1

PatientsPatientsClinical TrialClinical Trial Randomized Controlled Randomized Controlled Studies Studies

Healthy personHealthy person Field TrialField Trial

CommunitiesCommunitiesCommunity intervention studiesCommunity intervention studies Community TrialCommunity Trial

Experimental/ intervention StudiesExperimental/ intervention StudiesIndividualsIndividualsFollow-up/ LongitudinalFollow-up/ Longitudinal CohortCohort

IndividualsIndividualsCase-ReferenceCase-Reference Case-ControlCase-Control

IndividualsIndividualsPrevalencePrevalence Cross-sectionalCross-sectional

PopulationsPopulationsCorrelationalCorrelational EcologicalEcological

Analytical studiesAnalytical studiesDescriptive studiesDescriptive studies

Observational studiesObservational studies

Unit of studyUnit of studyAlternate nameAlternate nameType of studyType of study

Design options in epidemiologic Design options in epidemiologic researchresearch

2

Frame a research questionFrame a research question SMARTSMART FINERFINER

How best the question could be How best the question could be answered?answered? Need to take certain decisionsNeed to take certain decisions

Deciding which one to Deciding which one to useuse

PRD-3

Deciding which one to use

The investigator observes the events without altering them

Decision # 1Alter the events under study?

The investigator applies an intervention, & observes the effect on the outcome

NO

Yes

Observational study

Experimental study

Example: Comparing the history of needle sharing among IV drug abusers

who have HIV antibodies with those who do not

Example: Impact of health education on needle sharing habits

PRD-4

Deciding which one to use

For observational studiesDecision # 2

Make measurements on more than one occasion?

Each subject is examinedon only one occasion

Each subject is followed overA period of time

NO

Yes

Cross-sectional study

Longitudinal study

Example: Study of needle sharing habits and HIV antibodies measured at the

same time

Example: Cohort study that assesses current needle sharing habits of group of

IV drug abusers and observes who subsequently develop HIV antibodies

PRD-5

Enlist three research questions that you will like to study

• Let us discuss what could be the best design for particular research question

PRD-6

Cross-sectional Studies

Pradeep DeshmukhProfessor,

Dr Sushila Nayar School of Public Health,Mahatma Gandhi Institute of Medical

Sciences, Sewagram

PRD-7

PRD-8

Definition

• A cross-sectional studies – a type of observational study– the investigator has no control over the exposure of

interest (e.q. diet).

• It involves– identifying a defined population at a particular point in

time– measuring a range of variables on an individual basis

• e.g. include past and current dietary intake

– At the same time measuring outcome of interest• e. g. obesity

PRD-9

Definition

• Measurement of exposure of interest and outcome of interest is carried out at the same time (e.g. Obesity and Hypertension)

• There is no in-built directionality as both exposure and outcome are present in the study subject for quite some time

PRD-10

Cross-sectional studies

• Deals with the situation existing at a given time (or during a given period) in a group or population

• These may be concerned with:– The presence of disorders such as diseases, disabilities and

symptoms of ill health– Dimensions of positive health, such as physical fitness– Other attributes relevant to health such as blood pressure and

body measurements– Factors a/w health & disease such as exposure to specific

environmental exposure or defined social & behavioral attributes and demographic attributes

– Determining the workload of personnel in a health program as given by prevalence

PRD-11

Which came first?

?? Causality

PRD-12

PRD-13

Cross-sectional studies

• May be– Descriptive– Analytical or– Both

• At descriptive level, it yields information about a single variable, or about each of number of separate variables in a study population

• At analytic level, it provides information about the presence and strength of associations between variables, permitting testing of hypothesis

PRD-15

Synonyms

• Instantaneous study

• Prevalence study

• Simultaneous study

PRD-16

Steps in cross-sectional studies

PRD-17

PRD-18

Chose the problem & analyze it

• Important steps:– Problem identification– Prioritize the problem– Analyze the problem to convert it in “Research

Question”• Specific• Measurable• Realistic• Time bound

• Questions to ask:– What is the problem?– Why should it be studied?

PRD-19

Literature review

• What information is already available?

• Helps you understand and analyze the problem– Is it the same thing which is bothering me?– Uncertainty about a health issue that the

investigator wants to resolve

• Helps you to frame SMART research question

PRD-20

SMART research question: Example

• What is the distribution of hemoglobin in adolescent girls of Anji PHC?

• What is the prevalence of anemia among adolescent girls of Anji PHC?

• Is the prevalence of anemia among non-school going adolescent girls higher as compared to that of school going adolescent girls of Anji PHC?

PRD-21

Other attributes of SMART RQ

• Feasible– Adequate number of subjects– Adequate technical expertise– Adequate resources (time & money)

• Interesting to investigator• Novel

– Confirms or refutes previous findings– Extends previous findings– Provides new findings

• Ethical• Relevant

– For scientific knowledge– For policy implications– For future research directions

PRD-22

Research Methodology

• Questions to be asked:– What data do we need to meet our objectives?– How will I get this? – How will it be collected?

• Elements:– Study population– Study subjects – Sampling & Sample size– Variables– Data collection instruments & techniques & plan– Data management – data processing & analysis– Ethical clearance– Piloting

PRD-23

Choosing the study subjects

• Good choice of study subjects serves the vital purpose of assuring that the findings in the study accurately represent what is going on in the population– Sample of subjects which are affordable in time &

money, – yet it is large enough to control random error in

generalizing the study findings to the population– and representative enough to control systematic error

in these inferences

PRD-24

Internal & External validity

PRD-25

Some terminologies

• Target population

• Accessible population

• Study subjects

PRD-26

Actual study

Actual subjects

Association between hypertension and CHD observed in actual sample of Framingham adults

Study plan

Intended sample

Same association exists in designed sample of Framingham adults

Accessible population

Same association exists in all Framingham adults

Research question

Target population

Same association exists in all sub-urban US adults

Same association exists in all sub-urban Indian adults

Internal validity inference

External validity inference # 1

External validity inference # 2

Internal & External validity

PRD-27

Specify clinical & demographic characteristics

CRITERIA

Well suited to the Research Question

Specifications & sampling

Research Question

(Truth in universe)

Step # 1

Target population

Study plan

(Truth in study)

Step # 3

Intended sample

Design an approach to select the sample

CRITERIA

Representative of accessible population & easy to do

Step # 2Accessible Population

Specify temporal and

geographic characteristics

CRITERIA

Representative of target

populations and easy to study

Specification Sampling

PRD-28

Specifications: Designing inclusion & exclusion criteria

Criteria Considerations Examples

Inclusion criteria (be specific)

Target population

Accessible population

Specifying the characteristics that define populations that are relevant to the research question and efficient for study:

Demographic characteristics

Clinical characteristics

Geographic characteristics

Temporal characteristics

A CS study to find out Essential hypertension in adults specified:

Aged 18 years and more

-

Field practice area of MGIMS

Between 1st Jan to 31st Jan 05

Exclusion criteria

(be parsimonious)

Specify subsets of population that will not be studied because of:

Inability to provide good/reliable data

Ethical barriers

Subject’s refusal to participate

Mentally retarded individual

Seriously ill individual

Not given consent

PRD-29

Sampling methods

• Probability sampling– Simple random sampling– Systematic sampling– Stratified random sampling– Cluster sampling

• Non-probability sampling– Consecutive sampling– Convenience sampling– Purposive (Judgmental) sampling

PRD-30

Sample size• One sample situation:

– A. Proportion• Estimating a population proportion with specified precision

– Absolute– Relative

• Hypothesis test for population proportion– B. Mean

• Estimating a population mean with specified precision• Estimating sample size with unknown mean • Hypothesis test for population mean

• Two sample situation– A. Proportions

• Estimating difference between two population proportions with specified precision

• Hypothesis test for two population proportions– B. Means

• Estimating difference between two population means with specified precision

• Hypothesis test for two population means

PRD-31

Single population - Proportion

• Absolute – N=Z2p(1-p)/d2

• Relative– N=Z2p(1-p)/e2p

• Hypothesis test– N={Z1-* sqrt[p0(1-p0)+ Z1-* sqrt[pa(1-pa)]}2/(p0-pa)2

Note – Replace by for two tailed hypothesis

PRD-32

Single population -Mean

• Estimating population mean with specified precision– N> (1.96)2 SD2/(0.05M)2

• Estimating sample size with unknown mean– N =

d

• Hypothesis tests for population mean– N=[

PRD-34

Sample size calculation

• EPI-Info

• Readymade tables– Lwanga SK and Lemeshow S. Sample size

determination in health studies: A practicle manual. World Health Organization, Geneva; 1991

PRD-35

Shall we do some calculations here?

PRD-36

Variables• What characteristics will be studied- variable• Depends on objective of study• Variables

– Outcome variable (dependent variable)– Predictor variable (independent variable)– Continuous & Categorical variables

• Literature search:– you have not left out any important predictor variable– How other people have defined these variables– How other people have measured these variables

• Biological rationale

PRD-37

• Defining variable– Clear & explicit definition– Operational definition– Obesity as defined by body fat content more

than 33% Vs BMI > 25

Variables

PRD-38

VariablesType of variable

Characteristic Example Appropriate statistics

Information content & power

Categorical

Nominal Unordered categories

Sex, blood gp Counts, rates, proportions, RR, chi-square, Regression

Low

Ordinal Ordered categories with intervals which are not quantifiable

Degree of pain Above & median, rank correlation

Intermediate

Continuous or discrete

Ranked spectrum with quantifiable intervals

Weight, number of cigarettes/day

Above & mean, SD, t-test, ANOVA, more powerful regression

High

PRD-39

Data collection

• Data collection instrument

• Data collection plan

• Quality check plan

PRD-40

Data collection instrument: Questionnaire/Interview

schedule• General:

– Brief description of purpose of study– Instructions specifying how to fill– Group the questions concerning major subject area under a

short heading– Warm-up questions

• Open-ended & close-ended questions• Instrument format

– Format should make it as easy as possible for filling and avoiding data entry confusions

• Wording– Clarity, simplicity, neutrality, double-barreled questions, time

frame• Codes, scores and scales

PRD-41

Steps in designing questionnaire

• Make a list of variables• Borrow from other instruments• Write a draft• Revise• Pretest• Shorten and revise again• Precode

• Use of “Free Listing” & “Pile Sorting”

PRD-42

Precision & Accuracy

Good precision Poor precision Good precision Poor precision

Poor accuracy Good accuracy Good accuracy Poor accuracy

PRD-43

Precision & accuracy

Precision Accuracy

Definition The degree to which a variable has nearly the same value when measured several times

The degree to which a variable actually represents what it is supposed to represent

Best way to assess

Comparing among repeated measures

Comparison with a reference standard

Value to study Increase power to detect effects

Increase validity of conclusions

Threatened by Random error (variance) contributed by:

-the observer

-the subject

-the instrument

Systematic error (bias) contributed by:

-the observer

-the subject

-the instrument

PRD-44

Strategies for reducing random error to increase precision

Strategy Source of error Example of error Example of strategy

Standardizing the measurement methods in an operations manual

Observer Variations in BP measurement due to variable rate of cuff deflation

Specify that the cuff be deflated at 2 mmHg/sec

Subject Variation in BP due to variable length of quiet sitting

Specify that the subject sit in a quiet room for 5 min before BP measurement

Training the observer Observer Variation in BP due to variable observer technique

Train observer in standard techniques

Refining the instrument Instrument or observer

Variation in BP due to digit preference

Use zero muddler to conceal BP reading until after it has been recorded

Automating the instrument

Observer Variation in BP due to variable observer technique

Use automatic BP recording device

Subject Variation on BP due to variable reaction to observer by subject

Use automatic BP recording device

Repeating the measurement

Observer, subject, instrument

All measurements and all sources of variation

Use mean of two or more BP measurements

PRD-45

Strategies for reducing systematic error to increase accuracy

Strategy Source of error Example of error Example of strategy

Standardizing the measurement methods in an operations manual

Observer Consistently high BP readings due to using a point at which sounds become muffled

Specify the point in operations manual which point to be taken for cut-off

Subject Consistently high readings due to measuring BP right after walk

Specify that subject sit for 5 min in quiet room

Training the observer Observer Consistently high BP readings due to failure to follow the guidelines given in manual

Trainer checks the accuracy of observer’s reading

Refining the instrument

Instrument Consistently high BP readings with standard cut-off in subjects with very large arms

Use wide BP cuff in obese patients

Automating the instrument

Observer Tendency of observer to read BP lower in treatment group

Use automatic BP measuring device

Subject Variation on BP due to variable reaction to observer by subject

Use automatic BP recording device

Calibrating the instrument

Instrument Consistently high weight readings due to scale being out of adjustment

Calibrate balance with a specific weight every week

PRD-46

Data collection

• Quality Checks

• Capture-recapture:– All are not always met– Ascertainment-corrected total number of

Cases = [(A+1)(B+1)/(C+1)]-1

– A = No of cases by method 1– B = No of cases by method 2– C = No of cases common to both the above methods

PRD-47

Data management

• Recording data in schedule

• Choice of software

• Duplicate data entry

• Missing data

• Data cleaning

• Data storage

PRD-48

Analysis

• Analysis plan– Depending on objectives of the study– Dummy tables

PRD-49

Time for Group Work

• Three groups

• Design the cross-sectional study

PRD-50

Analysis- Descriptive CS study

• Objective: – To describe the disease in time, place and person – To generate hypothesis

• Analysis– Means & SD– Median & percentile– Proportions – Prevalence– Ratios– Age, sex or other group specific analysis

PRD-51

Analysis – Analytical CS study

• Objective:– Is there any association?– If “YES”, then what is the strength of association?

• Analysis:– Is there any association?

• Chi-square, student-t test, etc– What is the strength of association?

• Correlations• Regression coefficients• Differences between mean• Odds ratio• Rate ratio• Rate difference

PRD-52

Analysis- Analytical CS study

• Measures of impact– Risk factor:

• Attributable fraction (exposed)• Attributable fraction (population)

– Protective factor• Prevented fraction (exposed)• Prevented fraction (population)

PRD-53

Prevalence

• Prevalence proportion: Proportion of the subjects who have the disease at a point in time

• Example: – Of 1500 middle aged women 30 had diabetes on

January 1, 2007.– The prevalence proportion of diabetes was 30/1500 =

0.02 or 2%

• Point prevalence• Period prevalence

PRD-54

Time

1

2

3

4

5

tAt time ‘t’, 2 out of 5 had the disease. PP=2/5=0.4

Number of

subjects

PRD-55

Point prevalence

Number of individuals with disease at a specified period of time

P = -------------------------------------------------------------------------------------Population at that time

Number of individuals with disease at a time the individual is studied

P = -------------------------------------------------------------------------------------Number of individuals are studied

• Paradox: Point prevalence of congenital anomalies

PRD-56

Period prevalence

• Refers to prevalence not at a single point in time but during a defined period

• Represents proportion of population manifesting the disease at any time during the period

Number of individuals manifesting the disease in the stated time period

P = --------------------------------------------------------------------------------------------------

Population at risk

• Population at risk = population in the middle of the period

PRD-57

Period prevalence

• Lifetime prevalence– Refers to whole of subjects prior life

No of individuals with evidence of disease (past or present)

P = ---------------------------------------------------No of individuals studied

• CS study in Jerusalem revealed that the point prevalence of inguinal hernia among men aged 65-74 years is 30% where as lifetime prevalence was 40 % - men with scar of operation as case

PRD-58

Exercise 1

Calculate:

•Point prevalence on 1st Jan

•Point prevalence on 1st Jul

•Point prevalence on 31st Dec

•Period prevalence in the year

PRD-59

Exercise 2• A population of 1000 females aged 40 &

over was screened for diabetes on 1 January 2006 and 40 cases were detected. During the latter half of the year, five patients died, five migrated and five recovered. Meanwhile, 20 new cases were detected. We want to measure morbidity from this group I year 2006.– Point prevalence on 1Jan– Point prevalence on 31 Dec– Period prevalence 2006

PRD-60

Screening: 1 Jan 2006 31 Dec 2006

PRD-61

Measures of association- Odds ratio

• Odds: probability that something is so or will occur to the probability that it is not so or will not occur

• a/b is an odds in favor of headacheExposure to fumes

Headache present

Headache absent

Total

Factor present

a=10 b=90 a+b= 100

Factor absent c=50 d=850 c+d= 900

Total a+c=60 b+d=940 n=1000

PRD-62

Odd ratio

• OR is the ratio of one odds to another Odds of disease among exposed

Disease OR = -------------------------------------

Odds of disease among not exposed

Odds of exposure among diseased

Exposure OR = -------------------------------------

Odds of exposure among not diseased• Jewell’s low-bias estimator

PRD-63

Useful features of odds ratio

• Facilitates comparisons of result from different kinds of study – CS Vs Time-span study

• Odds ratio of freedom from disease is reciprocal of disease OR which is not true for prevalence ratio

• Observations in different population groups/strata are combined by MH procedure based on assumption that the association has same strength in each stratum – legible

• OR sometimes serve as proxy for ratio of incidence in exposed and unexposed

PRD-64

Rate ratio

Exposure to fumes

Headache present

Headache absent

Total

Factor present

a=10 b=90 a+b= 100

Factor absent c=50 d=850 c+d= 900

Total a+c=60 b+d=940 n=1000

Prevalence ratio = {a/(a+b)}/{c/(c+d)} = 1.8

Exposure ratio = {a/(a+c)}/{b/(b+d)} = 1.74

PRD-65

Rate difference

Exposure to fumes

Headache present

Headache absent

Total

Factor present

a=10 b=90 a+b= 100

Factor absent c=50 d=850 c+d= 900

Total a+c=60 b+d=940 n=1000

Prevalence difference = {a/(a+b)} - {c/(c+d)} = 0.0444

Exposure difference = {a/(a+c)} - {b/(b+d)} = 0.07

Number needed to avoid one case in unexposed group = 1/prevalence difference = 1/0.0444=22.5

PRD-66

Measures of Impact: Risk factor

• Excess risk among exposed== {a/(a+b)} - {c/(c+d)} = 0.0444

• Population excess risk == (a+c)/n – c/(c+d) = 0.004

• Attributable fraction (exposed)== [(Prevalence ratio – 1)/Prevalence ratio] *100= 44.4

• Attributable fraction (population)== [(Prevalence ratio – 1)*E]/{1+[(Prevalence ratio -1)*E]} *100= 7.4 E = exposure rate in population

PRD-67

Measures of impact: Preventive factors

• Excess risk among unexposed = c/(c+d) – a(a+b)• Population excess risk = (a+c)/n – a(a+b)• Prevented fraction (exposed) =

= {[c/(c+d) – a(a+b)]/[c/(c+d)}*100• Prevented fraction (population) =

={[(a+c)/n – a(a+b)]/[(a+c)/n]}*100

PRD-68

Other analysis

• Stratified analysis

• Logistic regression

• Negative binomial regression

PRD-69

Bias

• Any effect at any stage of investigation or inference tending to produce results that depart systematically from true values (towards one side)

PRD-70

Sources of error• Systematic error (bias):

– Confounding bias: • Lack of comparability between the exposed & unexposed with

regards to other factors that affect the risk of developing the disease– Misclassification bias:

• Errors in the classification of subjects according to exposure or disease – interviewer bias, response bias, recall bias

– Selection bias:• Selection of subjects or their participation in the study is influenced

by the disease under study– Sample bias – non-representative sample selection– Non-response bias– Non-participant bias– Berkson’s bias– Membership bias

• Random error (chance):• Uncertainty introduced by small number of observations

PRD-71

Strategies in dealing with systematic error

• Confounding bias:– Restriction– Matching– Stratified analysis/Multivariate analysis

• Misclassification bias:– Blinding– Minimal gap between theoretical and empirical definition of

exposure/disease• Selection bias:

– Population should be defined independently of disease of interest

– All information on the subjects should be secured to avoid selective loss of information

– Prevent loss to follow-up

PRD-72

Report

• Important for dissemination

• Based on client/user

• STROBE Guidelines

PRD-73

Uses of CS studies..

• The findings may be used to promote the health of the population studied i.e. can be used as tool in community health care

• Can contribute to clinical care• Can provide “new knowledge”

• The uses are not mutually exclusive & single study can fulfill more than one purpose

PRD-74

Uses in community health care

• Community diagnosis– Health status– Determinants of health & disease– Association between variables– Identification of groups requiring special care

• Surveillance• Community education & community

involvement• Evaluation of community’s health care

PRD-75

Uses in clinical practice

• Individual & family care

• Community oriented primary care

PRD-76

Studies yielding “new knowledge”

• Studies of growth & development

• Studies of etiology

• Program trials

PRD-77

Guidelines for critical appraisal of prevalence studies

1. Are the study design & sampling method appropriate for the RQ?

2. Is the sampling frame appropriate?3. Is the sample size adequate?4. Are objective, suitable and standard criteria used to

measure the health outcome?5. Is the health outcome measured in unbiased manner?6. Is the response rate adequate? Are the refusers

described?7. Are the estimates of prevalence given with CI & in detail

by subgroup – if appropriate?8. Are the study subjects and the setting described in

detail and similar to those of interest to you?

PRD-78

Comparison of three analytic strategies

Cohort Case-control

PRD-79

Choice of strategy

PRD-80

PRD-81

Advantages & disadvantages of different observational study

designs

PRD-82

Relative ability of different types of study to prove

causation

PRD-83

Cross-Sectional StudiesAdvantages

• Cheap and quick studies.

• Data is frequently available through current records or statistics.

• Ideal for generating new hypothesis.

PRD-84

Cross-Sectional StudiesDisadvantages

The importance of the relationship between the cause and the effect cannot be determined.

• Temporal weakness:– Cannot determine if cause preceded the

effect or the effect was responsible for the cause.

– The rules of contributory cause cannot be fulfilled.