Impact of temperature changes between neighboring days on COPD in a city in Northeast China
2020
Ma, Yuxia | Jiao, Haoran | Zhang, Yifan | Cheng, Bowen | Feng, Fengliu | Yu, Zhiang | Ma, Bingji
Sudden temperature changes between neighboring days (T₂₄ₕ) have adverse effects on human health. In this study, we used a time series analysis to evaluate the impact of T₂₄ₕ on the number of hospital admissions for chronic obstructive pulmonary disease (COPD) from 2009 to 2012 in Changchun (the capital of Northeast China’s Jilin province). We performed the analysis in a generalized additive model (GAM), and the controlling factors included long-term trends, day of the week effect, and the selected weather elements. We divided the entire study group into two gender subgroups (males and females) and two age subgroups (aged < 65 years and aged ≥ 65 years). T₂₄ₕ showed the greatest effect on the entire study group at lag 3 days. In particular, the greatest effect of T₂₄ₕ on females (males) occurred at lag 1 day (lag 3 days); the greatest effect of T₂₄ₕ on the aged ≥ 65 years (aged < 65 years) occurred at lag 1 day (lag 6 days). This indicates that temperature changes between neighboring days have a relatively more acute effect on the elderly and the females than on the younger people and the males. When T₂₄ₕ is less than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 4 days during the warm season (1.025, 95% CI: 0.981, 1.069) and lag 3 days during the cold season (1.019, 95% CI: 0.988, 1.051). When T₂₄ₕ is greater than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 6 days during the warm season (1.026, 95% CI: 0.977, 1.077) and lag 5 days during the cold season (1.021, 95% CI: 0.986, 1.057). The results of this study could be provided to local health authorities as scientific guidelines for controlling and preventing COPD in Changchun, China.
显示更多 [+] 显示较少 [-]