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Epidemiology QuestionsQuestion

Question Detail:Epidemiology QuestionsQuestion 1
The following information applies to questions 1-4.In January 2000 you began a one-year study of tuberculosis (TB) in a subsidized housing community in the Lower East Side of New York City. You enrolled 500 residents in your study and checked on their TB status on a monthly basis. At the start of your study on January 1st, you screened all 500 residents. Upon screening, you found that 20 of the healthy residents were immigrants who were vaccinated for TB and so were not at risk. Another 30 residents already had existing cases of TB on January 1st. On February 1st, 5 residents developed TB. On April 1st, 5 more residents developed TB. On June 1st, 10 healthy residents moved away from New York City were lost to follow-up. On July 1st, 10 of the residents who had existing TB on January 1st died from their disease. The study ended on December 31, 2000. Assume that once a person gets TB, they have it for the duration of the study, and assume that all remaining residents stayed healthy and were not lost to follow-up.What was the prevalence of TB in the screened community on January 1st?Answer50/500, or 10%30/500, or 6%20/450, or 4.4%30/450, or 6.7%Question 2What was the prevalence of TB on June 30th?Answer10/450, or 2.2%10/500, or 2%40/500, or 8%40/490, or 8.2%Question 3What was the cumulative incidence of TB over the year?Answer10/450, or 2.2%40/500, or 8%10/480, or 2.1%40/450, or 8.9%Question 4What was the case-fatality rate among residents with TB over the course of the year?Answer10/500, or 1.02%10/40, or 25%10/30, or 33%10/450, or 2.2%Question 5The purpose of double blinding in clinical trials is to:AnswerReduce error that results from how the outcome is assessedReduce error that results from subject’s participation in the trialReduce error that results from assignment to study conditionsThe 1st and 3rd answers onlyAll of the aboveQuestion 6An analysis that includes all subjects who were randomized to the treatment and comparison groups, regardless of whether they received or completed their assigned study protocol.AnswerRun-in periodEfficacy analysisComparabilityIntent-to-treat analysisQuestion 7The ideal comparison group in a cohort studyAnswerIs as similar as possible to the exposed group with respect to factors other than the exposure that could influence the development of disease.Would, if possible, consist of exactly the same individuals in the exposed group had they not been exposed.Both of the aboveNeither of the aboveQuestion 8Noncompliance in an experimental study biases the results toward the null.AnswerTrueFalseQuestion 9The following information applies to questions 9 and 10.A study was done to determine whether the amount of money spent on soft drinks was related to mortality from diabetes. The investigators collected data on per capita (average per person) soft drink consumption in 10 U.S. states and examined its relationship to mortality rates from diabetes in those 10 states. In order to calculate per capita sales, they gathered annual data on soft drink sales from commerce records and then divided these figures by the state’s population from the most recent Census. The mortality data were gathered from the vital records department in each state. Here are the data that they collected.U.S. StateAnnual Per Capita Soft Drink SalesAnnual Diabetes Mortality Rate (per 100,000 population)Massachusetts$150207New York$300353Florida$500688Alabama$700801Alaska$5075California$500605Nevada$200310Idaho$250325Ohio$400454Arkansas$350405What type of study is this?AnswerEcologicCross-sectionalCase-controlCohortQuestion 10Based on these findings, the investigators concluded that there was an association between consumption of soft drinks and mortality from diabetes. A potential flaw in this reasoning is that it is not known if the people who died from diabetes consumed soft drinks.AnswerTrueFalseQuestion 11Each activity below has a specific purpose in epidemiological research. Match each activity in the first column with its corresponding purpose in the second column by selecting the correct letter. Each activity has only one correct answer.Answer-A.B.C.D.Conduct screeningRead Answer Items for Question 11-A.B.C.D.Blind/mask study staffRead Answer Items for Question 11-A.B.C.D.Include a large sample sizeRead Answer Items for Question 11-A.B.C.D.Use matchingRead Answer Items for Question 11AnswerDecreases confoundingDecreases interviewer biasIncreases statistical stabilityImproves survivalQuestion 12The following information applies to questions 12-14.An article was recently published on the relationship between caffeine consumption during pregnancy and low birth weight. The article was based on the results of a case-control study. As you know, caffeine is present in a wide variety of beverages, foods, and medications, including coffee, tea, and colas. The following statements have been taken from the introduction and results sections of the article. Select the Hill’s guideline that best describes each statement.Caffeine exposure during pregnancy could have a harmful effect because caffeine interferes with cell division, metabolism, and growth.AnswerConsistencyDose-responseTemporalityBiological plausibilityStrength of the associationQuestion 13Four prior case-control studies and three cohort studies of caffeine intake during pregnancy have shown an increased risk of low-birth-weight infants among women who consumed high amounts of caffeine.AnswerConsistencyDose-responseTemporalityBiological plausibilityStrength of the associationQuestion 14The risk of low birth weight increased as the caffeine consumption increased. Compared to women who did not consume any caffeine during pregnancy, the relative risk of giving birth to a low-birth-weight infant was 1.4 for women who had low caffeine consumption, 2.3 for women who had moderate caffeine consumption, and 5.6 for women who had high caffeine consumption.AnswerConsistencyDose-responseTemporalityBiological plausibilityStrength of the associationQuestion 15Use the following information to answer questions 15-17.Suppose that your company has just developed a new screening test for a disease and you are in charge of testing its validity and feasibility. You decide to evaluate the test on 1000 individuals and compare the results of the new test to the gold standard. Below are the results.Gold Standard Determination of DiseaseTotalResults of Screening TestYesNoPositive2857292Negative15693708Total3007001,000Calculate the sensitivity of the new screening test. Answer285/300 = 95%285/1000 = 28.5%15/300 = 5%693/700 = 99%Question 16What is the correct interpretation of the results of a calculation of specificity?AnswerThe test is able to correctly classify as positive 95% of those with the disease.The test is able to correctly classify as negative 99% of those without the disease.Of those who screened positive, 97.6% of them actually have the disease.Of those who screened negative, 97.9% of them actually do not have the disease.Question 17What would happen to the predictive value positive if this test were administered in a population with a disease prevalence of 1% instead of 30%? (Note that the sensitivity and specificity of the test remain the same.)AnswerPredictive value positive would remain the same.Predictive value positive would increase.Predictive value positive would decrease.Question 18The following information applies to questions 18 through 20.The association between cellular telephone use and the risk of brain cancer was investigated in a case-control study. The study included 475 cases and 400 controls and the following results were seen:CasesControlsCellular Phone UserYes270200470No205200405Total475400475Calculate the odds ratio based on these data.AnswerOR = (200*205) / (270*200) = 0.76OR = (270/475) / (200/400) = 1.33OR = (270/470) / (200/405) = 1.80OR = (270*200) / (200*205) = 1.32Question 19The p-value for this odds ratio is 0.06. What is the correct interpretation of this p-value?AnswerGiven that the null hypothesis is not true, the chances of seeing these results, or more extreme results, is 6%Given that the null hypothesis is true, there is a 6% chance that users of cell phones will develop brain cancerGiven that the null hypothesis is true, the chances of seeing these results, or more extreme results, is 6%Given that the null hypothesis is not true, there is no association between cell phone use and brain cancer.Question 20Gender was considered a potential confounder and effect measure modifier in this study. The data were stratified into males and females in order to assess these issues.MalesFemalesCasesControlsCasesControlsCellular Phone UserYes242150Yes2850No10050No105150Stratum-specific OR = 0.8Stratum-specific OR = 0.8Choose the correct statement about gender as a confounder and/or effect modifier in this study. AnswerGender is a confounder and effect modifier.Gender is not a confounder but is an effect modifierGender is a confounder but not an effect modifierGender is neither a confounder nor an effect modifier

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