Epidemiological Study Designs

Muhammad Tahir, MPH,MSc Epi & Bio

Acknowledgment:Ms. Tazeen Saeed AliAssistant Prof. AKUSON

Objectives By the end of the session the participants

will be able» Examine the purposes, structure, strengths and

weaknesses of the different types of research designs.

» Compare difference between these approaches» Review the definition of epidemiology, objectives,

and history.» Compare the different phases of natural history

of disease transmission. » Explain the integration of epidemiological designs

in to community health nursing practice.

Background Rationale and Characteristics of epidemiological

Research» Need to understand disease causation» Need to describe disease occurrence» Used to generate and test hypothesis, and

evaluate health interventions» Design Characteristics

– Specific goals and objectives– Methodology

Background Goals of Epidemiology and Public Health

» Scientific research is the process of proposing and testing postulates and hypothesis in a specific field that may be or not related to public health

» Evaluation research is concerned with the decision making process to implement, continue or adopt a new program that may be or not in the public health field

» Epidemiological studies can be and has been used in both research approaches

Applications of Epidemiological Designs

Clinical Trials» testing new drugs or clinical management

approaches» determining prognosis

Cohort» natural history of disease» etiology of disease - test hypothesis on

causation

Applications of Epidemiological Designs

Case-Control» natural history of disease» etiology - test hypothesis on causation

Case report, case series, X-sectional, » describe disease occurrence» natural history of disease» generate hypothesis

Research Designs in the Health Field

Observational Designs» Analytic

– Cohort studies– Case-control studies– Cross-sectional studies

» Descriptive– Case report– Case series– Cross-sectional studies– Ecological or correlation studies

Research Designs in the Health Field

Experimental Designs–Laboratory experiments–Clinical Trials–Field Trials–Intervention Trials

Quasi-Experimental–Field –Intervention Trials

Epidemiological Designs Descriptive

» objective is to describe the patterns and trends» help to generate hypothesis» help to plan programs

– measure frequency of disease or other health outcome (occurrence)

– measures determinants (risk factors) and effects on health outcomes

– risk factors and effects may be measured over time

Case Report What?

the profile of a single patient is reported in detail by one or more clinicians

ExampleIn 1961, a published case report of a 40 year-old women who developed pulmonary embolism after beginning use oral contraceptive

Case Series What?

An individual case report that has been expanded to include a number of patients with a given disease

ExampleIn Los Angeles, five young homosexuals men, previously healthy, were diagnosed with pneumocyst cariini pneumonia in a 6-month period

Case Series Clinical case-series: usually a coherent and consecutive

set of cases of a disease (or similar problem) which derive from either the practice of one or more health care professionals or a defined health care setting, e.g. a hospital or family practice.

A case-series is, effectively, a register of cases. Analyse cases together to learn about the disease. Clinical case-series are of value in epidemiology for:

» Studying symptoms and signs » Creating case definitions » Clinical education, audit and research

Cross-sectional» often interest is to describe frequency and

pattern of either disease or health-related outcome occurrence.

» existing traits, be it disease or health-related outcome, are measured at same time.

» Usually data collected in a survey. door to door, mail or telephone interview and measurement.

» neither cases nor comparison group, if exist, are pre-selected (post hoc selection).

Example - X-sectional Prevalence of Pap Smear

67.5

85.2

48.6

64.6

85 85

0102030405060708090

100

Prevalence <= 1 yr Prevalence <=3 yr

%MONationalYear 2000

Cross-Sectional Study In special circumstances can be analytic neither cases nor comparison group are pre-

selected. post hoc selection. existing traits, be it exposure or health

outcome, are measured at same time. therefore, assessment of temporality in found association is not possible. There are exceptions.

Cross-Sectional Study

in elig ible

exposed&

bad ou tcom e

exposed&

good ou tcom e

unexposed&

bad ou tcom e

unexposed&

good ou tcom e

partic ipation no partic ipation

elig ible

Source P opu lation

Cross-Sectional Study

ineligib le

phys ically active&

C H D

phys ically active&

n o C H D

physically inactive&

C H D

phys ically inactive&

n o C H D

partic ipation no partic ipation

eligible

F arm ers

Cross-Sectional Study

Disease

Exposure yes no total

yes a b a + b

no c d c + d

Cross-Sectional Study

CHDPhysicallyactive yes no total

yes 3 87 90

no 14 75 89

Prevalence

Proportion of individuals in a population with disease at a specific point of time

Provides estimate of the probability or risk at one will be ill at a point in time

Provides an idea of how severe a problem may be

Useful for planning health services (facilities, staff)

Number of existing cases of diseaseP = at a given point in time Total population at risk

Formula for prevalence:

2176 subjects with asthma encounter P = = .07 31005 subjects

= 7 asthmatics per 100 subjects= 7 %

Types of Prevalence Point prevalence: number of cases that

exist at a given point in time Lifetime prevalence: proportion of the

population that has a history of a given disorder at some point in time

Period prevalence: number of cases that exist in a population during a specified period of time

Ecological or Correlation Ecological Studies

» whole population is the unit of analysis» relationship between exposure and outcome at the

individual level is missing (incomplete design)» ecological fallacy

Correlation Studies» same as ecological» aim to show strength of the ecological

association

Ecological fallacy: example

Imagine a study of the rate of coronary heart disease in the capital cities of the world relating the rate to average income.

Within the cities studied, coronary heart disease is higher in the richer cities than in the poorer ones.

We might predict from such a finding that being rich increases your risk of heart disease.

In the industrialised world the opposite is the case - within cities such as London, Washington and Stockholm, poor people have higher CHD rates than rich ones.

The ecological fallacy is usually interpreted as a major weakness of ecological analyses.

Ecological analyses, however, informs us about forces which act on whole populations.

Epidemiological Designs Analytic

» main objective is to test hypothesis of relationship between exposure to a risk factor and disease or other health outcome

» a measure of association is estimated» the magnitude, precision and statistical

significance of the association is determined

Case Control Study

» select population of cases and controls that are comparable

» using historical data, determinant (exposure or risk factor) is measured retrospectively among case and controls

» exposure and level of exposure measurement results compared between cases and controls to test a-priori hypothesis

ineligible

exposed unexposed

bad ou tcom e(cases)

exposed unexposed

good ou tcom e(con trols )

partic ipation no partic ipation

elig ible

S ou rce P opu lation

Case-Control Study

in elig ible

no partic ipation

c igarette sm oke(exposed)

no c igarette sm oke(un exposed)

partic ipation

lu ng cancer(cases)

no partic ipation

c igarette sm oke(exposed)

no c igarette sm oke(u nexposed)

partic ipation

no lu ng cancer(con trols )

S t. L ou is res iden ts> 50 years old

durin g 19 96 - 199 7(e lig ible)

G eneral popu lation

Case-Control Study

Case-Control StudyDisease

Exposure yes no total

yes a b a + b

no c d c + d

total a + c b + d a + b + c + d

Case-Control Study

Exposure Cases Controls total

yes 500 200 700

no 100 400 500

total 600 600 1200

Odds Ratio

Breast No Breast Cancer CancerAlcohol 70 100No alcohol 50 140 a x d (70) (140) b x c (50) (100)* Used for case control studies because persons are

selected based on disease status so you can’t calculate risk of getting disease

OR = = = 2.0

RR or OR RR = 1 Risk in exposed is equal to risk

in non exposed RR > 1 Risk in exposed is greater than

risk in non exposed RR < 1 Risk in exposed is less than risk

in non exposed

Cohort or Follow-up Study determinant (risk factor) is measured in pre-

selected cohort to identify exposed and non-exposed

cohort is followed-up effect or health outcome (disease) is

measured over time at the end of study period results are

compared between exposed and non-exposed to test a-priori hypothesis

follow-up period

end of follow-up

Cohort study

notexposed

exposed

Cohort study

notexposed

exposedIncidence among

exposed

Incidence amongnon-exposed

RR

ineligible

no partic ipation

bad ou tcom e good ou tcom e

partic ipation

exposed

no partic ipation

bad ou tcom e good ou tcom e

partic ipation

unexposed

elig ible

Sou rce P opu lation

Cohort Study

inelig ib le

no partic ipation

deep chest SS I no deep chest S S I

partic ipation

obese

no partic ipation

deep chest SS I no deep ches t SS I

partic ipation

not obese

C A BG su rgery perform edat BJC hospitals

du ring 1 999

C ABG patien ts

Cohort Study

Coho

rt

Des

ign

timeStudy begins here

Studypopulation

free ofdisease

Factorpresent

Factorabsent

disease

no disease

disease

no disease

presentfuture

Disease

Exposure Yes No Total

Yes a b a+b

No c d c+d

Cohort Study

Deep chest SSI

Obese Yes No Total

Yes 10 490 500

No 15 1,485 1,500

Cohort Study

Relative Risk Measure of association between incidence

of disease and factor being investigated Ratio of incidence rate for persons exposed

to incidence rate for those not exposed Incidence rate among exposed

RR = Incidence rate among unexposed Estimate of magnitude of association

between exposure and disease

Incidence rate among exposedRR = Incidence rate among unexposed

Formula for relative risk:

a / (a + b)RR = c / (c+ d)

Difference Measures

Attributable risk» # of cases among the exposed that could be eliminated

if the exposure were removed= Incidence in exposed - Incidence in unexposed

Population attributable risk percent» Proportion of disease in the study population that could

be eliminated if exposure were removed

Incidence in total population - Incidence in unexposed incidence in total population=

Attributable risk Relative risk: RR

Cohort Study Design Diseased Non

Diseased

Exposed 60

40 100 (fix)

Non Exposed

40

60 100 (fix)

Cohort Study Design Diseased Non Diseased Exposed 60 (people who were

exposed and developed the disease)

40 (people who were exposed and did not developed the disease)

100 (fix)

Non Exposed 40 (people who were not exposed and developed the disease)

60 (people who were not exposed and did not developed the disease)

100 (fix)

RR=60 /100

40 /100

= 60/100 x 100/40= 1.5

The rate (proportion) of a disease or other outcome in exposed individuals that can be attributed to the exposure

Attribute: one of the feature of a disease Or cause of a disease

Causes of Lung cancer

30%

30%

40%

smoking

Radiation

genetic

30%

30%

40%

Formula for Attributable RiskIncidence in exposed group - incidence in non exposed group

Incidence in exposed group(60/100) - (40/100)

(60/100)

=

= = 0.33 = 33 %

•Attributable risk indicates the prevention or cessation of smoking or risk factor facilitates the decrease in the burden of lunge cancer

Research Designs Controlled experiments (Experimental)

» determinant or intervention (treatment) is planned

» control (non-treatment) group is free from the intervention

» subjects selected into intervention (treatment) and control (non-treatment) groups by randomization

Examples Laboratory experiments

» effects of anti-cancer drugs in mice Clinical trials

» effect of anti-cancer drugs in humans ( volunteers) Field trials

» a-priori hypothesis about effect of intervention is assessed» subjects of study not patients. usually healthy individuals in the community» because probability of disease is small, a large number of subjects are

needed Salk and Sabin vaccine trials Intervention Trials

» similar to field trial» however, intervention is available at a group or community level.» a-priori hypothesis about effect of intervention is assessed» fluoridation of tap water

Expe

rimen

tal

Desig

n

timeStudy begins here (baseline point)

Studypopulation

Intervention

Control

outcome

no outcome

outcome

no outcome

baselinefuture

RANDOMIZATION

Experimental Advantages

Best evidence study design No selection bias (using blinding) Controlling for possible confounders Comparable Groups (using

randomization)

Quasi-Experimental Does not meet all of the requirements

necessary for controlling the influence of extraneous variables.» Most common criteria not met is random

assignment.