EPIDEMIOLOGY

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• 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.

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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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