Abstract

BackgroundMost studies examining the short-term effects of temperature on health were based on the daily scale, few were at the hourly level. Revealing the relationship between unfavorable temperatures on an hourly basis and health is conducive to the development of more accurate extreme temperature early warning systems and reasonable dispatch of ambulances. MethodsHourly data on temperature, air pollution (including PM2.5, O3, SO2 and NO2) and emergency ambulance calls (EACs) for all-cause, cardiovascular and respiratory diseases from January 16, 2014 to December 31, 2016 were obtained from Luoyang, China. A distributed lag non-linear model (DLNM) was used to assess the association between hourly temperature and ambulance calls after adjusting for potential confounding factors. The fractions of EACs attributable to non-optimum temperatures were also estimated. ResultsHourly temperature was associated with increased ambulance calls with a varying lag pattern. Extreme hot temperature (>32.1 °C) was positively associated with all-cause, cardiovascular diseases at lag 0–30 h and lag 0–9 h, while no significant effects were found for respiratory morbidity. Extreme cold temperature (<−2.5 °C) was positively associated with all-cause, cardiovascular and respiratory morbidity at lag 56–157 h, 50–145 h and 123–170 h. An overall EACs fraction of 6.84% [Backward estimate, 95% confidence interval (CI): 5.01%, 8.59%] could be attributed to non-optimum temperatures, and more contributions were caused by cold [Backward estimate: 6.06% (95% CI: 5.10%, 8.48%)] than by heat [Backward estimate: 0.79% (95% CI: 0.12%, 1.45%)]. ConclusionsExtreme hot temperature may lead to increased ambulance calls within a few hours, while extreme cold temperature may not increase ambulance calls until more than 2 days later. Effective measures, such as forming hourly temperature warning standards, optimizing ambulance services at extreme temperatures, etc., should be taken to reduce the unfavorable temperature - associated EACs burden.

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