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      Ambient Nitrogen Dioxide and Hospitalizations of Full-Spectrum Respiratory Diseases: A National Case-Crossover Study

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          Abstract

          Few multicity studies have examined the acute effects of nitrogen dioxide (NO 2) on respiratory disease (RD), especially its specific causes. This study aimed to investigate the associations between short-term exposure to NO 2 and hospitalization of full-spectrum RDs in China. Hospitalization of 10 major categories and 40 cause-specific RDs were obtained from 20 provinces over the study period of 2013–2020. A time-stratified case-crossover study was conducted at the individual level to explore the associations between NO 2 and RDs. NO 2 was significantly associated with increased hospitalization of eight major RDs (acute upper respiratory infections, influenza and pneumonia, acute lower respiratory infections, upper respiratory tract diseases, chronic lower respiratory diseases, respiratory interstitium diseases, pleura diseases, and other respiratory diseases) and 18 specific causes of RDs, with the largest associations observed on lag 0–1 day. The effect estimates ranged from 0.75 to 4.09% per 10 μg/m 3 of NO 2 exposure. The associations remained robust after controlling for copollutants. The concentration–response curves were mostly positive and linear. This nationwide study provides comprehensive information on the acute effects of NO 2 on respiratory morbidity across the full spectrum, highlighting the need for caution with regard to this important traffic-related air pollutant in current pollution control programs.

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          Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries.

          Giacomo Bellani, John Laffey, Tài Pham … (2016)
          Limited information exists about the epidemiology, recognition, management, and outcomes of patients with the acute respiratory distress syndrome (ARDS).
          Article 0 comments Cited 1613 times – based on 0 reviews     Review now
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            Ambient Particulate Air Pollution and Daily Mortality in 652 Cities

            Cong Cong Liu, Renjie Chen, Francesco Sera … (2019)
            The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 μ m or less (PM 10 ) and fine PM with an aerodynamic diameter of 2.5 μ m or less (PM 2.5 ) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration–response curves from each city were pooled to allow global estimates to be derived. On average, an increase of 10 μ g per cubic meter in the 2-day moving average of PM 10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM 2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration–response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. Our data show independent associations between short-term exposure to PM 10 and PM 2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.)
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              Exposure measurement error in time-series studies of air pollution: concepts and consequences.

              S Zeger, Owen D Thomas, F Dominici … (2000)
              Misclassification of exposure is a well-recognized inherent limitation of epidemiologic studies of disease and the environment. For many agents of interest, exposures take place over time and in multiple locations; accurately estimating the relevant exposures for an individual participant in epidemiologic studies is often daunting, particularly within the limits set by feasibility, participant burden, and cost. Researchers have taken steps to deal with the consequences of measurement error by limiting the degree of error through a study's design, estimating the degree of error using a nested validation study, and by adjusting for measurement error in statistical analyses. In this paper, we address measurement error in observational studies of air pollution and health. Because measurement error may have substantial implications for interpreting epidemiologic studies on air pollution, particularly the time-series analyses, we developed a systematic conceptual formulation of the problem of measurement error in epidemiologic studies of air pollution and then considered the consequences within this formulation. When possible, we used available relevant data to make simple estimates of measurement error effects. This paper provides an overview of measurement errors in linear regression, distinguishing two extremes of a continuum-Berkson from classical type errors, and the univariate from the multivariate predictor case. We then propose one conceptual framework for the evaluation of measurement errors in the log-linear regression used for time-series studies of particulate air pollution and mortality and identify three main components of error. We present new simple analyses of data on exposures of particulate matter < 10 microm in aerodynamic diameter from the Particle Total Exposure Assessment Methodology Study. Finally, we summarize open questions regarding measurement error and suggest the kind of additional data necessary to address them. Images Figure 1 Figure 2 Figure 3
              Article 0 comments Cited 316 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Environ Health (Wash)
                Journal ID (iso-abbrev): Environ Health (Wash)
                Journal ID (publisher-id): eh
                Journal ID (coden): ehnea2
                Title: Environment & Health
                Publisher: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, and American Chemical Society
                ISSN (Electronic): 2833-8278
                Publication date (Electronic): 16 July 2023
                Publication date Collection: 18 August 2023
                Volume: 1
                Issue: 2
                Pages: 130-138
                Affiliations
                [† ]School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University , Shanghai 200032, China
                [‡ ]Health Economic Research Institute, School of Pharmacy, Sun Yat-Shen University , Guangzhou 510275, China
                [§ ]Children’s Hospital of Fudan University, National Center for Children’s Health , Shanghai 201102, China
                Author notes
                [* ]Tel: +86 (21) 64046351. Fax: +86 (21) 64046351. Email: kanh@ 123456fudan.edu.cn .
                Author information
                https://orcid.org/0000-0002-1871-8999
                Article
                DOI: 10.1021/envhealth.3c00039
                PMC ID: 11504538
                PubMed ID: 39473582
                SO-VID: 2980c734-63a4-43a0-9e58-4c0b37200178
                Copyright © © 2023 The Authors. Co-published by Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, and American Chemical Society
                License:

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Date received : 23 April 2023
                Date accepted : 29 June 2023
                Date revision received : 28 June 2023
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 82103790
                Funded by: Shanghai International Science and Technology, doi 10.13039/501100009962;
                Award ID: 21230780200
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 92043301
                Categories
                Subject: Article
                Custom metadata
                document-id-old-9 eh3c00039
                document-id-new-14 eh3c00039
                ccc-price

                Keywords: nitrogen dioxide,respiratory disease,hospitalization,cause-specific,case-crossover study
                Data availability:
                Keywords: nitrogen dioxide, respiratory disease, hospitalization, cause-specific, case-crossover study

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