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

2. 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.

3. 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

4. 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

5. 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

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

7. St. George’s data base

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

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

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

11. 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

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

13. 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

14. 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

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

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

17. 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

18. 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

19. 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

20. 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

21. Are all meta-analyses the same?

22. 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

23. National Morbidity Mortality Air Pollution Study 1987—2000

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

25. 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)

26. 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

27. 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)

28. 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

29. 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.

30. % 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

31. HEI’s PAPA-SAN Project

32. 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?