Short-Term Associations between Air Pollution Concentrations and Respiratory Health-Comparing Primary Health Care Visits, Hospital Admissions, and Emergency Department Visits in a Multi-Municipality Study

The association between air pollutions and emergency hospitalizations due to COPD and asthma across 16 Polish cities: population-based study

OBJECTIVES

In recent years numerous initiatives aimed at reducing air pollution have been undertaken in Poland. The general objective was to examine the correlation between air pollution measured by the level of particulate matter ≤10 μm in diameter (PM10) and emergency hospitalizations due to chronic obstructive pulmonary disease (COPD) and asthma in 16 Polish cities (capitals of the regions).

MATERIAL AND METHODS

The authors aimed to diagnose the situation across 16 cities over a 5‑year period (2014-2019). Data on the number of hospitalizations was retrieved from the national public insurance system, the National Health Fund. A total number of 22 600 emergency hospitalizations was analyzed (12 000 and 10 600 in 2014 and 2019, respectively). The data on air pollution was accessed via the public register of the Chief Inspectorate for Environmental Protection air quality database. The authors of this article have used the data on PM10 daily exposure in each of the 16 cities in 2014 and 2019. Statistical methods included: non-parametric tests, a 2-stage modelling approach for time-series data, and multivariate meta-analysis of the results.

RESULTS

The results indicated that there was a statistically significant decrease in PM10 concentration in 2019 in comparison to 2014 in all cities, mainly in the autumn and winter season. However, the correlation between the improvement in the air quality and a decrease in emergency hospitalizations due to asthma and COPD turned out to not be as strong as expected. The authors observed a strong correlation between PM10 concentrations and hospitalizations due to asthma and COPD, but only when air quality norms were significantly above acceptable levels.

CONCLUSIONS

Air pollution measured by PM10 concentration might be used as one of the predictors of the asthma and COPD emergency hospitalization risk, yet other factors like respiratory tract infection, health care organizational aspect, patient self-control, compliance and comorbidities should also be taken into consideration. Int J Occup Med Environ Health. 2024;37(1):110-27.

Association and interaction of O3 and NO2 with emergency room visits for respiratory diseases in Beijing, China: a time-series study

BACKGROUND

Ozone (O₃) and nitrogen dioxide (NO₂) are the two main gaseous pollutants in the atmosphere that act as oxidants. Their short-term effects and interaction on emergency room visits (ERVs) for respiratory diseases remain unclear.

METHODS

We conducted a time-series study based on 144,326 ERVs for respiratory diseases of Peking University Third Hospital from 2014 to 2019 in Beijing, China. Generalized additive models with quasi-Poisson regression were performed to analyze the association of O₃, NO₂ and their composite indicators (O_x and O_x^wt) with ERVs for respiratory diseases. An interaction model was further performed to evaluate the interaction between O₃ and NO₂.

RESULTS

Exposure to O₃, NO₂, O_x and O_x^wt was positively associated with ERVs for total respiratory diseases and acute upper respiratory infection (AURI). For instance, a 10 μg/m³ increase in O₃ and NO₂ were associated with 0.93% (95%CI: 0.05%, 1.81%) and 5.87% (95%CI: 3.92%, 7.85%) increase in AURI at lag0-5 days, respectively. Significant linear exposure-response relationships were observed in O_x and O_x^wt over the entire concentration range. In stratification analysis, stronger associations were observed in the group aged < 18 years for both O₃ and NO₂, in the warm season for O₃, but in the cold season for NO₂. In interaction analysis, the effect of O₃ on total respiratory emergency room visits and AURI visits was the strongest at high levels (> 75% quantile) of NO₂ in the < 18 years group.

CONCLUSIONS

Short-term exposure to O₃ and NO₂ was positively associated with ERVs for respiratory diseases, particularly in younger people (< 18 years). This study for the first time demonstrated the synergistic effect of O₃ and NO₂ on respiratory ERVs, and O_x and O_x^wt may be potential proxies.

Air Pollution in Kosovo: Short Term Effects on Hospital Visits of Children Due to Respiratory Health Diagnoses

The Republic of Kosovo is a small country in the Balkans. The capital city of Pristina hosts most of its population and is situated in a mountain basin with poor air exchange, especially during winter. Domestic heating, road transport, industry and coal-fired power plants contribute to high levels of air pollution. We performed a time-series analysis on effects of particulate air pollution (PM2.5) on respiratory health of children and adolescents, using hospital admission and ambulatory visit numbers from the pediatric university clinic. From 2018 until 2020, daily mean concentrations of PM2.5 ranged between 2.41 and 161.03 µg/m³. On average, there were 6.7 ambulatory visits per day with lower numbers on weekends and during the first COVID-19 wave in 2020. An increase in PM2.5 led to an immediate increase in visit numbers that lasted over several days. Averaged over a full week, this amounted to about a 1% increase per 10 µg/m³. There were, on average, 1.7 hospital admissions per day. Two and three days after a rise in air pollution, there was also a rise in admission numbers, followed by a decline during the consecutive days. This might indicate that the wards were overstressed because of high admission numbers and restricted additional admissions.

Research on prediction of daily admissions of respiratory diseases with comorbid diabetes in Beijing based on long short-term memory recurrent neural network

To compare the performance of generalized additive model (GAM) and long short-term memory recurrent neural network (LSTM-RNN) on the prediction of daily admissions of respiratory diseases with comorbid diabetes. Daily data on air pollutants, meteorological factors and hospital admissions for respiratory diseases from Jan 1st, 2014 to Dec 31st, 2019 in Beijing were collected. LSTM-RNN was used to predict the daily admissions of respiratory diseases with comorbid diabetes, and the results were compared with those of GAM. The evaluation indexes were calculated by five-fold cross validation. Compared with the GAM, the prediction errors of LSTM-RNN were significantly lower [root mean squared error (RMSE): 21.21±3.30 vs. 46.13±7.60, <0.01; mean absolute error (MAE): 14.64±1.99 vs. 36.08±6.20, <0.01], and the value was significantly higher (0.79±0.06 vs. 0.57±0.12, <0.01). In gender stratification, RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting female admission (all <0.05), but there were no significant difference in predicting male admission between two models (all >0.05). In seasonal stratification, RMSE and MAE of LSTM-RNN were lower than those of GAM in predicting warm season admission (all <0.05), but there was no significant difference in value (>0.05). There were no significant difference in RMSE, MAE and between the two models in predicting cold season admission (all >0.05). In the stratification of functional areas, the RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting core area admission (all <0.05). has lower prediction errors and better fitting than the GAM, which can provide scientific basis for precise allocation of medical resources in polluted weather in advance.

Short-Term Exposure to Ambient Air Pollution and Increased Emergency Room Visits for Skin Diseases in Beijing, China

Skin diseases have become a global concern. This study aims to evaluate the associations between ambient air pollution and emergency room visits for skin diseases under the background of improving air quality in China. Based on 45,094 cases from a general hospital and fixed-site monitoring environmental data from 2014–2019 in Beijing, China, this study used generalized additive models with quasi-Poisson regression to estimate the exposure–health associations at lag 0–1 to lag 0–7. PM_2.5 and NO₂ exposure were associated with increased emergency room visits for total skin diseases (ICD10: L00-L99). Positive associations of PM_2.5, PM₁₀, O₃ and NO₂ with dermatitis/eczema (ICD-10: L20–30), as well as SO₂ and NO₂ with urticaria (ICD-10: L50) visits were also found. For instance, a 10 μg/m³ increase in PM_2.5 was associated with increases of 0.7% (95%CI: 0.2%, 1.2%) in total skin diseases visits at lag 0–5 and 1.1% (95%CI: 0.6%, 1.7%) in dermatitis/eczema visits at lag 0–1, respectively. For PM_2.5, PM₁₀ and CO, stronger annual associations were typically observed in the high-pollution (2014) and low-pollution (2018/2019) years. For instance, a 10 μg/m³ increase in PM_2.5 at lag 0–5 was associated with increases of 1.8% (95%CI: 1.0%, 2.6%) and 2.3% (95%CI: 0.4%, 4.3%) in total skin disease visits in 2014 and 2018, respectively. Our study emphasizes the necessity of controlling the potential health hazard of air pollutants on skin, although significant achievements in air quality control have been made in China.

Spatial Analysis of Ambient Air Pollution and Cardiovascular Disease (CVD) Hospitalization Across Sweden

The associations of multiple pollutants and cardiovascular disease (CVD) morbidity, and the spatial variations of these associations have not been nationally studied in Sweden. The main aim of this study was, thus, to spatially analyze the associations between ambient air pollution (black carbon, carbon monoxide, particulate matter (both <10 µm and <2.5 µm in diameter) and Sulfur oxides considered) and CVD admissions while controlling for neighborhood deprivation across Sweden from 2005 to 2010. Annual emission estimates across Sweden along with admission records for coronary heart disease, ischemic stroke, atherosclerotic and aortic disease were obtained and aggregated at Small Areas for Market Statistics level. Global associations were analyzed using global Poisson regression and spatially autoregressive Poisson regression models. Spatial non-stationarity of the associations was analyzed using Geographically Weighted Poisson Regression. Generally, weak but significant associations were observed between most of the air pollutants and CVD admissions. These associations were non-homogeneous, with more variability in the southern parts of Sweden. Our study demonstrates significant spatially varying associations between ambient air pollution and CVD admissions across Sweden and provides an empirical basis for developing healthcare policies and intervention strategies with more emphasis on local impacts of ambient air pollution on CVD outcomes in Sweden.

Spatial Effects of Environmental Pollution on Healthcare Services: Evidence from China

With the rapid development of urbanization and industrialization in China, environmental issues have become an urgent problem, especially issues related to air, water, and solid-waste pollution. These pollutants pose threats to the health of the population and to that of communities and have a vicious influence on the healthcare system. Additionally, pollution also exhibits spill-over effects, which means that pollution in the local region could affect the healthcare services in a neighboring region. Therefore, it is necessary to explore the relationship between pollution and healthcare. A spatial autocorrelation analysis was conducted and spatial panel econometric models were constructed to explore the characteristics of pollution and healthcare services in China and the relationship between them using data on all 31 provinces over 12 consecutive years (2006-2017). The results showed that the utilization of healthcare services and environmental pollution were not randomly distributed; unsurprisingly, air pollution and solid-waste pollution were mainly found in parts of northern China, while water pollution was highest in southern and coastal China. In addition, environmental pollution exhibited spill-over effects on healthcare services. For example, a 1% increase in solid waste in one specific geographical unit was estimated to increase the inpatient visits per capita in adjacent counties by 0.559%. Specifically, pollution showed different degrees of influence on healthcare services, which means that the impact of environmental pollution on the number of outpatient visits is greater than on the number of inpatient visits. Our results provide the government with evidence for effectively formulating and promulgating policies, especially policies aimed at tackling spill-over effects among different regions.

Pollutant-sex specific differences in respiratory hospitalization and mortality risk attributable to short-term exposure to ambient air pollution

BACKGROUND

Many studies have reported associations of individual pollutants with respiratory hospitalization and mortality based on different populations, which makes it difficult to directly compare adverse health effects among multiple air pollutants.

OBJECTIVES

The study goal is to compare acute respiratory-related hospitalization and mortality associated with short-term exposure to three ambient air pollutants and analyze differences in health risks by season, age and sex.

METHODS

Hourly measurements of air pollutants (ozone, NO₂, PM_2.5) and temperature were collected from ground-monitors for 24 cities along with daily hospitalization (1996-2012) and mortality (1984-2012) data. National associations between air pollutant and health outcome were estimated for season (warm, cold vs. year-round), age (base ≥ 1, seniors > 65), and sex (females ≥ 1 and males ≥ 1) using Bayesian hierarchical models.

RESULTS

Overall, the three air pollutants were significantly associated with acute respiratory health outcomes at different lag-days. For respiratory hospitalization, the increased risks in percent changes with 95% posterior intervals for a 10-unit increase in each pollutant were: ozone (lag1, 0.7% (0.4, 0.9)), NO₂ (lag0, 0.7% (0.1, 1.4)), and PM_2.5 (lag1, 1.3% (0.7, 1.9)). For respiratory mortality: ozone (lag2, 1.2% (0.4, 1.9)), NO₂ (lag1, 2.1% (0.6, 3.5)), and PM_2.5 (lag1, 0.6% (-1.0, 2.2)). While some differences in risk were observed by season and age group, sex-specific differences were more pronounced. Compared with males, females had a higher respiratory mortality risk (1.8% (0.6, 2.9) vs 0.5% (-0.3, 1.3)) from ozone, a higher respiratory hospitalization risk (0.9% (0.0, 1.8) vs 0.6% (-0.3, 1.4)) but lower mortality risk (1.4% (-1.0, 3.7) vs 2.2% (0.4, 4.0)) from NO₂, and a lower hospitalization risk (0.7% (-0.2, 1.7) vs 1.8% (1.0, 2.6)) from PM_2.5.

CONCLUSION

This study reports significant health effects of short-term exposure to three ambient air pollutants on respiratory hospitalization (ozone≈NO₂ < PM_2.5 per-10 unit; ozone>NO₂ ≈ PM_2.5 per-IQR) and mortality (ozone≈NO₂ > PM_2.5) in Canada. Pollutant-sex-specific differences were found, but inconclusive due to limited biological and physiological explanations. Further studies are warranted to understand the pollutant-sex specific differences.

The short-term effects of air pollution on respiratory disease hospitalizations in 5 cities in Poland: comparison of time-series and case-crossover analyses

Very few publications have compared different study designs investigating the short-term effects of air pollutants on healthcare visits and hospitalizations for respiratory tract diseases. This study describes, using two different study designs (a case-crossover design and a time-series analysis), the association of air pollutants and respiratory disease hospitalizations. The study has been conducted on 5 cities in Poland on a timeline of almost 4 years. DLNM and regression models were both used for the assessment of the short-term effects of air pollution peaks on respiratory hospitalizations. Both case-crossover and time-series studies equally revealed a positive association between air pollution peaks and hospitalization occurrences. Results were provided in the form of percentage increase of a respiratory visit/hospitalization, for each 10-μg/m3 increment in single pollutant level for both study designs. The most significant estimated % increases of hospitalizations linked to increase of 10 μg/m3 of pollutant have been recorded in general with particulate matter, with highest values for 24 h PM2.5 in Warsaw (6.4%, case-crossover; 4.5%, time series, respectively) and in Białystok (5.6%, case-crossover; 4.5%, time series, respectively). The case-crossover analysis results have shown a larger CI in comparison to the results of the time-series analysis, while the lag days were easier to identify with the case-crossover design. The trends and the overlap of the results occurring from both methods are good and show applicability of both study designs to air pollution effects on short-term hospitalizations.

Influence of Ultrafine Particles Exposure on Asthma Exacerbation in Children: A Meta-Analysis

BACKGROUND

Air pollution is a major cause of asthma exacerbation. Most studies have shown that exposure to coarse and fine particulate matter is associated with asthma exacerbation. Ultrafine particles (UFPs, aerodynamic diameter ≤ 0.1 µm) are the smallest airborne particles, which are capable of penetrating deep into the lungs. Toxicological studies have suggested that exposure to UFPs may have serious effects on respiratory health. However, epidemiological evidence on the effects of UFPs exposure on asthma exacerbation in children remains unclear.

OBJECTIVE

We conducted a meta-analysis to quantitatively assess the effects of exposure to UFPs on childhood asthma exacerbation.

METHODS

We searched four databases for epidemiological studies published until March 20, 2018. Pooled Odds Ratios (OR) and 95% confidence intervals (95% CIs) per 10000 particles/cm3 were estimated using fixed-effect models. Subgroup analyses, sensitivity analyses, and Begg's and Egger's regression were also performed.

RESULTS

Eight moderate-high quality studies with 51542 events in total satisfied the inclusion criteria. Exposure to UFPs showed a positive association with childhood asthma exacerbation [OR (95% CI): 1.070 (1.037, 1.104)], increased asthma-associated emergency department visits [OR (95% CI): 1.111 (1.055, 1.170)], and asthma-associated hospital admissions [OR (95% CI): 1.045 (1.004, 1.088)] and had a stronger association with childhood asthma exacerbation at long lags [OR (95% CI):1.060 (1.039, 1.082)]. A low heterogeneity and no publication bias were detected.

CONCLUSION

Exposure to UFPs may increase the risk of asthma exacerbation and may be strongly associated with childhood asthma exacerbation at long lags.

Relationship between atmospheric pollutants and risk of death caused by cardiovascular and respiratory diseases and malignant tumors in Shenyang, China, from 2013 to 2016: an ecological research

Background:

Air pollutants and their pathogenic effects differ among regions and seasons. We aimed to explore the relationship between fine particulate matter (PM_2.5), sulfur dioxide (SO₂), and ozone-8 hours (O₃-8h) concentrations in heating and non-heating seasons and the associated death risk due to cardiovascular diseases (CDs), respiratory diseases (RDs), and malignant tumors.

Methods:

Data were collected in Shenyang, China, from April 2013 to March 2016. We analyzed the correlation or lagged effect of atmospheric pollutant concentration, meteorological conditions, and death risk due to disorders of the circulatory system, respiratory system, and malignant tumor in heating and non-heating seasons. We also used multivariate models to analyze the association of air pollutants during holidays with the death risk due to the evaluated diseases while considering the presence or absence of meteorological factors.

Results:

An increase in the daily average SO₂ concentration by 10 μg/m³ increased the death risk by CDs, which reached a maximum of 2.0% (95% confidence interval [CI]: 1.3%–2.7%) on lagging day 4 during the non-heating season and 0.2% (95% CI: 0.1%–0.4%) on lagging day 3 during the heating season. The risk of death caused by RDs peaked on lagging day 1 by 0.8% (95% CI: 0.4%–1.2%) during the heating season. An increase in O₃-8h concentration by 10 μg/m³ increased the risk of RD-related death on lagging day 2 by 1.0% (95% CI: 0.4%–1.7%) during the non-heating season, which was significantly higher than the 0.1% (95% CI: 0–0.9%) increase during the heating season. Further, an increase in the daily average PM_2.5 concentration by 10 μg/m³ increased the risk of death caused by RDs by 0.3% and 0.8% during heating and non-heating seasons, respectively, which peaked on lagging day 0. However, air pollution was not significantly associated with the risk of death caused by malignant tumors.

Conclusion:

Short-term exposure to PM_2.5, SO₂, and O₃ during the non-heating season resulted in higher risks of CD-related death, followed by RD-related death.

Impact of air pollution on hospital admissions with a focus on respiratory diseases: a time-series multi-city analysis

Together with the growing availability of data from electronic records from healthcare providers and healthcare systems, an assessment of associations between different environmental parameters (e.g., pollution levels and meteorological data) and hospitalizations, morbidity, and mortality has become possible. This study aimed to assess the association of air pollution and hospitalizations using a large database comprising almost all hospitalizations in Poland. This time-series analysis has been conducted in five cities in Poland (Warsaw, Białystok, Bielsko-Biała, Kraków, Gdańsk) over a period of almost 4 years (2014-2017, 1255 days), covering more than 20 million of hospitalizations. The hospitalizations have been extracted from the National Health Fund registries as daily summaries. Correlation analysis and distributed lag nonlinear models have been used to investigate for statistically relevant associations of air pollutants on hospitalizations, trying by various methods to minimize potential bias from atmospheric parameters, days of the week, bank holidays, etc. A statistically significant increase of respiratory disease hospitalizations has been detected after peaks of particulate matter concentrations (particularly PM_2.5, between 0.9 and 4.5% increase per 10 units of pollutant increase, and PM₁₀, between 0.9 and 3.5% per 10 units of pollutant increase), with a typical time lag between the pollutant peak and the event of 2 to 6 days. For other pollution parameters and other types of hospitalizations (e.g., cardiovascular events, eye and skin diseases, etc.), a weaker and ununiform correlations were recorded. Ambient air pollution exposure increases are associated with a short-term increase of hospitalizations due to respiratory tract diseases. The most prominent effect was recorded with the correlation of PM_2.5 and PM₁₀. There is only weak evidence indicating that such short-term associations exist between peaks of air pollution concentrations and increased hospitalizations for other (e.g., cardiovascular) diseases. The obtained information could be used to better predict hospitalization patterns and costs for the healthcare system and perhaps trigger additional vigilance on particulate matter pollution in the cities.

Outdoor Air Pollution and Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

BACKGROUND

During the past 20 years, the prevalence of gestational diabetes mellitus (GDM) has increased by ∼10%-100% in several race/ethnicity groups. There is an association between ambient air pollution (AAP) and GDM. This study aimed to summarize the evidence about the association between AAP and GDM.

METHODS

PubMed, Embase, Scopus, Web of Science and Cochrane Library were searched from inception till Oct 2017. Studies about the association between ambient air pollutants levels and GDM were included. Pooled effect estimates and their 95% confidence interval (CI) were calculated using R.

RESULTS

Eight studies met the inclusion criteria. The odds of developing GDM upon exposure to CO (per 1 ppm), NO (per 1 ppb), NO2 (per 10 μg/m3), NOx (per 1 ppb), O3 (per 10 ppb), SO2 (per 10 ppb), PM10 (per 10 μg/m3) and PM2.5 (per 10 μg/m3) were 1.47 (95% CI 0.88-2.06), 1.04 (95% CI 1.03-1.06), 1 (95% CI 0.93-1.08), 1.02 (95% CI 1-1.04), 1.05 (95% CI 0.94-1.16), 1.39 (95% CI 1.04-1.73), 0.97 (95% CI 0.94-0.99) and 1.12 (95% CI 0.93-1.31), respectively.

CONCLUSION

The current literature showed evidence for an association between AAP and GDM. However, further well-designed studies are needed.