Objective: To quantitatively evaluate the effects of daily mean temperature on respiratory diseases.
Methods: Based on the data of daily hospital admissions for respiratory diseases, meteorological parameters and air pollution in Shanghai between January 2006 and December 2011, we used a generalized additive model (GAM) to explore the effects of daily mean temperature on hospital admissions on respiratory diseases adjusted for the secular trend, seasonal trend, day of week and other confounders.
Results: A J-shaped relationship was found between daily mean temperature and respiratory disease and the optimum temperature (OT) corresponding to low risk of respiratory hospital admissions was about 25 °C. For cold effects over lag 0-30 days, the overall excess risk (ER) of hospital admission associated with 1 °C below the OT was 3.00% (95% CI: 2.54%-3.45%), 3.00% (95% CI: 2.55%-3.45%) and 3.02% (95% CI:2.51%-3.49%) for overall, males and females, respectively. For hot effects over lag 0-30 days, the overall excess risk (ER) was 2.15% (95% CI: 0.67%-3.66%), 1.86% (95% CI: 0.39%-3.34%) and 2.57% (95% CI: 0.82%-4.36%) for overall, males and females, respectively. The optimum temperature between daily mean temperature and respiratory disease were 14 °C, 20 °C, 25 °C and 28 °C in different age groups. The effect of low temperature increased with age for the people above 45 years old; however the effect of high temperature was significant for the people under 65 years old.
Conclusions: Both of higher temperature and lower temperature resulted in ER of respiratory hospital admissions increase with lag effects. The effects of lower temperature lagged longer and stronger than higher temperature. Different age group and gender shows different effects.