Dataset Information

Impacts of Temperature and its Variability on Mortality in New England.

ABSTRACT: Rapid buildup of greenhouse gases is expected to increase the Earth surface mean temperature, with unclear effects on temperature variability1-3. This adds urgency to better understand the direct effects of the changing climate on human health. However, the effects of prolonged exposures to temperatures, which are important for understanding the public health burden, are unclear. Here we demonstrate that long-term survival was significantly associated with both seasonal mean values and standard deviations (SDs) of temperature among the Medicare population (aged 65+) in New England, and break that down into long-term contrasts between ZIP codes and annual anomalies. A rise in summer mean temperature of 1 °C was associated with 1.0% higher death rate whereas an increase in winter mean temperature corresponded to 0.6% lower mortality. Increases in temperature SDs for both summer and winter were harmful. The increased mortality in warmer summers was entirely due to anomalies, while it was long term average differences in summer SD across ZIP codes that drove the increased risk. For future climate scenarios, seasonal mean temperatures may in part account for the public health burden, but excess public health risk of climate change may also stem from changes of within season temperature variability.

SUBMITTER: Shi L

PROVIDER: S-EPMC4666547 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Impacts of Temperature and its Variability on Mortality in New England.

Shi Liuhua L Kloog Itai I Zanobetti Antonella A Liu Pengfei P Schwartz Joel D JD

Nature climate change 20150713

Rapid buildup of greenhouse gases is expected to increase the Earth surface mean temperature, with unclear effects on temperature variability<sup>1-3</sup>. This adds urgency to better understand the direct effects of the changing climate on human health. However, the effects of prolonged exposures to temperatures, which are important for understanding the public health burden, are unclear. Here we demonstrate that long-term survival was significantly associated with both seasonal mean values an ...[more]

PMID: 26640524

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Project description:BackgroundThe evidence and method are limited for the associations between mortality and temperature variability (TV) within or between days.ObjectivesWe developed a novel method to calculate TV and investigated TV-mortality associations using a large multicountry data set.MethodsWe collected daily data for temperature and mortality from 372 locations in 12 countries/regions (Australia, Brazil, Canada, China, Japan, Moldova, South Korea, Spain, Taiwan, Thailand, the United Kingdom, and the United States). We calculated TV from the standard deviation of the minimum and maximum temperatures during the exposure days. Two-stage analyses were used to assess the relationship between TV and mortality. In the first stage, a Poisson regression model allowing over-dispersion was used to estimate the community-specific TV-mortality relationship, after controlling for potential confounders. In the second stage, a meta-analysis was used to pool the effect estimates within each country.ResultsThere was a significant association between TV and mortality in all countries, even after controlling for the effects of daily mean temperature. In stratified analyses, TV was still significantly associated with mortality in cold, hot, and moderate seasons. Mortality risks related to TV were higher in hot areas than in cold areas when using short TV exposures (0-1 days), whereas TV-related mortality risks were higher in moderate areas than in cold and hot areas when using longer TV exposures (0-7 days).ConclusionsThe results indicate that more attention should be paid to unstable weather conditions in order to protect health. These findings may have implications for developing public health policies to manage health risks of climate change.CitationGuo Y, Gasparrini A, Armstrong BG, Tawatsupa B, Tobias A, Lavigne E, Coelho MS, Pan X, Kim H, Hashizume M, Honda Y, Guo YL, Wu CF, Zanobetti A, Schwartz JD, Bell ML, Overcenco A, Punnasiri K, Li S, Tian L, Saldiva P, Williams G, Tong S. 2016. Temperature variability and mortality: a multi-country study. Environ Health Perspect 124:1554-1559; http://dx.doi.org/10.1289/EHP149.

Project description:BackgroundSeveral studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce.ObjectivesTo investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China.MethodsWe calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV.ResultsU-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment.SignificanceOur findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability.Impact(1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.

Project description:BackgroundSeasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality. Seasonal temperature and cohort analyses allow the long-term effects of regional climatic change on mortality to be analyzed.ObjectivesWe aimed to carry out one of the first investigations of seasonal temperature variability and mortality across the contiguous United States. We also investigated factors that modify this association. Using adapted quasi-experimental methods, we hoped to account for unobserved confounding and to investigate regional adaptation and acclimatization at the ZIP code level.MethodsWe examined the mean and standard deviation (SD) of daily temperature in the warm (April-September) and cold (October-March) season in the Medicare cohort from 2000 to 2016. This cohort comprised 622,427,230 y of person-time in all adults over the age of 65 y from 2000 to 2016. We used daily mean temperature obtained from gridMET to develop yearly seasonal temperature variables for each ZIP code. We used an adapted difference-in-difference approach model with a three-tiered clustering approach and meta-analysis to observe the relationship between temperature variability and mortality within ZIP codes. Effect modification was assessed with stratified analyses by race and population density.ResultsFor every 1°C increase in the SD of warm and cold season temperature, the mortality rate increased by 1.54% [95% confidence interval (CI): 0.73%, 2.15%] and 0.69% (95% CI: 0.22%, 1.15%) respectively. We did not see significant effects for seasonal mean temperatures. Participants who were classified by Medicare into an "other" race group had smaller effects than those classified as White for Cold and Cold SD and areas with lower population density had larger effects for Warm SD.DiscussionWarm and cold season temperature variability were significantly associated with increased mortality rates in U.S. individuals over the age of 65 y, even after controlling for seasonal temperature averages. Warm and cold season mean temperatures showed null effects on mortality. Cold SD had a larger effect size for those who were in the racial subgroup other, whereas Warm SD was more harmful for those living in lower population density areas. This study adds to the growing calls for urgent climate mitigation and environmental health adaptation and resiliency. https://doi.org/10.1289/EHP11588.

Dataset Information

Impacts of Temperature and its Variability on Mortality in New England.

Publications

Impacts of Temperature and its Variability on Mortality in New England.

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