Ambient PM2.5 and PM10 Exposure and Respiratory Disease Hospitalization in Kandy, Sri Lanka

The size distribution of nanoparticles emitted from advanced manufacturing devices impacts predicted carcinogenic potential

Advanced manufacturing devices such as 3D printers bring users into closer contact with processes that generate ultrafine particles or release engineered nanomaterials. While approaches to assessing the risk of lung carcinogenesis and related health effects are developing, serious questions exist regarding the impact such devices may have on human health and safety if proper actions (i.e., engineering controls including ventilation or filtration) are not taken to mitigate exposures. The size distribution of particulates emitted during fused deposition modeling (FDM) 3D printing was measured following the ANSI/CAN/UL 2904 method and associated lung cancer risk was estimated through a developing model. Particulate morphologies were assessed, identifying agglomerative and morphological characteristics which may further impact health effects. The estimation of excess lung cancer risk for 3D printer emissions based upon particle size was found to vary according to aerodynamic diameter distribution and emitted concentration, with values projected as high as 468 cases per 10,000 workers in the measured exposure scenario (1 m3 enclosure with air fully exchanged once per hour); predicted excess lung cancer risk was found to drop significantly as print extrusion temperature decreased. Actual health impacts will depend highly upon the exposure scenario, as room air volume, ventilation, and number of printers in operation will impact the concentration of particulates present. This model provides a means for assessing excess lung cancer risk across a broad aerodynamic diameter distribution, improving resolution over methods that use a single particle size bin such as PM2.5 or PM10. The effects of particle composition are only anecdotally considered in this model, however; this limitation should be accommodated as the model is implemented in practical settings.

Moderating effect of green space on relationship between atmospheric particulate matter and cardiovascular and cerebrovascular disease mortality in Ningxia, China

OBJECTIVE

This study explores the moderating effect of green space on the association between atmospheric particulate matter (PM) and cardiovascular and cerebrovascular disease (CCVD) mortality.

METHODS

Data on CCVD mortality, PM, meteorological factors, and the Normalized Difference Vegetation Index (NDVI) of green spaces in Ningxia from 2010 to 2020 were collected. A time-series generalized additive mixed-effect model (GAMM) was applied to analyze the exposure-response relationship between PM and CCVD mortality. The moderating effect of green spaces was examined using green space buffers of different radii (300 m, 500 m, 1000 m, and 2000 m) and density.

RESULTS

There were 150,356 CCVD deaths in Ningxia during the study period. The annual mean concentrations of PM2.5 and PM10 were 44.44 μg/m³ and 105.30 μg/m³, respectively, with an annual mean NDVI value of 0.25 within a 500 m radius buffer. An increase of 10 μg/m³ in PM2.5 and PM10 concentrations was significantly associated with an elevated risk of CCVD mortality, with the strongest excess risk (ER) observed at lag07 lag. The ER for PM2.5 was 1.43% (95% CI: 0.97%, 1.89%), and for PM10 was 0.55% (95% CI: 0.38%, 0.72%). The interaction analysis indicated that higher green space density could moderate the association between PM exposure and CCVD mortality risk. and as the green space buffer zone expanded, the interaction on CCVD mortality risk progressively strengthened. The independent moderation analysis indicated that an increase in green space buffer zone was associated with a reduced risk, and as green space density increased from Q1 to Q3, the ER for PM2.5-related CCVD mortality decreased from 1.56% to 0.6%, while the ER for PM10-related CCVD mortality decreased from 0.53% to 0.09%. In conclusion, atmospheric PM is associated with increased CCVD mortality risk, while larger green space buffers and higher green space density significantly moderated this association.

A comparative analysis of three PM2.5 exposure metrics and their impact on respiratory disease hospitalizations in Lanzhou, China

Research on the associations between PM2.5 and total respiratory diseases (RD) in Lanzhou is limited. We investigated the short-term impact of PM2.5 on total RD hospitalizations in Lanzhou (2015-2019) using various exposure metrics. We collected data on hospitalizations, daily air pollutant concentrations, and meteorological factors during the study period. Daily excessive concentration hours (DECH) were calculated according to the World Health Organization's air quality guidelines. A distributional lag nonlinear model (DLNM) based on a generalized additive model (GAM) was used to comparatively analyze the association between three PM2.5 exposure metrics (DECH (DECH PM2.5), daily mean concentration (Mean PM2.5), and hourly peak concentration (Peak PM2.5)) and RD hospitalizations. Subgroup analyses and sensitivity analyses were also performed. We found similar effects on RD hospitalizations using DECH PM2.5 and Mean PM2.5, but relatively weak associations observed using Peak PM2.5. The cumulative lag effect increased daily. Subgroup analyses showed that females and children aged 0-17 years were more susceptible to PM2.5 pollution and that the association was enhanced during the cold season. Our research strengthened the evidence that exposure to ambient PM2.5 increases the risk of RD. This study revalidated the reliability of the new metrics and confirmed that DECH PM2.5 effect estimates for exposure-disease were more accurate than the Mean PM2.5.

Air Pollutants Associated Hospitalization in Pediatric Pneumonia: A National Database Analysis

BACKGROUND

Pneumonia ranks as a leading contributor to hospital admissions and mortality among children worldwide. This study aimed to investigate the association between aerosol components of air pollution and pediatric pneumonia hospitalization.

METHODS

Employing an observational study design, data from hospitalized children under 15 years diagnosed with pneumonia in Thailand from 2015 to 2019 were analyzed to ascertain the relationship between air pollution and health outcomes. Utilizing the Modern-Era Retrospective analysis for Research and Application version 2 (MERRA-2) data for aerosol components, and adjusting for demographic and geographical factors, using Poisson regression models.

RESULTS

A total of 732,700 children were hospitalized with pneumonia, with children under the age of five accounting for the majority of admissions (637,313 cases, 86.9%). Dust had the strongest association with the incidence rate ratio of hospitalization in children with pneumonia across all age groups. The incidence rate ratio was 1.288 (95% CI: 1.271-1.304, p < 0.001), 1.392 (95%CI: 1.344-1.442, p < 0.001), and 1.349 (95%CI: 1.265-1.439, p < 0.001) for children under the age of 5, 5 to under 10, and 10 to under 15, respectively. The association of hospitalization among children with pneumonia increased by 21.0% and 13.8% for each 1 μg/m3 increase in black carbon and dust levels, respectively.

CONCLUSION

The findings reveal a compelling link between certain air pollutants and pediatric pneumonia hospitalization, highlighting the urgent need for targeted interventions to mitigate air pollution's adverse effects.

Modifying factors and temporal trends of adverse health effects of short-term exposure to PM2.5 in Canada (2001-2018)

Considerable evidence has been accumulated on serious acute health outcomes associated with short-term exposure to ambient fine particulate matter (PM2.5). Modifying factors of those associations, however, have been less explored and need further analyses. In this national study, we investigated whether short-term effects of PM2.5 are modified according to region, cause of mortality/hospitalization, season, age, and sex. PM2.5-related adverse health effects were estimated by an ecological time-series study, covering about 80 % of the Canadian population for 18 years (2001-2018). We estimated city-specific associations using daily averages of PM2.5 and temperature, and daily counts of hospitalizations and mortality (non-accidental all-cause, circulatory, and respiratory). National and regional associations were then estimated with a 2-stage model. We considered potential modifying factors of PM2.5-related adverse health effects, and examined linear trends in the annual associations. Nationally, PM2.5 exposure was associated with both hospitalizations and mortality, and there was evidence of differences by the modifying factors. Of the various causes, circulatory mortality and respiratory hospitalization were more attributable to PM2.5 exposure. We found regional differences for both all-cause hospitalization and all-cause mortality, and seasonal differences for respiratory hospitalization (warm season) and circulatory hospitalization (cold season). Circulatory mortality risk was significant for seniors and females. All-cause hospitalizations appeared to gradually decrease over time, but annual all-cause mortality remained constant at 0.6 % of the population. Adverse health effects of PM2.5 exposures may depend on not only PM2.5 concentration, but also other factors (region, cause, season, age, sex). National estimates for the baseline (age ≥ 1 year, both sexes) risk cannot be interpreted without consideration of the differences by modifying factors. Study findings can be used by seniors, women, and those who have pre-existing health conditions to make informed decisions regarding their health risks from daily exposure to ambient PM2.5.

Different effects of air pollutant concentrations on influenza A and B in Sichuan, China

BACKGROUND

The detrimental effects of air pollution on the respiratory system are well documented. Previous research has established a correlation between air pollutant concentration and the frequency of outpatient visits for influenza-like illness. However, studies investigating the variations in infection among different influenza subtypes remain sparse. We aimed to determine the correlation between air pollutant levels and different influenza subtypes in Sichuan Province, China.

METHODS

A generalized additive model and distributed lag nonlinear model were employed to assess the association between air pollutants and influenza subtypes, utilizing daily influenza data obtained from 30 hospitals across 21 cities in Sichuan Province. The analysis considered the temporal effects and meteorological factors. The study spanned from January 1, 2017, to December 31, 2019. To provide a more precise evaluation of the actual impact of air pollution on different subtypes of influenza, we also performed subgroup analyses based on factors such as gender, age, and geography within the population.

RESULTS

During the investigation, 17,462 specimens from Sichuan Province tested positive for influenza. Among these, 12,607 and 4855 were diagnosed with Flu A and B, respectively. The related risk of influenza A infection significantly increased following exposure to PM2.5 on Lag2 days (RR=1.008, 95 % confidence interval [CI]: 1.000-1.016), SO2 and CO on Lag1 days (RR=1.121, 95 % CI: 1.032-1.219; RR=1.151, 95 % CI: 1.030-1.289), and NO2 on Lag0 day (RR=1.089, 95 % CI: 1.035-1.145). PM10 and SO2 levels on Lag0 day, PM2.5 levels on Lag1 day, and CO levels on Lag6 day, with a reduced risk of influenza B (RR=0.987, 95 % CI: 0.976-0.997; RR=0.817, 95 % CI: 0.676-0.987; RR=0.979, 95 % CI: 0.970-0.989; RR=0.814, 95 % CI: 0.561-0.921).

CONCLUSION

The findings from the overall population and subgroup analyses indicated that the impact of air pollutant concentrations on influenza A and B is inconsistent, with influenza A demonstrating greater susceptibility to these pollutants. Minimizing the levels of SO2, CO, NO2, and PM2.5 can significantly decrease the likelihood of contracting influenza A. Analyzing the influence of environmental contaminants on different influenza subtypes can provide insights into seasonal influenza trends and guide the development of preventive and control strategies.

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019)

BACKGROUND

Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China.

METHODS

An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data.

RESULTS

A total of 18,275 COPD hospitalizations were enrolled. For 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD.

CONCLUSION

Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions

The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

"I have to stay inside …": Experiences of air pollution for people with asthma

Asthma, characterized by airway inflammation, sensitization and constriction, and leading to symptoms including cough and dyspnoea, affects millions of people globally. Air pollution is a known asthma trigger, yet how it is experienced is understudied and how individuals with asthma interact with air quality information and manage exacerbation risks is unclear. This study aimed to explore how people living with asthma in Scotland, UK, experienced and managed their asthma in relation to air pollution. We explored these issues with 36 participants using semi-structured interviews. We found that self-protection measures were influenced by place and sense of control (with the home being a "safe space"), and that the perception of clean(er) air had a liberating effect on outdoor activities. We discuss how these insights could shape air quality-related health advice in future.

Relationship between fine particulate matter (PM2.5) concentration and risk of hospitalization due to chronic obstructive pulmonary disease: a systematic review and meta-analysis

BACKGROUND

Short-term exposure to PM2.5 has been associated with human health risks. However, evidence on the association between short-term exposure to PM2.5 and the risk of chronic obstructive pulmonary disease (COPD) remains limited and controversial. This study aimed to specifically assess the relationship between exposure to PM2.5 and the risk of hospitalization due to COPD.

METHODS

A systematic search was conducted in PubMed, Web of Science, and Google Scholar databases from January 1, 2010 to May 1, 2022. The odds ratio (OR) statistic was calculated as a common measure of effect size. Publication bias was also examined in all eligible studies on COPD hospitalization using funnel plots and Egger's test, as well as trim-and-fill method for missing studies on COPD hospitalization.

RESULTS

A total of 19 studies were included in this meta-analysis. Random-effects models were plotted to calculate the pooled effect size by measuring OR (χ2 = 349.95; df = 18; I2 = 94.86%; P = 0.007; Z = 2.68; P < 0.001). A 10-mg/m3 daily increase in PM2.5 concentration was associated with a 1.6% (95% CI: 0.4-2.9%) increase in COPD hospitalization. There was no publication bias regarding the association between COPD hospitalization and PM2.5 (bias = 1.508; 95% CI: -1.475, 4.491; t = 1.066; P = 0.301). The subgroups of age ≥ 65 years and Asian countries were associated with an increased risk of COPD hospitalization. Besides, higher risks were estimated in the subgroups of studies performed in the warm season, case-crossover studies, studies with three lag days, and studies without adjustments for humidity and temperature confounders, with very small heterogeneity.

CONCLUSION

Evidence suggests that short-term exposure to PM2.5 increases COPD hospitalization. Further studies are needed to understand the mechanism of the association between PM2.5 and COPD for reducing air pollution, which can be beneficial for COPD patients.

Asthma in developing countries in the Asia-Pacific Region (APR)

There is growing interest in the epidemiology of asthma in developing countries, especially in the Asia-Pacific Region (APR). A number of reviews have been published in this field, but a comprehensive synthesis of overall data has not been reported. Here, we summarized the burden, risk factors and challenges of asthma management in developing countries with a specific emphasis on the APR by consolidating evidence from both systematic and narrative reviews published up until February 2023. We found that although asthma prevalence in low and low-middle-income countries (LMICs) is known to be generally lower compared to high-income countries, the burden is substantially greater. Studies conducted in APR LMIC have reported a range of risk factors, including pre- and post-natal factors, environmental considerations, lifestyle measures, individual features and genetics. The low and inequitable distribution of quality preventive and curative health care, a lack of advanced diagnostic measures, non-availability and non-affordability of novel therapeutics, cultural beliefs and practices, and diverse disease phenotypes make it challenging to achieve optimal asthma control in the region. Hence, we call for the development of a region-specific blueprint for action to mitigate this challenging situation, to help reduce the burden of asthma in APR LMIC.

Personal exposure to fine particulate matter (PM2.5) and self-reported asthma-related health

PM2.5 (fine particulate matter ≤2.5 μm in diameter) is a key pollutant that can produce acute asthma exacerbations and longer-term deterioration of respiratory health. Individual exposure to PM2.5 is unique and varies across microenvironments. Low-cost sensors (LCS) can collect data at a spatiotemporal resolution previously unattainable, allowing the study of exposures across microenvironments. The aim of this study is to investigate the acute effects of personal exposure to PM2.5 on self-reported asthma-related health. Twenty-eight non-smoking adults with asthma living in Scotland collected PM2.5 personal exposure data using LCS. Measurements were made at a 2-min time resolution for a period of 7 days as participants conducted their typical daily routines. Concurrently, participants were asked to keep a detailed time-activity diary, logging their activities and microenvironments, along with hourly information on their respiratory health and medication use. Health outcomes were modelled as a function of hourly PM2.5 concentration (plus 1- and 2-h lag) using generalized mixed-effects models adjusted for temperature and relative humidity. Personal exposures to PM2.5 varied across microenvironments, with the largest average microenvironmental exposure observed in private residences (11.5 ± 48.6 μg/m3) and lowest in the work microenvironment (2.9 ± 11.3 μg/m3). The most frequently reported asthma symptoms, wheezing, chest tightness and cough, were reported on 3.4%, 1.6% and 1.6% of participant-hours, respectively. The odds of reporting asthma symptoms increased per interquartile range (IQR) in PM2.5 exposure (odds ratio (OR) 1.29, 95% CI 1.07-1.54) for same-hour exposure. Despite this, no association was observed between reliever inhaler use (non-routine, non-exercise related) and PM2.5 exposure (OR 1.02, 95% CI 0.71-1.48). Current air quality monitoring practices are inadequate to detect acute asthma symptom prevalence resulting from PM2.5 exposure; to detect these requires high-resolution air quality data and health information collected in situ. Personal exposure monitoring could have significant implications for asthma self-management and clinical practice.

Climate change and mortality rates of COPD and asthma: A global analysis from 2000 to 2018

BACKGROUND

Climate change plays a significant role in global health threats, particularly with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma, but the long-term global-scale impact of climate change on these diseases' mortality remains unclear.

OBJECTIVE

This study aims to investigate the impact of climate change on the age-standardized mortality rates (ASMR) of COPD and asthma at national levels.

METHODS

We used Global Burden of Disease (GBD) data of ASMR of COPD and asthma from 2000 to 2018. The climate change index was represented as the deviance percentage of temperature (DPT) and relative humidity (DPRH), calculated based on 19-year temperature and humidity averages. Annual temperature, RH, and fine particulate matter (PM2.5) levels in 185 countries/regions were obtained from ERA5 and the OECD's environmental statistics database. General linear mixed-effect regression models were used to examine the associations between climate change with the log of ASMR (LASMR) of COPD and asthma.

RESULTS

After adjusting for annual PM2.5, SDI level, smoking prevalence, and geographical regions, a 0.26% increase in DPT was associated with decreases of 0.016, 0.017, and 0.014 per 100,000 people in LASMR of COPD and 0.042, 0.046, and 0.040 per 100,000 people in LASMR of asthma for both genders, males, and females. A 2.68% increase in DPRH was associated with increases of 0.009 and 0.011 per 100,000 people in LASMR of COPD. We observed a negative association of DPT with LASMR for COPD in countries/regions with temperatures ranging from 3.8 to 29.9 °C and with LASMR for asthma ranging from -5.3-29.9 °C. However, we observed a positive association of DPRH with LASMR for both COPD and asthma in the RH range of 41.2-67.2%.

CONCLUSION

Climate change adaptation and mitigation could be crucial in reducing the associated COPD and asthma mortality rates, particularly in regions most vulnerable to temperature and humidity fluctuations.

A case study on occupational exposure assessment and characterization of particles in a printing shop in China

Printers can release numerous particles to contaminate indoor environments and pose health risks. Clarifying the exposure level and physicochemical properties of printer-emitted particles (PEPs) will help to evaluate the health risks of printer operator. In our study, the particles concentration in the printing shop was monitored in real time for a long time (12 h/day, total 6 days), and the PEPs were collected to characterize their physicochemical properties including shape, size and compositions. The result showed that the concentration of PEPs is closely related to the printing workload and the highest particle mass concentration of PM₁₀ and PM_2.5 was 212.73 μg m^-3 and 91.48 μg m^-3, respectively. The concentration of PM₁ in the printing shop was in the range of 11.88-80.59 μg m^-3 for mass value, and 174.83-1348.84 P cm^-3 for count value which changed with the printing volume. The particle sizes of PEPs were less than 900 nm, 47.99% of PEPs was less than 200 nm, and 14.21% of the particles were at the nanoscale. PEPs contained 68.92% organic carbon (OC), 5.31% elemental carbon (EC), 3.17% metal elements, and 22.60% other inorganic additives, which contained more OC and metal elements than toners. Total polycyclic aromatic hydrocarbons (PAHs) levels were 18.95 ng/mg in toner and 120.70 ng/mg in PEPs. The carcinogenic risk of PAHs in PEPs was 1.40 × 10^-7. These findings suggested future studies should pay more attention to the health effects of printing workers exposed to nanoparticles.

Environmental pollution in North-Eastern Italy and its influence on chronic obstructive pulmonary disease: time series modelling and analysis using visibility graphs

The impact on human health from environmental pollution is receiving increasing attention. In the case of respiratory diseases such as chronic obstructive pulmonary disease (COPD), the relationship is now well documented. However, few studies have been carried out in areas with low population density and low industrial production, such as the province of Belluno (North-Eastern Italy). The aim of the study was to analyze the effect of exposure to certain pollutants on the temporal dynamics of hospital admissions for COPD in the province of Belluno. Daily air pollution concentration, humidity, precipitations, and temperature were collected from the air monitoring stations in Belluno. Generalized additive mixed models (GAMM) and visibility graphs were used to determine the effects of the short-term exposure to environmental agents on hospital admissions associated to COPD. In the case of the city of Belluno, the GAMM showed that hospital admissions were associated with NO₂, PM₁₀, date, and temperature, while for the city of Feltre, GAMM produced no associated variables. Several visibility graph indices (average edge overlap and interlayer mutual information) showed a significant overlap between environmental agents and hospital admission for both cities. Our study has shown that visibility graphs can be useful in establishing associations between environmental agents and COPD hospitalization in sparsely populated areas.

Associations between air pollutant and pneumonia and asthma requiring hospitalization among children aged under 5 years in Ningbo, 2015-2017

Introduction

Exposure to ambient air pollutants is associated with an increased incidence of respiratory diseases such as pneumonia and asthma, especially in younger children. We investigated the relationship between rates of hospitalization of children aged under 5 years for pneumonia and asthma and the concentration of air pollutants in Ningbo between January 1, 2015 and August 29, 2017.

Methods

Data were obtained from the Ningbo Air Quality Data Real-time Publishing System and the big data platform of the Ningbo Health Information Center. A generalized additive model was established via logarithmic link function and utilized to evaluate the effect of pollutant concentration on lag dimension and perform sensitivity analysis.

Results

A total of 10,301 cases of pneumonia and 115 cases of asthma were identified over the course of this study. Results revealed that PM2.5, PM10, SO2 and NO2 were significantly associated with hospitalization for pneumonia and asthma in children under 5 years of age. For every 10-unit increase in lag03 air pollutant concentration, hospitalization for pneumonia and asthma due to PM2.5, PM10, SO2 and NO2 increased by 2.22% (95%CI: 0.64%, 3.82%), 1.94% (95%CI: 0.85%, 3.04%), 11.21% (95%CI: 4.70%, 18.10%) and 5.42% (95%CI: 3.07%, 7.82%), respectively.

Discussion

Adverse effects of air pollutants were found to be more severe in children aged 1 to 5 years and adverse effects due to PM2.5, PM10 and SO2 were found to be more severe in girls. Our findings underscore the need for implementation of effective public health measures to urgently improve air quality and reduce pediatric hospitalizations due to respiratory illness.

Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011-2020

The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet's ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM2.5, and PM10). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month's PM2.5 and temperature (lag1) had a significant association with influenza incidence, while the previous month's temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM2.5 lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM10 and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.