Hospital admissions of hypertension, angina, myocardial infarction and ischemic heart disease peaked at physiologically equivalent temperature 0 °C in Germany in 2009–2011
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We aimed to understand and to provide evidence on relationships of the weather as biometeorological and hospital admissions due to hypertension, angina, myocardial infarction and ischemic heart disease in a national setting in recent years that might help indicate when to expect more admissions for health professionals and the general public. This is an ecological study. Ten percent of daily hospital admissions from the included hospitals (n = 1618) across Germany that were available between 1 January 2009 and 31 December 2011 (n = 5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I11 hypertensive heart disease, I13 hypertensive heart and renal disease, I15 secondary hypertension, I20 angina pectoris, I21 acute myocardial infarction and I25 chronic ischemic heart disease by International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that covered 13 German States including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure were obtained and generated into physiologically equivalent temperature (PET). Two-way fractional-polynomial prediction was plotted with 95 % confidence intervals. Hospital admissions of hypertension, angina, myocardial infarction, heart disease peaked in winter and early spring when PETs were around 0 °C. Admissions had an apparent drop when PETs reached 10 °C. More medical resources could have been needed on days when PETs were around 0 °C than on other days. While adaptation to such weather change for health professionals and the general public would seem to be imperative, future research with a longitudinal monitoring would still be needed.
KeywordsHospital admission Weather Biometeorology Heart disease Hypertension Angina Myocardial infarction Cold
Ivy Shiue was supported by the EU FP-7 project, Data without Boundaries (grant no. 262608). The authors would also like to thank Mr Rafael Beier and other German colleagues at Statistisches Bundesamt for their professional assistance in coordinating and checking data and hosting the research visit for the purpose of data analysis.
Conflict of interest
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