The effects of temperature variability on ischemic heart disease mortality in Hangzhou, China

Abstract

Abstract Ischemic heart disease (IHD) is a leading cause of death in cardiovascular patients. In China, the disease burden of IHD deaths has significantly increased. One of the main influencing factors of IHD is changing climates, and temperature and diurnal temperature range (DTR) are important indicators of climate change. In this study, we aimed to assess the associations of temperature variability on IHD mortality in a fast developing city Hangzhou,China. We obtained daily IHD mortality data and meteorological data from mortality surveillance system from 2014 to 2016. Quasi-Poisson generalized linear regression with a distributed lag non-linear model (DLNM) was applied to estimate the associations between temperature variability and IHD deaths. Potential confounders were controlled in the analysis, including relative humidity, day of the week, public holidays, and long-term trends. A total of 7423 IHD mortality data were included in this study. A J-shaped pattern of DTR and a reversely J-shaped pattern of temperature for IHD mortality were observed. Risk estimates showed that the relative risks (RRs) of IHD mortality with extreme high DTR at lag 0–7 days were 1.309 (95% CI: 0.985, 1.740) while RRs of IHD mortality with extreme low DTR at lag 0–2 days were 1.234 (95% CI: 1.043, 1.460). For extreme hot temperature, the highest RRs at lag 0–2 days were 1.559 (95% CI: 1.250, 1.943); for extremely cold temperatures, the RRs increased from 1.049 (95% CI: 0.930, 1.183) to 2.089 (95% CI: 1.854, 2.352). In Hangzhou city, short-term exposure to extreme temperature was associated with mortality for IHD. These findings have implications for policy decision-making and targeted interventions.

Keywords

• Temperature
• Ischemic heart disease
• Mortality
• Distributed lag non-linear model