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Transcript of Epidemiology
EPIDEMIOLOGY
www.drjayeshpatidar.blogspot.com
www.drjayeshpatidar.blogspot.in
• Epidemiology, "the study of what is upon
the people", is derived from the Greek
terms epi = upon, among; demos =
people, district; logos = study, word,
discourse; suggesting that it applies only
to human populations. But
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History
• The Greek physician Hippocrates is sometimes said to be the uncle of epidemiology. He is the first person known to have examined the relationships between the occurrence of disease and environmental influences. He coined the terms endemic (for diseases usually found in some places but not in others) and epidemic (for disease that are seen at some times but not others
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• One of the earliest theories on the origin of disease was that it was primarily the fault of human luxury. This was expressed by philosophers such as Plato and Rousseau,and social critics like Jonathan Swift.
• In the medieval Islamic world, physicians discovered the contagious nature of infectious disease. In particular, the Persian physician Avicenna, considered a "father of modern medicine," in The Canon of Medicine (1020s), discovered the contagious nature of tuberculosis and sexually transmitted disease, and the distribution of disease through water and soil. Avicenna stated that bodily secretion is contaminated by foul foreign earthly bodies before being infected.He introduced the method of quarantine as a means of limiting the spread of contagious disease. He also used the method of risk factor analysis, and proposed the idea of a syndrome in the diagnosis of specific diseases.
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• John Graunt, a professional haberdasher and
serious amateur scientist, published Natural and
Political Observations ... upon the Bills of
Mortality in 1662. In it, he used analysis of the
mortality rolls in London before the Great Plague
to present one of the first life tables and report
time trends for many diseases, new and old. He
provided statistical evidence for many theories
on disease, and also refuted many widespread
ideas on them.
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• Dr. John Snow is famous for his investigations into the causes of the 19th Century Cholera epidemics. He began with noticing the significantly higher death rates in two areas supplied by Southwark Company. His identification of the Broad Street pump as the cause of the Soho epidemic is considered the classic example of epidemiology. He used chlorine in an attempt to clean the water and had the handle removed, thus ending the outbreak. (It has been questioned as to whether the epidemic was already in decline when Snow took action.) This has been perceived as a major event in the history of public health and can be regarded as the founding event of the science of epidemiology.
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Original map by Dr. John Snow showing the clusters of cholera
cases in the London epidemic of 1854www.drjayeshpatidar.blogspot.in
When the Black Death (bubonic
plague) reached Al Andalus in the
14th century, Ibn Khatima
hypothesized that infectious
diseases are caused by small
"minute bodies" which enter the human body and cause disease.
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• Another 14th century Andalusian-Arabian physician, Ibn
al-Khatib (1313–1374), wrote a treatise called On the
Plague, in which he stated how infectious disease can
be transmitted through bodily contact and "through
garments, vessels and earrings.
• In the middle of the 16th century, a famous Italian doctor
from Verona named Girolamo Fracastoro was the first to
propose a theory that these very small, unseeable,
particles that cause disease were alive. They were
considered to be able to spread by air, multiply by
themselves and to be destroyable by fire.
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• In this way he refuted Galen's theory of miasms(poison gas in sick people).
• In 1543 he wrote a book De contagione et contagiosis morbis, in which he was the first to promote personal and environmental hygiene to prevent disease.
• The development of a sufficiently powerful microscope by Anton van Leeuwenhoek in 1675 provided visual evidence of living particles consistent with a germ theory of disease.
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• In the study of communicable and non-communicable diseases, the work of epidemiologists ranges from outbreakinvestigation to study design, data collection and analysis including the development of statistical models to test hypotheses and the documentation of results for submission to peer-reviewed journals. Epidemiologists rely on a number of other scientific disciplines, such as biology (to better understand disease processes), Geographic Information Science (to store data and map disease patterns) and social science disciplines (to better understand proximate and distal risk factors).
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• Other pioneers include Danish physician P. A. Schleisner, who in 1849 related his work on the prevention of the epidemic of tetanus neonatorum on the Vestmanna Islands in Iceland
• Another important pioneer was Hungarian physician Ignaz Semmelweis, who in 1847 brought down infant mortality at a Vienna hospital by instituting a disinfection procedure. His findings were published in 1850, but his work was ill received by his colleagues, who discontinued the procedure. Disinfection did not become widely practiced until British surgeon Joseph Lister'discovered' antiseptics in 1865 in light of the work of Louis Pasteur.
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• In the early 20th century, mathematical methods
were introduced into epidemiology by Ronald
Ross, Anderson Gray McKendrick and others.
• Another breakthrough was the 1954 publication
of the results of a British Doctors Study, led by
Richard Doll and Austin Bradford Hill, which lent
very strong statistical support to the suspicion
that tobacco smoking was linked to lung cancer.
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• Although epidemiology is sometimes viewed as a collection of statistical tools used to elucidate the associations of exposures to health outcomes, a deeper understanding of this science is that of discovering causal relationships.
• It is nearly impossible to say with perfect accuracy how even the most simple physical systems behave beyond the immediate future, much less the complex field of epidemiology, which draws on biology, sociology, mathematics, statistics, anthropology, psychology, and policy; "Correlation does not imply causation" is a common theme for much of the epidemiological literature
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• For epidemiologists, the key is in the term
inference. Epidemiologists use gathered
data and a broad range of biomedical and
psychosocial theories in an iterative way to
generate or expand theory, to test
hypotheses, and to make educated,
informed assertions about which
relationships are causal, and about exactly
how they are causal
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• Epidemiologists Rothman and Greenland
emphasize that the "one cause - one
effect" understanding is a simplistic mis-
belief. Most outcomes, whether disease or
death, are caused by a chain or web
consisting of many component causes
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Epidemiology
is the study of factors affecting the
health and illness of populations,
and serves as the foundation and
logic of interventions made in the
interest of public health and
preventive medicine
• It is considered a cornerstone
methodology of public health research,
and is highly regarded in evidence-based
medicine for identifying risk factors for
disease and determining optimal treatment
approaches to clinical practice.
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• Epidemiological studies can only go to prove that an agent could have caused, but not that it did cause, an effect in any particular case:
• "Epidemiology is concerned with the incidenceof disease in populations and does not address the question of the cause of an individual’s disease. This question, sometimes referred to as specific causation, is beyond the domain of the science of epidemiology. Epidemiology has its limits at the point where an inference is made that the relationship between an agent and a disease is causal (general causation) and where the magnitude of excess risk attributed to the agent has been determined; that is, epidemiology addresses whether an agent can cause a disease, not whether an agent did cause a specific plaintiff’s disease."
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• As a public health discipline, epidemiologic
evidence is often used to advocate both
personal measures like diet change and
corporate measures like removal of junk
food advertising, with study findings
disseminated to the general public in order
to help people to make informed decisions
about their health
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• Epidemiological tools have proved effective in establishing major causes of diseases like cholera and lung cancer but have had problems with more subtle health issues, and several recent epidemiological results on medical treatments (for example, on the effects of hormone replacement therapy) have been refuted by later randomized controlled trials
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Population-based health
management
• Epidemiological practice and the results of
epidemiological analysis make a
significant contribution to emerging
population-based health management
frameworks
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• Population-based health management encompasses the ability to:
• Assess the health states and health needs of a target population;
• Implement and evaluate interventions that are designed to improve the health of that population; and
• Efficiently and effectively provide care for members of that population in a way that is consistent with the community’s cultural, policy and health resource values.
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• Modern population-based health
management is complex, requiring a
multiple set of skills (medical, political,
technological, mathematical etc.) of which
epidemiological practice and analysis is a
core component, that is unified with
management science to provide efficient
and effective health care and health
guidance to a population.
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• This task requires the forward looking ability of
modern risk management approaches that
transform health risk factors, incidence,
prevalence and mortality statistics (derived from
epidemiological analysis) into management
metrics that not only guide how a health system
responds to current population health issues, but
also how a health system can be managed to
better respond to future potential population
health issues.
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Legal interpretation
• Epidemiological studies can only go to prove that an agent could have caused, but not that it did cause, an effect in any particular case:
• "Epidemiology is concerned with the incidence of disease in populations and does not address the question of the cause of an individual’s disease. This question, sometimes referred to as specific causation, is beyond the domain of the science of epidemiology. Epidemiology has its limits at the point where an inference is made that the relationship between an agent and a disease is causal (general causation) and where the magnitude of excess risk attributed to the agent has been determined; that is, epidemiology addresses whether an agent can cause a disease, not whether an agent did cause a specific plaintiff’s disease."[13]
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• In United States law, epidemiology alone
cannot prove that a causal association
does not exist in general. Conversely, it
can be (and is in some circumstances)
taken by US courts, in an individual case,
to justify an inference that a causal
association does exist, based upon a
balance of probability.
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Population-based health
management
• Epidemiological practice and the results of epidemiological analysis make a significant contribution to emerging population-based health management frameworks.
• Population-based health management encompasses the ability to:
• Assess the health states and health needs of a target population;
• Implement and evaluate interventions that are designed to improve the health of that population; and
• Efficiently and effectively provide care for members of that population in a way that is consistent with the community’s cultural, policy and health resource values.
www.drjayeshpatidar.blogspot.in
Modern population-based health management is complex,
requiring a multipleset of skills (medical, political, technological,
mathematical etc.) of which epidemiological practice and
analysis is a corecomponent, that is unified with management
science to provide efficient and effective health care and health
guidance to a population.
This task requires the forward looking ability of modern risk
management approaches that transform health risk factors,
incidence, prevalence and mortality statistics
(derived from epidemiological analysis) into management
metrics that not only guide how
a health system responds to current population health issues,
but also how a healthsystem can be managed to better respond
to future potential population health issues.
www.drjayeshpatidar.blogspot.in
Advocacy
• As a public health discipline, epidemiologic evidence is often used to advocate both personal measures like diet change and corporate measures like removal of junk food advertising, with study findings disseminated to the general public in order to help people to make informed decisions about their health. Often the uncertainties about these findings are not communicated well; news articles often prominently report the latest result of one study with little mention of its limitations, caveats, or context. Epidemiological tools have proved effective in establishing major causes of diseases like cholera and lung cancer but have had problems with more subtle health issues, and several recent epidemiological results on medical treatments (for example, on the effects of hormone replacement therapy) have been refuted by later randomized controlled trials.
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Sources of data
• Routinely collected data
• Records from health sector
• original documents
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Descriptive epidemiologyMigrant studies
Person distribution
•Defining persons who develop the disease by
age,sex,occupation,marital status ,social class and other host
factors
•Don't necessarily represent etiological factors ,but they
contribute a good deal to our understanding of the natural
history of disease .
Age: strongly related to disease than any other single host
factor .
Certain diseases –more frequent in certain age groups than in
others –
eg.measles in childhood
cancer in middle age
atheroslerosisin old age
As age advances –many chronic progressive disorders increse
in prevalence.
Bimodality
Ther may be two separate peaks instead of one in the age
incidence curve of a disease .
eg leukemia,Hodgkin's disease.
gender
• Is a host characteristic which is often studied in relation to disease
• Indexes used-sex ratio,sex-specific morbidity&mortality rates
• Some diseases common in women:diabetes ,hyperthyroidism and obesity
Uncommon ’lung cancer,chd
1. Basic biological differences between the sexes including sex linked genetic
inheritance
2. Cultural and behavioral differences between the sexes (alcoholism,automobile use
etc.)due to different roles
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•ethnicity
Differences in disease occurrence observed between population
subgroupsof different racial and ethnic origin.
• MARITAL STAUS
Mortality rates were lower for males and females who are married.
•Occupation
•Social class
•Upperer class
•behavior
Cigarette smoking
alcoholism
Sedentary life style
•Stress
•Migrationwww.drjayeshpatidar.blogspot.in
Measurement of disease
Disease load –mortality,morbidity disability etc
Mortality –straight forward
Morbidity –2 aspects—incidence and prevalence
Measurement can be extended to health statesand
events.
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Comparing with known indices
comparison between different populations and subgroups of he same population
,it is possible to arrive at clues to disease etiology .
Formulation of a hypothesis
Relating to disease etiology
Should specify the following
1. The population
2. The specific cause being considered
3. The expected outcome
4. The dose response relationship
5. The time response relationship
Eg. The smoking of 30-40cigaretes per day causes lung cancer in 10% of smokers
after 20 years of exposure.
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Uses of descriptive epidemiology
1. Provide data regarding magnitude of the disease load and the type of
diseases problems in he community in terms of morbidity and mortality
rates and ratios
2. Provide clues to disease etiology and help in the formulation of an
etiological hypothesis
3. Provide back ground data for planning ,organising and evaluating
preventive and curative services.
4. they contribute to research by describing variations in disease occurrence
by time ,place and person.
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Analytical epidemiology
• The subject of interest is individual within
the population
• The object is to test hypothesis
• 2 distinct types of obsnl. Studies
1. Case control studies
2. Cohort studies
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• From each of these one can determine
• A. whether or not a statistical association
exists between a disease and a suspected
factor
• If one exists –the strength of association
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Analytical epidemiology (Schematic diagram)
Case control study indls with particular disease}cases
Factors indls without particular disease}controls
Present
Or
Absent
PROSPECTIVE(cohort study)
Indl. Exposed to particular factors.
Inld unexposed to particular factors
presence or absence of particular disease
Time
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Case control study
(retrospective study)
3 distinct features
• Both exposure and outcome have
occurred before the start of the study
• It uses a control/comparison group
• The study proceeds backwards from
effect to cause.
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• Involves 2 populations
• Cases controls
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basic steps
• Selection of cases and control
• Matching
• Measurement of exposure
• Analysis and interpretation
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Selection of cases and control
1. Selection of cases:
a. Definition of case-involves 2
specifications—
i. Diagnostic criteria: criteria of the disease
and stage of the disease if any
ii. Eligibility criteria :only newly diagnosed
cases within a specified period of time
are eligible
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b.Sources of cases
• Hospitals :from a single or network of hospitals admitted during a specified period of time.
• general population: all cases of study diseases occurring within a defined geographic area during a specified period of time are ascertained—often through a survey or ,a disease registry or hospital network.
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Selection of controls
• Controls must be free from the disease
under study.
• They must be similar to the cases as
possible ,except for the absence of the
disease under study
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Sources of controls
• Hospitals
• Relatives
• Neighbors
• general population
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Matching
• Comparability between cases and controls to be ensured this is done through -Matching
• 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. which are known to influence the outcome of the disease and which if not adequately matched for comparability ,could distort or confound the results.
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Matching
• A confounding factor is defined as the one
associated with both exposure and disease, and
is distributed unequally in the study and control
groups.
• Eg:Role of alcohol –esophageal cancer
Smoking is a compounding factor---it is associated
with the consumption of alcohol and it is an
independent risk factor for esophageal cancer.
in this case the effect of alcohol consumption
can be determined only if the influence of
smoking is neutralized by matching
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• Age could be compounding variable:
Relationship between Steroid contraceptive
and breast cancer
Matching protects against an un expected
strong association between the matching
factor and the disease .
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Kinds of matching
• Group
• Pairs
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Measurement of exposure
• Information about exposure should be
obtained in precisely the same manner
both for cases and controls
• May be 0btained by interviews
,questionnaires or by studying past
records of cases such as hospital records
or employment cards
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Analysis
To find out
• Exposure rates among cases and controls
to suspected factor
• ESTIMATION OF DISEASE RISK
ASSOCIATED WITH EXPOSURE (ODD
RATIO)
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Exposure rates(FREQUENCY OF
EXPOSURE)
• Direct estimation of the exposure rates to
suspected factor in disease and non
disease group.
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A case control study of smoking and lung CaCases(with lung Ca) Controls (without lung
Ca)
Smokers <5 cigars/day 33(a) 55(b)
Non smokers 2(c) 27(d)
total 35(a+c) 82(b+d)Table 1
Exposure rates
Cases=a/a=c=33/35=94.2%
Controls=b/b+d=55/82=67%,p<0.001
Frequency rate of Lung Ca is higher among smokers
than non smokers.
If p</=0.o5----statistically significantwww.drjayeshpatidar.blogspot.in
Estimation of risk
• Estimation of disease risk associated with
exposure—is obtained by an index known
as relative risk or risk ratio .
Relative risk = incidence among exposed
incidence among non exposed
=a/(a+b) + c/(c+d)
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Odds ratio(cross product ratio)(OR)
• Measure of the strength of the assocn. between risk factor and outcome
• Odds ratio is closely related to relative risk
• The derivation of odds ratio is based on 3asssumptions
1. The diseases being investigated must be relatively rare
2. The cases must be representative of those with the disease
3. Controls must be representative without disease
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Suspected or risk
factors
Case /disease present Control /disease
absent
present a b
Absent
Odds
ratio=ad/bc
c
a+c
d
b+d
Odds ratio=ad/bc=33x27/55x2=8.1(data from table1)
Smokers of less than 5 cigars/day showed a risk of having lung Ca 8.1times that
of nonsmokers. odd ratio is the key parameter in the analysis of case control
studies www.drjayeshpatidar.blogspot.in
Bias in case control studies
• Any systematic error in the determination of the
association between the exposure and disease
• Reflects non comparability
Bias—
confounding rectified by matching
memory or recall
selection—cases may not be representative in general
population
Berkesonian –different rates of admission to hospitals for
people with different diseases
Interviewer-double blinding is used to rectify
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Advantages &disadvantages
Advantages
• Easy to carry out
• Rapid and inexpensive
• Require few subjects
• Suitable to investigate rare diseases.
• No risk to subjects
• Study of different etiological factors
• Risk factors can be identified
• No attrition problems..
• ethical problems minimal
Disadvantage
•Bias-on memory or past
records, accuracy may be
uncertain
•Selection of appropriate
control group difficult
•Cannot measure
incidence ,can only
measure relative risk
•Don’t distinguish between
cause and associated
factors
•Concern of representative
ness of cases and controls
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Cohortstudies(Longitudinal,prospective,incidence,
forward- looking study)
• Usually undertaken to obtain additional evidence to
refute to or support of the existence of an association
between suspected causes and diseases
Features
1. Cohorts are identified prior to the appearance of the
disease under investigation
2. Study groups ,so defined ,are observed over a period
of time to determine the frequency of disease among
them
3. Study proceeds forward from cause to effect
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Concept • Cohort –a group of people who share a common
characteristic or experience within a defined time period
Indications for cohort study
• When there is a good evidence of an association
between exposure and disease ,as derived from clinical
observations and supported by descriptive and case
control studies
• When exposure is rare ,but the incidence of the disease
high among exposed.
• When attrition of study population can be minimized.
• Ample funds are available
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framework
• Cause to effect =exposure has occurred but not the disease
cohort Disease
Yes no
total
Exposed to
putative
etiologic factor
a b A+b(study
cohort)
not Exposed to
putative
etiologic factor
c d C+d(contr
ol cohort)
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General considerations in
assembling cohort
• Free from disease
• Both the groups equally susceptible
• Both the groups should be comparable
• Diagnostic eligibility criteria the disease must be defined before hand
A well designed cohort study is considered the most reliable means of showing an association between a suspected risk factor and subsequent disease .
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types
• Prospective—the out come has not yet
occurred at the time of inv. begin in the
present and continue in the future
• Retrospective. outcomes have
occuredbefore the inv.goes back in time
• A combination of both: cohort from past
recordsand assessed of dat efor outcome
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Elements
• Selection of study subjects
• Obtaining data on exposure
• Selection of comparison of groups
• Follow up
• analysis
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Selection of study subjects
• General population
• Special groups
These may be special groups or exposure groups that can readily be
studied
1.Select groups: Professional groups(eg.doctors,nurses,lawyersetc.)
,insured persons, obstetric population, college alumini,govt employees,
volunteers etc.
These groups are homogenous, advantages of accessibility and easy to
follow up for a protracted period.
2.Exposure groups: if the exposure is rare more economical procedure to
select a cohort of persons known to have experienced the
exposure.eg.workers in industries.
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Obtaining data on exposureInformation can be obtained from
1. Cohort members:interviews,mail questionnaires
2. Review of records: certain kind of information can be obtained from records.eg.dose of radiation, kinds of surgery,detailas of medication
3. Medical examination or special tests:
eg. BP,ECG.
4.Environmental surveys: obtaining information on exposure levels of the suspected factor in the environment where the cohort lived or worked.
Information to be collected in a manner that will allow classification of cohort
a. According to whether or not they have been exposed to the suspected factor or not.
b.According to the degree of exposure
In addition demographic variables also to be collected.
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Selection of comparison groups
1. Internal comparisons:
no outside comparison groups.
in built comparison groups.
ie.single cohort enters the study ,and its members may ,on
the basis of information obtained, be classified into
several comparison groups according to the level of
exposure to risk before the development of the disease
in question.eg.smoking ,blood pressure, serum
cholesterol
The groups so defined, are compared in terms of their
subsequent morbidity and mortality rates.
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Age standardized death rates /100000men per year by
amount of current smoking
Classification of
exposure (cigarettes)
No of deaths Death rate
½ pack 24 95.2
1/2pack-1 pack 84 107.8
1-2 pack 90 229.2
2packs+ 97 264.2
Mortality from lung Ca increases with increased no of cigarettes smoked –there
is valid association
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b.External comparisons
• External control Is used when information
on degree on exposure is not available –
evaluate the experience of the exposed
group.
Eg .smokers and non smokers ,a cohort of
radiologist with a cohort of
ophthalmologist.
study and control variables should be
similar in demographic and possibly
important variables
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c.Comparison group with general population values
• None available –mortality experience of the exposed group is compared with the mortality experience of the general population
• Eg. Comparison of frequency of lung ca.among uranium workers with lung ca.mortality with general population where the miners resided.
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d.Follow up
• Regular follow up is part of cohort studies.
Procedure to obtain data:
1. Periodic medical examination of each member of the cohort
2. Reviewing physician and hospital records
3. Routine surveillance of death records
4. Mailed questionnaire ,telephone call s,periodic
home visits-preferably all 3 on annual basis
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analysis
The data are analysed in terms of
1. Incidence rates of outcome among
exposed and non exposed
2. Estimation of risk
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Incidence rates• Can be calculated directly
Cigarette smoking Developed lung ca Did not develop
lung ca
total
yes 70(a) 6930(b) 7000(a+b)
no 3(c) 2997(d) 3000(c+d)
Incidence rates
a. among smokers =70/7000=10/1000
b. Among non smokers=3/3000=1/1000
p<0.001
Contingency table applied to hypothetical cigarette smoking and
lung cancer eg.
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Estimation of risks
Risk of outcome :
• relative risk
• attributable ratiorelative risk(RR)= incidence of disease /deathamong exposed
incidence disease/death among nonexposed
RR=10/1=10(data from table)
relative risk (RR) is a direct measure or (index) of the strength of the association
between the cause and effect
RR-1-indicates no association
>1suggests +association between exposure and the disease under study
2-indicates-incidence rate of disease is 2 times higher in ht exposed group as
compared to un exposed
Smokers are 10 times at greater risk of developing lung ca than non smokers
Larger RR---greater the strength of association
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attributable risk (AR)(risk difference)
• Difference in incidence rate of disease or death between an
exposed and non exposed group
• Expressed in %
• AR=
incidence of disease rate among exposed-incidence disease rate
among nonexposed
incidence of disease rate among exposed
AR=10-1/10x100=90%(table data)
Indicates to what extend the disease under study can be attributed to
the exposure.
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Population of attributable risk
• Incidence of the disease or death in the total population - Incidence of the disease or death among those who were not exposed to the suspected causal factor
Deaths per 100, 000-years
Heavy smokers 224 Exposed to suspected
factor(a)
Non smokers 10 Non exposed to
suspected factors(b)
Deaths in total
population
74(c)
Individual RR=a/b=224/10=22.4
Population AR=c-b/cx100=86%
Deaths per 100, 000-years
Heavy smokers 224 Exposed to suspected
factor(a)
Non smokers 10 Non exposed to
suspected factors(b)
Deaths in total
population
74(c)
Individual RR=a/b=224/10=22.4
Population AR=c-b/cx100=86%www.drjayeshpatidar.blogspot.in
• The concept of population attributable risk
is useful in that it provides an estimate of
the amount by which the disease could be
reduced in that population if the suspected
factor was eliminated or modified
• In the eg.--86%deaths could have been
avoided if the risk of cigarettes were
eliminated.
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Relative risk and attributable risk
• RR is imp. in etiological enquiries.
• its size is a better index for assessing the etiological role of a factor in disease.
• The larger the RR ,the stronger the assocn.between cause and effect.
• RR does not reflect the potential public health importance as does the attributable risk
• AR gives a better idea than does RR of the impact of successful preventive or public health programme might have in reducing the problem
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Cardiovascular risk
100,000patient yearsAges
30-39 40-44
RR 2.8 2.8
AR 3.5 20.0
The RR and AR of cardiovascular complications in women taking oral
contraceptives
RR independent of age
AR is .5times higher in the older age.
This epidemiological observation is the basis for not recommending
OCP to those aged 35yers and above
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Risk assessment smokers vs non smokers
Cause of
death
Death rate/1000
Smokers nonsmokers
RR AR
Lung Ca .90 0.7 12.86 92.2
CHD 4.87 4.22 1.15 13. 3
Smoking is attributable to 92%of Calung&13.3%of CHD .
In CHD,both RR and AR not very high –suggests not much of the
disease could be prevented as compared to lung ca
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Advantages &disadvantages
1. Incidence can be calculated
2. Several possible outcomes related to exposure can be studied simultaneously
3. Provide direct estimate of RR
4. Dose response ratio –can be calculated
5. Bias can be minimized-groups formed before disease develops
1. Long time
2. Large no of people
3. Administrative problems-loss of experienced staff ,loss of funding and extensive record keeping are in evitable
4. Original cohort may be lo
5. Selection of controls limiting factor
6. There may be change in diagnostic criteria
7. Expensive
8. May alter peoples behavior
9. Limited no of factors are concentrated
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Main difference between case control &cohort
1. Proceeds from effect to cause
2. Starts with disease
3. Tests whether the disease occurs more frequently in those with disease than among those without disease
4. First Approach to testing hypothesis
5. Involve fewer no of subjects
6. quick results
7. Suitable for the study of rare disease
8. Only estimate of RR
9. Cannot yield information about disease other than that selected for study
10. Relatively in expensive
1. cause to effect
2. People
3. Test in those exposed
4. Reserved for testing precisely formulated hypothesis
5. Larger no of subjects
6. Long follow up period
7. Inappropriate for rare disease
8. Yields incidence rate,RR&AR
9. Can yield information about more than one disease outcome
10. expensive
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Experimental epidemiology
• Equated with randomised controls
• It is similar to cohort study except The conditions under
which study is carried out is under the direct control of
the investigator
• Involve action, intervention or manipulation –deliberate
application or withdrawal of the suspected causes or
changing one variable in the causative chain in the
experimental group while making no change in the
control group.
• Observing and comparing the outcome of the experiment
in both ht egroups
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Aims1. To provide scientific proof of etiologic factor which may permit the
modification or control of those diseases
2. To provide a method of measuring the effectiveness and
efficiency of health services for he prevention ,control and
treatment of disease and improve the health of the community
They may be conducted in animals and human beings
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Animal studies-application
1. Experimental reproduction of human disease
in animals to confirm etiological hypotheses
and to study their pathogenetic phenomena or
mechanisms
2. Testing the efficacy-preventive and
therapeutic measures such as vaccines and
drugs
3. Completing a natural history of disease.
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Animal experiments
Advantages
• Can be bred in labs and
manipulated easily
• They multiply rapidly and
genetic studies can be
carried out
• Disadvantages
• Not all human diseases
can be reproduced in
animals
• conclusions may not be
strictly applicable to
human beings
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human experiments
• Will always have to investigate disease etiology and to
evaluate the preventive and therapeutic measures.
• Even more in essential in the investigation of diseases
that cannot be reproduced in animals
• The benefits of the experiment have to be weighed
against risk involved. WHO has laid down strict code of
practice in connection with human trials
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types
• Randomised controlled trials-those
involving a process of random allocation
• Non randomised or non experimental
trials
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Randomised controlled trialsdesign
Select suitable population(ref.or target)
Select suitable sample
Make necessary exclusions
randomise
Experiment group Control
Manipulation and follow up
Those not eligible
Do not wish to give consent
Assessment www.drjayeshpatidar.blogspot.in
Steps in conducting RCT
• Developing a protocol
• Selecting reference and experimental
populations
• Randomisation
• Manipulation and intervention
• Follow up
• Assessment of outcome
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The protocol
• Aims and objectives
• Questions to be answered
• Criteria for the selection of study and control groups
• Size of the sample
• The procedures for allocation of subj.into study and
control groups treatment to be appliedProtocol to be strictly adhered till end ,helps in preventing bias and
source of error in the study
Pilot/preliminary studies are done prior to protocol –
feasibility/operational efficiency of certain procedures, or unknown
effects ,or on the acceptability of certain policies
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Selecting reference and experimental populations
1. Reference or target population
The popln.to which the findings of the trial ,if found successful are
expected to be applicable
Mankind/geographically limited/person in specific
age/gender/occupational/social group.
Population of a whole city, school children,etc.
2.experimental /study populations
Derived from ref popln.-actual popln.
Ideally should be randomly chosen.
3 criteria to be fulfilled:
informed consent
Representative of the population to which they belong
Qualified or eligible for the trial
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3.Randomisation
Statistical procedure
Control study
• Helps in removing bias and allow for comparability
• Heart of control trial
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Manipulation
• Deliberate application or withdrawal or reduction of the suspected causal factor as laid down in protocol
• Creates independentvariable(drug,vaccine dietary component ,a habit etc.) whose effect is determined by measurement of the final outcome –dependent variable (incidence of disease, survival time, recovery period)
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Follow up
• Examination of experimental and control
group at defined intervals time, in a
standard manner ,with equal intensity
,under the same given circumstances in
the same time frame till final assessment
of outcome
• There can be attrition
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Assessment
• Positive results :benefits of experimental
measure
• Negative results severity and frequency
of side effects and complications
Bias1. Part of participants –subject variation
2. Observer bias-
3. Evaluation to rectify blinding is used.
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Study designs -controlled
• Concurrent parallel :comparisons are made between 2 randomly assigned
groups one exposed to treatment other not
• Cross over type :each pt.serves as his own control
Randomised
Clinical trials
Preventive trials
Risk factor
Cessation experiments
Trial of etiological agents
Evaluation of health services
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Nonrandomized trials
• Uncontrolled trials
• Natural experiments
• Before and after comparison studies
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