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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.
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