Use of poisson regression and box-jenkins models to evaluate the short-term effects of environmental noise levels on daily emergency admissions in Madrid, Spain

Eur J Epidemiol. 2001;17(8):765-71. doi: 10.1023/a:1015663013620.


The relationship between environmental factors and hospital admissions has usually been analysed without taking into account the influence of a factor closely related to traffic in big cities, that is, environmental noise levels. We analysed the relationship between environmental noise and emergency admissions, for all causes and specific causes in Madrid (Spain), for the study period 1995-1997, using two statistical methods for the analysis of epidemiological time series data: Poisson autoregressive models and Box Jenkins (ARIMA) methodology. Both methods produce a clear association between emergency admissions for all and specific causes and environmental noise levels. We found very similar results from both methods for all and circulatory causes, but slightly different for respiratory causes. Around 5% of all emergency admissions can be attributed to high noise levels, with a lower figure for specific causes. Current levels of environmental noise have a considerable epidemiological impact on emergency admissions in Madrid. A reduction of environmental noise levels could be accompanied by a possible reduction in the number of emergency admissions.

MeSH terms

  • Air Pollutants / analysis
  • Chi-Square Distribution
  • Climate
  • Confounding Factors, Epidemiologic
  • Emergency Service, Hospital / statistics & numerical data*
  • Environmental Exposure / adverse effects*
  • Humans
  • Models, Statistical
  • Noise / adverse effects*
  • Patient Admission / statistics & numerical data*
  • Poisson Distribution
  • Spain
  • Urban Population


  • Air Pollutants