2023 NR 503 Final Study Guide

2023 NR 503 Final Study Guide (Version-2), Final Exam NR 503 Population Health, Epidemiology & Statistical Principles, Chamberlain. 1. Objectivesof epidemiology a. Understand the aetiologyor cause of adisease (risk factors) b. Find outthe extentthat a disease or health problemaffects a community or population c. Determine the natural history orprognosis d. Evaluateexisting and newlydevelopedpreventativetherapeuticmeasures and modes of healthcare delivery 2. Define, compare, calculate, and interpret Measures ofMorbidity a. Incidence rate: measurement ofthe number of new individuals who contract a disease during a particular period of time i. Calculation:Number of new cases of disease orinjury during specified period DIVIDED BY Size of population at start of period b. Attack rate: Same asrisk,proportion ofindividualsin apopulation (initially freeof disease) who develop the disease within a specified time interval. i. Calculation: Totalnumber of new casesDIVIDEDBY The total population c. Prevalence: measurement of all individuals affected by the disease at aparticular time i. Calculation:Number of new cases of disease orinjury during specified period DIVIDED BY Time each person was observed, totaled for all persons d. These rates are used to measure disease occurrence and make comparisons between population groups. They are commonlyusedmeasuresthat help our understanding of the distribution of disease in a given population. 3. Understand why incidence data are importantformeasuring risk. a. Incidence isimportantformeasuring risk because ittells you the rate at which new people are contracting the disease 4. Define, compare, calculate, andinterpret Measures ofMortality a. Mortality: a measure of the frequency of occurrence of death in a defined population during a specified interval. Morbidity and mortality measures are often the samemathematically; it'sjust amatter of what you choose tomeasure, illness or death. i. Calculation:Deaths occurring during a given time period DIVIDED BY Size of the population amongwhich the deaths occurred TIMES 10n b. Cause-specific mortality rate: Themortality rate froma specified cause for a population. i. Calculation: The number of deaths attributed to a specific cause DIVIDED BY The size ofthe population at the midpoint of the time period c. Annual mortality rate: The rate of death in a one-year period. i. Calculation:Deaths occurringwithin the one-yearperiod DIVIDED BY Size of population in which the deaths occured d. Case-fatality: the proportion of deaths within a designated population of "cases" (people with a medical condition) overthe course of the disease i. Calculation: he number of deaths from a specified disease over a defined period of time DIVIDED BY The number of individuals diagnosed with the disease during thattime TIMES 100 (final answershould be percentage) e. Proportionate mortality: the proportion of deathsin a particular population overa specified period of time, attributable to different causes i. Calculation: Number of deaths within a population due to a specific disease or causeDIVIDEDBY the total number of deathsin the population during a time period such as a year. 5. AssesstheValidity and ReliabilityofDiagnostic andScreeningTests a. Define, compare andcalculatemeasuresof validity, including sensitivity and specificity. i. Sensitivity identifies the proportion of individuals who truly DO have the disease AND are given a positive test result. I find it helpful to remember: sensiTivity = sensitive to the Truth (i.e. do have disease + do have positive result) 1. We want to know what proportion of individuals who have the disease (a+c) were given a positive testresult(a), therefore… a. Sensitivity = a/(a+c) ii. Specificity identifiesthe proportion ofindividuals who trulyDONOT have the disease AND were given the correct negative test result. I find it helpful to remember: specificity = speciFies the False (i.e. do not have disease and do not have positive test result 1. Thistime we want to know what proportion of people who do not have the disease (b+d) were given the correct negative test result (d), therefore… a. Specificity = d/(b+d). b. Defineand calculate positivepredictive value. i. Positive Predictive Value: The probability thatsubjects with apositive screening test truly have the disease. 1. Calculation: a/(a+c) c. Understand positive predictive value (PPV) and relationshiptodisease prevalence and specificity of a screening test. i. Higherprevalence/specificityrates=higherppvrates 6. Epidemiologic transition a. Phase of development witnessed by a sudden and stark increase in population growth rates brought by improvedfood security and innovationsin publichealth andmedicine,followed by a re-levelingof population growth due to subsequent declines in fertility rates. 7. Studydesigns(case-control, crosssectional,prospective andretrospective cohort, clinical trial) a. Case-control study: An observational study that compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease oroutcome (controls) and looksback retrospectively to comparehowfrequently the exposure to a risk factoris present in each group to determine therelationship between the risk factor and the disease. i. Incidence Density Sampling: the selection of controls is governed by the diagnoses of cases. Every time a case is diagnosed one or more controls are selected. from other members of the cohort who, at that time, do not have the diagnosis. ii. Selection Bias: cases(or controls) are included in (or excluded from) a study because of some characteristic they exhibit which is related to exposure to the risk factor under evaluation b. Cross-Sectionalstudy: Atype of observationalstudy that analyzes data froma population, or a representative subset, at a specific point in time i. Nonresponse Bias: Non-response can result in bias of the measures of outcome. This is a particular problem when the characteristics of nonresponders differ from responders. c. Prospective Cohort study: longitudinal cohort study that follows over time a group ofsimilarindividuals(cohorts)who differ with respectto certain factors understudy,to determine howthese factors affectratesof acertain outcome. i. Information Bias: collectdifferent quality and extent ofinformation from exposed and not exposed groups d. Retrospective Cohort study: A longitudinal study where the participants already have a known disease or outcome. The study looks back into the past to try to determine why the participants have the disease or outcome and when theymay have been exposed i. Recall bias: butsubjectsmay havedifficulty rememberingpast exposures, and their recollection may be biased e. Clinical Trial: any research studythat prospectively assignshuman participants or groups of humans to one or more health-related interventions to evaluate the effects on health outcomes. i. Detectionbias:systematic differencesbetweengroupsinhowoutcomes are determined 8. Causal Inferences a. Identify, define and provide examples for common biases in different epidemiologicalstudies, including selection bias and information bias(e.g.,recall, misclassification, differential classification, etc.). i. Selection Bias: ^ ii. Information Bias: ^ iii. Recall Bias: ^ iv. Misclassification bias:Also refereed to asinformation bias v. Differential Classification bias: happens when the information errors differ between groups. In other words, the biasis different for exposed and non-exposed, orbetween those who have the disease and those do have not. b. Factorsthat could increase or decrease bias. i. Increase: poorly researched or gathered data ii. Decrease: blind studies