Observational study

PRESENTED BY :- KINJAL S. GAMIT
DEPARTMENT OF PHARMACOLOGY
EN.NO :- 172280825005
M.PHARM
SEM -2
L.M.C.P.
OBSERVATIONAL STUDY

WHAT IS OBSERVATIONAL STUDY ?
 Observational studies fall under the category of analytic
study designs and are further sub-classified as :
• observational or
• experimental study designs (Figure)
 The goal of analytic studies is to identify and evaluate
causes or risk factors of diseases or health-related
events.
 The differentiating characteristic between observational and
experimental study designs is that in the latter, the presence
or absence of undergoing an intervention defines the
groups.2 172280825005 (M.PH SEM-2)

WHAT IS OBSERVATIONAL STUDY ?
 By contrast, in an observational study, the investigator does
not intervene and rather simply “observes” and assesses
the strength of the relationship between an exposure and
disease variable.
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Temporal Design of Observational Studies: Cross-sectional
studies are known as prevalence studies and do not have an
inherent temporal dimension. These studies evaluate subjects at
one point in time, the present time.
172280825005 (M.PH SEM-2)4

TYPES
1. Case-control study: study originally developed in
epidemiology, in which two existing groups differing in
outcome are identified and compared on the basis of
some supposed causal attribute.
2. Cross-sectional study: involves data collection from a
population, or a representative subset, at one specific
point in time.
3. Cohort study or Panel study: a particular form of
longitudinal study where a group of patients is closely
monitored over a span of time.
4. Longitudinal study: co-relational research study that
involves repeated observations of the same variables
over long periods of time.
5. Ecological study: an observational study in which at
least one variable is measured at the group level.5 172280825005 (M.PH SEM-2)

INTRODUCTION
 A case-control study is a type of observational
study in which two existing groups differing in
outcome are identified and compared on the basis of
some supposed causal attribute.
 Case-control studies are often used to identify factors
that may contribute to a medical condition by comparing
subjects who have that condition/disease (the "cases")
with patients who do not have the condition/disease but
are otherwise similar (the "controls").
 They require fewer resources but provide less evidence
for causal inference than a randomized controlled trial.
 We only get odds ratio from a case control study which is
an inferior measure of strength of association as
compared to relative risk.
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INTRODUCTION
 In medical research and social science, a cross-sectional
study (also known as a cross-sectional
analysis, transverse study, prevalence study) is a type
of observational study that analyzes data from a
population, or a representative subset, at a specific point
in time—that is, cross-sectional data.
 A cohort study is a particular form of longitudinal
study (panel study) that sample a cohort (a group of
people who share a defining characteristic, typically who
experienced a common event in a selected period, such as
birth or graduation), performing a cross-section at intervals
through time.
 A cohort study is a panel study, but a panel study is not
always a cohort study as individuals in a panel study do not
always share a common characteristic.
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WHAT IS COHORT STUDY ?
 Cohort studies are important in research design.
 The term “cohort” is derived from the Latin word “Cohors”
– “a group of soldiers.”
 It is a type of non-experimental or observational study
design.
 The term “cohort” refers to a group of people who
have been included in a study by an event that is
based on the definition decided by the researcher.
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DESIGN OF COHORT STUDY
 In a cohort study, the participants do not have the
outcome of interest to begin with.
 They are selected based on the exposure status of the
individual. Thus, some of the participants may have the
exposure and others do not have the exposure at the time of
initiation of the study.
 They are then followed over time to evaluate for the
occurrence of the outcome of interest.
 As seen in Figure, at baseline, some of the study participants
have exposure (defined as exposed) and others do not have
the exposure (defined as unexposed).
 Over the period of follow-up, some of the exposed individuals
will develop the outcome and some unexposed individuals will
develop the outcome of interest.
 We will compare the outcomes in these two groups.
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EXAMPLES OF COHORT STUDIES
1. Framingham cohort study
(https://www.framinghamheartstudy.org/index.php)
 This cohort study was initiated in 1948 in Framingham.
Framingham, at the time of initiation of the cohort, was an
industrial town 21 miles west of Boston with a population of
28,000.
 This Framingham Heart Study recruited 5209 men and
women (30–62-year-old) in the study to assess the factors
associated with cardiovascular disease (CVD). The
researchers also recruited second generation participants
(children of original participants) in 1971 and the third general
participants in 2002. This has been one of the landmark
cohort studies and has contributed immensely to our
knowledge of some of the important risk factors for CVD. The
investigators have published 3064 publications using the
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2. Swiss HIV cohort study (http://www.shcs.ch/)
 This cohort study was initiated in 1988. It was a longitudinal
study of HIV-infected individuals to conduct research on HIV
pathogenesis, treatment, immunology, and co-infections.
 They also work on the social aspects of the disease and
management of HIV-infected pregnant women. The study
started with a recruitment of individuals ≥16 years.
 The cohort was gradually expanded to include the Swiss
Mother and Child HIV Cohort Study.
 The cohort has provided useful information on various
aspects of HIV and published 542 manuscripts on these
aspects.
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3. The Danish cohort study of psoriasis and
depression (Jensen, 2015)
 This is another large cohort study that evaluated the
association between psoriasis and onset of depression.
 The participants in the cohort were enrolled from national
registries in Denmark. None of the included participants had
psoriasis or depression at baseline.
 The outcome of interest was the initiation of antidepressants
or hospitalization for depression.
 The authors compared the incidence rates of hospitalization
for depression in psoriasis and reference population. The
psoriasis group was further classified as mild and moderate
psoriasis.
 The authors found that psoriasis was an independent risk
factor for new-onset depression in young people.
 However, in the elderly, it was mediated through comorbid
conditions.13 172280825005 (M.PH SEM-2)

TYPES OF COHORT STUDIES
Cohort studies can be grouped in several ways:
1. Prospective: none of the subjects have the disease (or
other outcome) being measured when the study
commences; data analysis happens after a period of time
has elapsed.
2. Retrospective (Historical): the researcher looks at
historical data for a group. Some of the people in this group
have developed the disease, and some have not. This can
result in finding out who has the disease and when they
developed it.
3. Case-control nested within a cohort: a smaller
group is chosen from within the cohort for a deeper look.
These investigations may include genotyping, collecting
tissue samples or other factors.
4. Case-cohort: similar to case-control nested within a
cohort. The difference is that in a case-cohort study,
participants are evaluated for outcome risk factors at any14 172280825005 (M.PH SEM-2)

WHAT IS PROSPECTIVE COHORT
STUDY ?
 A prospective cohort study takes a group of similar people (a
cohort) and studies them over time. At the time the baseline
data is collected, none of the people in the study have the
condition of interest.
 This is in contrast to a retrospective cohort study, which takes
a group of people who already have the condition and then
attempts to piece together the reasons why.
 The now famous Framingham Heart Study is one example
of a prospective cohort study; the researchers have, to
date, studied three generations of Framingham residents in
order to understand the causes of heart disease and stroke.
 Although none of the participants actually have the disease of
interest in a prospective cohort study, some of the cohort are
expected to develop the disease in the future.
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WHAT IS PROSPECTIVE COHORT
STUDY ?
For example,
 a cohort of thirty-year-old people in a certain town might be
studied to see who develops lung cancer. Half of the cohort
might be smokers and half may not. This enables
comparisons between the two groups.
 Once the prospective cohort study has been established,
researchers follow up with the participants and track their
progress.
 Follow ups can be:
In-person interviews. Lab tests.
Imaging tests. Phone interviews.
Physical exams. Internet
questionnaires.
Mail questionnaires.16 172280825005 (M.PH SEM-2)

ADVANTAGES AND DISADVANTAGES
Advantages
 One major advantage of a prospective cohort study is
that researchers don’t have to tackle with the ethical
issues surrounding randomized control trials (i.e.
who receives a placebo and who gets the actual
treatment).
 Incidence and prevalence of a disease can be easily
calculated.
 Multiple diseases and outcomes can be studied at the
same time.
Disadvantages
 Selection bias and confounding variables can be a
problem.
 Cohort studies can be expensive and time consuming.17 172280825005 (M.PH SEM-2)

WHAT IS RETROSPECTIVE COHORT
STUDY ?
 A retrospective cohort study (also known as a historic
study or longitudinal study) is a study where the
participants already have a known disease or outcome.
 The study looks back into the past to try to
determine why the participants have the disease or
outcome and when they may have been exposed.
 In a retrospective cohort study the researcher:
• Uses historical data to identify members of a population
who have been exposed (or not exposed) to a disease or
outcome.
• Assembles a group to be studied.
• Determines the current status of the disease or outcome
in the participants.18 172280825005 (M.PH SEM-2)

WHAT IS RETROSPECTIVE COHORT
STUDY ?
For example,
 One of the first recognized retrospective cohort studies
was Lane-Claypon’s 1926 study of breast cancer risk
factors, titled “A Further Report on Cancer of the Breast,
With Special Reference to Its Associated Antecedent
Conditions.”
 The study of 500 hospitalized patients and 500 controls
led to the identification of most of the risk factors for
breast cancer that we know today.
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Prospective vs. Retrospective cohort
study
 In a retrospective cohort study, the group of interest already
has the disease/outcome.
 In a prospective cohort study, the group does not have the
disease/outcome, although some participants usually
have high risk factors.
 Retrospective example:
• a group of 100 people with AIDS might be asked about their
lifestyle choices and medical history in order to study the
origins of the disease.
• A Second group of 100 people without AIDS are also studied
and the two groups are compared.
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Prospective vs. Retrospective cohort
study
 Prospective example:
• a group of 100 people with high risk factors for AIDS are
followed for 20 years to see if they develop the disease.
• A control group of 100 people who have low risk factors are
also followed for comparison.
 A retrospective cohort study can be combined with a
prospective cohort study: the researcher takes
the retrospective study groups, and then follows the cohort in
the future.
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WHAT IS THE COHORT EFFECT?
 A cohort effect is the influence of a group’s life
experience on the outcome of an experiment.
• It’s the effect of being born at the same time (i.e. GenXer
vs. Baby Boomer), or in the same region (i.e. born in
New Orleans vs. Seattle) or some other factor that
makes the group unique.
• Cohorts in schools are usually defined by age group,
while cohorts in organizations are defined by their date of
entry into the job.
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WHAT IS THE COHORT EFFECT?
172280825005 (M.PH SEM-2)23
 Children who grew up in New Orleans during Hurricane
Katrina would have vastly different experiences than a
cohort born at the same time in Seattle.

EXAMPLE OF COHORT EFFECT
 Lets say you were conducting cross sectional research (a
method that compares different age groups at the same point
in time) to find out how basic mathematics ability improves
with age.
• You give the same basic math standardized test to groups of
students who are 7-years-old, 14-years-old, and 21-years-old.
• You get the following mean results:
• 7-years-old: 24% correct
 You might conclude that every 7 years that pass makes a
difference of 24% in scores.
• However, what you haven’t accounted for is the cohort effect.
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EXAMPLE OF COHORT EFFECT
• The students differ not only in age, but they belong to different
cohorts (in this case, groups of people born around the same
time), some of which may have grown up when basic
mathematics was strongly emphasized in schools.
• If the 21-year-old cohort in the above study experienced
strong emphasis on basic math, it’s a possibility that they
could have achieved 72% when they were 14-years old or
even 7-years-old.
 The problems associated with the cohort effect can be
lessened by testing the same cohort over a period of time, a
method called longitudinal research.
 In the above example, you would test a group of 7-year-olds,
then test the same group every 7 years.
 A disadvantage to longitudinal research is that it’s costly,
and dropout rates can affect the results.
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OUTCOMES IN A COHORT STUDY
 A cohort study may have different types of outcomes.
 Some of the outcomes may occur only once.
 In the above mentioned retrospective study, if we assess
the mortality in these individuals, then the outcome will
occur only once.
 Other outcomes in the cohort study may be measured
more than once.
 For instance, if we assess CD4 counts in the same
retrospective study, then the values of CD4 counts may
change at every visit.
 Thus, the outcome will be measured at every visit.
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STRENGTHS OF A COHORT STUDY
 Temporality: Since at the time of entry into the cohort study,
the individuals do not have outcome, the temporality between
exposure and outcome is well defined.
 A cohort study helps us to study multiple outcomes in the
same exposure.
• For example, if we follow patients of hypercholesterolemia,
we can study the incidence of melasma or psoriasis in them.
Thus, there is one exposure (hypercholesterolemia) and
multiple outcomes (melasma and psoriasis).
• However, we have to ensure that none of the individuals have
any of the outcomes at the baseline.
 If the exposure is rare, then a cohort design is an efficient
method to study the relation between exposure and
outcomes.
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 It is generally said that a cohort design may not be efficient for
rare outcomes (a case-control design is preferred).
 However, if the rare outcome is common in some exposures,
then it may be useful to follow a cohort design.
• For example, melanoma is not a common condition in India.
Hence, if we follow individuals to study the incidence of
melanoma, then it may not be efficient.
• However, if we know that, theoretically, a particular chemical
may be associated with melanoma, then we should follow a
cohort of individuals exposed to this chemical (in occupational
settings or otherwise) and study the incidence of melanoma in
this group
 In a prospective cohort study, the exposure variable, other
variables, and outcomes may be measured more
accurately.
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• This is important to maintain uniformity in the measurement of
exposures and outcomes.
• This is also useful for exposures that may require subjective
assessment or recall by the patient.
• For example, dietary history, smoking history, or alcoholic
history, etc.
• This may help in reducing the bias in measurement of
exposure
 A retrospective cohort study can be completed fast and is
relatively inexpensive compared with a prospective cohort
study.
• However, it also has other strengths of the prospective cohort
study.
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LIMITATIONS OF A COHORT STUDY
 One major limitation of a prospective cohort design is
that is time consuming and costly.
• For example, if we have to study the incidence of
cardiovascular patients in patients of psoriasis, we may
have to follow them up for many years before the
outcome occurs
 In a retrospective cohort study, the exposure and the
outcome variables are collected before the study has
been initiated.
• Thus, the measurements may not be very accurate or
according to our requirements.
• In addition, the some of the exposures may have been
assessed differently for various members of the cohort
 As discussed earlier, cohort studies may not be very
efficient for rare outcomes except in some conditions.
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WHAT IS NESTED CASE-CONTROL
STUDY ?
 This is a specific type of study design nested within a cohort
study.
 In this, the investigator will match the controls to the cases
within a specific cohort.
 The exposure of interest will be assessed in these selected
cases and controls.
 For example, our hypothesis is that there is a biological
marker that in present/elevated (to begin with) in individuals
who develop cardiovascular events in psoriatic patients. It is
expensive to assess this marker in all patients. Thus, we
select all those who develop the outcomes (cases) in our
cohort and a sample of individuals who do not develop the
outcomes (controls). An important aspect, however, is that we
should have stored the biological material that we have
collected at baseline, and the biological marker should be
assessed in this sample. This procedure maintains the
temporal strength of the cohort study.
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ANALYSIS OF COHORT STUDIES
 Cohort studies will help us to estimate the cumulative
incidence and incidence rate.
Cumulative incidence
Example
 We follow 10,000 psoriatic patients for 10 years. Of these, 50
have a cardiovascular event.
 Thus, the cumulative incidence will be 50/10,000 or 0.005.
This measure is a proportion. Thus, the cumulative incidence
will be 0.5% or 5/1000.
Incidence rate
Example
 We follow-up 10,000 psoriatic patients for 10 years. Of these,
50 have a cardiovascular event.
33 172280825005 (M.PH SEM-2)

ANALYSIS OF COHORT STUDIES
How do we calculate the incidence rate?
 Let us assume that all the cardiovascular events occurred at
the end of the 2nd year. Our outcome of interest was the first
cardiovascular event. Thus, at the end of the 2ndyear, 50
individuals have the outcome.
 The total time contributed by these 50 individuals is 50 × 2
years = 100 person years (PY) - (A).
 The total time contributed by the rest of the cohort is (10,000
− 50) × 10 = 99,500 PY - (B).
 Thus, the total person time is A + B = 99,600.
 The incidence rate is 50/99,600 or 0.000502. As it is obvious
from the term, this measure is a rate (compared with
cumulative incidence which was a proportion). Thus, the
incidence rate of first cardiovascular event in psoriatic
patients is 0.502/1000 PY or 5.02/10,000 PY.
34 172280825005 (M.PH SEM-2)

WHAT IS CROSS-SECTIONAL STUDIES
?
 Cross-sectional study design is a type of observational
study design.
 The investigator measures the outcome and the
exposure(s) in the population, and may study their
association.
DESIGN OF CROSS-SECTIONAL STUDY
 In a cross-sectional study, the investigator measures the
outcome and the exposures in the study participants at the
same time.
 Unlike in case–control studies (participants selected based on
the outcome status) or cohort studies (participants selected
based on the exposure status), the participants in a cross-
sectional study are just selected based on the inclusion and
exclusion criteria set for the study.35 172280825005 (M.PH SEM-2)

DESIGN OF CROSS-SECTIONAL
STUDY
 After the entry into the study, the participants are measured
for outcome and exposure at the same time [Figure ].
 The investigator can study the association between these
variables. It is also possible that the investigator will recruit
the study participants and examine the outcomes in this
population. The investigator may also estimate the prevalence
of the outcome in those surveyed.
36 172280825005 (M.PH SEM-2)

EXAMPLES OF CROSS-SECTIONAL
STUDIES
1.Antibiotic resistance in Propionibacterium acnes
strains (Sardana et al., 2016)
 A study by Sardana et al. evaluated the antibiotic
resistance in isolates of Propionibacterium acnes in a
tertiary care hospital in India.
• They recruited 80 patients of acne vulgaris, collected
specimen for isolation from open or closed comedones.
• These specimens were then cultured, the growth identified,
and antibiotic susceptibility and resistance were assessed.
 They isolated P. acnes 52% of the cases. In these isolates,
resistance for erythromycin, clindamycin, and azithromycin
was observed in 98%, 90%, and 100% of the isolates,
respectively.
• However, sensitivity for tetracycline, doxycycline, minocycline,
and levofloxacin was observed in 69%, 56%, 98%, and 90%
of the isolates, respectively.
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EXAMPLES OF CROSS-SECTIONAL
STUDIES
2.HIV and male sex workers (Shinde et al., 2009)
 The authors presented a cross-sectional analysis to assess
the prevalence of HIV and risk behaviors in male sex
workers. They also evaluated the association between HIV
and sociodemographic factors.
 The data were collected by interviewer-administered
questionnaires (for sociodemographic and behavior data),
clinical evaluation for sexually transmitted infections (STIs),
and serological evaluation for STIs (including HIV).
 The authors reported that the prevalence of HIV in male sex
workers was 33%.
• They also found that male-to-female transgendered people
were significantly more likely to be HIV-infected compared
with males (odds ratio [OR]: 3.5, 95% confidence intervals:
1.0, 11.7).
 Similarly, they also found that HIV prevalence was higher
among those in whom sex work was the main occupation
compared with those in whom sex work was not the main
occupation (40% vs. 7%, P = 0.02).
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Measurements In A Cross-sectional
Study
Cross-sectional study designs may be used for population-
based surveys
Example:
 The prevalence of vitiligo in a village. So design a population-
based survey to assess the prevalence of this condition. Go
to all the houses that were supposed to be included in the
study and examine the population. The total sample surveyed
is 5686. Of these, found that 98 individuals have vitiligo.
 Thus, the prevalence of vitiligo in this community is:
Prevalence = 98/5686 or 17.23/1000 population
Cross-sectional studies may also be used for estimating the
prevalence in clinic-based studies.
Example:
 Research question – What is the prevalence of HIV in39 172280825005 (M.PH SEM-2)

Study
 Evaluate 300 patients with an STI clinic and record this
history, clinical examination, and test them for HIV antibodies
(using ELISA) during their first visit to the clinic.
 Find that 60 of these individuals are HIV infected. Thus, they
have detected a prevalence of 20% HIV infection among STI
patients. This type of study will be classified as a cross-
sectional study.
Cross-sectional studies may also be used to calculate the ORs
Example :
 if we wish to understand the association between gender and
HIV status, we will able to create a 2 × 2 table for the above-
mentioned cross-sectional study. Of the 300 individuals
evaluated, we have recruited 200 male and 100 female
participants. Of the 60 HIV-infected individuals, 50 are males
and 10 are females.
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Study
 The 2 × 2 table will be as follows:
 The OR is AD/BC or 50*90/10*150.
 Thus, the OR is 3.0.
 The interpretation of this OR is that males had a higher odds
of being HIV infected compared with females.
 Since the OR is >1, the outcome is more likely in those
exposed (males) compared with those who are not exposed
(females).
 However, will require confidence intervals to comment on
further interpretation of the OR.
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STRENGTHS OF A CROSS-SECTIONAL
STUDY
 Be conducted relatively faster and are inexpensive –
particularly when compared with cohort studies
(prospective)
 These are conducted either before planning a cohort
study or a baseline in a cohort study.
 Give us information about the prevalence of outcomes or
exposures; this information will be useful for designing
the cohort study
 May be useful for public health planning, monitoring,
and evaluation.
 For example,
• sometimes the National AIDS Programme conducted
cross-sectional sentinel surveys among high-risk groups42 172280825005 (M.PH SEM-2)

LIMITATIONS OF A CROSS-SECTIONAL
STUDY
 Since this is a 1-time measurement of exposure and outcome,
it is difficult to derive causal relationships from cross-
sectional analysis
 These studies are also prone to certain biases.
Example:
• To study the relation between diet and exercise and being
overweight/obese. Conduct a cross-sectional study and
recruit 250 individuals.
• We assess their dietary habits, exercise habits, and body
mass index at one point of time in a cross-sectional survey.
However, individuals who are overweight/obese have started
to exercise more or altered their feeding habits (eat more
salads). Hence, in a cross-sectional survey, we may find that
overweight/obese individuals are also more likely to eat
salads and exercise more.
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LIMITATIONS OF A CROSS-SECTIONAL
STUDY
 Thus, we have to be careful about interpreting the
associations and direction of associations from a cross-
sectional survey
 The prevalence of an outcome depends on the incidence of
the disease as well as the length of survival following the
outcome.
 For example,
• even if the incidence of HIV (number of new cases) goes
down in one particular community, the prevalence (total
number of cases – old as well as new) may increase. This
may be due to cumulative HIV positive cases over a period.
• Thus, just performing cross-sectional surveys may not be
sufficient to understand disease trends in this situation.
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WHAT IS CASE-CONTROL STUDY ?
 Case-Control study design is a type of observational study
design.
 In an observational study, the investigator does not alter the
exposure status.
 The investigator measures the exposure and outcome in
study participants, and studies their association.
DESIGN OF CASE-CONTROL STUDY
 In a case-control study, participants are selected for the study
based on their outcome status.
 Thus, some participants have the outcome of interest
(referred to as cases), whereas others do not have the
outcome of interest (referred to as controls).
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DESIGN OF CASE-CONTROL STUDY
 The investigator then assesses the exposure in both these
groups.
 Thus, by design, in a case-control study the outcome has to
occur in some of the participants that have been included in
the study.
 As seen in Figure, at the time of entry into the study (sampling
of participants), some of the study participants have the
outcome (cases) and others do not have the outcome
(controls).
 During the study procedures, will examine the exposure of
interest in cases as well as controls.
 And then study the association between the exposure and
outcome in these study participants.
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EXAMPLES OF CASE-CONTROL
STUDIES
1.Smoking and lung cancer study
 In their landmark study, Doll and Hill (1950) evaluated the
association between smoking and lung cancer.
 They included 709 patients of lung carcinoma (defined as
cases). They also included 709 controls from general medical
and surgical patients. The selected controls were similar to
the cases with respect to age and sex. Thus, they included
649 males and 60 females in cases as well as controls.
 They found that only 0.3% of males were non-smokers
among cases.
 However, the proportion of non-smokers among controls was
4.2%; the different was statistically significant (P =
0.00000064).
 Similarly they found that about 31.7% of the female were non-
smokers in cases compared with 53.3% in controls; this
48 172280825005 (M.PH SEM-2)

STUDIES
2.Melanoma and tanning (Lazovic et al., 2010)
 The authors conducted a case-control study to study the
association between melanoma and tanning.
 The 1167 cases - individuals with invasive cutaneous
melanoma – were selected from Minnesota Cancer
Surveillance System.
 The 1101 controls were selected randomly from Minnesota
State Driver's License list; they were matched for age (+/- 5
years) and sex.
 The data were collected by self administered questionnaires
and telephone interviews.
 The investigators assessed the use of tanning devices (using
photographs), number of years, and frequency of use of these
devices.49 172280825005 (M.PH SEM-2)

STUDIES
 They also collected information on other variables (such as
sun exposure; presence of freckles and moles; and colour of
skin, hair, among other exposures.
 They found that melanoma was higher in individuals who
used UVB enhances and primarily UVA-emitting devices.
 The risk of melanoma also increased with increase in
years of use, hours of use, and sessions.
50 172280825005 (M.PH SEM-2)

STUDIES
3.Risk factors for erysipelas (Pitché et al, 2015)
 Pitché et al (2015) conducted a case-control study to assess
the factors associated with leg erysipelas in sub-Saharan
Africa.
 This was a multi-centre study; the cases and controls were
recruited from eight countries in sub-Saharan Africa.
 They recruited cases of acute leg cellulitis in these eight
countries.
 They recruited two controls for each case; these were
matched for age (+/- 5 years) and sex. Thus, the final study
has 364 cases and 728 controls.
 They found that leg erysipelas was associated with
obesity, lympoedema, neglected traumatic wound, toe-
web intertrigo, and voluntary cosmetic depigmentation.51 172280825005 (M.PH SEM-2)

TYPES OF CONTROLS
 We can select controls from a variety of groups.
 Some of them are: General population; relatives or friends; or
hospital patients.
Hospital controls
 An important source of controls is patients attending the
hospital for diseases other than the outcome of interest.
 These controls are easy to recruit and are more likely to have
similar quality of medical records.
Relative and friend controls
 Relative controls are relatively easy to recruit.
 They can be particularly useful when we are interested in
trying to ensure that some of the measurable and non-
measurable confounders are relatively equally distributed in
cases and controls (such as home environment, socio-
economic status, or genetic factors).
52 172280825005 (M.PH SEM-2)

TYPES OF CONTROLS
Population controls
 These controls can be easily conducted the list of all
individuals is available.
 For example, list from state identity cards, voter's
registration list, etc., In the Tanning and melanoma study,
the researchers used population controls. They were
identified from Minnesota state driver's list.
53 172280825005 (M.PH SEM-2)

STRENGTHS OF A CASE-CONTROL
STUDY
 Case-Control studies can usually be conducted relatively
faster and are inexpensive – particularly when compared
with cohort studies (prospective)
 It is useful to study rare outcomes and outcomes with long
latent periods.
Example:
 If we wish to study the factors associated with melanoma
in India, it will be useful to conduct a case-control study.
 We will recruit cases of melanoma as cases in one study site
or multiple study sites.
 If we were to conduct a cohort study for this research
question, we may to have follow individuals (with the
exposure under study) for many years before the occurrence
of the outcome54 172280825005 (M.PH SEM-2)

STRENGTHS OF A CASE-CONTROL
STUDY
 It is also useful to study multiple exposures in the same
outcome.
• For example, in the metabolic syndrome and psoriasis study,
we can study other factors such as Vitamin D levels or
genetic markers
 Case-control studies are useful to study the association of
risk factors and outcomes in outbreak investigations.
• For instance, Freeman and colleagues (2015) in a study
published in 2015 conducted a case-control study to
evaluate the role of proton pump inhibitors in an outbreak
of non-typhoidal salmonellosis.
55 172280825005 (M.PH SEM-2)

LIMITATIONS OF A CASE-CONTROL
STUDY
 The design, in general, is not useful to study rare
exposures. It may be prudent to conduct a cohort study for
rare exposures.
 We are not able to estimate the incidence or prevalence in a
case-control study.
 The design is not useful to study multiple outcomes.
 Since the cases are selected based on the outcome, we can
only study the association between exposures and that
particular outcome.
 Sometimes the temporality of the exposure and outcome may
not be clearly established in case-control studies.
 The case-control studies are also prone to certain biases.
 If the cases and controls are not selected similarly from the
study base, then it will lead to selection bias.56 172280825005 (M.PH SEM-2)

ANALYSIS OF CASE-CONTROL STUDY
 Odds Ratio: We are able to calculate the odds ratios (OR)
from a case-control study.
 We are not able to measure incidence data in case-control
study, an odds ratio is a reasonable measure of the relative
risk (under some assumptions).
 The OR in the above study is 3.5. Since the OR is greater
than 1, the outcome is more likely in those exposed (those
who are diagnosed with metabolic syndrome) compared with
those who are not exposed (those who do are not diagnosed
with metabolic syndrome).
58 172280825005 (M.PH SEM-2)

REFERENCES
1. http://www.statisticshowto.com/cohort-study/
2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763690
/
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60 172280825005 (M.PH SEM-2)

Observational study

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