DOI: 10.5176/2251-3833_GHC14.02

Authors: Yue Zhang, Haidong Kan, Shengnan Wang, Weibing Wang


Abstract: Objective: To evaluate the short-term effects of daily mean temperature on respiratory hospital admissions in Shanghai.
Methods: After controlling secular trend, seasonal trend, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) was used to examine the associations between daily mean temperature and cause-specific respiratory hospital admissions from 2006 to 2011 in Shanghai. We examined the effects of daily mean temperature for stratified groups by gender and used a moving average lag model to evaluate the lag effects of temperature on hospital admissions.
Results: Significant associations were between daily mean temperature and cause-specific respiratory hospital admissions across different gender groups, whereas both cold and hot temperatures resulted in the excess risk (ER) of hospital admissions increase. For cold effects over lag0~30 days, the overall excess risk (ER) of hospital admission associated with 1℃ below the OT (the optimum temperature) was 3.00{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 2.54{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~3.45{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}), 4.05{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 3.44{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~4.65{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}) and 4.73{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 4.26{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~5.19{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}) for respiratory, pneumonia and COPD, respectively. For hot effects over lag0~30 days, the overall excess risk (ER) was 2.15{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 0.67{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~3.66{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}) and 2.61{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 1.16{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~4.09{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}) for respiratory disease and pneumonia, but at lag0~3 days, the overall excess risk (ER) was 2.67{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} (95{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}CI: 0.30{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}~4.97{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465}) for COPD. For cold effects, females had a higher risk for cause-specific respiratory hospital admissions, however, for hot effects, the higher risk was found among males for pneumonia and COPD, with the exception of respiratory hospital admissions.
Conclusions: This study demonstrated that both of higher temperature and lower temperature may have impacts on cause-specific respiratory hospital admissions. The effects of lower temperature lagged longer and stronger than higher temperature. Different gender groups have different effects. The study provides useful findings for policy makers that some prevention programs to manage the impact of high and cold temperature on population health.

Keywords: daily mean temperature, respiratory hospital admission, generalized additive model

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