מצגת מתוך הרצאה שקיימה פרופסור פרנסין ליידן באיגוד ערים לאיכות סביבה בחיפה על האתגרים וההזדמנויות בבריאות הסביבה – חקר סרטן

1. Challenges and Opportunities
in Environmental Epidemiology
of Cancer
Francine Laden, ScD
Associate Professor of Environmental Epidemiology
Harvard School of Public Health
and
The Channing Laboratory
Brigham and Women’s Hospital, Harvard Medical School

2. Structure of Talk
• Challenges of environmental
epidemiology
• Example: Diesel exhaust and lung
cancer

3. How do you define ENVIRONMENT?

4. Environmental Exposures are:
• Not genetic
_______________________________________________________________________________________________________
• Pollution as opposed to life style
• Passive as opposed to active
• Involuntary as opposed to voluntary
• External as opposed to internal

5. A Few More Definitions:
• The ambient environment
– By the general population
• The occupational environment
– By the working population

6. Challenge:
Pollutants in the Ambient Environment are-
• Ubiquitous
– Hard to identify unexposed people
• Low levels
– Tight range
– Measurement error
• Passive
– Potentially unknown to participant
– Hard to identify unexposed AND exposed
people

7. Challenge:
What is the Responsible Exposure?
“The Environment caused my cancer”
“Living in/working at _________
caused my cancer”

8. Challenge:
What to Measure:
• What is the chemical of interest?
• Is there a specific marker for your
exposure?
• What is the causative aspect of your
exposure?
• Is there a biomarker available?

9. Challenge:
When to Measure?
• Cancer is generally a disease of long
latency
• Timing during life cycle may be critical
• Usually performing measurements after
the fact

10. Challenge:
Who to Measure?
• Can you sample a representative
group?
• How do you define the boundaries of
your cluster (in both space and time)?

11. Example:
Diesel Exhaust Exposure and
Lung Cancer

12. Outline
• What is diesel exhaust?
• Overview of animal and human cancer
studies
• The Trucking Industry Particle Study

13. Diesel Exhaust
“a complex mixture of particles and gases”
• Vapor Phase • Particulate Phase
Carbon Monoxide Elemental Carbon
Carbon Dioxide Sulfates
Sulfur Dioxide (from Hydrocarbons
fuel)
Nitrogen Oxides PAH Compounds
Aldehydes (odor)
Hydrocarbons
PAH Compounds
PAH= Polycyclic Aromatic Hydrocarbons

14. Diesel Particle
CO2 CO Elemental
SO2 Nitrogen oxides Carbon (EC)
Organic
Carbon
(OC)
On surface
(Polycyclic Aromatic Hydrocarbons)
(PAH Compounds)
Health Effects Institute, 1995

15. What to Measure?
• Fine particle mass (PM2.5): < 2.5 µm
• PM1.0 mass: < 1.0 µm
• Elemental carbon core (EC mass)
• Organics on particle (OC mass)
• Gaseous pollutants (NO2 = vehicle
exposure)
• PAHs (e.g. naphthalene)
• Particle number/surface area

16. Or Smell:

17. Animal Lung Cancer Studies
• Dose related increase in lung tumors at high
levels of exposure (3500 µg/m3) in rats
• Negative results in other rodent species
• Results not specific to particles with associated
organics (carbon particles )
• Mechanism:
– In rats: overload of particle clearance mechanisms
and inflammatory changes precede the development
of lung cancer
– But…inflammation is not part of the human lung
cancer pathology

18. Human Lung Cancer Studies
• ~40 studies with 20%-50% elevated risk in
diesel associated occupations
– Truck Drivers
– Railroad Workers
– Bus Garage And Transport Workers
– Dock Workers
– Miners
• EPA, IARC, WHO
– likely or probable carcinogen
• California
– Toxic Air Contaminant (definite)

19. Previous Truck Driver Studies
“Null”
Decreased risk Increased risk
Statistically significant
solid circle = smoking adjusted open circle = smoking unadjusted

20. • Diesel exhaust is likely to be carcinogenic to
humans by inhalation and this hazard applies
to environmental exposures
• Conclusions are based on the totality of
evidence from human, animal, and other
supporting studies
• Epidemiologic studies were done in
occupational cohorts, but occupational and
environmental levels overlap

21. How the Previous Epi Studies
Measure Exposure:
• Exposure definitions
– Single job title or usual job
– Yearly job, years of employment
• Source of information
– Self-report, census, next-of-kin, death certificate
– Union or work record
• Measurement of current exposure
– Used to rank and validate exposure categories
– Not used in primary analysis
– No historical measurements

22. The Trucking Industry Particle Study
(TrIPS)
Funded by the National Cancer Institute

23. Research Questions
• Is lung cancer risk increased among
diesel exposed workers?
• What is the quantitative exposure-
risk relationship?

24. Population
• Four national unionized less-than-
truckload trucking companies
– Cooperation from both management and
labor (Teamsters)

25. Study Design
• Retrospective cohort study 1985-2000
• National assessment of current
exposures
• Smoking survey to representative
sample of workers

26. Epidemiologic Component
• From company records:
– Identified all unionized workers working ≥
1 day in 1985 (58,326)
– Obtained personal work histories:
chronological listing of job titles and work
locations (terminal address, size)
• Mortality follow-up 1985-2000: NDI
– Date of death
– Cause of death – primary and underlying

27. Exposure Assessment Component
• Randomly selected 36 large terminals
(>100 employees)
• Each was grouped with 1-2 smaller
terminals located within 50 miles
• 7 day sampling trips
• Measured PM2.5, EC and OC in PM1.0
at each work location and upwind of the
terminal

28. Trucking Terminals

29. Freight Terminal
Wind Emission Sources
Air
Pollution Incoming Outgoing
Repair
Trailers Trailers Shop
Freight
Tractors
(idling)
Forklift
Tractor
Dock Yard
(cab) Dock
Trailer Office
Offices &
Lunchroom
Pickup & Long Haul
Pickup & Long Haul
Delivery (rural)
Delivery (rural) Emission sources

30. Wind
Freight Terminal Operations
Air Jobs Mechanic
Pollution
Supervisor Repair
Freight
Shop
Tractors
(idling)
Forklift
Dock Yard
Dock Dockman
Office Supervisor
Drivers:
Offices & Dispatcher Pickup &
Lunchroom Manager delivery
Clerks Long-haul
Emission sources

39. Linking Exposure to Epidemiology
• Information available for everybody: job title,
terminal location and characteristics,
calendar year, years of work
• Develop statistical model to extrapolate
exposure for each individual
– Describes how above factors affect exposure
intensity
– Historic records used to estimate changes in
factors

40. Historical Exposures
• Traffic exposure in cities
– Trend for traffic emissions and traffic density
• Truck fleet changes with time
– Emissions by engine type, cab design, exhaust
leaks
• Diesel fuel changes with time
– Sulfur, aromatic, and component contents
• Other exposure factors
– Changes in other sources
– Air pollution

41. Extrapolation of Historical Exposures
• Validation of the model
– Estimate 1989 exposures at sites of NIOSH
surveys
– Data from older operations
• Potential limitations
– Absence of data on exposures before 1989
– Uncertainty in simulations of older exposures
– Missing company records
– Crude historic air pollution data

42. Comparisons to the
General Population
• Overall mortality:
– SMR=0.72 (95%CI=0.70-0.74)
• Lung cancer mortality
– Overall: SMR=1.04 (95%CI=0.97-1.12)
– All drivers: SMR=1.10 (95%CI=1.02-1.19)
– Dockworkers: SMR=1.10 (95%CI=0.94-
1.30)
Laden et al. EHP 2007

43. Smoking Rates:
Trucking versus General population

44. Cohort Study
• Exposure = job title
• Dose = cumulative years of work
• Comparison group = other job titles

45. Summary of Personal Exposure
Measurements (µg/m3)
EC PM2.5
N GM GSD GM GSD
Clerk 15 0.09 9.98 5.96 1.86
Dockworker 342 0.76 2.13 18.73 1.75
P&D 366 1.09 2.48 16.20 1.82
Long haul 173 1.12 1.91 19.96 2.30
GM=geometric mean; GSD=geometric standard deviation
Smith et al. JEM 2006

46. Lung Cancer HRs for +1 yrs of work
Job title PY Deaths HR (95%CI)*
Long haul 161,503 323 1.15 (0.92, 1.43)
P&D 139,054 233 1.19 (0.99, 1.42)
Dock 147,513 205 1.30 (1.07, 1.58)
Combo 96,543 150 1.40 (1.12, 1.73)
Mechanic 25,523 38 0.95 (0.66, 1.38)
Hostler 29,947 29 0.99 (0.68, 1.45)
Clerk 24,728 15 0.55 (0.32, 0.95)
Other jobs 13,040 12 0.89 (0.48, 1.63)
* Hazard ratio calculated using regression coefficients from a multivariate Cox proportional hazards
regression model stratified on age in 1985, decade of hire, and calendar time, with risk sets by attained
age, adjusted for the healthy worker survivor effect (total years on work, years off of work), race, and
census region.

47. Increased Risk with Years of Work
Long-haul drivers P&D drivers
2.5 % Δ/yr wrk 3.6 % Δ/yr wrk

48. Increased Risk with Years of Work
Dockworkers Combo Worker
3.4 % Δ/yr wrk 4.0 % Δ/yr wrk

49. Implications
• Increased risk of lung cancer for job
titles exposed to “freshly generated
exhaust”
• Easily extrapolated to the general
population driving on the same
roadways

50. Addressing the Challenges
• Ubiquitous, low level, passive exposures
• Responsible exposure
• What to measure
• When to measure
• Who to measure

51. Acknowledgments
• HSPH and HMS • U of Wisconsin
• Eric Garshick • Jamie Shauer
• Thomas Smith
• Mary Davis • Advisory Board
• Ellen Eisen • John Peters
• Jaime Hart • David Savitz
• Kevin Lane • Hans Kromhout
• Serena Hon • Vicki Stover Hertzberg