Health Impact Of Air Pollution Research Articles

Novel R package to quantify and monetize burden of disease attributable to air pollution and noise

Abstract Background Ambient air pollution and noise substantially impact public health and the economy. Different methods to quantify these impacts are described in the literature. Objectives Within the European project BEST-COST (Burden of disease-based methods for estimating the socio-economic cost of environmental stressors), we aim to develop an open-source R package to quantify and monetise the disease burden attributable to air pollution and noise, including the impact of social inequalities. Methods The developed code will allow for different calculation pathways including: single baseline health data vs. age-specific estimates from life tables; relative and absolute risk; scenario comparison based on the population attributable fraction vs. population impact fraction; single-pollutant vs. correlated exposures; and outdoor vs. indoor air pollution. Moreover, the package can digest a variety of input data formats for the exposure-response function (e.g. relative risk with fixed shape vs. user-defined function) and exposure data (e.g. population-weighted mean vs. categorical distribution, spatial data). Eligible impact metrics will include morbidity incidence and prevalence, number of deaths, years of life lost, and years lived with disability. Finally, the R package will enable quantifying social inequities (using a novel multiple deprivation index) and monetising the attributable disease burden (using a state-of-the-art approach). Results During development, the R package will be tested in BEST-COST case studies in 5 European countries (BE, EE, FR, NO, PT), compared with existing tools, and discussed with key users in a workshop. The final R package will be available on GitHub in 2026. Conclusions This tool will allow the quantification and monetisation of the health impact of air pollution and noise. The R package will be a flexible programming resource that can be used as a standalone or combined with existing tools to build a more solid basis for evidence-based policy making. Key messages • This open-source tool will allow the quantification and monetisation of the health impact of air pollution and noise, including the impact of social inequalities. • The R package will be a flexible programming resource that can be used as a standalone or combined with existing tools to build a more solid basis for evidence-based policy making.

Benefits of hypothetical air pollution reduction interventions on NCDs in Belgium

Abstract Background The adverse health impact of air pollution on non-communicable diseases (NCDs) is well documented, yet methodological tools for assessing the potential health benefits of interventions are lacking. This study uses a parametric g-computation approach to evaluate the impact of hypothetical interventions targeting long-term air pollution exposure on reducing NCDs prevalence in Belgium, using data from three national Health Interview Surveys (BHIS 2008-2013-2018). Methods BHIS data (n = 27,536) were linked to environmental data at participants’ residential addresses. A g-computation approach was used to calculate the potential impact fractions of air quality interventions on several NCDs. Regression models were adjusted for socio-economic, environmental and lifestyle factors. The scenarios involved reducing individual long-term air pollution exposure to WHO air quality guideline levels, followed by investigating dose-response functions through various percentage reductions in air pollution exposure. Results Significant associations were found between air pollution and asthma, stroke, and multimorbidity. Adhering to WHO air quality guidelines would substantially reduce stroke risk in Belgium by 0.87% (95% CI:0.38; 1.35) for PM2.5 and 0.32% (95% CI:-0.05; 0.70) for NO2, preventing 63% and 22% of cases, respectively. For asthma, risk reduction was 1.43% (95% CI:-0.53; 3.4) for PM2.5 and 0.83% (95% CI: 0.01; 1.63) for NO2, preventing 27% and 16% of cases, respectively. For multimorbidity, risk reduction was 3.20 % (95% CI: -1.75; 8.16) for PM2.5 and 0.43% (95% CI:-2.03; 2.90) for NO2, preventing 7% and 0.4% of cases, respectively. Results revealed a clear dose-response association between air pollution reduction and the prevalence of stroke, asthma, and multimorbidity in Belgium. Conclusions This study demonstrates that air pollution reduction interventions could effectively decrease the prevalence of asthma, stroke, and multimorbidity in Belgium. Key messages • Air pollution reduction interventions could effectively decrease the prevalence of asthma, stroke, and multimorbidity in Belgium. • The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data.

Calibration of particle sensor with neural network algorithm

AbstractBased on air quality index data for the period 2018–2022, Hungary ranks as the 80th most polluted country in the world. Given the air pollution data measured in Hungary and the health impact of air pollution, it is of utmost importance to measure air quality in Hungary focusing on PM10 and PM2.5 pollutants. One possible solution for high-density measurement is to utilize low-cost sensors at the population level. The calibration procedure has to be carried out in a way that does not incur extra costs and maintenance at the physical level. A potential solution is the development of an algorithm to perform the calibration with remote access. This publication presents a fragment of this development, where we attempted to implement the procedure using a neural network and performed a comparative analysis with official data.

Estimating potentially preventable ambient PM2.5-attributable adult deaths by improving air quality in Nepal

Air pollution is an important global environmental health risk factor, with many Asian countries experiencing alarming levels in recent decades. Nepal, a South Asian country, has been facing severe degradation in air quality in recent years, where data are scarce on the health impact of air pollution, especially at sub-national levels. In this study, we investigated ambient fine particulate matter (PM2.5)-attributable adult (≥25 years) premature mortality in Nepal, analyzed its long-term trend, and estimated potentially preventable adult mortality under different improved air quality scenarios defined using the World Health Organization's (WHO) interim targets (IT) and the air quality goal (AQG). Leveraging an open-source high-resolution PM2.5 dataset and an age-specific population dataset, we employed the Global Exposure Mortality Model to estimate mean and 95% confidence intervals of PM2.5-attributable adult mortality using Monte Carlo simulations. We estimated the country-level NCD + LRI (non-communicable diseases and lower respiratory infections) adult deaths attributable to PM2.5 exposure as 48881 (95% CI: 37175−61470), and the PM2.5-attributable NCD + LRI adult mortality rate as 267 (95% CI: 203−335) per 100000 in 2019. The adult mortality burden consistently increased during 2000–2019. Moreover, improving air quality to the WHO ITs and AQG could prevent an estimated 9690 (95% CI: 7698−11812) to 39419 (95% CI: 30311−49277) premature adult deaths across the country in 2019. Our findings suggest that the adult mortality burden due to air pollution in Nepal is substantial, which offers an opportunity to prevent a considerable number of premature adult deaths by mitigating air pollution in the country.

Mental Health Impact of Air Pollution in the Southeast Asian Subcontinent

Mental Health Impact of Air Pollution in the Southeast Asian Subcontinent

Variability and health impact of air pollutants and bioaerosols in multi-functional indoor environments with mechanical ventilation system

The condition of indoor environments significantly impacts human daily life and health, where exposure to harmful substances affects the resilience of occupants. To understand the dynamics of indoor air quality and its implications for occupant health thus this study evaluated air pollutant concentration (TVOC, NO2, O3, CO, CO2, PM10, PM2.5, and PM1) and bioaerosol in mechanically ventilated offices, laboratories, corridors, a library and a mechanical workshop. Simultaneous measurements of all air pollutants were performed for 24 h, including non-working hours, while bioaerosol was sampled for fungal identification and quantified via the colony counting method. High concentrations of PM10, PM2.5, PM1, O3 and bioaerosol were found in the mechanical workshop, where these pollutants were strongly related to humidity (p < 0.05) and indoor source contributions. Other air pollutants such as TVOC had the highest concentrations in the office areas during working hours with an average concentration of 361 ± 14.8 μg m−3, while for CO, the highest concentration was observed in the laboratories for both working hours (442 ± 26.0 ppb) and 24 h average concentration (438 ± 22.1 ppb). Dominant species identified in bioaerosol were Aspergillus sp., Geotrichum sp., Fusarium sp., and Penicillium sp., where the exposure to bioaerosol was found to be of low risk to all workers as the hazard quotient (HQ) was <1 for all multi-functional indoor environments. The results from this study suggest that indoor air pollutants and bioaerosol concentrations have a variety of characteristics and source contributions, especially from human activities and indoor sources.

Greenness, air pollution, and temperature exposure effects in predicting premature mortality and morbidity: A small-area study using spatial random forest model

BackgroundAlthough studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework. MethodsYears of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008–2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation. ResultsSpatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions. ConclusionAir pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.

Rooting the Health Impact of Air Pollution: A Review of Human and Constitutional Rights

Rooting the Health Impact of Air Pollution: A Review of Human and Constitutional Rights

Biomarkers in Air Pollution Exposure Health Risk Assessment

Air pollution, a global environmental issue, is comprised of complex mixtures of gases and particulate matter which pose substantial health risks including respiratory diseases and cancer. Biomarkers are measurable indicators of biological processes and are essential for understanding the health impact of air pollution. This study reviews key biomarkers associated with air pollution exposure and their implications for health risk assessment. Inflammatory biomarkers, oxidative stress markers, lung function parameters, and biomarkers of DNA damage emerged as crucial indicators of air pollution-induced health effects. The assessment of air pollution-related biomarkers may be performed using biomonitoring, exposure assessment, oxidative stress assays, genetic and epigenetic analysis, and omics technologies. Challenges and limitations in utilizing biomarkers for assessing health risks linked to air pollution exposure include response variability, specificity, multiple exposure sources, and ethical issues that hinder biomarker research and analysis. Future progress in biomarker detection technologies could involve the integration of multiomics methods, personalized exposure assessment techniques, wearable biosensors, detection of emerging pollutants, and a combination of biomarkers and artificial intelligence tools. Implementing biomarkers in regulatory decisions and public health policies can help mitigate air pollution’s adverse health effects and improve air quality standards.

Modeling of carbonaceous aerosols for air pollution health impact studies in Europe

AbstractAir pollution from fine particulate matter (PM2.5) has been associated with various health implications that can lead to increased morbidity and excess mortality. Epidemiological and toxicological studies have shown that carbonaceous particles (black carbon and organic aerosols) may be more hazardous to human health than inorganic ones. Health impact studies and emission reduction policies are based on total PM2.5 concentration without differentiating the more harmful components. In such assessments, PM2.5 and their sub-component concentrations are usually modeled with air quality models. Organic aerosols have been shown to be consistently underestimated, which may affect excess mortality estimates. Here, we use the WRF-Chem model to simulate PM2.5 (including carbonaceous particles) over the wider European domain and assess some of the main factors that contribute to uncertainty. In particular, we explore the impact of anthropogenic emissions and meteorological modeling on carbonaceous aerosol concentrations. We further assess their effects on excess mortality estimates by using the Global Exposure Mortality Model (GEMM). We find that meteorological grid nudging is essential for accurately representing both PM2.5 and carbonaceous aerosols and that, for this application, results improve more significantly compared to spectral nudging. Our results indicate that the explicit account of organic precursors (semi-volatile and intermediate-volatile organic carbons—SVOCs/IVOCs) in emission inventories would improve the accuracy of organic aerosols modeling. We conclude that uncertainties related to PM2.5 modeling in Europe lead to a ∼15% deviation in excess mortality, which is comparable to the risk model uncertainty. This estimate is relevant when all PM2.5 sub-components are assumed to be equally toxic but can be higher by considering their specific toxicity.

Assessment of health impacts and costs attributable to air pollution in urban areas using two different approaches. A case study in the Western Balkans

In this study, two different air quality impact assessment methodologies were adopted and combined with a sensitivity analysis to estimate the unit costs. Air pollution health impact (mortality) assessment was carried out using one methodology based on log-linear concentration response functions (CRF) and another relying on the integrated exposure response curve (IER) from the Global Burden of Disease. Morbidity impacts were estimated with the CRF approach only. To assess the inequalities between low and high income countries, an area of low-medium income countries with a critical air pollution situation, was selected. The health impact and related external costs attributable to air pollution in 2019 were assessed in 30 urban areas of the Western Balkans region, one of Europe’s air pollution hot spots. The evaluation was based on PM2.5, O3 and NO2 concentrations in background sites from official monitoring networks. In 2019, the cost of mortality attributable to PM2.5 in 26 urban areas was 7.8 and 9.0 billion Euro according to IER and CRF methodologies, respectively. The cost of O3 associated with all-cause mortality estimated with the CRF methodology in 17 urban areas was 1.0 billion Euro while the one attributable to NO2 pollution in 28 urban areas was 1.5 billion Euro. The study results suggest that the economic burden of air pollution in the Western Balkans is higher in terms of GDP than the one observed in EU27 in the same time window. The study concludes that CRF and IER methodologies are coherent, because the discrepancy in the results are explained by the differences in the assessed health outcomes. The two approaches are complementary because the combination of them makes it possible to obtain a wider range of outcomes. In addition, despite the different causes of death considered, the comparison between them is useful for cross-validation.

PM2.5 Air Quality Monitoring during COVID-19 Restrictions in Portugal: Key Findings

Abstract Background Particulate matter with or less 2.5 diameters (PM2.5) has deleterious health effects on humans. In 2020, exposure to levels of PM2.5 above World Health Organization Air Quality Guidelines (WHO AQG) caused 238,000 and 2,600 premature deaths in the European Union and Portugal, respectively. During the lockdowns and restrictions periods due to the COVID-19 pandemic, air quality was improved. The aim of this study was to assess the variation of PM2.5 concentrations in Portugal during the years 2020 and 2021, considering COVID-19 restrictions. Methods The daily average (24-hour) concentrations of PM2.5 were calculated based on the hourly values registered at the monitoring stations (Online Database on Air Quality of the Portuguese Environment Agency). Friedman tests were used for paired samples to assess differences between levels of PM2.5 in the months of total lockdown, partial restriction due to the COVID-19 pandemic and months without restrictions, considering a level of significance of 5%. Results The levels of PM2.5 had heterogeneous variation over the months of the two years. The higher levels of PM2.5 in 2020 and 2021 were 21 and 34 µg/m3 in March and February, respectively. Although 2020 did not exceed the EU Air Quality Directive 2008/50 (25 µg/m3), the levels of PM2.5 exceeded the current WHO Guideline (5 µg/m3) during the whole year. Levels of PM2.5 were statistically significant different between the months of lockdown, partial restrictions and without restrictions in the both years (p &amp;lt; 0,001). Conclusions Despite the evidence showing that the lockdown and restrictions due to COVID-19 minimized emissions from anthropogenic activities mainly related with mobility, Portugal still exceeded the WHO AQG highlighting the need for further measures to improve air quality accordingly with the international standards. Acknowledgments This work is funded by FCT/MCTES through national funds to PMCardImpact (EXPL/SAU-PUB/0944/2021). Key messages • Additional environmental policies are required to improve air quality in Portugal. • Air monitoring is the first step to estimate the health impact of air pollution.

Air pollution costs in Western Balkans’ cities

Abstract Poor air quality is responsible for increased risk of mortality which global cost in in 2019 was associated with 4.1 million premature deaths globally. The Western Balkans were selected for this study because the levels of particulate matter and ozone are frequently above the EU Air Quality Directive guidelines. Air pollution health impact (mortality and morbidity) assessment was carried out using the attributable fraction approach based on different relative risk attribution methodologies: concentration response functions (CRF) and integrated exposure responses (IER). Air pollution costs were estimated using the value of statistical life (VSL) and the value of life year (VOLY) attributable to air pollution obtained with the benefit transfer method (BT) from a global database of non-market welfare-based unit costs. The health impact and related external costs attributable to air pollution in 2019 were assessed in 30 urban areas of the Western Balkans region, one of Europe's air pollution hot spots. The evaluation was based on PM2.5, O3 and NO2 concentrations in 2019. The average cost of mortality attributable to PM2.5 in 26 urban areas was above 200 million Euro per city while the ones of O3 and NO2 were 4 times lower than PM2.5. The study results suggest that the economic burden of air pollution per capita and compared to the GDP in the Western Balkans is higher than the one observed in EU27 in the same time window.

Impacts of dust storms on indoor and outdoor bioaerosol concentration in the Sistan region of Iran

Monitoring indoor and outdoor bioaerosol concentrations is essential for environmental management and evaluation of the health impact of air pollution. This study assessed indoor and outdoor microbial air quality for two cities of the Sistan region in Iran, Zabol and Zahak, in summer (July and August) and autumn (October and November) of 2022. Indoor air quality was compared between two rooms with varying conditions associated with windows (living room: windows opened to the north and to the prevailing wind; bedroom: opened to the south and opposite to the prevailing wind). Bacterial concentrations were monitored using the settle plate method inside and outside household environments at 6:30 a.m., 10:30 a.m., 4:30 p.m., 7:30 p.m., and 12:30 a.m. Zahak exhibited higher PM10 and bacterial concentrations compared to Zabol. Bacterial concentrations in the outdoor environment were significantly higher than those in indoor air and also higher in summer than autumn in both cities. There was no significant difference in indoor air samples between the two rooms (p> 0.05) in Zabol, indicating that the bacteria pollution was similar in the two rooms. Diurnal and day-to-day patterns of airborne bacteria were similar in indoor and outdoor air, consistent with PM10 variations, pointing to the association between outdoor and indoor air quality. PM10 and bacterial concentrations peaked at 10:30 a.m. and were lowest at 4:30 p.m. Results of this study have implications for other dust-prone cities of the world and offer a valuable dataset for bacterial concentrations to compare with other regions of the world.

Impacts of Air Pollution on Health and Cost of Illness in Jakarta, Indonesia

(1) Background: This study aimed to quantify the health and economic impacts of air pollution in Jakarta Province, the capital of Indonesia. (2) Methods: We quantified the health and economic burden of fine particulate matter (PM2.5) and ground-level Ozone (O3), which exceeds the local and global ambient air quality standards. We selected health outcomes which include adverse health outcomes in children, all-cause mortality, and daily hospitalizations. We used comparative risk assessment methods to estimate health burdens attributable to PM2.5 and O3, linking the local population and selected health outcomes data with relative risks from the literature. The economic burdens were calculated using cost-of-illness and the value of the statistical life-year approach. (3) Results: Our results suggest over 7000 adverse health outcomes in children, over 10,000 deaths, and over 5000 hospitalizations that can be attributed to air pollution each year in Jakarta. The annual total cost of the health impact of air pollution reached approximately USD 2943.42 million. (4) Conclusions: By using local data to quantify and assess the health and economic impacts of air pollution in Jakarta, our study provides timely evidence needed to prioritize clean air actions to be taken to promote the public's health.

Air pollution and pregnancy outcomes in Dhaka, Bangladesh

• Air quality in Dhaka city remains in ‘unhealthy’ to ‘extremely unhealthy’ state for two third of the year • There is an alarming increase in the number of ‘unhealthy’ to ‘extremely unhealthy’ air days • Low birth weight (LBW) increases from 20.6% to 36.0% for the lowest and highest category air pollution exposure. • Percent preterm births (PTB) shows a linear increase from 9% to 15.2% between lowest and highest category of air pollution exposure • Female fetuses are at higher risk of LBW and male fetuses are more prone to PTB • For every 10,000 Air Quality Index (AQI) value increase in cumulative exposure, the rate of increase in LBW and PTB is 4% and 2% respectively • Second trimester could be potentially the most vulnerable period of pregnancy due to ambient air pollution Air pollution, one of the biggest environmental risks to health, is a severe problem in Bangladesh. The Lancet ‘Commission on Pollution and Health’ emphasized on the importance of research on health effects of ambient air pollution. This study explored the negative health impact of air pollution on pregnancy outcomes - preterm births (PTB) and low birth weight (LBW). The study assessed air quality in terms Air Quality Index (AQI) and, quantified the association with LBW and PTB. Pregnancy outcome data was collected from the Maternal and Child Health Training Institute in Dhaka, and the AQI data from the Clean Air and Sustainable Environment project of Department of Environment. A total 3,206 birth outcome records were assessed within the period from 2014 to 2017. Air pollution situation is quite alarming in Dhaka city, at ‘Unhealthy’ to ‘Extremely Unhealthy’ levels for two thirds of the year. An increase in the prevalence of LBW and PTB was found with increasing cumulative air pollution exposure. LBW increased from 20.6% to 36.0% and PTB increased from 9% to 15.2% respectively between the lowest and highest category AQI value exposure. For every 10,000 AQI value increase in cumulative exposure, LBW and PTB increased by 4% and 2%, respectively. There is significant gender differentiated impact on LBW and PTB due to air pollution where female fetuses are at higher risk of LBW and males are more prone to PTB. Air pollution exposure during the second trimester increased LBW and PTB more compared to first and third trimesters; suggesting it potentially the most vulnerable period of pregnancy. Proper interventions to reduce air pollution levels need to be urgently implemented.

A call for action: Air Pollution, a serious health and economic hazard suffocating Africa

Air pollution research has been conducted in Europe and North America as well as in Asia and South America for decades. Until recently, global inventories of pollutants from North America Europe and Asia have been used for air quality and climate change modelling in Africa (Bond et al., 2004, Streets et al., 2004, Bond et al., 2007, Klimont et al., 2009, Klimont et al., 2013, Lamarque et al., 2010). Research in air pollution has, however, been lagging far behind in Africa, despite the increasing death toll and the economic impact associated with air pollution in these nations. The health impact of air pollution in African cities has only been sparsely studied: a review from 2018 (Coker and Kizito, 2018) found only 3 studies outside South Africa. Earlier last year, a study showed that air pollution was responsible for 1.1 million deaths across Africa in 2019, with household air pollution—driven largely by solid biofuel used in indoor cook stoves—accounting for 697 000 fatalities (64%), while increased outdoor air pollution claimed 394 000 lives (36%) (Fisher et al., 2021).

Biologic Pollution Due to Ambrosia (Ragweed) Pollen in Urban Environment of Bucharest.

Ragweed pollen is an important component of biological pollution in the urban environment, responsible for increasing respiratory allergies and significant contribution to the health impact of air pollution in the Bucharest area. The aim of this paper is to present the eight-year ragweed pollen monitoring data from Bucharest, to place them in the context of local air pollution, public health regulations and available data on the health impact of ragweed pollen in the urban environment. Our pollen data were correlated with major air pollutant concentrations and with meteorological factors in a recently published local paper and the clinical data of patients with ragweed-induced respiratory symptoms were collected and published in 2019. The ragweed pollen monitoring data, correlated with field data reported by patients and plant specialists confirm the rapid spread of Ambrosia in the Bucharest city area, in addition to some stringent environmental local problems due to air pollution. The number of patients addressed to allergists almost doubled from one year to another, confirming the real alarming health impact of this environmental hazard. Our study confirms the need for more coherent strategies to control ragweed spread, based on application of existing local and international regulations, air pollution control and evaluation of consequences on human health.

The Chinese Spring Festival Impact on Air Quality in China: A Critical Review

It is known that the sharp change of air pollutants affects air quality. Chinese Spring Festival is the most important holiday for Chinese people, and the celebration of the holiday with fireworks and the movement of people all around the country results in significant change in multiple air pollutant emissions of various sources. As many cities and rural areas suffer from the air pollution caused by firework displays and more residential fuel consumption, there is an urgency to examine the impact of the Chinese Spring Festival on air quality. Hence, this paper firstly gives an overall insight into the holiday’s impact on ambient and household air quality in China, both in urban and rural areas. The main findings of this study are: (1) The firework displays affect the air quality of urban and rural atmosphere and household air; (2) the reduction in anthropogenic emissions improves the air quality during the Chinese Spring Festival; (3) the household air in urban areas was affected most by firework burning, while the household air in rural homes was affected most by fuel consumption; and (4) the short-term health impact of air pollution during the holidays also need more concern. Although there have been many publications focused on the holiday’s impact on ambient and household air quality, most of them focused on the measurement of pollutant concentration, while studies on the formation mechanism of air pollution, the influence of meteorological conditions, and the health outcome under the effect of the Chinese Spring Festival are rare. In the future, studies focused on these processes are welcomed.

A Dynamic Structural Equation Approach to Estimate the Short-Term Effects of Air Pollution on Human Health

Abstract Detailed knowledge on the effects of air pollutants on human health is a prerequisite for the development of effective policies to reduce the adverse impact of ambient air pollution. However, measuring the effect of exposure on health outcomes is an extremely difficult task as the health impact of air pollution is known to vary over space and over different exposure periods. In general, standard approaches aggregate the information over space or time to simplify the study but this strategy fails to recognize important regional differences and runs into the well-known risk of confounding the effects. However, modelling directly with the original, disaggregated data requires a highly dimensional model with the curse of dimensionality making inferences unstable; in these cases, the models tend to retain many irrelevant components and most relevant effects tend to be attenuated. The situation clearly calls for an intermediate solution that does not blindly aggregate data while preserving important regional features. We propose a dimension-reduction approach based on latent factors driven by the data. These factors naturally absorb the relevant features provided by the data and establish the link between pollutants and health outcomes, instead of forcing a necessarily high-dimensional link at the observational level. The dynamic structural equation approach is particularly suited for this task. The latent factor approach also provides a simple solution to the spatial misalignment caused by using variables with different spatial resolutions and the state-space representation of the model favours the application of impulse response analysis. Our approach is discussed through the analysis of the short-term effects of air pollution on hospitalization data from Lombardia and Piemonte regions (Italy).