Impact of High Temperatures on Mortality

Is There an Added Heat Wave Effect?

Dados Bibliográficos

ID23329253
AutoresShakoor Hajat (0000-0002-3086-362X, London School of Hygiene & Tropical Medicine, autor correspondente), Ben Armstrong (0000-0002-3354-4376, University of London, autor correspondente), Michela Baccini (0000-0002-2619-2130, University of Florence), Annibale Biggeri (0000-0003-2343-3346, University of Florence), Luigi Bisanti (Local Government Association), Antonio Giampiero Russo (0000-0002-5681-5861, Local Government Association), Antonio Russo (0000-0001-6019-1425), Anna Páldy (0000-0002-9166-7374, National Public Health and Medical Officer Service), Bettina Menne (0000-0002-3135-2290, World Health Organization Regional Office for Europe), Tom Kosatsky (McGill University Health Centre)
Ano2006
Volume17
Fascículo6
Páginas632-638
Data de publicação2006-11-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoEpidemiology (JOURNAL)
Identificadores do periódicoISSN: 1044-3983 • E-ISSN: 1531-5487
EditoraOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/01.ede.0000239688.70829.63
PMID17003686
OpenAlexW2012406979
IdiomaEN
Citações recebidas76
Referências citadas23

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Apparent temperature · Climate change · Climatology · Confidence interval · Fraction (chemistry) · Geography · Heat wave · Linear regression · Meteorology · Statistics · Chemistry · Climate Change and Health Impacts · Demography · Environmental Science · Geology · Mathematics · Thermal Regulation in Medicine · Thermoregulation and physiological responses