The effect of apparent temperature on hospital admissions for cardiovascular diseases in rural areas of Pingliang, China
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School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China
School of Management, Lanzhou University, Lanzhou 730000, China
Yiwen Tian   

School of Economics and Management, University of Technology, Lanzhou, China
Introduction and objective:
There is a well-reported association between temperature and the relative risk (RR) of cardiovascular disease (CVD) in urban areas in China. However, insufficient research has been performed in rural areas. The aim of the study was to analyze the association between apparent temperature (AT) and the RR of CVD hospital admissions in rural areas of Pingliang, northwest China.

Material and methods:
Daily data and weather conditions were collected in Pingliang from 2014–2015. The median value of AT was selected to estimate the RR of CVD, and the distributed lag nonlinear model (DLNM) used to examine the relationship between AT and the RR of CVD admissions for up to 21 days.

The results showed a nonlinear relationship between AT and the RR of CVD admissions. Regarding the heat effect, there was a protective effect. Meanwhile, the cold effect on the RR of CVD admissions appeared at day 0 and persisted until day 21, resulting in a cumulative RR of 2.304 (95%CI: 1.809–2.936) compared with the median value of AT, and the maximum RR appeared at about -5 °.The cumulative RR values of CVD on men and adults were more sensitive than those on women and elders in the cold effect.

AT is associated with the hospitalization of CVD patients. Both gender and age factors were associated with the increase in RR of CVD admissions. More preventive measures should be taken to avoid this adverse effect.

RR – relative risk; CVD – cardiovascular disease; AT – apparent temperature; DLNM – distributed lag nonlinear model; DTR – diurnal temperature range; NRCMS – New Rural Cooperative Medical Scheme; AIC – Akaike’s information criterion; CI – confidence Interval
The authors express their thanks to the National Natural Science Foundation of China [71861026], Gansu Natural Science Project ‘Knowledge-driven Meteorological Environment for Public Health Economic Loss Evaluation’ [20JR5RA474] and China Postdoctoral Science Foundation [2016M600827], who provided funds for the research.
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