Epidemiology. Improve health of populations zfrequencies of diseases & health states (trends)...
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![Page 1: Epidemiology. Improve health of populations zfrequencies of diseases & health states (trends) zfactors that cause zpredicting occurrence & distribution.](https://reader030.fdocuments.us/reader030/viewer/2022032704/56649d3b5503460f94a16168/html5/thumbnails/1.jpg)
Epidemiology
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Epidemiology
Improve health of populations
frequencies of diseases & health states (trends)
factors that causepredicting occurrence & distributionfactors that prevent, prolong life,
improve health
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Epidemiology
Identify / Explain causal factors (exposures)
epidemics
epi - above/arounddem - people
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Epidemiology
Distribution and determinants
disease, injury, or dysfunction
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Epidemiology
Exposures risk (causal) factors
lifestyleoccupational hazardsenvironmental influencesinterventions
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Epidemiology
Descriptivedistributions / patterns
Analyticcause and effectmake inferences
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Epidemiology
DescriptiveDescriptive ExploratoryExploratory ExperimentalExperimental
DescribePopulations
IdentifyRelationships
Cause and Effect
Clinical TrialsClinical Trials
Cohort/Case-ControlCohort/Case-ControlStudiesStudies
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Descriptive Epidemiology
Who
Where
When
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Descriptive Epidemiology - Research Designs
Case report/series
Correlational studies
Cross-sectional surveys
NO Causality
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Measures of Disease Frequency
Prevalence
Point Prevalence
# of existing cases
total population at risk
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Point Prevalence
1,000 therapists in NYS during 1999 had LBP10,000 therapists in NYS
P = 1000/10,000 = 10%
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Measures of Disease Frequency
IncidenceCumulative Incidence
# of new cases
total population at risk
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Cumulative Incidence
500 therapists in NYS developed LBP in 199910,000 total therapists
CI = 500/10,000 = 5%
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Measures of Disease Frequency
Incidence Rate
# of new cases
total person-time
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Incident Rate
Of the 10,000 therapists in 1999 - 2,000 worked for only six months8,000 therapists contributed 8,000 person-years2,000 therapists contributed 1,000 person-yearsIR = 500/9,000 = 5.6%
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Descriptive EpidemiologyVital Statistics
Birth rateMortality rate:
total mortality - all causes
crude mortality - total mortality / avg. midyear population
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Descriptive EpidemiologyVital Statistics
Mortality rate“cause-specific” - specific disease /
avg. midyear population (AIDS, CAD, etc.)
“case-fatality” - deaths / individuals with disease
Age-specific rates
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Analytic EpidemiologyObservational Studies Case-Control CohortClinical Trials Intervention Study
DescriptiveDescriptive ExploratoryExploratory ExperimentalExperimental
IdentifyRelationships
Cause and Effect
Clinical TrialsClinical Trials
Cohort/Case-ControlCohort/Case-ControlStudiesStudies
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Observational Analytic Designs
Objective:Test hypotheses about
association/relationship of risk factors and disease
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Case-Control Studies
Case DefinitionCase Selectionpopulation-based – general
population of those w/ disorder
hospital-based – patients in medical institution
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Case-Control Studies
Analysis IssuesSelection bias
Misclassified
Observation/Interviewer bias
Extraneous variables
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Cohort (follow-up) Studies
Cohort – group of individuals followed over time
Temporal component
Limited use w/ rare disorders
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Cohort Studies
ProspectiveControl and monitor data collectionSubjects readily availableRetrospectiveInexpensive and fasterIncomplete/inadequate data
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Cohort Studies
representative sample generalize
group identification
internal comparison
external comparison
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Cohort Studies
Analysis Issues
Misclassification -
Attrition -
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Clinical Trials (RCT)
Intervention Study
Causality
Rigorous - Gold standard
Prospective - intervention vs. control
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Clinical Trials
TherapeuticEffect of rx or intervention
PreventativeAgent/procedure reduce risk of
developing a disease
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Clinical Trials
Subject SelectionTarget/Reference
Experimental/accessible population
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Clinical Trials
Validitysample size
achievable
attrition
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Clinical Trials
Analysisrandomizationblindingbiasethics
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Clinical Trials
Analysistests of statistical significance
(difference)t-tests, ANOVA, etc.causalityinferences about the population
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Measures of Association - Observational Studies
Test Hypotheses
Relationships
Association Exposure represents a risk factor
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Measures of Association
Relative EffectExposed:Unexposed
Absolute EffectDisease Rateexposed - Disease
Rateunexposed
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Relative Risk
a bc d
DiseaseYes No
Exp
osur
e
Yes
No
a + b
c + d
a + c b + d N
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Relative Risk
Cumulative Incidence Estimate Exposed (CIE)
Unexposed (CIO)
RR = CIE
CIO
= a / (a + b)
c / (c + d)
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Relative Risk
50 3319 259
Disease
Yes No
Exp
osur
e Yes
No
a + bc + d
a + c b + d N
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Relative Risk
CIE = 50/83 = 0.602
CIO = 19/278 = 0.068
RR = 0.602/0.068 = 8.9
RR = CIE
CIO
= a / (a + b)
c / (c + d)
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Relative Risk
Odds Ratio – Case-control
OR = a / cb / d
=adbc
= (50)(259) / (33)(19)
= 20.6
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Attributable Risk
Risk Difference = AR = IE - EO
AR = a
a + b - cc+ d
CIE - CIO =
AR = 0.602 - 0.068 = 0.534
AR = 534/1,000
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Attributable Proportion
AR% = ARIE
x 100IE -IO
IE
x 100=
AR% =0.534/(50/83) = 88.7%
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Attributable Proportion
AR% = OR-1OR
x 100
AR% = 19.6/20.6 = 95.1%
For case-control (Odds Ratio)
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Confounding
Extraneous (interfering) variable
associated w/ exposureconsidered a risk factor -
independently of the exposureNOT part of the causal link
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Causality
Inherent to interventional research but not observation research subject to interpretation:
Time sequenceStrength of associationBiologic credibilityConsistencyDose-Response
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Other Research Approaches
Historical
Evaluation
Methodological
Secondary Analysis
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Historical Research
To determine:
how present conditions evolved
anticipate future events
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Historical Research
Incorporates:judgementsanalysesinferencesEstablish relationships thru:organizingsynthesizing
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Historical Research
Critical Review of:eventsdocumentsliteratureother
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Sources of Historical Data
Primaryoriginal documents
letters, videotapes, photographs, minutes
eyewitness accounts
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Sources of Historical Data
Secondarybiographiestextbooksencyclopediasliterature reviewsnewspapersummaries
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Historical Research
Reliability and Validity
External Criticism authenticity
Internal Criticism content within context of question
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Historical Research
After data is collected:
establish relationships
no cause and effect
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Evaluation Research
Systematic approach to evaluating programs
clinicalacademic
Effectiveness
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Evaluation Research
Establish questions/hypotheses
Choosing variables sensitive
Methodology and design
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Evaluation Research
Data Collection and analysis
EvaluationsFormative – performed as part of
program planning or during implementation
Summative – assesses outcomes after program is implemented
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Evaluation Research
Evaluation of Program Objectives (measurable)
Quantitative
Qualitative/Behavioral
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Evaluation Research
Goal-Free Evaluation
evaluating predetermined goals vs.overall effect of program
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Evaluation Research
LimitationsBiasComplexLong termUsefulness
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Methodological Research
Development and testing of new instruments/measurement tools
Reliability and Validity applications to various patient populations sensitivity conditions “gold standard”
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Methodological Research
Only the beginning
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Secondary Analysis
Analyzing previously collected data
subsets of original datanew statistical techniquestest different hypotheses
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Secondary Analysis
Advantages:Low costLittle wait for dataLearn from predecessorsDisadvantages:Lack of control of data collection