Air pollutants and daily number of admissions to psychiatric emergency services: evidence for detrimental mental health effects of ozone

Bernardini, Francesco; Attademo, Luigi; Trezzi, Riccardo; Gobbicchi, Chiara; Balducci, Pierfrancesco Maria; Bello, Valentina Del; Menculini, Giulia; Pauselli, Luca; Piselli, Massimiliano; Sciarma, Tiziana; Moretti, Patrizia; Tamantini, Antonia; Quartesan, Roberto; Compton, Michael T.; Tortorella, Alfonso

doi:10.1017/s2045796019000623

Cited by 44 publications

(24 citation statements)

References 35 publications

(59 reference statements)

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“…Similarly, Xue et al (2020) studied spatiotemporal variations for Shanghai and suggested that increased focus on urban residential planning and introduction of emission management policies have significantly reduced NO 2 concentrations in Shanghai. Bernardini et al (2020) explored the impact of air pollutants, i.e., O 3 , and suggested that a number of patients into the emergency section have direct correlation with air pollutants. Furthermore, Adach et al (2020) and Ha (2020) registered similar findings.…”

Section: Methodsmentioning

confidence: 99%

Environmental pollution and COVID-19 outbreak: insights from Germany

Bilal

Bashir

Benghoul

et al. 2020

Air Qual Atmos Health

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The impact of environmental pollutants and climate indicators on the outbreak of COVID-19 has gained considerable attention in the recent literature. However, specific investigation of industrial economies like Germany is not available. This provides us motivation to examine the association between environmental pollutants, climate indicators and the COVID-19 cases, recoveries, and deaths in Germany using daily data from February 24, 2020, to July 02, 2020. The correlation analysis and wavelet transform coherence (WTC) approach are the analytical tools, which are used to explore the association between variables included in the study. Our findings indicate that PM2.5, O 3 , and NO 2 have a significant relationship with the outbreak of COVID-19. In addition, temperature is the only significant climate indicator which has significant correlation with the spread of COVID-19. Finally, PM10, humidity, and environmental quality index have a significant relationship only with the active cases from COVID-19 pandemic. Our findings conclude that Germany's successful response to COVID-19 is attributed to environmental legislation and the medical care system, which oversaw significant overhaul after the SARS and MERS outbreaks. The current study implicates that other industrial economies, especially European economies, that are still facing COVID-19 outbreak can follow the German model for pandemic response.

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Section: Methodsmentioning

confidence: 99%

Environmental pollution and COVID-19 outbreak: insights from Germany

Bilal

Bashir

Benghoul

et al. 2020

Air Qual Atmos Health

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show abstract

“…Researchers and healthcare practitioners across fields of biomedicine acknowledge the tremendous impact that environmental exposures have on health and disease. For example, airborne pollutant exposures have been linked to diseases as diverse as asthma [1][2][3][4][5][6], diabetes [7][8][9], cardiovascular disease [10], dementia [11], mental health disorders [12], obesity [13], liver disease [14], and premature mortality [15]. Yet, informatics tools to study the interaction between environmental exposures and health outcomes at the level of the individual are largely non-existent.…”

Section: Introductionmentioning

confidence: 99%

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

Cox

Stillwell

et al. 2020

BMC Med Inform Decis Mak

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Background: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results: We have developed an open-source software application-FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)-to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution's clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. Conclusions: While FHIR PIT was developed to support our driving use case on asthma, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

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Section: Introductionmentioning

confidence: 99%

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

Cox

Stillwell

et al. 2020

Preprint

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Background: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. Results: We have developed an open-source software application—FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)—to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution’s clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We have validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations.Conclusions: While FHIR PIT was developed to support our driving use case, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.

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Air pollutants and daily number of admissions to psychiatric emergency services: evidence for detrimental mental health effects of ozone

Cited by 44 publications

References 35 publications

Environmental pollution and COVID-19 outbreak: insights from Germany

Environmental pollution and COVID-19 outbreak: insights from Germany

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data

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