A new method to estimate the temperature-CVD mortality relationship.

Area of Science:

• Environmental Health
• Cardiovascular Epidemiology
• Biostatistics

Background:

• Cardiovascular disease (CVD) mortality is a global health concern.
• The impact of temperature on CVD mortality requires detailed, population-specific investigation, particularly in diverse regions like China.
• Existing research lacks comprehensive analysis of temperature-CVD mortality relationships across various sociodemographic subgroups.

Purpose of the Study:

• To investigate the adverse health effects of temperature on cardiovascular disease (CVD) mortality in Beijing.
• To analyze the exposure-response relationships between temperature and CVD mortality for the general population and specific sociodemographic subgroups.
• To propose and apply a novel model (COCKTAIL) for understanding temperature-CVD mortality dynamics.

Main Methods:

• A distributed lag nonlinear model (DLNM) was employed to assess temperature-related CVD mortality.
• Analysis included all populations and stratified subgroups based on age, sex, education, living arrangement, and occupation.
• A new model, COCKTAIL (Code Of Climate Key To An Ill), was developed to reveal split-and-merge relationships in temperature-CVD mortality curves.

Main Results:

• Cold temperatures (e.g., -14°C) significantly elevated CVD mortality risk for individuals with low socioeconomic status, single individuals, indoor workers, and those with low education.
• Hot temperatures (e.g., 35°C) were associated with increased CVD mortality risk, particularly for females and single individuals.
• The study identified distinct vulnerability patterns to temperature extremes across different sociodemographic groups.

Conclusions:

• Temperature extremes pose a significant risk for cardiovascular disease mortality, with varying impacts across different population subgroups.
• Findings highlight the need for tailored public health interventions to mitigate temperature-related CVD deaths.
• The developed COCKTAIL model offers a novel approach for forecasting temperature-CVD mortality relationships and informing climate-health adaptation strategies.