kuliah descriptive epid

Descriptive EpidemiologyDr. Arulita Ika Fibriana M.Kes

Epidemiology: DefinitionDynamic study of theDeterminantsOccurrenceDistributionControl PatternOf health and disease in a population

EpidemiologyDescribeshealth eventscause and risk factors of diseaseclinical pattern of diseaseIdentify syndromesIdentify control and/or preventive measures

Epidemiology is a Quantitative DisciplineMeasures of frequencyCounts and ratesMeasures of associationRelative riskOdds ratioStatistical inferencep-valueConfidence limits

Two Broad Types of EpidemiologyDescriptive EpidemiologyExamining the distribution of disease in a population, and observing the basic features of its distribution

Analytic EpidemiologyTesting a hypothesis about the cause of disease by studying how exposures relate to the disease

Kinds of EpidemiologyDescriptive

Analytic

ExperimentalFurther studies to determine the validity of a hypothesis concerning the occurrence of disease.Deliberate manipulation of the cause is predictably followed by an alteration in the effect not due to chanceStudy of the occurrence and distribution of disease

Epidemiologic ActivitiesDescriptive epidemiology person, place & timeDemographic distributionGeographic distributionSeasonal patterns etc.Frequency of disease patternsUseful for:Allocating resourcesPlanning programsHypotheses development

Epidemiologic ActivitiesAnalytic epidemiologyanalysis of the relationship between two itemsExposuresEffects (disease)looking for determinants or possible causes of diseaseuseful forhypothesis testing

Overview of epidemiologic design strategiesDescriptive Populations{Correlational studies} IndividualCase reportCase seriesCross sectional studiesAnalytic studiesObservational Case controlCohortRetrospectiveProspectiveInterventional/ExperimentalRandomized controlled trialField trialClinical trial

Descriptive vs. Analytic Epidemiology DescriptiveUsed when little is known about the disease

Rely on preexisting data

Who, where, when

Illustrates potential associations

AnalyticUsed when insight about various aspects of disease is available

Rely on development of new data

Why

Evaluates the causality of associationsBoth are important!

Descriptive StudiesRelatively inexpensive and less time-consuming than analytic studies, they describe,

Patterns of disease occurrence, in terms of,Who gets sick and/or who does notWhere rates are highest and lowestTemporal patterns of disease

Data provided are useful for,Public health administrators (for allocation of resources)Epidemiologists (first step in risk factor determination)

Objectives of Descriptive EpidemiologyTo evaluate trends in health and disease and allow comparisons among countries and subgroups within countries

To provide a basis for planning, provision and evaluation of services

To identify problems to be studied by analytic methods and to test hypotheses related to those problems

Descriptive EpidemiologyCorrelational studies

Case reports

Case series

Cross sectional studies

Correlational Studies (Ecological Studies)Uses measures that represent characteristics of entire populations It describes outcomes in relation to age, time, utilization of services, or exposures

ADVANTAGESWe can generate hypotheses for case-control studies and environmental studiesWe can target high-risk populations, time-periods, or geographic regions for future studies

Correlational Studies LIMITATIONSBecause data are for groups, we cannot link disease and exposure in individualExample: Percentage of teenagers taking drivers education and fatal teenage car accidents study done by National Safety CouncilWe cannot control for potential confoundersData represent average exposures rather than individual exposures, so we cannot determine a dose-response relationshipCaution must be taken to avoid drawing inappropriate conclusions, or ecological fallacy

Breast Cancer Mortality and Dietary Fat Intake

Case Reports (case series) Report of a single individual or a group of individuals with the same diagnosisAdvantagesWe can aggregate cases from disparate sources to generate hypotheses and describe new syndromes Example: hepatitis, AIDSLimitationsWe cannot test for statistical association because there is no relevant comparison groupBased on individual exposure {may simply be coincidental}

Case report/Case series(contd.)Important interface between clinical medicine & epidemiology

Most common type of studies published in medical journals{1/3rd of all}

e.g. Frisbee finger , break dancing neck

AIDS, 5 cases of P.carinii pneumonia were diagnosed among previously healthy young homosexual males in L.A.

Cross-Sectional Studies (prevalence studies)Measures disease and exposure simultaneously in a well-defined populationAdvantagesThey cut across the general population, not simply those seeking medical careGood for identifying prevalence of common outcomes, such as arthritis, blood pressure or allergiesLimitationsCannot determine whether exposure preceded diseaseIt considers prevalent rather than incident cases, results will be influenced by survival factorsRemember: P = I x D

Cross-Sectional StudiesCan be used as a type of analytic study for testing hypothesis, when;

Current values of exposure variables are unalterable over time

Represents value present at initiation of disease

E.g. eye colour or blood group

If risk factor is subject to alterations by disease, only hypothesis formulation can be done

The epidemiologic approach:Steps to public health actionDESCRIPTIVEWhat (case definition)Who (person)Where (place)When (time)How many (measures)

ANALYTICWhy (Causes)How (Causes)MEASURES Counts Times Rates Risks/Odds Prevalence

METHODS Design Conduct Analysis InterpretationALTERNATIVEEXPLANATIONS Chance Bias Confounding

INFERENCES Epidemiologic CausalACTION Behavioural Clinical Community Environmental

Descriptive EpidemiologyStudy of the occurrence and distribution of diseaseTerms:TimePlacePerson

What are the three categories of descriptive epidemiologic clues?

Person: Who is getting sick? Place: Where is the sickness occurring? Time: When is the sickness occurring?

PPT = person, place, time

TimeSecular

Periodic

Seasonal

Epidemic

Secular Trend

The long-time trend of disease occurrence

Tetanus by year, USA, 1955-2000During 2000, a total of 35 cases of tetanus were reported. The percentage of cases among persons aged 25-59 yearsHas increased in the last decade. Note: A tetanus vaccine was first available in 1933.

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Possible Reasons for Changes in Trends (cont.)RealChanges in age distribution of the populationChanges in survivorshipChanges in incidence of disease resulting fromGenetic factorsEnvironmental factors

Possible Reasons for Changes in TrendsArtifactualErrors in numerator due toChanges in the recognition of diseaseChanges in the rules and procedures for classification of causes of deathChanges in the classification code of causes of deathChanges in accuracy of reporting age at deathErrors in the denominator due to error in the enumeration of the population

Other phrases Cyclic trends ~ recurrent alterations in occurrence , interval or frequency of diseaseSecular cyclicityLevels of immunizationsBuild up of susceptiblese.g. Hep A-7 yr cycle,Measles-2yr cycleShort term cyclicityChickenpox,salmonella(yearly basis)

Periodic Trend

Temporal interruption of the general trend of secular variation

Whooping Cough - Four-monthly admissions, 1954-1973

SeasonalA cyclic variation in disease frequency by time of year & season.

Seasonal fluctuations in,Environmental factorsOccupational activitiesRecreational activities

Seasonal TrendPneumonia-Influenza Deaths By year, 1934-1980

EpidemicAn increase in incidence above the expected in a defined geographic area within a defined time period

Endemic, Epidemic and Pandemic Endemic - The habitual presence (or usual occurrence) of a disease within a given geographic areaEpidemic - The occurrence of an infectious disease clearly in excess of normal expectancy, and generated from a common or propagated sourcePandemic - A worldwide epidemic affecting an exceptionally high proportion of the global populationNumber of Casesof DiseaseTime

Time clusteringTime Place Cluster/disease clusterA group of cases occur close together & have a well aligned distribution pattern {in terms of time and place}

Cluster analysis-used for rare or special disease events.

PersonAgeHobbiesSexPetsOccupationTravelImmunization statusPersonal HabitsUnderlying disease StressMedicationFamily unitNutritional statusSchoolSocioeconomic factorsGeneticsCrowdingReligion

Descriptive epidemiology :Patterns of Disease Occurrence distribution of disease in populations numerator ( event count ) / denominator ( group at risk ) by person : age , race / ethnicity , gender , occupation , education , marital status , genetic marker , sexual preference by place : residence (urban vs. rural) , worksite , social event by time : week , month , year ; sporadic , seasonal , trends --- incubation period ; latency

Sources of informationCensus dataVital statistical recordsEmployment health examinationsClinical records from hospitalsNational figures on food consumption , medications, health events etc

Epidemiologic ( scientific ) Approach

1. Identify a PROBLEM : clinical suspicion ; case series ; review of medical literature 2. Formulate a HYPOTHESIS ( asking the right question ) ; good hypotheses are: Specific, Measurable, and Plausible

3. TEST that HYPOTHESIS ( assumptions vs. type of data )

4. always Question the VALIDITY of the result(s) : Chance ; Bias ; and Causality

Epidemiologic Study: threats to Validity Chance : role of random error in outcome measure(s) ( p - value ; power of the study and the confidence interval ) --- largely determined by sample size

Bias : role of systematic error in outcome measure(s)

Selection bias - subjects not representative Information bias - error(s) in subject data / classification

Confounding - 3rd variable (causal) assoc. w/ both X and Y

What is a hypothesis?

An educated guess

an unproven idea

based on observation or reasoning, that can be proven or disproven through investigation.

What goes into a hypothesis?Characteristics of the diseaseThe illnessEstablished modes of transmission

Distribution In timeBy placeBy person

MeasuresMorbidity: Refers to the presence of disease in a population

Mortality: Refers to the occurrence of death in a population

Methods for MeasuringHow do we determine disease frequency for a population?

Rate = Frequency of defined events in specified population for given time period

Rates allow comparisons between two or more populations of different sizes or of a population over time

Compute Disease RateNumber of persons at risk = 5,595,211

Number of persons with disease = 17,382

Rate = 17,382 persons with heart disease5,595,211 persons= .003107 heart disease / resident / year

RatesRates are usually expressed as integers and decimals for populations at risk during specified periods to make comparisons easier. .003107 heart disease / resident / year x 100,000

= 310.7 heart disease / 100,000 residents / year

Prevalence vs. Incidence

Prevalence is the number of existing cases of disease in the population during a defined period.

Incidence is the number of new cases of disease that develop in the population during a defined period.

IncidenceIncidence rate is a measure of the probability of the event among persons at risk.

Incidence RatesPopulation denominator:

IR = # new cases during time period X Kspecified population at risk

Example (Incidence Rate)During a six-month time period, a total of 53 nosocomial infections were recorded by an infection control nurse at a community hospital. During this time, there were 832 patients with a total of 1,290 patient days. What is the rate of nosocomial infections per 100 patient days?

IR

=

53 X 100

1,290 pt. days

=

4.1 infections per

100 pt. days

Mortality RatesA special type of incidence rate

Number of deaths occurring in a specified population in a given time period

Use of Mortality ratesMortality rates are used to estimate disease frequency whenincidence data are not available, case-fatality rates are high,

goal is to reduce mortality among screened or targeted populations

Mortality Rates: ExamplesCrude mortality: death rate in an entire populationRates can also be calculated for sub-groups within the population

Cause-specific mortality: rate at which deaths occur for a specific cause

Mortality Rates: ExamplesCase-fatality: Rate at which deaths occur from a disease among those with the disease

Maternal mortality: Ratio of death from childbearing for a given time period per number of live births during same time period

Mortality Rates: ExamplesInfant mortality: Rate of death for children less than 1 year per number of live births

Neonatal mortality: Rate of death for children less than 28 days of age per number of live births

PrevalencePrevalence: Existing cases in a specified population during a specified time period (both new and ongoing cases)

Prevalence is a measure of burden of disease or health problem in a population

PrevalencePrevalence: The number of existing cases in the population during a given time period.

PR =# existing cases during time periodpopulation at same point in time

Prevalence rates are often expressed as a percentage.

Factors Influencing Prevalence Increased by:Longer duration of the diseaseProlongation of life of patients without cure

Increase in new cases(increase in incidence)

In-migration of cases

Out-migration of healthy peopleIn-migration of susceptible people

Improved diagnostic facilities (better reporting)Decreased by:Shorter duration of disease

High case-fatality rate from disease

Decrease in new cases (decrease in incidence)

In-migration of healthy people

Out-migration of cases

Improved cure rate of cases

Basic Measures of AssociationRelative risk& odds ratio

We often need to know the relationship between an outcome and certain factors (e.g., age, sex, race, smoking status, etc.)

Used to guide planning and intervention strategies

2 x 2 contingency table for Calculation of Measures of AssociationNote: Exposure is a broad term that represents any factor that may be related to an outcome.

OutcomeExposurePresentAbsentTOTALPresentaba+bAbsentcdc+dTOTALa+cb+da+b+c+d

Relative RiskRatio of the incidence rates between two groupsCan only be calculated from prospective studies (cohort studies)InterpretationRR > 1: Increased risk of outcome among exposed groupRR < 1: Decreased risk, or protective effects, among exposed groupRR = 1: No association between exposure and outcome

Calculation of Relative Risk incidence rate among exposedRR = incidence rate among non-exposed

Calculation of Relative RiskRelative Risk =


Relative Risk Case StudySmoking and low birth weight

Birth WeightSmoking status2500 gTOTALSmoker120240360Non-smoker60580640TOTAL1808201000

Answers to Relative Risk Case Study1. Incidence of LBW among smokers

2. Incidence of LBW among non-smokers

3. Relative risk for having a LBW baby among smokers versus non-smokers

Understanding Probability and OddsProbability: Chance or risk of an event occurring (a proportion)Probability= no. of times an event occurs no. of times an event can occur

Odds: ratio of the probability of an event occurring to the probability of an event not occurring

Odds = P/(1-P)

Calculation of Odds RatioOdds Ratio =


Odds RatioThe odds ratio (OR) is a ratio of two odds.

The OR can be calculated for all three study designsCross-sectional Case-controlCohort.

Various approaches to Odds ratio

Cross product/odds ratio 2 x 2 contingency table (ad/bc)

Prevalence odds ratio cross sectional studies

Exposure odds ratio( odds of exposure in diseased vs. nondiseased)In rare cases or exotic diseases

Disease odds/Rate odds ratio(odds of getting a disease if exposed or unexposed) Cohort & cross sectional

Risk odds ratioCross sectional ,cohort & case control

Odds RatioFor cohort & cross sectional studies: OR is a ratio of the odds of the outcome in exposed persons to the odds of the outcome in non-exposed persons.

For case-control studies: OR is a ratio of the odds of exposure in cases to the odds of exposure in controls.

Provides an estimate of the relative risk when the outcome is rare

Interpretation of Odds RatioOR > 1: Increased odds of exposure among those with outcome

OR < 1: Decreased odds, or protective effects, among those with outcome

OR = 1: No association between exposure and outcome

Keeping the Terms StraightRisk ratio = relative risk

Relative odds = odds ratio

Remember the key is recognizing the terms risk and odds

Appropriateness of MeasuresRemember that the relative risk can only be calculated in prospective studies

Odds ratio can be calculated for any designCohort / prospectiveCase-controlCross-sectional

InferenceThe relative risk and odds ratio provide the magnitude of difference between some factor and an outcome

How do we know if the magnitude is statistically significant?

Confidence IntervalsA confidence interval is a range of values that is likely (e.g., 95%) to contain the true value in the underlying population

The 10 Steps of Outbreak InvestigationPrepare for field workEstablish the existence of an outbreakVerify the diagnosisDefine & identify casesPerform descriptive epidemiologyDevelop hypothesesPerform analytic epidemiologyRefine hypotheses & conduct additional studiesImplement control & prevention measuresCommunicate findings

*****Ecologic correlation of breast cancer mortality and dietary fat intake. Source: Reprinted from Carroll, K.K., Experimental Evidence of Dietary Factors and Hormone-Dependent Cancers, Cancer Research, Vol. 35, p.3379, with permission of Waverly Press, Inc., 1975.

kuliah descriptive epid

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