Attributing mortality from temperature extremes: A time series analysis in Varanasi, India

Area of Science:

• Environmental Health
• Climatology
• Epidemiology

Background:

• Climate extremes, such as temperature variations, are increasingly linked to human mortality.
• Understanding these associations is crucial for public health interventions, especially in vulnerable regions like Varanasi, India.
• Previous studies highlight spatial and temporal variations in the impact of climate on mortality.

Purpose of the Study:

• To systematically investigate the effects of temperature extremes, daily means, and diurnal temperature variations (DTV) on all-cause mortality in Varanasi, India.
• To analyze mortality data from 2009-2016 in relation to meteorological and air quality parameters.
• To explore potential effect modifications by age, gender, and place of death.

Main Methods:

• Utilized time series data on daily mortality, air quality (SO2, NO2, O3, PM10), and weather variables.
• Employed a semiparametric quasi-Poisson regression model to estimate temperature effects on mortality.
• Adjusted for nonlinear confounding effects of time trends, relative humidity, and air pollution; stratified analyses by season were performed.

Main Results:

• Daily mean temperature showed a strong association with excess mortality in both summer and winter.
• Heat waves significantly increased daily mortality by 12.02%.
• Diurnal temperature variations (DTV) exhibited a downward trend and a negative association with all-cause mortality.

Conclusions:

• Significant associations between temperature extremes and mortality, coupled with decreasing DTV, indicate a clear impact of climate change on public health in Varanasi.
• Findings underscore the need for government policies to mitigate climate change factors and develop early warning systems.
• The study provides valuable insights for public health planning and climate change adaptation strategies in urban India.