siroli lily: state flower of manipur
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Siroli Lily: State Flower of Manipur. Cross-sectional Study. Subodh S Gupta MGIMS, Sewagram. Simplest research questions. What is the total population of Imphal ? What proportion of married men in Imphal help their wives in kitchen. - PowerPoint PPT PresentationTRANSCRIPT
Siroli Lily: State Flower of Manipur
Cross-Cross-sectional sectional
StudyStudy Subodh S GuptaSubodh S GuptaMGIMS, SewagramMGIMS, Sewagram
Simplest research Simplest research questionsquestions
► What is the total population of Imphal?What is the total population of Imphal?► What proportion of married men in What proportion of married men in
Imphal help their wives in kitchen. Imphal help their wives in kitchen. ► What proportion of patients attending What proportion of patients attending
OPD in Imphal hospital and research OPD in Imphal hospital and research center come for psychiatric disorders? center come for psychiatric disorders?
► What is the prevalence of underweight What is the prevalence of underweight among under-five children in Ukhrul?among under-five children in Ukhrul?
► What proportion of residents of Imphal What proportion of residents of Imphal above 30 years of age do exercise above 30 years of age do exercise regularly? regularly?
More research More research questionsquestions
► Do married men younger than 40 Do married men younger than 40 years help their wives in household years help their wives in household chores more often than those chores more often than those above 40 years?above 40 years?
► Is the prevalence of hypertension Is the prevalence of hypertension higher in those who exercise higher in those who exercise regularly than those who do not regularly than those who do not exercise regularly?exercise regularly?
Types of Types of study study designdesign
Grimes and Schulz. Lancet 2002
Snapshot observation Vs longitudinal observation
Snapshot observation Vs longitudinal observation
Cross-sectional studiesCross-sectional studies
►Descriptive, orDescriptive, or►Analytical, orAnalytical, or►BothBoth
Gynecomastia in a drug Gynecomastia in a drug companycompany
►Puerto Rico pharmaceutical company: Survey showed that employees had gynecomastia
►OC pills; oestrogen dust might be the cause
►Dust control measures; epidemic disappeared
Harrington et al. Arch Environ Health 1978; 33: 12-15
Demographic surveys: Demographic surveys: a type of cross-sectional a type of cross-sectional
studiesstudies► National Family Health SurveyNational Family Health Survey► District level Health SurveyDistrict level Health Survey► NNMB SurveyNNMB Survey► Sentinel surveillance for HIVSentinel surveillance for HIV
HIV prevalence in India HIV prevalence in India by district, 2005by district, 2005
Multiple cross-sections help Multiple cross-sections help in giving a whole picture?in giving a whole picture?
Estimated adult HIV prevalence & Estimated adult HIV prevalence & number of PLHA, India, 2004-09number of PLHA, India, 2004-09
HIV estimation 2010HIV estimation 2010
Uses of cross-sectional Uses of cross-sectional studiesstudies
Public Health Public Health ►Community diagnosisCommunity diagnosis
Health statusHealth status Determinants of health & diseaseDeterminants of health & disease Association between variablesAssociation between variables Identification of groups requiring special Identification of groups requiring special
carecare►SurveillanceSurveillance►Evaluation of community’s health care Evaluation of community’s health care
(coverage evaluation)(coverage evaluation)
► Individual & family careIndividual & family care►Studies on diagnostic testStudies on diagnostic test►Studies of growth & developmentStudies of growth & development
Uses of cross-sectional Uses of cross-sectional studiesstudies
Cross-Sectional StudiesCross-Sectional StudiesAdvantagesAdvantages
►Cheap and quick studies.Cheap and quick studies.►Data is frequently available through current Data is frequently available through current
records or statistics.records or statistics.► Ideal for generating new hypothesisIdeal for generating new hypothesis►Generalizable results if population based Generalizable results if population based
samplesample►Study multiple outcomes and exposuresStudy multiple outcomes and exposures►Can measure prevalenceCan measure prevalence►Hypothesis generating for causal linksHypothesis generating for causal links►Serial surveysSerial surveys
Cross-Sectional StudiesCross-Sectional StudiesDisadvantagesDisadvantages
The importance of the relationship between The importance of the relationship between the cause and the effect cannot be the cause and the effect cannot be determined.determined.
►Temporal weakness:Temporal weakness: Cannot determine if cause Cannot determine if cause precededpreceded the effect the effect
or the effect was or the effect was responsible responsible for the cause.for the cause. The rules of The rules of contributory causecontributory cause cannot be cannot be
fulfilled.fulfilled.► Impractical for rare diseases if pop based Impractical for rare diseases if pop based
sample Prone to bias (selection, measurement)sample Prone to bias (selection, measurement)
Sampling methodsSampling methods►Probability samplingProbability sampling
Simple random samplingSimple random sampling Systematic samplingSystematic sampling Stratified random samplingStratified random sampling Cluster samplingCluster sampling
►Non-probability samplingNon-probability sampling Consecutive samplingConsecutive sampling Convenience samplingConvenience sampling Purposive (Judgmental) samplingPurposive (Judgmental) sampling
Target population
Accessible population
Intended Sample
Target population: Clearly defined clinical & demographic characteristics well suited to the research question
Specifications & SamplingSpecifications & Sampling
Example: Hypertension among adults (aged 18 years and above)
Target population
Accessible population
Intended Sample
Accessible population: Specify temporal and geographic characteristics representative of target populations and easy to study
Specifications & SamplingSpecifications & Sampling
Example: Hypertension among adults (aged 18 years and above in the field practice area of MGIMS)
Target population
Accessible population
Intended Sample
Intended population: Design an approach to select a sample representative of accessible population & easy to do
Specifications & SamplingSpecifications & Sampling
Example: Hypertension among adults (aged 18 years and above in the field practice area of MGIMS)
Precision & AccuracyPrecision & Accuracy
Good precision Poor precision Good precision Poor precision
Poor accuracy Good accuracy Good accuracy Poor accuracy
ConfoundingConfounding
►ExampleExample
Criteria for confoundingCriteria for confounding
1.1. The confounder must be associated The confounder must be associated with the exposure with the exposure
2.2. The confounder must be associated The confounder must be associated with the disease, independent of the with the disease, independent of the exposureexposure
3.3. The confounder must not be part of The confounder must not be part of the causal pathway connecting the the causal pathway connecting the exposure to the disease.exposure to the disease.
ExampleExample
►Crude analysisCrude analysis
Criteria 1Criteria 1
►Stratified analysisStratified analysis
Example: Example:
►Criteria 1: The confounder must be Criteria 1: The confounder must be associated with the exposure associated with the exposure
Example: Example:
►Criteria 2: The confounder must be Criteria 2: The confounder must be associated with the disease, associated with the disease, independent of the exposureindependent of the exposure
Bias in cross-sectional Bias in cross-sectional studiesstudies
Selection BiasSelection Bias (eg, NSSP study) (eg, NSSP study)Is study population representative of target Is study population representative of target
population? population? Is there systematic increase or decrease of RF?Is there systematic increase or decrease of RF?
Measurement BiasMeasurement BiasOutcomeOutcome► Misclassified (dead, misdiagnosed, undiagnosed)Misclassified (dead, misdiagnosed, undiagnosed)► Length-biased samplingLength-biased sampling
Cases overrepresented if illness has long duration and are Cases overrepresented if illness has long duration and are underrepresented if short duration.(Prev = k x I x duration)underrepresented if short duration.(Prev = k x I x duration)
Risk FactorRisk Factor► Recall biasRecall bias► Prevalence-incidence biasPrevalence-incidence bias
RF affects disease duration not incidence eg, HLA-A2RF affects disease duration not incidence eg, HLA-A2
AnalysisAnalysis
►Analysis planAnalysis plan Depending on objectives of the Depending on objectives of the
studystudy Dummy tablesDummy tables
Analysis- Descriptive CS Analysis- Descriptive CS studystudy
►Objective: Objective: To describe the disease in time, place and To describe the disease in time, place and
person person To generate hypothesisTo generate hypothesis
►AnalysisAnalysis Means & SDMeans & SD Median & percentileMedian & percentile Proportions – Proportions – PrevalencePrevalence RatiosRatios Age, sex or other group specific analysisAge, sex or other group specific analysis
Analysis – Analytical CS studyAnalysis – Analytical CS study►Objective:Objective:
Is there any association?Is there any association? What is the strength of association?What is the strength of association?
►Analysis:Analysis: Is there any association?Is there any association? What is the strength of association?What is the strength of association?
►CorrelationsCorrelations►Regression coefficientsRegression coefficients►Differences between meanDifferences between mean►Odds ratioOdds ratio►Risk ratioRisk ratio►Risk difference Risk difference
Other analysisOther analysis
►Stratified analysisStratified analysis►Logistic regressionLogistic regression