Ma Pan, Wang Shigong, Zhou Ji, Li Tanshi, Fan Xingang, Fan Jin, Wang Siyi
Institute of Environmental Meteorology and Health, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, Sichuan, China.
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China.
Heliyon. 2020 May 30;6(5):e04034. doi: 10.1016/j.heliyon.2020.e04034. eCollection 2020 May.
The intricately fluctuating onset of respiratory and circulatory diseases displays rhythms of multi-scaled meteorological conditions due to their sensitivity to weather changes. The intrinsic meteorological rhythms of these diseases are revealed in this bio-meteorological study via Fourier decomposition and harmonic analysis. Daily emergency room (ER) visit data for respiratory and circulatory diseases from three comprehensive hospitals in Haidian district of Beijing, China were used in the analysis. Meteorological data included three temperature metrics, relative humidity, sunshine duration, daily mean air pressure, and wind speed. The Fourier decomposition and harmonic analysis on ER visits and meteorological variables involve frequency, period, and power of all harmonics. The results indicated that: i) for respiratory morbidity, a strong climatic annual rhythm responding to annual temperature change was firstly revealed; its ratio of spectral density was 16-33%. Moreover, significant correlations existed between the high-frequency fluctuations (<30 d) of morbidity and short-term harmonics of humidity and solar duration. High-frequency harmonics of temperature and pressure showed no statistically significant effect. ii) With regard to all types of circulatory morbidity, their annual periodicity was weaker than that of respiratory diseases, whose harmonic energy took a ratio less than 8%. Besides, the power of all high-frequency harmonics of circulatory morbidity accounted for up to 70-90% in the original sequences, and their relationship to many short-term meteorological factors were significant, including the mean and maximum temperatures, wind speed, and solar duration. iii) The weekly rhythm appeared in respiratory ER visits with 15% of harmonic variance but not prominent in circulatory morbidity. In summary, by decomposing the sequence of respiratory and circulatory diseases as well as recognizing their meteorological rhythms, different responses to meteorological conditions on various time scales were identified.
呼吸和循环系统疾病复杂多变的发病情况,由于对天气变化敏感,呈现出多尺度气象条件的节律。在这项生物气象学研究中,通过傅里叶分解和谐波分析揭示了这些疾病内在的气象节律。分析使用了中国北京市海淀区三家综合医院呼吸和循环系统疾病的每日急诊室就诊数据。气象数据包括三个温度指标、相对湿度、日照时长、日平均气压和风速。对急诊室就诊次数和气象变量进行的傅里叶分解和谐波分析涉及所有谐波的频率、周期和功率。结果表明:i)对于呼吸系统发病率,首次揭示了对年度温度变化有强烈气候年度节律响应;其谱密度比为16 - 33%。此外,发病率的高频波动(<30天)与湿度和日照时长的短期谐波之间存在显著相关性。温度和气压的高频谐波没有统计学上的显著影响。ii)关于所有类型的循环系统发病率,其年度周期性比呼吸系统疾病弱,谐波能量占比小于8%。此外,循环系统发病率所有高频谐波的功率在原始序列中占比高达70 - 90%,并且它们与许多短期气象因素的关系显著,包括平均温度和最高温度、风速和日照时长。iii)每周节律出现在呼吸急诊室就诊中,谐波方差为15%,但在循环系统发病率中不明显。总之,通过分解呼吸和循环系统疾病序列并识别其气象节律,确定了在不同时间尺度上对气象条件的不同响应。