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      The burden of ambient temperature on years of life lost in Guangzhou, China

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          Abstract

          Limited evidence is available on the association between temperature and years of life lost (YLL). We applied distributed lag non-linear model to assess the nonlinear and delayed effects of temperature on YLL due to cause-/age-/education-specific mortality in Guangzhou, China. We found that hot effects appeared immediately, while cold effects were more delayed and lasted for 14 days. On average, 1 °C decrease from 25 th to 1 st percentile of temperature was associated with an increase of 31.15 (95%CI: 20.57, 41.74), 12.86 (8.05, 17.68) and 6.64 (3.68, 9.61) YLL along lag 0–14 days for non-accidental, cardiovascular and respiratory diseases, respectively. The corresponding estimate of cumulative hot effects (1 °C increase from 75 th to 99 th percentile of temperature) was 12.71 (−2.80, 28.23), 4.81 (−2.25, 11.88) and 2.81 (−1.54, 7.16). Effect estimates of cold and hot temperatures-related YLL were higher in people aged up to 75 years and persons with low education level than the elderly and those with high education level, respectively. The mortality risks associated with cold and hot temperatures were greater on the elderly and persons with low education level. This study highlights that YLL provides a complementary method for assessing the death burden of temperature.

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          Effects of cold weather on mortality: results from 15 European cities within the PHEWE project.

          A Analitis, K Katsouyanni, A. Biggeri … (2008)
          Weather-related health effects have attracted renewed interest because of the observed and predicted climate change. The authors studied the short-term effects of cold weather on mortality in 15 European cities. The effects of minimum apparent temperature on cause- and age-specific daily mortality were assessed for the cold season (October-March) by using data from 1990-2000. For city-specific analysis, the authors used Poisson regression and distributed lag models, controlling for potential confounders. Meta-regression models summarized the results and explored heterogeneity. A 1 degrees C decrease in temperature was associated with a 1.35% (95% confidence interval (CI): 1.16, 1.53) increase in the daily number of total natural deaths and a 1.72% (95% CI: 1.44, 2.01), 3.30% (95% CI: 2.61, 3.99), and 1.25% (95% CI: 0.77, 1.73) increase in cardiovascular, respiratory, and cerebrovascular deaths, respectively. The increase was greater for the older age groups. The cold effect was found to be greater in warmer (southern) cities and persisted up to 23 days, with no evidence of mortality displacement. Cold-related mortality is an important public health problem across Europe. It should not be underestimated by public health authorities because of the recent focus on heat-wave episodes.
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            Impact of high temperatures on mortality: is there an added heat wave effect?

            Michela Baccini, Bettina Menne, Anna Pàldy … (2006)
            Mortality during sustained periods of hot weather is generally regarded as being in excess of what would be predicted from smooth temperature-mortality gradients estimated using standard time-series regression models. However, the evidence for an effect of continuous days of exceptional heat ("heat wave effect") is indirect. In addition, because some interventions may be triggered only during forecasted heat waves, it would be helpful to know what fraction of all heat-related deaths falls during these specific periods and what fraction occurs throughout the remainder of the summer. Extended time-series data sets of daily mortality counts in 3 major European cities (London, 28 years of data; Budapest, 31 years; Milan, 18 years) were examined in relation to hot weather using a generalized estimating equations approach. We modeled temperature and specific heat wave terms using a variety of specifications. With a linear effect of same-day temperature above an identified threshold, an additional "heat wave" effect of 5.5% was observed in London (95% confidence interval = 2.2 to 8.9), 9.3% in Budapest (5.8 to 13.0), and 15.2% in Milan (5.7 to 22.5). Heat wave effects were reduced slightly when we relaxed the linear assumption and these effects were reduced substantially when temperature was modeled as an average value of lags 0 to 2 days. In London, fewer than half of all heat-related deaths could be attributed to identified heat wave periods. In Milan and Budapest, the fraction was less than one fifth. Heat wave effects were apparent in simple time-series models but were reduced in multilag nonlinear models and small when compared with the overall summertime mortality burden of heat. Reduction of the overall heat burden requires preventive measures in addition to those that target warnings and responses uniquely to heat waves.
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              Vulnerability to heat-related mortality: a multicity, population-based, case-crossover analysis.

              Massimo Stafoggia, Francesco Forastiere, Daniele Agostini … (2006)
              Although studies have documented increased mortality during heat waves, little information is available on the subgroups most susceptible to these effects. We evaluated the effects of summertime high temperature on daily mortality among population subgroups defined by demographic characteristics, socioeconomic status, and episodes of hospitalization for various conditions during the preceding 2 years. We studied a total of 205,019 residents of 4 Italian cities (Bologna, Milan, Rome, and Turin) age 35 or older who died during 1997-2003. The case-crossover design was applied to evaluate the association between mean apparent temperature (same and previous day) and all-cause mortality. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of dying at 30 degrees C (apparent temperature) relative to 20 degrees C were estimated accounting for time, population changes, and air pollution. We found an overall OR of 1.34 (CI = 1.27-1.42) at 30 degrees C relative to 20 degrees C. The odds ratio increased with age and was higher among women (OR = 1.45; 1.37-1.52) and among widows and widowers (1.50; 1.33-1.69). Low area-based income modestly increased the effect. Among the preexisting medical conditions investigated, effect modification was detected for previous psychiatric disorders (1.69; 1.39-2.07), depression (1.72; 1.24-2.39), heart conduction disorders (1.77; 1.38-2.27), and circulatory disorders of the brain (1.47; 1.34-1.62). Temperature-related mortality was higher among people residing in nursing homes, and a large effect was also detected for hospitalized subjects. Subsets of the population that are particularly vulnerable to high summer temperatures include the elderly, women, widows and widowers, those with selected medical conditions, and those staying in nursing homes and healthcare facilities.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 06 August 2015
                Publication date Collection: 2015
                Volume: 5
                Electronic Location Identifier: 12250
                Affiliations
                [1 ]State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing 102206, China
                [2 ]State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health and Tropical Medicine, Southern Medical University , Guangzhou 510515, China
                [3 ]Division of Epidemiology and Biostatistics, School of Public Health, The University of Queensland , Brisbane, Queensland 4006, Australia
                [4 ]Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention , Qunxian Road, 160, Guangzhou 511430, China
                [5 ]Climate Change and Health Center, Shandong University , Jinan 250012, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                Publisher Item ID: srep12250
                DOI: 10.1038/srep12250
                PMC ID: 4527090
                PubMed ID: 26247571
                SO-VID: 46985d37-9f4a-4640-97a5-eaa979862534
                Copyright © Copyright © 2015, Macmillan Publishers Limited
                License:

                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
                Date received : 01 October 2014
                Date accepted : 23 June 2015
                Categories
                Subject: Article

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