causal inference dr. amna rehana siddiqui department of family and community medicine
TRANSCRIPT
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Causal Inference
Dr. Amna Rehana Siddiqui
Department of Family and Community Medicine
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Objectives:
Explain basic models of disease causation.Explain basic models of disease causation.
To understand concepts related to scientific inference for cause effect relation
To understand the applicability of causal criteria as applied to epidemiological studies
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Approach to etiology To see whether a certain substance is an
agent / microorganism; a controlled laboratory experiment can be done by Exposing animals to organism Setting the exposure dose Monitoring environmental conditions Selecting genetic factors Minimum loss to follow up Species differ in response
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Observations in Human populations
Cannot randomize human beings for harmful substances
Depend on nonrandomized observations Important populations – occupational cohorts Natural experiments
Residents of Hiroshima and Nagasaki Residents of Bhopal
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Stages of disease and Levels of prevention Susceptibility
Pre-symptomatic
Clinical
Disability or Recovery
Primary prevention
Secondary prevention(Screening)
Tertiary prevention
Tertiary prevention
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Development of Disease Combination of events
A harmful agent A susceptible host An appropriate environment
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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)
General Models of Causation
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The Epidemiologic Triad
HOST
AGENT ENVIRONMENT
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Agent factorsAgent factors
•Infectious agents: agent might be microorganism—virus, Infectious agents: agent might be microorganism—virus, bacterium, parasite, or other microbes. e.g. polio, measles, bacterium, parasite, or other microbes. e.g. polio, measles, malaria, tuberculosis Generally, these agents must be present malaria, tuberculosis Generally, these agents must be present for disease to occur. for disease to occur.
•Nutritive: excesses or deficiencies (Cholesterol, vitamins, Nutritive: excesses or deficiencies (Cholesterol, vitamins, proteins)proteins)
•Chemical agents: (carbon monoxide, drugs, medications)Chemical agents: (carbon monoxide, drugs, medications)
•Physical agents (Ionizing radiation,…Physical agents (Ionizing radiation,…
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Host factorsHost factors
•Host factors are intrinsic factors that influence an individual’s Host factors are intrinsic factors that influence an individual’s
exposure, susceptibility, or response to a causative agent. exposure, susceptibility, or response to a causative agent.
•Host factors that affect a person’s risk of exposure to an agent:Host factors that affect a person’s risk of exposure to an agent:
•e.g. Age, race, sex, socioeconomic status, and behaviors e.g. Age, race, sex, socioeconomic status, and behaviors
(smoking, drug abuse, lifestyle, sexual practices and eating (smoking, drug abuse, lifestyle, sexual practices and eating
habits) habits)
•Host factors which affect susceptibility &response to an agent:Host factors which affect susceptibility &response to an agent:
•Age, genetic composition, nutritional and immunologic status, Age, genetic composition, nutritional and immunologic status,
anatomic structure, presence of disease or medications, and anatomic structure, presence of disease or medications, and
psychological makeup.psychological makeup.10
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Environmental factorsEnvironmental factors
Environmental factors are extrinsic factors which affect the agent Environmental factors are extrinsic factors which affect the agent
and the opportunity for exposure. and the opportunity for exposure.
Environmental factors include: Environmental factors include:
physical factors such as geology, climate,.. physical factors such as geology, climate,..
biologic factors such as insects that transmit an agent; and biologic factors such as insects that transmit an agent; and
socioeconomic factors such as crowding, sanitation, and the socioeconomic factors such as crowding, sanitation, and the
availability of health services.availability of health services.
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Agent
Host Environment
Vector
MalariaMalaria
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Agent:Amount, infectivity, pathogenicity, virulence, chemical composition,
cell reproduction
Environment:Physical, biological, social
Host:Intrinsic factors, genetic, physiologic factors,
psychological factors, immunity
Health
or
Illness
?
The epidemiologic triad ModelThe epidemiologic triad Model
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Web of CausationWeb of Causation
There is no single cause
Causes of disease are interacting
Illustrates the interconnectedness of
possible causes
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The Web of causation
Developed to de-emphasis agent Chain of causation Complexity of origin is web Multiple factors promote or inhibit Emphasizes multiple interactions between
host and environment
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Web of Causation
Disease
behaviourUnk
nown f
acto
rsgenes
phenotype
workplace
soci
al o
rgan
izat
ion
microbes
environment
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Web of Causation - CHD
RS Bhopal
Disease
smokingUnk
nown f
acto
rsgender
genetic susceptibility
inflamm
ation
med
icat
ions
lipids
physical activityblood pressure
stress
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Example of a Web of Causation
Susceptible Host Infection Tuberculosis
Vaccination Genetic
Overcrowding Malnutrition
Tissue Invasion and Reaction
Exposure to Mycobacterium
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The Wheel of CausationThe 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.
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The Wheel of Causation
Social Environment
Genetic Core
Physical Environment
Biological Environment
Host (human)
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Association Vs. Causation
Association refers to the statistical dependence between two variables
The presence of an association…in no way implies that the observed relationship is one of cause and effect
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Types of causes
Sufficient causes:a set of conditions without any one of which the disease
would not have occurrednot usually a single factor, often several
Necessary cause:must be present for disease to occur, disease never develops
in the absence of that factor.a component cause that is a member of every sufficient
cause
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The sufficient cause and component causes model The sufficient cause and component causes model Rothman’s component causes modelRothman’s component causes model
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Necessary and sufficient causesNecessary and sufficient causes
A A necessarynecessary cause is a causal factor whose presence is cause is a causal factor whose presence is
required for the occurrence of the effect.required for the occurrence of the effect. If disease does If disease does
not develop without the factor being present, then we term not develop without the factor being present, then we term
the causative factor the causative factor ““necessarynecessary”.”.
SufficientSufficient cause is a “minimum set of conditions, factors or cause is a “minimum set of conditions, factors or
events needed to produce a given outcome.events needed to produce a given outcome.
The factors or conditions that form a sufficient cause are The factors or conditions that form a sufficient cause are
called called componentcomponent causes.causes.
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Example
The tubercle bacillus is required to cause The tubercle bacillus is required to cause
tuberculosis but, alone, does not always tuberculosis but, alone, does not always
cause it, cause it,
so tubercle bacillus is a so tubercle bacillus is a necessarynecessary,, not a not a
sufficient, cause.sufficient, cause.
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Rothman'sRothman's model has emphasised that the causes of disease model has emphasised that the causes of disease
comprise a collection of factors. comprise a collection of factors.
These factors represent pieces of a pie, the whole pie These factors represent pieces of a pie, the whole pie
((combinations of factors) are the the sufficientsufficient causes for a causes for a
disease.disease.
It shows that a disease may have more that one sufficient It shows that a disease may have more that one sufficient
cause, with each sufficient cause being composed of several cause, with each sufficient cause being composed of several
factors.factors.
Rothman’s Component Causes and Component Causes and Causal Pies ModelCausal Pies Model
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The factors represented by the pieces of the pie in this model
are called componentcomponent causes.
Each single component cause is rarely a sufficientsufficient cause by
itself, But may be necessarynecessary 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.
Rothman’sComponent Causes and Causal PiesComponent Causes and Causal Pies
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Exercise 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?
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Causal pies representing all sufficient causes of a particular disease
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Types of Associations
Real: probability depends upon the occurrence of one or more other events, characteristics, or other variables
Spurious: Non causal associations depend on bias, chance, failure to control for extraneous variables (confounding)
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Percentage of pregnancies (n=50,267) with infant weighing < 2500 g by maternal cigarette smoking category (peri-natal mort study Comm Vol 1, 1967
4.7
7.7
12
0
2
4
6
8
10
12
14
Non smoker < 1 pack >=1 pack
% less than 2500 g
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Percentage of LBW infants by smoking status of their mothers (Yerushalmay J, Am J Obs & Gynecol)
5.3
9.5 8.9
6
0
2
4
6
8
10
Non Smoker Non Smoker Smoker Smoker All pregnancies Future All Preg Future Smoker Ex smoker
% of LBW infants
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“Is there an association between an exposure and a disease?”
IF SO…. Is the association likely to be due to chance? Is the association likely to be due to bias? Is the association likely to be due to
confounding? Is the association real/causal?
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Establishing the cause of diseaseAssociation?Association?
Chance?Chance?
Bias ?Bias ?
Confounding?Confounding?
Causal?Causal?
presentpresent
absentabsent
absentabsent
absentabsent
absentabsent
presentpresent
likelylikely
likelylikely
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Association Vs. Causation
Association refers to the statistical dependence between two variables
The presence of an association…in no way implies that the observed relationship is one of cause and effect
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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.
Epidemiological criteria (guidelines) for Epidemiological criteria (guidelines) for causalitycausality
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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
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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
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Consistency of findings
Consistency refers to the repeated observation of an Consistency refers to the repeated observation of an
association in different populations under different association in different populations under different
circumstances. circumstances.
Causality is more likely when the association is repeated by Causality is more likely when the association is repeated by
other investigations conducted by different persons in different other investigations conducted by different persons in different
places, circumstances and time-frames, and using different places, circumstances and time-frames, and using different
research designs.research designs.
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Specificity of association
It means that an exposure leads to a single or characteristic It means that an exposure leads to a single or characteristic effect, or affects people with a specific susceptibilityeffect, or affects people with a specific susceptibility easier to support causation when associations are easier to support causation when associations are
specific, butspecific, but this may not always be the casethis may not always be the case
as many exposures cause multiple diseasesas many exposures cause multiple diseases This is more feasible in infectious diseases than in non-This is more feasible in infectious diseases than in non-
infectious diseases, which can result from different risk infectious diseases, which can result from different risk agents. agents.
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Temporal sequence (temporality)
Did the cause precede the effect? Did the cause precede the effect?
Temporality refers to the necessity that the cause must Temporality refers to the necessity that the cause must
precede the disease in time. precede the disease in time.
This is the only absolutely essential criterion. This is the only absolutely essential criterion.
It is easier to establish temporality in experimental and It is easier to establish temporality in experimental and
cohort studies than in case-control and cross-sectional cohort studies than in case-control and cross-sectional
studies.studies.
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Biological gradient
Does the disease incidence vary with the level of exposure? Does the disease incidence vary with the level of exposure?
((dose-response relationship)dose-response relationship)
Changes in exposure are related to a trend in relative riskChanges in exposure are related to a trend in relative risk
A dose-response relationship (if present) can increase the A dose-response relationship (if present) can increase the
likelihood of a causal association.likelihood of a causal association.
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Biological gradient(Dose Response)
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Age standardized death rates due to bronchogenic carcinoma by current amount of smoking
Dose-response relationship
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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.
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Coherence
Coherence implies that a cause-and-effect implies that a cause-and-effect
interpretation for an association interpretation for an association
does not conflictdoes not conflict with what is known of the with what is known of the
natural history and biology of the disease natural history and biology of the disease
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Experimental evidence
It refers to evidence from laboratory It refers to evidence from laboratory
experiments on animal or to evidence from experiments on animal or to evidence from
human experiments human experiments
Causal understanding can be greatly advanced Causal understanding can be greatly advanced
by laboratory and experimental observations.by laboratory and experimental observations.
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Judging the causal basis of the associationJudging the causal basis of the association
No single study is sufficient for causal inferenceNo single study is sufficient for causal inference It is always necessary to consider multiple alternate It is always necessary to consider multiple alternate
explanations before making conclusions about the explanations before making conclusions about the causal relationship between any two items under causal relationship between any two items under investigation. investigation.
Causal inference is not a simple processCausal inference is not a simple process consider weight of evidenceconsider weight of evidence requires judgment and interpretationrequires judgment and interpretation
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Figure 5.12 The scales of causal judgement
Weigh up weaknesses in data and alternative explanations
Weigh up quality of science and results of applying causal
frameworks
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Pyramid of Associations
RS Bhopal
Causal
Non-causal
Confounded
Spurious / artefact
Chance
50
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Evaluating Evidence of Causal relationship Major Criteriaa. Temporal relationshipb. Biologic plausibilityc. Consistency of Resultsd. Alternative explanationsOther criteriaa. Strength of associationb. Dose-response relationshipc. Cessation of effects