Low climate-patterned temperature and cardiovascular disease: Worldwide trends and implications for public health policy.

Background: Short-term cold spells and heat events are commonly considered risk factors for cardiovascular disease (CVD). This study quantitatively examined the effects of country-specific "climate-patterned temperature" (T), measured as long-term mean temperature, on global CVD incidence.

Methods: Recently published country-specific data on CVD incidence and T were analysed for statistical correlations at the population level using Microsoft Excel and SPSS. Confounding effects of humidity, aging, GDP PPP, obesity prevalence, and urbanization were controlled. Fisher r-to-z transformation compared correlation coefficients.

Results: Pearson's r and nonparametric analyses revealed a significant inverse correlation between T and CVD incidence worldwide (r = -0.646 and -0.574, respectively, p < 0.001). This relationship remained significant after controlling for confounders in a partial correlation model (r = -0.584, p < 0.001). Multiple linear regression showed T as a significant and independent predictor of CVD incidence (Beta = -0.384, p < 0.001). Stepwise regression identified aging as the most influential factor (R = 0.591), with T and GDP PPP following, increasing R to 0.731 and 0.747, respectively. Humidity, obesity prevalence, and urbanization were not significant predictors. T had a stronger predictive effect on CVD incidence in high-income countries compared to low- and middle-income countries (z = 1.96 and 2.28 in Pearson's r and nonparametric models, respectively, p < 0.05).

Conclusions: Long-term lower mean temperature (T) is a significant and independent risk factor for CVD worldwide, particularly in developed countries. T should be considered in epidemiological studies of CVD.