Research Program Area: Health & Exposure
Topic Areas: Health Effects of Air Pollution
The possible association between three kinds of mortality and several pollution and weather variables is investigated using a general multiple time series regression model on daily data collected during fourteen London winters spanning the time period 1958-1971. The best model for predicting overall mortality, cardiovascular mortality, or respiratory mortality involved using lagged temperature in combination with the logarithms of the same day levels of either sulfur dioxide or black smoke deposits. The pollutants are more important than temperature in predicting changes in overall and respiratory mortality but are less important in predicting cardiovascular mortality. The mechanism indicated by the regression analysis is that pollution acts positively and instantaneously, whereas temperature acts negatively with the strongest component at a lag of two days for cardiovascular mortality and positively as a function of the two-day temperature differential for overall and respiratory mortality. The strongest associations, as measured by the multiple coherence, occur at periods ranging between seven and 21 days, implying that pollution and temperature "episodes" must persist in order to influence mortality.
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