RESUMO
BACKGROUND: Non-lineal temperature-mortality relationship varies depending on the characteristics of the designated study geographic zone. In given places, a growing level of economic development has led to lesser influence of environmental variables on mortality. This paper analyzes trends in the association between maximum temperatures and organic-cause mortality from 1975 to 2003 in Castile-La Mancha (Spain). METHODS: Daily maximum temperatures and organic-cause mortality data were divided into 3 time period: 1975-1984, 1985-1994 and 1995-2003. After data pre-whitening by applying ARIMA model estimated for the daily maximum temperature series, we calculate cross-correlation functions between residuals of temperature and mortality, 7 days lagged for summer, 15 for cold months, and comparing its correlation coefficients. RESULTS: We observe an increasing number of significant lags during the warm season (p < 0.05) between first and second decades studied in regional overall but with some provincial differences. In the third study period the number of significant lags varies slightly, although cross correlation coefficients were significantly upward (p < 0.05) at lag 3 in the entire region and Toledo in particular. CONCLUSIONS: Maximum temperature and mortality by organic cause association became more extensive and intense since 1975-1984 decade in Castile-La Mancha. The aging of regional population could offset the probable beneficial effect of economic growth on this relationship. No appreciable time trends are found in cold months.
Assuntos
Causas de Morte/tendências , Temperatura Alta/efeitos adversos , Humanos , Espanha/epidemiologiaRESUMO
Fundamento: La relación no lineal temperatura- mortalidad varía según las características de la zona geográfica estudiada. En determinados lugares un incremento en el nivel de desarrollo ha conducido a una menor influencia de las variables ambientales sobre la mortalidad. Se analiza la evolución entre 1975 y 2003 de la asociación de las temperaturas máximas con la mortalidad por causas orgánicas en Castilla-La Mancha. Métodos: Los datos diarios de temperaturas máximas y de mortalidad por causas orgánicas se dividen en tres periodos: 1975-1984, 1985-1994 y 1995-2003. Tras un preblanqueo de los datos aplicando el modelo ARIMA ajustado para las series de temperaturas, se calculan las funciones de correlación cruzada entre los residuos de las series de temperaturas y de mortalidad con 7 desfases en verano y 15 en invierno, comparándose los coeficientes de correlación. Resultados: Se observa en los meses calurosos un incremento del número de retardos significativos (p<0,05) de la primera a la segunda década de estudio en el conjunto regional, con algunas diferencias provinciales. En la tercera década el número de lags significativos varía ligeramente, incrementándose los coeficientes de correlación cruzada de forma significativa (p<0,05) para el desfase 3 en Toledo y en el total regional. Conclusiones: La asociación de las temperaturas máximas con la mortalidad por causas orgánicas se ha ampliado e intensificado desde la década 1975-1984. El envejecimiento de la población podría haber contrarrestado el posible efecto beneficioso del crecimiento económico sobre esta relación. En los meses fríos no se encuentra evolución temporal apreciable
Background: Non-lineal temperature-mortality relationship varies depending on the characteristics of the designated study geographic zone. In given places, a growing level of economic development has led to lesser influence of environmental variables on mortality. This paper analyzes trends in the association between maximum temperatures and organic-cause mortality from 1975 to 2003 in Castile- La Mancha (Spain). Methods: Daily maximum temperatures and organic-cause mortality data were divided into 3 time period: 1975-1984, 1985- 1994 and 1995-2003. After data pre-whitening by applying ARIMA model estimated for the daily maximum temperature series, we calculate cross-correlation functions between residuals of temperature and mortality, 7 days lagged for summer, 15 for cold months, and comparing its correlation coefficients. Results: We observe an increasing number of significant lags during the warm season (p<0.05) between first and second decades studied in regional overall but with some provincial differences. In the third study period the number of significant lags varies slightly, although cross correlation coefficients were significantly upward (p<0.05) at lag 3 in the entire region and Toledo in particular. Conclusions: Maximum temperature and mortality by organic cause association became more extensive and intense since 1975-1984 decade in Castile- La Mancha. The aging of regional population could offset the probable beneficial effect of economic growth on this relationship. No appreciable time trends are found in cold months
Assuntos
Humanos , Temperatura Extrema , Fatores Epidemiológicos , Mortalidade , Estações do Ano , Causas de Morte/tendênciasRESUMO
BACKGROUND: Numerous articles relate atmospheric variables to health indicators. In large regions, such as Castilla-La Mancha, it may be necessary to divide the region into areas in terms of the atmospheric variables available by selecting a representative weather station for each zone. This article focuses on analyzing the daily temperature data from numerous Castilla La Mancha observatories and reducing the number thereof to a few representative stations for being used in studies relating atmospheric variables to health indicators in this region. METHODS: Castilla-La Mancha weather stations were selected in terms of the number of years available and missing data. After filling in the gaps in the selected series, to detect any possible discontinuities and to homogenize the series, the daily temperature data is used in hierarchical cluster and factorial analyses by principal components. RESULTS: Factorial analyses extract one single factor by using the maximum, mean or minimum temperature series. For the maximum temperatures, this factor explains 93.45% of the variance, with an eigenvalue of 39.249. The "Compuesta" station in Toledo shows correlation coefficients in the principal components matrix of 0.987, 0.991 and 0.981 respectively for the maximum, mean and minimum temperature series. CONCLUSIONS: Castilla-La Mancha is an isoclimatic region in terms of the temperature, the "Compuesta" station in Toledo being selected as the representative station for the region for public health studies. The results afford the possibility of conducting studies broken down into small units such as the provinces, with the stations in the government capitals as a reference.
Assuntos
Saúde Pública/estatística & dados numéricos , Temperatura , EspanhaRESUMO
Fundamento: Numerosos trabajos relacionan variables atmosféricascon indicadores sanitarios. En regiones extensas, como Castilla-La Mancha, puede ser necesario dividirla en áreas en función delas variables atmosféricas disponibles, eligiendo una estación meteorológicarepresentativa para cada zona. El objetivo de este artículoes analizar los datos diarios de temperaturas de numerosos observatoriosde Castilla- La Mancha y su reducción a unas pocas estacionesrepresentativas para ser utilizadas en estudios que relacionen variablesatmosféricas con indicadores sanitarios de esta región.Métodos: Se seleccionaron estaciones meteorológicas de Castilla-La Mancha en función del número de años disponibles y de datosperdidos. Tras rellenar las lagunas de las series elegidas, detectarposibles discontinuidades y homogeneizar las series, los datos diariosde temperaturas se utilizan en análisis de conglomerados jerárquicoy factorial mediante componentes principales.Resultados: El análisis factorial extrae un solo factor utilizandolas series de temperaturas máximas, medias o mínimas. En las máximas,ese factor explica el 93,45% de la varianza, con autovalor39,249. La estación Toledo «Compuesta» tiene coeficientes decorrelación en la matriz de componentes principales de 0,987; 0,991y 0,981 para las series de temperaturas máximas, medias y mínimasrespectivamente. Conclusiones: Castilla-La Mancha es una región isoclimática enfunción de la temperatura y la estación Toledo «Compuesta» la elegidacomo representativa regional para estudios en salud pública.Los resultados permiten la realización de estudios desagregados enunidades menores como las provincias, con las estaciones de lascapitales administrativas como referencia
Background: Numerous articles relate atmospheric variablesto health indicators. In large regions, such as Castilla-La Mancha, itmay be necessary to divide the region into areas in terms of theatmospheric variables available by selecting a representativeweather station for each zone. This article focuses on analyzing thedaily temperature data from numerous Castilla La Mancha observatoriesand reducing the number thereof to a few representative stationsfor being used in studies relating atmospheric variables tohealth indicators in this region.Methods: Castilla-La Mancha weather stations were selected interms of the number of years available and missing data. After fillingin the gaps in the selected series, to detect any possible discontinuitiesand to homogenize the series, the daily temperature data is usedin hierarchical cluster and factorial analyses by principal components.Results: Factorial analyses extract one single factor by using themaximum, mean or minimum temperature series. For the maximumtemperatures, this factor explains 93.45% of the variance, with aneigenvalue of 39.249. The «Compuesta» station in Toledo showscorrelation coefficients in the principal components matrix of 0.987,0.991 and 0.981 respectively for the maximum, mean and minimumtemperature series. Conclusions: Castilla-La Mancha is an isoclimatic region interms of the temperature, the «Compuesta» station in Toledo beingselected as the representative station for the region for public healthstudies. The results afford the possibility of conducting studies brokendown into small units such as the provinces, with the stations inthe government capitals as a reference
