4. Classification of epidemiological studies
Epidemiological
Studies
Observational Experimental
Descriptive Analytical RCT Field Trials
Community
Trials
Cross
sectional Ecological Case-control Cohort
WHO 1993
5. Descriptive studies
“The best study of mankind is man”
Usually the first phase
Observe and identify
The FAQs of descriptive studies
When? --------- time distribution
Where? -------- place distribution
Who? ---------- person distribution
6. Procedures in descriptive studies
1. Defining the population to be studied
2. Defining the disease under study
3. Describing the disease by time, place and
person
4. Measurement of disease
5. Comparing with known indices
6. Formulation of an etiologic hypothesis
7. Defining the population
Why ?
Population forms the denominator
Epidemiologists are men in search of the
denominator
Population at risk
X 10n
No. of events in specified period
Rate =
no. of school children with dental caries at a certain time
Total no. of children in school at same time
X 100
Proportion of carious children in a school =
8. Defining the disease under study
Why ?
Clinical definition – Operational definition
A study on diet and dental caries…
Clinical definition of dental caries
Operational definition of dental caries
If the definition is not valid, it would be a
powerful source of error
9. Describing the disease
Frequently the distribution of the disease is
described in terms of time, place and person
Time
Year, season, month, week, day, hour of onset, duration etc.
Place
Climatic zones, country, region, urban/rural, local
community, towns, cities, institutions, etc.
Person
Age, sex, marital status, occupation, social status, education,
birth order, family size, height, weight, blood pressure,
personal habits, etc.
10. Time distribution
3 kinds of time trends/ fluctuations in disease
occurrence.
Short term fluctuations
Epidemics
Periodic fluctuations
Seasonal trends
Eg. URT infections- winter, GIT infections- summer,
malaria- rainy season
Cyclic trends
Eg. Measles in pre- vaccination period- 2-3 years,
influenza pandemics- 7- 10 years
Long term fluctuations or secular trends
Changes in the occurrence of disease over a long period of
time, generally several years or decades
Eg. Coronary heart disease, cancers, dental caries
… Describing the disease
11. Place distribution
Geographical pathology
Geogaphic variations of disease can be classified
as…
International variations
National variations
Rural- urban variations
Local variations
Migration studies
… Describing the disease
14. Person distribution
Define persons by age, sex, marital status etc.
May not necessarily represent etiological
factors, but they contribute to the
understanding of the natural history of the
disease
To identify high risk groups
… Describing the disease
15. Procedures in descriptive studies
1. Defining the population to be studied
2. Defining the disease under study
3. Describing the disease by time, place and
person
4. Measurement of disease
5. Comparing with known indices
6. Formulation of an etiologic hypothesis
16. Measurement of disease
Disease load
Mortality and morbidity data
Two kinds of studies…
Cross sectional studies/ prevalence studies
Exposure & effect are measured simultaneously
Easy & economic
Often the first step in an investigation
Longitudinal studies/ incidence studies
Exposure & outcome are measured at different times
Same individuals are observed at different times over a period
Useful in studying the natural history of the disease, risk factors
Difficult & expensive comparatively
Measurement of health related states or events
17. Comparing with known indices
The essence of any epidemiologic study is
To make comparisons
To ask questions
Can be helpful in
Finding the etiology
Identifying the high risk groups
Assessing the efficacy of health care delivery
systems and strategies
18. Formulation of an etiologic hypothesis
Hypothesis is a supposition arrived at from an
observation or reflection
The final step in a descriptive study
The hypothesis can be tested using the
techniques of analytic and experimental
epidemiology.
19. The primary objective of descriptive epidemiology is
to describe the occurrence and distribution of
disease or health related events or characteristics
within populations by time place and person; and
identifying those characteristics associated with
presence or absence of disease in individuals. This
involves systematic collection and analysis of data.
20. Uses of descriptive studies
Data pertaining to morbidity and mortality of
communities
Provide clues to etiology & help in
formulating the etiological hypothesis
Provide background data for planning,
organizing and evaluating health services
Contribute to research by describing variations
in disease occurrence by time, place and
person.
21. Classification of epidemiological studies
Epidemiological
Studies
Observational Experimental
Descriptive Analytical RCT Field Trials
Community
Trials
Cross
sectional Ecological Case-control Cohort
WHO 1993
22. Analytical studies
Second major type of epidemiological studies
Subject of interest is the individual or small
groups of individuals in contrast to descriptive
studies where researcher deals with large
populations
Tests the hypothesis
23. Ecological studies/ Correlational studies
Frequently initiate the epidemiological process
The units of analysis are populations or
groups of people rather than individuals
Eg. Dental caries- water fluoride levels
Simple to conduct and thus attractive
Often difficult to interpret since it is seldom
possible to examine directly the various
potential explanations for findings
24. Since the unit of analysis is a population or
group, the individual link between exposure
and effect cannot be made.
An ecological fallacy or bias results if
inappropriate conclusions are drawn
Association observed between variables at the
group level does not necessarily represent the
association that exists at the individual level.
Ecological studies, however, have often
provided a fruitful start for more detailed
epidemiological work.
Ecological studies/ Correlational studies
25. Cross-sectional studies
Measure the prevalence of disease and are
often called prevalence studies.
In a cross-sectional study the measurements of
exposure and effect are made at the same time.
It is not easy to assess the reasons for associ-
ations demonstrated in cross-sectional studies.
The key question - whether the exposure
precedes or follows the effect. If the exposure
data are known to represent exposure before
any effect occurred, the data analysis can be
approached in a similar way to that used in
cohort studies.
26. Cross-sectional studies are relatively easy and
economical to conduct and are useful for
investigating exposures that are fixed
characteristics of individuals, such as
ethnicity, socioeconomic status, and blood
group.
In sudden outbreaks of disease a cross-
sectional study involving measurement of
several exposures is often the most convenient
first step in an investigation into the cause.
27. Case- Control Studies
A common first approach to test causal
hypothesis
Increasingly used to know the causes of
diseases, esp rare diseases
Features of …
Both exposure and outcome have occurred before the onset of
the study
Study proceeds backwards, from effect to cause
Use a control or comparison group to support or refute an
inference
28. Design of a case-control study
Population
Cases
Controls
Exposed
Not exposed
Exposed
Not exposed
Time
Direction of enquiry
… Case- Control Studies
Retrospective X prospective???
29. Steps in …
1. Selection of cases and controls
2. Matching
3. Measurement of exposure
4. Analysis and interpretation
… Case- Control Studies
30. 1. Selection of cases & controls
Selection of cases
Define the cases
Diagnostic criteria
Eligibility criteria
Sources of cases
Hospitals
General population
… Case- Control Studies
31. Selection of controls
Crucial step in case-control studies
Controls must be
Free from the disease under study
Be similar to the cases except for the absence of the disease
under study
Sources of controls
Hospitals
Relatives
Neighborhood controls
General population
How many controls are needed?
… Case- Control Studies
32. 2. Matching
Definition:
the process by which we select controls in such a way that
they are similar to cases with regard to certain pertinent
selected variables, which are known to influence the out come
of disease and which, if not adequately matched for
comparability, could distort or confound the results.
Confounding factor
One which is associated both with exposure and disease; and
is distributed unequally in study and control groups
Although associated with ‘exposure’ under investigation, it
itself is a risk factor for the disease
Eg1. Coffee- CHD : confounding factor – smoking
Eg2. Steroid contraceptives- Breast cancer: confounder - age
… Case- Control Studies
33. Do not match the suspected etiological factor
Methods of matching
Group matching
Matching by pairs
Over matching
Difficult to find controls
Reduced odds ratio
… Case- Control Studies - Matching
34. 3. Measurement of exposure
Define and set the criteria for exposure
Information about exposure should be
obtained in the same manner for cases and
controls.
Exposure can be measured by
Interviews
Questionnaires
By studying past records
Examinations
Bias/ systematic error should be avoided
while measuring the exposure
… Case- Control Studies
35. 4. Analysis
Involves two steps
1. Exposure rates among cases and controls
2. Estimation of disease risk associated with
exposure (odds ratio)
… Case- Control Studies
36. 1. Exposure rates
Cases Controls
Smokers 33
(a)
55
(b)
Non smokers 2
( c )
27
(d)
Total 35
(a+c)
82
(b+d)
A case control study of smoking and lung cancer
Exposure rate among cases= (a/a+c)100 = (33/35) 100 = 94.2 %
Exposure rate among controls= (b/b+d)100 = (55/82) 100 = 67 %
P < 0.001. What does it mean???
However, p value does not imply causation
… Case- Control Studies
37. 2. Estimation of risk
Relative risk (RR) or Risk ratio
The ratio between incidence of disease among the exposed
and non exposed
Cases Controls
Smokers 33
(a)
55
(b)
Non smokers 2
( c )
27
(d)
Total 35
(a+c)
82
(b+d)
Relative risk =
Incidence among non exposed
Incidence among exposed
a/(a+b) / c/(c+d)
But, a typical case-control study does not provide incidence rates …
… Case- Control Studies
38. Odds ratio (cross product ratio)
It is a key parameter in the analysis of case
control studies
A measure of the strength of the association
between risk factor and outcome
Derivation of odds ratio is based on 3
assumptions
Disease under investigation is a rare one
Cases are representative of those with disease
Controls are representative of those without
disease
… Case- Control Studies
39. Cases Controls
Smokers 33
(a)
55
(b)
Non
smokers
2
( c )
27
(d)
Total 35
(a+c)
82
(b+d)
… Case- Control Studies: odds ratio
Odds ratio = ad/bc = 33 X27/ 55X2 = 8.1
Smokers have a risk of having lung cancer
8.1 times that of non smokers
40. Bias in case control studies
Bias due to confounding
Memory or recall bias
Selection bias
Berkesonian bias
Interviewer bias
… Case- Control Studies
41. ADVANTAGES of …
Relatively easy to carry out
Rapid and inexpensive (compared with cohort studies)
Require comparatively few subjects
suitable to investigate rare diseases or diseases
about which little is known.
No risk to subjects
Allows the study of several different aetiological factors (e.g.,
smoking, physical activity and personality characteristics in
myocardial infarction)
Risk factors can be identified. Rational prevention and control
programmes can be established
No attrition problems, because case control studies do not
require follow-up of individuals into the future
Ethical problems minimal
… Case- Control Studies
42. Disadvantages of …
High chances for bias
Validation of information obtained is difficult
or sometimes impossible
Selection of an appropriate control group
may be difficult
We cannot measure incidence, and can only
estimate the odds ratio but not relative risk
Difficult to establish temporality of cause and
effect
Not suited to the evaluation of therapy or
prophylaxis of a disease
Another major concern is the representative
ness of cases and controls
… Case- Control Studies
43. Cohort studies
Usually undertaken to obtain additional
evidence to refute or support the existence of
an association between suspected cause and
disease
Other names
Incidence study
Forward looking study
Longitudinal study
Prospective study
However, the most widely used and
appropriate term is cohort study
44. Features of …
Cohorts are identified prior to the appearance
of the disease under investigation
Study groups are observed over a period of
time to determine the incidence of disease
The study proceeds from cause to effect
… Cohort studies
45. Cohort is defined as a group of people who
share a common characteristic or experience
within a defined time period
Eg, age cohorts, occupational cohorts,
exposure to a drug cohorts, marriage cohort
etc.
The comparison group may be…
the general population from which the cohort is drawn
Another cohort of persons thought to have had little or no
exposure to the substance in question, but otherwise similar
… Cohort studies
46. Indications for …
When there is a good evidence of an
association between exposure and disease
When the exposure is rare but the incidence of
disease is high among exposed
When the attrition can be minimised
When ample funds are available
… Cohort studies
47. Design of a cohort study
Healthy
Population
Exposed
Not exposed
Disease
No disease
Disease
No disease
Time
Direction of enquiry
… Cohort studies
48. Considerations for selecting cohorts
Cohorts must be free from the disease under
study
Insofar as the knowledge permits, both the
groups should be equally susceptible to
disease understudy
Both the groups should be comparable in
respect of all possible variables, except the
assumed risk factors
Diagnostic and eligibility criteria of the disease
must be defined beforehand.
Inclusion and exclusion criteria should be
clearly stated before the commencement
… Cohort studies
49. Types of …
Prospective cohort study
Retrospective cohort study
Combination of retrospective and prospective
cohort studies
… Cohort studies
50. Steps in …
Selection of study subjects
Obtaining data on exposure
Selection of comparison groups
Follow up
Analysis
… Cohort studies
51. Selection of study subjects
Cohorts can be selected from
General population
Special groups
Select groups (eg. Doctors, lawyers, teachers, etc.)
Exposure groups
… Cohort studies
52. Obtaining data on exposure
Information can be obtained from
Cohorts
Review of records
Medical examination or special tests
Environmental surveys
Information about exposure should facilitate
classification of cohort members
According to whether or not they were exposed
According to the degree of exposure
… Cohort studies
53. Selection of comparison groups
Internal comparisons
External comparisons
Comparison with general population
… Cohort studies
54. Follow up
Periodic medical examination of each member
Reviewing physician and hospital records
Routine surveillence of morbidity and
mortality records
Mailed questionnaires, telephone interviews,
periodic home visits
… Cohort studies
55. Analysis
Data is analysed interms of
i. Incidence rates of outcome among exposed and non-exposed
ii. Estimation of risk
Relative risk
Attributable risk
… Cohort studies
56. Incidence rates
Incidence can be
measured directly
Incidence rate among
smokers = 70/7000 =
10 per thousand
Incidence rate among
non-smokers= 3/3000 =
1 per 1000
P < 0.001
Cigare
tte
smoki
ng
Lung
cancer
No
lung
cancer
Total
Yes 70
a
6930
b
7000
a+b
No 3
c
2997
d
3000
c+d
… Cohort studies
57. Relative risk
The ratio of incidence
among exposed and
incidence among
non-exposed
Also called ‘risk ratio’
RR=
What does it mean ???
RR is the direct measure of strength of association
between suspected cause and effect
Cigarett
e
smokin
g
Lung
cancer
No lung
cancer
Total
Yes 70
a
6930
b
7000
a+b
No 3
c
2997
d
3000
c+d
Incidence among exposed
Incidence among non-exposed = 10/1 = 10
58. Attributable risk
The difference in incidence rates between exposed and
non-exposed groups
Also called risk difference
AR =
What does it mean???
It indicates to what extent disease can be attributed to
the exposure
Suggests the amount of disease that might be
eliminated if the factor could be controlled
Incident rate among exposed – incidence rate among non-exposed
Incident rate among exposed
X 100
(10-1/10) X 100 = 90%
… Cohort studies
59. Population attributable risk
Incidence in the total
population minus
incidence among those
who were not exposed
to the suspected causal
factor
Estimates the amount by
which the disease could
be reduced in that
population if the
suspected factor was
eliminated or modified
86% of deaths from lung
cancer could be avoided
if cigarette smoking was
controlled
Heavy smokers
(exposed) a
224
Non-smokers
(non-exposed)
b
10
Total
population c
74
RR a/b= 224/10 =
22.4
Population AR (c-b) X100/c =
6400/74 = 86%
Tab. Deaths per 1,00,000 person years
… Cohort studies
60. Relative risk X Attributable risk
Relative risk
Etiological enquiries
Larger the RR, stronger
the association between
risk factor and outcome
Does not reflect the
potential public health
importance
Attributable risk
Gives a better idea of the
impact of a successful
intervention might have
in reducing the problem
… Cohort studies
61. Cardio
vascular risk in
usersof oral
contraceptives
Age
30-39 40-44
RR 2.8 2.8
AR 3.5 20.0
In this study, RR was independent of age,
but AR was very high in older age group.
This finding was the basis for not
recommending oral contraceptives for
those aged 35yrs & over
… Cohort studies
62. Advantages of cohort studies
Allow the possibility of measuring directly
the relative risk of developing the condition for those
who have the characteristic, compared to those who
do not
Allows for a conclusion of cause-effect relationship
(a necessary, but not sufficient, condition).
Because the presence or absence of the risk factor is
recorded before the disease occurs, there is no chance
of bias being introduced due to awareness of being
sick as encountered in case-control studies.
… Cohort studies
63. There is also less chance of encountering the problem
of selective survival or selective recall, although
selection bias can still occur because some subjects
who contracted the disease will have been eliminated
from consideration at the start of the study.
Cohort studies are capable of identifying other
diseases that may be related to the same risk factor.
Unlike case-control studies, cohort studies provide the
possibility of estimating attributable risks, thus
indicating the absolute magnitude of disease
attributable to the risk factor.
… Cohort studies
64. Disadvantages of cohort studies
Not always feasible.
Relatively inefficient for studying rare conditions.
They are very costly in time, personnel, space and patient
follow-up.
Sample sizes required for cohort studies are extremely large,
especially for infrequent conditions; it is usually difficult to find
and manage samples of this size.
The most serious problem is that of attrition, which can affect the
validity of the conclusion, if it renders the samples less
representative, or if the people who become unavailable are
different from those actually followed up. The higher the
proportion lost (say beyond 10-15%) the more serious the
potential bias.
… Cohort studies
65. There may also be attrition among investigators who
may
lose interest, leave for another job, or become involved
in another project.
Over a long period, many changes may occur in the
environment, among individuals or in the type of
intervention, and these may confuse the issue of
association and attributable risk.
Hawthorne effect may creep in
… Cohort studies, disadvantages
66. Case control study
Proceeds from effect to cause
Starts with the disease
Tests whether the suspected
exposure occurs more frequently
in those with the disease than
among those without the
disease.
Usually the first approach to
the testing of a hypothesis, but
also useful for exploratory
studies
Involves fewer number of
subjects
Yields relatively quick results
Suitable for the study of rare
diseases
Generally yields only estimate
of RR (odds ratio)
Cannot yield information about
diseases other than that
selected for study
Relatively inexpensive
Cohort study
Proceeds from "cause to effect".
Starts with people exposed to
risk factor or suspected cause.
Tests whether disease occurs
more frequently in those
exposed, than in those not
similarly exposed.
Reserved for testing of precisely
formulated hypothesis
Involves larger number of
subjects
Long follow-up period often
needed, involving delayed
results.
Inappropriate when the disease
or exposure under investigation
is rare.
Yields incidence rates, RR as
well as AR.
Can yield information about
more than one disease outcome.
Expensive.
67. Nested case-control studies
A combined design of case-control and cohort
studies
Cases and controls are selected from the study
population of a cohort study
Less expensive and less time consuming than
a cohort study, yet yields the findings with
nearly the same level of precision
Reduced bias and temporal ambiguity
compared to a case-control study
Mostly used in occupational epidemiology
68. Attribute Type of analytical strategy
Case-control Cohort Cross-sectional
Classification of
population
Population free from
condition or disease,
with or without
characteristic
Cases with condition
(disease) with or with-
out the characteristic,
and controls
Populations without
identification of
condition or
characteristic
, Sample represented Non-diseased Uncertain: the source
population of the cases
is unknown
Survivors at a point or
period in time
Temporal sequence Prospective or
retrospective
Retrospective Contemporary or
retrospective
Function Compares incidence
rates in exposed and
unexposed
Compares prevalence
of exposure among
cases and controls
Describes association
between exposure and
disease simultaneously
Outcome Incidence of disease in
exposed and
unexposed
Prevalence of
exposure in cases and
controls
Prevalence of disease
in exposed and
unexposed
Risk measure Relative risk,
attributable risk
Odds ratio (estimate of
relative risk)
Prevalence ratio
(inexact estimate of
relative risk); also odds
ratio
Evidence of causality Strong Needs more careful
analysis
Only suggestive
Bias Easy to manage Needs more effort and
sometimes very difficult
to manage
May be very difficult to
manage
69. Basis Cohort Case-control Cross-sectional
Rare condition Not practical Bias Not appropriate
To determine a
precise risk
Best Only estimate
possible
Gives relative
prevalence, not
incidence
To determine
whether exposure
preceded disease
Best Not appropriate Not appropriate
For administrative
purposes
Not appropriate Not appropriate Best
If attrition is a
serious problem
Not appropriate Attrition is
usually minimal
Attrition may
have occurred
before the study
If selective survival
is problem
Best Not appropriate Not appropriate
If all factors are not
known
Best Not appropriate Less appropriate
Time and money Most expensive Least expensive In between
CHOICE OF STRATEGY
70. Experimental studies
What is an experimental study?
When should it be taken up?
Aims of …
To provide scientific proof for etiological or risk factors…
To establish safety and efficacy of diagnostic and treatment
techniques and procedures
To assess the efficiency and effectiveness of health services for
the prevention, control and treatment of diseases
Animal studies
Human studies
71. Randomized controlled trials (RCTs)
In modern usage, experimental epidemiology
is often equated with Randomized controlled
trials
Questioned the validity of widely used
treatments such as oral hypoglycemic agents,
varicose vein stripping, tonsillectomy,
hospitalization of all patients with myocardial
infarction etc.
“For new programmes or therapies, the RCT is
the No.1 method of evaluation”_ Park
Randomized…
Controlled…
72. D
e
s
i
g
n
o
f
a
n
R
C
T
Select suitable population
(Reference or target population)
Select suitable sample
(Experimental or study population)
Selection by defined criteria
Potential participants
(Meet selection criteria)
Participants
Invitation to participate
Randomization
Experimental group
Control group
Manipulation,
Follow up
&
Assessment
Non-participants
(do not meet selection criteria)
Non-participants
(do not give consent)
73. Steps in a RCT
1. Drawing up a protocal
2. Selecting reference and experimental
population
3. Randomization
4. Manipulation or intervention
5. Follow- up
6. Assessment of outcome
74. The protocol
A strict protocol is the basic requisite
It specifies
Aims & objectives of the study
Questions to be answered
Criteria for study and control groups
Sample size,
Standardization of working procedures and schedules
… till the evaluation of the outcomes
It aims at preventing bias and reducing the
sources of error
Preliminary or pilot studies before setting the
protocol
75. Selecting reference & experimental populations
Reference or target population
Experimental or study population
Consent
Representative of the reference population
Satisfy selection criteria
76. Randomization
A statistical procedure by which the study
participants are allocated in to groups- usually
called study and control groups
Every individual gets an equal chance of being
allocated in to either group or any of the trial
groups
Eliminates selection bias and allows
comparability
Comparability is Assured by matching. But
the limitation of matching…
77. Manipulation
Experimental group is exposed to the procedure under test,
strictly according to the pre-determined protocol
Follow up
Examination of experimental & control groups at defined
intervals of time
Examinations should be done in a standard manner, with
equal intensity, under the same circumstances & in the same
timeframe
Duration of the trial …
Attrition
79. Some designs of RCT
Concurrent parallel design
Cross-over design
Split mouth technique
80. Field trials
Study population is disease free/ healthy
individuals, presumed to be at risk
Data collection in the field, among general
population
Often huge undertakings involving major
logistics and financial considerations
Preventive in nature
General population
Eg. Salk vaccine trials to prevent polio myelitis
- 1 million children
81. Community trials
Study groups are communities rather than
individuals
Diseases that have social origin
Coronary heart disease studies
Limitations
Small number of communities can be included
Random allocation of communities is not practical
Difficult to isolate communities from general ongoing
changes
83. Random error
Divergence due to chance alone
Major sources
Individual biologic variation
Sampling error
Measurement error
It can never be completely eliminated, but
minimized to the maximum extent
84. Systematic error
Also called bias
Results are different from the true values in a
systematic manner
Lesser the bias, greater the accuracy
Over 30 types of bias have been identified
Major ones are
Selection bias
Measurement bias
Recall bias
Interviewer bias
Berkesonian bias
Bias due to confounding
85. References
1. R. Beaglehole, R. Bonita, T. Kjellstrom. Basic Epidemiology. World
Health Organization, Geneva .
2. Health research methodology: A guide for training in research methods,
2nd edition. World Health Organization, Geneva.
3. K. Park. Park’s Text book of Preventive and Social Medicine, 18th edition
4. Soben Peter. Essentials of Preventive and Community Dentistry, 2nd
edition
5. Brian Mc Mahon, Thomas F.Pugh, Liitle. Epidemiology- Principles and
methods. Brown and Co. Boston.
6. Kenneth J. Rothman, Sander Greenland. Modern epidemiology, 2nd
edition. Lippincott Williams & Wilkins.
