This document provides an overview of analytical epidemiology study designs, focusing on case-control studies. It defines a case-control study as one that compares exposures in individuals who have a disease (cases) to those who do not (controls) to identify potential risk factors for the disease. The key steps of a case-control study are described as: 1) selecting cases and controls, 2) matching cases and controls, 3) measuring exposure, and 4) analyzing and interpreting the data. Advantages are that they are relatively easy and inexpensive to conduct, while disadvantages include reliance on recall and potential for selection bias. Nested case-control and case-cohort designs are also summarized as variations that incorporate elements of cohort studies.

1. ANALYTICAL EPIDEMIOLOGY
DR MAMATA M NAIK
2nd MDS
PUBLIC HEALTH DENTISTRY

2. CONTENTS
• Introduction
• Epidemiology
• Types of Epidemiological Studies
• Analytical Epidemiology
• Case control study
• Nested case-control study
• Cohort study
• Ecological study
• Conclusion

3. CASE-CONTROL STUDY DESIGN
• Contents
1. Introduction
2. Framework
3. Steps
4. Bias
5. Application
6. Advantages & Disadvantages
7. Classical studies

4. CASE-CONTROL STUDY DESIGN
• Referred to as, case referent, retrospective or trohoc study
• A common first approach to test causal hypothesis.
• Involves 2 populations- Cases and Controls.
• Unit of study is individual rather than the group.
• Focus is on disease / some other health problem that has already developed.

5. THREE DISTINCT FEATURES
• Both exposure and outcome have occurred before the start of the study
• The study proceeds backwards from effect to cause
• Uses a control / comparison group to support / refute inference

6. Design of a Case Control Study

7. CASE-CONTROL STUDY
If my hypothesis is
“"cigarette smoking causes lung cancer”

8. CASE-CONTROL STUDY
1. Assembling group of lung cancer
cases and suitably matched controls.
2. Explore the past history of the two
groups for smoking –
RETROSPECTION
3. If the frequency of smoking is higher
in cases than in controls…..
Then an association is said to exist
smoking and lung cancer

9. CASE-CONTROL STUDY
STEPS
1. Selection of cases and controls
2. Matching
3. Measurement of exposure
4. Analysis and interpretation

10. CASE-CONTROL STUDY
1. Selection of cases and controls :
A suitable group of cases and a group of controls is to be identified.
(A) Selection of cases :
Definition of a case : A person in the population or study group
identified as having the particular disease, health disorder or condition
under investigation.
(Dictionary of Epidemiology: 3rd ed; John M Last. 2000)

11. CASE-CONTROL STUDY
• CASES
Diagnostic criteria
Eligibility criteria
• The diagnostic criteria of the disease and the
stage of the disease - specified before the
study is undertaken.
• Should not be altered or changed till the
study is over.
A criterion customarily employed – is the
requirement that only newly diagnosed
(incident cases)within a specified period of
time are eligible .

12. Sources of cases:
I. General population :
 In a population based study all cases of the study disease occurring within a
defined geographical area
 Source- Survey, Disease registry, Hospital network
 Entire case series or a random sample is taken
 Cases- fair representative of all cases in the population

13. CASE-CONTROL STUDY
II. Hospitals :
• Convenient
• May be drawn from a single hospital or a network of hospitals
• Desirable to select from several hospitals in the community
• The entire case series or a random sample of it is selected.

14. CASE-CONTROL STUDY
(B) Selection of controls :
• Definition of control: Person or persons in a comparison group that differs, in
disease experience (or other health related outcome) in not having the outcome
being studied.
(Dictionary of Epidemiology: 3rd ed; John M Last. 2000)
1. Must be as similar to the cases as possible, except for the absence of the
disease under study.
2. Controls must be identified before the study begins.
3. Controls are important because it is against them, comparison, inferences and
judgements are made about the outcome of the investigation

15. CASE-CONTROL STUDY
• Sources of controls:
I. Hospitals
II. Relatives
III. Neighbourhood controls
IV. General population

16. CASE-CONTROL STUDY
• 1. Hospital controls-
• Convenient and economical
• Same hospital, but with other illness than the disease under study.
• Ideally- Controls must have undergone the same diagnostic work-up as the cases;
except with negative results.

17. CASE-CONTROL STUDY
2. Relatives
• The controls may also be taken up from relatives like spouses and siblings
• Siblings controls may be unsuitable when genetic conditions are under study

18. CASE-CONTROL STUDY
3. Neighbours-
• Controls may be drawn from persons living in the same locality, working in the
same factory or children in the same school

19. CASE-CONTROL STUDY
4. General population-
• Can be obtained from a defined geographical area by taking a random sample of
individuals free of the study disease.
• They should accurately reflect the population that is free of the disease of interest.

20. CASE-CONTROL STUDY
2. Matching :
Matching is defined as the “ process by which we select controls in such a
way that they are similar to cases with regard to certain pertinent selected
variables(age) which are known to influence the outcome of the disease and which if
not adequately matched for comparability, could distort or confound the results.”

21. CASE-CONTROL STUDY
MATCHING
Group matching
(frequency matching)
Pair matching
Proportion of controls with a certain
characteristic is identical to the
proportion of cases with the same
characteristic.
e.g. if 25% of the cases are married, the
controls will be selected so that 25% of
that group is also married.
A control is selected who is similar to the
case in terms of the specific variable or
variables of concern.
e.g., if the first case enrolled in our study
is a 25‐year‐old female, we will seek a
25‐year‐old female control.

22. CASE-CONTROL STUDY
• Problems with matching-
1. Practical Problems with Matching: If an attempt is made to match according
to too many characteristics, it may prove difficult or impossible to identify an
appropriate control.
2. Conceptual Problems with Matching: Once the controls are matched to cases
according to a given characteristic, that characteristic cannot be studied.
3. Unplanned matching

23. CASE-CONTROL STUDY
• CONFOUNDING :
• A confounding factor is associated both with exposure and disease
• It is distributed unequally in study and control groups.
• It is one that, although associated with "exposure" under investigation, is itself,
independently of any such association, a "risk factor” for the disease.

24. Relationship between coffee and cancer of pancreas:
• Smoking is a confounder, because, although the interest was in a possible
relationship between coffee consumption (Factor A) and cancer of the pancreas
(Disease B):
1. Smoking is a known risk factor
for Pancreatic cancer
2. Smoking is associated with coffee drinking,
but is not a result of coffee drinking.

25. CASE-CONTROL STUDY
3. Measurement of exposure-
Information about exposure should be obtained in precisely the same manner both
for cases and controls.
Obtained by interviews, questionnaires or past records or hospital records.

26. CASE-CONTROL STUDY
4. Analysis :
• Final step in analysis is done to find out-
1. Exposure rates among cases and controls to the suspected factor
2. Estimation of disease risk associated with exposure (Odds Ratio)

27. CASE-CONTROL STUDY
1. Exposure Rates:
Case Control study provides a direct estimation of exposure rates
(frequency of exposure) to a suspected factor in disease and non disease
groups.

28. Example: Smoking and Lung Cancer
Exposure rates:
Cases= a/(a+c) = 33/35 = 94.2 %
Controls= b/(b+d) = 55/82 = 67.0 %

29. CASE-CONTROL STUDY
• The presence of statistical association between the exposure status and outcome is
determined by calculating the p value (using tests of significance).
• The particular test of significance will depend upon the variables under
investigation.
• According to convention, if P is less than or equal to 0.05, it is regarded as
"statistically significant".

30. CASE-CONTROL STUDY
2. Estimation of risk
• The estimation of disease risk associated with an exposure is obtained by an index
known as relative risk.
• Relative Risk- the ratio between the incidence of disease among exposed and the
incidence among non-exposed.

31. CASE-CONTROL STUDY
• Odds Ratio (Cross-product ratio)
Odds Ratio (OR) is a measure of the strength of the association
between risk factor and outcome.
Odds ratio is closely related to relative risk.

32. CASE-CONTROL STUDY
• The odds ratio is based on three assumptions:
(a) the disease being investigated must be relatively rare;
(b) the cases must be representative of those with the disease, and
(c) the controls must be representative of those without the disease.

33. CASE-CONTROL STUDY

36. CASE-CONTROL STUDY
• BIAS
Bias is any systematic error in the determination of the association
between the exposure and the disease.
• Many types of bias may be seen -
a) Bias due to confounding: Is to be removed by proper matching between the
cases and controls

37. CASE-CONTROL STUDY
(b) Memory or recall bias :
• When cases and controls are asked questions about their past history, it may be
more likely for the cases to recall the certain events or factors, than the controls.
For example,
Those who have had a myocardial infarction might be more likely to remember and
recall certain habits or events than those who have not.
• Thus cases may have a different recall of past events than controls.

38. CASE-CONTROL STUDY
c) Selection bias: Cases and controls may not be fully representative of cases
and controls in the general population
e) Berkesonian bias: Due to different rates of admission to hospitals of patients
with different diseases .
d) Interviewer’s bias: When the interviewer knows the hypothesis and who the
cases are. It can be eliminated by blinding.

39. CASE-CONTROL STUDY
ADVANTAGES
1. Relatively easy to carry out.
2. Rapid and inexpensive.
3. Require comparatively few subjects.
4. Particularly suitable to investigate rare diseases or diseases
about which little is known.
5. No risk to subjects.
6. Allows the study of several different aetiological factors
7. Risk factors can be identified.
8. No attrition problems.
9. Ethical problems minimal.

40. CASE-CONTROL STUDY
DISADVANTAGES
1. Problems of bias relies on memory or past - validation of information obtained is
difficult
2. Selection of an appropriate control group may be difficult.
3. Cannot measure incidence, and can only estimate the relative risk.
4. Cannot distinguish between causes and associated factors.
5. Not suited - evaluation of therapy or prophylaxis of disease.

41. • Adenocarcinoma of
vagina.Herbst, A.L.
et al

43. • Oral contraceptives and
thromboembolic disease.
Vassey, M.P. and R.Doll
(1968). Brit. Med. J., 2: 199

45. Thalidomide tragedy.
Speirs, A.L (1962). Lancet, 1:
303

47. CASE CONTROL STUDIES BASED
IN A COHORT
• Is it possible to take advantage of both case-control and cohort study
designs by combining some elements of both into a single study.
• The resulting combined study is in effect a hybrid design in which a
case-control study is initiated within a cohort study.

48. • In this type of study, a population is identified and followed over time. i.e for a
period of years.
• A small percentage of study participants manifest the disease, whereas most do
not.
• A case-control study is then carried out using as cases - persons in whom the
disease developed,
• controls in whom the disease did not develop.

49. • Such cohort-based case-control studies can be divided into two types , based
on approach used for selecting the controls.
1. Nested case-control studies
2. Case-cohort studies

50. 1. Nested case-control studies
• In nested case-control studies the controls are a sample of individuals who are at
risk for the disease at the time each case of the disease develops.

53. 1. Nested case-control studies
• At the end of 5 years, five cases have appeared, and at the times the cases
appeared a total of five controls were selected for study.
• In this way, the cases and controls are, in effect, matched on calendar time
and length of follow-up.
• A control who is selected early in the study could later develop the disease
and become a case in the same study because a control is selected each time a
case develops.

54. •Example of Nested Case Control Study
• A nested case control study examined the relationship between serum
organochlorides and breast cancer.
• Study subject were drawn from a cohort of over 57,000 female members of
Kaiser Permanente Medical Care Program who went multiphasic
examination in late 1960s, at which time blood samples were collected and
stored.
• The cohort was followed up to 1990.
• 150 women who developed breast cancer during the follow up period
were then randomly selected and individually matched to 150 women in the
cohort who had remained free of breast cancer.

55. 2. Case-cohort studies
• In this design - cases develop at the same times , but the controls are randomly
chosen from the defined cohort with which the study began.

56. • This subset of the full cohort is called the subcohort
• An advantage - controls are not individually matched to each case, is possible to
study different diseases (different sets of cases) in the same case-cohort study
using the same cohort for controls.
• In this design, cases and controls are not matched on calendar time and length of
follow-up; instead, exposure is characterized for the subcohort.

57. REFERENCES
1. Park, K. (2019) Park’s Textbook of Preventive and Social Medicine, 25th
edition: Bhanot
2. Ahrens, W., Pigeot I. (2005) Handbook of Epidemiology: Springer
3. Friis, R.H., Sellers, T.A. (2004) Epidemiology for Public Health Practice,
3rd edition: Jones and Bartlett
4. MacMohan, B., Trichopoulos, D. (1996) Epidemiology Principles and
Methods, 2nd edition: Little, Brown and Company
5. Kaye KS, Harris A, Samore M, Carmeli Y. The case-case-control
study design: addressing the limitations of risk factor studies for
antimicrobial resistance
6. Valanis B. Epidemiology in health care. Prentice Hall; 1999

59. CROSS OVER STUDY DESIGN
• Case-Crossover Design is a scientific way to ask and answer the
question that “Was the patient doing anything unusual just before the
onset of the disease”

60. CROSS OVER STUDY DESIGN
CONCEPT
• For example, to find out what might trigger the onset of myocardial infarction, we may
wonder if the patient endured certain heavy physical activity, or
• If he/she consumed specific type of food right before the disease.
• If we can gather the so called "exposure" information from many patients, it is possible
to determine the effect of the event or "attitude" on the onset of disease.

61. CROSS OVER STUDY DESIGN
CONCEPT

62. CROSS OVER STUDY DESIGN
• Within the subjects
• Only subjects (cases) who have experienced the disease of interest are
selected.
• Compare exposure just before event and exposure at an earlier time, in
the same case
• Suited to brief (acute) exposure with a relatively rapid effect on the
outcome
• Good for studying effects of transient exposures

63. CROSS OVER STUDY DESIGN
• Biased selection of controls (selection bias) is eliminated (assuming matched
analysis is conducted) since controls represent the population that produced the
cases.
• Since each subject serves as their own control, thus, “fixed” confounders are
eliminated.
• However, confounding can occur from factors that vary over time and are
associated with the exposure and disease of interest (e.g. smoking).

64. CROSS OVER STUDY DESIGN

65. CROSS OVER STUDY DESIGN
• Advantages of Case-crossover
• Efficient –self-matching
• Efficient –select only cases
• Can use multiple control windows for one case window
• On the other hand, the case crossover study can also be viewed as a retrospective
cohort study as the control data are not necessarily the "counts", they can be units
of exposure person-time.

66. CROSS OVER STUDY DESIGN
• Disadvantages of Case-crossover
• Information bias –inaccurate recall of exposure during control window(can be
overcome by choosing control window to occur after case window)
• Requires careful selection of time period during which the control window occurs
(circumstance associated with the control window should be similar to
circumstances associated with case window)
• Requires careful selection of the length and timing of the windows (e.g., in an
investigation of the risk of cell phone usage on auto accidents, cell phone usage
that ceases 30 minutes before accident unlikely to be relevant to accident)

67. CASE-CASE CONTROL DESIGN
• This design uses two separate case–control analyses within a single
study

68. CASE-CASE CONTROL DESIGN

69. .
CASE-CASE DESIGN
• It is an efficient alternative to case-control study and can be useful in
identifying risk factors for healthcare associated infection (HAI)
outbreak and clusters
Cases of interest
Comparison cases ( or people with a
different disease.)

72. ANALYTICAL EPIDEMIOLOGY
part 2
DR MAMATA M NAIK
2nd MDS
PUBLIC HEALTH DENTISTRY

73. CONTENTS
• Introduction
• Epidemiology
• Types of Epidemiological Studies
• Analytical Epidemiology
• Case control study
• Nested case-control study
• Cohort study
• Ecological study
• References

74. Cohort Study
• Analytical study , undertaken to obtain additional evidence to refute or support
the existence of an association between suspected cause and disease.
• Prospective study, longitudinal study, incidence study, forward-looking study
• Aim: to establish the aetiology or association of various risk factors of a disease

75. Cohort Study
• “Cohort” is defined as a group of people who share a common characteristic or
experience within a defined time period.
E.g., birth cohort,
exposure cohort
marriage cohort

76. • Comparison group-
1. General population from which the cohort is drawn.
2. Another cohort of people with little/ no exposure to the substance in question,
but otherwise similar.

77. Features of cohort studies are:
• The cohorts are identified prior to the appearance of the disease under
investigation
• The study groups, so defined, are observed over a period of time to determine the
frequency of disease among them.
• The study proceeds forward from cause to effect.

78. Indications for cohort studies:
• When there is a good evidence of an association between exposure and disease.
• When exposure is rare, but the incidence of the disease is high among the exposed.
• When attrition of study population can be minimised.
• When ample funds are available.

79. Design of a Cohort study
• Basic approach in cohort studies - ‘Cause to effect’.
• Exposure has already occurred, but disease has not.
• Investigator Observes events that have not yet occurred

80. Design of a Cohort study

81. Types of Cohort studies
On the basis of the time of occurrence of disease in relation to the time at which
the investigation is initiated and continued:
1. Prospective cohort studies
2. Retrospective cohort studies
3. A combination of retrospective and prospective cohort studies.

82. Prospective Cohort study
• Concurrent cohort study / Longitudinal study
• A study in which the outcome has not yet occurred at the time the investigation
begins.
• The investigator identifies the original population at the beginning of the study
and, in effect, accompanies the subjects concurrently through calendar time until
the point at which the disease develops or does not develop.

84. Problems :
• The study will take long time to complete.
• If one is fortunate enough - research grant, such funding is generally limited to a
maximum of only 5 years.
• In addition, with a study of this length, there is the risk that the study subjects will
outlive the investigator, or at least that the investigator may not survive to the end
of the study.

85. Prospective Cohort study
E.g.,
• US Public Health’s Framingham heart study
• Doll and Hill’s prospective study on smoking and lung cancer
• Study on oral contraceptives and health by the Royal College of General
Practitioners

86. US Public Health’s Framingham Heart Study (1948)
• Classic example of cohort study.
• Initiated in 1948 - town of Framingham (Massachusetts) had a population of
28,000
• Aim- Study the relationship of a number of (risk) factors to the subsequent
development of cardiovascular disease.
• Both men and women between 30 and 59 years of age and were free of
cardiovascular disease at that time participated in the study with a sample of 5127
people.

87. • The study population was examined every 2 years for a 20 year period
• The study showed increasing risk of CHD with increasing serum cholesterol levels
in the 45-54 age group.
• Smoking was more strongly associated with sudden death from CHD than with
less fatal forms of the disease.
• Risk factors - found to include male sex, advancing age, high serum lipid
concentration, high blood pressure, cigarette smoking, diabetes mellitus, obesity,
low vital capacity and certain ECG abnormalities.

88. Dolls and Hills Prospective Study on Lung Cancer
• A prospective cohort study which ran from 1951 to 2001
• October 1951 – Richard Doll and Andrew Hill sent a questionnaire to 59,600
British doctors listed in the Medical register of the UK enquiring about their
smoking habits.

89. • Form two cohorts (smokers and non-smokers) who were similar in all other
respects like age, education and social class.
• They received usable replies from 40,701 physicians.
• The respondents were stratified into decade of birth, sex and their cause-specific
mortality, as well as general physical health and current smoking habits
• Followed up in further questionnaires in 1957, 1966, 1971, 1978, 1991 and finally
in 2001.

90. Conclusions
• Both lung cancer and "coronary thrombosis" occurred markedly more often in
smokers.
• Smoking decreases life span up to 10 years, and that more than 50% of all smokers die of
a disease known to be smoking-related, although the excess mortality depends on amount
of smoking, specifically, on average,
- Those who smoke until age 30 have no excess mortality
- Those who smoke until age 40 lose 1 year
- Those who smoke until 50 lose 4 years
- Those who smoke until age 60 lose 7 years.

91. The Nurses' Health Study (NHS) 1976
• The Nurses' Health Study (NHS) was established by Dr. Frank Speizer in 1976 .
• The primary motivation for the study was to investigate the potential long-term
consequences of oral contraceptives, which were being prescribed to hundreds of
millions of women.
• Nurses were selected as the study population because of their knowledge about
health and their ability to provide complete and accurate information regarding
various diseases, due to their nursing education.

92. • Relatively easy to follow over time and were motivated to participate in a long-
term study.
• The cohort - limited to married women due to the sensitivity of questions about
contraceptive use at that time.
• 121,700 married nurses, aged 30 to 55 in 1976 participated in this study.
• Every two years, cohort members receive a follow-up questionnaire with
questions about diseases and health-related topics.
• The original focus- contraceptive methods, smoking, cancer, and heart disease,

93. • The study brought out the risks and benefits of oral contraceptive use.
• For example, the study showed that the risk of hypertension increases, and the risk
of benign breast disease decreases with the dose of progestogen in the combined
pill which is an important finding.
• The study found an increased mortality from diseases of cardiovascular system in
pill users.

94. Retrospective Cohort study
• Historical cohort study, prospective study in retrospect, non-concurrent
prospective study
• A study in which the outcomes have all occurred before the start of the
investigation.
• The investigator goes back in time to select his study groups from existing records
and traces them forward through time , from a past date fixed on the records,
usually up to the present.

96. Retrospective Cohort study
• Historical data from the past is used to telescope the frame of calendar time for the
study and obtain the results sooner.
• The study begins with a pre-existing population to reduce the duration of the
study.
• These studies are particularly useful for unusual exposures or occupational
exposures.

97. • If an investigator - to determine whether exposure to chemicals used in tire
manufacturing was associated with an increased risk of death,
• One might find a tire manufacturing factory that had been in operation for several
decades.
• Potentially use employee health records to identify
Exposed workers(e.g., workers who actually manufactured tires) and
Non-exposed coworkers (e.g., clerical workers or sales personnel).
• One could then ascertain what had happened to all the subjects and compare the
incidence of death in the exposed and non-exposed workers.

99. Retrospective Cohort study
• More economical
• Produce results more quickly
EXAMPLE :
• Study of the role of arsenic in human carcinogenesis
• Study of lung cancer in uranium miners
• Study of mortality experience of group of physicians in
relation to their probable exposure to radiation

100. AMBISPECTIVE COHORT STUDIES
• Combination of Retrospective & Prospective Cohort studies
• The cohort is identified from past records, and is assessed of date for the outcome.
• The same cohort is followed up prospectively into future for further assessment of
outcome.
e.g.,
• Court-Brown and Doll study on the effects of
radiation

101. COURT-BROWN & DOLL- EFFECTS OF RADIATION
• They assembled a cohort in 1955 consisting - 13,352 patients who had received
large doses of radiation therapy for ankylosing spondylitis between 1934 and1954.
• The outcome evaluated was death from leukemia or aplastic anemia between
1935 and 1954.
• They found that the death rate from leukemia or aplastic anemia was
substantially higher in their cohort than that of the general population.
• A prospective component was added to the study and the cohort was followed, as
established in1955, to identify deaths occurring in subsequent years

102. Elements of Cohort Study
Analysis
Follow-up
Selection of comparison groups
Obtaining data on exposure
Selection of study subjects

103. Selection of Study subjects
General population
OR
Special groups
Select groups
Exposure groups

104. General population:
• When the exposure or cause of death - fairly frequent in the
population.
• If population is large, an appropriate sample can be taken.
• The exposed and unexposed segments of the study population
should be representative of the corresponding segments of the
general population.

105. Special groups:
1. Select groups: These may be
• Professional groups
• Government employees
• Pregnant women
Advantages-
• Usually homogenous
• Easy accessibility and follow-up

106. Exposure groups:
• If the exposure is rare, a more economical procedure is to select a cohort of
persons known to have experienced the exposure.
• Readily accessible source
workers in industries
high-risk situations (e.g., radiologists exposed to X-rays).
Advantages :
• Facilitates classification of cohort members according to the degree or duration of
exposure to the suspected factor for subsequent analytical study

107. Obtaining data on exposure
• Cohort members
• Review of records
• Medical examination or special tests
• Environmental surveys

108. • Information about exposure should be collected in a manner that will allow
classification of cohort members:
1. According to whether or not they have been exposed to the suspected factor
2. According to the level or degree of exposure

109. Selection of comparison groups
Methods of assembling comparison groups:
• Internal comparisons
• External comparisons
• Comparison with general population rates

110. 1. Internal comparison:
• Comparison groups are in-built.
• Single cohort enters the study and its members are classified into several
comparison groups based on the degree of exposure to risk before
development of the disease
• Groups are compared in their subsequent rates of morbidity and mortality.
Classification of
exposure-
cigarettes
No. of
deaths
Death rate
½ pack 24 95.2
½ - 1 pack 84 107.8
1-2 packs 90 229.2
>2 packs 97 264.2

111. 2. External comparison
• When information on degree of exposure is not available, an external control
needs to be put up to evaluate the experience of the exposed group.
• Ex- smokers and non-smokers
• The study and comparison cohorts should be similar in demographic and other
important variables

112. 3. Comparison with general population rates
• The mortality experience of the exposed group is compared with the
mortality experience of the general population in the same geographic area.
• E.g- Comparison of frequency of lung cancer among uranium mine workers
with the frequency of lung cancer in the general population.

113. Follow-up
Methods to obtain data for assessing the outcome should be devised at the start of
the study depending on the outcome to be determined :
• Periodic medical examination of each member of the cohort
• Reviewing physician and hospital records
• Routine surveillance of death records
• Mailed questionnaires, telephone calls, periodic home visits- preferably all 3 on an
annual basis

114. 5. Analysis
• The data are analyzed in terms of
1. Incidence rates of outcome among exposed and non-exposed
2. Estimation of risk

115. Among smokers = 70/7000 = 10 per 1000
Among non smokers = 3/3000 = 1 per 1000
5. Analysis
Incidence Rates: Incidence rate can be calculated among those
exposed and those non exposed as-
Cigarette
smoking
Developed
lung cancer
Did not
develop lung
cancer
Total
Yes 70
(a)
6930
(b)
7000
(a+b)
No 3
(c)
2997
(d)
3000
(c+d)

116. Estimation of Risk
• After calculating the incidence rates, estimation of the risk of outcome in the
exposed and non exposed groups is carried out.
• This is done in terms of
1. Relative risk
2. Attributable risk

117. Estimation of Risk
Relative Risk
• The ratio of the incidence of the disease among exposed and the incidence among non-
exposed.
Attributable risk
It is the difference in incidence rates of disease (or death) between an exposed group and
non- exposed group.

118. Relative Risk :
Incidence of disease (death) among exposed
Incidence of disease (death) among unexposed
= RELATIVE RISK (RR)

119. Incidence Rates :
Among smokers = 70/7000 = 10 per 1000
Among non smokers = 3/3000 = 1 per 1000
RR is 10 i.e., smokers are 10 times at greater risk of developing lung cancer than non-smokers
Cigarette smoking Developed lung cancer Did not develop lung
cancer
total
Yes 70
(a)
6930
(b)
7000
(a+b)
No 3
(c)
2997
(d)
3000
(c+d)

120. Relative risk/Risk ratio
A direct measure of the strength of the association between
suspected cause and effect.
Estimation of relative risk is important in etiological enquiries.
. Greater the relative risk, greater is the strength of association between the
suspected factor and the disease.
RR of 1 = no
association
RR > 1 suggests
positive association
between exposure
and outcome

121. 5. Analysis
Attributable Risk
• The difference in incidence rates of disease between an exposed group and non-
exposed group.
Risk Difference
• Expressed in percentage.
• Indicates to what extent the disease under study can be attributed to the exposure

122. 5. Analysis
Attributable Risk :
Incidence of disease rate among exposed - Incidence of disease rate among non-exposed
Incidence rate among exposed
x 100

123. Incidence Rates :
Among smokers = 70/7000 = 10 per 1000
Among non smokers = 3/3000 = 1 per 1000
Cigarette smoking Developed lung cancer Did not develop lung
cancer
total
Yes 70
(a)
6930
(b)
7000
(a+b)
No 3
(c)
2997
(d)
3000
(c+d)
ATTRIBUTABLE RISK = 10-1
10
X 100 = 90%

124. 5. ANALYSIS
Population Attributable Risk
Refers to the attributable risk for the total population.
• The incidence of the disease in the total population minus the incidence of disease among those
who were not exposed to the suspected causal factor.
• Provides an estimate of the amount by which the disease could be reduced in that population if
the suspected factor was eliminated or modified.

125. 5. Analysis
Population Attributable Risk
86% of deaths from lung cancer could be avoided if the risk
factor of cigarettes were eliminated
Deaths per 100000 person years
Heavy smokers 224 (a)
Non –smokers 10 (b)
Deaths in total population 74 (c)
Individual RR a/b = 224/10 =22.4
Population AR (c-b)/ c = 86%

126. RELATIVE RISK vs ATTRIBUTABLE RISK
• Relative risk is better for
assessing the aetiological
role of a factor in disease.
• The larger the relative risk,
the stronger is the
association between the
cause and effect.
• Attributable risk reflects the
potential public health
importance.
• It gives a better idea of the
impact of successful
preventive public health
program in reducing the
health problems.

127. • Bias can be defined as any systematic error in the design, conduct, or analysis of a
study.
• A number of potential biases must be either avoided or taken into account in
conducting cohort studies.
1. Selection Bias- the approach adopted for selecting subjects for a study.
2. Information Bias- the approach adopted for collecting or measuring data from a
study.
Biases in cohort studies

128. Selection Bias
• Selection bias may occur in cohort studies if the exposed and unexposed groups
are not truly comparable
• e.g. comparing an occupational cohort with the general population.

129. Selection Bias- Loss to follow-up bias
• Loss to follow-up bias occurs if the loss of follow-up is associated with both
exposure and outcome e.g. associated with exposed cases.
• It behaves similarly to non-response bias in cohort studies.
• Differences in loss to follow-up between exposure groups can lead to bias as the
people who are lost to follow-up may be more (or less) likely to have developed
the outcome of interest

130. Information bias
• If the quality and extent of information - different for exposed persons than for the
unexposed persons, a significant bias can be introduced.
• This is particularly likely to occur in historical cohort studies, in which
information is obtained from past records
• In any cohort study, it is essential that the quality of the information obtained be
comparable in both exposed and unexposed individuals.

131. Confounding Bias
• It arises due to the confounding factor.
• It occurs when other factors that are associated with the outcome and exposure
variables do not have the same distribution in the exposed and unexposed groups.

132. Advantages of cohort studies
1. Incidence can be calculated
2. Several possible outcomes related to exposure can be studied
simultaneously.
3. Provide direct estimate of relative risk
4. Dose response ratios can be calculated
5. Comparison groups formed before disease develops, certain forms of
bias minimized like misclassification of individuals into exposed and
unexposed groups
150

133. Disadvantages of cohort studies
1. Involve a large number of people .
2. Unsuitable for investigating uncommon diseases or those with low
incidence in the population .
3. Takes long time to complete study and obtain results – investigators
may have died or participants may have changed their classification.
4. Administrative problems – loss of experienced staff, loss of funding
and extensive record keeping.
151

134. 5. Drop-outs may migrate, lose interest in study or refuse to provide
information.
6. Selection of representative comparison groups is a limiting factor.
7. There may be changes in standard methods / diagnostic criteria of the disease
over prolonged follow up.
8. Expensive
9. Ethical problems
152

135. CASE CONTROL STUDY COHORT STUDY
Proceeds from effect to cause Proceeds from cause to effect
Starts with the disease Starts with people exposed to risk factor or suspected cause
Tests whether the suspected cause occurs more frequently in
those with the disease than among those without the disease
Tests whether disease occurs more frequently in those
exposed, than in those not similarly exposed
Usually the first approach to the testing of a hypothesis Reserved for testing of precisely formulated hypothesis
Involves fewer number of subjects Involves larger number of subjects
Yields relatively quick results Long follow up period often needed, involving delayed results
Suitable for the study of rare diseases Inappropriate when the disease or exposure under
investigation is rare
Generally yields only estimate of RR (odds ratio) Yields incidence rates, RR as well as AR
Cannot yield information about diseases other than that
selected for study
Can yield information about more than one disease outcome
Relatively inexpensive Expensive 153

136. Ecological Study
• An ecological study is one that examines a group as a unit of analysis.
• This type of a study design can be used for both generating a hypothesis and in
analytical studies as well.
• Example: a study on mortality due to lung diseases in different cities that are
known to have differing levels of air pollution. The unit of analysis is a city.

137. • Gives information on group characteristics but lacks information on classification
of individual level characteristics within groups.

138. Ecological study – types
Study type Design Time frame
Cross-sectional • Across communities • Same time period
Time-trend • Within the same
community
• Over time

139. Ecological study – limitations
Ecological fallacy
• An ecological fallacy is a formal fallacy in the interpretation of statistical data that
occurs when inferences about the nature of individuals are deduced from
inferences about the group to which those individuals belong.
• Fallacy of drawing inferences at individual level(i.e., regarding variability across
individuals) based on group level data.
• Arises when association between 2 variables at group level (or ecological level)
differ from association between analogous variables measured at individual level.

140. REFERENCES
1. Park, K. (2019) Park’s Textbook of Preventive and Social Medicine, 25th edition:
Bhanot
2. Ahrens, W., Pigeot I. (2005) Handbook of Epidemiology: Springer
3. Friis, R.H., Sellers, T.A. (2004) Epidemiology for Public Health Practice, 3rd
edition: Jones and Bartlett
4. MacMohan, B., Trichopoulos, D. (1996) Epidemiology Principles and Methods,
2nd edition: Little, Brown and Company
5. Kaye KS, Harris A, Samore M, Carmeli Y. The case-case-control study design:
addressing the limitations of risk factor studies for antimicrobial resistance
6. Valanis B. Epidemiology in health care. Prentice Hall; 1999