Changing heat-related mortality in the United States.

Abstract

Heat is the primary weather-related cause of death in the United States. Increasing heat and humidity, at least partially related to anthropogenic climate change, suggest that a long-term increase in heat-related mortality could occur. We calculated the annual excess mortality on days when apparent temperatures--an index that combines air temperature and humidity--exceeded a threshold value for 28 major metropolitan areas in the United States from 1964 through 1998. Heat-related mortality rates declined significantly over time in 19 of the 28 cities. For the 28-city average, there were 41.0 +/- 4.8 (mean +/- SE) excess heat-related deaths per year (per standard million) in the 1960s and 1970s, 17.3 +/- 2.7 in the 1980s, and 10.5 +/- 2.0 in the 1990s. In the 1960s and 1970s, almost all study cities exhibited mortality significantly above normal on days with high apparent temperatures. During the 1980s, many cities, particularly those in the typically hot and humid southern United States, experienced no excess mortality. In the 1990s, this effect spread northward across interior cities. This systematic desensitization of the metropolitan populace to high heat and humidity over time can be attributed to a suite of technologic, infrastructural, and biophysical adaptations, including increased availability of air conditioning.

Differential and combined impacts of extreme temperatures and air pollution on human mortality in south–central Canada. Part II: future estimates

“…Across the study area, the nolag-time prediction model in the hot weather group was usually more significant than other lag-time models. This finding is consistent with that of previous studies (e.g., Dessai 2002;Rainham and Smoyer-Tomic 2003;Sheridan and Kalkstein 2004), although other studies identified a 1-or 2-day lag between the mortality response and a heat event (e.g., Rogot and Padgett 1976;Davis et al 2003). For the rest of the weather groups (e.g., pollution-related or cold), most of the prediction models were more significant with 1-day lag or no lag time between the deaths and the environmental factors.…”

“…In hot and cold weather groups, 15:00 local standard time (LST) temperature was used to sort the data from lowest to highest; then the days were put into ranking groups with a roughly equal number of days in each ranking group. The afternoon was chosen as the time to take the temperature reading because the analysis revealed this to be the time when the strongest relationships with elevated mortality exist; this finding is consistent with previous studies (e.g., Smoyer et al 1999;Davis et al 2003). In air pollutionrelated weather groups, an air pollutant was used to rank the data for that pollutant-related weather group; for example, O 3 was used to rank the data for O 3 -related weather group.…”

Effects of diurnal variations in temperature on non-accidental mortality among the elderly population of Montreal, Québec, 1984–2007

“…These "thresholds" are about 17-18°C in Northern and Central Europe, 22-23°C in Southern Europe, 25°C on the Eastern Coast of the United States, and 26-29°C in Australia and South-East Asia. The adverse effects of increased temperatures can be prolonged for many days (so-called lagged effects) (Braga and Zanobetti 2002;Conti et al 2005;Curriero et al 2002;Davis et al 2003a;Davis et al 2003b;Dessai 2002;Donaldson et al 2001;Donaldson et al 2003;Gosling et al 2007;Gouveia et al 2003;Hajat et al 2005;Huynen et al 2001;Keatinge et al 2000;Michelozzi et al 2005;O'Neill et al 2003;Paldy et al 2005;Pattenden et al 2003;Sartor et al 1995;Vandentorren et al 2004). In addition, there is evidence suggesting that colder than normal temperatures can increase mortality (Carson et al 2001;Doyon et al 2008;Goodwin 2007;Gouveia et al 2003;Kovats et al 1998;Martens 1998;McMichael et al 2006), although these effects appear to be delayed for as many as two weeks into the future (Braga and Zanobetti 2002;Gouveia et al 2003;Huynen et al 2001;Pattenden et al 2003).…”

Hospital admissions as a function of temperature, other weather phenomena and pollution levels in an urban setting in China

“…A smooth term with a maximum representing the MDT with a lag of 0 to 10 days (MDT (0-10) ) was used in the subsequent generalized additive model, along with smooth terms for MDRH with a lag of 0 to 10 days (MDRH (0-10) ), average DTGSR with the same lag period (DTGSR (0)(1)(2)(3)(4)(5)(6)(7)(8)(9)(10) ) and MDWS with the same lag period (MDWS (0-10) ). Same-day rainfall (square-root-transformed) was also included in all models based on the hypothesis that heavy rain would deter people from going to hospital.…”

“…[1][2][3][4][5][6][7][8][9] Although there is evidence of an association between outdoor temperature and mortality rates, the interplay between the two remains only partially understood in Asia because of a lack of databases with comprehensive, comparable data for most urban communities in low-and middle-income settings. 10,11 Evidence from European and American cities suggests that when outdoor temperatures are unusually high, there is a rise in hospital admissions 10,[12][13][14][15] for respiratory ailments, renal diseases, 12 and infectious diseases (both vector-borne and foodborne) and cerebrovascular accidents, including subarachnoid haemorrhage 13 and transient ischaemic attacks.…”