Critical air pollutant assessments and health effects attributed to PM2.5 during and after COVID-19 lockdowns in Iran: application of AirQ+ models

Association between chronic PM2.5 exposure and neurodegenerative biomarkers in adults from critically polluted area

BACKGROUND

Air pollution is a significant public health concern, increasingly recognized for its association with adverse health outcomes including neurodegenerative and neuroinflammatory conditions. The present study aimed to characterize plasma levels of key biomarkers related to neurodegeneration and neuroinflammation among middle-aged to elderly adults living in areas designated as critically polluted.

METHODS

A total of 202 adults, aged 41 to 60 years, residing in CPA (CEPI > 70) for over ten years were recruited in the study. The exposures of air pollutant were measured as per the established protocols by CPCB. The plasma levels of neurodegenerative markers (Aβ(1-42), Total τ, α-Synuclein, BDNF and GFAP) were estimated using commercially available ultra-sensitive ELISA kits. The data analysis was performed through mean and standard deviation, percentile distribution and multivariate logistic regression using SPSS 26.0.

RESULTS

This study confirmed the elevated PM2.5 levels at the study location exceeding the regulatory limits. Women exhibited relatively higher Amyloid Aβ(1-42), α-Synuclein and GFAP levels, while men exhibited relatively higher Total τ, & BDNF levels. Further, older participants (aged 50 - 60 years) exhibited higher levels of all markers but α-Synuclein, as compared to the younger peers (aged 40 - 50 years). A weak positive trend (p = 0.08) was observed for α-Synuclein with prolonged exposure.

CONCLUSION

This study is among the first community-based investigations in India to assess plasma levels of neurodegenerative and neuroinflammatory biomarkers in apparently healthy adults chronically exposed to high ambient air pollution. By integrating chronic exposure data from a Critically Polluted Area (CEPI > 70) with biomarker profiling, the study offers early insights into potential neurobiological alterations associated with environmental pollutants, highlighting sex- and age-specific vulnerabilities. These findings emphasize the importance of considering environmental influences in neurodegenerative disease research and the potential need for tailored health interventions.

COPD Exacerbations, Air Pollutant Fluctuations, and Individual-Level Factors in the Pandemic Era

Purpose

Pandemic-era associations between air pollutant exposures and exacerbations of chronic obstructive pulmonary disease (COPD) are under-explored. Given the considerable observed pandemic-era pollutant fluctuations, these associations were investigated along with possible individual-level risk factors.

Patients and Methods

Participants with spirometry-confirmed COPD from Canadian Cohort Obstructive Lung Disease (CanCOLD) were included, with data collected before ("pre-pandemic") and during ("pandemic") the COVID-19 pandemic. Nitrogen dioxide (NO2), fine particulate matter (PM2.5), ground-level ozone (O3), total oxidant (Ox) and weather data were obtained from national databases. Associations between each air pollutant and "symptom-based" exacerbations (increased dyspnea or sputum volume/purulence ≥48hrs) and "event-based" exacerbations ("symptom-based" plus requiring antibiotics, corticosteroids, or unscheduled healthcare use) were estimated in separate models. Generalized estimating equations (GEE) models were reported as rate ratios (RRs) per interquartile range (IQR) increment in pollutant concentration with 95% confidence intervals (95% CIs).

Results

NO2, PM2.5, and Ox (NO2+O3) concentrations (but not O3) fell significantly during the pandemic. In the 673 participants with COPD included, both symptom-based and event-based exacerbation rates were likewise significantly higher during the pre-pandemic period. During the pre-pandemic period, Ox was positively associated with symptom-based exacerbations (RR: 1.21 [1.08,1.36]). During the pandemic period, Ox was positively associated with symptom-based (1.46 [1.13,1.89]) and event-based (1.43 [1.00,2.05]) exacerbations. Fewer self-reported pandemic protective behaviors, and higher viral infectious symptoms, were also associated with exacerbations. In stepwise multivariable risk-factor analyses, female gender (1.23 [1.04,1.45] and 1.41 [1.13,1.76]) and co-morbid asthma (1.65 [1.34,2.03] and 1.54 [1.19,2.00]) were associated with symptom-based and event-based exacerbations, respectively, blood eosinophils (1.42 [1.10,1.84]) were associated with event-based exacerbations, and each IQR increment in Ox was associated with symptom-based exacerbations (1.31 [1.06,1.61]).

Conclusion

Ox exposure was consistently associated with symptom-based COPD exacerbations, and female gender, co-morbid asthma, and blood eosinophilia were found to be relevant risk factors.

Risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 over 2017-2022 in Sanandaj, an area of Iran

The risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 has been less investigated. In this study, the attributable risk was estimated in an area of Iran. The predicted air PM2.5 using satellite data and a two-stage regression model was used as the predictor of the diseases. The dose-response linkage between the bias-corrected predictor employing a strong statistical approach and the outcomes was evaluated using the distributed lag nonlinear model. We considered two distinct scenarios of PM2.5 for the risk estimation. Alongside the risk, the attributable risk and number were estimated for different levels of PM2.5 by age and gender categories. The cumulative influence of PM2.5 particles on respiratory illnesses was statistically significant at 13-16 µg/m3 relative to the reference value (median), mostly apparent in the middle delays. The cumulative relative risk of 90th and 95th percentiles were 2.03 (CI 95%: 1.28, 3.19) and 2.25 (CI 95%: 1.28, 3.96), respectively. Nearly 600 cases of the diseases were attributable to the non-optimum values of the pollutant during 2017-2022, of which more than 400 cases were attributed to high values range. The predictor's influence on cardiovascular illnesses was along with uncertainty, indicating that additional research into their relationship is needed. The bias-corrected PM2.5 played an essential role in the prediction of respiratory illnesses, and it may likely be employed as a trigger for a preventative strategy.

Fine particulate matter air pollution and health implications for Nairobi, Kenya

Background

Continuous ambient air quality monitoring in Kenya has been limited, resulting in a sparse data base on the health impacts of air pollution for the country. We have operated a centrally located monitor in Nairobi for measuring fine particulate matter (PM2.5), the pollutant that has demonstrated impact on health. Here, we describe the temporal levels and trends in PM2.5 data for Nairobi and evaluate associated health implications.

Methods

We used a centrally located reference sensor, the beta attenuation monitor (BAM-1022), to measure hourly PM2.5 concentrations over a 3-year period (21 August 2019 to 20 August 2022). We used, at minimum, 75% of the daily hourly concentration to represent the 24-hour concentrations for a given calendar day. To estimate the deaths attributable to air pollution, we used the World Health Organization (WHO) AirQ+ tool with input as PM2.5 concentration data, local mortality statistics, and population sizes.

Results

The daily (24-hour) mean (±SEM) PM2.5 concentration was 19. 2 ± 0.6 (µg/m3). Pollutant levels were lowest at 03:00 and, peaked at 20:00. Sundays had the lowest daily concentrations, which increased on Mondays and remained high through Saturdays. By season, the pollutant concentrations were lowest in April and highest in August. The mean annual concentration was 18.4 ± 7.1 (µg/m3), which was estimated to lead to between 400 and 1,400 premature deaths of the city's population in 2021 hence contributing 5%-8% of the 17,432 adult deaths excluding accidents when referenced to WHO recommended 2021 air quality guideline for annual thresholds of 5 µg/m3.

Conclusion

Fine particulate matter air pollution in Nairobi showed daily, day-of-week, and seasonal fluctuations consistent with the anthropogenic source mix, particularly from motor vehicles. The long-term population exposure to PM2.5 was 3.7 times higher than the WHO annual guideline of 5 µg/m3 and estimated to lead to a substantial burden of attributable deaths. An updated regulation targeting measures to reduce vehicular emissions is recommended.

Elossaily G, Vellapandian C, Prajapati B. Investigating the Potential Impact of Air Pollution on Alzheimer's Disease and the Utility of Multidimensional Imaging for Early Detection

Pollution is ubiquitous, and much of it is anthropogenic in nature, which is a severe risk factor not only for respiratory infections or asthma sufferers but also for Alzheimer's disease, which has received a lot of attention recently. This Review aims to investigate the primary environmental risk factors and their profound impact on Alzheimer's disease. It underscores the pivotal role of multidimensional imaging in early disease identification and prevention. Conducting a comprehensive review, we delved into a plethora of literature sources available through esteemed databases, including Science Direct, Google Scholar, Scopus, Cochrane, and PubMed. Our search strategy incorporated keywords such as "Alzheimer Disease", "Alzheimer's", "Dementia", "Oxidative Stress", and "Phytotherapy" in conjunction with "Criteria Pollutants", "Imaging", "Pathology", and "Particulate Matter". Alzheimer's disease is not only a result of complex biological factors but is exacerbated by the infiltration of airborne particles and gases that surreptitiously breach the nasal defenses to traverse the brain, akin to a Trojan horse. Various imaging modalities and noninvasive techniques have been harnessed to identify disease progression in its incipient stages. However, each imaging approach possesses inherent limitations, prompting exploration of a unified technique under a single umbrella. Multidimensional imaging stands as the linchpin for detecting and forestalling the relentless march of Alzheimer's disease. Given the intricate etiology of the condition, identifying a prospective candidate for Alzheimer's disease may take decades, rendering the development of a multimodal imaging technique an imperative. This research underscores the pressing need to recognize the chronic ramifications of invisible particulate matter and to advance our understanding of the insidious environmental factors that contribute to Alzheimer's disease.