Air Pollution Reduction: Is it Real and Does it Work?

Transcription

1 Air Pollution Reduction: Is it Real and Does it Work? C. Arden Pope III Mary Lou Fulton Professor of Economics Presented at: Frontiers in Spatial Epidemiology Imperial College of London, Natural History Museum of London November 5-6, 2012

2 Illustration for Charles Dickens Sketches by Boz, by George Cruikshank, 1838 The chimney, smoke Stack, and smoke and fog (smog) have long played important iconic roles in the art and literature of London.

3 Over London by Rail, 1870 Gustave Doré Depicts the congested and polluted Industrial environment of 1870 London

4 Coffee Stall by Gustave Doré, In a description of a representative London Fog day (April 6, 1870) Doré s friend Blanchard Jerrold say s of an experience with Doré: We were well into the morning and it was as dark as the darkest midnight... It was choking: it made the eyes ache. From: London: A pilgrimage, 1872 and Doré s London: All 180 illustrations from London, A Pilgrimage, 2004

5 Claude Monet, Houses of Parliament, London, 1903

6 Claude Monet, Houses of Parliament, London, 1904

7 Claude Monet, Waterloo Bridge, London, 1903

8 Claude Monet, Waterloo Bridge, London, 1903 Zoom in on background of pollution

9 Classical Economics Adam Smith Wealth of Nations (1776), free markets, competition, and the metaphor of the invisible hand. Laissez-faire What about air pollution? Smells like money to me!

10 Meuse Valley, Belgium Smog, December 1-5, deaths, 10 time expected

11 Donora, PA (Severe episode, Oct , 1948) From, Public Health Service, Bulletin No. 306, 1949

12 Danora, PA. Noon, Oct 29,

13 Donora, PA administering oxygen --Approx. 20 deaths, 6 times expected

14 London, England (Dec. 5-9, 1952)

15 London, England (Dec. 5-9, 1952)

16 London Fog Episode, Dec From: Brimblecombe P. The Big Smoke, Methuen 1987

17 Loss of Faith in the doctrine of Laissez-faire No longer did air pollution smell like money but it smelled like something unhealthy. In the UK, US, and elsewhere there were public policy efforts to clean up the air and eliminate the Killer Smog Episodes. (Clean air act) There was success at eliminating or reducing the extreme air pollution episodes but air pollution remained and we learned that even moderate air pollution had adverse health effects.

18 Brief methodological outline of air pollution epidemiological studies: Studies of short-term exposure Episode Population-based daily time-series Panel-based acute exposure Case-crossover Studies of long-term exposure Population-based cross-sectional Cohort-based mortality Cohort- and panel-based morbidity Case-control studies Intervention/natural experiment Exploit temporal variability Exploit spatial variability Exploit both temporal and spatial variability

19 Brief methodological outline of air pollution epidemiological studies: Studies of short-term exposure Episode Population-based daily time-series Panel-based acute exposure Case-crossover Studies of long-term exposure Population-based cross-sectional Cohort-based mortality Cohort- and panel-based morbidity Case-control studies Intervention/natural experiment Exploit temporal variability Exploit spatial variability Exploit both temporal and spatial variability

20 Age-, sex-, and race- adjusted populationbased mortality rates in U.S. cities for 1980 plotted over various indices of particulate air pollution (From Pope 2000). Adjusted Mortality for 1980 (Deaths/Yr/100,000) Median PM 2.5 for aprox. 1980

21 Brief methodological outline of air pollution epidemiological studies: Studies of short-term exposure Episode Population-based daily time-series Panel-based acute exposure Case-crossover Studies of long-term exposure Population-based cross-sectional Cohort-based mortality Cohort- and panel-based morbidity Case-control studies Intervention/natural experiment Exploit temporal variability Exploit spatial variability Exploit both temporal and spatial variability

22 An Association Between Air Pollution and Mortality in Six U.S. Cities 1993 Dockery DW, Pope CA III, Xu X, Spengler JD, Ware JH, Fay ME, Ferris BG Jr, Speizer FE. Methods: yr prospective follow-up of 8,111 adults living in six U.S. cities. Monitoring of TSP PM 10, PM 2.5, SO 4, H +, SO 2, NO 2, O 3. Data analyzed using survival analysis, including Cox Proportional Hazards Models. Controlled for individual differences in: age, sex, smoking, BMI, education, occupational exposure.

23 Clean cities Average Polluted cities Highly Polluted cities

24 Cox Proportional Hazards Survival Model Cohort studies of outdoor air pollution have commonly used the CPH Model to relate survival experience to exposure while simultaneously controlling for other well known mortality risk factors. The model has the form ( l) ( t) ( l) ( t) exp T x ( l) ( t) i 0 i Hazard function or instantaneous probability of death for the i th subject in the l th strata. Baseline hazard function, common to all subjects within a strata. Regression equation that modulates the baseline hazard. The vector X i (l) contains the risk factor information related to the hazard function by the regression vector β which can vary in time.

25 Adjusted risk ratios (and 95% CIs) for cigarette smoking and PM 2.5 Cause of Death Current Smoker, 25 Pack years Most vs. Least Polluted City All 2.00 ( ) 1.26 ( ) Lung Cancer Cardiopulmonary All other 8.00 ( ) 2.30 ( ) 1.46 ( ) 1.37 ( ) 1.37 ( ) 1.01 ( )

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27 Particulate Air Pollution as a Predictor of Mortality in a Prospective Study of U.S. Adults Pope CA III, Thun MJ, Namboodiri MM, Dockery DW, Evans JS, Speizer FE, Heath CW Jr. Michael Thun 1995 Clark Heath Methods: Linked and analyzed ambient air pollution data from U.S. metro areas with risk factor data for over 500,000 adults enrolled in the ACS- CPSII cohort.

28 Adjusted mortality risk ratios (and 95% CIs) for cigarette smoking the range of sulfates and fine particles Cause of Death Current Smoker All 2.07 Lung Cancer Cardio- Pulmonary ( ) 9.73 ( ) 2.28 ( ) All other 1.54 ( ) Sulfates 1.15 ( ) 1.36 ( ) 1.26 ( ) 1.01 ( ) Fine Particles 1.17 ( ) 1.03 ( ) 1.31 ( ) 1.07 ( )

29 Legal uncertainty largely resolved with 2001 unanimous ruling by the U.S. Supreme Court.

30 Dan Krewski Rick Burnett Mark Goldberg and 28 others

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32 Cox Proportional Hazards Survival Model Cohort studies of outdoor air pollution have commonly used the CPH Model to relate survival experience to exposure while simultaneously controlling for other well known mortality risk factors. The model has the form ( l) ( t) ( l) ( t) exp T x ( l) ( t) i 0 i Hazard function or instantaneous probability of death for the i th subject in the l th strata. Baseline hazard function, common to all subjects within a strata. Regression equation that modulates the baseline hazard. The vector X i (l) contains the risk factor information related to the hazard function by the regression vector β which can vary in time. Note: We have extended this basic model to deal with random effects (spatial clustering), spatial autocorrelation, and allow for non-parametric spatial smoothing.

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34 Further extension of the Cox Proportional Hazards model to allow for random effects (spatial clustering) and to include spatial socioeconomic and environmental (contextual) variables at two spatial levels (zip code and MSA). Contextual variables included: Poverty (%), Income disparity (Gini), Median Household income, Unemployment (%), Not white (%), Grade 12 education (%), Air conditioning (%). Results: Contextual variables do no reduce the PM 2.5 -mortality effect estimates

35 Comparisons of PM 2.5 -mortality effects estimate over time with improving methods. Sources Data/ periods Model Strata Lave/Seskin 1977, Ozkaynak/ Thurston 1987 Pope et al. AJRCCM 1995 Krewski et al. HEI 2000 Pope et al. JAMA 2002 Krewski et al. HEI 2009 U.S. pop.- based mortality rates ACS CPS-II cohort/ ACS CPS-II cohort/ ACS CPS-II cohort/ OLS or WLS cross-sectional regression models Standard Cox proportional hazards model Random Effects Cox proportional hazards model Random Effects Cox proportional hazards model Individual risk factor variables Ecological/contextual spatial variables NA None Various including: Population, population density, percent elderly, none white, poverty levels, etc. Age, Sex, Race Age, Sex, Race Age, Sex, Race smoking, education, marital status, BMI, alcohol, dust/fume exposure smoking, education, marital status, BMI, alcohol, occupation/ occupational exposure, diet smoking, education, marital status, BMI, alcohol, occupation/ occupational exposure, diet Spatial smoothing? % increase/10 µg/m 3 All- Cardio- Cause pulmonary No ~ None No 7 (4-10) 12 (7-17) None Yes 6 (2-11) 9 (3-16) Poverty, income disparity, household income, unemployment, none white, education, air conditioning at two levels of spatial scale (Zip Code, Metro) No 6 (4-8) 13 (10-16)

36 Other cohort studies have shown associations between exposure to fine PM and increased risk of cardiovascular death. 190 Percent increase in mortalily risk (95% CI) Six Cities (Dockery et al 1993; Krewski et al. 2000; Laden et al. 2008) Six-Cities studies Six Cities, Medicare (Efim et al. 2008) ACS studies Other studies Pope et al. 1995; Krewski et al. 2000; Pope et al. 2002, 2004; Jerrett et al. 2005; Krewski et al. 2009) ACS LA ACS Medicare (Efim et al. 2008) U.S. Medicare; East/Central/West (Zegar et al. 2008) All Cause CPD CVD IHD AHSMOG, Males (McDonnell et al. 2000) VA, Hypertensive, Males (Lipfert et al. 2006) 11 CA county, elderly (Enstrom 2005) French PAARC (Filleul et al. 2005) Geman women (Gehring et al. 2006) Dutch Cohort (Beelen et al. 2008) Nurses' Health Study (Puett et al. 2008) Cal. Teachers Study (Ostro et al. 2009) Six Cities ACS LA AHSMOG, Males (McDonnell et al. 2000) French PAARC (Filleul et al. 2005) Geman women (Gehring et al. 2006) Cal. Teachers Study (Ostro et al. 2009) Six Cities ACS Women's Health Initiative (Miller et al. 2007) AHSMOG, Female (Chen et al. 2005) Oslo, men and women, (Naess et al. 2007) Oslo, men and women, (Naess et al. 2007) Dutch Cohort (Beelen et al. 2008) Nurses' Health Study (Puett et al. 2008) ACS LA Cal. Teachers Study (Ostro et al. 2009)

37 Women s Health Initiative Study All Cause CPD CVD IHD Percent increase in mortalily risk (95% CI) Lianne Sheppard Joel Kaufman

38 190 All Cause CPD CVD IHD Lung Cancer Nurses Health Study: Puett et al. Am. J. Epidemiology 2008 Percent increase in mortalily risk (95% CI) Stronger association with CVD than with all cause. Frank Speizer

39 Percent increase in mortalily risk (95% CI) All Cause CPD CVD IHD Lung Cancer Netherlands, Germany, Norway studies: Beelen et al. EHP 2008 Gehring et al. Epidemiology 2006 Naess et al. Am. J. Epidemiology 2007 Again, positive associations, generally Stronger for cardiovascular disease. Brunekreef (summary paper) JESEE 2007 Bert Brunekreef

40 U.S. Medicare Cohort Studies U.S. Medicare Cohort studies: Eftim et al. Epidemiology 2008 Zegar et al. EHP 2008 All Cause CPD CVD IHD Percent increase in mortalily risk (95% CI) Cohorts of Medicare participants cities of the 6-cities and ACS study, plus all U.S

41 Survival Probability Survival curves based on projected U.S life tables and alternative excess risk assumptions Baseline survival curve, life expect.= RR from Pollut, ages < 45 unaffected; life expect.= RR from Pollut., infants unaffected; life expect.= RR from Pollut., infants affected; life expect. = RR from Smoking from age 20; life expect.=67.9 Note: 1.15 RR from Polut., infants uneffected; life expect=74.6 (curve not shown) Age Brunekreef 1997 Pope 2000

42 Brief methodological outline of air pollution epidemiological studies: Studies of short-term exposure Episode Population-based daily time-series Panel-based acute exposure Case-crossover Studies of long-term exposure Population-based cross-sectional Cohort-based mortality Cohort- and panel-based morbidity Case-control studies Intervention/natural experiment Exploit temporal variability Exploit spatial variability Exploit both temporal and spatial variability

43 Southern California Children s Health Study Effects of air pollution on children s health, especially lung function growth. David Bates, Advisor W. James Gauderman John Peters

44 Southern California Children s Health Study, has shown that air pollution impacts lung development in children. Gauderman et al Children living in cities with higher air pollution and living near major traffic sources showed greater deficits in lung function growth.

45 AJRCCM 2001

46 Brief methodological outline of air pollution epidemiological studies: Studies of short-term exposure Episode Population-based daily time-series Panel-based acute exposure Case-crossover Studies of long-term exposure Population-based cross-sectional Cohort-based mortality Cohort- and panel-based morbidity Case-control studies Intervention/natural experiment Exploit temporal variability Exploit spatial variability Exploit both temporal and spatial variability

47 Follow up analysis of the Six-Cities cohort: Air pollution reductions reduced risk of death Kingston Topeka Steubenville Portage St. Louis Watertown Reduction in fine particulate air pollution: Extended follow-up of the Harvard Six Cities Study Laden, Schwartz, Speizer, Dockery, 2006

48 Copper Smelter Strike, Mid July 1967 March 1968 Adapted from: Trijonis, John. Atmospheric Environment 1979

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51 Survival Probability Survival curves based on projected U.S life tables and alternative excess risk assumptions Baseline survival curve, life expect.= RR from Pollut, ages < 45 unaffected; life expect.= RR from Pollut., infants unaffected; life expect.= RR from Pollut., infants affected; life expect. = RR from Smoking from age 20; life expect.=67.9 Note: 1.15 RR from Polut., infants uneffected; life expect=74.6 (curve not shown) Age Brunekreef 1997 Pope 2000

52 Do cities with bigger improvements in air quality have bigger improvements in health, measured by life expectancy? Fine-Particulate Air Pollution and Life Expectancy in the United States January 22, 2009 C. Arden Pope, III, Ph.D., Majid Ezzati, Ph.D., and Douglas W. Dockery, Sc.D. - Matching PM 2.5 data for and in 51 Metro Areas - Life Expectancy data for and in 211 counties in 51 Metro areas - Evaluate changes in Life Expectancy with changes in PM 2.5 for the 2-decade period of approximately

53 Covariates included in the regression models Changes in socio-economic and demographic variables (from U.S. Census Data): Per capita income Population 5-yr in-migration High-school graduates Urban population Black proportion of population Hispanic proportion of population Proxy cigarette smoking variables available for all 211 counties COPD mortality rates Lung Cancer mortality rates Survey-based metro-area estimates of smoking prevalence National Health Interview Survey ( ) Behavioral Risk Factor Surveillance System ( ) Matching data available for only 24 of 51 metro areas

54 Clustered standard errors (clustered by the 51 metro areas) were estimated for all models except for analysis that included only the 51 largest counties in each metro area.

55 A 10 µg/m 3 decrease in PM 2.5 was associated with a 7.3 (± 2.4) month increase in life expectancy. This increase in life expectancy persisted even after controlling for socio-economic, demographic, or smoking variables

56 Residual changes in LE controlling for covariates B Reduction in PM 2.5,

57 Air Pollution Reduction: Is it Real and Does it Work? Yes