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ID 35254
file
creator
Matsumura, Makoto
HEWS group
subject
myocardial infarction
atmospheric pressure
prevention
NDC
Medical sciences
abstract
Prediction of high-risk days for onset of acute myocardial infarction (AMI) would aid prevention by taking specific actions on such days. To construct a predictive model, we investigated meteorological conditions related to high risk, with particular attention to atmospheric pressure.

The data used were records of conveyance by ambulances in the city of Hiroshima from January 1993 to December 2002, and corresponding meteorological data in the area. We used a Poisson regression model and several variables representing different critical conditions of atmospheric pressure decline. Finally, we selected the best model according to Akaike's Information Criterion (AIC).

A prediction model using a continuous variable of daily mean atmospheric temperature was established as the baseline model. Among models using different variables, one using weather pattern variables achieved the lowest AIC, showing it to be the best choice. In this model, strong winter patterns on the previous day were correlated with high risk of AMI.

The following meteorological factors were particularly related to high AMI risk: 1) A weather chart showing a strong winter pattern on the previous day, and 2) a decline in atmospheric pressure ≥ 16 hPa in addition to low atmospheric temperature. Such a strong winter pattern is easy to use and will improve performance of the Hiroshima prefectural AMI alert system.
journal title
Journal of health sciences, Hiroshima University
volume
Volume 11
issue
Issue 2
start page
43
end page
51
date of issued
2013-10-31
publisher
広島大学保健学出版会
issn
1347-7323
ncid
SelfDOI
language
jpn
nii type
Departmental Bulletin Paper
HU type
Departmental Bulletin Papers
DCMI type
text
format
application/pdf
text version
publisher
rights
Copyright (c) 2013 広島大学保健学出版会
department
Graduate School of Health Science
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