Modelling the relationship between extreme temperature metrics and cardiovascular disease burden in India: Insights from a multi-state study on climate change challenges for 2011–2019

IF 1.7 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Clinical Epidemiology and Global Health Pub Date : 2025-06-03 DOI:10.1016/j.cegh.2025.102084

Soundarya Soundararajan , Bhavani Shankara Bagepally , Jhalak Dhingra , Meghna P. Dinesh , K. Nimithamohan , Rakesh Balachandar

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Abstract

Background

Climate change, particularly the rise in global temperatures, has significantly increased the burden of cardiovascular disease (CVD).

Objective

The objective of this study is to investigate the CVD-burden attributable to temperature variations within the context of India's diverse climate conditions from 2011 to 2019.

Methods

2-m temperature data from the ERA5 dataset is used for estimating temperature metrics—average, median, mode, minimum, maximum, and variations. From the state-level temperature metrics, 2.5th and 97.5th percentiles are identified as extremes. CVD-burden data per 100,000 population, are sourced from the Global Burden of Disease study. The relationship between the temperature predictors and CVD burden is estimated using Poisson panel regression, followed by estimation of incidence rate ratios by exponentiation of coefficients.

Results

A unit increase in average temperature increased the CVD-burden by ∼2.5 %. The 97.5th percentile consistently showed strong association with CVD-burden indices. The population attributable fraction for CVD mortality due to elevated average temperatures in India during the study period was estimated as 3.3 %.

Significance

These findings reinforce existing research and underscore the impact of temperature variations on the CVD-burden, highlighting the need for public health interventions to mitigate the effects of temperature on cardiovascular health.

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印度极端温度指标与心血管疾病负担之间的关系建模：来自2011-2019年气候变化挑战的多州研究的见解

气候变化，特别是全球气温上升，显著增加了心血管疾病（CVD）的负担。本研究的目的是调查2011年至2019年印度不同气候条件下温度变化导致的cvd负担。方法利用ERA5数据集的2-m温度数据估算温度指标——平均值、中位数、模态、最小值、最大值和变化。从州一级的温度指标来看，2.5和97.5%被确定为极端。每10万人的心血管疾病负担数据来源于全球疾病负担研究。利用泊松面板回归估计温度预测因子与心血管疾病负担之间的关系，然后通过系数的指数估计发病率比。结果平均温度每升高1个单位，cvd负荷增加~ 2.5%。97.5%与cvd负担指数一致显示出强相关性。在研究期间，印度平均气温升高导致的心血管疾病死亡率的人口归因比例估计为3.3%。这些发现加强了现有的研究，强调了温度变化对心血管疾病负担的影响，强调了采取公共卫生干预措施以减轻温度对心血管健康的影响的必要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Epidemiology and Global Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

4.60

自引率

7.70%

发文量

218

审稿时长

66 days

期刊介绍： Clinical Epidemiology and Global Health (CEGH) is a multidisciplinary journal and it is published four times (March, June, September, December) a year. The mandate of CEGH is to promote articles on clinical epidemiology with focus on developing countries in the context of global health. We also accept articles from other countries. It publishes original research work across all disciplines of medicine and allied sciences, related to clinical epidemiology and global health. The journal publishes Original articles, Review articles, Evidence Summaries, Letters to the Editor. All articles published in CEGH are peer-reviewed and published online for immediate access and citation.