Dataset Information

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017.

ABSTRACT:

Background

Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection.

Methods

We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987-2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987-2002 and 2003-2017 to evaluate temporal heterogeneity.

Findings

The model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003-2017 to 1987-2002.

Interpretation

The analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.

SUBMITTER: Wei Y

PROVIDER: S-EPMC8169607 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Publications

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017.

Wei Yaguang Y Tiwari Abhiyant Suresh AS Li Longxiang L Solanki Bhavin B Sarkar Jayanta J Mavalankar Dileep D Schwartz Joel J

Environmental research 20210511

<h4>Background</h4>Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection.<h4>Methods</h4>We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987-2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics ...[more]

PMID: 33965390

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Project description:BackgroundAlthough 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.

Project description:ObjectiveTo examine the total non-accidental mortality burden attributable to ambient temperatures and assess the effect modification of the burden by specific causes of death and individual characteristics in a high plateau area in southwest China.MethodsUsing daily mortality and meteorological data from 2009 to 2016, we applied a quasi-Poisson model combined with a distributed lag non-linear model to estimate the temperature-mortality association with the assessment of attributable fraction and number. We calculated attributable fractions and deaths with 95% empirical CIs (eCIs), that were due to cold and heat, defined as temperatures below and above the median temperature, and for mild and extreme temperatures, defined by cut-offs at the 2.5th and 97.5th temperature percentiles.ResultsWe analysed 89 467 non-accidental deaths; 4131 were attributable to overall temperatures, with an attributable fraction of 4.75% (95% eCI 2.33% to 6.79%). Most of the mortality burden was caused by cold (4.08%; 0.86% to 7.12%), whereas the burden due to heat was low and non-significant (0.67%; -2.44% to 3.64%). Extreme cold (1.17%; 0.58% to 1.69%) was responsible for 24.6% (ie, 1.17% divided by 4.75%) of the total death burden. In the stratification analyses, attributable risk due to cold was higher for cardiovascular than respiratory disease (6.18% vs 3.50%). We found a trend of risk of increased death due to ambient temperatures with increasing age, with attributable fractions of 1.83%, 2.27% and 6.87% for age ≤64, 65-74 and ≥75 years old, respectively. The cold-related burden was slightly greater for females, farmers, ethnic minorities and non-married individuals than their corresponding categories.ConclusionsMost of the burden of death was attributable to cold, and specific causes and individual characteristics might modify the mortality burden attributable to ambient temperatures. The results may help make preventive measures to confront climate change for susceptible population in this region.

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Project description:BackgroundNon-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.MethodsThe global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.FindingsWe estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.InterpretationA substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.FundingNational Key Research and Development Program.

Project description:BackgroundSolid organ transplant recipients have an elevated risk of cancer. Quantifying deaths attributable to cancer can inform priorities to reduce cancer burden.MethodsLinked transplantation and cancer registry data were used to identify incident cancers and deaths among solid organ transplant recipients in the United States (1987-2014). Population-attributable fractions (PAFs) of deaths due to cancer and corresponding cancer-attributable mortality rates were estimated using Cox models.ResultsAmong 221,962 solid organ transplant recipients, 15,012 developed cancer. Approximately 13% of deaths (PAF, 13.2%) were attributable to cancer, corresponding to a cancer-attributable mortality rate of 516 per 100,000 person-years. Lung cancer was the largest contributor to mortality (PAF, 3.1%), followed by non-Hodgkin lymphoma (NHL; PAF, 1.9%), colorectal cancer (PAF, 0.7%), and kidney cancer (PAF, 0.5%). Cancer-attributable mortality rates increased with age at transplantation, reaching 1229 per 100,000 person-years among recipients aged ≥65 years. NHL was the largest contributor among children (PAF, 4.1%) and lung cancer was the largest contributor among recipients aged ≥50 years (PAFs, 3.7%-4.3%). Heart recipients had the highest PAF (16.4%), but lung recipients had the highest cancer-attributable mortality rate (1241 per 100,000 person-years). Overall, mortality attributable to cancer increased steadily with longer time since transplantation, reaching 15.7% of deaths (810 per 100,000 person-years) at ≥10 years after transplantation. Comparison of cancer-attributable mortality rates with specified causes of death indicated that some deaths recorded as other causes might instead be caused by cancer or its treatment.ConclusionsCancer is a substantial cause of mortality among solid organ transplant recipients, with major contributions reported from lung cancer and NHL. Cancer-attributable mortality increases with age and time since transplantation, and therefore cancer deaths will become an increasing burden as recipients live longer.

Dataset Information

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017.

Background

Methods

Findings

Interpretation

Publications

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017.

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