Search

Introduction: Evidence from epidemiological studies based on individual-level data indicates that air pollution may be associated with coronavirus disease 2019 (COVID-19) severity. We aimed to test whether (1) long-term exposure to air pollution is associated with COVID-19-related hospital admission or mortality in the general population; (2) short-term exposure to air pollution is associated with COVID-19-related hospital admission following COVID-19 diagnosis; (3) there are vulnerable population subgroups; and (4) the influence of long-term air pollution exposure on COVID-19-related hospital admissions differed from that for other respiratory infections., Methods: We constructed a cohort covering nearly the full population of Catalonia through registry linkage, with follow- up from January 1, 2015, to December 31, 2020. Exposures at residential addresses were estimated using newly developed spatiotemporal models of nitrogen dioxide (NO 2 3 ), particulate matter ≤2.5 μm in aerodynamic diameter (PM 2.5 ), particulate matter ≤10 μm in aerodynamic diameter (PM 10 ), and maximum 8-hr-average ozone (O 3 ) at a spatial resolution of 250 m for the period 2018-2020., Results: The general population cohort included 4,660,502 individuals; in 2020 there were 340,608 COVID-19 diagnoses, 47,174 COVID-19-related hospital admissions, and 10,001 COVID-19 deaths. Mean (standard deviation) annual exposures were 26.2 (10.3) μg/m 3 for NO 2 , 13.8 (2.2) μg/m 3 for PM 2.5 , and 91.6 (8.2) μg/m 3 for O 3 . In Aim 1, an increase of 16.1 μg/m 3 NO 2 was associated with a 25% (95% confidence interval [CI]: 22%-29%) increase in hospitalizations and an 18% (10%-27%) increase in deaths. In Aim 2, cumulative air pollution exposure over the previous 7 days was positively associated with COVID-19-related hospital admission in the second pandemic wave (June 20 to December 31, 2020). Associations of exposure were driven by exposure on the day of the hospital admission (lag0). Associations between short-term exposure to air pollution and COVID-19-related hospital admission were similar in all population subgroups. In Aim 3, individuals with lower individual- and area-level socioeconomic status (SES) were identified as particularly vulnerable to the effects of long-term exposure to NO 2 and PM 2.5 on COVID-19-related hospital admission. In Aim 4, long-term exposure to air pollution was associated with hospital admission for influenza and pneumonia: (6%; 95% CI: 2-11 per 16.4-μg/m 3 NO 2 and 5%; 1-8 per 2.6-μg/m 3 PM 2.5 ) as well as for all lower respiratory infections (LRIs) (18%; 14-22 per 16.4-μg/m 3 NO 2 and 14%; 11-17 per 2.6-μg/m 3 PM 2.5 ) before the COVID-19 pandemic. Associations for COVID-19-related hospital admission were larger than those for influenza or pneumonia for NO 2 , PM 2.5 , and O 3 when adjusted for NO 2 ., Conclusions: Linkage across several registries allowed the construction of a large population-based cohort, tracking COVID-19 cases from primary care and testing data to hospital admissions, and death. Long- and short-term exposure to ambient air pollution were positively associated with severe COVID-19 events. The effects of long-term air pollution exposure on COVID-19 severity were greater among those with lower individual- and area-level SES., (© 2024 Health Effects Institute. All rights reserved.)

Competing Interests: Declaration of interests VK and OS are staff members of the WHO Regional Office for Europe. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions or policies of WHO. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of WHO concerning the legal status of any country, territory, city, or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there might not yet be full agreement. AK and EV are staff members of the European Environment Agency. The views expressed in this article are solely those of the authors and its content does not necessarily represent the views or position of the European Environment Agency. All other authors declare no competing interests.

Objective: Factors that shape individuals' vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO 2 , PM 2.5 , and PM 10 and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease., Methods: We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO 2 , PM 2.5 , and PM 10 . We evaluated interaction on both additive and multiplicative scales., Results: Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO 2 and 0.16, 95 % CI, 0.11 to 0.22 for PM 2.5 for males; 0.13, 95 % CI, 0.09 to 0.18 for NO 2 and 0.10, 95 % CI, 0.05 to 0.14 for PM 2.5 for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO 2 and 0.09, 95 % CI, 0.05 to 0.14 for PM 2.5 for lower area-level socioeconomic status. Results for PM 10 were similar to PM 2.5 . Results on multiplicative scale were inconsistent., Conclusions: Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19., Methods: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days., Results: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0&#95;7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant., Conclusions: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization., (© The Author(s) 2024; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Epidemiological evidence linking exposure to landscape fires to child health remains scarce. We assessed the association between daily landscape fire smoke and child hospital visits and admissions in the Manhiça district, Mozambique, an area characterised by frequent forest and cropland fires., Methods: In this time-series analysis (2012-20), our primary metric for exposure to landscape fires was fire-originated PM 2·5 from smoke dispersion hindcasts. We also assessed total and upwind fire exposure using daily satellite-derived fire density data. Daily numbers of hospital visits and admissions were extracted from an ongoing paediatric morbidity surveillance system (children aged ≤15 years). We applied quasi-Poisson regression models controlling for season, long-term trend, day of the week, temperature, and rainfall, and offsetting by annual population-time at risk to examine lag-specific association of fires on morbidity., Findings: A 10 μg/m 3 increase in fire-originated PM 2·5 was associated with a 6·12% (95% CI 0·37-12·21) increase in all-cause and a 12·43% (5·07-20·31) increase in respiratory-linked hospital visits on the following day. Positive associations were also observed for lag 0 and the cumulative lag of 0-1 days. Null associations were observed for hospital admissions. Landscape fires mostly occurred in forested areas; however, associations with child morbidity were stronger for cropland than for forest fires., Interpretation: Landscape fire smoke was associated with all-cause and respiratory-linked morbidity in children. Improved exposure assessment is needed to better quantify the contribution of landscape fire smoke to child health in regions with scarce air pollution monitoring., Funding: H2020 project EXHAUSTION, Academy of Finland, Spanish Ministry of Science and Innovation, Generalitat de Catalunya, and Government of Mozambique and Spanish Agency for International Cooperation and Development., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Environmental epidemiology studies require models of multiple exposures to adjust for co-exposure and explore interactions. We estimated spatiotemporal exposure to surface air temperature and pollution (PM 2.5 , PM 10 , NO 2 , O 3 ) at high spatiotemporal resolution (daily, 250 m) for 2018-2020 in Catalonia. Innovations include the use of TROPOMI products, a data split for remote sensing gap-filling evaluation, estimation of prediction uncertainty, and use of explainable machine learning. We compiled meteorological and air quality station measurements, climate and atmospheric composition reanalyses, remote sensing products, and other spatiotemporal data. We performed gap-filling of remotely-sensed products using Random Forest (RF) models and validated them using Out-Of-Bag (OOB) samples and a structured data split. The exposure modelling workflow consisted of: 1) PM 2.5 station imputation with PM 10 data; 2) quantile RF (QRF) model fitting; and 3) geostatistical residual spatial interpolation. Prediction uncertainty was estimated using QRF. SHAP values were used to examine variable importance and the fitted relationships. Model performance was assessed via nested CV at the station level. Evaluation of the gap-filling models using the structured split showed error underestimation when using OOB. Temperature models had the best performance (R 2 =0.98) followed by the gaseous air pollutants (R 2 =0.81 for NO 2 and 0.86 for O 3 ), while the performance of the PM 2.5 and PM 10 models was lower (R 2 =0.57 and 0.63 respectively). Predicted exposure patterns captured urban heat island effects, dust advection events, and NO 2 hotspots. SHAP values estimated a high importance of TROPOMI tropospheric NO 2 columns in PM and NO 2 models, and confirmed that the fitted associations conformed to prior knowledge. Our work highlights the importance of correctly validating gap-filling models and the potential of TROPOMI measurements. Moderate performance in PM models can be partly explained by the poor station coverage. Our exposure estimates can be used in epidemiological studies potentially accounting for exposure uncertainty., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The association between long-term exposure to ambient air pollutants and severe COVID-19 is uncertain. We followed 4,660,502 adults from the general population in 2020 in Catalonia, Spain. Cox proportional models were fit to evaluate the association between annual averages of PM 2.5 , NO 2 , BC, and O 3 at each participant's residential address and severe COVID-19. Higher exposure to PM 2.5, NO 2, and BC was associated with an increased risk of COVID-19 hospitalization, ICU admission, death, and hospital length of stay. An increase of 3.2 µg/m 3 of PM 2.5 was associated with a 19% (95% CI, 16-21) increase in hospitalizations. An increase of 16.1 µg/m 3 of NO 2 was associated with a 42% (95% CI, 30-55) increase in ICU admissions. An increase of 0.7 µg/m 3 of BC was associated with a 6% (95% CI, 0-13) increase in deaths. O 3 was positively associated with severe outcomes when adjusted by NO 2 . Our study contributes robust evidence that long-term exposure to air pollutants is associated with severe COVID-19., (© 2023. The Author(s).)

Competing Interests: Declaration of interests VK and OS are staff members of the WHO Regional Office for Europe. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions or policies of the World Health Organization. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of WHO concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there may not yet be full agreement. All other authors declare no competing interests.

Objective: Although there is evidence for the association between air pollution and decreased lung function in children, evidence for adolescents and young adults is scarce. For a peri-urban area in India, we evaluated the association of ambient PM 2.5 and household air pollution with lung function for young adults who had recently attained their expected maximum lung function., Methods: We measured, using a standardized protocol, forced expiratory volume in the first second (FEV 1 ) and forced vital capacity (FVC) in participants aged 20-26 years from the third follow-up of the population-based APCAPCS cohort (2010-2012) in 28 Indian villages. We estimated annual average PM 2.5 outdoors at residence using land-use regression. Biomass cooking fuel (a proxy for levels of household air pollution) was self-reported. We fitted a within-between linear-mixed model with random intercepts by village, adjusting for potential confounders., Results: We evaluated 1,044 participants with mean age of 22.8 (SD = 1) years (range 20-26 years); 327 participants (31%) were female. Only males reported use of tobacco smoking (9% of all participants, 13% of males). The mean ambient PM 2.5 exposure was 32.9 (SD = 2.8) µg/m 3 ; 76% reported use of biomass as cooking fuel. The adjusted association between 1 µg/m 3 increase in PM 2.5 was -27 ml (95% CI, -89 to 34) for FEV 1 and -5 ml (95% CI, -93 to 76) for FVC. The adjusted association between use of biomass was -112 ml (95% CI, -211 to -13) for FEV 1 and -142 ml (95% CI, -285 to 0) for FVC. The adjusted association was of greater magnitude for those with unvented stove (-158 ml, 95% CI, -279 to -36 for FEV 1 and -211 ml, 95% CI, -386 to -36 for FVC)., Conclusions: We observed negative associations between ambient PM 2.5 and household air pollution and lung function in young adults who had recently attained their maximum lung function., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Little is known about whether second-hand smoke (SHS) exposure affects tuberculosis (TB). Here, we investigate the association of cigarette smoke exposure with active TB and latent TB infection (LTBI) in children, analyzing Interferon-Gamma Release Assays' (IGRAs) performance and cytokine immune responses. A total of 616 children from contact-tracing studies were included and classified regarding their smoking habits [unexposed, SHS, or smokers]. Risk factors for positive IGRAs, LTBI, and active TB were defined. GM-CSF, IFN-γ, IL-2, IL-5, IL-10, IL-13, IL-22, IL-17, TNF-α, IL-1RA and IP-10 cytokines were detected in a subgroup of patients. Being SHS exposed was associated with a positive IGRA [aOR (95% CI): 8.7 (5.9-12.8)] and was a main factor related with LTBI [aOR (95% CI): 7.57 (4.79-11.94)] and active TB [aOR (95% CI): 3.40 (1.45-7.98)]. Moreover, IGRAs' sensitivity was reduced in active TB patients exposed to tobacco. IL-22, GM-CSF, IL-5, TNF-α, IP-10, and IL-13 were less secreted in LTBI children exposed to SHS. In conclusion, SHS is associated with LTBI and active TB in children. In addition, false-negative IGRAs obtained on active TB patients exposed to SHS, together with the decrease of specific cytokines released, suggest that tobacco may alter the immune response.

Quantitative evidence of health and environmental tradeoffs between individuals' drinking water choices is needed to inform decision-making. We evaluated health and environmental impacts of drinking water choices using health impact and life cycle assessment (HIA, LCA) methodologies applied to data from Barcelona, Spain. We estimated the health and environmental impacts of four drinking water scenarios for the Barcelona population: 1) currently observed drinking water sources; a complete shift to 2) tap water; 3) bottled water; or 4) filtered tap water. We estimated the local bladder cancer incidence attributable to trihalomethane (THM) exposure, based on survey data on drinking water sources, THM levels, published exposure-response functions, and disability-adjusted life years (DALYs) from the Global Burden of Disease 2017. We estimated the environmental impacts (species lost/year, and resources use) from waste generation and disposal, use of electricity, chemicals, and plastic to produce tap or bottled drinking water using LCA. The scenario where the entire population consumed tap water yielded the lowest environmental impact on ecosystems and resources, while the scenario where the entire population drank bottled water yielded the highest impacts (1400 and 3500 times higher for species lost and resource use, respectively). Meeting drinking water needs using bottled or filtered tap water led to the lowest bladder cancer DALYs (respectively, 140 and 9 times lower than using tap water) in the Barcelona population. Our study provides the first attempt to integrate HIA and LCA to compare health and environmental impacts of individual water consumption choices. Our results suggest that the sustainability gain from consuming water from public supply relative to bottled water may exceed the reduced risk of bladder cancer due to THM exposure from consuming bottled water in Barcelona. Our analysis highlights several critical data gaps and methodological challenges in quantifying integrated health and environmental impacts of drinking water choices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region., Objectives: Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia., Methods: The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies., Results: From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures - above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate., Conclusions: The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)