Some Methodological Issues in Statistical Estimation of Air Pollution and Health

Abstract:

This paper introduces a new method for estimating a dose-response relationship from spatially averaged time series of air pollution and health data. Because time is perceived as a nuisance parameter to be eliminated, least-squares regression and traditional time series methodology (e.g., spectral analysis Box-Jenkins methods) are rejected in favor of a nonparametric estimation procedure based on observing health effects in times of nearly equal pollution. The method requires estimating the ratio of two density functions and avoids problems of aggregation, linearity and normality. In spite of the formal tests described, the procedure seems most useful at present as a data analytic and data display device rather than as an inferential tool.

Key-words:

Air Pollution - Health - Statistical Modeling - Exploratory Data Analysis

• REFERENCES

• 1 Lipfert FW. Statistical studies of mortality and air pollution. The Science of the Total Environment 1980; 16: 165-83.
• 2 Lipfert FW. Mortality and air pollution lessons from statistics. The Science of the Total Environment 1982; 23: 175-88.
• 3 Neyman J. Assessing the chain: energy crisis, pollution and health. Internat Statist Rev 1975; 43: 253-67.
• 4 Gottinger HW. Air pollution health effects in the Munich metropolitan area: preliminary results based on a statistical model. Environm Internat 1983; 9: 207-20.
• 5 Parzen E. On estimation of a probability density function and mode. Ann Math Statist 1962; 33: 1065-76.
• 6 Kronmal R, Tartar M. The estimation of probability densities and cumulatives by Fourier series methods. J Amer Statist Assoc 1968; 63: 925-52.
• 7 Wegman E. Nonparametric probability density estimation: I. a summary of available methods. Technometrics 1972; 14: 533-46.
• 8 Matheron G. The intrinsic random functions and their applications. Adv Appl Prob 1973; 5: 439-69.
• 9 Behar JV. Application of computer simulation techniques to problems in air pollution. In: Sixth Berkeley Symposium on Mathematical Statistics and Probability. . Berkeley CA: Univ. of California Press; 1972: 29-69.
• 10 Shir C, Shieh L. A generalized urban air pollution model and its application to the study of SO₂ distribution in the St. Louis metropolitan area. J Appl Meteorol 1974; 13: 185-204.
• 11 Knox JB, Pollack RI. An investigation of the frequency distributions of surface airpollutant concentrations. In: Proceedings of Symposium on Statistical Aspects of Air Quality Data. US Environmental Protection Agency EPA-650/4-74-038. 1974. chapter 9
• 12 Barlow R, Bartholomew D, Bremner J, Brunk HD. Statistical Inference under Order Restrictions. . New York: Wiley and Sons; 1972
• 13 Lehmann E. Testing Statistical Hypotheses. . New York: Wiley and Sons; 1952