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. 2011 Dec;119(12):1719-25.
doi: 10.1289/ehp.1103598. Epub 2011 Aug 9.

The impact of temperature on mortality in Tianjin, China: a case-crossover design with a distributed lag nonlinear model

Yuming Guo  1 , Adrian G Barnett, Xiaochuan Pan, Weiwei Yu, Shilu Tong
Affiliations

The impact of temperature on mortality in Tianjin, China: a case-crossover design with a distributed lag nonlinear model

Yuming Guo et al. Environ Health Perspect. 2011 Dec.

Abstract

Background: Although interest in assessing the impacts of temperature on mortality has increased, few studies have used a case-crossover design to examine nonlinear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China or on what temperature measure is the best predictor of mortality.

Objectives: Our objectives were to use a distributed lag nonlinear model (DLNM) as a part of case-crossover design to examine the nonlinear and distributed lag effects of temperature on mortality in Tianjin, China and to explore which temperature measure is the best predictor of mortality.

Methods: We applied the DLNM to a case-crossover design to assess the nonlinear and delayed effects of temperatures (maximum, mean, and minimum) on deaths (nonaccidental, cardiopulmonary, cardiovascular, and respiratory).

Results: A U-shaped relationship was found consistently between temperature and mortality. Cold effects (i.e., significantly increased mortality associated with low temperatures) were delayed by 3 days and persisted for 10 days. Hot effects (i.e., significantly increased mortality associated with high temperatures) were acute and lasted for 3 days and were followed by mortality displacement for nonaccidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature.

Conclusions: In Tianjin, extreme cold and hot temperatures increased the risk of mortality. The effects of cold last longer than the effects of heat. Combining the DLNM and the case-crossover design allows the case-crossover design to flexibly estimate the nonlinear and delayed effects of temperature (or air pollution) while controlling for season.

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Conflict of interest statement

The authors declare they have no actual or potential competing financial interests.

Figures

Figure 1
Figure 1
Relative risks of mortality types by mean temperature (°C), using a natural cubic spline–natural cubic spline DLNM with 5 df natural cubic spline for temperature and 4 df for lag. (A) Nonaccidental, (B) cardiopulmonary, (C) cardiovascular, and (D) respiratory mortality.
Figure 2
Figure 2
The estimated overall effects of mean temperature (°C) over 28 days on mortality types, using a natural cubic spline–natural cubic spline DLNM with 5 df natural cubic spline for temperature and 4 df for lag. (A) Nonaccidental, (B) cardiopulmonary, (C) cardiovascular, and (D) respiratory mortality. The black lines are the mean relative risks, and the blue regions are 95% CIs.
Figure 3
Figure 3
The estimated effects of a 1°C decrease in mean temperature below the cold threshold (left) and of a 1°C increase in mean temperature above the hot threshold (right) on mortality types over 27 days of lag, using a double threshold–natural cubic spline DLNM with 4 df natural cubic spline for lag. (A) Nonaccidental, (B) cardiopulmonary, (C) cardiovascular, and (D) respiratory mortality. The black lines are mean relative risks, and blue regions are 95% CIs. The cold and hot thresholds were 0.8°C and 24.9°C for nonaccidental mortality (A), 0.1°C and 25.3°C for cardiopulmonary mortality (B), 0.6°C and 25.1°C for cardiovascular mortality (C), 0.7°C and 24.8°C for respiratory mortality (D).
Figure 4
Figure 4
Comparison of the impacts of temperature on nonaccidental mortality in different populations ordered by latitude.
See this image and copyright information in PMC

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