SEPARATING THE EFFECTS OF TEMPERATURE AND SEASON ON DAILY MORTALITY FROM THOSE OF AIR-POLLUTION IN LONDON - 1965-1972

Authors
Citation
M. Lippmann et K. Ito, SEPARATING THE EFFECTS OF TEMPERATURE AND SEASON ON DAILY MORTALITY FROM THOSE OF AIR-POLLUTION IN LONDON - 1965-1972, Inhalation toxicology, 7(1), 1995, pp. 85-97
Citations number
12
Categorie Soggetti
Toxicology
Journal title
ISSN journal
08958378
Volume
7
Issue
1
Year of publication
1995
Pages
85 - 97
Database
ISI
SICI code
0895-8378(1995)7:1<85:STEOTA>2.0.ZU;2-#
Abstract
Most analyses of the large database of daily mortality and indices of pollution in London, England, have dealt with the confounding influenc e of ambient temperature and/or season by using empirical adjustment m odels in the determination of the regression coefficients for the poll utants. The conclusions about the influence of the measured pollutants , that is, aerosol strong acid (H+), sulfur dioxide (SO2), and black s moke (BS), on mortality have varied due, at least in part, to the sele ction of the form of the temperature/season adjustment model. We have taken an alternate approach to separate the influences of temperature, season, and ambient pollutant levels on daily mortality in Greater Lo ndon between 1965 and 1972. In each season, the majority of days fell within one or two temperature ranges, within which the daily death rat es also fell within narrow ranges. Within these restricted temperature and mortality ranges, preliminary analyses indicated that there were relatively strong associations between daily mortality and the daily l ogs of the concentrations of H+ and SO2 that were not confounded by te mperature or seasonal variations. By contrast, the associations betwee n the daily log of BS and daily mortality in these restricted ranges w ere weaker, especially in the winter and summer seasons. While a more comprehensive analysis of these London data and of other pollutant and mortality data sets is needed these initial results suggest that this new approach can serve as a valuable complement to model-based approa ches for studying associations between pollutant exposures and daily m ortality.