Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 May 30;6(5):e04034.
doi: 10.1016/j.heliyon.2020.e04034. eCollection 2020 May.

Meteorological rhythms of respiratory and circulatory diseases revealed by Harmonic Analysis

Pan Ma  1   2 , Shigong Wang  1 , Ji Zhou  3 , Tanshi Li  4 , Xingang Fan  5   6 , Jin Fan  1 , Siyi Wang  1
Affiliations

Meteorological rhythms of respiratory and circulatory diseases revealed by Harmonic Analysis

Pan Ma et al. Heliyon. .

Abstract

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.

Keywords: Chronic disease; Circulatory system; Climatic cycle; Climatology; Environmental health; Environmental science; Epidemiology; Fourier decomposition; Harmonic spectrum; Meteorology; Respiratory system; Short-term weather.

PubMed Disclaimer

Figures

Figure 1
Figure 1
The time-series of daily ER visits for (A) the total respiratory diseases and (B) the total circulatory diseases in Beijing.
Figure 2
Figure 2
The harmonic power spectrum of the total respiratory diseases, which showed in ratio (%) of partitioned or single harmonic energy to the total energy.
Figure 3
Figure 3
The harmonic power spectrum of the total circulatory diseases, showed in ratio (%) of partitioned or single harmonic energy to its total energy.
Figure 4
Figure 4
The (A) annual periods, (B) superimposed non-annual low-frequency harmonics (>30 d), and (C) the remaining numerous high-frequency waves for the pretreated series of respiratory ER visits.
Figure 5
Figure 5
The (A) annual periods, (B) superimposed non-annual low-frequency harmonics, and (C) the remaining numerous high-frequency waves for the pretreated series of circulatory ER visits.
Figure 6
Figure 6
The annual periodic harmonics in morbidity of URI and LRI, as well as the annual cycle of air temperature (T).
Figure 7
Figure 7
The annual cyclic wave of morbidity for CVD and CBD, relatively to annual cycle of air temperature.
See this image and copyright information in PMC

References

    1. Abboud S., Bruderman I., Sadeh D. Frequency and time domain analysis of airflow breathe patterns in patients with chronic obstructive airway disease. Comput. Biomed. Res. 1986;19(3):266–273. - PubMed
    1. Acharya R., Niranjan U.C., Iyengar S.S., Kannathal N., Min L.C. Simultaneous storage of patient information with medical images in the frequency domain. Comput. Methods Progr. Biomed. 2004;76(1):13–19. - PubMed
    1. Ban J., Huang L., Chen C., Guo Y., He M.Z., Li T. Integrating new indicators of predictors that shape the public's perception of local extreme temperature in China. Sci. Total Environ. 2017;579:529–536. - PMC - PubMed
    1. Barry R.G., Chorley R.J. ROUTLEDGE; 2003. Atmosphere, Weather, and Climate [M]
    1. Breitner S., Wolf K., Devlin R.B., Diaz-Sanchez D., Peters A., Schneider A. Short-term effects of air temperature on mortality and effect modification by air pollution in three cities of Bavaria, Germany: a time-series analysis. Sci. Total Environ. 2014;485–486:49–61. - PubMed

LinkOut - more resources