The predictability of heat-related mortality in Prague, Czech Republic, during summer 2015-a comparison of selected thermal indices
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu srovnávací studie, časopisecké články
Grantová podpora
18-22125S
Grantov? Agentura ?esk? Republiky
MSM100421604
Akademie V?d ?esk? Republiky
1444758
National Science Foundation
1520803
National Science Foundation
PubMed
30739159
DOI
10.1007/s00484-019-01684-3
PII: 10.1007/s00484-019-01684-3
Knihovny.cz E-zdroje
- Klíčová slova
- Central Europe, Heat, Heat warning system, Heat-related mortality, Thermal indices,
- MeSH
- lidé MeSH
- poruchy vyvolané tepelným stresem mortalita MeSH
- roční období MeSH
- teoretické modely * MeSH
- velkoměsta epidemiologie MeSH
- vítr MeSH
- vlhkost MeSH
- vysoká teplota škodlivé účinky MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- srovnávací studie MeSH
- Geografické názvy
- Česká republika epidemiologie MeSH
- velkoměsta epidemiologie MeSH
We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices-Universal Thermal Climate Index and Excess Heat Factor (EHF)-were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May-September) during 1994-2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of "false alerts" compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.
Global Change Research Centre Czech Academy of Sciences Bělidla 986 603 00 Brno Czech Republic
Institute of Geophysics Czech Academy of Sciences Boční 2 1401 141 31 Prague 4 Czech Republic
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Int J Biometeorol. 1999 Oct;43(2):71-5 PubMed
Int J Biometeorol. 1999 Oct;43(2):76-84 PubMed
Am J Public Health. 2002 May;92(5):830-3 PubMed
AMA Arch Ind Health. 1957 Oct;16(4):302-16 PubMed
Int J Biometeorol. 2004 Nov;49(2):91-7 PubMed
Int J Biometeorol. 2005 Nov;50(2):121-9 PubMed
Int J Biometeorol. 2006 Jan;50(3):144-53 PubMed
Eur J Public Health. 2006 Dec;16(6):592-9 PubMed
Ind Health. 2006 Jul;44(3):388-98 PubMed
Occup Environ Med. 2007 Feb;64(2):93-100 PubMed
Int J Biometeorol. 2007 Mar;51(4):323-34 PubMed
Int J Biometeorol. 2007 Aug;51(6):525-40 PubMed
J Sci Med Sport. 2008 Jan;11(1):20-32 PubMed
Int J Biometeorol. 2008 Mar;52(4):301-10 PubMed
Int J Epidemiol. 2008 Apr;37(2):309-17 PubMed
Int J Biometeorol. 2008 Nov;52(8):733-45 PubMed
BMC Public Health. 2009 Jan 15;9:19 PubMed
Epidemiology. 2009 Jul;20(4):575-83 PubMed
Int J Biometeorol. 2010 Mar;54(2):131-9 PubMed
Am J Public Health. 2010 Jun;100(6):1137-44 PubMed
Environ Health Perspect. 2011 Apr;119(4):542-6 PubMed
Int J Biometeorol. 2012 May;56(3):537-55 PubMed
Environ Pollut. 2011 Aug-Sep;159(8-9):2035-43 PubMed
Int J Biometeorol. 2012 May;56(3):515-35 PubMed
Int J Biometeorol. 2012 Sep;56(5):801-10 PubMed
J Stat Softw. 2011 Jul;43(8):1-20 PubMed
Int J Biometeorol. 2012 May;56(3):421-8 PubMed
Int J Environ Res Public Health. 2011 Dec;8(12):4623-48 PubMed
Environ Int. 2012 Oct 1;46:23-9 PubMed
Int J Biometeorol. 2013 Jul;57(4):615-30 PubMed
Sci Rep. 2012;2:830 PubMed
Int J Biometeorol. 2013 Nov;57(6):895-907 PubMed
Int J Biometeorol. 2014 Mar;58(2):109-20 PubMed
Environ Health. 2013 Apr 05;12:27 PubMed
Int J Biometeorol. 2014 Aug;58(6):1057-68 PubMed
Environ Pollut. 2013 Dec;183:54-63 PubMed
Eur J Public Health. 2014 Aug;24(4):615-9 PubMed
Am J Epidemiol. 2014 Feb 15;179(4):467-74 PubMed
Int J Environ Res Public Health. 2014 Jan 09;11(1):952-67 PubMed
ScientificWorldJournal. 2014 Jan 08;2014:961750 PubMed
Environ Health Perspect. 2014 Sep;122(9):912-8 PubMed
Sci Total Environ. 2014 Aug 15;490:538-44 PubMed
BMC Public Health. 2014 May 21;14:480 PubMed
Int J Environ Res Public Health. 2014 Dec 23;12(1):227-53 PubMed
Int J Environ Res Public Health. 2014 Dec 23;12(1):254-67 PubMed
Environ Health Perspect. 2015 Aug;123(8):766-72 PubMed
Lancet. 2015 Jul 25;386(9991):369-75 PubMed
Environ Health Perspect. 2016 Feb;124(2):176-83 PubMed
Aust N Z J Public Health. 2015 Dec;39(6):582-7 PubMed
Int J Biometeorol. 2018 Jan;62(1):85-96 PubMed
Int J Environ Res Public Health. 2015 Dec 08;12(12):15567-83 PubMed
Environ Res. 2016 May;147:343-9 PubMed
Int J Environ Res Public Health. 2016 Mar 04;13(3):null PubMed
Am J Epidemiol. 2016 Jun 1;183(11):1027-36 PubMed
Swiss Med Wkly. 2016 Dec 05;146:w14379 PubMed
Environ Res. 2017 Oct;158:703-709 PubMed
Int J Biometeorol. 2017 Sep;61(Suppl 1):59-69 PubMed
Int J Environ Res Public Health. 2017 Dec 13;14(12): PubMed
Lancet Planet Health. 2017 Dec;1(9):e360-e367 PubMed
Int J Environ Res Public Health. 2018 Feb 27;15(3): PubMed
Int J Biometeorol. 2018 Jul;62(7):1155-1165 PubMed
Int J Environ Res Public Health. 2018 Mar 19;15(3): PubMed
Int J Biometeorol. 2018 Dec;62(12):2205-2213 PubMed