Inverted U-shape relationships of the weather as biometeorological and hospital admissions due to carcinoma in situ and benign neoplasm in Germany in 2009-2011

Environ Sci Pollut Res Int. 2015 Jun;22(12):9378-99. doi: 10.1007/s11356-015-4095-5. Epub 2015 Jan 22.

Abstract

We aimed to understand the relationships of the weather as biometeorological and hospital admissions due to carcinoma in situ and benign neoplasms, which have been less paid attention to, in a national setting in recent years. 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 D00-D48 in situ neoplasms, benign neoplasms and neoplasms of uncertain or unknown behaviour 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). For most subtypes, peaks of admissions were observed in spring and late autumn. There could be four groups of phenomenon among these admissions. To be specific, D06, D16, D21, D24-25, D35 and D39 peaked when PET was at 0 °C. D46 peaked when PET was at 5-10 °C. D03, D04 and D33 had linear relationships. Other admissions peaked when PET was between 0 and 5 °C. All admissions were in common with a drop when PET reached 10 °C or higher. More medical resources could have been needed on days when PETs were at 0-10 °C than on other days. Adaptation to such weather change for medical professionals and the general public would seem to be imperative.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma in Situ / diagnosis*
  • Carcinoma in Situ / epidemiology*
  • Germany / epidemiology
  • Hospitalization* / statistics & numerical data
  • Humans
  • Meteorology*
  • Retrospective Studies
  • Seasons
  • Temperature
  • Weather*