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Cohort Study
Subodh S GuptaDr. Sushila Nayar
School of Public Health
MGIMS, Sewagram
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Type of study Alternate name Unit of study
Observational studies
Descriptive studies Analytical studies
Ecological Correlational Populations
Cross-sectional Prevalence Individuals
Case-Control Case-Reference Individuals
Cohort Follow-up/ Longitudinal Individuals
Experimental/ intervention StudiesRandomized ControlledStudies
Clinical Trial Patients
Field Trial Healthy person
Community Trial Community interventionstudies
Communities
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Definition & SynonymsDefinition
The cohort study is an observationalepidemiological study which, after themanner of an experiment, attempts to
study the relationship between apurported cause (exposure) and thesubsequent risk of developing disease.
Synonyms Follow-up Longitudinal Prospective
Incidence study
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Groups are exposure based: The group or groupsof persons to be studied are defined in terms of characteristics manifest prior to the appearance of
the disease under investigation The study is conceptually longitudinal: The study
groups so defined are observed over a period of time to determine the frequency of disease amongthem
A definite beginning and end
The cohort design
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The cohort design
Efficient for examiningWhen there is good evidence of exposure anddisease.
When exposure is rare but incidence of diseaseis higher among exposedWhen follow-up is easy, cohort is stableWhen ample funds are availableCommon outcomes
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The cohort design
Many different outcomes for same exposure The dynamic nature of many risk factors
and their relations in time to diseaseoccurrence can be captured here (cannotbe done in cross-sectional study and onlywith difficulty in case-control study)
Associations (not cause and effect) Estimate incidence within risk factor groups
Cannot estimate prevalence of risk factor
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Time
Direction of enquiry
Population
Cases
(Peoplewith disease)
Exposed
Not exposed
Exposed
Not exposed
Controls(Peoplewithout disease)
Case control study
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Types of cohort study
Historical/ Retrospective/ Non-concurrent Prospective/ Concurrent
The distinction between retrospective andprospective cohort studies is important, notbecause of any conceptual difference ordifferences in interpretability of findings, butbecause of relevance to some practical issues,mostly the ability to control confounding.
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Time
Population
Peoplewithout
theoutcome
Exposed
Not Exposed
Diseased
Not diseased
Diseased
Not diseased
Direction of enquiry
Point in time when enquiry begins?
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Population
Peoplewithout
theoutcome
Exposed
Not Exposed
Diseased
Not diseased
Diseased
Not diseased
Time
Direction of enquiry
Both exposures and outcomesmeasured prospectively
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Population
Peoplewithout
theoutcome
Exposed
Not Exposed
Diseased
Not diseased
Diseased
Not diseased
Exposures measured retrospectivelyand outcomes prospectively
Time
Direction of enquiry
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Population
Peoplewithout
theoutcome
Exposed
Not Exposed
Diseased
Not diseased
Diseased
Not diseased
Both exposures and outcomesmeasured retrospectively
Time
Direction of enquiry
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Advantages Direct estimate of risk and rate of disease
occurrence over time An efficient means of studying rare exposures Assess multiple outcomes of a single exposure Establish temporal relationship between exposure
and outcome Exposure definitely precedes the outcome Avoids recall bias, survival bias Does not require strict random assignments of
subjects Can be done with original data or secondary data
Best observational design to establish
association
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Disadvantages
Very large sample sizes, especially for rareoutcomes Expensive and time-consuming Attrition problem (Loss to follow-up) Differences in the quality of measurement of exposure or disease b/w the cohorts may
introduce misclassification (information bias) Can not infer causal relation
Very specific finding Complexity of data analysis Ethical issues Study effects
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Cohort Study: Steps
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1. Identification of study population andinitial steps
2. Measurement of exposure3. Selection of study and comparison
cohorts4. Follow-up (for outcome
measurement)5. Data analysis
Steps in conducting cohort study
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Types of cohorts
Closed or fixed cohorts:Fixed group of persons followed from a certainpoint in time until a defined endpointStarting point - exposure defining event
Endpoint occurrence of the disease, loss tofollow-up, deathThe exposure is an event which occurs onlyonce
Open or dynamic cohorts: Subjects may enter or leave the study at anytime
Exposure status may change over time
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Cohorts
General population cohorts: populationgroups offering special resources for follow-up or data linkage are chosen, and the
individuals are subsequently allocatedaccording to their exposure status Special exposure cohorts: Samples chosen
on the basis of a particular exposure
Exposures may be a particular event, apermanent state or a reversible state
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General population cohorts(groups offering special resources)
Groups with readily available health records Certain professional categories
Obstetric populations Volunteer groups Geographically identified cohorts
Record linkage
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Special exposure cohorts(groups offering special resources)
Exposed to certain factor or event Occupational groups
Based on qualitative characteristics
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Population-based Cohort Studies
Advantages Estimation of distributions and prevalence
rates of relevant variables Risk factor distributions Ideal setting in which to carry out unbiased
evaluation of relations
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Selection of comparison group
Internal comparisonOnly one cohort identifiedLater on, classified into study and comparison cohortbased on exposure
External comparisonMore than one cohort identifiede.g. Cohort of radiologist compared withophthalmologists
Comparison with general population ratesIf no comparison group is available we can comparethe rates of study cohort with general populationCancer rate of uranium miners with cancer in generalpopulation
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Ideal Cohort
Stable cohort Cooperative cohort Committed cohort Well informed cohort
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Exposure measurement
Exposures: exogenous and/ or endogenousReference periodFrequency of follow-up
Challenge of prospective data collectionChanges in instrument over time
Use of repeated measuresData collection costs
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Discrete events Single events
MortalityFirst occurrence of a disease or health-relatedoutcome
Multiple occurrencesDisease outcome
Transition between states of health/ diseaseTransitions between functional states
Level of a marker
Follow-up: Types of outcomes
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Exercise 1 An investigator wants to discover whether or not
being overweight in adolescence increases the risk of cardiovascular mortality in adulthood.a) Assuming historical records are available, would a
prospective or retrospective study be morepractical?
b) Who would comprise the investigator's cohortunder study?
c) Who would comprise the investigator's exposedand unexposed groups in this cohort?
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Group Exercise Design a Cohort Study
Outline the steps which you will require to do forthis study
Special efforts you may need to do for follow-up of the study subjects
What care you will need to take to reducemeasurement bias
Calculate the sample size
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Challenges in conducting
Cohort Study
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Challenge 1: multiple dimensions of time in cohort study
Age
Calendar period
Exposure 1
Exposure 2
Exposure i
Covariate 1Covariate 2
Covariate iStart of study End of study
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Effect of Nonresponse
Nonresponse: a major problem A differential nonresponse will distrorts the
true relationship b/w exposure and outcome
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Nonresponse: random or selective?
Exposure data: find out if nonrespondentsare different from the respondents
Intensive efforts within the study designFollow-up of the nonrespondents as well asrespondents
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Challenge 3:Large Modern Cohort Studies
Huge requirements of resources and manpower Management of huge database Follow-up Exposure information Data quality? Collection of biologic samples?
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Challenge 4:Long term follow-up
Operational problems Cumulative risk getting closer to one
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Cohort Study Analysis
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Standard 2 X 2 table(Relation between exposure and outcome)
DISEASE STATUS
Present Absent Total
EXPOSURE
STATUS
Present a b a + b
Absent c d c + d
Total a + c b + d N
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Two types of measures for rate
Cumulative incidence = Proportion of studysubjects getting the outcome during thestudy period
Incidence rate = New cases/ Person-timeunder observation
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Number of new cases of disease
occurring over a specified periodof time in a population at risk.
1. Cumulative incidence rate:
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EXAMPLE
A surveillance system for Hospitalacquired infection among the post-operative patients in a month.
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Example
0 5 10 15 20 25 30
9
61414
24
1914
4
5
1921
6
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Number of new cases of diseaseoccurring over a specified periodof time in a population at risk
throughout the interval .
2. Incidence density:
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Incidence density requires us to addup the period of time each individualwas present in the population, andwas at risk of becoming a new caseof disease.Incidence density characteristicallyuses as the denominator person-years at risk. (Time period can beperson-months, days, or even hours,depending on the disease processbeing studied.)
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USES OF INCIDENCE DENSITY ANDCUMULATIVE INCIDENCE
Incidence density gives the bestestimate of the true risk of acquiringdisease at any moment in time. Cumulative incidence gives the
best estimate of how many peoplewill eventually get the disease in anenumerated population.
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Standard 2 X 2 table(Relation between exposure and outcome)
Peripheral Vascular Disease
Present Absent Total
Cigarette
Smoking
Present 15 1712 1727
Absent 41 3188 3229
Total 56 4900 4956
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l X 2 table(Relation between exposure and outcome)
Disease status
Present Absent Total
Cholesterolquintiles
1st 15 798 813 2nd 20 794 814 3rd 26 791 817
4th
41 785 826 5 th 48 777 825
Total 150 3945 4095
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Comparing risks in different groups
Relative risk OR Risk ratio (RR) Attributable risk OR Risk difference (AR) Attributable risk percent (AR%) Population attributable risk (PAR) Population attributable risk percent (PAR%)
Odds Ratio (OR)
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Relative risk OR Risk ratio
Ratio of the risk among exposed to the risk among unexposed[Risk (Exp) / Risk (Unexp)]
Risk of disease among exposed = [a/ [a+ b)] Risk of disease among unexposed = [c/ [c +d)]
RR = [a/ [a +b)] / [c/ [c +d)] For null hypothesis, Risk ratio will equal
one
SE=
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Risk difference vs. Relative risk
191
8.7
0
20
40
60
80
100
120
140
160
180
200
A b s o
l u t e r i s
k L u n g c a n c e r
d e a
t h s p e r
1 0 0
, 0 0 0
a d u
l t m a
l e p e r y e a r
Smokers
Non smokers
R el a t i v er i s k
1
22
A b s ol u t er i s k
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Risk difference vs. Relative risk
191
8.7
0
20
40
60
80
100
120
140
160
180
200
A b s o
l u t e r i s
k L u n g c a n c e r
d e a
t h s p e r
1 0 0
, 0 0 0
a d u
l t m a
l e p e r y e a r
Smokers
Non smokers
Ri s k d i f f er en c e
A b s ol u t er i s k s
( E x p & Un ex p )
Att ib t bl i k t
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Attributable risk percent amongexposed
Among exposed, what percent of the total risk for disease is due to the exposure
AR% (Exposed) = [Risk (Exp) Risk (Unexp)]/ Risk (Exp) X 100 = (RR 1)/ RR X 100
= (OR 1)/ OR X 100 (if risk is small)
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191
8.7
0
20
40
60
80
100
120
140
160
180
200
A b s o
l u t e r i s k L u n g c a n c e r
d e a
t h s p e r
1 0 0 , 0 0 0 a
d u
l t m a
l e p e
r y e a r
Smokers Non smokers
R el a t i v er i s k
% r i s k d u e
t o
ex p o s ur e
1
22
A b s ol u t er i s k s
( E x p )
% risk due tobackground
Attributable Risk Percent
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Attributable Risk Percent191
8.7
0
20
40
60
80
100
120
140
160
180
200
A b s o
l u
t e r i s k
L u n g c a n c e r
d e a
t h s p e r
1 0 0
, 0 0 0 a
d u
l t m a
l e p e r y e a r
Smokers Non smokers
R el a t i v er i s k
p 0 ( RR-1 )
p 0
p0RR
p 0 RR
1
Attributable risk Percent = (RR-1)/ RR *100
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Population attributable risk
In the general population, how much of thetotal risk for disease is due to the risk factor
Risk (Total) Risk (Unexp) Risk (Total)
= [Proportion population Exp X Risk (Exp)] +[Proportion population Unexp X Risk (Unexp)]
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Population attributable risk percent
Among the general population, what percentof the total risk for disease is due to the risk factor
PAR% = [Risk (Total) Risk (Unexp)]/ Risk (Total) X 100 = [Pe (RR 1)]/ [1+ Pe (RR 1)] X 100
Population attributable risk percent
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0
20
40
60
80
100
120
140
160
180
A b s o
l u t e r i s k o
f l u n g c a n c e r
d e a
t h p e r
1 0 0
, 0 0 0 a
d u l t m a
l e p e r y e a
r
Smoker Nonsmoker
(RR-1)(1-P e )Pe (RR-1)
(1-P e )P e
Population attributable risk percent
Population Attributable risk Percent
= [Pe (RR 1)]/ [1+ Pe (RR 1)] X 100
RR
1
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Risk Reduction Risk (T/t) = a/(a+b) Risk (Exp) = c /(c+d) RR = Risk (T/t)/ Risk (Exp) ARR = Risk (Exp) Risk (T/t) RRR = [Risk (Exp) Risk (T/t)] / Risk (Exp)
= 1-Risk(T/t)/Risk(Exp)= 1-RR
NNT = 1/ARR = 1/Risk(Exp)*RRR NNH
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Analytical considerations
Concurrent follow-up Varying follow-up dates Moving baseline dates Withdrawals Competing causes of death
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Anal tical considerations
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Analytical considerations Concurrent follow-up
Simple risk-based analysesSurvival analysis
Varying follow-up dates
Simple risk analysis for all events up to, but notexceeding, the minimum elapsed timeSurvival analysis
Moving baseline dates
Ignore and measure elapsed time since recruitmentSurvival analysis
Withdrawals
Competing causes of failure
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Advanced methods
Standardization Stratification Life Tables Multivariate analysis and Cox regression
E i 2
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Exercise 2 A cohort study to explore the relationship between
visual impairment and the risk of injuries from fallsamong the elderly.
A total of 400 visually impaired (VI) persons >70yrs are compared against 400 controls without VI.
Over a 5-year follow-up period, 80 VI persons and20 non-VI persons have injuries from falls.
a) Construct a 2x2 table from the information above
b) Calculate the followings with their CI :Cumulative Incidence rate for exposed and unexposedRelative risk
Attributable risk & Attributable risk percent
E i 2
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Exercise 2 A cohort study to explore the relationship between
visual impairment and the risk of injuries from fallsamong the elderly.
A total of 400 visually impaired (VI) persons >70yrs are compared against 400 controls without VI.
Over a 5-year follow-up period, 80 VI persons and20 non-VI persons have injuries from falls.
a) Construct a 2x2 table from the information above
b) Calculate the followings with their CI :Cumulative Incidence rate for exposed and unexposedRelative risk
Attributable risk & Attributable risk percent
Exercise 3
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Exercise 3
A retrospective cohort study to explore therelationship between perimenopausalexogenous estrogen use and the risk of coronary heart disease (CHD).
A total of 5000 exposed and 5000unexposed women are enrolled andfollowed for 15 years for the developmentof myocardial infarction (MI).
A total of 200 estrogen users and 300nonusers had MIs.
Exercise 3 (Contd )
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a) The risk (CI) of a MI among estrogen usersb) The risk (CI) of a MI among nonusers of
estrogenc) The relative risk (CIR) for MId) Based on the results of this study is
estrogen use a causative or protectivefactor for MI?
Exercise 3 (Contd.)
Exercise 4
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Exercise 4Shaper et. al. (1988) A random sample of 7729 middle-aged British men Each man asked, at baseline, his alcohol
consumption Next 7.5 years, death certificates collected for any
subject who died
Alcohol consumption group ( Unit/wk )
None Occasional(42)
Subjects 466 1845 2544 2042 832Deaths 41 142 143 116 62
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a) Calculate the risk and the relative risk foreach alcohol consumption group.
b) Why might the conclusion based on theabove table may be misleading? Givenadequate funding, describe how?
Exercise 4 (Contd.)
Exercise 5
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Exercise 5 In a cohort study of 34387 menopausal women in Iowa,
intakes of certain vitamins were assessed in 1986. In theperiod up to the end of 1992, 879 of these women werenewly diagnosed with breast cancer. The table belowshows data for two vitamins, classified according to rankedcategories of intake.
Vitamin C Vitamin EEvents PY Events PY
1 (low) 507 124,373 570 143,117
2 217 57,268 129 33,9503 76 19,357 71 19,536
4 55 17,013 28 6,942
5 (high) 24 7,711 81 22,176
Exercise 5 (Contd )
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a) For each vitamin, calculate the relativerates (with 95% confidence intervals)taking the low-consumption group as thebase. Do your results suggest any
beneficial (or otherwise) effect of additional vitamin C or E intake?
Exercise 5 (Contd.)
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Types of bias
Selection bias Follow-up bias Information bias Confounding bias Post hoc bias
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Selection bias
Group studied does not reflect the samedistribution of factors (such as age, sex,SES, behavior etc.) as occurs in the generalpopulation
Effect of volunteeringWhole spectrum of independent variables notrepresented in the study group
Presence of incipient diseaseDistribution of covariatesSurvival cohorts: cohorts ascertained long afterexposure
Follow up bias
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Also known as
Migration Bias
In nearly all large studies some members
of the original cohort drop out of the study
If drop-outs occur randomly, such thatcharacteristics of lost subjects in onegroup are on an average similar to thosewho remain in the group, no bias isintroduced
But ordinarily the characteristics of thelost subjects are not the same
Follow-up bias
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Example of
lost to follow-up
+ - Total
+ 50 100 150-
10000 20000 30000
EXPOSURE
irradiation
+ - Total
+ 60-
4000 8000 12000
30 30
EXPOSURE
irradiation
RR= 50/10000100/20000
= 1
RR= 30/400030/8000
= 2
Example
healthy worker
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Example. healthy workereffect
Question: association b/w formaldehydeexposure and eye irritation
Subjects: factory workers exposed toformaldehyde
Bias: those who suffer most from eyeirritation are likely to leave the job attheir own request or on medical advice
Result: remaining workers are lessaffected; association effect is diluted
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Measurement / (Mis) classification
Exposure misclassification occurs whenexposed subjects are incorrectly classifiedas unexposed, or vice versa
Disease misclassification occurs whendiseased subjects are incorrectly classifiedas non-diseased, or vice versa
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Reassignment to exposure category
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eass g e t to e posu e catego y Changes in dichotomous exposure, if not taken
into consideration will tend to make the strengthof an observed association lower than that whichactually existed
Latency is likely to be short
Exposure accumulates over time during the study Very accurate results desirable
Reassignment may not be possible
Close cohort as a ruleLatency is very longDuration of follow-up is very long
Separate examination of outcome in those whochanged exposure status during the study
C f di bi
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Confounding bias
Other factors which are associated withboth outcome and exposure variables donot have the same distribution in theexposed and unexposed group
E l f di
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Examples confounding
COFFEE DRINKING HEART DISEASE
SMOKING
(Coffee drinkers are
more likely to smoke)
(Smoking increasesthe risk of heart ds)
R l i C f di Bi
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Resolving Confounding Bias
Standardization Stratification Multivariate adjustment
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Th k
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Thank you
I t l & E t l lidit
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Internal & External validity
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