25
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Aging Will Amplify the Heat-related Mortality Risk under a Changing Climate: Projection for the Elderly in Beijing, China

      research-article

      Read this article at

      Bookmark
          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

          An aging population could substantially enhance the burden of heat-related health risks in a warming climate because of their higher susceptibility to extreme heat health effects. Here, we project heat-related mortality for adults 65 years and older in Beijing China across 31 downscaled climate models and 2 representative concentration pathways (RCPs) in the 2020s, 2050s, and 2080s. Under a scenario of medium population and RCP8.5, by the 2080s, Beijing is projected to experience 14,401 heat-related deaths per year for elderly individuals, which is a 264.9% increase compared with the 1980s. These impacts could be moderated through adaptation. In the 2080s, even with the 30% and 50% adaptation rate assumed in our study, the increase in heat-related death is approximately 7.4 times and 1.3 times larger than in the 1980s respectively under a scenario of high population and RCP8.5. These findings could assist countries in establishing public health intervention policies for the dual problems of climate change and aging population. Examples could include ensuring facilities with large elderly populations are protected from extreme heat (for example through back-up power supplies and/or passive cooling) and using databases and community networks to ensure the home-bound elderly are safe during extreme heat events.

          Related collections

          Most cited references20

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

          Global variation in the effects of ambient temperature on mortality: a systematic evaluation.

          Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Models for the relationship between ambient temperature and daily mortality.

            Ambient temperature is an important determinant of daily mortality that is of interest both in its own right and as a confounder of other determinants investigated using time-series regressions, in particular, air pollution. The temperature-mortality relationship is often found to be substantially nonlinear and to persist (but change shape) with increasing lag. We review and extend models for such nonlinear multilag forms. Popular models for mortality by temperature at given lag include polynomial and natural cubic spline curves, and the simple but more easily interpreted linear thresholds model, comprising linear relationships for temperatures below and above thresholds and a flat middle section. Most published analyses that have allowed the relationship to persist over multiple lags have done so by assuming that spline or threshold models apply to mean temperature in several lag strata (e.g., lags 0-1, 2-6, and 7-13). However, more flexible models are possible, and a modeling framework using products of basis functions ("cross-basis" functions) suggests a wide range, some used previously and some new. These allow for stepped or smooth changes in the model coefficients as lags increase. Applying a range of models to data from London suggest evidence for relationships up to at least 2 weeks' lag, with smooth models fitting best but lag-stratified threshold models allowing the most direct interpretation. A wide range of multilag nonlinear temperature-mortality relationships can be modeled. More awareness of options should improve investigation of these relationships and help control for confounding by them.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Climate change effects on human health: projections of temperature-related mortality for the UK during the 2020s, 2050s and 2080s.

              The most direct way in which climate change is expected to affect public health relates to changes in mortality rates associated with exposure to ambient temperature. Many countries worldwide experience annual heat-related and cold-related deaths associated with current weather patterns. Future changes in climate may alter such risks. Estimates of the likely future health impacts of such changes are needed to inform public health policy on climate change in the UK and elsewhere.
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                20 June 2016
                2016
                : 6
                : 28161
                Affiliations
                [1 ]Institute for Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention , Beijing, China
                [2 ]Center for Climate Systems Research, Columbia University , New York, USA
                [3 ]The National Center for Chronic and Noncommunicable Disease Control and Prevention , Beijing, China
                [4 ]Institute of Urban Meteorology, China Meteorological Administration (CMA) , Beijing, China
                [5 ]Mailman School of Public Health, Columbia University , New York, USA
                Author notes
                Article
                srep28161
                10.1038/srep28161
                4913346
                27320724
                2693b4d8-4e5f-4ef5-bf0e-4064f560c371
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 06 October 2015
                : 31 May 2016
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article