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What is a cause?
Epidemiology matters: a new introduction to methodological foundations
Chapter 7
Seven steps
1.
Define the population of interest
2.
Conceptualize and create measures of exposures and health
indicators
3.
Take a sample of the population
4.
Estimate measures of association between exposures and health
indicators of interest
5. Rigorously evaluate whether the association observed
suggests a causal association
6.
Assess the evidence for causes working together
7.
Assess the extent to which the result matters, is externally valid,
to other populations
Epidemiology Matters – Chapter 1
2
Early conceptions of cause
“for now, I will stretch out mine hand, that I may smite thee and thy
people with pestilence”
God, from Exodus (9:14)
Epidemiology matters – Chapter 7
3
1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
4
1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
5
Motivating examples

The Uncle Joe example

“My mother smoked in pregnancy - no one knew the
health dangers back then - and I’m just fine. All of these
warnings about smoking during pregnancy are
overdone.”
If one person smoked in pregnancy with no adverse
consequences for their offspring, can we conclude that
smoking in pregnancy is not harmful?
Epidemiology matters – Chapter 7
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Epidemiology matters – Chapter 7
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Unexposed
Exposed
Epidemiology matters – Chapter 7
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Unexposed
Exposed
Unexposed
with disease
Epidemiology matters – Chapter 7
Exposed
with disease
9
Epidemiologists understand disease causation
to be a multifactorial process
Epidemiology matters – Chapter 7
10
1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
11
Example: A man’s depression

Man developed depression

Personal history:

Born Boise, Idaho 1965

Parents working class

Youngest of 5 children

Trouble with the law growing up

Married at 25, divorced 4 years ago

Lost job 2 years ago
What are the causes of the man’s depression?
Epidemiology matters – Chapter 7
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Would the depression have occurred if we kept everything
about his life the same, but changed one detail?
1.
If everything about the man stayed the same, but the plant
had not closed, would the depression have occurred?
2.
If everything about the man had stayed the same, but the
divorce had not occurred, would the depression have
occurred?
3.
If everything about the man had stayed the same, but his
parents had more resources in his childhood, would the
depression have occurred?
Epidemiology matters – Chapter 7
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Counterfactual

The counterfactual is the condition that is
counter to the fact

A factor is a cause if the outcome would not
have occurred in the absence of that factor,
holding all other things constant, including
space and time.
Epidemiology matters – Chapter 7
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What is a cause?
1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
Epidemiology matters – Chapter 7
15
Non-diseased
Epidemiology matters – Chapter 7
Diseased
16
Example: Individual diabetes
Combination of causes in
individuals
Person 1. Obese weight, lack of
preventive care, diabetes family
history, 20 pack-years smoking
Person 2. Poor nutritional
education, diabetes family history,
high blood pressure, advanced age
Person 3. Obese weight, diabetes
family history, high blood pressure
Epidemiology matters – Chapter 7
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Example: Individual diabetes
Is each factor necessary?
Is each factor sufficient?
For each individual
case, all component
causes are necessary
for that individual, but
none are sufficient.
Epidemiology matters – Chapter 7
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Causes and the individual marble game

Each marble is a component cause

But, one marble is rarely sufficient to cause disease

A particular marble set can be a sufficient cause for
disease

There can be more than one marble set that become a
sufficient cause

Causes are rooted in a counterfactual definition, each
marble is a necessary cause of disease for that
particular sufficient cause set
Epidemiology matters – Chapter 7
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Necessary and sufficient causes for
populations

Necessary if all cases of disease require the cause in
order for disease to onset

Sufficient if all individuals exposed to the cause will
acquire the disease

Causes can be

necessary and sufficient

unnecessary but sufficient

necessary but insufficient

unnecessary and insufficient
Epidemiology matters – Chapter 7
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Necessary and sufficient causes
Trisomy 21 and Down Syndrome
All individuals with three copies of the 21st
chromosome will evidence Down Syndrome. Trisomy
21 is thus sufficient for DS.
All individuals with Down syndrome have three
copies of the 21st chromosome. Trisomy 21 is thus
necessary for DS.
Epidemiology matters – Chapter 7
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Necessary but insufficient causes
Alcohol consumption and alcoholism
Not all individuals who consume alcohol will develop
alcoholism. Alcohol consumption is thus insufficient for
alcoholism.
However, all individuals with alcoholism will have
consumed alcohol. Alcohol consumption is thus
necessary for alcoholism.
Epidemiology matters – Chapter 7
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Unnecessary but sufficient cause
Hysterectomy and pregnancy prevention
All women who have a hysterectomy are unable to
become pregnant. Hysterectomy is thus sufficient for
pregnancy prevention.
Not all pregnancies are prevented through
hysterectomy. Hysterectomy is thus unnecessary for
pregnancy prevention.
Epidemiology matters – Chapter 7
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Unnecessary and insufficient cause
Smoking and lung cancer
Not all individuals who smoke will develop lung cancer.
Smoking is thus insufficient to cause lung cancer.
Not all lung cancer cases are smokers. Smoking is thus
unnecessary to cause lung cancer.
Epidemiology matters – Chapter 7
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1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
25
Collecting marbles across the life course

People can accumulate marbles

At birth

In adolescence

During young adulthood

At older adulthood

At one point vs. slow accumulation over time
Epidemiology matters – Chapter 7
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Collecting marbles across the life
course: Example
Infancy
Collecting throughout life
 tobacco smoke in utero



Childhood
chronic poverty, chaotic
home environment in
childhood
Adolescence
cigarette smoking starts
in adolescence
Adulthood
]
poor nutrition in
adulthood
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Marbles are not independent

Shared across individuals

One person’s marble collection may influence
another person’s marble collection

Example, person-to-person infectious disease
transmission
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Examples of shared marbles

Unhealthy food environment

Community violence

Social norms around substance use and cigarette
smoking; e.g., adolescents are more likely to begin
smoking if an influential peer begins smoking

Policies and laws managing access to quality health
care
Epidemiology matters – Chapter 7
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Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
Epidemiology matters – Chapter 7
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Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
Epidemiology matters – Chapter 7
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Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
Epidemiology matters – Chapter 7
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Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
Epidemiology matters – Chapter 7
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Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
34
Epidemiology matters – Chapter 7
Sharing marble exposures
Person 2
Person 1
Person 3
Person 4
35
Epidemiology matters – Chapter 7
Summary: marble analogy

Individuals share marbles and transmit marbles from
one space to another

Within each person’s space, there remains a
complete set of marbles that is necessary to cause
disease.

One person’s complete set of marbles may differ
from another persons
Epidemiology matters – Chapter 7
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Summary: causes in time and space

At population level need to understand exposure to
unhealthy environments and transmission of disease
to understand and intervene to prevent adverse
health conditions

By identifying marbles that are common across many
marble spaces, we can identify the exposures and
environments for intervention and prevention
efforts.
Epidemiology matters – Chapter 7
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1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
38
Public health implications

Marble example, individual

Each individual’s set of marbles that caused disease may be unique,
with or without overlap across individuals

Each marble was necessary for that person to develop the disease
when and how he or she did

Marble example, population

Epidemiologists look for the ‘marbles’ that are most common across
individuals with disease compared to those without disease

Preventing any one of the marbles can prevent disease in that
individual

Prevent common marbles can prevent more disease in more
individuals
Epidemiology matters – Chapter 7
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Public health target?
Exposure combinations and disease causation
Which cause should we try and prevent?
Epidemiology matters – Chapter 7
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Public health target?
Remove cause
W
Person 1 and 3 saved
X
Person 1 and 2 saved
Y
Person 1, 2, and 3 saved
Z
Person 2 and 3 saved
Target cause Y for prevention to save most people
Epidemiology matters – Chapter 7
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Summary: public health implications

At the population level causes may be necessary
and/or sufficient, but need not be either

Multifactorial and complex diseases are often caused
by many factors necessary in at least one person

Identifying factors, i.e., component causes, common to
most individuals has the greatest impact on reducing
disease for largest amount of people
Epidemiology matters – Chapter 7
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1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
43
From marble space to probability

Process of disease development may begin in utero
and continue until the moment that the disease
occurs

Often many causes must align for a disease to occur
in an individual
Epidemiology matters – Chapter 7
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Example: Smoking and lung cancer

Smoking is not sufficient to cause lung cancer; smoking
must act with other causes – i.e. an individual smokes,
works in a occupation with a high degree of exposure to
asbestos, has a genetic predisposition to develop lung
cancer

Another person who develops lung cancer may have a
different constellation of causes

Causes can be shared across people or be unique to a
certain person
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From marble space to probability

The idea that many causes must accumulate through
the life course before the disease manifests is, in
epidemiology, expressed as the concept of interaction

That is, if seven marbles are all necessary to cause
disease in an individual, then all of these marbles
interact with each other

By preventing exposure to even one marble, the
disease will not occur
Epidemiology matters – Chapter 7
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Example A. Diet and phenylketonuria (PKU)

Disorder: PKU, an inability to process phenylalanine
(amino acid); if untreated results in altered
appearance, hyperactivity, mental retardation, and
seizures

All PKU patients have specific maternal and paternal
genetic sequence alone will not cause PKU
What type of cause is genetic sequence?
Epidemiology matters – Chapter 7
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Diet and phenylketonuria (PKU)

Disorder: PKU, an inability to process phenylalanine
(amino acid); if untreated results in altered
appearance, hyperactivity, mental retardation, and
seizures

All PKU patients have specific maternal and paternal
genetic sequence alone will not cause PKU
What type of cause is a PA-rich diet?
Epidemiology matters – Chapter 7
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Diet and phenylketonuria (PKU)
Only genetic
+ PA-rich diet
= PKU manifestation
Epidemiology matters – Chapter 7
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Example B. Causes of obesity

Genetic variants involved in the process of increasing and
maintaining high weight

In utero environment on obesity in childhood and
adulthood

Childhood factors including food insecurity, socioeconomic position, availability of healthy food and food
cost

Health behaviors including high consumption of sugarsweetened beverages
Epidemiology matters – Chapter 7
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Example B. Causes of obesity
Potential causal mechanism may be
High consumption of sugar sweetened beverages + low
physical activity + genetic predisposition = obesity
There is no single cause of obesity, we need to
conceptualize causes as interacting
Epidemiology matters – Chapter 7
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Summary: Causation in nondeterministic world

Interaction: many causes must accumulate
through the life course before the disease
manifests

Necessary but insufficient causes interact for
disease to manifest in an individual

Multifaceted disease causation requires many
component causes interacting
Epidemiology matters – Chapter 7
52
1. A motivating example
2. What is a cause?
3. Disease causation – marble game
4. Disease causation – time and space
5. Public health implications
6. Disease causation in a non-deterministic world
7. Epidemiology and probability
8. Summary
Epidemiology matters – Chapter 7
53
Epidemiology is probabilistic

Deterministic “… occurrences … are causally
determined by preceding events or natural laws”*

Probabilistic “of, relating to, or based on
probability”*

Epidemiology is probabilistic

Considering component causes

Often have not identified all of the causal partners for a
sufficient cause
*Definitions: http://www.merriam-webster.com/dictionary/determinism
and http://www.merriam-webster.com/dictionary/probabilistic accessed on
9/10/2013
Epidemiology matters – Chapter 7
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Hypothetical example X,Y, Z
Reality
X, Y, and Z are all necessary and insufficient causes of disease in an individual
Component Causes
# People with component causes
Probability of disease
X
Y
Z
✔
✔
✔
10
1
✔
8
0
11
0
5
0
9
0
3
0
12
0
42
0
✔
✔
✔
✔
✔
✔
✔
✔
Epidemiology matters – Chapter 7
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Hypothetical example X,Y, Z
Reality
Component
Causes
# People with
component causes
Measured
Probability of
disease
Component
Causes
# People with
component causes
Probability of
disease
X
Y
Z
✔
✔
✔
10
1
✔
10
1
✔
8
0
✔
8
0
11
0
✔
11
0
5
0
5
0
9
0
9
0
3
0
3
0
12
0
12
0
42
0
42
0
✔
✔
✔
✔
✔
✔
✔
✔
X
Y
Z
✔
X, Y, and Z are all necessary and insufficient causes of disease in an individual
What is prevalence of disease, given exposure to X?
N exposed to X = 38 (10+8+11+9)
N exposed to X with disease = 10
Prevalence of disease : P(D|X)=10/38 = 0.26
Epidemiology matters – Chapter 7
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Transition from knowing all component causes to just
those measured takes epidemiologist from
deterministic to probabilistic
Epidemiology matters – Chapter 7
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Hypothetical example A,B,C, X,Y, Z
Reality
A,B, and C OR X, Y, and Z are all necessary and insufficient causes of disease in an individual
Component Causes
A
B
C
X
Y
Z
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
# People with
component causes
Probability of
disease
5
1
6
1
10
1
20
0
15
0
14
0
12
0
18
0
Epidemiology matters – Chapter 7
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Hypothetical example A,B,C, X,Y, Z
Reality
Component Causes
C
X
Y
Measured
# People with
component causes
Probability
of disease
Z
Component Causes
# People with
component causes
Probability
of disease
5
1
6
1
A
B
✔
✔ ✔ ✔ ✔ ✔
5
1
✔
✔ ✔
6
1
10
1
✔
10
1
20
0
✔
20
0
15
0
15
0
14
0
14
0
12
0
12
0
18
0
18
0
✔ ✔ ✔
✔ ✔
✔
✔
✔ ✔
✔ ✔
✔ ✔
✔ ✔
A
B
C
A,B, and C OR X, Y, and Z are all necessary and
insufficient causes of disease in an individual
What is probability of disease, given X?
P(D|X): 15/47, or 0.32 or 32%
Epidemiology matters – Chapter 7
X
✔
✔
Y
Z
59
Remember this?
Unexposed
Exposed
Unaffected
with disease
Affected
with disease
Higher ‘risk’ of disease given exposure to X
Probabilistic or deterministic?
Epidemiology matters – Chapter 7
61
1. Disease causation is a multifactorial process
2. A cause, necessary or sufficient
3. Disease causation, the marble game
4. Disease causation, time and space
5. Public health implications, identifying component
causes for most individuals
6. Disease causation in a non-deterministic world interaction
7. Epidemiology is probabilistic
8. Summary
Epidemiology matters – Chapter 7
62
Seven steps
1.
Define the population of interest
2.
Conceptualize and create measures of exposures and health
indicators
3.
Take a sample of the population
4.
Estimate measures of association between exposures and health
indicators of interest
5. Rigorously evaluate whether the association observed
suggests a causal association
6.
Assess the evidence for causes working together
7.
Assess the extent to which the result matters, is externally valid,
to other populations
Epidemiology Matters – Chapter 1
63
epidemiologymatters.org
Epidemiology Matters – Chapter 1
64

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