epidemiological study desgns

1. Basic steps in a survey –
An 8-step Model
1
Formulating the
research
problem
2
Conceptualizing
the research
design
3
Constructing an
instrument for
data collection
4
Selecting a
sample
5
Writing the
survey proposal
6
Collecting data
7
Processing data
8
Writing the
survey report

2. 2
Conceptualizing
the research
design

4. Observational Studies
• A DESCRIPTIVE STUDY is limited to a
description of the occurrence of a disease in a
population and is often the first step in an
epidemiological investigation.
• An ANALYTICAL STUDY goes further by
analyzing relationship between health status
and other variables.

6. Some Examples of Descriptive Studies
• Case Report
• Case Series
• Surveys
Pure descriptive studies make no
attempt to analyze the links between
outcome and exposure

8. Ecological Studies
• In an ecological study, the units of analysis are
groups of people rather than individuals.

11. Cross-sectional studies
• Because they measure the prevalence of a
disease, they are sometimes also called
‘prevalence studies’.
• Exposure and effect (outcome) are measured
at the same time.

12. Uses of cross-sectional studies
• Prevalence
• Disease outbreaks
• Assessing healthcare needs of populations.
• Trends in diseases (repeated c/s studies)
• Risk factors for diseases (e.g., NCDs)

13. Advantages and Disadvantages
• Easy and relatively inexpensive
• Less time consuming
• The temporal relationship between exposure
and effect is difficult to establish.

14. CASE-CONTROL STUDIES

15. Key Features
• The exposure experience of a group of people
who have the disease [CASES] is compared to
the exposure experience of a similar
(matched) group who do not have the disease
[CONTROLS]
• Suitable for rare diseases or diseases with long
latency periods
• The study proceeds backwards from “EFFECT
to CAUSE’

16. Basic Design

17. • Selection of cases
• Selection of controls
• Measurement of exposure
• Analysis
Steps

18. Selection of Cases
• Define a ‘case’
Hospital
General population
• Sources of cases
• ‘Incident’ cases
‘Prevalent cases’???
Temporality
Disease severity (Those who are exposed survive longer)

19. Selection of Controls
• Free from disease
• As similar to the cases (matched) as possible,
except for the absence of disease under study
• Sources of controls
• General population
• Relatives/Friends/Neighbours
• Hospital controls
• How many controls per case?
• One to four

20. “MATCHING” is the process of selecting
controls in a case-control study so that the
controls are similar to the cases with regard
to certain key characteristics-such as age, sex
and race.
Group matching
(Frequency matching)
Individual matching
(Pair matching)

21. Measurement of exposure
• Definition and criteria
• Done in the same way for both cases and
controls
• How to measure exposures?
– Interviews/Questionnaires
– Past records (Hospital, Employment)
– Laboratory measurements

22. Analysis
• Find exposure rate in cases
• Find exposure rate in controls
• Calculate “Odds Ratio”

23. Exposure
Disease
Yes No
Yes a b
No c d
Total a+c b+d
Odds Ratio=ad/bc

24. Use of Oral
Contraceptive
Thromboembolism
Yes No
Yes 26 10
No 32 106
Total 58 116
Exposure rate among cases=(26/58)x100=45%
Exposure rate among controls=(10/116)x100=9%
Odds ratio= (26x106)/(10x32)=2756/320=8.6

25. How to interpret the OR?
People who use oral contraceptives have an
8.6 times higher risk of developing
thromboembolism compared to those who
do not use oral contraceptives

26. Cigarette smoking
Lung cancer
Yes No
Yes 85 160
No 15 240
Total 100 400
Odds Ratio=(85x240)/(160x15)=8.5

27. Q. An investigator selected 40 cases of
gastric carcinoma and an equal number of
controls matched for age, sex and
socioeconomic status. It was found that
among cases 30 had an 5
evidence of H pylori
infection and among controls 15 had an
evidence of H pylori infection. Is there an
evidence of association between H pylori
infection and gastric carcinoma?

29. COHORT STUDIES

30. Key Features
• The study proceeds from “CAUSE to EFFECT”
• At the start of the study, all participants are
free from disease.
• A group of people who are ‘exposed’ to some
factor and another ‘not-exposed’ group are
followed up for a certain time. The disease
rate (incidence of disease) among ‘exposed’ is
compared to the disease rate among the ‘not-exposed’
group.

31. Basic Design

32. • Selection of study subjects
• Obtaining data on exposure
• Follow-up
• Analysis
Steps

33. Selection of Study Subjects
• General population
• Special groups
– Occupation group
– Professional group
• Radiologists
• Nurses
• Doctors
• Teachers, etc.
Free from study
disease

34. Obtaining data on exposure
Cohort
Exposed
Not-exposed
1
2
Exposed Cohort Not-Exposed Cohort
3 Low Exposure
Exposed Cohort
Medium Exposure
High Exposure

35. Follow-up
• The follow-up procedures should be similar for
both the exposed and the non-exposed
groups.
• Clear, and valid definitions for disease status.

36. Analysis
• Find disease incidence rate in exposed
• Find disease incidence rate in non-exposed
• Calculate “Relative Risk” (Risk Ratio)

37. Exposure
Disease
Total
Yes No
Yes a b a+b
No c d c+d
Incidence rate among exposed=(a/a+b)*10x
Incidence rate among non-exposed=(c/c+d)*10x
Relative Risk =
(a/a+b)
(c/c+d)

38. Exposure to
prolonged
heat stress
Kidney disease
Total
Yes No
Yes 67 4458 4525
No 39 5443 5482
Incidence rate among exposed= 14.8
Incidence rate among non-exposed= 7.1
Relative Risk= 14.8/7.1 = 2.1

39. How to interpret the RR?
People exposed to prolonged heat stress
have a 2.1 times higher risk of developing
kidney disease compared to those who are
not exposed to prolonged heat stress

40. THREE types of Cohort studies
• Prospective
• Retrospective (Historical)
• Retrospective-Prospective (Ambispective)

41. Retrospective cohort studies
Study starts
2014
1990
Data about oral
contraceptive intake
in a cohort of women
How many of the
women have
thromboembolic
disease, exposed
versus not-exposed

42. Case-control studies start with
outcome/disease
Cohort studies start with exposure
Case-control studies compare
exposure rates among cases and
controls
Cohort studies compare disease rates
among exposed and not-exposed

43. Case control Cohort
Advantages
Excellent way to study rare
diseases with long latency
Better for studying rare
exposures
Relatively quick
Provides complete data on
cases, stages
Relatively inexpensive
Allows study of more than
one effect of exposure
Requires relatively few study
subjects
Can calculate and compare
rates in exposed and
unexposed
Can often use existing
records
Choice of factors available
for study
Can study many possible
causes of a disease
Quality control of data

44. Case control Cohort
Disadvantages
Relies on recall or existing
records about past exposure
Need to study large numbers
Difficult or impossible to
validate data
May take many years
Control of extraneous factors
incomplete
Circumstances may change
during study
Difficult to select suitable
comparison group
Expensive
Cannot calculate rates Control of extraneous factors
may be incomplete
Cannot study mechanism of
disease
Rarely possible to study
mechanism of disease

47. Experimental epidemiology

48. • Intervention or experimentation involves
attempting to change a variable in one or
more groups of people.
• The effects of an intervention are measured
by comparing the outcome in the
experimental group with that in a control
group.
• Ethical considerations
• Informed consent

49. RANDOMIZED CONTROLLED TRIALS

50. A randomized controlled trial is an
epidemiological experiment designed to study
the effects of a particular intervention, usually a
treatment for a specific disease (clinical trial).
Subjects in the study population are randomly
allocated to intervention and control groups, and
the results are assessed by comparing outcomes.

51. “Randomization” is a statistical
procedure wherein patients are
allocated randomly to either the
intervention group or the control
group. The purpose of randomization is
to ensure that the patients in the two
groups are similar and hence
comparable.

52. FIELD TRIALS

53. Field trials, in contrast to clinical trials,
involve people who are healthy.
Data collection takes place “in the field,”
usually among people in the general
population

55. COMMUNITY TRIALS

56. Treatment groups are communities,
rather than individuals.
This is particularly appropriate for
diseases that are influenced by social
conditions, and for which prevention
efforts target group behavior.

57. ERRORS
IN
EPIDEMIOLOGICAL STUDIES

58. RANDOM ERROR
SYSTEMATIC ERROR

59. RANDOM ERROR
• When a value of the sample
measurement diverges-due to chance
alone-from that of the true population
value.
• Random error is “random”; therefore
cannot be predicted.

60. • THREE major sources of random error
– Individual biological variation
– Sampling error
• Increase the size of the sample
– Measurement error
• Stringent protocols
• Systematic quality control measures

61. SYSTEMATIC ERROR
• Also called “BIAS”
• Systematic deviation of results or
inferences from truth.
• Bias is defined as ‘any systematic error in
the design, conduct or analysis of a study
that results in a mistaken estimate of an
exposures effect on the risk of disease’.

62. TWO major types of bias
SELECTION BIAS
INFORMATION BIAS

63. SELECTION BIAS
• A systematic difference between the
characteristics of the people selected for a
study and the characteristics of those who are
not.
• Examples
– Bias due to non-response
– Exclusion bias
– Berkson’s bias (Berksonian bias)

64. • Bias due to non-response
– Those who volunteer to take part in a study are
different from those who don’t
• Exclusion bias
– Different eligibility criteria for cases and controls
•Berkson’s bias or Berksonian bias

65. • Berkson’s bias (Berksonian bias)
–When both exposure and disease under
study affect selection. This occurs when the
combination of exposure and disease under
study increases the chance of admission to
hospital, leading to a higher exposure rate
among hospital cases as compared to
hospital controls. Thus it causes hospital
cases and controls in a case-control study to
be systematically different from one
another.

66. INFORMATION BIAS
• A flaw in measuring exposure or outcome
variables that results in different accuracy of
information between comparison groups.
• This usually arises when the way of obtaining
information about exposure or outcome is
inadequate and hence may lead to incorrect
information about exposure or outcome.

67. Examples of Information bias
• Misclassification bias
– Wrongly classify exposure or outcome
• Recall bias
– Differential recall about exposure among cases
and controls. Case are more likely to remember
exposure as compared to controls
• Reporting bias
– Cases may be reluctant to report exposure

68. • Surveillance bias
– If exposed group is monitored more closely
compared to the unexposed group
• Interviewer bias
– Knowledge about exposure status may consciously
or subconsciously influence the interviewers
measurements biased. Observer bias is a related
bias.
• Single-blinding
• Double-blinding
• Triple blinding

69. CONFOUNDING

70. • In a study of whether factor A is a cause of
disease B, we say that a third factor, factor X is
a confounder if the following are true:
– Factor X is a known risk factor for disease B
– Factor X is associated with factor A, but is
not a result of factor A

74. Approaches to handling confounding
• In designing and carrying out the study
– Matching
– Exclusion
• In the analysis of data
– Stratification
– Adjustment