Seasonal analysis of the short-term effects of air pollution on daily mortality in Northeast Asia

Mapping nationwide concentrations of sulfate and nitrate in ambient PM2.5 in South Korea using machine learning with ground observation data

Particulate matter (PM) is a major air pollutant in Northeast Asia, with frequent high PM episodes. To investigate the nationwide spatial distribution maps of PM2.5 and secondary inorganic aerosols in South Korea, prediction models for mapping SO42- and NO3- concentrations in PM2.5 were developed using machine learning with ground-based observation data. Specifically, the random forest algorithm was used in this study to predict the SO42- and NO3- concentrations at 548 air quality monitoring stations located within the representative radii of eight intensive air quality monitoring stations. The average concentrations of PM2.5, SO42-, and NO3- across the entire nation were 17.2 ± 2.8, 3.0 ± 0.6, and 3.4 ± 1.2 μg/m3, respectively. The spatial distributions of SO42- and NO3- concentrations in 2021 revealed elevated concentrations in both the western and central regions of South Korea. This result suggests that SO42- concentrations were primarily influenced by industrial activities rather than vehicle emissions, whereas NO3- concentrations were more associated with vehicle emissions. During a high PM2.5 event (November 19-21, 2021), the concentration of SO42- was primarily influenced by SOX emissions from China, while the concentration of NO3- was affected by NOX emissions from both China and Korea. The methodology developed in this study can be used to explore the chemical characteristics of PM2.5 with high spatiotemporal resolution. It can also provide valuable insights for the nationwide mitigation of secondary PM2.5 pollution.

Temperature modifies the effects of air pollutants on respiratory diseases

Increasing studies have reported temperature modification effects on air pollutants-induced respiratory diseases. In the current study, daily data of respiratory emergency room visits (ERVs), meteorological factors, and concentrations of air pollutants were collected from 2013 to 2016 in Lanzhou, a northwest city in China. Daily average temperature was stratified into low (≤ 25 percentile, P₂₅), medium (25-75 percentile, P₂₅-P₇₅) and high (≥ 75 percentile, P₇₅) to explore how temperature modifies the effects of air pollutants (PM_2.5, PM₁₀, SO₂, and NO₂) on respiratory ERVs by using generalized additive Poisson regression model (GAM). Seasonal modification was also investigated. Results showed that (a) PM₁₀, PM_2.5, and NO₂ had the strongest effects on respiratory ERVs in low temperature; (b) males and 15-and-younger were more vulnerable in low temperature while females and those older than 46 years were highly affected in high temperature; (c) PM₁₀, PM_2.5, and NO₂ were mostly associated with the total and both males and females in winter, while SO₂ resulted in the highest risk for the total and males in autumn and females in spring. In conclusion, this study found significant temperature modification effects and seasonal differences on the risks of respiratory ERVs due to air pollutants in Lanzhou, China.

Exploring the impact of particulate matter on mortality in coastal Mediterranean environments

Air pollution is one of the most important problems the world is facing nowadays, adversely affecting public health and causing millions of deaths every year. Particulate matter is a criteria pollutant that has been linked to increased morbidity, as well as all-cause and cause-specific mortality. However, this association remains under-investigated in smaller-size cities in the Eastern Mediterranean, which are also frequently affected by heat waves and dust storms. This study explores the impact of particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀) and ≤ 2.5 μm (PM_2.5) on mortality (all-cause, cardiovascular, respiratory) in two coastal cities in the Eastern Mediterranean; Thessaloniki, Greece and Limassol, Cyprus. Generalized additive Poisson models were used to explore overall and gender-specific associations, controlling for long- and short-term patterns, day of week and the effect of weather variables. Moreover, the effect of different lags, season, co-pollutants and dust storms on primary associations was investigated. A 10 μg/m³ increase in PM_2.5 resulted in 1.10 % (95 % CI: -0.13, 2.34) increase in cardiovascular mortality in Thessaloniki, and in 3.07 % (95 % CI: -0.90, 7.20) increase in all-cause mortality in Limassol on the same day. Additionally, significant positive associations were observed between PM_2.5 as well as PM₁₀ and mortality at different lags up to seven days. Interestingly, an association with dust storms was observed only in Thessaloniki, having a protective effect, while the gender-specific analysis revealed significant associations only for the males in both cities. The outcome of this study highlights the need of city- or county-specific public health interventions to address the impact of climate, population lifestyle behaviour and other socioeconomic factors that affect the exposure to air pollution and other synergistic effects that alter the effect of PM on population health.

Association between Outdoor Air Pollution and Fatal Acute Myocardial Infarction in Lithuania between 2006 and 2015: A Time Series Design

BACKGROUND

Air pollution has a significant effect on human health and there is a broad body of evidence showing that exposure to air pollution is associated with an increased risk of adverse health effects. The main objective of this study was to assess the association of traffic-related air pollutants with fatal AMI during the ten-year period.

METHODS

The study was conducted in Kaunas city, where the WHO MONICA register included a total of 2273 adult cases of fatal AMI cases during the 10-year study period. We focused on the period between 2006 and 2015. The associations between exposure to traffic-related air pollution and the risk of fatal AMI were evaluated by using a multivariate Poisson regression model, RR presented per an increase in IQR.

RESULTS

It was found that the risk of fatal AMI was significantly higher in all subjects (RR 1.06; 95% CI 1.00-1.12) and women (RR 1.12; 95% CI 1.02-1.22) when the concentration of PM₁₀ in the ambient air was increased 5-11 days before the onset of AMI, adjusting for NO₂ concentration. The effect was stronger during spring in all subjects (RR 1.12; 95% CI 1.03-1.22), in men (RR 1.13; 95% CI 1.01-1.26), in younger-aged (RR 1.15; 95% CI 1.03-1.28), and in winter in women (RR 1.24; 95% CI 1.03-1.50).

CONCLUSIONS

Our findings show that ambient air pollution increases the risk of fatal AMI, and this pertains to PM₁₀ specifically.

Investigating the Effects of Air Pollution on Plant Species Resistance in Urban Areas

Context: Air pollution is a serious concern for environmental and human health, especially due to increasing the risk of respiratory and cardiovascular diseases. The purpose of this study was to investigate the effects of air pollution on plant species resistance in urban areas. Evidence Acquisition: This narrative review was conducted by searching the databases of Web of Science, Science Direct, Scopus, PubMed, Google Scholar, and Springer. Sixty-five articles were screened by reading their abstracts and full texts. In the end, 12 relevant papers published from 1993 to 2021 were finally selected. Results: The literature review showed that the green spaces created by municipalities in different areas of the city included a set of trees and shrubs compatible by the climate, grass, soil, and water of the region, leading to a significant improvement in air quality. Based on the results, urban green space has the ability to reduce the amount of artificially produced pollutants, and the use of natural potential of trees can improve the quality of the environment depending on various factors such as the climatic condition of the region and the density and amount of vegetation cover. Conclusions: The most effective ways to reduce health and economic costs include reducing the emission of pollutants from cars and industries, extending urban green space, educating citizens, and organizational planning and cooperation. The findings of this study may have important implications for selecting plant species for vegetation traffic barriers.

Associations between seasonal ambient air pollution and adverse perinatal outcomes: a retrospective cohort study in Wenzhou, China

Prenatal exposure to ambient air pollution has been associated with adverse perinatal outcomes in previous studies. However, few studies have examined the interaction between air pollution and the season of conception on term low birth weight (TLBW) or macrosomia. Birth registry data of singleton live births in Wenzhou, China, between January 2015 and December 2016 were accessed from the Wenzhou Maternal and Child Health Information Management platform, and data on the ambient air pollutants in Wenzhou were obtained from the Chinese Air Quality Online Monitoring and Analysis Platform. Single-/two-pollutant binary logistic regression models were used to assess the associations between ambient air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, and O₃) and TLBW/macrosomia, further exploring whether the season of conception interacts with air pollution to impact birth weight. Finally, 213,959 term newborns were selected, including 2452 (1.1%) infants with TLBW and 13,173 (6.1%) infants with macrosomia. In the single-/two-pollutant models, we observed an increased risk of TLBW associated with maternal exposure to PM_2.5, PM₁₀, SO₂, and NO₂ during the entire pregnancy, especially in the 2nd trimester. Maternal exposure to O₃ during the 1st trimester was associated with increased macrosomia risk, and O₃ exposure during the 3rd trimester was associated with increased TLBW risk. Pregnant women who conceive in the warm season may experience a more adverse ambient air environment that is related to the risks of TLBW. These findings add to the evidence suggesting that air pollution and the season of conception may have synergistic effects on adverse perinatal outcomes, especially TLBW. Further prospective cohort studies are needed to validate our results.

Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear regression, and support vector regression

Climate change is generally known to impact ozone concentration globally. However, the intensity varies across regions and countries. Therefore, local studies are essential to accurately assess the correlation of climate change and ozone concentration in different countries. This study investigates the effects of climatic variables on ozone concentration in Malaysia in order to understand the nexus between climate change and ozone concentration. The selected data was obtained from ten (10) air monitoring stations strategically mounted in urban-industrial and residential areas with significant emissions of pollutants. Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. The analysis was carried out during the southwest monsoon due to the rise of ozone in the dry season. The results show a very strong correlation between temperature and ozone. Wind speed also exhibits a moderate to strong correlation with ozone, while relative humidity is negatively correlated. The highest correlation values were obtained at Bukit Rambai, Nilai, Jaya II Perai, Ipoh, Klang and Petaling Jaya. These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. The random forest outperformed other algorithms with a very high R² of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. This study's outcome indicates a linkage between temperature and wind speed with ozone concentration in the study area. An increase of these variables will likely increase the ozone concentration posing threats to lives and the environment. Therefore, this study provides data-driven insights for decision-makers and other stakeholders in ensuring good air quality for sustainable cities and communities. It also serves as a guide for the government for necessary climate actions to reduce the effect of climate change on air pollution and enabling sustainable cities in accordance with the UN's SDGs 13 and 11, respectively.

The impact of size-segregated particle properties on daily mortality in Seoul, Korea

To investigate the causative component for certain health outcomes, the associations between the properties of ambient particles and cause-specific mortality (all-cause, cardiovascular, and respiratory-related mortality) measured in Seoul, Korea, from January 1, 2013, to December 31, 2016, were evaluated with a quasi-Poisson generalized additive model (GAM). The total mass of PM₁₀ and PM_2.5 moderately affected respiratory-related mortality but had almost no impact on all-cause and cardiovascular-related mortality. Among PM_2.5 mass compositions, ammonium sulfate, which is in generally 300-500 nm as a secondary species, showed the most statistically significant effect on respiratory-related mortality at lag 4 (p < 0.1) but not for other mortalities. However, from the size-selective investigations, cardiovascular-related mortality was impacted by particle number concentrations (PNCs), particle surface concentrations (PSCs), and particle volume concentrations (PVCs) in the size range from 50 to 200 nm with a statistically significant association, particularly at lag 1, suggesting that mass is not the only way to examine mortality, which is likely because mass and chemical composition concentrations are generally controlled by larger-sized particles. Our study suggests that the size-specific mortality and/or impacts of size-resolved properties on mortalities need to be evaluated since smaller particles get into the body more efficiently, and therefore, more diverse size-dependent causes and effects can occur.

Air Pollution and Public Bike-Sharing System Ridership in the Context of Sustainable Development Goals

A bicycle-sharing system (BSS) has been implemented in Seoul, South Korea to promote green transportation policy as a Sustainable Development Goal (SDG) to mitigate climate change, reduce traffic jams, and promote physical activity. However, the concentration of air pollutants in Seoul often exceeds the standards of the World Health Organization, thereby creating a conflict with SDG 3 (Health). Therefore, it is important to recognize the trade-offs between actions targeted at SDGs as they might offset each other. In this context, a primary concern is investigating how the behavior of BSS users regarding outdoor air pollution appears. This study explores the relationship between ambient air pollution and the behavior of BSS riders in Seoul. We conducted a time-series analysis of associations between particulate air pollution and participation in the BSS. We used generalized additive models, adjusted for mean temperature, humidity, rainfall, day of the week, long-term trends, and seasonality to construct an exposure–response relationship. We observed a nonlinear relationship between increasing air pollution and bicycle ridership. This study method can be used as a basis for similar analyses to investigate BSS policies in other cities.

Pricing air pollution: evidence from short-term exposure to air pollution on hospitalization of acute bronchitis and chronic obstructive pulmonary disease in southwestern China

Existing evidence suggests that ambient air pollution has serious adverse effects on respiratory diseases, yet there is little direct evidence from China regarding corresponding economic losses. Here we quantified air pollution-related acute health effects and related economic losses of the most common two respiratory diseases in southwestern China, acute bronchitis and chronic obstructive pulmonary disease (COPD). We applied a distributed lag non-linear model to analyse the relationship between ambient air pollutants and hospital admissions of acute bronchitis and COPD, then applied the cost of illness method to explore the attributing economic burden. During the study period, 528 334 and 99 419 hospital admissions of acute bronchitis and COPD, respectively, were recorded. As a result, during the study period the total hospitalization economic losses attributable to air pollution were 486.40 and 254.74 million yuan for acute bronchitis and COPD, respectively, accounting for 0.015% of local gross domestic product. Our research provides intuitive evidence on the health and economic impacts of short-term exposure to air pollution, which is a key basis for the formulation of environmental policies.

Forecasting PM2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran

The main objective of the present study was to predict the associated health endpoint of PM_2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ ⁺ software was utilized for assessing Health effects of PM_2.5 levels. The mean PM_2.5 over the 9-year study period was 63.27(μg/m³), about six times higher than the WHO guideline. However, the PM_2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM_2.5 concentration and temperature and wind speed. Considering the importance of predicting PM_2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.

Association between air pollution and chronic rhinosinusitis: a nested case-control study using meteorological data and national health screening cohort data

BACKGROUND

Inconsistent results about the effect of air pollution on chronic rhinosinusitis (CRS) have been reported. This study aimed to evaluate the impact of meteorological conditions/air pollution on the prevalence of CRS in adult Koreans.

METHODOLOGY

The data from the Korean National Health Insurance Service-Health Screening Cohort from 2002 through 2015 were used. A CRS group (defined as ICD-10 codes J32, n=6159) was matched with a control group (n=24,636) in 1:4 ratios by age, sex, income, and region of residence. The meteorological conditions and air pollution data included the daily mean, highest, and lowest temperature (°C), daily temperature range (°C), relative humidity (%), ambient atmospheric pressure (hPa), sunshine duration (hr), and the rainfall (mm), SO2 (ppm), NO2 (ppm), O3 (ppm), CO (ppm), and PM10 (μg/m3) levels before the CRS diagnosis. Crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for CRS were analyzed using logistic regression analyses.

RESULTS

When the NO2 level increased by 0.1 ppm, the odds for CRS increased 5.40 times, and when the CO level increased by 1 ppm and PM10 increased by 10 μg/m3, the odds for CRS decreased 0.75 times and 0.93 times, respectively. Other meteorological conditions, such as the mean/highest/lowest temperature, temperature range, rainfall and other air pollution, such as SO2 and O3, were not statistically significant. NO2 for 90 days before the index date increased the risk of CRS in all subgroups, except for the nasal polyp and older age subgroups.

CONCLUSION

CRS is related to high concentrations of NO2.

Modification of the effects of nitrogen dioxide and sulfur dioxide on congenital limb defects by meteorological conditions

STUDY QUESTION

Can meteorological conditions modify the associations between NO2 and SO2 exposure and congenital limb defects (CLDs) during the first trimester of pregnancy?

SUMMARY ANSWER

Increases in NO2 and SO2 exposure were consistently associated with higher risks of CLDs during the first trimester of pregnancy; both low- and high-temperature exposure and high air humidity act synergistically with the two air pollutants on CLDs.

WHAT IS KNOWN ALREADY

Animal studies have indicated air pollutants are associated with CLDs, but corresponding epidemiological studies are limited with equivocal conclusions. Meteorological conditions are closely connected to the generation, diffusion, distribution and even chemical toxicity of air pollutants.

STUDY DESIGN, SIZE, DURATION

This case-control study included 972 cases of CLDs and 9720 controls in Changsha, China during 2015-2018.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Cases from the hospital based monitoring system for birth defects (including polydactyly, syndactyly, limb shortening, and clubfoot) and healthy controls from the electronic medical records system were studied. Complete data on daily average NO2 and SO2 concentrations and meteorological variables were obtained from local monitoring stations to estimate monthly individual exposures during the first trimester of pregnancy, using the nearest monitoring station approach for NO2 and SO2 concentrations, and the city-wide average approach for temperature and relative humidity, respectively. The 25th and 75th percentiles of daily mean temperature, as well as the 50th percentile of daily mean relative humidity during the study period were used to classify high- and low-temperature exposure, and high humidity exposure based on existing evidence and local climate characteristics. Multivariate logistic regression models were used to estimate the independent effects per 10 μg/m3 increase in NO2 and SO2 on CLDs, and the attribute proportions of interaction (API) were used to quantify the additive joint effects of air pollutants with meteorological conditions after including a cross product interaction term in the regression models.

MAIN RESULTS AND THE ROLE OF CHANCE

NO2 and SO2 exposures during the first trimester of pregnancy were consistently and positively associated with overall CLDs and subtypes, with adjusted odd ratios (aORs) ranging from 1.13 to 1.27 for NO2, and from 1.37 to 2.49 for SO2. The effect estimates were generally observed to be the strongest in the first month and then attenuated in the second and third months of pregnancy. Synergistic effects of both low and high temperature in combination with NO2 (with APIs ranging from 0.07 to 0.38) and SO2 (with APIs ranging from 0.18 to 0.51) appeared in the first trimester of pregnancy. Several significant modifying effects by high humidity were also observed, especially for SO2 (with APIs ranging from 0.13 to 0.38). Neither NO2 nor SO2 showed an interactive effect with season of conception.

LIMITATIONS, REASONS FOR CAUTION

The methods used to estimate individual exposure levels of air pollutants and meteorological factors may lead to the misclassification bias because of the lack of information on maternal activity patterns and residential mobility during pregnancy. Moreover, we were unable to consider several potentially confounding factors, including socioeconomic status, maternal nutrient levels, alcohol use and smoking during early pregnancy due to unavailable data, although previous studies have suggested limited change to the results after when including these factors in the analysis.

WIDER IMPLICATIONS OF THE FINDINGS

The findings are helpful for understanding the combined effects of air pollution and meteorological conditions on birth defects. Environmental policies and practices should be formulated and implemented to decrease air pollutant emissions and improve meteorological conditions to reduce their harmful effects on pregnancy. Additionally, pregnant women should be suggested to reduce outdoor time when the air quality is poor, especially when ambient temperature is higher or lower than what is comfortable, or when it is excessively humid.

STUDY FUNDING/COMPETING INTEREST(S)

The study is funded by Major Scientific and Technological Projects for Collaborative Prevention and Control of Birth Defects in Hunan Province (2019SK1012), Major Research and Development Projects in Hunan Province (2018SK2060) and Scientific and Technological Department Projects in Hunan Province (2017SK50802). There are no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

Association between ambient air pollution and cause-specific mortality in Cape Town, Durban, and Johannesburg, South Africa: any susceptible groups?

Studies have confirmed that adverse human health effects that are associated with exposure to air pollution may differ depending on other factors such as age, gender, environmental conditions, and socio-economic factors. This study was conducted to assess the association between ambient air pollution and cause-specific mortality in the three big cities in South Africa and to determine the susceptible groups thereof. Cause-specific mortality data for all ages and PM10, NO2, and SO2 in Cape Town, Durban, and Johannesburg for the period from 1 January 2006 to 31 December 2010 were obtained. Statistical analyses were done to estimate the associations between air pollutants and cause-specific mortality. Susceptibility was therefore investigated in stratified analyses by sex and age (≥60 years) and environmental conditions (heat and cold) followed by models with interaction terms. Our estimates showed independent associations between these air pollutants, environmental conditions, and susceptible groups.

Seasonal and monthly variation in peak expiratory flow rate in children with asthma

Background

Although understanding the seasonal patterns of asthma deterioration is important to prevent asthma exacerbation, previous approaches have limitations in evaluating the actual trend of asthma exacerbation.

Objective

This study aimed to evaluate the seasonal and monthly variations in the peak expiratory flow rate (PEFR) among children with asthma.

Methods

A total of 89 patients with asthma were enrolled between December 2012 and March 2015. The PEFR in the morning and evening was recorded daily, and the percentage change in PEFR from baseline was calculated. Generalized estimating equation models were constructed after adjusting for age, sex, body mass index, and sensitization to house dust mites or pollen.

Results

The PEFR records of 11,222 person-days showed a significant decrease in the morning and evening in autumn than in winter by -1.9% (95% confidence interval [CI], -3.73 to -0.15) and -2.1% (95% CI, -3.80 to -0.37), respectively. The morning PEFR was significantly lower in April, August, October, and December than in January with changes of -4.2% (95% CI, -7.08 to -1.23) in April, -3.1% (95% CI, -5.79 to -0.47) in August, -3.7% (95% CI, -6.09 to -1.21) in October, and -1.9% (95% CI, -3.62 to -0.12) in December. The percentage change of evening PEFR significantly decreased by -3.3% (95% CI, -6.38 to -0.25) in April and by -3.3% (95% CI, -5.56 to -1.07) in October.

Conclusion

The PEFR in children with asthma was lower in autumn than in winter. In terms of monthly patterns, the PEFR was significantly reduced in April and October than in January. These results can serve as a basis for preventing asthma exacerbations by developing seasonal or monthly management strategies for children with asthma.

Interaction of Air Pollutants and Meteorological Factors on Birth Weight in Shenzhen, China

BACKGROUND

This study aimed to assess if air pollutants and meteorological factors synergistically affect birth outcomes in Shenzhen, China.

METHODS

A total of 1,206,158 singleton live births between 2005 and 2012 were identified from a birth registry database. Daily average measurements of particulate matter ≤10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ambient air temperature (T), and dew point temperature (Td), a marker of humidity, were collected. Multivariable logistic regression models were used to evaluate associations between air pollution and small for gestational age (SGA), and full-term low birth weight (TLBW). We classified births into those conceived in the warm (May-October) and cold seasons (November-April) and then estimated interactions between air pollutants and meteorological factors.

RESULTS

An interquartile range (IQR) increase in PM10 exposure during the first trimester (23.1 µg/m) and NO2 during both the first and second trimesters (15.1 and 13.4 µg/m) was associated with SGA and TLBW risk; odds ratios ranged from 1.01 (95% confidence interval [CI] = 1.00, 1.02) to 1.09 (1.07, 1.12). We observed interactive effects of both air temperature and humidity on PM10 and SGA for newborns conceived in the warm season. Each IQR increase in PM10 (11.1 µg/m) increased SGA risk by 90% (95% CI = 19%, 205%), 29% (23, 34%), 61% (10, 38%), and 26% (21, 32%) when T < 5th percentile, 5th < T < 95th percentile, Td < 5th percentile, and 5th < Td < 95th percentile, respectively.

CONCLUSIONS

Our study found evidence of an interactive effect of air temperature and humidity on the relationship between PM10 exposure and SGA among newborns conceived in the warm season (May-October). Relatively low air temperature or humidity exacerbated the effects of PM10.

Exposure to ambient fine particulate matter is associated with changes in fasting glucose and lipid profiles: a nationwide cohort study

BACKGROUND

Ambient fine particulate matter is a rising concern for global public health. It was recently suggested that exposure to fine particulate matter may contribute to the development of diabetes and dyslipidaemia. This study aims to examine the potential associations of ambient particulate matter exposure with changes in fasting glucose and lipid profiles in Koreans.

METHOD

We used the data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC), a nationwide database representative of the Korean population. A total of 85,869 individuals aged ≥20 years were included. Multiple regression analyses were conducted to assess the associations between exposure to particulate matter and changes in fasting glucose and lipid profiles at 2-year intervals after adjusting for confounders.

RESULTS

Significant associations were observed between an increase in interquartile range for particulate matter < 2.5 μm in diameter (PM_2.5) and elevated levels of fasting glucose and low-density lipoprotein cholesterol (p for trend = 0.015 and 0.010, respectively), while no association for particulate matter sized 2.5-10 μm in diameter (PM_10-2.5) was noted after adjusting for the other covariates. Sub-group analyses showed stronger associations in individuals who were older (≥60 years) or physically inactive.

CONCLUSIONS

Fine particulate matter exposure affects worsening fasting glucose and low-density lipoprotein cholesterol levels, with no evidence of an association for coarse particulate matter.

Fifteen Years of Airborne Particulates in Vitro Toxicology in Milano: Lessons and Perspectives Learned

Air pollution is one of the world’s leading environmental causes of death. The epidemiological relationship between outdoor air pollution and the onset of health diseases associated with death is now well established. Relevant toxicological proofs are now dissecting the molecular processes that cause inflammation, reactive species generation, and DNA damage. In addition, new data are pointing out the role of airborne particulates in the modulation of genes and microRNAs potentially involved in the onset of human diseases. In the present review we collect the relevant findings on airborne particulates of one of the biggest hot spots of air pollution in Europe (i.e., the Po Valley), in the largest urban area of this region, Milan. The different aerodynamic fractions are discussed separately with a specific focus on fine and ultrafine particles that are now the main focus of several studies. Results are compared with more recent international findings. Possible future perspectives of research are proposed to create a new discussion among scientists working on the toxicological effects of airborne particles.

The nonlinear association between outdoor temperature and cholesterol levels, with modifying effect of individual characteristics and behaviors

Few studies have been conducted to investigate the underlying mechanisms of the effect of temperature on cardiovascular disease at population level, especially among Chinese population. A total of 56,039 participants were recruited from Kailuan cohort study, China. The lipoprotein profile indicators, including triglycerides (TG), low-density lipoprotein (LDL), and high-density lipoprotein, were collected. Non-linear associations between temperature and the lipoprotein profile indicators were examined using a nonlinear function for temperature. Stratified analyses were performed in groups by individual characteristics (age, gender, and body mass index) and individual behaviors (physical activities and smoking habits). Generally, a non-linear relationship was found between cholesterol levels and temperature. A 1 °C decrease in temperature below the threshold was related with 0.004 mmol/L (95% CI 0.0004, 0.008), 0.022 mmol/L (95% CI 0.020, 0.025), and 0.009 mmol/L (95% CI 0.008, 0.011) increase in TG, LDL, and HDL, respectively; a 1 °C increase in temperature above the threshold was associated with 0.005 mmol/L (95% CI 0.003, 0.007), 0.012 mmol/L (95% CI 0.009, 0.015), and 0.002 mmol/L (95% CI 0.001, 0.004) increase in TG, LDL, and HDL, respectively. Stratified analyses showed that effect estimates on TG and LDL were larger among females, subjects with higher BMI, and those with smoking habits, while effect estimates on HDL were smaller among these subjects (expect for female). Our results suggest both cold and hot effect of temperature on cholesterol. Furthermore, females, and people with higher BMI or smoking habit may be more susceptible to outdoor temperature.

Elderly Mortality and Exposure to Fine Particulate Matter and Ozone

BACKGROUND

The effects on particulate matter (PM) and ozone on health are being reported by a number of studies. The effects of these air pollutants are likely to be stronger in the elderly population, but studies in this regard are scarce. The purpose of this study was to study the effects of PM ≤ 2.5 μ and ozone on chronic health effects of the elderly population.

METHODS

In order to analyze the health status of the elderly population, National Statistical Office Mortality records were used. In this study, we calculated the number of deaths in Seoul of people who were 60 years or older between 2002 and 2012. The current study analyzed each disorder separately and the lag effect. PM and ozone were analyzed using the single exposure model, as well as the adjusted multi exposure model.

RESULTS

In the single exposure analysis with PM2.5 as the exposure variable, with the increase of 10 μ/m³, the number of deaths increased by 1.0039 fold, and vascular disease 1.0053 fold. In the multi exposure model adjusting for ozone, the number of deaths increased by 1.0037 fold, and vascular disease 1.0049 fold. In the single exposure analysis with ozone as the exposure variable, with the increase of 10 ppb, the number of deaths increased by 1.0038 fold, and in the multi exposure model adjusting for PM2.5, the number of deaths increased by 1.0027 fold. These results differed depending on the period or season. There was a 5-day lag effect between PM2.5 and deaths in the multi exposure model, and 1.0028 fold when adjusted for ozone. There was a 1-day lag effect in single exposure models with ozone as the main variable, and 1.0027 fold increase in deaths.

CONCLUSION

In our study, an increase in the number of deaths in the elderly population in accordance with the increase in the PM2.5 and ozone was found. The association found in our study could also influence socioeconomic burden. Future studies need to be performed in regards to younger population, as well as other air pollutants.

Adverse birth outcomes in Guangdong province, China, 2014-2017: a spatiotemporal analysis of 2.9 million births

OBJECTIVES

Adverse birth outcomes pose a great threat to the public health and bring a heavy burden of disease in China. A comprehensive examination of the temporal and spatial trends of preterm birth (PTB), low birth weight (LBW) and small for gestational age (SGA) epidemics can provide some elementary information for subsequent aetiological and epidemiological studies. This study aimed to characterise the spatiotemporal features of PTB, LBW and SGA based on a large cohort of live births in China.

DESIGN

Spatiotemporal descriptive analysis was performed in Guangdong province, China, from 2014 to 2017.

SETTING

Data involving 2 917 098 live births in Guangdong province, China from 2014 to 2017 was collected from Guangdong Birth Certificate System. Information was collected, including the date of birth, gestational age in week, birth weight, sex of the infant, age of the mother and registered residence of the mother.

RESULTS

The estimated rate of PTB, LBW and SGA was 4.16%, 4.14% and 12.86%, respectively. For temporal trends, the rates of PTB, LBW and SGA showed seasonal fluctuations, especially for LBW and SGA. In addition, there were regional differences in the rates of PTB, LBW and SGA between the Pearl River Delta and Non-Pearl River Delta regions. From 2014 to 2017, the high rates of PTB and LBW expanded from the Pearl River Delta region to the Non-Pearl River Delta regions. However, compared with the Pearl River Delta region, the rate of SGA was higher in the Non-Pearl River Delta regions on the whole.

CONCLUSION

The findings of this study contribute to the understanding of the aetiology and epidemiology of PTB, LBW and SGA in south China.

Effect of O3, PM10 and PM2.5 on cardiovascular and respiratory diseases in cities of France, Iran and Italy

At present, both tropospheric ozone (O₃) and particulate matters (PM) are among the most threatening air pollutants for human health in cities. The air pollution effects over public health include increased risk of hospital admissions and mortality for respiratory and cardiovascular diseases even when air pollutant concentrations are below European and international standards. The aim of this study was to (i) estimate the burden of mortality and morbidity for cardiovascular and respiratory diseases attributed to PM_2.5, PM₁₀ and O₃ in nine selected cities in France, Iran and Italy in 2015 and 2016 and to (ii) compare estimated burdens at current O₃ and PM levels with pre-industrial levels. The selected Mediterranean cities are among the most affected by the air pollution in Europe, in particular by rising O₃ while the selected Iranian cities rank as the most polluted by PM in the world. The software AirQ+ was used to estimate the short-term health effects, in terms of mortality and morbidity by using in situ air quality data, city-specific relative risk values and baseline incidence. Compared to pre-industrial levels, long-term exposures to ambient PM_2.5, PM₁₀ and O₃ have substantially contributed to mortality and hospital admissions in selected cities: about 8200 deaths for non-accidental causes, 2400 deaths for cardiovascular diseases, 540 deaths for respiratory diseases, 220 deaths for chronic obstructive pulmonary diseases as well as 18,800 hospital admissions for cardiovascular diseases and 3400 for respiratory diseases were reported in 2015. The study supports the need of city-specific epidemiological data and urgent strategies to mitigate the health burden of air pollution.

Seasonal variation and etiologic inferences of childhood pneumonia and diarrhea mortality in India

Control of pneumonia and diarrhea mortality in India requires understanding of their etiologies. We combined time series analysis of seasonality, climate region, and clinical syndromes from 243,000 verbal autopsies in the nationally representative Million Death Study. Pneumonia mortality at 1 month-14 years was greatest in January (Rate ratio (RR) 1.66, 99% CI 1.51-1.82; versus the April minimum). Higher RRs at 1-11 months suggested respiratory syncytial virus (RSV) etiology. India's humid subtropical region experienced a unique summer pneumonia mortality. Diarrhea mortality peaked in July (RR 1.66, 1.48-1.85) and January (RR 1.37, 1.23-1.48), while deaths with fever and bloody diarrhea (indicating enteroinvasive bacterial etiology) showed little seasonality. Combining mortality at ages 1-59 months with prevalence surveys, we estimate 40,600 pneumonia deaths from Streptococcus pneumoniae, 20,700 from RSV, 12,600 from influenza, and 7200 from Haemophilus influenzae type b and 24,700 diarrheal deaths from rotavirus occurred in 2015. Careful mortality studies can elucidate etiologies and inform vaccine introduction.

Temperature as a risk factor of emergency department visits for acute kidney injury: a case-crossover study in Seoul, South Korea

BACKGROUND

Previous studies show that escalations in ambient temperature are among the risk factors for acute kidney injury (AKI). However, it has not been adequately studied in our location, Seoul, South Korea. In this study, we aimed to examine the association between ambient temperatures and AKI morbidity using emergency department (ED) visit data.

METHODS

We obtained data on ED visits from the National Emergency Medical Center for 21,656 reported cases of AKI from 2010 to 2014. Time-stratified case-crossover design analysis based on conditional logistic regression was used to analyze short-term effects of ambient temperature on AKI after controlling for relevant covariates. The shape of the exposure-response curve, effect modification by individual demographic characteristics, season, and comorbidities, as well as lag effects, were investigated.

RESULTS

The odds ratio (OR) per 1 °C increase at lag 0 was 1.0087 (95% confidence interval [CI]: 1.0041-1.0134). Risks were higher during the warm season (OR = 1.0149; 95% CI: 1.0065-1.0234) than during the cool season (OR = 1.0059; 95% CI: 1.0003-1.0116) and even higher above 22.3 °C (OR = 1.0235; 95% CI: 1.0230-1.0239).

CONCLUSIONS

This study provides evidence that ED visits for AKI were associated with ambient temperature. Early detection and treatment of patients at risk is important in both clinical and economic concerns related to AKI.

Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea

BACKGROUND

Exposure to fine particles in the atmosphere can adversely affect health and even lead to premature death. Recently, South Korea has attracted attention because of its rapid increase in the concentration of Particulate Matter (PM).

OBJECTIVES

We estimated the economic benefits of reducing PM₁₀ in Seoul, South Korea, based on MODerate-resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD). Based on the retrieved PM₁₀ data, we estimated its effects on overall health in each district of Seoul, Korea between 2014 and 2015.

METHODS

The relationships between MODIS AOD and ground-based PM₁₀ data were identified in different seasons in South Korea between 2012 and 2013 using the linear regression model. The health benefits were estimated by the Benefits Mapping and Analysis Program (Benmap) using the scenarios from the World Health Organization (WHO).

RESULTS

The correlation between MODIS AOD and PM₁₀ concentration differed with the season. There was a higher correlation between MODIS AOD and PM₁₀ concentration in winter (R = 0.57) than there was in other seasons. Based on the MODIS AOD, the average annual PM₁₀ concentration in Seoul was higher in 2014 than it was in 2015, at values of 45.7 μg/m³, and 41.6 μg/m³, respectively. The greatest economic benefit of reducing PM₁₀ concentration (WHO annual standard of 20 μg/m³) was in 2014. This benefit was estimated to be 7022 (95% CI: 599, 20496), 2617 (95% CI: 216, 7750), and 1328 (95% CI: -159, 4679) billion KRW for all-cause, cardiovascular, and respiratory mortalities in 2014 and 2015, respectively.

CONCLUSIONS

These results demonstrate that, despite considerable improvements in air quality in recent decades, there is still a need for countermeasures to prevent economic loss due to air pollution in Seoul.

Particulate Matter Mortality Rates and Their Modification by Spatial Synoptic Classification

Air pollution levels are highly correlated with temperature or humidity, so we investigated the relationship between PM₁₀ and the spatial synoptic classification (SSC) scheme on daily mortality, according to age group and season. Daily death data for 2000-2014 from Seoul, Korea, were acquired, and time-series analysis was applied with respect to season and to each of seven distinct SSC types: dry moderate (DM); dry polar (DP); dry tropical (DT); moist moderate (MM); moist polar (MP); moist tropical (MT); and transition (T). Modification effects were estimated for daily, non-accidental, cardiovascular, and respiratory mortality between PM₁₀ and SSC types. The following SSC-type-specific increased mortalities were observed, by cause of death: non-accidental mortality: DT (1.86%) and MT (1.86%); cardiovascular mortality: DT (2.83%) and MM (3.00%); respiratory mortality: MT (3.78%). Based on simplified weather types, increased PM₁₀ effects in non-accidental mortality rates were observed in dry (1.54%) and moist (2.32%) conditions among those aged 40-59 years and were detected regardless of conditions in other age groups: 60-74 (1.11%), 75-84 (1.55%), and 85+ (1.75%). The effects of particulate air pollution, by SSC, suggest the applicability of SSC to the comparison and understanding of acute effects of daily mortality based on weather type.

Using spatio-temporal lagged association pattern to unravel the acute effect of air pollution on mortality

BACKGROUND

Acute mortality effects of air pollution have been recognized in plenty of environmental epidemiologic studies. However, existing studies usually assume a universal lag association across sites and seasons. Such a strategy ignores the heterogeneity of lag structures and may lead to bias in the estimation of effects.

METHODS

A Bayesian hierarchical model with flexible lag structures was applied to estimate the impact of particulate matter less than 10 μm (PM₁₀) on mortality and determine whether the lag structure varied by season and location. Data from nine US communities, obtained from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), was used to examine the lagged associations between PM₁₀ and daily mortality. The estimates obtained from the flexible lag approaches were compared with those from the universal lag approach.

RESULTS

Of potential varying lag structures, a 10-μg/m³ increase in PM₁₀ was associated with 0.32% (95% credible interval: 0.16, 0.45) and 0.36% (0.18, 0.52) increases in mortality from nonaccidental and cardiovascular-respiratory death. The community-specific estimates of PM₁₀ mortality effects were distinct between the flexible and the universal lag approaches, with relative change of the effects ranged from -7.21% to 9.25% for nonaccidental morality, and from -5.78% to 4.16% for cardiovascular-respiratory morality. Moreover, the lag structure varied by location and season. For instance, the nonaccidental mortality effect of PM₁₀ attributable to the current and previous day was 29.8% in El Paso while 55.0% in Chicago; the overall effect attributable to the previous two to five days were 60.6%, 51.9%, 59.5%, and 59.3% in winter, spring, summer, and fall, respectively.

CONCLUSION

The results indicated that a universal lag association across sites and seasons may bias the mortality effect of air pollution. The varying lag structures should be considered in studies of short-term environmental exposures to get a more precise effect estimate.

Current State of Research on the Risk of Morbidity and Mortality Associated with Air Pollution in Korea

PURPOSE

The effects of air pollution on health can vary regionally. Our goal was to comprehensively review previous epidemiological studies on air pollution and health conducted in Korea to identify future areas of potential study.

MATERIALS AND METHODS

We systematically searched all published epidemiologic studies examining the association between air pollution and occurrence of death, diseases, or symptoms in Korea. After classifying health outcomes into mortality, morbidity, and health impact, we summarized the relationship between individual air pollutants and health outcomes.

RESULTS

We analyzed a total of 27 studies that provided 104 estimates of the quantitative association between risk of mortality and exposure to air pollutants, including particulate matter with aerodynamic diameter less than 10 μm, particulate matter with aerodynamic diameter less than 2.5 μm, sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide in Korea between January 1999 and July 2018. Regarding the association with morbidity, there were 38 studies, with 98 estimates, conducted during the same period. Most studies examined the short-term effects of air pollution using a time series or case-crossover study design; only three cohort studies that examined long-term effects were found. There were four health impact studies that calculated the attributable number of deaths or disability-adjusted life years due to air pollution.

CONCLUSION

There have been many epidemiologic studies in Korea regarding air pollution and health. However, the present review shows that additional studies, especially cohort and experimental studies, are needed to provide more robust and accurate evidence that can be used to promote evidence-based policymaking.

Seasonal analyses of the association between prenatal ambient air pollution exposure and birth weight for gestational age in Guangzhou, China

Ambient air pollution has been linked to small for gestational age (SGA); however, the relationship with large for gestational age (LGA) is unclear and very few studies have investigated seasonal effects on the association between air pollution and SGA or LGA. Using birth registry data of 506,000 singleton live births from 11 districts in Guangzhou, China between January 2015 and July 2017, we examined associations between ambient air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, and O₃) and SGA/LGA, and further assessed the modification effect of season. Daily concentrations of air pollutants from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district of residence during pregnancy. Two-level binary logistic regression models were used to evaluate associations between air pollution and SGA/LGA. Stratified analyses by season and a Cochran Q test were performed to assess the modification of season. Exposure to PM_2.5, NO₂, SO₂, and O₃ was significantly associated with increased risk of SGA, especially for exposure during the second and third trimester. For an interquartile range (IQR) increase in PM_2.5 (6.5 μg/m³), NO₂ (12.7 μg/m³), SO₂ (2.8 μg/m³) and O₃ (20.8 μg/m³) during the entire pregnancy, SGA risk increased by 2% (OR = 1.02, 95% CI: 1.00-1.04), 8% (OR = 1.08, 95% CI: 1.04-1.12), 2% (OR = 1.02, 95% CI: 1.01-1.03), and 14% (1.14, 1.11-1.17), respectively. A decreased risk of LGA was found for PM_2.5, PM₁₀, SO₂, and O₃ during the first trimester or entire pregnancy. When examined by season, significant associations between air pollutants and SGA were observed for women who conceived during summer or fall, and the patterns were consistent for all pollutants. Our study suggests that conception during different seasons might modify the association between ambient air pollution and SGA.

Impact of air pollution on cause-specific mortality in Korea: Results from Bayesian Model Averaging and Principle Component Regression approaches

Health effects related to air pollution are a major global concern. Related studies based on reliable exposure assessment methods would potentially enable policy makers to propose appropriate environmental management policies. In this study, integrated Bayesian Model Averaging (BMA) and Principle Component Regression (PCR) were adopted to assess the severity of air pollution impacts on mortality related to circulatory, respiratory and skin diseases in 25 districts of Seoul, South Korea for the years 2005-2015. These methods were consistent in determining the best regression models and most important pollutants related to mortality in those highly susceptible to poor air quality. Specifically, the results demonstrated that pneumonia was highly associated with air pollution, with a large determination coefficient (BMA: 0.46, PCR: 0.51) and high model's posterior probability (0.47). The most reliable prediction model for pneumonia was indicated by the lowest Bayesian Information Criterion. Among the pollutants, particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) was associated with serious health risks on evaluation, with the highest posterior inclusion probabilities (range, 80.20 to 100.00%) and significantly positive correlation coefficients (range, 0.14 to 0.34, p < 0.05). In addition, excessive PM₁₀ concentration (approximately 2.54 times the threshold) and a continuous increase in mortality due to respiratory diseases (approximately 1.50-fold in 10 years) were also exhibited. Overall, the results of this study suggest that currently, socio-environmental policies and international collaboration to mitigate health effects of air pollution is necessary in Seoul, Korea. Moreover, consideration of uncertainty of the regression model, which was verified in this research, will facilitate further application of this approach and enable optimal prediction of interactions between human and environmental factors.

Associations between mortality and prolonged exposure to elevated particulate matter concentrations in East Asia

Previous epidemiological studies regarding mortality and particulate matter with an aerodynamic diameter of <10μm (PM₁₀) have considered only absolute concentrations of PM₁₀ as a risk factor. However, none have evaluated the durational effect of multi-day periods with high PM₁₀ concentrations. To evaluate the durational effect (i.e., number of days) of high PM₁₀ concentrations on mortality, we collected data regarding 3,662,749 deaths from 28 cities in Japan, South Korea, and China (1993-2009). Exposure was defined as consecutive days with daily PM₁₀ concentrations ≥75μg/m³. A Poisson model was used with duration as the variable of interest, while controlling for daily PM₁₀ concentrations, meteorological variables, seasonal trends, and day of the week. The increase in mortality risk for each additional consecutive day with PM₁₀ concentrations ≥75μg/m³ was 0.68% in Japan (95% confidence interval [CI]: 0.35-1.01%), 0.48% in South Korea (95% CI: 0.30-0.66%), and 0.24% in China (95% CI: 0.14-0.33%). The annual average maximum number of consecutive days with high PM₁₀ in Japan (2.40days), South Korea (6.96days), and China (42.26days) was associated with non-accidental death increases of 1.64% (95% CI: 1.31-1.98%), 3.37% (95% CI: 3.19-3.56%), and 10.43% (95% CI: 10.33-10.54%), respectively. These findings may facilitate the planning of public health interventions to minimize the health burden of air pollution.