Journal Information
Vol. 11. Issue 1.
Pages 9-15 (January - February 1997)
Vol. 11. Issue 1.
Pages 9-15 (January - February 1997)
Open Access
Modelización de la mortalidad diaria en la Comunidad Autónoma de Madrid (1986–1991)
Modeling of daily mortality in the Autonomous Community of Madrid, Spain [1986–19911]
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J.C. Alberdi Odriozola, J. Díaz Jiménez*
Centro Universitario de Salud Pública
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Resumen
Objetivo

Describir, cuantificar y modelizar las tendencias y variaciones cíclicas de la mortalidad diaria en la Comunidad de Madrid (C.M.).

Métodos

Se analizaron la tasa bruta de mortalidad diaria y las tasas de mortalidad por sexo, grupos de edad y causas específicas en la C.M. desde el 1 de enero de 1986 al 31 de diciembre de 1991. Se utilizó la Transformada Rápida de Fourier para detectar y cuantificar las periodicidades. La mode-lización de la serie se realizó mediante modelos ARIMA y regresión de Poisson.

Resultados

El análisis espectral realizado indica la existencia de periodicidades en las bajas frecuencias de carácter anual (invernal) y semestral (estival). La primera está constituida por las enfermedades del aparato circulatorio en las mujeres mayo res de 65 años y del aparato circulatorio, respiratorio y digestivo en los hombres mayores de 44. La estacionalidad semestral está relacionada con las muertes por accidente cerebrovascular agudo en las mujeres de 65 y más.

Conclusiones

Las estacionalidades anual y semestral detectadas soportan la hipótesis de una estrecha relación de la mortalidad con factores ambientales externos.

Palabras clave:
Mortalidad diaria
Estacionalidad
Modelos ARIMA
Modelos Poisson
Summary
Objective

To describe, estimate and model trends and seasonal variations in daily mortality in the Comunidad ot Madrid, Spain.

Methods

Overall mortality rate, as well as gender, age and cause-specific mortality rates between january 1, 1986 and december 31, 1991 were analyzed. A cyclic pattern was detected using fast Fourier transform. Mortality was modelled using ARIMA stochastic models and Poisson regression models.

Results

Spectral analysis detected two statistically significant periodic components (winter-summer). Winter peak was related mainly to an excess in cardiovascular diseases in women aged 65 and over, as well as with cardiovascular, respiratory and digestive diseases in men aged 45 and over. The summer peak was related with women, aged 65 and over with cerebrovascular diseases as the cause of death.

Conclusions

The two cycles detected support the hypothesis of an association between mortality and environmental factors.

Key words:
Daily mortality
Spectral analysis
ARIMA stochastic models
Poisson regression models
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