53
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      An association between air pollution and daily outpatient visits for respiratory disease in a heavy industry area.

      1 ,
      PloS one
      Public Library of Science (PLoS)

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In this work we used daily outpatient data from the Landseed Hospital in a heavily industrial area in northern Taiwan to study the associations between daily outpatient visits and air pollution in the context of a heavily polluted atmospheric environment in Chung-Li area during the period 2007-2011. We test the normality of each data set, control for the confounding factors, and calculate correlation coefficient between the outpatient visits and air pollution and meteorology, and use multiple linear regression analysis to seek significance of these associations. Our results show that temperature and relative humidity tend to be negatively associated with respiratory diseases. NO and [Formula: see text] are two main air pollutants that are positively associated with respiratory diseases, followed by [Formula: see text], [Formula: see text], [Formula: see text], CO, and [Formula: see text]. Young outpatients (age 0-15 years) are most sensitive to changing air pollution and meteorology factors, followed by the eldest (age [Formula: see text]66 years) and age 16-65 years of outpatients. Outpatients for COPD diseases are most sensitive to air pollution and meteorology factors, followed by allergic rhinitis, asthma, and pneumonia diseases. In the context of sex difference to air pollution and meteorological factors, male outpatients are more sensitive than female outpatients in the 16-65 age groups, while female outpatients are more sensitive than male outpatients in the young 0-15 age groups and in the eldest age groups. In total, female outpatients are more sensitive to air pollution and meteorological factors than male outpatients.

          Related collections

          Most cited references21

          • Record: found
          • Abstract: found
          • Article: not found

          Air pollution and health

          The health effects of air pollution have been subject to intense study in recent years. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in mortality and hospital admissions due to respiratory and cardiovascular disease. These effects have been found in short-term studies, which relate day-to-day variations in air pollution and health, and long-term studies, which have followed cohorts of exposed individuals over time. Effects have been seen at very low levels of exposure, and it is unclear whether a threshold concentration exists for particulate matter and ozone below which no effects on health are likely. In this review, we discuss the evidence for adverse effects on health of selected air pollutants.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Confounding control in healthcare database research: challenges and potential approaches.

            Epidemiologic studies are increasingly used to investigate the safety and effectiveness of medical products and interventions. Appropriate adjustment for confounding in such studies is challenging because exposure is determined by a complex interaction of patient, physician, and healthcare system factors. The challenges of confounding control are particularly acute in studies using healthcare utilization databases where information on many potential confounding factors is lacking and the meaning of variables is often unclear. We discuss advantages and disadvantages of different approaches to confounder control in healthcare databases. In settings where considerable uncertainty surrounds the data or the causal mechanisms underlying the treatment assignment and outcome process, we suggest that researchers report a panel of results under various specifications of statistical models. Such reporting allows the reader to assess the sensitivity of the results to model assumptions that are often not supported by strong subject-matter knowledge.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Regression modelling and other methods to control confounding.

              R McNamee (2005)
                Bookmark

                Author and article information

                Journal
                PLoS ONE
                PloS one
                Public Library of Science (PLoS)
                1932-6203
                1932-6203
                2013
                : 8
                : 10
                Affiliations
                [1 ] Department of Atmospheric Sciences, National Central University, Chung-Li, Taiwan.
                Article
                PONE-D-13-03185
                10.1371/journal.pone.0075220
                3808380
                24204573
                c72594f1-c790-4459-9fda-bf6fa9fe3f4a
                History

                Comments

                Comment on this article