with a generalized additive model using a distributed-lag non-linear model to assess the association between ambient air pollution (particulate matter less than 10 μm in aerodynamic diameter, nitrogen dioxide [NO₂], sulfur dioxide, carbon monoxide, and ozone) and emergency department (ED) visits for DM with coma in Seoul, Korea from 2005 to 2009.

Methods

The ED data and medical records from the 3 years previous to each diabetic coma event were obtained from the Health Insurance Review and Assessment Service to examine the relationship with air pollutants.

Results

Overall, the adjusted relative risks (RRs) for an interquartile range (IQR) increment of NO₂ was statistically significant at lag 1 (RR, 1.125; 95% confidence interval [CI], 1.039 to 1.219) in a single-lag model and both lag 0-1 (RR, 1.120; 95% CI, 1.028 to 1.219) and lag 0-3 (RR, 1.092; 95% CI, 1.005 to 1.186) in a cumulative-lag model. In a subgroup analysis, significant positive RRs were found for females for per-IQR increments of NO₂ at cumulative lag 0-3 (RR, 1.149; 95% CI, 1.022 to 1.291).

Conclusions

The results of our study suggest that ambient air pollution, specifically NO₂, is associated with ED visits for diabetic coma.

Ambient Air Pollution and Morbidity in Chinese

The rapid economic growth in China is coupled with a severe ambient air pollution, which poses a huge threat to human health and the sustainable development of social economy. The rapid urbanization and industrialization over the last three decades have placed China as one of countries with the greatest disease burden in world. Notably, the prevalence rate of chronic noncommunicable diseases (CND), including respiratory diseases, CVD, and stroke, in 2010 reaches 16.9%. The continuous growth of the incidence of CND urgent needs for effective regulatory action for health protection. This study aims to evaluate the impact of rapid urbanization on status of ambient air pollution and associated adverse health effects on the incidence and the burden of CND and risk assessment. Our findings would be greatly significant in the prediction of the risk of ambient air pollution on CND and for evidence-based policy making and risk management in China.

Comparison of Health Impact of Air Pollution Between China and Other Countries

Air pollution is the world's largest single environmental risk according to the World Health Organization (WHO), which caused around seven million deaths in 2012. Extensive epidemiological studies have been carried out worldwide to examine the health impacts of ambient air pollution, consistently demonstrating significant health impacts of ambient air pollution. Air pollution problem in China is especially serious; it has become the fourth biggest threat to the health of the Chinese people. In this review, we summarized existing literature, compared health impact of air pollution between China and other countries, and found substantial heterogeneity in the risk estimates of air pollution. The effect heterogeneities may be due to the differences in the characteristics of populations (e.g., the proportion of the elder population and people with preexisting diseases), exposure profile (e.g., air pollution concentrations and composition), and regional climate. Although the magnitude of relative risk estimates of air pollution is generally similar with that in other parts of the world, air pollution is one of China's most serious environmental health problems given the huge number of people exposed to high concentration levels of air pollution in China.