| Literature DB >> 33932207 |
Fengliu Feng1, Yuxia Ma2, Yifan Zhang1, Jiahui Shen1, Hang Wang1, Bowen Cheng1, Haoran Jiao1.
Abstract
Under the global climate warming, extreme weather events occur more and more frequently. Epidemiological studies have proved that extreme temperature is strongly correlated with respiratory diseases. We evaluated extreme-temperature effect on respiratory emergency room (ER) visits for 5 years in Lanzhou, a northwest temperate climate city of China from January 1st, 2013, to August 31st, 2017. We built a distributed lag non-linear model (DLNM) to evaluate the lag effect up to 30 days. Results showed the relative risk (RR) of respiratory disease always reached the maximum at lag 0 day and decreased to 1.0 at lag 5 days. Extremely low temperature showed the lag effect of 22 days and the maximum RR was 1.415 (95% CI 1.295-1.546) at lag 0 day. Extremely high temperature showed the lag effect of 7 days and the maximum RR was 1.091 (95% CI 1.069-1.114) at lag 0 day. The elders (age > 65 years) were at the greatest risk to extreme temperatures and the response were very acute. Children (age ≤ 15 years) were at the lowest risk but the lag effect lasted the longest lag days than other subgroups. Males showed longer-term lag effect and higher RR than females. Our study indicated that the extremely low temperature has a significantly greater effect on respiratory diseases than extremely high temperature.Entities:
Keywords: Distributed lag linear and non-linear models; Extreme temperature; Respiratory diseases
Year: 2021 PMID: 33932207 DOI: 10.1007/s11356-021-14169-x
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 4.223