BASIC CONCEPTS IN EPIDEMIOLOGY

Dr. Yasser AbdelrahmanLecturer Of Anesthesia Ain Shams

University

WHAT IS EPIDEMIOLOGY

From Greek language Epi…………………On, Upon, Among Demos…………….The people Logos……………...Theory, Study

Epidemiology is the study of disease occurrence in human population

The only medical subspecialty that is concerned with the occurrence of illness over time

WHAT IS EPIDEMIOLOGY

TIME 1

Disease absentDisease present

or absent

TIME 2

Fundamental Assumptions

Human disease Does not occur at random Has causal and preventive factors Is a consequence of specific exposures

Environmental, Biological Behavioral

Radiation…………………….…………..CancerReduced fluoride…………..……Dental carriesSecond hand smoke…….Respiratory disease

Viruses………………………………....MeaslesBacteria………………………...…..Pneumonia

Cigarette smoking……………..….lung cancerPhysical inactivity……………………...ObesityNon marital sexual behavior……………...STD

EPIDEMIOLOGY RESEARCH

Explain why certain diseases are higher in some population groups than in others

Modify the exposure levels in the high risk groups to reduce their excess burden of disease

Identify specific Exposure (E) That might be causally related

To a Disease (D)

E D

AND TIME LINE

STUDY DESIGN

ED

DESCRIPTIVE STUDY

ED

ANALYTICAL STUDY

Descriptive studies Correlation study Cross sectional study Case study

i.e. correlation study is a cross sectional study in which the sample is the whole population

STUDY DESIGN

STUDY DESIGN

ED

Useful for generating a causal hypothesis

Cross sectional study Both diseased and non

diseased are studied Both D & E are measured They are measured as

present or absent at single point in the time line

It may be difficult to determine if E actually precede D in time

Case study Case report Case series

Descriptive studies

Analytical studies Observational studies

Case-control Cohort

Interventional studies (clinical trials)

STUDY DESIGN

ED

ANALYTICAL STUDY

STUDY DESIGN

There are two considerations regardingthe study designs based on

how “D” and “E” are handledby the investigator

Does the “E” refer to some periodin the subjects life beforethe occurrence of the “D”

Is the sample being studiedSelected

on “D” basis or on “E” basis

COHORTANALYTICALDISCRIPTIVE Case-Control

YESNO ED

Sequence of research study

STUDY DESIGN

There are two considerations regardingthe study designs based on

how “D” and “E” are handledby the investigator

Does the “E” refer to some periodin the subjects life beforethe occurrence of the “D”

Is the sample being studiedSelected

on “D” basis or on “E” basis

COHORTANALYTICALDISCRIPTIVE Case-Control

YESNO ED

Intervention study is a cohort study in which the investigator decides who gets the “E” and

who does not

Sequence of research study

RANDOMIZATIONdefinition

A method based on chance alone by which study participants are assigned to a treatment

group

CHANCE

RANDOMIZATIONbenefits

Eliminates the source of bias in treatments assignment

Facilitates blinding the type of treatments to the investigator, participants, and evaluators

Permits the use of probability theory to express the likelihood of chance as a source for the difference between outcomes

RANDOMIZATIONtypes

SIMPLESIMPLE RESTRICTEDRESTRICTED

BLOCKINGBLOCKING STRATIFICATIONSTRATIFICATION MINIMIZATIONMINIMIZATION

RANDOMIZATIONtypes

BLINDING

Single blind trial: The investigator is kept blind to the subject’s assigned group.

Double blind trial: The investigator and the subject are kept blind to the subject’s assigned group

Triple blind trial: Investigator, subject and assigners are kept blind to the subject’s assigned group

BLINDING

Investigator

Assigner

BASIC MEASUREMENTSMath

Ratio: a pair of numbers that compares two quantities

Rate : When a ratio is used to compare two different kinds of quantities

Proportion: is a statement that two ratios are equal(equal cross products)

apples to oranges 3 to 6 3:6

½ or half

Measures of Disease Frequency

Incidence:No. of newly added disease cases in a population at risk during a specified time interval

Prevalence:The proportion of individuals in a population who have disease at a specific point in time

RATE

RATIO

•measure of the instantaneous rate of disease•useful in estimating length of time needed to follow up individuals

•measure the individual risk of disease•useful in estimating the probability that an individual will be ill at a specific point in time

Measures of Disease Frequency

Cumulative incidence: The proportion of people who become diseased during a specified period of time

RATIO •measure the individual risk of disease•useful in estimating the probability that an individual will be ill at a specific point in time

PREVALENCE = Incidence x Duration of disease

Measures of Disease Frequency

prevalence

Mortality

AndRemissi

on

Incidence or

relapses

graph

Measures of Disease Frequency

equations

Number of new cases of a disease during a given period of time*

Total population at risk

Number of new cases of a disease during a given period of time*

Total person time of observation**

CI =

IR =

*Participants are observed till they get sick*Denominator is the total amount of disease-free person-time contributed by all individuals

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASEHow to

construct

2X2 TABLE

2X2 TABLE

Uses Risk assessment

Absolute risk Relative risk Attributable risk Odds ratio

Screening test components Sensitivity Specificity

Risk assessment

Involves people who develop disease due to an exposure

Doesn’t consider those who are sick but haven’t been exposed

Absolute risk

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASEAbsolute risk

2X2 TABLE

Absolute risk = A/A+B

Risk assessment

Is the ratio of Prevalence of “D” in Exposed persons : Prevalence of “D” in non-Exposed persons

A measure of strength of association between Exposure and Disease

Relative risk

RR= A/(A+B)C/(C+D)

Relative Risk= Absolute risk in ExposedAbsolute risk in non Exposed

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASERelative risk

2X2 TABLE

Risk assessment

If RR = 1 Risk in exposed = Risk in unexposed

( no association )

If RR > 1 Risk in exposed more than in unexposed

(positive association; causal)

If RR < 1 Risk in exposed less than in unexposed

(Negative association; protective)

Relative risk interpretation

Odds ratioOR

In case-control study participants are selected on the basis of “D”

We don’t know the incidence of “D” among exposed and non-exposed (A&C)

The ratio of the odds of exposed developing disease to the odds of non-exposed developing the disease

OR = =AD/BCA/CB/D

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASEOdds ratio

2X2 TABLE

Risk assessment

Is the mathematical difference between Prevalence of “D” in Exposed persons - Prevalence of “D” in

A measure of excess occurrence of disease due to the exposure assuming that the exposure is causally related to the disease.

Attributable risk

AR= A/(A+B) - C/(C+D)

Attributable Risk= Absolute risk in Exposed - Absolute risk in non Exposed

non – exposed persons

Risk assessment

Is the mathematical difference between Prevalence of “D” in Exposed persons - Prevalence of “D” in

A measure of excess occurrence of disease due to the exposure assuming that the exposure is causally related to the disease.

Attributable risk

AR= A/(A+B) - C/(C+D)

Attributable Risk= Absolute risk in Exposed - Absolute risk in non Exposed

the whole population

Population

A+C/(A+B+C+D)

non – exposed persons

Absolute risk in the whole population

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASEAttributable risk

2X2 TABLE

Statistical associationbetween “E” and “D”

It may be valid in a given study, or there may be some alternative explanation for it:

1. Association might be due to chance

2. Association might be due to bias

3. Association might be due to confounding

The smaller the sample size, the more room there is for chance to influence the study findings

BIAS

Population ExperimentalUnits

Treatment Group

Control Group

Treatment

No Treatment

Result

Result

3 421

An experiment or study is biased if it systematically favors a particular outcome

1. Subjects are not representative of the population2. Treatment and control groups are inherently

different on some lurking or confounding variable3. Subjects are influenced by knowing they are in

treatment or control groups4. Evaluator of outcomes is influenced by knowing

they are in treatment or control groups

Evaluating Bias inEpidemiological Study

Definition:An incorrect estimate of the “E” / “D” relationship because some extraneous factor was not adequately controlled in the study

Types of Bias:1. Selection Bias

2. Information Bias

a. Recall Bias

b. Observer Bias

3. Non response Bias

4. Loss of follow up

How to Control Bias

Blind data collector to avoid observer bias Mask the key “E” by asking many other useful

questions to avoid information bias Ask close-ended questions to reduce

recording errors by interviewer When assessing “E” history use multiple

sources of information whenever possible

Bias is a propriety of studydesign and not of a statistical analysis

CONFOUNDING

Causation: change in X cause change in Y

Common response: Both X and Y are responding to change in some other variable Z

Confounding: the effect of X on Y cannot be distinguished from the effect of other variable Z on Y

X Y

Z

X Y X Y

Z

?

?

Causation Common response Confounding

Evaluating confounding inEpidemiological Study

A confounding factor is a third variable associated with “E” under study and also independently affects risks of “D”

E/D association is due to mixing of effects between “E”,”D” and a third variable

Common confounding factors: age, sex and race Confounding can be positive or negative Randomization, restriction, matching and multivariable

analysis are methods to control confounding in the study design and analysis respectively

SCREENING

Is the application of a test to people who are asymptomatic for the purpose of classifying them to have particular disease

Does not diagnose disease: persons who test positive are referred for more detailed diagnostic evaluation.

Leads by early detection, before the development of symptoms to a more favorable diagnosis

SCREENING

SENSITIVITY: Probability that a person who really has the disease will be classified as such (good positive)

SPECIFICITY: Probability that a person who does not have disease will be classified as such (good negative)

TEST

A+B+C+DB+DA+CTotal

C+DDCNo

A+BBAYes

TotalNoYes

DISEASESensitivity

Specificity

2X2 TABLE

TRUTH

TEST

Total

B+DA+C A+B+C+DB+DA+C

C+D

A+B+C+DB+DA+C

A+B

C+D

A+B+C+DA+C

DCNo

BAYes

NoYes

Sensitivity

Specificity

2X2 TABLE

TRUTH

TEST

Sensitivity = A/A+C

Specificity = D/D+B

DEFINITIONS

Sensitivity= True positive

True positive + False positive

Specificity= True negative

True negative + False positive

PREDICTIVE VALUE

Predictive value of a

positive test

True positive

True positive + False positive

True negative

True negative + False negative

=

Predictive value of a

positive test

=