Health Effects of Air Pollution:\\ A Statistical Review

作者: Francesca Dominici , Lianne Sheppard , Merlise Clyde

DOI: 10.1111/J.1751-5823.2003.TB00195.X

关键词: EstimationComputer scienceSampling (statistics)DemographyResearch opportunitiesMultivariate analysisExposure measurementAir pollutionEnvironmental planningData limitationsStatistical model

摘要: Summary We critically review and compare epidemiological designs statistical approaches to estimate associations between air pollution health. More specifically, we aim address the following questions: 1 Which methods are available health? 2 What recent methodological advances in estimation of health effects time series studies? 3 main challenges future research opportunities relevant regulatory policy? In question 1, identify strengths limitations series, cohort, case-crossover panel sampling designs. In 2, focus on studies for: 1) combining information across multiple locations overall effects; 2) estimating taking into account model uncertainties; 3) investigating consequences exposure measurement error pollution; 4) pollution-health exposure-response curves. Here, also discuss extent which these contributions have addressed key substantive questions. 3, within a set policy-relevant-questions, point out current data limitations.

参考文章(123)
D. V. Lindley, A. F. M. Smith, Bayes Estimates for the Linear Model Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 34, pp. 1- 18 ,(1972) , 10.1111/J.2517-6161.1972.TB00885.X
Thurston Gd, A critical review of PM10-mortality time-series studies. Journal of Exposure Science and Environmental Epidemiology. ,vol. 6, pp. 3- 21 ,(1996)
J Spengler, H Ozkaynak, J Xue, L Wallace, P Jenkins, E Pellizzari, Personal exposure to airborne particles and metals: Results from the Particle TEAM Study in Riverside, California Journal of Exposure Science and Environmental Epidemiology. ,vol. 6, pp. 57- 78 ,(1996)
Peter McCullagh, Regression Models for Ordinal Data Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 42, pp. 109- 127 ,(1980) , 10.1111/J.2517-6161.1980.TB01109.X
David Draper, Assessment and Propagation of Model Uncertainty Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 57, pp. 45- 70 ,(1995) , 10.1111/J.2517-6161.1995.TB02015.X
Francesca Dominici, Michael Daniels, Scott L Zeger, Jonathan M Samet, Air pollution and mortality: Estimating regional and national dose-response relationships Journal of the American Statistical Association. ,vol. 97, pp. 100- 111 ,(2002) , 10.1198/016214502753479266
Chris T. Volinsky, Adrian E. Raftery, David Madigan, Jennifer A. Hoeting, Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors Statistical Science. ,vol. 14, pp. 382- 417 ,(1999) , 10.1214/SS/1009212519
Hugh Chipman, Edward I George, Robert E McCulloch, Merlise Clyde, Dean P Foster, Robert A Stine, The Practical Implementation of Bayesian Model Selection Institute of Mathematical Statistics Lecture Notes - Monograph Series. ,vol. 38, pp. 65- 116 ,(2001) , 10.1214/LNMS/1215540964
K Katsouyanni, G Touloumi, C Spix, J Schwartz, F Balducci, S Medina, G Rossi, B Wojtyniak, J Sunyer, L Bacharova, J P Schouten, A Ponka, H R Anderson, Short term effects of ambient sulphur dioxide and particulate matter on mortality in 12 European cities: Results from time series data from the APHEA project BMJ. ,vol. 314, pp. 1658- 1663 ,(1997) , 10.1136/BMJ.314.7095.1658
Joel Schwartz, Air Pollution and Daily Mortality in Birmingham, Alabama American Journal of Epidemiology. ,vol. 137, pp. 1136- 1147 ,(1993) , 10.1093/OXFORDJOURNALS.AJE.A116617