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Cause and effect: theepidemiological approach
Raj Bhopal,
Bruce and John Usher Professor of Public Health,
Public Health Sciences Section,
Diision of Communit! Health Sciences,
Uniersit! of "dinburgh, "dinburgh "H#$%&
Raj'Bhopal(ed'ac'u)
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"ducational objecties*n completion of !our studies !ou should
understand:
+he purpose of stud!ing cause and effect in epidemiolog!is to generate )noledge to preent and control disease'
+hat cause and effect understanding is difficult to achieein epidemiolog! because of the long natural histor! ofdiseases and because of ethical restraints on human
e-perimentation' Ho causal thin)ing in epidemiolog! fits in ith other
domains of )noledge, both scientific and non.scientific' +he potential contributions of arious stud! designs for
ma)ing contributions to causal )noledge'
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Cause and effect
Cause and effect understanding is the highestform of achieement of scientific )noledge'
Causal )noledge permits rational plans and
actions to brea) the lin)s beteen the factorscausing disease, and disease itself' Causal )noledge can help predict the outcome
of an interention and help treat disease' /uote Hippocrates "To know the causes of a
disease and to understand the use of thevarious methods by which the disease may be
prevented amounts to the same thing as beingable to cure the disease".
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"pidemiological contributions
to cause and effect
% philosoph! of health and disease' 0odels hich illustrate that philosoph!' 1rameor)s for interpreting and appl!ing the
eidence' Stud! designs to produce eidence' "idence for cause and effect in the
relationships of numerous factors and diseases'
Deelopment of the reasoning of otherdisciplines including philosoph! andmicrobiolog!, in reaching judgement'
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% cause2
+he first and difficult 3uestion is, hat is acause2
% cause is something hich has an effect' 4n epidemiolog! a cause can be considered
to be something that alters the fre3uenc! ofdisease, health status or associated factorsin a population'
Pragmatic definition' Philosophers hae grappled ith the nature
of causalit! for thousands of !ears'
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Some philosoph! Daid Hume5s philosoph! has been influential'
% cause cannot be deduced logicall! from the fact that toeents are lin)ed'
Because thunder follos lightning does not mean thunderis caused b! lightning' *bsering this one million timesdoes not ma)e it true'
+he a-iom 6%ssociation does not mean causation7' Cause and effect deductions need more than obseration
alone . the! need understanding' +he contribution of another philosopher, John Stuart 0ill,
captured in his canons, is so similar to the modernempiricall! based ideas of epidemiolog!'
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"pidemiological strateg! and
reasoning: the e-ample of Semeleis Diseases form patterns, hich are eer changing'Clues to the causes of disease are inherent ithin
these pattern'Semeleis 89#9#.9#;< obsered that the
mortalit! from childbed feer 8no )non aspuerperal feer< as loer in omen attendingclinic = run b! midies than it as in thoseattending clinic 9 run b! doctors'
Do these obserations spar) off an! ideas ofcausation in !our mind2
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Births, deaths, and mortalit! rates 8>< for
all patients at the to clinics 9#?9.9#?
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Semmeleis@ inspiration
4n 9#?A, his colleague and friend Professorolletsch)a died folloing a fingerpric) ith a )nifeused to conduct an autops!'
olletsch)a@s autops! shoed inflammation to beidespread, ith peritonitis, and meningitis'
“Day and night I was haunted by the image ofKolletschka’s disease and was forced to recogniseever more decisively that the disease from whichKolletschka died was identical to that from which somany maternity patients died '7
Semeleis5 inspired idea as that particles had beentransferred from the scalpel to the ascular s!stem ofhis friend and that the same particles ere )illingmaternit! patients'
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Semmeleis@ action
4f so, something stronger than ordinar!
soap as needed for handashing
He introduced chlorina li3uida, and thenfor reasons of econom!, chlorinated lime'
+he maternal mortalit! rate plummeted'
Semeleis@s discoer! as resented in
ienna'
.
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essons from Semmeleis@s or) Deep )noledge deries from the e-planation of disease
patterns, rather than in their description'
4nspiration is needed, and ma! come from une-pectedsources, as here from olletsch)a@s autops!' %ction cannot ala!s aait understanding the mechanism' "pidemiological data to sho that la!ing an infant on its
front 8prone position< to sleep raises the ris) of 5cot death5
or sudden infant death s!ndrome' % campaign to persuade parents to la! their infants on theirbac)s has haled the incidence of cot death'
"pidemiologists are reliant on other sciences, laborator! orsocial, to be e3ual partners, in pursuit of the mechanisms'
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"pidemiological principles and
models of cause and effect
0ost important of the cause and effect ideas underpinned b!epidemiolog! is that disease is irtuall! always a result of theinterpla! of the enironment, the genetic and ph!sical ma)eupof the indiidual, and the agent of disease'
Diseases attributed to single causes are inariabl! so b!
definition' +he fact that 6tuberculosis7 is 6caused7 b! the tuberclebacillus is a matter of definition'
+he causes of tuberculosis, from an epidemiological orpublic.health perspectie, are man!, including malnutritionand oercroding'
+his idea is captured b! seeral ell )non disease causationmodels, such as the line, triangle, the heel, and the eb'
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1igure ;'=
Clues
Stable in incidence
Clusters in families
Clues
4ncidence aries rapidl!
oer time or beteengeneticall! similar
populations
4s the disease predominantl!
genetic or enironmental2
&enetic
"nironmental
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1igure ;'E
Down’s syndrome
Phenylketonuria
Sickle cell disease
Diabetes
Asthma
Coronary heart disease
Stroke Lung cancer
Road traffic
accidents
&enetic "nironmental
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1igure ;'?
Host
"nironment%gent
+he underl!ing cause of the
disease is a result of the
interaction of seeral factors,
hich can be anal!sed using
the components of the
epidemiological triangle'
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1igure ;';
Host:Inhalation of infectie
organism! age! smoking!male se"!
cardio#res$iratory disease
"nironment:Presence of cooling towers
and com$le" hot water
systems% aerosols created
but not contained!
meteorological conditions
take aerosol to humans
%gent:
&irulentLegionella
organisms! e.g.
$neumo$hila
seroty$e
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1igure ;'
Control smo)ing
and causes of
immunodeficienc!
%oid et t!pe cooling
toers, loo) for a betterdesign and location,
separate toers from
population and enhance
toer h!giene
0inimise groth of
organisms and factorshich enhance
pathogenicit!, e'g' algae
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Ph!sicalenironment
Socialenironment
Chemical Fbiological
enironment
!ene
host
1igure ;'A
+he model
emphasises the unit!
of the gene and host
ithin an interactie
enironmental
enelope
+he oerlap beteen
enironmental
components
emphasises the
arbitrar! distinctions
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1igure ;'#
Ph!sical
enironment:
aailability of
health care
facilities fordiagnosis
Social
enironment:
social su$$ort
to sustain
dietary change
Chemical F
biological
enironment:
diet content
!ene defect
en#yme
deficiencybrain
damage
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0odels of cause and effect %gent factors, arguabl!, receie less attention
than the! desere' Characterising the irulence of organisms is difficult' 4n other diseases conceptualising the cause as an agent
is not eas!' +he concept of the disease agent has been applied to
infections but it or)s ell ith man! non.infectiousagents, for e-ample, cigarettes, motor cars, and alcohol' +he interaction of the host, agent and enironment is
rarel! understood' +he effect of cigarette smo)ing is substantiall! greater in
poor people than in rich people'
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0odels of cause and effect
"ach model is a simplification'0oe from simple to comple- models' +he categories of host, agent and
enironment are arbitrar!' +he host and agent are, of course, both
part of the enironment'
"nironment, in this conte-t, is arbitraril!defined to mean factors e-ternal to thehost and the agent of disease'
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+he triangle and preention
+he epidemiological triangle can be
combined ith the schema of theleels of preention to deise a
comprehensie frameor) for
thin)ing about possible preentie
actions'
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0odels: the heel
+he heel of causation' "mphasises the unit! of the interacting factors' "mphasises the fact that the diision of the
enironment into components is somehat arbitrar!'
0odel is applied to phen!l)etonuria, the archet!palgenetic disorder'
Phen!l)etonuria is an autosomal single genedisease '
%n enG!me re3uired to metabolise the dietar! amino.acid phen!lalanine and turn it into t!rosine, isdeficient'
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+he heel: phen!l)etonuria
Brain damage is the outcome' +he cause of this disease could be said to be a
gene'
+he cause of the disease could be consideredas a combination of a gene'
"-posure to a chemical and biologicalenironment hich proides a diet containing a
high amount of phen!lalanine' % social enironment unable to protect the child
from the conse3uences, of a gene disorder'
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0odels: the spider@s eb
1or man! disorders our understanding of thecauses is highl! comple-' "ither the causes are trul! comple-, or e3uall! li)el!,
our understanding is too rudimentar! to permit clarit!' +hese disorders are referred to as multifactorial or
pol!factorial disorders' 0echanisms of causation are not apparent' Portra!ed b! the metaphor of the spider@s eb' +his modelindicates the potential for the disease to
influence the causes and not just the other a! around,
so.called, reerse causalit!' 4t also poses a fundamental 3uestion: here is the
spider that spun the eb2
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4ndiidual e-ercise on
geneIenironment interaction
+hin) about a disease that one of !our friends or relatieshae had'''e-cept for those e hae discussed
Reflect on the causes using the line, triangle and heel ofcausation'
%t !our leisure: +hin) through the cause of disease K using these models
8bo- 9', chapter 9<' 4s disease K li)el! to be genetic or enironmental2 h!2
&o oer !our ansers ith !our classmates
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%nal!sing diseases using the
heel and eb models
Reie the health problems or diseases
that !ou pic)ed and disease K 8Chapter 9,
bo- 9'< using the heel and eb models'
L d ffi i t
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Lecessar! and sufficient cause ast5s Dictionar! tells us that a necessar! cause is M%
causal factor hose presence is re3uired for theoccurrence of the effect7 , and,
Sufficient cause as a 6minimum set of conditions, factorsor eents needed to produce a gien outcome7' +he tubercle bacillus is re3uired to cause tuberculosis but,
alone, does not ala!s cause it, so it is a necessar!, not asufficient, cause'
Consider the causes of Don@s s!ndrome 8+risom! =9<,sic)le cell disease, tuberculosis, scur!, phen!l)etonuria,and lung cancer'
hen a specific cause of disease is sufficientl! ell )non
it can be incorporated into its definition 8as in Don5s
S!ndrome, sic)le cell disease and itamin C deficienc!<'
R th @ t d l
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Rothman@s component causes model Rothman5s interacting component causes model has
emphasised that the causes of disease comprise aconstellation of factors'
4t has broadened the sufficient cause concept to be a minimalset of conditions hich together ineitabl! produce thedisease'
+he concept is shon in figure 99 +hree combinations of factors 8%BC, B"D, %C"< are shon
here as sufficient causes of the disease' "ach of the constituents of the causal MpieM are necessar!' Control of the disease could be achieed b! remoing one of
the components in each MpieM and if there ere a factorcommon to all MpiesM the disease ould be eliminated b!remoing that alone'
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1igure ;'99
% B
C
% "
D
% "
C
"ach of the three components of theinteracting constellations of causes
8%BC, %D", %C"< are in themseles
sufficient and each is necessar!
& id li f id i l i l
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&uidelines for epidemiological
reasoning on cause and effect +urning epidemiological data into an understanding of
cause and effect is challenging' "pidemiologists need an e-plicit mode of reasoning' Subjectie judgements on cause and effect in
epidemiolog! should not be dismissed'
"pidemiologists place much more emphasis on theealuation of empirical data'
Criteria for causalit! proide a a! of reaching judgements on the li)elihood of an association beingcausal'
% frameor) for thought, applied before ma)ing a judgement, based on all the eidence'
" id i l i l it i
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"pidemiological criteria
8guidelines< for causalit!
Causal criteria in microbiolog!, health economics,philosoph! offer much to epidemiolog!'
Henle.och postulates' 0ill@s canons
"conomics also ealuates associations in similar a!s' %ccording to CharemGa and Deadman, the operational
meaning of causalit! in economics is more on the linesof 5to predict5 than 5to produce5 8an effect<'
"pidemiological criteria are, hoeer, designed forthin)ing about the causes of disease in populationsand not in indiiduals'
"pidemiological thin)ing in cause
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"pidemiological thin)ing in cause
and effect "pidemiolog! establishes causes in populations
but this information applies to indiiduals in a probabilistica!' hich does not proe cause and effect at the indiidual leel ' 4f $N> of all lung cancer in a population is due to smo)ing,
hat is the li)elihood that in an indiidual ith lung cancer thecause as smo)ing2
+here is no a! to distinguish a lung cancer resulting fromsmo)ing from a lung cancer arising from another cause'
% factor demonstrated to cause a disease in an indiidual, sa!using to-icolog! or patholog!, ma! not be demonstrable asharmful in the population' h!2
imitation of a science of indiiduals'
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%pplication of guidelinesIcriteria
to associations
%n association rarel! reflects a causal
relationship but it ma!'
+hese si- criteria are a distillation of, or at
least, echo the ten %lfred "ans5
postulates in ast5s Dictionar! of
"pidemiolog! 8?th edition< and the nine
Bradford Hill criteria'
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+emporalit!
Did the cause precede the effect2 4f the effect follos the action of a proposed cause
the association ma! be a causal one and theanal!sis can proceed'
+hunder follos lightning' Does lightning cause
thunder2 4f !ou flic) a sitch and a light goes on, can !ou
deduce that !ou and !our action cause the light togo on2
Just because B follos %, does not of itself, confirma causal relation' Deeper understanding or openingthe blac) bo- is essential'
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Strength and dose response
Does e-posure to the cause change disease
incidence2 4f not there is no epidemiological basis for a conclusion oncause and effect'
1ailure to demonstrate this does not, hoeer, disproe acausal role'
+he usual measure of the increase in incidence is the relatieris) and the technical name for this criterion is the strengthof the association'
Dose.response Does the disease incidence ar! ith the leel of e-posure2
4f !es, the case for causalit! is adanced' +he dose.response relation is also measured using the
relatie ris)'
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Specificit!
4s the effect of the supposed cause specific toreleant diseases, and, are diseases caused b! alimited number of supposed causes2
4magine a factor hich as lin)ed to all health
effects h! ould that be so2 Lon.specificit! is characteristic of spurious
associations eg underestimating the siGe of thedenominator'
hile specificit! is not a criticall! important criterionepidemiologists should ta)e adantage of thereasoning poer it offers'
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Consistenc!
4s the eidence ithin and beteen
studies consistent2
Consistenc! is lin)ed to generalisabilit! of
findings'
Spurious associations are often local'
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"-periment
Does changing e-posure to the supposed
cause change disease incidence2
*ften there hae been natural e-periments'
Deliberate e-perimentation ill be necessar!'
Human e-periments or trials are sometimes
impossible on ethical grounds'
Causal understanding can be greatl! adancedb! laborator! and e-perimental obserations'
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Biological plausibilit!
4s there a biological mechanism b! hich thesupposed cause can induce the effect2
1or trul! noel adances, hoeer, thebiological plausibilit! ma! not be apparent'
Biologicall! plausible that la!ing an infant on itsbac) to sleep ma! lead to its inhaling omitus'
*erturned b! the biologicall! implausibleobseration that la!ing a child on its bac)
hales the ris) of cot death' Lonetheless, biological plausibilit! remains
releant to establishing causalit!'
Judging the causal basis of the
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Judging the causal basis of the
association +he criteria are particularl! aluable in e-posing the
lac) of eidence for causalit!, for indicating the needfor further research and for aoiding prematureconclusions'
Sometimes firm judgements are possible' Sometimes, judgments are forced upon us' +hree e-amples of the case for causalit! in boo)' Dieth!lstilboestrol as a cause of adenocarcinoma of
the agina 8Herbst et al<' Smo)ing as a cause of lung cancer, 8Doll et al< and
Residential pro-imit! to a co)ing or)s as a cause ofill.health 8Bhopal et al<'
"-ample of judging causalit!: lung cancer
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"-ample of judging causalit!: lung cancer
causalit!: lung cancer
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causalit!: lung cancer
1i ; 9E +h id f i ti
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1igure ;'9E +he p!ramid of associations
9 Causal and mechanisms
understood
= Causal
E Lon.causal
? Confounded
; Spurious I artefact
Chance
4 t t ti f d t t d
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4nterpretation of data, stud!
design and causal criteria
Causal )noledge is born in the imagination andunderstanding of the disease process of theinestigator'
Same data can be interpreted in 3uite different a!s' +he paradigm ithin hich epidemiologists or) ill
determine the nature of the causal lin)s the! see andemphasise'
Researchers to ma)e e-plicit in their ritings theirguiding research philosoph!'
Lo epidemiological design confirms causalit! and nodesign is incapable of adding important eidence'
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1igure ;'9= +he scales of causal judgement
'eigh u$ weaknesses in data
and alternatie e"$lanations
'eigh u$ (uality of science
and results of a$$lying causal
frameworks
" id i l i l th
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"pidemiological theor!
illustrated b! this chapter
Diseases arise from a comple- interactionof genetic and enironmental factors'
Causes of disease in indiiduals ma! not
necessaril! be demonstrable causes ofdisease in populations and ice ersa'
Cause and effect judgements areachieable through h!pothesis generationand testing, ith data interpreted using alogical frameor) of anal!sis'
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Summar!
Cause and effect understanding is the highestform of scientific )noledge'
"pidemiological and other forms of causal
thin)ing shos similarit!' %n association beteen disease and the
postulated causal factors lies at the core ofepidemiolog!'
Demonstrating causalit! is difficult because ofthe comple-it! and long natural histor! ofman! human diseases and because of ethicalrestraints on human e-perimentation'
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Summar!
%ll judgements of cause and effect aretentatie'
Be alert for error, the pla! of chance and
bias'Causal models broaden causal perspecties'%ppl! criteria for causalit! as an aid to
thin)ing' oo) for corroboration of causalit! from
other scientific frameor)s'