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International Journal of Biometeorology

, Volume 47, Issue 4, pp 227–229 | Cite as

Sensitivity analysis of common statistical models used to study the short-term effects of air pollution on health

  • Aurelio TobíasEmail author
  • Marc Sáez
  • Iñaki Galán
  • Michael J. Campbell
Original Article

Abstract.

The relationship between photochemical air pollutants (nitrogen dioxide and ozone) and emergency room admissions for asthma in Madrid (Spain) for the period 1995–1998 was analysed using the statistical models commonly used to studying the short-term effects of air pollution on health: linear and Cochrane-Orcutt regression, standard Poisson and Poisson corrected by overdispersion, Poisson autoregressive models, and generalised additive models. Linear regression models presented residual autocorrelation, Poisson regression models also showed overdispersion, and generalised additive models did not show residual autocorrelation and overdispersion was substantially reduced. Linear models provided biased estimates because our health outcome is non-normally distributed. Estimates from Poisson regression allowing for overdispersion and autocorrelation did not differ substantially from those reported by generalised additive models, which present the best model fit in terms of the absence of autocorrelation and reduction of overdispersion.

Keywords.

Air pollution Statistical models Autocorrelation Overdispersion Sensitivity analysis 

Notes

Acknowledgements.

We are grateful to Dr. José Banegas also to the anonymous referees and to the Editor for their useful comments. We would also thank to the Madrid Municipal Air Pollution Control Department (Departamento de Control de Contaminación Atmosférica del Ayuntamiento de Madrid), the Ministry of the Environment Subdirectorate-General for Environmental Quality (Subdirección General de Calidad Ambiental del Ministerio de Medio Ambiente) the Regional Asthma Prevention & Control Programme (Programa Regional de Prevención y Control del Asma) and the Gregorio Marañón Hospital Emergency Ward for allowing us access to their data. This study was funded by the Advisory Committee to the Madrid Regional Asthma Prevention & Control Programme (Comisión Asesora del Programa Regional de Prevención y Control del Asma de la Comunidad de Madrid). Aurelio Tobías was enjoying a postgraduate fellowship of the Universidad Autónoma de Madrid.

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Copyright information

© ISB 2003

Authors and Affiliations

  • Aurelio Tobías
    • 1
    • 2
    Email author
  • Marc Sáez
    • 3
  • Iñaki Galán
    • 4
  • Michael J. Campbell
    • 5
  1. 1.Department of Statistics and Econometrics, Universidad Carlos III de Madrid, C/Madrid 126, E-28903 Getafe, Spain
  2. 2.Department of Preventive medicine and Public Health, Universidad Autónoma de Madrid, Spain
  3. 3.Statistics and Econometrics, Applied Economics and Health (GRECS), Department of Economics, Universitat de Girona, Spain
  4. 4.Department of Epidemiology, Institute of Public Health, Consejería de Sanidad, Madrid, Spain
  5. 5.Institute of General Practice and Primary Care, University of Sheffield, UK

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