Abstract

ABSTRACT Cardiovascular disease (CVD) is the leading cause of mortality worldwide, posing a significant threat to public health. Research on the relationship between CVD and temperature has primarily focused on developed urban settings, with limited studies conducted in rural regions with lower levels of development. Additionally, compared to relative risks, attributable risks can provide more information when assessing the risk of CVD hospitalizations associated with exposure to apparent temperature (AT). Apparent temperature is a composite temperature index that takes into account both meteorological factors and temperature, providing an objective reflection of human thermal sensation. Therefore, this study investigates the impact of AT on CVD hospitalization and quantifies the burden of CVD admission in the rural areas of China. We employed the distributed lag non-linear model (DLNM) to estimate the relationship between AT and the relative risk (RR) of CVD hospitalization. Finally, we used attributable risk methods to quantify this relationship further.

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