1 / 33

Impact of Air Pollution on Public Health: Transportability of Risk Estimates

Department of Epidemiology. Impact of Air Pollution on Public Health: Transportability of Risk Estimates. Jonathan M. Samet, MD, MS NERAM V October 16, 2006 Vancouver, B.C. What is transportability?.

ajay
Download Presentation

Impact of Air Pollution on Public Health: Transportability of Risk Estimates

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Department of Epidemiology Impact of Air Pollution on Public Health: Transportability of Risk Estimates Jonathan M. Samet, MD, MS NERAM V October 16, 2006 Vancouver, B.C.

  2. What is transportability? • The idea that risks of air pollution observed in one or more populations can be extended to other populations. • AKA: generalizability or external validity

  3. Why transport risk estimates? • Local evidence not available as basis for policy formulation. • Use external evidence as framework to strengthen interpretation of locally derived evidence. • To estimate burden of disease globally

  4. What factors influence transportability? • Characteristics of the air pollution mixture in study community(ies). • Population characteristics that determine susceptibility to air pollution. • Methodologic issues • Characteristics of exposure and outcome data • Data analysis approach • Publication bias

  5. Local vs non-local risk estimates • Local estimates • Motivate policy • Facilitate burden estimation • Accountability assessment • Non-local estimates • Credibility • Stability and precision • Bound risks

  6. St. George’s data base

  7. Time-series estimates to 2006 Daily all-cause mortality and PM10 (n=314) St. George’s data base, 10/06

  8. Time-series estimates to 2006 Daily cardiovascular mortality and PM10 (n=177) St. George’s data base, 10/06

  9. Time-series estimates to 2006 Respiratory mortality and PM10 (n=47) St. George’s data base, 10/06

  10. All-cause mortality: % change in number of deaths associated with 10 µg/m3 increase in daily PM2.5 Source: Anderson HR et al. WHO 2004

  11. What is responsible for heterogeneity? • Publication bias? • Population characteristics? • Methodologic approaches?

  12. What is publication bias? • A tendency for the publication process to differentially lead to publication of papers reporting statistically significant findings. • May influence data analysis and selection of findings for publication • Can it be identified? • Graphical approaches • Analytic approaches

  13. Ozone for example: a meta-analysis • 144 effect estimates from 39 time-series studies • Strong statistically significant association identified between ozone and mortality for total deaths and cardiovascular disease • Implied relationship between ozone and respiratory disease mortality • Large heterogeneity in individual study estimates • Some indication of publication bias Bell et al., 2005

  14. Comparison of ozone meta-analysis and multi-city results Bell et al. 2005

  15. Funnel plot for estimates for respiratory mortality and ozone Publication Bias Zone Source: Anderson HR et al. WHO 2004

  16. Variation in ozone effect by cause • Percent increase in daily total mortality for a 10 ppb increase in daily ozone (95% PI) Total: 0.87% (0.55, 1.18%) CVD: 1.11% (0.68, 1.53%) Respiratory: 0.47% (-0.51, 1.47%) Source: Bell et al. Epidemiol 2005

  17. Variation in ozone effect by location • Percent increase in daily total mortality for a 10 ppb increase in daily ozone (95% CI) • U.S.: 0.84% (0.48, 1.20%) • 11 estimates from 9 studies • Non-U.S.: 0.92% (0.47, 1.38%) • 20 estimates from 14 studies • Heterogeneity among estimates Source: Bell et al. Epidemiol 2005

  18. Variation in ozone effect by age • Percent increase in daily total mortality for a 10 ppb increase in daily ozone (95% CI) • All ages:0.83% (0.53, 1.12%) • 65+ or 64+:1.27% (0.65, 1.89%) Source: Bell et al. Epidemiol 2005

  19. Ranking of PM10 estimates for all-cause mortality by annual average levels of PM10 * *left y-axis: mean PM10 levels in µg/m3; right y-axis: RR in total mortality of a 10 µg/m3 increase of PM10 Source: Anderson HR et al. WHO 2004

  20. Are all meta-analyses the same?

  21. Some solutions • Maintained data base and periodic meta-analysis • Multi-city analyses • Periodic global analyses • Also needed: • Unbiased publication processes • Transparent analytic approaches • Bayesian methods for handling local data

  22. National Morbidity Mortality Air Pollution Study 1987—2000

  23. City, Regional and National Estimates City-specific and regional estimates

  24. Sensitivity of the national average estimates of the PM10 - mortality association to adjustment for seasonality and model choice (1987-2000) Peng, Dominici, Louis JRSS (2006)

  25. Sensitivity of national average estimates to model selection methods • National average estimates of the % increase in mortality for a 10 mg/m3 increase in PM10 • Previously reported results appear robust to choice of model selection method

  26. Benefits: Verifying published findings Conducting alternative analyses of the same data Eliminating uninformed criticisms which do not match data Expediting interchange of ideas among investigators Reproducible Research(www.biostat.jhsph.edu/MCAPS)

  27. Overview of APHENAAir Pollution and Health: a Combined European And North American Approach (APHENA) The APHENA Group Europe: Touloumi G, Samoli E, Pipikou M, Atkinson R, Le Tertre A, Anderson R, Katsouyanni K US: Dominici F, Peng R, Schwartz J, Zanobetti A, Samet J Canada: Ramsay T, Burnett R, Krewski D. Supported by the Health Effects Institute

  28. Objectives: • Develop a common approach for first-stage analyses of mortality and admissions time-series data and assess sensitivity of findings to critical elements of the model (using simulations and real data). • Comparative evaluation of different methods to identify and combine dose-response curves; • Comparison of alternative methods for addressing mortality displacement, and eventual application of one or more approaches to the various databases; • Development of a data base on potential effect modifiers with exploration of differences in common, core items across the involved countries; • Parallel and combined analyses of the air pollution and mortality data, and air pollution and hospitalization data, including exploration of geographic heterogeneity.

  29. % increase in daily number of deaths (75+ years old), associated with 10 μg/m3 increase in PM10 (lags 0 and 1) in 21 European and 15 U.S. cities with daily PM10 data

  30. HEI’s PAPA-SAN Project

  31. Looking Ahead • Need for tracking development of risk estimates through systematic data bases • Empiric evaluation of impact of local research estimates is needed • Methods development needed for use of local risk estimates in context of regional and global estimates • Continuation of APHENA-like approaches?

More Related