Temporal associations between weather and headache: Analysis by empirical mode decomposition

Albert C. Yang, Jong Ling Fuh, Norden E. Huang, Ben Chang Shia, Chung Kang Peng, Shuu Jiun Wang

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons.

Original languageEnglish
Article numbere14612
JournalPLoS One
Volume6
Issue number1
DOIs
Publication statusPublished - 2011
Externally publishedYes

Fingerprint

headache
Weather
Headache
weather
Decomposition
degradation
angle of incidence
Time series
Association reactions
Incidence
Linear regression
Atmospheric humidity
Sunlight
wind speed
Temperature
time series analysis
Linear Models
solar radiation
methodology
duration

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Temporal associations between weather and headache : Analysis by empirical mode decomposition. / Yang, Albert C.; Fuh, Jong Ling; Huang, Norden E.; Shia, Ben Chang; Peng, Chung Kang; Wang, Shuu Jiun.

In: PLoS One, Vol. 6, No. 1, e14612, 2011.

Research output: Contribution to journalArticle

Yang, Albert C. ; Fuh, Jong Ling ; Huang, Norden E. ; Shia, Ben Chang ; Peng, Chung Kang ; Wang, Shuu Jiun. / Temporal associations between weather and headache : Analysis by empirical mode decomposition. In: PLoS One. 2011 ; Vol. 6, No. 1.
@article{89ceb738bcb34b8c8fb280770110acdc,
title = "Temporal associations between weather and headache: Analysis by empirical mode decomposition",
abstract = "Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3{\%} of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons.",
author = "Yang, {Albert C.} and Fuh, {Jong Ling} and Huang, {Norden E.} and Shia, {Ben Chang} and Peng, {Chung Kang} and Wang, {Shuu Jiun}",
year = "2011",
doi = "10.1371/journal.pone.0014612",
language = "English",
volume = "6",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "1",

}

TY - JOUR

T1 - Temporal associations between weather and headache

T2 - Analysis by empirical mode decomposition

AU - Yang, Albert C.

AU - Fuh, Jong Ling

AU - Huang, Norden E.

AU - Shia, Ben Chang

AU - Peng, Chung Kang

AU - Wang, Shuu Jiun

PY - 2011

Y1 - 2011

N2 - Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons.

AB - Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons.

UR - http://www.scopus.com/inward/record.url?scp=79551635671&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79551635671&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0014612

DO - 10.1371/journal.pone.0014612

M3 - Article

C2 - 21297940

AN - SCOPUS:79551635671

VL - 6

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 1

M1 - e14612

ER -