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<p>Climate change has increased the frequency and intensity of extreme temperature events, adversely impacting human health and mortality. This study examines daily all-cause mortality concerning daily maximum and minimum temperature over a six-year period (2010–2015) in Chandigarh, India. Using an over-dispersed Poisson Generalized Additive Model (GAM), with visibility as a surrogate for other meteorological factors, we found a strong model fit (R<sup>2</sup> = 0.996; <i>P</i> &lt; 0.05). Our results show a significant increase in all-cause mortality during heatwave conditions. A moderately positive association between temperature and mortality was observed in summer (R<sup>2</sup> 0.014 in May; R<sup>2</sup> = 0.133 in June; <i>p</i> &lt; 0.05), while a negative association was found in winter (r = −0.155 in December; r =  − 0.141 in January; <i>p</i> &lt; 0.05). A critical temperature threshold of 33.8&#xa0;°C (<i>p</i> = 0.0007) was identified, above which mortality significantly increases, although the effect size remains modest. Mortality risk was found to be elevated during heatwaves, with similar risk levels observed for both males and females. These findings highlight the need for targeted interventions and adaptation strategies to reduce temperature-related mortality, particularly in vulnerable populations exposed to extreme weather conditions.</p>

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Extreme temperature events and their relationship with excess all-cause mortality in Chandigarh, India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Ravindra Khaiwal,
  • Prachi Chauhan,
  • Sanjeev Bhardwaj,
  • Abhishek Kumar,
  • Suman Mor

摘要

Climate change has increased the frequency and intensity of extreme temperature events, adversely impacting human health and mortality. This study examines daily all-cause mortality concerning daily maximum and minimum temperature over a six-year period (2010–2015) in Chandigarh, India. Using an over-dispersed Poisson Generalized Additive Model (GAM), with visibility as a surrogate for other meteorological factors, we found a strong model fit (R2 = 0.996; P < 0.05). Our results show a significant increase in all-cause mortality during heatwave conditions. A moderately positive association between temperature and mortality was observed in summer (R2 0.014 in May; R2 = 0.133 in June; p < 0.05), while a negative association was found in winter (r = −0.155 in December; r =  − 0.141 in January; p < 0.05). A critical temperature threshold of 33.8 °C (p = 0.0007) was identified, above which mortality significantly increases, although the effect size remains modest. Mortality risk was found to be elevated during heatwaves, with similar risk levels observed for both males and females. These findings highlight the need for targeted interventions and adaptation strategies to reduce temperature-related mortality, particularly in vulnerable populations exposed to extreme weather conditions.