Description
Epidemiology, the so-called "science of public health," has undergone a boom in the last decade as public interest and engagement in population health has skyrocketed. While this boom has done much to spark advances in the technology of epidemiology, it has also made it harder for those who want to use epidemiology to guide policy and clinical practice to fully appreciate the meaning of the research findings.Interpreting Epidemiologic Evidence offers those who have had an introductory course in epidemiology the knowledge they need to make clear connections from research findings to practical applications. Written in clear and lively prose, it empowers students at all levels to evaluate a study's design, implementation, and ultimate findings, giving the guidance needed to apply the information appropriately. Liberal use of practical examples serves both to illustrate core concepts and to motivate readers to think critically about the causal connections that population health studies aim to explore.Completely revised and updated, this new edition of Interpreting Epidemiologic Evidence is an invaluable core text for both epidemiologists in training and practitioners across other disciplines with even an introductory knowledge of epidemiology.
Table of Contents
Interpreting Epidemiologic Evidence: Connecting Research to Applications1. IntroductionSynopsisLearning ObjectivesPerspectiveApproach to the Evaluation of EvidenceOrganization of Book2. The Nature of Epidemiologic EvidenceSynopsisLearning ObjectivesGoals of Epidemiologic ResearchMeasurement of Causal Relations Between Exposure and DiseaseApplications of Epidemiologic ResearchFramework for Examining Epidemiologic EvidenceRelationship of Epidemiology to Health PolicyExercise: Critical Assessment of Study Methods, Results, and Applications3. Causal Diagrams for Epidemiologic InferenceSynopsisLearning ObjectivesIntroductionCausal Diagrams in EpidemiologyPurpose and TerminologyDAGs Encode Our AssumptionsStatistical AssociationsConnection to Data AnalysesDepicting Passage of TimeDirect vs. Indirect EffectsConcluding ThoughtsRecommended Additional ReadingsExercise: Application of Causal Diagrams for Epidemiologic Inference4. Strategy for Drawing Inferences from Epidemiologic EvidenceSynopsisLearning ObjectivesConceptual Framework for the Evaluation of ErrorEstimation of Measures of AssociationSystematic Evaluation of Sources of ErrorObjective Evaluation of Sources of ErrorIdentifying the Most Important Sources of ErrorSpecifying Bias ScenariosExercise: Specifying Scenarios of Bias5. Confounding I: Theoretical ConsiderationsSynopsisLearning ObjectivesDefinitionIdentifying Potential ConfoundersTraditional Approach to Assessing ConfoundingModern Approach to Assessing ConfoundingInappropriate AdjustmentsAssessing the Direction and Magnitude of Potential ConfoundingMethods of Controlling ConfoundingRandomizationSelection of Study Setting Free of ConfoundingRestrict Study Groups to Enhance ComparabilityStatistical Adjustment for ConfoundingRecommended Additional ReadingsExercise: Conceptual Basis of Confounding6. Confounding II: Practical ConsiderationsSynopsisLearning ObjectivesEvaluating the Presence and Impact of ConfoundingSpecifying Scenarios of ConfoundingAssessing Whether Confounding is PresentConsider Potential for Complete ConfoundingAssess Consequences of Inaccurate Confounder MeasurementApplying Knowledge of Confounding Based on Other StudiesAssessing Confounding When Risk Factors are UnknownDose-Response Gradients and Potential for ConfoundingIntegrated Assessment of Potential ConfoundingExercise: Connecting Conceptual and Statistical Assessment of Confounding7. Selection Bias and Confounding Resulting from Selection in Cohort StudiesSynopsisLearning ObjectivesStudy DesignsDefinition and Examples of Selection BiasSelection Bias Versus ConfoundingEvaluation of Bias in Cohort StudiesCompare Those Included to Those Not IncludedCompare Disease Rates Among Unexposed to External Populations Assess Whether Expected Patterns of Disease are PresentAssess Pattern of Results in Relation to Markers of Susceptibility to Bias Due to Participant SelectionAssess Rates for Diseases Known Not to Be Affected by the ExposureIntegrated Assessment of Potential for Bias in Cohort StudiesExercise: Assessment of Bias Due to Selection in Cohort Studies8. Selection Bias in Case-Control StudiesSynopsisLearning ObjectivesControl SelectionParticipant Selection in Case-Control and Cohort StudiesSelection of Controls from the Source PopulationCoherence of Cases and ControlsEvaluation of Selection Bias in Case-Control StudiesTemporal Coherence of Cases and ControlsDiscretionary Health Care of Cases and ControlsCompare Exposure Prevalence in Controls to an External PopulationDetermine Whether Exposure Prevalence Varies as Expected Among ControlsExamine Markers of Potential Selection Bias in Relation to Measures of AssociationAdjust Measures of Association for Known Sources of Non- ComparabilityDetermine Whether Established Associations Can Be ConfirmedIntegrated Assessment of Potential for Selection Bias in Case-Control StudiesExercise: Assessing Selection Bias in Case-Control Studies9. Bias Due to Loss of Study ParticipantsSynopsisLearning ObjectivesConceptual Framework for Examining Bias Due to Loss of Study ParticipantsEvaluation of Bias Due to Loss of Study ParticipantsCharacterize NonparticipantsConsider Gradient of Difficulty in RecruitmentStratify Study Base by Markers of ParticipationImpute Information for NonparticipantsIntegrated Assessment of Potential for Bias Due to Loss of Study ParticipantsExercise: Examining Implications of Non-Participation10. Measurement and Classification of ExposureSynopsisLearning ObjectivesIntroductionIdeal Versus Operational Measures of ExposureBiologically Relevant ExposureTemporally Relevant ExposureOptimal Level of Exposure AggregationComparison of Optimal to Operational Measures of ExposureDoes Exposure Misclassification Differ by Disease Status?DefinitionsMechanisms of Differential Exposure MisclassificationEvaluation of Exposure MisclassificationCompare Routine Measure to Superior MeasuresExamine Multiple Indicators of ExposureExamine Subsets of the Population with Differing Exposure Data QualityEvaluate Known Predictors of ExposureEvaluate Known Consequences of ExposureExamine Dose-Response GradientsEvaluate Whether Exposure Misclassification Differs by Disease StatusIdentification of Subgroups with Nondifferential Exposure MisclassificationIntegrated Assessment of Bias Due to Exposure MisclassificationExercise: Assessing the Presence and Impact of ExposureMisclassification11. Measurement and Classification of DiseaseSynopsisLearning ObjectivesFramework for Evaluating Disease MisclassificationSources of Disease MisclassificationImpact of Differential and Nondifferential Disease MisclassificationEvaluation of Disease MisclassificationVerify Diagnostic Accuracy for Subset of Study ParticipantsExamine Results Across Levels of Diagnostic CertaintyEvaluate Alternate Methods of Disease GroupingDetermine Whether Misclassification is Differential by Exposure StatusCreate Subgroups with Accurate Ascertainment or Non-DifferentialUnderascertainmentRestrict Inference to Disease Outcome That Can Be Ascertained AccuratelyIntegrated Assessment of Potential for Bias Due to Disease MisclassificationExercise: Assessing the Presence and Impact of Disease Misclassification12. Random ErrorSynopsisLearning ObjectivesNature of Random VariationSequential Approach to Considering Random and Systematic ErrorSpecial Considerations in Evaluating Random Error in Observational StudiesStatistical Significance TestingInterpretation of Confidence IntervalsMultiple Comparisons and Related IssuesIntegrated Assessment of Random ErrorExercise: Assessing Random Error13. Integration of Evidence Across StudiesSynopsisLearning ObjectivesIntroductionSystematic Evidence ReviewsData Pooling and Comparative AnalysesMeta-AnalysisInterpreting Consistency and Inconsistency Among StudiesInconsistent FindingsConsistent FindingsEvolution of Epidemiologic ResearchIntegrated Assessment from Combining Evidence Across StudiesExercise: Interpreting Evidence from a Collection of Studies14. Characterization and Communication of ConclusionsSynopsisLearning ObjectivesPresenting Clear, Objective, and Informed ConclusionsApplications of EpidemiologyIntegration of Epidemiologic Evidence with Other InformationIdentification of Key ConcernsControversy over InterpretationThe Case Against Algorithms for Interpreting Epidemiologic EvidenceExercise: Communicating Summary Assessment of Epidemiologic Evidence
