Basic steps in a survey –An 8-step Model

1

Formulating the research problem

2

Conceptualizing the research

design

3

Constructing an instrument for data collection

4

Selecting a sample

5

Writing the survey proposal

6

Collecting data

7

Processing data

8

Writing the survey report

2

Conceptualizing the research

design

Observational Studies• A DESCRIPTIVE STUDY is limited to a

description of the occurrence of a disease in a population and is often the first step in an epidemiological investigation.

• An ANALYTICAL STUDY goes further by analyzing relationship between health status and other variables.

Some Examples of Descriptive Studies

• Case Report

• Case Series

• Surveys

Pure descriptive studies make noattempt to analyze the links betweenoutcome and exposure

Ecological Studies

• In an ecological study, the units of analysis are groups of people rather than individuals.

Cross-sectional studies

• Because they measure the prevalence of a disease, they are sometimes also called ‘prevalence studies’.

• Exposure and effect (outcome) are measured at the same time.

Uses of cross-sectional studies

• Prevalence

• Disease outbreaks

• Assessing healthcare needs of populations.

• Trends in diseases (repeated c/s studies)

• Risk factors for diseases (e.g., NCDs)

Advantages and Disadvantages

• Easy and relatively inexpensive

• Less time consuming

• The temporal relationship between exposure and effect is difficult to establish.

CASE-CONTROL STUDIES

Key Features

• The exposure experience of a group of people who have the disease [CASES] is compared to the exposure experience of a similar (matched) group who do not have the disease [CONTROLS]

• Suitable for rare diseases or diseases with long latency periods

• The study proceeds backwards from “EFFECT to CAUSE’

Basic Design

• Selection of cases

• Selection of controls

• Measurement of exposure

• Analysis

Steps

Selection of Cases

• Define a ‘case’HospitalGeneral population

‘Prevalent cases’???TemporalityDisease severity (Those who are exposed survive longer)

• Sources of cases

• ‘Incident’ cases

Selection of Controls

• Free from disease

• As similar to the cases (matched) as possible, except for the absence of disease under study

• Sources of controls• General population

• Relatives/Friends/Neighbours

• Hospital controls

• How many controls per case?• One to four

“MATCHING” is the process of selectingcontrols in a case-control study so that thecontrols are similar to the cases with regardto certain key characteristics-such as age, sexand race.

Group matching(Frequency matching)

Individual matching(Pair matching)

Measurement of exposure

• Definition and criteria

• Done in the same way for both cases and controls

• How to measure exposures?

– Interviews/Questionnaires

– Past records (Hospital, Employment)

– Laboratory measurements

Analysis

• Find exposure rate in cases

• Find exposure rate in controls

• Calculate “Odds Ratio”

ExposureDisease

Yes No

Yes a b

No c d

Total a+c b+d

Odds Ratio=ad/bc

Use of Oral Contraceptive

Thromboembolism

Yes No

Yes 26 10

No 32 106

Total 58 116

Exposure rate among cases=(26/58)x100=45%

Exposure rate among controls=(10/116)x100=9%

Odds ratio= (26x106)/(10x32)=2756/320=8.6

People who use oral contraceptives have an8.6 times higher risk of developingthromboembolism compared to those whodo not use oral contraceptives

How to interpret the OR?

Cigarette smokingLung cancer

Yes NoYes 85 160No 15 240

Total 100 400

Odds Ratio=(85x240)/(160x15)=8.5

Q. An investigator selected 40 cases ofgastric carcinoma and an equal number ofcontrols matched for age, sex andsocioeconomic status. It was found thatamong cases 30 had an evidence of H pyloriinfection and among controls 15 had anevidence of H pylori infection. Is there anevidence of association between H pyloriinfection and gastric carcinoma?

5

COHORT STUDIES

Key Features

• The study proceeds from “CAUSE to EFFECT”

• At the start of the study, all participants are free from disease.

• A group of people who are ‘exposed’ to some factor and another ‘not-exposed’ group are followed up for a certain time. The disease rate (incidence of disease) among ‘exposed’ is compared to the disease rate among the ‘not-exposed’ group.

Basic Design

• Selection of study subjects

• Obtaining data on exposure

• Follow-up

• Analysis

Steps

Selection of Study Subjects

• General population

• Special groups

– Occupation group

– Professional group

• Radiologists

• Nurses

• Doctors

• Teachers, etc.

Free from study disease

Obtaining data on exposure

Cohort

Not-exposed

Exposed1

Exposed Cohort Not-Exposed Cohort

2

Exposed CohortHigh Exposure

Medium Exposure

Low Exposure3

Follow-up

• The follow-up procedures should be similar for both the exposed and the non-exposed groups.

• Clear, and valid definitions for disease status.

Analysis

• Find disease incidence rate in exposed

• Find disease incidence rate in non-exposed

• Calculate “Relative Risk” (Risk Ratio)

ExposureDisease

TotalYes No

Yes a b a+b

No c d c+d

Incidence rate among exposed=(a/a+b)*10x

Incidence rate among non-exposed=(c/c+d)*10x

Relative Risk = (a/a+b)

(c/c+d)

Exposure to prolonged heat stress

Kidney diseaseTotal

Yes No

Yes 67 4458 4525

No 39 5443 5482

Incidence rate among exposed= 14.8

Incidence rate among non-exposed= 7.1

Relative Risk= 14.8/7.1 = 2.1

People exposed to prolonged heat stresshave a 2.1 times higher risk of developingkidney disease compared to those who arenot exposed to prolonged heat stress

How to interpret the RR?

THREE types of Cohort studies

• Prospective

• Retrospective (Historical)

• Retrospective-Prospective (Ambispective)

Retrospective cohort studies

2014

1990

Data about oral contraceptive intake

in a cohort of women

How many of the women have

thromboembolicdisease, exposed

versus not-exposed

Study starts

Case-control studies start with outcome/diseaseCohort studies start with exposure

Case-control studies compare exposure rates among cases and controlsCohort studies compare disease rates among exposed and not-exposed

Case control CohortA

dva

nta

ges

Excellent way to study rare diseases with long latency

Better for studying rare exposures

Relatively quickProvides complete data on cases, stages

Relatively inexpensiveAllows study of more than one effect of exposure

Requires relatively few study subjects

Can calculate and compare rates in exposed and unexposed

Can often use existing records

Choice of factors available for study

Can study many possible causes of a disease

Quality control of data

Case control CohortD

isad

van

tage

sRelies on recall or existing records about past exposure

Need to study large numbers

Difficult or impossible to validate data

May take many years

Control of extraneous factors incomplete

Circumstances may change during study

Difficult to select suitable comparison group

Expensive

Cannot calculate rates Control of extraneous factors may be incomplete

Cannot study mechanism of disease

Rarely possible to study mechanism of disease

Experimental epidemiology

• Intervention or experimentation involves attempting to change a variable in one or more groups of people.

• The effects of an intervention are measured by comparing the outcome in the experimental group with that in a control group.

• Ethical considerations

• Informed consent

RANDOMIZED CONTROLLED TRIALS

A randomized controlled trial is an

epidemiological experiment designed to study

the effects of a particular intervention, usually a

treatment for a specific disease (clinical trial).

Subjects in the study population are randomly

allocated to intervention and control groups, and

the results are assessed by comparing outcomes.

“Randomization” is a statisticalprocedure wherein patients areallocated randomly to either theintervention group or the controlgroup. The purpose of randomization isto ensure that the patients in the twogroups are similar and hencecomparable.

FIELD TRIALS

Field trials, in contrast to clinical trials,

involve people who are healthy.

Data collection takes place “in the field,”

usually among people in the general

population

COMMUNITY TRIALS

Treatment groups are communities, rather than individuals.

This is particularly appropriate for diseases that are influenced by social conditions, and for which prevention efforts target group behavior.

ERRORSIN

EPIDEMIOLOGICAL STUDIES

RANDOM ERROR

SYSTEMATIC ERROR

RANDOM ERROR

• When a value of the sample measurement diverges-due to chance alone-from that of the true population value.

• Random error is “random”; therefore cannot be predicted.

• THREE major sources of random error

– Individual biological variation

– Sampling error

• Increase the size of the sample

–Measurement error

• Stringent protocols

• Systematic quality control measures

SYSTEMATIC ERROR

• Also called “BIAS”

• Systematic deviation of results or inferences from truth.

• Bias is defined as ‘any systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of an exposures effect on the risk of disease’.

TWO major types of bias

SELECTION BIAS

INFORMATION BIAS

• A systematic difference between the characteristics of the people selected for a study and the characteristics of those who are not.

• Examples

– Bias due to non-response

– Exclusion bias

– Berkson’s bias (Berksonian bias)

SELECTION BIAS

• Bias due to non-response

– Those who volunteer to take part in a study are different from those who don’t

• Exclusion bias

– Different eligibility criteria for cases and controls

•Berkson’s bias or Berksonian bias

• Berkson’s bias (Berksonian bias)

–When both exposure and disease understudy affect selection. This occurs when thecombination of exposure and disease understudy increases the chance of admission tohospital, leading to a higher exposure rateamong hospital cases as compared tohospital controls. Thus it causes hospitalcases and controls in a case-control study tobe systematically different from oneanother.

• A flaw in measuring exposure or outcome variables that results in different accuracy of information between comparison groups.

• This usually arises when the way of obtaining information about exposure or outcome is inadequate and hence may lead to incorrect information about exposure or outcome.

INFORMATION BIAS

Examples of Information bias

• Misclassification bias

– Wrongly classify exposure or outcome

• Recall bias

– Differential recall about exposure among cases and controls. Case are more likely to remember exposure as compared to controls

• Reporting bias

– Cases may be reluctant to report exposure

• Surveillance bias

– If exposed group is monitored more closely compared to the unexposed group

• Interviewer bias

– Knowledge about exposure status may consciously or subconsciously influence the interviewers measurements biased. Observer bias is a related bias.

• Single-blinding

• Double-blinding

• Triple blinding

CONFOUNDING

• In a study of whether factor A is a cause of

disease B, we say that a third factor, factor X is

a confounder if the following are true:

– Factor X is a known risk factor for disease B

– Factor X is associated with factor A, but is

not a result of factor A

• In designing and carrying out the study

– Matching

– Exclusion

• In the analysis of data

– Stratification

– Adjustment

Approaches to handling confounding