Literature DB >> 29238930

Modeling the impacts of ambient temperatures on cardiovascular mortality in Yinchuan: evidence from a northwestern city of China.

Huiling Zhang1, Qingan Wang1, Yajuan Zhang1, Yi Yang2, Yi Zhao1, Jianren Sang3, Yulong Zhang4, Yine Zhang2, Fan Xie2, Shanshan Li5, Yuhong Zhang6, Yuming Guo7.   

Abstract

No evidence is available on whether cardiovascular mortality is affected by the ambient temperatures in Yinchuan, which is located in the northwestern region of China, with a typical continental semi-humid semi-arid climate. Daily data on cardiovascular mortality and meteorological factors was collected from Yinchuan city for the period of 2010-2015. A distributed lag non-linear model with quasi-Poisson link was used to assess the association between daily temperatures and cardiovascular deaths, after controlling for seasonality, day of the week, atmospheric pressure, humidity, sunshine duration, and wind speed. The relationship between ambient temperature and cardiovascular mortality was non-linear, with a U-shaped exposure-response curve. For all cardiovascular mortality, the effects of high temperatures appeared at lag 2-5 days, with the largest hot effect at lag 3 day (RR 1.082, 95% CI 1.021-1.146), while the effects of cold temperatures were insignificant. Both cold and high temperatures have more serious influence on the elderly (age ≥ 65) and males than the youth and females, respectively. The study has shown that both cold and high temperatures affect cardiovascular mortality. The findings may be helpful to identify the susceptible subgroups of cardiovascular mortality induced by temperatures, and to provide useful information for establishing public health programs that would better protect local population health from ambient temperatures.

Entities:  

Keywords:  Ambient temperatures; Cardiovascular mortality; Distributed lag non-linear model; Northwestern China; Time-series

Mesh:

Year:  2017        PMID: 29238930     DOI: 10.1007/s11356-017-0920-3

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  25 in total

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4.  Distributed lag non-linear models.

Authors:  A Gasparrini; B Armstrong; M G Kenward
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Journal:  BMJ Open       Date:  2015-09-14       Impact factor: 2.692

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