Both low and high temperature may increase the risk of stroke mortality

Abstract

Objective: To examine temperature in relation to stroke mortality in a multicity time series study in China.

Methods: We obtained data on daily temperature and mortality from 8 large cities in China. We used quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on stroke mortality across multiple days, adjusting for long-term and seasonal trends, day of the week, air pollution, and relative humidity. We applied the Bayesian hierarchical model to pool city-specific effect estimates.

Results: Both cold and hot temperatures were associated with increased risk of stroke mortality. The potential effect of cold temperature might last more than 2 weeks. The pooled relative risks of extreme cold (first percentile of temperature) and cold (10th percentile of temperature) temperatures over lags 0-14 days were 1.39 (95% posterior intervals [PI] 1.18-1.64) and 1.11 (95% PI 1.06-1.17), compared with the 25th percentile of temperature. In contrast, the effect of hot temperature was more immediate. The relative risks of stroke mortality over lags 0-3 days were 1.06 (95% PI 1.02-1.10) for extreme hot temperature (99th percentile of temperature) and 1.14 (95% PI 1.05-1.24) for hot temperature (90th percentile of temperature), compared with the 75th percentile of temperature.

Conclusions: This study showed that both cold and hot temperatures were associated with increased risk of stroke mortality in China. Our findings may have important implications for stroke prevention in China.

Figure 1. Map of cities in this study

Figure 2. Nonlinear relationships between outdoor temperature and daily stroke mortality in 8 Chinese cities

The associations were presented as relative risks of the full range of temperature with lags of 0–14 days compared to the minimum-mortality temperature. The black lines are the central effect estimates and the gray areas are the 95% intervals.

Figure 3. City-specific relative risks of stroke mortality for extreme cold, cold, hot, and extreme hot temperatures

The dots are for the central effect estimates and the horizontal lines represent the 95% intervals. Extreme cold was defined as first percentile of temperature and cold as 10th percentile, both compared with the 25th percentile of temperature over lag 0–14 days. Extreme hot was defined as 99th percentile of temperature and hot as 90th percentile, both compared with the 75th percentile of temperature over lag 0–3 days. RR = relative risk.