Impact of temperature on mortality in Hubei, China: a multi-county time series analysis

Abstract

We examined the impact of extreme temperatures on mortality in 12 counties across Hubei Province, central China, during 2009-2012. Quasi-Poisson generalized linear regression combined with distributed lag non-linear model was first applied to estimate county-specific relationship between temperature and mortality. A multivariable meta-analysis was then used to pool the estimates of county-specific mortality effects of extreme cold temperature (1st percentile) and hot temperature (99th percentile). An inverse J-shaped relationship was observed between temperature and mortality at the provincial level. Heat effect occurred immediately and persisted for 2-3 days, whereas cold effect was 1-2 days delayed and much longer lasting. Higher mortality risks were observed among females, the elderly aged over 75 years, persons dying outside the hospital and those with high education attainment, especially for cold effects. Our data revealed some slight differences in heat- and cold- related mortality effects on urban and rural residents. These findings may have important implications for developing locally-based preventive and intervention strategies to reduce temperature-related mortality, especially for those susceptible subpopulations. Also, urbanization should be considered as a potential influence factor when evaluating temperature-mortality association in future researches.

Figure 1

County-specific and pooled temperature-mortality relationships at lag 0–2 (A), lag 0–7 (B), lag 0–14 (C) and lag 0–21 (D). The continuous bold red lines represent the pooled curves and the blue areas are the 95% confidential intervals, whereas the long-dashed grey lines are the county-specific estimates. The reference temperature was 27.7 °C.

Figure 2. Lag patterns for pooled heat effect and cold effect on non-accidental mortality of the 12 counties in Hubei Province.

The bold red lines are the effect estimates and the blue areas represent the 95% confidential intervals.

Figure 3. Pooled mortality risks and their 95% confidential intervals of heat effect (lag 0–2) and cold effect (lag 0–21) for urban and rural counties across Hubei Province in China, stratified by gender, age, education attainment, and place of death.

Figure 4. Locations of the 12 selected counties in Hubei Province, China.

The maps were created using ArcGIS (Version 10.2, ESRI, http://www.esri.com/).