Patterns of Emergency Room Visits for Respiratory Diseases in New York State in Relation to Air Pollution, Poverty and Smoking

Estimating exposure to pollutants generated from indoor and outdoor sources within vulnerable populations using personal air quality monitors: A London case study

Personal exposure to air pollution can originate from indoor or outdoor sources, depending on location and activity. This study aimed to quantify personal exposure from each source separately, allowing comparison of the associated epidemiological estimates from each source type. We utilised 12,901 participant-day personal measurements of exposure to multiple pollutants collected from 344 London dwelling participants of four panel studies conducted between 2015 and 2019. A four-step process was applied to personal measurements incorporating 1) GPS spatial analysis including address identification and location tagging; 2) estimating outdoor home pollutant levels from matched fixed ambient monitors; 3) calculation of infiltration efficiency when participants were at home; and 4) indoor and outdoor source separation for personal exposure measurements. From the results, our participants with Chronic Obstructive Pulmonary Disease (COPD) dataset had an average (SD) personal exposure from outdoor sources of 4.0 (1.3) μg/m3 for NO2 and 5.1 (3.0) μg/m3 for PM2.5, the school children's average (SD) personal exposure to PM2.5 from outdoor sources was 5.5 (4.3) μg/m3, the professional drivers' average (SD) personal exposure to black carbon from outdoor sources was 1.7 (1.0) μg/m3, and the healthy young adults' average (SD) personal exposure to black carbon from outdoor sources was 1.2 (0.5) μg/m3. Compared to the average total personal exposures, outdoor sources accounted for 49 % of NO2 exposure, 41 % to 55 % of PM2.5, and 60 % to 85 % of black carbon, dependent on the panel study - demonstrating a strong influence from outdoor sources for personal exposures to air pollution in London. Our findings highlighted that endeavours should continue to be made towards reducing pollution from both outdoor and indoor sources. The between-panel and within-panel exposure differences, derived from our novel partitioning methodology, can contribute to the estimation of health effects from indoor and outdoor sources and inform targeted interventions for vulnerable groups.

PM2.5 and its components and respiratory disease healthcare encounters - Unanticipated increased exposure-response relationships in recent years after environmental policies

Prior studies reported excess rates (ERs) of cardiorespiratory events associated with short-term increases in PM2.5 concentrations, despite implementation of pollution-control policies. In 2017, Federal Tier 3 light-duty vehicle regulations began, and to-date there have been no assessments of population health effects of the policy. Using the NYS Statewide Planning and Research Cooperative System (SPARCS) database, we obtained hospitalizations and ED visits with a principal diagnosis of asthma or chronic obstructive pulmonary disease (COPD) for residents living within 15 miles of six urban PM2.5 monitoring sites in NYS (2014-2019). We used a time-stratified case-crossover design and conditional logistic regression (adjusting for ambient temperature, relative humidity, and weekday) to estimate associations between PM2.5, POC (primary organic carbon), SOC (secondary organic carbon), and rates of respiratory disease hospitalizations and emergency department (ED) visits from 2014 to 2019. We evaluated demographic disparities in these relative rates and compared changes in ERs before (2014-2016) and after Tier 3 implementation (2017-2019). Each interquartile range increase in PM2.5 was associated with increased ERs of asthma or COPD hospitalizations and ED visits in the previous 7 days (ERs ranged from 1.1%-3.1%). Interquartile range increases in POC were associated with increased rates of asthma ED visits (lag days 0-6: ER = 2.1%, 95% CI = 0.7%, 3.6%). Unexpectedly, the ERs of asthma admission and ED visits associated with PM2.5, POC, and SOC were higher during 2017-2019 (after Tier 3) than 2014-2016 (before Tier-3). Chronic obstructive pulmonary disease analyses showed similar patterns. Excess Rates were higher in children (<18 years; asthma) and seniors (≥65 years; COPD), and Black, Hispanic, and NYC residents. In summary, unanticipated increases in asthma and COPD ERs after Tier-3 implementation were observed, and demographic disparities in asthma/COPD and PM2.5, POC, and SOC associations were also observed. Future work should confirm findings and investigate triggering of respiratory events by source-specific PM.

Differences in cellular and molecular processes in exposure to PM2.5 and O3

Epidemiological and toxicological studies have shown that PM2.5 and O3 could pose significant risks to human health, such as an increased incidence of respiratory and cardiovascular diseases. Usually, the adverse health outcomes induced by PM2.5 and O3 exposure are similar. However, PM2.5 and O3 have distinct physical and chemical properties, with PM2.5 being a solid-liquid mixture and O3 being a strongly oxidizing gaseous pollutant. Therefore, we speculated that there are some differences in biological processes induced by PM2.5 and O3 exposure. In the present study, we investigated the differences induced by PM2.5 and O3 exposure from the perspective of cellular and molecular processes. Firstly, the pulmonary epithelial cells (BEAS-2B) were exposed to different concentrations of PM2.5 or O3 at different durations. Then, we chose experimental models with the concentrations and duration at which the cell survival rate was 50 % after exposure to PM2.5 and O3, which were 100 μg/mL for 24 h for PM2.5, and 200 ppb for 4 h for O3. Our findings indicate that PM2.5 infiltrates cells via endocytosis without causing significant damage to cell membranes, while O3 induces lipid peroxidation at the cell surface. Moreover, the detection of mitochondrial function showed that the content of ATP was significantly reduced after exposure to both PM2.5 and O3. However, we found a significant difference in mtDNA copy number. PM2.5 exposure increased the mtDNA copy number by up-regulating the expression of fission genes (Fis1, Mff, Dnm1). O3 exposure decreased it by up-regulating the expression of fusion gene (Mfn1, Mfn2) and down-regulating the expression of fission gene (Fis1, Dnm1). These results indicate that although both PM2.5 and O3 exposure induced almost exactly similar adverse health outcomes, significant differences do exist in cellular and molecular processes.

Disease types and pathogenic mechanisms induced by PM2.5 in five human systems: An analysis using omics and human disease databases

Atmospheric fine particulate matter (PM2.5) can harm various systems in the human body. Due to limitations in the current understanding of epidemiology and toxicology, the disease types and pathogenic mechanisms induced by PM2.5 in various human systems remain unclear. In this study, the disease types induced by PM2.5 in the respiratory, circulatory, endocrine, and female and male urogenital systems have been investigated and the pathogenic mechanisms identified at molecular level. The results reveal that PM2.5 is highly likely to induce pulmonary emphysema, reperfusion injury, malignant thyroid neoplasm, ovarian endometriosis, and nephritis in each of the above systems respectively. The most important co-existing gene, cellular component, biological process, molecular function, and pathway in the five systems targeted by PM2.5 are Fos proto-oncogene (FOS), extracellular matrix, urogenital system development, extracellular matrix structural constituent conferring tensile strength, and ferroptosis respectively. Differentially expressed genes that are significantly and uniquely targeted by PM2.5 in each system are BTG2 (respiratory), BIRC5 (circulatory), NFE2L2 (endocrine), TBK1 (female urogenital) and STAT1 (male urogenital). Important disease-related cellular components, biological processes, and molecular functions are specifically induced by PM2.5. For example, response to wounding, blood vessel morphogenesis, body morphogenesis, negative regulation of response to endoplasmic reticulum stress, and response to type I interferon are the top uniquely existing biological processes in each system respectively. PM2.5 mainly acts on key disease-related pathways such as the PD-L1 expression and PD-1 checkpoint pathway in cancer (respiratory), cell cycle (circulatory), apoptosis (endocrine), antigen processing and presentation (female urogenital), and neuroactive ligand-receptor interaction (male urogenital). This study provides a novel analysis strategy for elucidating PM2.5-related disease types and is an important supplement to epidemiological investigation. It clarifies the risks of PM2.5 exposure, elucidates the pathogenic mechanisms, and provides scientific support for promoting the precise prevention and treatment of PM2.5-related diseases.

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.