Mortality risk attributable to high and low ambient temperature: a multicountry observational study

Abstract

SummaryBackgroundAlthough studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures.MethodsWe collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature–mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles.FindingsWe analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43–7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80–90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02–7·49) than by heat (0·42%, 0·39–0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84–0·87) of total mortality.InterpretationMost of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios.FundingUK Medical Research Council.

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].…”

Cardiopulmonary Mortality and Temperature

“…As was already mentioned, this study used a set of R routines developed and presented by other authors and accompanied to their published papers [1][2]. The analysis is done with R software (version 3.2.4) using the packages dlnm and mvmeta [1][2].…”

“…The analysis is done with R software (version 3.2.4) using the packages dlnm and mvmeta [1][2]. The corresponding codes used in this analysis, were retrieved from the personal website [5] of the first author of the publications [1][2].…”

“…This work is a kind of review study -it uses existing software accompanying two published papers on the mortality and temperature [1][2]. As an alternative input data for this software, Canadian data on mortality and temperature in 20 locations are used.…”

How can ecological urbanism promote human health?

“…According to the results, the temperature is responsible for increasing a considerable proportion of deaths to 7.71% (95% CI 7.43-7.91). Nevertheless, there are significant inter-country variations in attributable risk (for both hot and cold), with the uppermost attributable risk in Italy, China, and Japan and the lowermost estimates in Thailand, Brazil, and Sweden (Gasparrini et al, 2015).…”