2. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Health paradigms
• Specific or general?
• Recurring issues
– Summary
3. Epidemiology
• What is epidemiology?
– Study of the distribution and determinants of health-
related states and events in populations
• Includes physiologic states, psychological states, and
positive outcomes
– Clinical medicine also addresses health and disease
in individuals, but the unique aspect of epidemiology
is its focus on population distributions
5. Distribution of health
• Distribution – breast cancer
Incidence Rates by Race
Race/Ethnicity Female
All Races
White
Black
Asian/Pacific Islander
American Indian/Alaska Native
Hispanic
127.8 per 100,000 women
132.5 per 100,000 women
118.3 per 100,000 women
89.0 per 100,000 women
69.8 per 100,000 women
89.3 per 100,000 women
6. Obesity Trends Among U.S. Adults
199
9
200
9
199
0
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
Distribution of health
7. Determinants of health
• World Health Organization
• The determinants of health include:
– the social and economic environment,
– the physical environment, and
– the person’s individual characteristics and behaviours
9. Determinants of health
Results The leading causes of death in 2000 were tobacco (435000
deaths; 18.1%of total US deaths), poor diet and physical inactivity (400000
deaths; 16.6%), and alcohol consumption (85000 deaths; 3.5%). Other
actual causes of death were microbial agents (75000), toxic agents (55000),
motor vehicle crashes (43000), incidents involving firearms (29000), sexual
behaviors (20000), and illicit use of drugs (17000).
10. What brings you here?
• What “determinants” are you interested in?
• What “health related states and events” are you
interested in?
11. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Disease paradigms
• Specific or general?
• Recurring issues
– Summary
12. Epidemiologic terms
• “Determinants” of health also called
– Exposures (used generally)
– Treatment (used generally)
– X (as in X and Y in a statistical model)
– A (as in A and W and Y in a statistical model – A as
exposure/treatment of interest, W as nuisance, Y as
outcome)
X Y
13. Epidemiologic terms
• “Health related states and events” also called
– Outcome (used generally)
– Disease (used generally)
– Y (as in X and Y in a statistical model)
• Many terms seem to imply a yes/no
categorization but they encompass any kind of
health outcome (continuous, categorical, binary
measures)
X Y
14. Epidemiologic terms
• Covariates
– Other variables that have some influence on the
relation between an exposure and outcome
– X (“other” Xs) generically
– W if the influence on the relation is a nuisance
distortion you want to remove (aka, confounding)
– Z if the influence on the relation is of interest (e.g.,
effect modification, mediation)
15. Epidemiologic terms
• Strata
– Subgroups of a population separated according to
specified criteria such as age groups, sex etc.
• Stratification
– The process of separating a population into these
groups
16. Epidemiologic terms
• Associations distinguished from effects
– An association tells us about probabilities of past
events
• Carrying matches is associated with lung cancer
– An effect is causal and it tells us how probabilities
change if conditions change
• If you remove matches from pockets in the population, does
the rate of lung cancer decrease?
17. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Health paradigms
• Specific or general?
• Recurring issues
– Summary
19. Questions and answers
• Types of questions we can ask/answer with
epidemiologic methods (Rose 1985)
• Clinician’s question
– “Why did this patient get this disease at this time?”
• Causes of cases
– “Why do some individuals have hypertension?”
• Causes of incidence
– “Why do some populations have so much hypertension whilst in
others it is so rare?”
22. Questions and answers
• Determinants of the mean are the causes of incidence
• Determinants of location within the distribution are the
causes of cases
• Epidemiologic approaches can be used to identify either
types of determinants – but are being applied in the
service of fundamentally different questions
• Depending on the question you ask you get a different
answer
23. Questions and answers
• What makes these fundamentally different
questions?
– If a population is just an group of individuals, how are
the causes of cases and the causes of incidence
different?
– In a study focused on causes of cases you accept as
constant background aspects the group(s) to which
individuals belong that cause disease
– In a study focused on causes of incidence you
explicitly examine the effects of aspects of the group
(s) to which individuals belong
• Aspects of groups often driven by fundamental
characteristics of a society/culture
24. Questions and answers
• Example – causes of cases vs causes of incidence
• Obesity – today’s big epidemic – what is the cause?
– Epidemiologic studies of twins suggest 2/3 of obesity attributable
to genetics
25. Questions and answers
– US obesity prevalence has increased from 12% to 19% in less
than 10 years
– Are genetics behind this?
– Must be caused by changing environmental factors
26. Questions and answers
• Which is the right answer – genes or environment?
• Both the right answers to different questions
– Genes tell us about the causes of cases
– Environment tells us about the causes of incidence
• Where you focus your lens determines what you can see
– What exposure and outcome studied
– How much does the exposure vary across the population(s)
studied over the time studied
27. Questions and answers
P Menzel. Hungry Planet. What the World
Eats. Ten Speed Press, 2005.
Egypt
USA
Ecuador
28. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Health paradigms
• Specific or general?
• Recurring issues
– Summary
29. Paradigms
• Health paradigms shape epidemiology and
epidemiology shapes them
• Paradigms of health
– Sanitary (18th, 19th c) – miasma
– Infectious (20th c) – germ theory
– Chronic diseases come to fore in developed countries
• Multifactorial, lists of risk factors…
• But wait… some of them are infectious?
30. Paradigms
• Increases in peptic ulcer disease in first half 1900s was
of great concern
• Thought to be a “disease of civilization”
• Susser and Stein documented birth cohort patterns
suggesting peptic ulcer disease mortality had peaked
and had started to decline as of 1960
– Met with great skepticism
• Interpretation strongly influenced by current paradigm –
chronic disease was non-infectious and dependent
lifestyle in adulthood
31. Paradigms
Mervyn Susser
• “concluded that the apparent multifactorial
aetiology of peptic ulcer – with contributions from
diet, alcohol, cigarette smoking, emotional strain,
personality and genotype did not ‘exclude the
possibility that a major single causal factor
awaits discovery’” (Davey Smith, Ebrahim 2001)
32. Paradigms
• Heliobacter pylori infection was identified as the
cause
• Cause identified by a pathologist and clinician
with no input from the extensive body of
epidemiologic research
– Defied a long held biological tenet – bacteria cannot
survive in the acidic environment of the stomach
33. Paradigms
• Went against the paradigm of chronic disease
causality
• Contradicted a biological tenet
34. Paradigms
• Continuing discussion in epidemiology about
whether health paradigms, conceptual
frameworks etc. ground us or constrain us
– Some argue epidemiology is at its best documenting
patterns and associations without being influenced by
existing paradigms and theories
– Others say it is meaningless without theory
35. Paradigms
• “Scientists rely heavily on unstated criteria, or degrees of
confidence… in particular hypotheses or approaches,
and investigators are only sometimes fully able or willing
to acknowledge them… They include all of the vanities,
vested interests, hunches, experiences, politics,
careerism, grantsmanship tactics, competing cadres of
collaborators, imperfections, and backgrounds of the
scientists investigating problems at any given time.”
(Buchanan et al. 2006)
37. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Health paradigms
• Specific or general?
• Recurring issues
– Summary
38. Specific or general?
• Is it reasonable to expect uniform effects of
exposures on health outcomes across
populations and across time?
• In most instances probably not
– But if not, then we are stuck with the criticism that in
the face of inconsistent results we simply mobilize an
auxiliary hypothesis to explain the discrepancy
39. Specific or general?
• Income inequality and health
– Controversial area of research
– The greater the dispersion of income within a given
society, the lower the life expectancy and the higher
the mortality
40.
41. Specific or general?
• Theories about why this would be the case
– Psychosocial interpretation – perceptions of relative
disadvantage
– Neomaterial – structural causes of income inequality
also cause worse health outcomes
42. Specific or general?
• Large systematic review
– “…little support for the idea that income inequality is a
major, generalizable determinant of population health
differences within or between rich countries.” (Lynch
et al. 2004)
– Relations with homicide more consistent
– Relations among US states more consistent
• US has a unique history (slavery, segregation etc) so argued
to be a product of these structural causes
43. Specific or general?
• A recent meta-analysis was conducted
suggesting that there is a consistent relation
between income inequality and health across
countries, but it has a threshold shape (Kondo et
al. 2009)
44. Specific or general?
• “The results also support the threshold effect
hypothesis, which posits the existence of a
threshold of income inequality beyond which
adverse impacts on health begin to emerge.”
47. Specific or general?
• Do we conclude that there is little support for
income inequality as a generalizable determinant
of health?
• Do we conclude that income inequality is a
generalizable determinant with a threshold
shape?
48. Introduction outline
– Definition of epidemiology
– Epidemiologic terms
– Course in context
• Questions and answers
• Health paradigms
• Specific or general?
• Recurring issues
– Summary
49. Recurring issues
• Struggle to get from association to cause in
epidemiology
– Is it even reasonable to try?
– When do we make the leap?
– Do we make it alone? (ie, establish causality based
only on epidemiologic evidence)
50. Recurring issues
• Documentation of risk without studying
mechanism in epidemiology (“black box”
criticism)
– Is this informative?
– Can and should we be studying mechanisms?
51. Recurring issues
• Relationship to public health
– We provide the methodologic tools for research that
can inform public health decisions
– We can also use tools for research that may be
interesting and important scientifically but largely
irrelevant to public health
• Relationship to the public
– Lack of understanding of what we do and how to
interpret it by media and public
– How can we improve this?
52.
53. Move to confounding?
• Discordant trial and observational study findings
– Random Medical News cartoon
– “apparently indiscriminate identification of particular
aspects of daily life as dangerous to health”
– Worst cases are when associations seen repeatedly
in observational research are not realized based on
trials
– People observed doing certain behaviors are so
different from those not doing them and the
complexity of these differences not accounted for
adequately with statistical procedures
54. Move to analyzing epi data?
• Embracing and backlash against new statistical
developments (last 20 yrs or so) Fancy models
cannot do away with limitations of the data
– Most trained in epi do not get to do original data
collection – generation of “technicians” being trained
– However, statistical methods available shape the
questions we ask and answer and that is not a good
reason to ask a particular question in a particular way
56. Summary
• Perspective on where the field of epidemiology
sits currently and what it struggles with
• Setting the stage for the ways we will present
issues in this course
– Example: emphasis on causality and causal
frameworks and understanding the issues in moving
from association to cause
– Example: emphasis on meaning of the strength of
association to give better perspective on differences
in associations observed across studies
57. Cites
• Buchanan AV, Weiss KM, Fullerton SM. Dissecting complex disease: the
quest for the philosopher’s stone? Int J Epidemiol. 2006;35:562-71.
• Davey Smith G, Ebrahim S. Epidemiology – is it time to call it a day? Int J
Epidemiol. 2001;30:1-11.
• Greenland S, Gago-Dominguez M, Castelao JE. The value of risk factor
(“black-box”) epidemiology. Epidemiology. 2004;15:529-35.
• Rose G. Sick individuals and sick populations. Int J Epidemiol. 2001;30:427-
32.
• Savitz DA. In defense of black box epidemiology. Epidemiology. 1994;5:
550-2.
• Scrabanek P. The emptiness of the black box. Epidemiology. 1994;5:553-5.
• Taubes G, Mann CC. Epidemiology faces its limits. Science. 1995;269:16-
169.
• Weed DL. Commentary: rethinking epidemiology. Int J Epidemiol. 2006;35:
583-6.
