Effects of ambient particulate matter on fasting blood glucose: A systematic review and meta-analysis

Associations of insulin sensitivity and immune inflammatory responses with child blood lead (Pb) and PM2.5 exposure at an e-waste recycling area during the COVID-19 lockdown

Fine particular matter (PM2.5) and lead (Pb) exposure can induce insulin resistance, elevating the likelihood of diabetes onset. Nonetheless, the underlying mechanism remains ambiguous. Consequently, we assessed the association of PM2.5 and Pb exposure with insulin resistance and inflammation biomarkers in children. A total of 235 children aged 3-7 years in a kindergarten in e-waste recycling areas were enrolled before and during the Corona Virus Disease 2019 (COVID-19) lockdown. Daily PM2.5 data was collected and used to calculate the individual PM2.5 daily exposure dose (DED-PM2.5). Concentrations of whole blood Pb, fasting blood glucose, serum insulin, and high mobility group box 1 (HMGB1) in serum were measured. Compared with that before COVID-19, the COVID-19 lockdown group had lower DED-PM2.5 and blood Pb, higher serum HMGB1, and lower blood glucose and homeostasis model assessment of insulin resistance (HOMA-IR) index. Decreased DED-PM2.5 and blood Pb levels were linked to decreased levels of fasting blood glucose and increased serum HMGB1 in all children. Increased serum HMGB1 levels were linked to reduced levels of blood glucose and HOMA-IR. Due to the implementation of COVID-19 prevention and control measures, e-waste dismantling activities and exposure levels of PM2.5 and Pb declined, which probably reduced the association of PM2.5 and Pb on insulin sensitivity and diabetes risk, but a high level of risk of chronic low-grade inflammation remained. Our findings add new evidence for the associations among PM2.5 and Pb exposure, systemic inflammation and insulin resistance, which could be a possible explanation for diabetes related to environmental exposure.

Association between ambient particulate matter exposure and mitochondrial DNA copy number: A systematic review and meta-analysis

BACKGROUND

Ambient particulate matter (PM) has been recognized as inducing oxidative stress, which could contribute to mitochondrial damage and dysfunction. However, studies investigating the association between ambient PM and mitochondria, particularly mitochondrial DNA copy number (mtDNA-CN), have yielded inconsistent results.

METHODS

We conducted comprehensive literature searches to identify observational studies published before July 17, 2023, examining the association between ambient PM exposure and mtDNA-CN. Meta-analysis using random effects model was employed to calculate the pooled effect estimates for general individual exposures, as well as for prenatal exposure with specific trimester. Additionally, the quality and level of evidence for each exposure-outcome pair was evaluated.

RESULTS

A total of 10 studies were included in the systematic review and meta-analysis. The results indicated that general individual exposure to PM2.5 (β = -0.084, 95 % CI: -0.521, 0.353; I2 = 93 %) and PM10 (β = 0.035, 95 % CI: -0.129, 0.199; I2 = 95 %) did not significantly affect mtDNA-CN. Prenatal exposure to PM2.5 (β = 0.023, 95 % CI: -0.087, 0.133; I2 = 0 %) and PM10 (β = 0.006, 95 % CI: -0.135; 0.147; I2 = 51 %) were also not significantly associated with mtDNA-CN in offspring. The level of evidence for each tested exposure-outcome pair was assessed as "inadequate."

CONCLUSIONS

The findings of this systematic review and meta-analysis indicate that there is an "inadequate" strength of evidence for the association between general individual or prenatal exposure to ambient PM and mtDNA-CN. Future research necessitates studies with more rigorous design, enhanced control of confounding factors, and improved measures of exposure to substantiate our findings.

Assessment of the association between health problems and cooking fuel type, and barriers towards clean cooking among rural household people in Bangladesh

BACKGROUND

In low- and middle-income countries, households mainly use solid fuels like wood, charcoal, dung, agricultural residues, and coal for cooking. This poses significant public health concerns due to the emission of harmful particles and gases. To address these issues and support Sustainable Development Goals (SDGs), adopting cleaner cooking fuels like electricity and gas are acknowledged as a viable solution. However, access to these cleaner fuels is limited, especially in rural areas.

METHODS

This study conducted a face-to-face survey with 1240 individuals in rural Bangladesh to explore the link between health issues and cooking fuel type, as well as barriers to transitioning to clean cooking. Using a convenient sampling technique across four divisions/regions, the survey gathered socio-demographic and health data, along with information on clean cooking barriers through a semi-structured questionnaire. Binary and multivariable logistic regression analyses were then employed to identify significant associations between cooking fuel type and health problems.

RESULTS

The study revealed that a majority of participants (73.3%) relied on solid fuel for cooking. The use of solid fuel was significantly correlated with factors such as lower education levels, reduced family income, location of residence, and the experience of health issues such as cough, chest pressure while breathing, eye discomfort, diabetes, asthma, and allergies. Economic challenges emerged as the foremost obstacle to the adoption of clean cooking, accompanied by other contributing factors.

CONCLUSION

The use of solid fuel in rural Bangladeshi households poses substantial health risks, correlating with respiratory, eye, cardiovascular, and metabolic issues. Lower education and income levels, along with specific residential locations, were associated with higher solid fuel usage. Economic challenges emerged as the primary obstacle to adopting clean cooking practices. These findings emphasize the need for implementing strategies to promote clean cooking, address barriers, and contribute to achieving Sustainable Development Goal targets for health and sustainable energy access in Bangladesh.

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.

Cigarette smoking and PM2.5 might jointly exacerbate the risk of metabolic syndrome

Background

Cigarette smoking and particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) are major preventable cardiovascular mortality and morbidity promoters. Their joint role in metabolic syndrome (MS) pathogenesis is unknown. We determined the risk of MS based on PM2.5 and cigarette smoking in Taiwanese adults.

Methods

The study included 126,366 Taiwanese between 30 and 70 years old with no personal history of cancer. The Taiwan Biobank (TWB) contained information on MS, cigarette smoking, and covariates, while the Environmental Protection Administration (EPA), Taiwan, contained the PM2.5 information. Individuals were categorized as current, former, and nonsmokers. PM2.5 levels were categorized into quartiles: PM2.5 ≤ Q1, Q1 < PM2.5 ≤ Q2, Q2 < PM2.5 ≤ Q3, and PM2.5 > Q3, corresponding to PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3.

Results

The prevalence of MS was significantly different according to PM2.5 exposure (p-value = 0.0280) and cigarette smoking (p-value < 0.0001). Higher PM2.5 levels were significantly associated with a higher risk of MS: odds ratio (OR); 95% confidence interval (CI) = 1.058; 1.014-1.104, 1.185; 1.134-1.238, and 1.149; 1.101-1.200 for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. The risk of MS was significantly higher among former and current smokers with OR; 95% CI = 1.062; 1.008-1.118 and 1.531; 1.450-1.616, respectively, and a dose-dependent p-value < 0.0001. The interaction between both exposures regarding MS was significant (p-value = 0.0157). Stratification by cigarette smoking revealed a significant risk of MS due to PM2.5 exposure among nonsmokers: OR (95% CI) = 1.074 (1.022-1.128), 1.226 (1.166-1.290), and 1.187 (1.129-1.247) for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. According to PM2.5 quartiles, current smokers had a higher risk of MS, regardless of PM2.5 levels (OR); 95% CI = 1.605; 1.444-1.785, 1.561; 1.409-1.728, 1.359; 1.211-1.524, and 1.585; 1.418-1.772 for PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. After combining both exposures, the group, current smokers; PM2.5 > 38.205 μg/m3 had the highest odds (1.801; 95% CI =1.625-1.995).

Conclusion

PM2.5 and cigarette smoking were independently and jointly associated with a higher risk of MS. Stratified analyses revealed that cigarette smoking might have a much higher effect on MS than PM2.5. Nonetheless, exposure to both PM2.5 and cigarette smoking could compound the risk of MS.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.

KCNQ1 rs2237892 polymorphism modify the association between short-term ambient particulate matter exposure and fasting blood glucose: A family-based study

BACKGROUND

The association between particulate matter and fasting blood glucose (FBG) has shown conflicting results. Genome-wide association studies have shown that KCNQ1 rs2237892 polymorphism is associated with the risk of diabetes. Whether KCNQ1 rs2237892 polymorphism might modify the association between particulate matter and FBG is still uncertain.

METHODS

Data collected from a family-based cohort study in Northern China, were used to perform the analysis. A generalized additive Gaussian model was used to examine the short-term effects of air pollutants on FBG. We further conducted interaction analyses by including a cross-product term of air pollutants by rs2237892 within KCNQ1 gene.

RESULTS

A total of 4418 participants were included in the study. In the single pollutant model, the FBG level increased 0.0031 mmol/L with per 10 μg/m³ elevation in fine particular matter (PM_2.5) for lag 0 day. After additional adjustments for nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), similar results were observed for lag 0-2 days. As for particulate matter with particle size below 10 μm (PM₁₀), the significant association between the daily average concentration of the pollutant and FBG level was observed for lag 0-3 days. Additionally, rs2237892 in KCNQ1 gene modified the association between PM and FBG level. The higher risk of FBG levels associated with elevations in PM₁₀ and PM_2.5 were more evident as the number of risk allele C increased. Individuals with a CC genotype had the highest risk of elevation in FBG levels.

CONCLUSION

Short-term exposures to PM_2.5 and PM₁₀ were associated with higher FBG levels. Additionally, rs2237892 in KCNQ1 gene might modify the association between the air pollutants and FBG levels.

Association between household fuel combustion and diabetes among middle-aged and older adults in China: A cohort study

BACKGROUND

Few studies examined the associations of household fuel combustion with incident diabetes. The current study emphasizes the association of domestic fuel combustion with diabetes among middle- and older- Chinese.

METHODS

The data was extracted from a national and prospective cohort, the China Health and Retirement Longitudinal Study (CHARLS), which enrolled adults ≥ 45 years. A total of 4610 and 5570 participants were involved in heating and cooking-related analyses. Multivariable logistic models were conducted to assess the association of domestic fuel combustion for heating and cooking with diabetes. Furthermore, we also examined whether it differed from switching fuel types. Subgroup and interaction analyses were performed based on covariates to examine the robustness and find potential effect modifiers.

RESULTS

After about 5-year follow-up, 592 and 716 diabetes were diagnosed in heating and cooking-related analyses. Compared to cleaner fuel users, those who used solid fuel for heating [OR (95 % CI):1.32 (1.05-1.66)] maintained higher risks of incident diabetes. In addition, participants who were exposed to solid fuel for both heating and cooking [OR (95 % CI):1.55 (1.17-2.06)] might have further elevated diabetic risk. Those risks are likely to be attenuated if people switched cooking fuel from solid to cleaner [OR (95 % CI): 0.68 (0.53-0.89)].

CONCLUSIONS

Home solid fuel use for heating is associated with an increased risk of incident diabetes. If solid fuel was concurrently used for both cooking and heating, those risks might be further elevated. Interestingly, as compared to solid fuel users, the participants switching cooking fuel types from solid to cleaner presented reduced diabetic risk.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

The relationship between particulate matter and lung function of children: A systematic review and meta-analysis

There have been many studies on the relationship between fine particulate matter (PM_2.5) and lung function. However, the impact of short-term or long-term PM_2.5 exposures on lung function in children is still inconsistent globally, and the reasons for the inconsistency of the research results are not clear. Therefore, we searched the PubMed, Embase and Web of Science databases up to May 2022, and a total of 653 studies about PM_2.5 exposures on children's lung function were identified. Random effects meta-analysis was used to estimate the combined effects of the 25 articles included. PM_2.5 concentrations in short-term exposure studies mainly come from individual and site monitoring. And for every 10 μg/m³ increase, forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁) and peak expiratory flow (PEF) decreased by 21.39 ml (95% CI: 13.87, 28.92), 25.66 ml (95% CI: 14.85, 36.47) and 1.76 L/min (95% CI: 1.04, 2.49), respectively. The effect of PM_2.5 on lung function has a lag effect. For every 10 μg/m³ increase in the 1-day moving average PM_2.5 concentration, FEV₁, FVC and PEF decreased by 14.81 ml, 15.40 ml and 1.18 L/min, respectively. PM_2.5 concentrations in long-term exposure studies mainly obtained via ground monitoring stations. And for every 10 μg/m³ increase, FEV₁, FVC and PEF decreased by 61.00 ml (95% CI: 25.80, 96.21), 54.47 ml (95% CI: 7.29, 101.64) and 10.02 L/min (95% CI: 7.07, 12.98), respectively. The sex, body mass index (BMI), relative humidity (RH), temperature (Temp) and the average PM_2.5 exposure level modify the relationship between short-term PM_2.5 exposure and lung function. Our study provides further scientific evidence for the deleterious effects of PM_2.5 exposures on children's lung function, suggesting that exposure to PM_2.5 is detrimental to children's respiratory health. Appropriate protective measures should be taken to reduce the adverse impact of air pollution on children's health.

Effects of long-term PM2.5 exposure on metabolic syndrome among adults and elderly in Guangdong, China

BACKGROUND

We aimed to explore the association between long-term exposure to particulate matter ≤ 2.5 µm (PM_2.5) and metabolic syndrome (MetS) and its components including fasting blood glucose (FBG), blood pressure, triglyceride (TG), high-density lipoprotein cholesterol (HDL-c) and waist circumference among adults and elderly in south China.

METHODS

We surveyed 6628 participants in the chronic disease and risk factors surveillance conducted in 14 districts of Guangdong province in 2015. MetS was defined based on the recommendation by the Joint Interim Societies' criteria. We used the spatiotemporal land-use regression (LUR) model to estimate the two-year average exposure of ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and O₃) at individual levels. We recorded other covariates by using a structured questionnaire. Generalized linear mixed model was used for analysis.

RESULTS

A 10-μg/m³ increase in the two-year mean PM_2.5 exposure was associated with a higher risk of developing MetS [odd ratio (OR): 1.17, 95% confidence interval (CI): 1.01, 1.35], increased risk of fasting blood glucose level. (OR: 1.18, 95% CI: 1.02, 1.36), and hypertriglyceridemia (OR: 1.36, 95% CI: 1.18, 1.58) in the adjusted/unadjusted models (all P < 0.05). We found significant interaction between PM_2.5 and the region, exercise on the high TG levels, and an interaction with the region, age, exercise and grain consumption on FBG (P _interaction < 0.05).

CONCLUSIONS

Long-term exposure to PM_2.5 was associated with MetS, dyslipidemia and FBG impairment. Efforts should be made for environment improvement to reduce the burden of MetS-associated non-communicable disease.

Household solid fuel use with diabetes and fasting blood glucose levels among middle-aged and older adults in China

To explore the impacts of household solid fuel use for cooking and heating on diabetes and fasting blood glucose (FBG) levels, we used data from the China Health and Retirement Longitudinal Study, a national survey including middle-aged and older adults. Multivariable logistic and linear regression models were used to explore the relationship between household solid fuel use (coal, crop residue, and wood) for cooking and heating with diabetes and FBG levels. Subgroup analyses were also performed based on age, sex, region of residence, smoking status, and body mass index to examine potential interactions between the variables and household solid fuel use. Among the 6195 participants, 75.4% and 61.4%, respectively, used solid fuels for heating and cooking. Relative to clean fuel users, solid fuel users had higher odds of diabetes (heating: OR, 1.21; 95% CI, 1.01-1.44; cooking: OR, 1.31; 95% CI, 1.12-1.53) and higher FBG levels (heating: β = 3.23; 95% CI, 1.10-5.36; cooking: β = 2.86; 95% CI, 0.95-4.77). Simultaneous use of solid fuels for cooking/heating was also positively associated with diabetes (OR, 1.31; 95% CI, 1.07-1.61) and FBG (β = 4.30; 95% CI, 1.82-6.78). No significant interactions were detected between subgroup variables and the impacts of solid fuel use on diabetes and FBG. Household solid fuel use is positively associated with diabetes and FBG levels. These findings imply that inhibiting household solid fuel use may contribute to decreasing diabetes development in China.

Outdoor air quality and human health: An overview of reviews of observational studies

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NO_X, NO₂, O₃, PM₁₀, PM_2.5, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM_2.5, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM_2.5, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

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

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

Filtration of submicron dust by a dual-layer granular bed filter with an external electric field

To improve the filtration efficiency of submicron dust by dual-layer granular bed filters, filtration experiments for micro-silica powder were conducted for removing particles smaller than 1 μm that account for more than 96% (by volume) using a dual-layer granular bed filter with an external electric field. Electrostatic enhancement methods, including dust pre-charging, application of an electric field to the lower filter layer, and that to both the upper and lower filter layers, were examined. Results showed that the average filtration efficiency of a dual-layer granular bed filter for micro-silica powder without electric field was 76.52%, the average outlet dust concentration was 263.53 mg/m³, and the filtration cycle time was 73 min. With pre-charged dust, the average outlet dust concentration dropped to 82.51 mg/m³. A decrease in the thickness of the lower filter layer from 45 to 25 mm with electric field reduced the pressure drop from 2570 to 1770 Pa. Meanwhile, the application of an electric field to the lower/upper filter layer reduced the average outlet dust concentration to 25.98 mg/m³. Increasing the initial face velocity from 0.25 to 0.45 m/s increased the average outlet dust concentration from 25.98 to 30.27 mg/m³ and increased the pressure drop from 2570 to 3500 Pa.

Long-term exposure to ambient air pollution and metabolic syndrome in children and adolescents: A national cross-sectional study in China

BACKGROUND

The prevalence of metabolic syndrome (MetS) rapidly increased over the past decades. However, little evidence exists about the effects of long-term exposure to ambient air pollution on MetS in children and adolescents.

OBJECTIVE

This study aims to assess the association between long-term ambient air pollution and the prevalence of MetS in a large population of Chinese children and adolescents.

METHODS

In 2013, a total of 9,897 children and adolescents aged 10 to 18 years were recruited from seven provinces/municipalities in China. MetS was defined based on the recommendation by the International Diabetes Federation (IDF). Satellite based spatio-temporal models were used to estimate exposure to ambient air pollution (including particles with diameters ≤1.0 µm (PM₁), ≤2.5 µm (PM_2.5), and ≤10 µm (PM₁₀), and nitrogen dioxide (NO₂)). Individual exposure was calculated according to 94 schools addresses. After adjustment for a range of covariates, generalized linear mixed-effects models were utilized to evaluate the associations between air pollutants and the prevalence of MetS and its components. In addition, several stratified analyses were examined according to sex, weight status, outdoor physical activity time, and sugar-sweetened beverages (SSBs) intake.

RESULTS

The prevalence of MetS was 2.8%. The odds ratio of MetS associated with a 10 μg/m³ increase in PM₁, PM_2.5, PM₁₀ and NO₂ was 1.20 (95%CI: 0.99, 1.46), 1.31 (95%CI: 1.05, 1.64), 1.32 (95%CI: 1.08, 1.62), and 1.33 (95%CI: 1.03, 1.72), respectively. Regarding the MetS components, we observed associations between all pollutants and abdominal obesity. In addition, long-term PM₁ and NO₂ exposures were associated with the prevalence of elevated fasting blood glucose. Stratified analyses detected that the associations between air pollutants and the prevalence of MetS were stronger in boys (P_interaction < 0.05).

CONCLUSIONS

We found that long-term exposure to PM_2.5, PM₁₀, and NO₂ were positively associated with the prevalence of MetS in children and adolescents. Our findings may have certain public health implications for some comprehensive strategy of environment improvement and lifestyles changes in order to reduce the burden of non-communicable disease.

A review of multivariate analysis: is there a relationship between airborne particulate matter and meteorological variables?

Among statistical tools for the study of atmospheric pollutants, trajectory regression analysis (TRA), cluster analysis (CA), and principal component analysis (PCA) can be highlighted. Therefore, this article presents a systematic review of such techniques based on (i) air mass influences on particulate matter (PM) and (ii) the study of the relationship between PM and meteorological variables. This article aims to review studies that use TRA and to review studies that adopt CA and/or PCA to identify the associations and relationship between meteorological variables and atmospheric pollutants. Papers published between 2006 and 2018 and indexed by five of the main scientific databases were considered (ScienceDirect, Web of Science, PubMed, SciELO, and Scopus databases). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations supported this systematic review. From the resulting most relevant papers, eight studies analyzed the influence of air mass trajectories on PM using TRA and twenty-one studies searched for the relationship between meteorological variables and PM using CA and/or PCA. A combination of TRA and time series models was identified as the possibility of future works. Besides, studies that simultaneously combine the three techniques to identify both the influence of air masses on PM and its relationship with meteorological variables are a possibility of future papers, because it can lead to a better comprehension of such a phenomenon.

Lipidomics insight into chronic exposure to ambient air pollution in mice

More recent evidences are supportive of air pollution exposure on diabetes risk, including worsening of whole-body insulin sensitivity, enhancement of hepatic lipogenesis and nonalcoholic fatty liver disease after fine particulate matter (PM_2.5) exposure. Therefore, we aimed to explore the lipidomics to get a comprehensive insight about ambient real-world PM_2.5 exposure on lipid metabolism in blood and liver. After ambient PM_2.5 exposure for 6 months, excess triglyceride accumulation in the liver was observed. Remarkable metabolic alterations including neutral lipids, glycerophospholipids and sphingolipids were noticed. Lipidomic signatures in liver is different from plasma in response to PM_2.5 exposure. Lipids including species of ceramide, sphingomyeline and triglyceride may become potential biomarkers of lipotoxicity contributing to PM_2.5-induced metabolic dysfunction, and the present study may serve as a reference lipid bank for further studies.