Research on the cascading mechanism of "urban built environment-air pollution-respiratory diseases": a case of Wuhan city.

Background: Most existing studies have only investigated the direct effects of the built environment on respiratory diseases. However, there is mounting evidence that the built environment of cities has an indirect influence on public health via influencing air pollution. Exploring the "urban built environment-air pollution-respiratory diseases" cascade mechanism is important for creating a healthy respiratory environment, which is the aim of this study. Methods: The study gathered clinical data from 2015 to 2017 on patients with respiratory diseases from Tongji Hospital in Wuhan. Additionally, daily air pollution levels (sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter (PM2.5, PM10), and ozone (O3)), meteorological data (average temperature and relative humidity), and data on urban built environment were gathered. We used Spearman correlation to investigate the connection between air pollution and meteorological variables; distributed lag non-linear model (DLNM) was used to investigate the short-term relationships between respiratory diseases, air pollutants, and meteorological factors; the impacts of spatial heterogeneity in the built environment on air pollution were examined using the multiscale geographically weighted regression model (MGWR). Results: During the study period, the mean level of respiratory diseases (average age 54) was 15.97 persons per day, of which 9.519 for males (average age 57) and 6.451 for females (average age 48); the 24 h mean levels of PM10, PM2.5, NO2, SO2 and O3 were 78.056 µg/m3, 71.962 µg/m3, 54.468 µg/m3, 12.898 µg/m3, and 46.904 µg/m3, respectively; highest association was investigated between PM10 and SO2 (r = 0.762, p < 0.01), followed by NO2 and PM2.5 (r = 0.73, p < 0.01), and PM10 and PM2.5 (r = 0.704, p < 0.01). We observed a significant lag effect of NO2 on respiratory diseases, for lag 0 day and lag 1 day, a 10 µg/m3 increase in NO2 concentration corresponded to 1.009% (95% CI: 1.001, 1.017%) and 1.005% (95% CI: 1.001, 1.011%) increase of respiratory diseases. The spatial distribution of NO2 was significantly influenced by high-density urban development (population density, building density, number of shopping service facilities, and construction land, the bandwidth of these four factors are 43), while green space and parks can effectively reduce air pollution (R2 = 0.649). Conclusion: Previous studies have focused on the effects of air pollution on respiratory diseases and the effects of built environment on air pollution, while this study combines these three aspects and explores the relationship between them. Furthermore, the theory of the "built environment-air pollution-respiratory diseases" cascading mechanism is practically investigated and broken down into specific experimental steps, which has not been found in previous studies. Additionally, we observed a lag effect of NO2 on respiratory diseases and spatial heterogeneity of built environment in the distribution of NO2.

Multiple dietary patterns and the association between long-term air pollution exposure with type 2 diabetes risk: Findings from UK Biobank cohort study.

BACKGROUND: Evidence of modifying effect of various dietary patterns (DPs) on risk of type 2 diabetes (T2D) induced by long-term exposure to air pollution (AP) is still rather lacking, which therefore we aimed to explore in this study. METHODS: We included 78,230 UK Biobank participants aged 40-70 years with at least 2 typical 24-hour dietary assessments and without baseline diabetes. The annual average concentration of particulate matter with diameter micrometers ≤2.5 (PM2.5) and ≤10 (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX) estimated by land use regression model was the alternative proxy of long-term AP exposure. Three well-known prior DPs such as Mediterranean diet (MED), dietary approaches to stop hypertension diet (DASH), and empirical dietary inflammatory pattern (EDIP), as well as three posterior DPs derived by the rank reduced regression model were used to capture participants' dietary habits. Cox regression models were used to estimate AP-T2D and DP-T2D associations. Modifying effect of DPs on AP-T2D association was assessed using stratified analysis and heterogeneity test. RESULTS: During a median follow-up 12.19 years, 1,693 participants developed T2D. PM2.5, PM10, NO2, and NOX significantly increased the T2D risk (P <0.05), with hazard ratio (HR) and 95% confidence interval (95% CI) for per interquartile range increase being 1.09 (1.02,1.15), 1.04 (1.00, 1.09), 1.11 (1.04, 1.18), and 1.08 (1.03, 1.14), respectively. Comparing high with low adherence, healthy DPs were associated with a 14-41% lower T2D risk. Participants with high adherence to MED, DASH, and anti-EDIP, alongside the posterior anti-oxidative dietary pattern (AODP) had attenuated and statistically non-significant NO2-T2D and NOX-T2D associations (Pmodify <0.05). CONCLUSIONS: Multiple forms of healthy DPs help reduce the T2D risk associated with long-term exposure to NO2 and NOX. Our findings indicate that adherence to healthy DPs is a feasible T2D prevention strategy for people long-term suffering from NO2 and NOX pollution.

Association of ambient air pollution with hemoglobin levels and anemia in the general population of Korean adults.

BACKGROUND: Emerging evidence has suggested significant associations between ambient air pollution and changes in hemoglobin levels or anemia in specific vulnerable groups, but few studies have assessed this relationship in the general population. This study aimed to evaluate the association between long-term exposure to air pollution and hemoglobin concentrations or anemia in general adults in South Korea. METHODS: A total of 69,830 Korean adults from a large-scale nationwide survey were selected for our final analysis. Air pollutants included particulate matter with an aerodynamic diameter less than or equal to 10 micrometers (PM10), particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers, nitrogen dioxide, sulfur dioxide (SO2), and carbon monoxide (CO). We measured the serum hemoglobin concentration to assess anemia for each participant. RESULTS: In the fully adjusted model, exposure levels to PM10, SO2, and CO for one and two years were significantly associated with decreased hemoglobin concentrations (all p < 0.05), with effects ranging from 0.15 to 0.62% per increase in interquartile range (IQR) for each air pollutant. We also showed a significant association of annual exposure to PM10 with anemia (p = 0.0426); the odds ratio (OR) [95% confidence interval (CI)] for anemia per each increase in IQR in PM10 was estimated to be 1.039 (1.001-1.079). This association was also found in the 2-year duration of exposure (OR = 1.046; 95% CI = 1.009-1.083; adjusted Model 2). In addition, CO exposure during two years was closely related to anemia (OR = 1.046; 95% CI = 1.004-1.091; adjusted Model 2). CONCLUSIONS: This study provides the first evidence that long-term exposure to air pollution, especially PM10, is significantly associated with reduced hemoglobin levels and anemia in the general adult population.

Indoor sulfur dioxide prediction through air quality modeling and assessment of sulfur dioxide and nitrogen dioxide levels in industrial and non-industrial areas.

In this study, the levels of sulfur dioxide (SO2) and nitrogen dioxide (NO2) were measured indoors and outdoors using passive samplers in Tymar village (20 homes), an industrial area, and Haji Wsu (15 homes), a non-industrial region, in the summer and the winter seasons. In comparison to Haji Wsu village, the results showed that Tymar village had higher and more significant mean SO2 and NO2 concentrations indoors and outdoors throughout both the summer and winter seasons. The mean outdoor concentration of SO2 was the highest in summer, while the mean indoor NO2 concentration was the highest in winter in both areas. The ratio of NO2 indoors to outdoors was larger than one throughout the winter at both sites. Additionally, the performance of machine learning (ML) approaches: multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) were compared in predicting indoor SO2 concentrations in both the industrial and non-industrial areas. Factor analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO2 for the training set (RMSE = 2.108, MAE = 1.780, and R2 = 0.956) and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully approach the nonlinear relationship between indoor SO2 and input parameters and provide valuable insights to reduce exposure to this harmful pollutant.

Exposure to ambient air pollution and cognitive function: an analysis of the English Longitudinal Study of Ageing cohort.

BACKGROUND: An increasing number of studies suggest adverse effects of exposure to ambient air pollution on cognitive function, but the evidence is still limited. We investigated the associations between long-term exposure to air pollutants and cognitive function in the English Longitudinal Study of Ageing (ELSA) cohort of older adults. METHODS: Our sample included 8,883 individuals from ELSA, based on a nationally representative study of people aged ≥ 50 years, followed-up from 2002 until 2017. Exposure to air pollutants was modelled by the CMAQ-urban dispersion model and assigned to the participants' residential postcodes. Cognitive test scores of memory and executive function were collected biennially. The associations between these cognitive measures and exposure to ambient concentrations of NO2, PM10, PM2.5 and ozone were investigated using mixed-effects models adjusted for time-varying age, physical activity and smoking status, as well as baseline gender and level of education. RESULTS: Increasing long-term exposure per interquartile range (IQR) of NO2 (IQR: 13.05 µg/m3), PM10 (IQR: 3.35 µg/m3) and PM2.5 (IQR: 2.7 µg/m3) were associated with decreases in test scores of composite memory by -0.10 (95% confidence interval [CI]: -0.14, -0.07), -0.02 [-0.04, -0.01] and -0.08 [-0.11, -0.05], respectively. The same increases in NO2, PM10 and PM2.5 were associated with decreases in executive function score of -0.31 [-0.38, -0.23], -0.05 [-0.08, -0.02] and -0.16 [-0.22, -0.10], respectively. The association with ozone was inverse across both tests. Similar results were reported for the London-dwelling sub-sample of participants. CONCLUSIONS: The present study was based on a long follow-up with several repeated measurements per cohort participant and long-term air pollution exposure assessment at a fine spatial scale. Increasing long-term exposure to NO2, PM10 and PM2.5 was associated with a decrease in cognitive function in older adults in England. This evidence can inform policies related to modifiable environmental exposures linked to cognitive decline.

Impacts of urban emissions and air quality in São Paulo State, Brazil.

Daily violations of air quality have an impact on urban populations and cause damage to the environment. Thus, the study evaluated the violations of the daily concentrations of SO2, NO2, and PM10, in regions of the State of São Paulo (SSP), based on the National Environment Council (CONAMA) resolution no 491/2018 and the World Health Organization (WHO - World Health Organization. (2016). Ambient air pollution: a global assessment of exposure and burden of disease.) criteria. Daily SO2, NO2, and PM10data from 6 air quality stations operated by Environmental Company of the State of São Paulo CETESB (1996-2011) were organized and submitted to quality control, with data faults (gaps) being identified. The imputation of data via spline proved satisfactory in filling in the gaps (r > 0.7 and low values of Standard Error of the Estimate (SEE) and Root Mean Square Error (RMSE). The cluster analysis (CA) applied to SO2 formed only one homogeneous group (G1). Contrariwise, NO2 and PM10 formed two homogeneous groups (G1 and G2) each. The stations that showed the greatest similarity according to the CA were Cerqueira Cesar and Osasco. The cophenetic matrix generated for SO2 (0.83), NO2 (0.79), and PM10 (0.77) indicate a satisfactory adjustment of the dendrograms. The exploratory statistics applied to groups G1 and G2 point to the high variability of outliers. The WHO criteria are more restrictive than CONAMA regarding daily violations, with a reduction in SO2 and an increase in specific years for NO2 and PM10. Such variability is due to the adoption of public policies by the SSP and the influence of meteorological systems, being confirmed by the Run test that indicated oscillations in the time series, mainly in PM10, and also recognized well-defined biannual cycles.

Self-assembled peptide nanotubes (SPNTs)/SnO2nanocomposites for high-performance NO2sensing at room temperature.

Nitrogen dioxide (NO2) is a major pollutant that poses significant risks to sustainable human life. As a result, a growing focus has been placed on the development of highly selective and sensitive gas sensors for NO2. Traditional cutting-edge non-organic NO2gas detectors often necessitate stringent production conditions and potentially harmful materials, which are not environmentally friendly, and these shortcomings have limited their widespread practical use. To overcome these challenges, we synthesized self-assembled peptide nanotubes (SPNTs) through a molecular self-assembly process. The SPNTs were then combined with SnO2in varying proportions to construct NO2gas sensors. The design of this sensor ensured efficient electron transfer and leverage the extensive surface area of the SPNTs for enhanced gas adsorption and the effective dispersion of SnO2nanoparticles. Notably, the performance of the sensor, including its sensitivity, response time, and recovery rate, along with a lower detection threshold, could be finely tuned by varying the SPNTs content. This approach illustrated the potential of bioinspired methodologies, using peptide self-assemblies, to develop integrated sensors for pollutant detection, providing a significant development in environmentally conscious sensor technology.

Long-term exposure to ambient air pollution and risk of microvascular complications among patients with type 2 diabetes: a prospective study.

BACKGROUND: Patients with type 2 diabetes (T2D) may disproportionately suffer the adverse cardiovascular effects of air pollution, but relevant evidence on microvascular outcome is lacking. We aimed to examine the association between air pollution exposure and the risk of microvascular complications among patients with T2D. METHODS: This prospective study included 17 995 participants with T2D who were free of macro- and micro-vascular complications at baseline from the UK Biobank. Annual average concentrations of particulate matter (PM) with diameters <2.5 µm (PM2.5), <10 µm (PM10), nitrogen dioxide (NO2) and nitrogen oxides (NOx) were assessed using land use regression models. Cox proportional hazards regression was used to estimate the associations of air pollution exposure with incident diabetic microvascular complications. The joint effects of the air pollutant mixture were examined using quantile-based g-computation in a survival setting. RESULTS: In single-pollutant models, the adjusted hazard ratios (95% confidence intervals) for composite diabetic microvascular complications per interquartile range increase in PM2.5, PM10, NO2 and NOx were 1.09 (1.04-1.14), 1.06 (1.01-1.11), 1.07 (1.02-1.12) and 1.04 (1.00-1.08), respectively. Similar significant results were found for diabetic nephropathy and diabetic neuropathy, but not for diabetic retinopathy. The associations of certain air pollutants with composite microvascular complications and diabetic nephropathy were present even at concentrations below the World Health Organization limit values. Multi-pollutant analyses demonstrated that PM2.5 contributed most to the elevated risk associated with the air pollutant mixture. In addition, we found no interactions between air pollution and metabolic risk factor control on the risk of diabetic microvascular complications. CONCLUSIONS: Long-term individual and joint exposure to PM2.5, PM10, NO2 and NOx, even at low levels, was associated with an increased risk of diabetic microvascular complications, with PM2.5 potentially being the main contributor.

Air Pollutants and Mortality Risk in Patients with Aortic Dissection: Evidence from a Clinical Cohort, Single-Cell Sequencing, and Proteomics.

We aimed to evaluate the association between air pollutants and mortality risk in patients with acute aortic dissection (AAD) in a longitudinal cohort and to explore the potential mechanisms of adverse prognosis induced by fine particulate matter (PM2.5). Air pollutants data, including PM2.5, PM10.0, nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were collected from official monitoring stations, and multivariable Cox regression models were applied. Single-cell sequencing and proteomics of aortic tissue were conducted to explore the potential mechanisms. In total, 1,267 patients with AAD were included. Exposure to higher concentrations of air pollutants was independently associated with an increased mortality risk. The high-PM2.5 group carried approximately 2 times increased mortality risk. There were linear associations of PM10, NO2, CO, and SO2 exposures with long-term mortality risk. Single-cell sequencing revealed an increase in mast cells in aortic tissue in the high-PM2.5 exposure group. Enrichment analysis of the differentially expressed genes identified the inflammatory response as one of the main pathways, with IL-17 and TNF signaling pathways being among the top pathways. Analysis of proteomics also identified these pathways. This study suggests that exposure to higher PM2.5, PM10, NO2, CO, and SO2 are associated with increased mortality risk in patients with AAD. PM2.5-related activation and degranulation of mast cells may be involved in this process.

Association of early-life exposure to air and noise pollution with youth mental health: findings from the ALSPAC cohort.

BACKGROUND: Increasing evidence suggests that air pollution exposure contributes to the development of mental health problems, including psychosis and depression. However, little is known about the importance of early-life exposure, nor the potential role of noise pollution, a correlate of air pollution. We examined the association of exposure to air and noise pollution from pregnancy to age 12 years with three mental health problems assessed at ages 12, 18, and 24 years. METHODS: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC), which tracks the development of about 14 000 babies who had expected delivery dates between April 1, 1991, and Dec 31, 1992, in Avon, UK. This was linked with novel data on nitrogen dioxide, PM2·5, and noise pollution in pregnancy, childhood (ages 1-9 years), and adolescence (ages 10-12 years). Psychotic experiences, depression, and anxiety were measured at ages 12, 18, and 24 years. Logistic regression models were controlled for individual-level, family-level, and area-level confounders, and e-values were calculated to estimate residual confounding. FINDINGS: Participants exposed to higher PM2.5, particularly during pregnancy, had greater odds for psychotic experiences (adjusted odds ratio 1·17 [95% CI 1·05-1·30]) and depression (1·11 [1·01-1·22]). There was little evidence associating nitrogen dioxide or noise pollution with psychotic experiences or depression. Conversely, higher nitrogen dioxide (but not PM2·5) exposure in pregnancy (1·16 [1·01-1·33]), and higher noise pollution in childhood (1·20 [1·06-1·37]) and adolescence (1·17 [1·02-1·35]), were associated with greater odds for anxiety. INTERPRETATION: Our study builds on evidence linking air pollution to psychosis and depression and provides rare longitudinal evidence linking noise pollution to anxiety. Our findings indicate that air pollution exposure earlier in development (eg, during pregnancy) might be particularly important, and suggest a degree of specificity in terms of pollutant-outcome associations. If causal, our findings suggest that interventions to reduce air pollution would improve global mental health. FUNDING: Wellcome Trust, UK Medical Research Council-Wellcome, and University of Bristol.

Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study.

BACKGROUND: Chronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with environmental exposures. METHODS: Our primary objective is to examine creatinine-based estimated glomerular filtration rate (eGFRcr) and diagnosis of CKD and potential associations with fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) using a random sample of North Carolina electronic healthcare records (EHRs) from 2004 to 2016. We estimated eGFRcr using the serum creatinine-based 2021 CKD-EPI equation. PM2.5 and NO2 data come from a hybrid model using 1 km2 grids and O3 data from 12 km2 CMAQ grids. Exposure concentrations were 1-year averages. We used linear mixed models to estimate eGFRcr per IQR increase of pollutants. We used multiple logistic regression to estimate associations between pollutants and first appearance of CKD. We adjusted for patient sex, race, age, comorbidities, temporality, and 2010 census block group variables. RESULTS: We found 44,872 serum creatinine measurements among 7,722 patients. An IQR increase in PM2.5 was associated with a 1.63 mL/min/1.73m2 (95% CI: -1.96, -1.31) reduction in eGFRcr, with O3 and NO2 showing positive associations. There were 1,015 patients identified with CKD through e-phenotyping and ICD codes. None of the environmental exposures were positively associated with a first-time measure of eGFRcr < 60 mL/min/1.73m2. NO2 was inversely associated with a first-time diagnosis of CKD with aOR of 0.77 (95% CI: 0.66, 0.90). CONCLUSIONS: One-year average PM2.5 was associated with reduced eGFRcr, while O3 and NO2 were inversely associated. Neither PM2.5 or O3 were associated with a first-time identification of CKD, NO2 was inversely associated. We recommend future research examining the relationship between air pollution and impaired renal function.

Nitrogen dioxide exposure, attentional function, and working memory in children from 4 to 8 years: Periods of susceptibility from pregnancy to childhood.

BACKGROUND: Air pollution exposure during pregnancy and childhood has been linked to executive function impairment in children, however, very few studies have assessed these two exposure periods jointly to identify susceptible periods of exposure. We sought to identify potential periods of susceptibility of nitrogen dioxide (NO2) exposure from conception to childhood on attentional function and working memory in school-aged children. METHODS: Within the Spanish INMA Project, we estimated residential daily NO2 exposures during pregnancy and up to 6 years of childhood using land use regression models (n = 1,703). We assessed attentional function at 4-6 years and 6-8 years, using the Conners Kiddie Continuous Performance Test and the Attention Network Test, respectively, and working memory at 6-8 years, using the N-back task. We used distributed lag non-linear models to assess the periods of susceptibility of each outcome, adjusting for potential confounders and correcting for multiple testing. We also stratified all models by sex. RESULTS: Higher exposure to NO2 between 1.3 and 1.6 years of age was associated with higher hit reaction time standard error (HRT-SE) (0.14 ms (95 % CI 0.05; 0.22) per 10 µg/m3 increase in NO2) and between 1.5 and 2.2 years of age with more omission errors (1.02 (95 % CI 1.01; 1.03) of the attentional function test at 4-6 years. Higher exposure to NO2 between 0.3 and 2.2 years was associated with higher HRT-SE (10.61 ms (95 % CI 3.46; 17.75) at 6-8 years only in boys. We found no associations between exposure to NO2 and working memory at 6-8 years. CONCLUSION: Our findings suggest that NO2 exposure during the first two years of life is associated with poorer attentional function in children from 4 to 8 years of age, especially in boys. These findings highlight the importance of exploring long-term effects of traffic-related air pollution exposure in older age groups.

Dynamic and stationary monitoring of air pollutant exposures and dose during marathons.

Marathon running significantly increases breathing volumes and, consequently, air pollution inhalation doses. This is of special concern for elite athletes who ventilate at very high rates. However, race organizers and sport governing bodies have little guidance to support events scheduling to protect runners. A key limitation is the lack of hyper-local, high temporal resolution air quality data representative of exposure along the racecourse. This work aimed to understand the air pollution exposures and dose inhaled by athletes, by means of a dynamic monitoring methodology designed for road races. Air quality monitors were deployed during three marathons, monitoring nitrogen dioxide (NO2), ozone (O3), particulate matter (PMx), air temperature, and relative humidity. One fixed monitor was installed at the Start/Finish line and one mobile monitor followed the women elite runner pack. The data from the fixed monitors, deployed prior the race, described daily air pollution trends. Mobile monitors in combination with heatmap analysis facilitated the hyper-local characterization of athletes' exposures and helped identify local hotspots (e.g., areas prone to PM resuspension) which should be preferably bypassed. The estimation of inhaled doses disaggregated by gender and ventilation showed that doses inhaled by last finishers may be equal or higher than those inhaled by first finishers for O3 and PMx, due to longer exposures as well as the increase of these pollutants over time (e.g., 58.2 ± 9.6 and 72.1 ± 23.7 µg of PM2.5 for first and last man during Rome marathon). Similarly, men received significantly higher doses than women due to their higher ventilation rate, with differences of 31-114 µg for NO2, 79-232 µg for O3, and 6-41 µg for PMx. Finally, the aggregated data obtained during the 4 week- period prior the marathon can support better race scheduling by the organizers and provide actionable information to mitigate air pollution impacts on athletes' health and performance.

Air pollution exposure may impact the composition of human milk oligosaccharides.

Human milk oligosaccharides (HMOs) impact neonate immunity and health outcomes. However, the environmental factors influencing HMO composition remain understudied. This study examined the associations between ambient air pollutant (AAP) exposure and HMOs at 1-month postpartum. Human milk samples were collected at 1-month postpartum (n = 185). AAP (PM2.5, PM10, NO2) exposure included the 9-month pregnancy period through 1-month postpartum. Associations between AAP with (1) HMO diversity, (2) the sum of sialylated and fucosylated HMOs, (3) 6 a priori HMOs linked with infant health, and (4) all HMOs were examined using multivariable linear regression and principal component analysis (PCA). Exposure to AAP was associated with lower HMO diversity. PM2.5 and PM10 exposure was positively associated with the HMO 3-fucosyllactose (3FL); PM2.5 exposure was positively associated with the sum of total HMOs, sum of fucosylated HMOs, and the HMO 2'-fucosyllactose (2'FL). PCA indicated the PM2.5, PM10, and NO2 exposures were associated with HMO profiles. Individual models indicated that AAP exposure was associated with five additional HMOs (LNFP I, LNFP II, DFLNT, LNH). This is the first study to demonstrate associations between AAP and breast milk HMOs. Future longitudinal studies will help determine the long-term impact of AAP on human milk composition.

Assessing the Global Impact of Ambient Air Pollution on Cancer Incidence and Mortality: A Comprehensive Meta-Analysis.

PURPOSE: This study aims to examine the association between exposure to major ambient air pollutants and the incidence and mortality of lung cancer and some nonlung cancers. METHODS: This meta-analysis used PubMed and EMBASE databases to access published studies that met the eligibility criteria. Primary analysis investigated the association between exposure to air pollutants and cancer incidence and mortality. Study quality was assessed using the Newcastle Ottawa Scale. Meta-analysis was conducted using R software. RESULTS: The meta-analysis included 61 studies, of which 53 were cohort studies and eight were case-control studies. Particulate matter 2.5 mm or less in diameter (PM2.5) was the exposure pollutant in half (55.5%), and lung cancer was the most frequently studied cancer in 59% of the studies. A pooled analysis of exposure reported in cohort and case-control studies and cancer incidence demonstrated a significant relationship (relative risk [RR], 1.04 [95% CI, 1.02 to 1.05]; I2, 88.93%; P < .05). A significant association was observed between exposure to pollutants such as PM2.5 (RR, 1.08 [95% CI, 1.04 to 1.12]; I2, 68.52%) and nitrogen dioxide (NO2) (RR, 1.03 [95% CI, 1.01 to 1.05]; I2, 73.52%) and lung cancer incidence. The relationship between exposure to the air pollutants and cancer mortality demonstrated a significant relationship (RR, 1.08 [95% CI, 1.07 to 1.10]; I2, 94.77%; P < .001). Among the four pollutants, PM2.5 (RR, 1.15 [95% CI, 1.08 to 1.22]; I2, 95.33%) and NO2 (RR, 1.05 [95% CI, 1.02 to 1.08]; I2, 89.98%) were associated with lung cancer mortality. CONCLUSION: The study confirms the association between air pollution exposure and lung cancer incidence and mortality. The meta-analysis results could contribute to community cancer prevention and diagnosis and help inform stakeholders and policymakers in decision making.

Association between ambient air pollutants and short-term mortality risks during 2015-2019 in Guangzhou, China.

With the development of technology and industry, the problem of global air pollution has become difficult to ignore. We investigated the association between air pollutant concentrations and daily all-cause mortality and stratified the analysis by sex, age, and season. Data for six air pollutants [fine particulate matter (PM2.5), inhalable particles (PM10), nitric dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and daily mortality rates were collected from 2015 to 2019 in Guangzhou, China. A time-series study using a quasi-Poisson generalized additive model was used to examine the relationships between environmental pollutant concentrations and mortality. Mortality data for 296,939 individuals were included in the analysis. The results showed that an increase of 10 µg/m3 in the concentrations of PM2.5, PM10, SO2, O3, NO2, and CO corresponded to 0.84% [95% confidence interval (CI): 0.47, 1.21%], 0.70% (0.44, 0.96%), 3.59% (1.77, 5.43%), 0.21% (0.05, 0.36%), 1.06% (0.70, 1.41%), and 0.05% (0.02, 0.09%), respectively. The effects of the six air pollutants were more significant for male individuals than female individuals, the cool season than the warm season, and people 75 years or older than those younger than 75 years. PM2.5, PM10, SO2, and NO2 were all associated with neoplasms and circulatory and respiratory diseases. The two-pollutant models found that PM2.5, PM10, and NO2 may independently affect the risk of mortality. The results showed that exposure to PM2.5, PM10 and NO2 may increase the risk of daily all-cause excessive mortality in Guangzhou.

Investigation of formaldehyde sources and its relative emission intensity in shipping channel environment.

Formaldehyde (HCHO) is considered one of the most abundant gas-phase carbonyl compounds in the atmosphere, which can be directly emitted through transportation sources. Long-Path Differential Optical Absorption Spectroscopy (LP-DOAS) was used to observe HCHO in the river channel of Wusong Wharf in Shanghai, China for the whole year of 2019. Due to the impact of ship activity, the annual average HCHO level in the channel is about 2.5 times higher than that in the nearby campus environment. To explain the sources of HCHO under different meteorological conditions, the tracer-pair of CO and Ox (NO2+O3) was used on the clustered air masses. The results of the source appointment show that primary, secondary and background account for 24.14% (3.34 ± 1.19 ppbv), 44.78% (6.20 ± 2.04 ppbv) and 31.09% (4.31 ± 2.33 ppbv) of the HCHO in the channel when the air masses were from the mixed direction of the city and channel, respectively. By performing background station subtraction at times of high primary HCHO values and resolving the plume peaks, directly emitted HCHO/NO2 in the channel environment and plume were determined to be mainly distributed between 0.2 and 0.3. General cargo ships with higher sailing speeds or main engine powers tend to have higher HCHO/NO2 levels. With the knowledge of NO2 (or NOx) emission levels from ships, this study may provide data support for the establishment of HCHO emission factors.

Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany).

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone ( O 3 ), nitrogen dioxide ( NO 2 ), particulate matter ( P M 2.5 , P M 10 ) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (-0.84), April (-0.47), and October (-0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O 3 and NO 2 . Spatially, NO 2 , P M 2.5 , and P M 10 concentrations were significantly higher in urban than rural regions. For O 3 , this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

Population exposure to multiple air pollutants and its compound episodes in Europe.

Air pollution remains as a substantial health problem, particularly regarding the combined health risks arising from simultaneous exposure to multiple air pollutants. However, understanding these combined exposure events over long periods has been hindered by sparse and temporally inconsistent monitoring data. Here we analyze daily ambient PM2.5, PM10, NO2 and O3 concentrations at a 0.1-degree resolution during 2003-2019 across 1426 contiguous regions in 35 European countries, representing 543 million people. We find that PM10 levels decline by 2.72% annually, followed by NO2 (2.45%) and PM2.5 (1.72%). In contrast, O3 increase by 0.58% in southern Europe, leading to a surge in unclean air days. Despite air quality advances, 86.3% of Europeans experience at least one compound event day per year, especially for PM2.5-NO2 and PM2.5-O3. We highlight the improvements in air quality control but emphasize the need for targeted measures addressing specific pollutants and their compound events, particularly amidst rising temperatures.

Physical Activity-Induced Modification of the Association of Long-Term Air Pollution Exposure with the Risk of Depression in Older Adults.

PURPOSE: Evidence suggests that long-term air pollution exposures may induce depression; however, the influence of physical activity on this effect is unclear. We investigated modification of the associations between air pollution exposures and depression by the intensity of physical activity. MATERIALS AND METHODS: This cross-sectional study included 1454 Korean adults. Depression was defined as a Geriatric Depression Scale score ≥8. Concentrations of particulate matter (PM10 and PM2.5: diameter ≤10 µm and ≤2.5 µm, respectively) and nitrogen dioxide (NO2) level at each participant's residential address were estimated. Based on metabolic equivalents, physical activity intensity was categorized as inactive, minimally active, or health-enhancing physical activity (HEPA). RESULTS: Each 1-part per billion (ppb) NO2 concentration increase was significantly associated with a 6% [95% confidence interval (CI), 4%-8%] increase in depression risk. In older adults (≥65 years), a 1-ppb NO2 increase was associated (95% CI) with a 4% (1%-7%), 9% (5%-13%), and 21% (9%-33%) increase in depression risk in the inactive, minimally active, and HEPA groups, respectively. Compared with the inactive group, the minimally active (p=0.039) and HEPA groups (p=0.004) had higher NO2 exposure-associated depression risk. Associations of PM10 and PM2.5 with depression did not significantly differ by the intensity of physical activity. CONCLUSION: We suggest that older adults who vigorously exercise outdoors may be susceptible to air pollution-related depression.