Long-term projections and acclimatization scenarios of temperature-related mortality in Europe

Ballester, Joan; Robine, Jean-Marie; Herrmann, Françoís; Rodó, Xavier

doi:10.1038/ncomms1360

Cited by 135 publications

(114 citation statements)

References 37 publications

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“…Apparent temperature (AT) was derived from the daily mean temperature (°C) and dew point temperature (°C) using the formula AT = − 2. 65 3 + (0 .9 94 × dai ly m ea n te mp era tur e) + (0.0153×[daily dew point temperature] 2 ), which is commonly used in epidemiological studies of heat exposure (Alessandrini et al 2011;Almeida et al 2010;Ballester et al 2011;Kovats and Hajat 2008;Michelozzi et al 2009;O'Neill et al 2003;Wichmann et al 2011).…”

Section: Apparent Temperaturementioning

confidence: 99%

Temperature deviation index and elderly mortality in Japan

et al. 2015

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Few studies have examined how the precedence of abnormal temperatures in previous neighboring years affects the population's health. In the present study, we attempted to quantify the health effects of abnormal weather patterns by creating a metric called the temperature deviation index (TDI) and estimated the effects of TDI on mortality in Japan. We used data from 47 prefectures in Japan to compute the TDI on days between May and September from 1966 to 2010. The TDI is a summed product of an indicator of absence of high temperatures in the neighboring years, and more weights were assigned to the years closest to the current year. To estimate the TDI effects on elderly mortality, we used generalized linear modeling with a Poisson distribution after adjusting for apparent temperature, barometric pressure, day of the week, and time trend. For each prefecture, we estimated the TDI effects and pooled the estimates to yield a national average for 1991-2010 in Japan. The estimated effects of TDI in middle- or high-latitude prefectures were greater than in low-latitude prefectures. The estimated national average of TDI effects was a 0.5 % (95 % confidence intervals [CI], 0.1, 1.0) increase in elderly mortality per 1-unit (around 1 standard deviation) increase in the TDI. The significant pooled estimation of TDI effects was mainly due to the TDI effects on summer days with moderate temperature (25th-49th percentile, mean temperature 22.9 °C): a 1.9 % (95 % CI, 1.1, 2.6) increase in elderly mortality per 1-unit increase in the TDI. However, TDI effects were insignificant in other temperature ranges. These findings suggest that elderly deaths increased on moderate temperature days in the summer that differed substantially from days during that time window in the neighboring years. Therefore, not only high temperature itself but also temperature deviation compared to previous years could be considered to be a risk factor for elderly mortality in the summer.

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Section: Apparent Temperaturementioning

confidence: 99%

Temperature deviation index and elderly mortality in Japan

et al. 2015

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“…Heat wave exists if the daily composite mean of the surface air temperature anomaly becomes more than or equal +3˚C and persist for five successive days or more over the area of study. Whereas, the comfort apparent temperatures ranged from +14˚C in central Europe to +25˚C in southern Spain, and it significantly higher than annual mean apparent temperatures between +3.5˚C and +12.5˚C [25]. However, the present data and methodology are chosen according to the main features of the heat waves.…”

Section: Methodsmentioning

confidence: 99%

On the Relationship between Heat Waves over the Western and Central Europe and NAO, SOI, El-Nino 3.4 in Summer 2015

Hafez¹

2017

GEP

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An extreme warming hit Europe in summer of the year 2015. The present paper investigates the relationship between the North Atlantic Oscillation Index (NAO), Southern Oscillation Index (SOI) and El-Nino 3.4 and heat waves that persist over the western and central Europe in the summer of 2015. The NCEP/NCAR Reanalysis daily dataset of the mean surface air temperature for the domains of the western and central Europe for summer months (June, July and August) of the year, 2015 has used. In addition, the time cross-section analysis of the daily gridded operational data for the mean surface air temperature over the western and central Europe from 1 June to 31 August 2015 has done. Moreover, daily datasets of the NAO, SOI, and El-Nino 3.4 for that period have used. The time series, time cross section, anomaly and correlation coefficient techniques are used to analyze the data sets. The results revealed that the cases of heat waves that existed over the western and central Europe through the summer season of the year 2015 were controlled distinctly by the negative phase of the NAO and positive phase of ENSO.

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“…The city-specific level of human heat tolerance among urban populations has been investigated by studies that relate elevated ambient temperature or heat to mortality records of a city (Baccini et al 2008;Ballester et al 2011;Chung et al 2015;Gasparrini et al 2015). However, this information is very local, often provided in incomparable temperature metrics and determined by varying parameters.…”

Section: Heat Burden In Citiesmentioning

confidence: 99%