Temperature and Mortality in 11 Cities of the Eastern United States

Abstract

Episodes of extremely hot or cold temperatures are associated with increased mortality. Time-series analyses show an association between temperature and mortality across a range of less extreme temperatures. In this paper, the authors describe the temperature-mortality association for 11 large eastern US cities in 1973-1994 by estimating the relative risks of mortality using log-linear regression analysis for time-series data and by exploring city characteristics associated with variations in this temperature-mortality relation. Current and recent days' temperatures were the weather components most strongly predictive of mortality, and mortality risk generally decreased as temperature increased from the coldest days to a certain threshold temperature, which varied by latitude, above which mortality risk increased as temperature increased. The authors also found a strong association of the temperature-mortality relation with latitude, with a greater effect of colder temperatures on mortality risk in more-southern cities and of warmer temperatures in more-northern cities. The percentage of households with air conditioners in the south and heaters in the north, which serve as indicators of socioeconomic status of the city population, also predicted weather-related mortality. The model developed in this analysis is potentially useful for projecting the consequences of climate-change scenarios and offering insights into susceptibility to the adverse effects of weather.

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

“…Numerous studies have been conducted to investigate the short-term effects of changes in ambient temperature on mortality, and various study designs have been used to characterize or quantify the relationships, including time series (Curriero et al 2002;Goldberg et al 2011;Hajat et al 2005;Hajat et al 2002;Huynen et al 2001;LeTertre et al 2006;Saez et al 2000) and related case-crossover designs (Bell et al 2008;Stafoggia et al 2008;Stafoggia et al 2006). The objectives of these studies were related to answering questions regarding triggering mechanisms, such as "Do the number of adverse health events increase when temperature increases or decreases?…”

“…Time series studies have been used to assess the effects of heat-and cold-waves on human mortality in single or multiple locations (Braga et al 2001;Curriero et al 2002;Hajat et al 2002;LeTertre et al 2006;Saez et al 1995). More often than not, grouped population data on a health outcome, such as non-accidental mortality, are obtained in a specific geographical region over a specific period of time.…”

“…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).…”

“…A total of 12 papers fulfilled these criteria, of which nine provided quantitative results (Ballester et al 1997;Braga and Zanobetti 2002;Curriero et al 2002;Gemmell et al 2000;Hajat et al 2005;Hajat et al 2002;Huynen et al 2001;Pattenden et al 2003;Saez et al 2000) and three more addressed the same relationship but in the context of a heat wave (LeTertre et al 2006;Rooney et al 1998;Sartor et al 1995). All of the selected studies used the time series design.…”

Exploring the effects of high temperature on mortality in four cities in the Philippines using various heat wave definitions in different mortality subgroups

“…Globally, numerous studies have reported that the temperature-mortality relationship tends to follow U-, V-, and J-shaped non-linear patterns, whereby risks in the extreme ends constitute higher risks relative to the minimum mortality temperature (MMT) [1–5]. These extreme temperatures account for greater risks, and to a certain extent, when analyzed separately, in relation to duration and intensity, which are the length of day and threshold temperature, respectively, constitute the notion of heat waves (HW) [6–10].…”