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      Ambient air pollution and cause-specific risk of hospital admission in China: A nationwide time-series study

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          Abstract

          Background

          The impacts of air pollution on circulatory and respiratory systems have been extensively studied. However, the associations between air pollution exposure and the risk of noncommunicable diseases of other organ systems, including diseases of the digestive, musculoskeletal, and genitourinary systems, remain unclear or inconclusive. We aimed to systematically assess the associations between short-term exposure to main air pollutants (fine particulate matter [PM 2.5] and ozone) and cause-specific risk of hospital admission in China over a wide spectrum of human diseases.

          Methods and findings

          Daily data on hospital admissions for primary diagnosis of 14 major and 188 minor disease categories in 252 Chinese cities (107 cities in North China and 145 cities in South China) from January 1, 2013, to December 31, 2017, were obtained from the Hospital Quality Monitoring System of China (covering 387 hospitals in North China and 614 hospitals in South China). We applied a 2-stage analytic approach to assess the associations between air pollution and daily hospital admissions. City-specific associations were estimated with quasi-Poisson regression models and then pooled by random-effects meta-analyses. Each disease category was analyzed separately, and the P values were adjusted for multiple comparisons. A total of 117,338,867 hospital admissions were recorded in the study period. Overall, 51.7% of the hospitalized cases were male, and 71.3% were aged <65 years. Robust positive associations were found between short-term PM 2.5 exposure and hospital admissions for 7 major disease categories: (1) endocrine, nutritional, and metabolic diseases; (2) nervous diseases; (3) circulatory diseases; (4) respiratory diseases; (5) digestive diseases; (6) musculoskeletal and connective tissue diseases; and (7) genitourinary diseases. For example, a 10-μg/m 3 increase in PM 2.5 was associated with a 0.21% (95% CI 0.15% to 0.27%; adjusted P < 0.001) increase in hospital admissions for diseases of the digestive system on the same day in 2-pollutant models (adjusting for ozone). There were 35 minor disease categories significantly positively associated with same-day PM 2.5 in both single- and 2-pollutant models, including diabetes mellitus, anemia, intestinal infection, liver diseases, gastrointestinal hemorrhage, renal failure, urinary tract calculus, chronic ulcer of skin, and back problems. The association between short-term ozone exposure and respiratory diseases was robust. No safety threshold in the exposure–response relationships between PM 2.5 and hospital admissions was observed. The main limitations of the present study included the unavailability of data on personal air pollution exposures.

          Conclusions

          In the Chinese population during 2013–2017, short-term exposure to air pollution, especially PM 2.5, was associated with increased risk of hospitalization for diseases of multiple organ systems, including certain diseases of the digestive, musculoskeletal, and genitourinary systems; many of these associations are important but still not fully recognized. The effect estimates and exposure–response relationships can inform policy making aimed at protecting public health from air pollution in China.

          Abstract

          Jiangshao Gu reveal the increased risk of hospital admission from exposure to PM2.5 in a multi city analysis.

          Author summary

          Why was this study done?
          • Besides the well-known cardiorespiratory effects of air pollution, an increasing number of studies suggest that air pollution might be associated with certain non-cardiorespiratory diseases.

          • Evidence of associations between air pollution exposure and the risk of many non-cardiorespiratory diseases is still scarce and inconclusive.

          • Few studies have characterized the acute health effects of air pollution on multiple organ systems using uniform methodology and databases.

          What did the researchers do and find?
          • We conducted a national time-series study using data of 117,338,867 hospital admissions for 14 major and 188 minor disease categories in 252 Chinese cities from 2013 to 2017, to assess the associations between short-term exposure to fine particulate matter (PM 2.5) and ozone and cause-specific risk of hospital admission on a national scale.

          • City-specific associations were estimated with quasi-Poisson regression models and then pooled by random-effects meta-analyses. Each disease category was analyzed separately, and the P values were adjusted for multiple comparisons.

          • Short-term PM 2.5 exposure was significantly positively associated with hospital admissions for 13 major disease categories (of which 7 associations were considered robust, including for diseases of the digestive, musculoskeletal, and genitourinary systems) and 35 minor disease categories, whether adjusted for ozone or not. The association between short-term ozone exposure and respiratory diseases was robust.

          What do these findings mean?
          • To our knowledge, this is the first national study in China aimed at systematically investigating possible ways in which short-term air pollution exposure may be associated with severe illnesses requiring hospitalization.

          • Our findings highlight the extensive adverse impacts of air pollution on human health, and indicate the significant social benefits of effective mitigation measures.

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          Most cited references54

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            • Article: not found

            Fine particulate air pollution and mortality in 20 U.S. cities, 1987-1994.

            Air pollution in cities has been linked to increased rates of mortality and morbidity in developed and developing countries. Although these findings have helped lead to a tightening of air-quality standards, their validity with respect to public health has been questioned. We assessed the effects of five major outdoor-air pollutants on daily mortality rates in 20 of the largest cities and metropolitan areas in the United States from 1987 to 1994. The pollutants were particulate matter that is less than 10 microm in aerodynamic diameter (PM10), ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide. We used a two-stage analytic approach that pooled data from multiple locations. After taking into account potential confounding by other pollutants, we found consistent evidence that the level of PM10 is associated with the rate of death from all causes and from cardiovascular and respiratory illnesses. The estimated increase in the relative rate of death from all causes was 0.51 percent (95 percent posterior interval, 0.07 to 0.93 percent) for each increase in the PM10 level of 10 microg per cubic meter. The estimated increase in the relative rate of death from cardiovascular and respiratory causes was 0.68 percent (95 percent posterior interval, 0.20 to 1.16 percent) for each increase in the PM10 level of 10 microg per cubic meter. There was weaker evidence that increases in ozone levels increased the relative rates of death during the summer, when ozone levels are highest, but not during the winter. Levels of the other pollutants were not significantly related to the mortality rate. There is consistent evidence that the levels of fine particulate matter in the air are associated with the risk of death from all causes and from cardiovascular and respiratory illnesses. These findings strengthen the rationale for controlling the levels of respirable particles in outdoor air.
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              Trends in Chronic Kidney Disease in China.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: Writing – review & editing
                Role: Data curationRole: SupervisionRole: Writing – review & editing
                Role: Data curationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                6 August 2020
                August 2020
                : 17
                : 8
                : e1003188
                Affiliations
                [1 ] Center for Big Data Research in Health and Medicine, Institute for Data Sciences, Tsinghua University, Beijing, China
                [2 ] Tsinghua-Fuzhou Institute of Digital Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China
                [3 ] Institute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China
                [4 ] China Standard Medical Information Research Center, Shenzhen, China
                [5 ] Department of Environmental Health Science, University of California at Los Angeles, Los Angeles, California, United States of America
                [6 ] Institute of the Environment and Sustainability, University of California at Los Angeles, Los Angeles, California, United States of America
                [7 ] Clinical Trial Unit, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
                [8 ] Bureau of Medical Administration, National Health Commission of the People’s Republic of China, Beijing, China
                Monash University, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                ‡ These authors are joint senior authors on this work.

                Author information
                http://orcid.org/0000-0002-7897-381X
                http://orcid.org/0000-0002-0591-3322
                http://orcid.org/0000-0003-0818-138X
                http://orcid.org/0000-0002-3228-9166
                Article
                PMEDICINE-D-19-04229
                10.1371/journal.pmed.1003188
                7410211
                32760064
                408babfc-e518-4620-8735-14c93e19422e
                © 2020 Gu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 November 2019
                : 8 July 2020
                Page count
                Figures: 3, Tables: 4, Pages: 26
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 61872218, 61721003, and 61673241
                Award Recipient :
                Funded by: Beijing National Research Center for Information Science and Technology
                Award Recipient :
                JG, NC, and TC were supported by the National Natural Science Foundation of China (grants 61872218, 61721003, and 61673241; http://www.nsfc.gov.cn) and Beijing National Research Center for Information Science and Technology (BNRist). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Health Care Facilities
                Hospitals
                Ecology and Environmental Sciences
                Pollution
                Air Pollution
                Earth Sciences
                Geography
                Human Geography
                Urban Geography
                Cities
                Social Sciences
                Human Geography
                Urban Geography
                Cities
                People and Places
                Geographical Locations
                Asia
                China
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Biology and Life Sciences
                Anatomy
                Respiratory System
                Medicine and Health Sciences
                Anatomy
                Respiratory System
                Medicine and Health Sciences
                Diagnostic Medicine
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Respiratory Infections
                Medicine and Health Sciences
                Medical Conditions
                Respiratory Disorders
                Respiratory Infections
                Medicine and Health Sciences
                Pulmonology
                Respiratory Disorders
                Respiratory Infections
                Custom metadata
                Air pollution data can be accessed from the National Air Pollution Monitoring System ( http://106.37.208.233:20035/). Meteorological data can be accessed from the China Meteorological Data Sharing Service System ( http://data.cma.cn/). Hospital admission data were obtained from the Hospital Quality Monitoring System (HQMS) ( https://www.hqms.org.cn/) and cannot be made publicly available due to ethical and legal restrictions. These routinely collected healthcare data, though anonymized and de-identified, contain potentially identifying or sensitive patient information. Data that are not directly identifying, including the date of admission, clinical diagnosis, and demographic information, can become identifying in combination. According to the Personal Information Protection Law in the People’s Republic of China, these data cannot be shared publicly. The data are available upon request for researchers who meet the criteria for access to confidential data. Data requesters are required to submit a research proposal to the scientific committee of the HQMS via the Scientific Project Management System ( https://spms.hqms.org.cn/), under the regulation of Bureau of Medical Administration, National Health Commission of the People’s Republic of China. The research proposal should address: (1) the background and rationale of the proposed research project; (2) the scope of the relevant data (eg, the list of relevant data items, time range, hospital scope, and the list of relevant ICD-10 codes); (3) the significance of the expected results in terms of informing public health policy makers. The scientific committee of the HQMS will review the research proposal to ensure the appropriateness of its intended use, and the data will be available if the proposal is approved. For more information and for technical assistance, please contact the HQMS staff ( service@ 123456hqms.org.cn ).

                Medicine
                Medicine

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