Transcript 4.CausationAssociation 427_ incomplete.ppt

Models of Disease Causation
Family and Community Medicine Department
King Saud University
Learning objectives:
At the end of this lecture you (will) be able to:
• Explain basic models of disease causation.
• Identify purpose of studying the disease process.
Purpose of studying causal models
 Studying how different factors can lead to ill health
is important to generate knowledge to help prevent
and control diseases.
 Quote Hippocrates "To know the causes of a
disease and to understand the use of the various
methods by which the disease may be prevented
amounts to the same thing as being able to cure
the disease".
12/10/2009
Dr. Salwa Tayel
Causation&Association
4
General Models of Causation
 In epidemiology, there are several models of disease
causation that help understand disease process.
 The most widely applied models are:
 The epidemiological triad (triangle),
 the wheel, and
 the web. And
 The sufficient cause and component causes models
(Rothman’s component causes model)
12/10/2009
Dr. Salwa Tayel
Causation&Association
5
The epidemiologic triad Model
 The epidemiologic triangle or triad is the traditional model of
infectious disease causation.
 It has three components: an external agent, a susceptible
host, and environmental factors that interrelate in a variety of
complex ways to produce disease in humans.
 When we search for causal relationships, we must look at all
three components and analyze their interactions to find
practical and effective prevention and control measures.
12/10/2009
Dr. Salwa Tayel
Causation&Association
6
The Epidemiologic Triad
HOST
AGENT
12/10/2009
ENVIRONMENT
Dr. Salwa Tayel
Causation&Association
7
Agent factors
•Infectious agents: agent might be microorganism—virus,
bacterium, parasite, or other microbes. e.g. polio, measles,
malaria, tuberculosis Generally, these agents must be present
for disease to occur.
•Nutritive: excesses or deficiencies (Cholesterol, vitamins,
proteins)
•Chemical agents: (carbon monoxide, drugs, medications)
•Physical agents (Ionizing radiation,…
Host factors
•Host factors are intrinsic factors that influence an individual’s
exposure, susceptibility, or response to a causative agent.
•Host factors that affect a person’s risk of exposure to an agent:
•e.g. Age, race, sex, socioeconomic status, and behaviors
(smoking, drug abuse, lifestyle, sexual practices and eating
habits)
•Host factors which affect susceptibility &response to an agent:
•Age, genetic composition, nutritional and immunologic status,
anatomic structure, presence of disease or medications, and
psychological makeup.
Environmental factors
Environmental factors are extrinsic factors which affect the agent
and the opportunity for exposure.
Environmental factors include:
 physical factors such as geology, climate,..
 biologic factors such as insects that transmit an agent; and
 socioeconomic factors such as crowding, sanitation, and
the availability of health services.
Malaria
Agent
Vector
Host
12/10/2009
Dr. Salwa Tayel
Causation&Association
11
Environment
The epidemiologic triad Model
Host:
Intrinsic factors, genetic, physiologic factors,
psychological factors, immunity
Health
or
Illness
?
Agent:
Amount, infectivity, pathogenicity,
virulence, chemical composition,
12/10/2009
Dr. Salwa Tayel
cell reproduction Causation&Association
Environment:
Physical, biological, social
12
Other Models of causation
 Web of Causation is devised to address
chronic disease – can also be applied to
communicable disease) due to multi-
factorial nature of causation in many
diseases
12/10/2009
Dr. Salwa Tayel
Causation&Association
13
Web of Causation
 There is no single cause
 Causes of disease are interacting
 Illustrates the interconnectedness of
possible causes
12/10/2009
Dr. Salwa Tayel
Causation&Association
14
Web of Causation
RS Bhopal
Web of Causation - CHD
RS Bhopal
Example of a Web of Causation
Overcrowding
Malnutrition
Exposure to
Mycobacterium
Susceptible Host
Infection
Tuberculosis
Tissue Invasion
and Reaction
Vaccination
12/10/2009
Genetic
Dr. Salwa Tayel
Causation&Association
17
The Wheel of Causation
 The Wheel of Causation de-emphasizes the
agent as the sole cause of disease,
 It emphasizes the interplay of physical,
biological and social environments. It also
brings genetics into the mix.
12/10/2009
Dr. Salwa Tayel
Causation&Association
18
The Wheel of Causation
Social
Environment
Biological
Environment
Host
(human)
Genetic Core
Physical
Environment
12/10/2009
Dr. Salwa Tayel Causation&Association
19
The sufficient cause and component causes model
Rothman’s component causes model
Necessary and sufficient causes
 A necessary cause is a causal factor whose presence is
required for the occurrence of the effect. If disease does
not develop without the factor being present, then we term
the causative factor “necessary”.Agent in Malaria:
plasmodium Falciparum
parasite is necessary factor ( always present) such as A in the previous slide.
 Sufficient cause is a “minimum set of conditions, factors
or events needed to produce a given outcome. Usually there’s no
sufficient factor “rare”.> Rabies is both necessary and sufficient.
 The factors or conditions that form a sufficient cause are
called component causes.
Dr. Salwa Tayel
12/10/2009
Causation&Association
21
Example
 The tubercle bacillus is required to
cause tuberculosis but, alone, does not
always cause it,
 so tubercle bacillus is a necessary, not
a sufficient, cause.
12/10/2009
Dr. Salwa Tayel
Causation&Association
22
Rothman’s Component Causes and
Causal Pies Model
 Rothman's model has emphasised that the causes of disease
comprise a collection of factors.
 These factors represent pieces of a pie, the whole pie
(combinations of factors) are the sufficient causes for a
disease.
 It shows that a disease may have more that one sufficient
cause, with each sufficient cause being composed of several
factors.
12/10/2009
Dr. Salwa Tayel
Causation&Association
23
Rothman’s
Component Causes and Causal Pies
 The factors represented by the pieces of the pie in this model
are called component causes.
 Each single component cause is rarely a sufficient cause by
itself, But may be necessary cause.
 Control of the disease could be achieved by removing one of
the components in each "pie" and if there were a factor
common to all "pies“ (necessary cause) the disease would be
eliminated by removing that alone.
12/10/2009
Dr. Salwa Tayel
Causation&Association
24
 Exercise
If a particular disease is caused by any of the three sufficient
causes in the diagram. which components, if any, are a
necessary cause?
(Circle ALL that apply.)
A. A
B. B
C. C
D. D
E. E
F. F
G. None
Causal pies representing all sufficient causes of a
particular disease
Exercise
 Some of the risk factors for heart disease are smoking,
hypertension, obesity, diabetes, high cholesterol,
inactivity, stress, and type A personality.
- Are these risk factors necessary causes, sufficient causes,
or component causes? none of them is necessary or sufficient, but each
1 of them is a component factor.
12/10/2009
Dr. Salwa Tayel
Causation&Association
27
Causation and Association
 Causation - implies that there is a true mechanism that
leads from exposure to disease
 Epidemiology does not determine the cause of a disease
in a given individual
 Instead, we determine the relationship or association
between a given exposure and frequency of disease in
populations.
12/10/2009
Dr. Salwa Tayel
Causation&Association
28
Association vs. Causation
 Association is an identifiable relationship between an
exposure and disease
 Association implies that exposure might cause
disease
 Finding an association does not make it causal
 We infer (assume) causation based upon the
association and several other criteria.
12/10/2009
Dr. Salwa Tayel
Causation&Association
29
Epidemiological criteria (guidelines) for
causality
 An association rarely reflects a causal
relationship but it may.
 Criteria for causality provide a way of
reaching judgements on the likelihood
of an association being causal.
12/10/2009
Dr. Salwa Tayel
Causation&Association
30
Hill’s Criteria for Causal Relation
 Strength of association
 Consistency of findings
 Specificity of association
 Temporal sequence
 Biological gradient (dose-response)
 Biological plausibility
 Coherence with established facts
 Experimental evidence
12/10/2009
Dr. Salwa Tayel
Causation&Association
31
Strength of association association
 Does exposure to the cause change disease
incidence?
 The strength of the association is measured by the
relative risk.
 The stronger the association, the higher the
likelihood of a causal relationship.
 Strong associations are less likely to be caused by
chance or bias
12/10/2009
Dr. Salwa Tayel
Causation&Association
32
Consistency of findings
 Consistency refers to the repeated observation of an
association in different populations under different
circumstances.
 Causality is more likely when the association is repeated by
other investigations conducted by different persons in different
places, circumstances and time-frames, and using different
research designs.
12/10/2009
Dr. Salwa Tayel
Causation&Association
33
Specificity of association
 It means that an exposure leads to a single or characteristic
effect, or affects people with a specific susceptibility
 easier to support causation when associations are
specific, but
 this may not always be the case
 as many exposures cause multiple diseases
 This is more feasible in infectious diseases than in noninfectious diseases, which can result from different risk
agents.
12/10/2009
Dr. Salwa Tayel
Causation&Association
34
Temporal sequence (temporality)
 Did the cause precede the effect?
 Temporality refers to the necessity that the cause must
precede the disease in time.
 This is the only absolutely essential criterion.
 It is easier to establish temporality in experimental and
cohort studies than in case-control and cross-sectional
studies.
12/10/2009
Dr. Salwa Tayel
Causation&Association
35
Biological gradient
 Does the disease incidence vary with the level of
exposure? (dose-response relationship)
 Changes in exposure are related to a trend in relative risk
 A dose-response relationship (if present) can increase the
likelihood of a causal association.
12/10/2009
Dr. Salwa Tayel
Causation&Association
36
Biological gradient
12/10/2009
Dr. Salwa Tayel
Causation&Association
37
Biological plausibility
 Is there a logical mechanism by which the
supposed cause can induce the effect?
 Findings should not disagree with
established understanding of biological
processes.
12/10/2009
Dr. Salwa Tayel
Causation&Association
38
Coherence
 Coherence implies that a cause-andeffect interpretation for an association
 does not conflict with what is known of
the natural history and biology of the
disease
12/10/2009
Dr. Salwa Tayel
Causation&Association
39
Experimental evidence
 It refers to evidence from laboratory
experiments on animal or to evidence from
human experiments
 Causal understanding can be greatly advanced
by laboratory and experimental observations.
12/10/2009
Dr. Salwa Tayel
Causation&Association
40
Judging the causal basis of the association
 No single study is sufficient for causal inference
 It is always necessary to consider multiple alternate
explanations before making conclusions about the
causal relationship between any two items under
investigation.
 Causal inference is not a simple process
 consider weight of evidence
 requires judgment and interpretation
12/10/2009
Dr. Salwa Tayel
Causation&Association
41
Figure 5.12 The scales of causal judgement
Weigh up weaknesses in data
and alternative explanations
12/10/2009
Weigh up quality of science
and results of applying causal
frameworks
Dr. Salwa Tayel
Causation&Association
42
Pyramid of Associations
Causal
Non-causal
Confounded
Spurious / artefact
Chance
RS Bhopal
The End
Thank You
Website http://faculty.ksu.edu.sa/73234/default.aspx
[email protected]