Question 1)
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?
Answer
- 50/500, or 10%
- 30/500, or 6%
- 20/450, or 4.4%
- 30/450, or 6.7%
Question 2)
What was the prevalence of TB on June 30th?
Answer
- 10/450, or 2.2%
- 10/500, or 2%
- 40/500, or 8%
- 40/490, or 8.2%
Question 3
What was the cumulative incidence of TB over the year?
Answer
- 10/450, or 2.2%
- 40/500, or 8%
- 10/480, or 2.1%
- 40/450, or 8.9%
Question 4
What was the case-fatality rate among residents with TB over the course of the year?
Answer
- 10/500, or 1.02%
- 10/40, or 25%
- 10/30, or 33%
- 10/450, or 2.2%
Question 5
The purpose of double blinding in clinical trials is to:
Answer
- Reduce error that results from how the outcome is assessed
- Reduce error that results from subject's participation in the trial
- Reduce error that results from assignment to study conditions
- The 1st and 3rd answers only
- All of the above
Question 6
An 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.
Answer
- Run-in period
- Efficacy analysis
- Comparability
- Intent-to-treat analysis
Question 7
The ideal comparison group in a cohort study
- Is 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 above
- Neither of the above
Question 8
Noncompliance in an experimental study biases the results toward the null.
Answer
Question 9
The 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. State Annual Per Capita Soft Drink Sales Annual Diabetes Mortality Rate (per 100,000 population)
Massachusetts $150 207
New York $300 353
Florida $500 688
Alabama $700 801
Alaska $50 75
California $500 605
Nevada $200 310
Idaho $250 325
Ohio $400 454
Arkansas $350 405
What type of study is this?
- Ecologic
- Cross-sectional
- Case-control
- Cohort
Question 10
Based 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.
Question 11
The difference between primary and secondary prevention of disease is:
Answer
- Primary prevention means control of causal factors, while secondary prevention means control of symptoms.
- Primary prevention means control of acute disease, while secondary prevention means control of chronic disease.
- Primary prevention means control of causal factors, while secondary prevention means early detection and treatment of disease.
- Primary prevention means increasing resistance to disease, while secondary prevention means decreasing exposure to disease.
Question 12
The 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.
Answer
- Consistency
- Dose-response
- Temporality
- Biological plausibility
- Strength of the association
Question 13
Four 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.
Answer
- Consistency
- Dose-response
- Temporality
- Biological plausibility
- Strength of the association
Question 14
The 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.
Answer
- Consistency
- Dose-response
- Temporality
- Biological plausibility
- Strength of the association
Question 15
Use 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 Disease Total
Results of Screening Test Yes No
Positive 285 7 292
Negative 15 693 708
Total 300 700 1,000
Calculate the sensitivity of the new screening test.
Answer
- 285/300 = 95%
- 285/1000 = 28.5%
- 15/300 = 5%
- 693/700 = 99%
Question 16
What is the correct interpretation of the results of a calculation of specificity?
- The 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 17
What 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.)
Answer
- Predictive value positive would remain the same.
- Predictive value positive would increase.
- Predictive value positive would decrease.
Question 18
The 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:
Cases Controls
Cellular Phone User Yes 270 200 470
No 205 200 405
Total 475 400 475
Calculate the odds ratio based on these data.
Answer
- OR = (200*205) / (270*200) = 0.76
- OR = (270/475) / (200/400) = 1.33
- OR = (270/470) / (200/405) = 1.80
- OR = (270*200) / (200*205) = 1.32
Question 19
The p-value for this odds ratio is 0.06. What is the correct interpretation of this p-value?
Answer
- Given 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 cancer
- Given 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 20
Gender 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.
Males Females
Cases Controls Cases Controls
Cellular Phone User Yes 242 150 Yes 28 50
No 100 50 No 105 150
Stratum-specific OR = 0.8 Stratum-specific OR = 0.8
Choose the correct statement about gender as a confounder and/or effect modifier in this study.Answer
- Gender is a confounder and effect modifier.
- Gender is not a confounder but is an effect modifier
- Gender is a confounder but not an effect modifier
- Gender is neither a confounder nor an effect modifier
Question 21
The uses of epidemiology include:
Answer
- Understanding how a risk factor is related to a health outcome
- Developing etiologic hypotheses
- Evaluation of health services
- All of the above
Question 22
John Snow:
Answer
- Was the father of modern biostatistics.
- Established postulates for transmission of infectious disease.
- Was an early epidemiologist who used natural experiments.
- Argued that the environment was associated with diseases such as malaria.
Question 23
A dynamic population is one that adds new members through immigration and births and loses members through emigration and deaths.Answer
Question 24
Descriptive epidemiology characterizes the amount and distribution of disease within a population to enable the epidemiologist to:
Answer
- Test hypotheses regarding causality of disease
- Generate testable hypotheses regarding etiology
- Evaluate trends in health and disease within a population
- The 2nd and 3rd answers only
- All of the above
Question 25
When interpreting public health data from different sources, it is important to consider:
Answer
- The amount of missing data
- The population covered
- Any changes in data collection methods
- The 2nd and 3rd answers only
- The 1st and 3rd answers only
- All of the above
Question 26
A study collects information on occupation and blood pressure among current Mass Turnpike toll booth collectors and current Turnpike office workers. What type of study is this?
Answer
- Case report
- Case series
- Ecological study
- Cross-sectional study
Question 27
27)The Health Professionals Cohort Study began in 2005 in order to evaluate a series of hypotheses about men's health relating nutritional factors to the incidence of serious illnesses such as cancer, heart disease, and other vascular diseases. Every two years, members of the study will receive surveys with questions about diseases and health-related topics like smoking, physical activity, and medications taken. The surveys that ask detailed dietary information will be administered in four-year intervals. What kind of cohort study is this?
Answer
- Retrospective
- Prospective
- Ambidirectional
Question 28
Selection bias is most likely to occur in which type of study?
Answer
- Prospective cohort studies
- Retrospective cohort studies
- Case-control studies
- Both the 2nd and 3rd answers
Question 29
Interviewer/recording bias can occur in
Answer
- Case-control studies only
- Cohort studies only
- Experimental studies only
- Any type of epidemiologic study
Question 30
- Differential misclassification can bias study results in which direction?Answer
- Toward the null
- Away from the null
- Either toward or away from the null
Question 31
Which of the following is true about the P value?
Answer
- Indicates the probability of seeing the observed result, and results more extreme, by chance alone (given that the null hypothesis is true)
- Indicates the probability that the null hypothesis is true
- Rules out the role of bias and/or confounding
- Indicates that the results observed are of medical or public health significance
Question 32
When assessing the results of a study, what are the possible explanations for the observed results?
Answer
- The observed results may be due to chance (i.e., random error)
- The observed results may be true
- The observed results may be due to bias
- The observed results may be due to confounding
- All of the above
Question 33
Which of the following statements is/are true about the 95% confidence interval?
Answer
- If you did the study 100 times and got 100 point estimates and 100 confidence intervals, in 95 of the 100 results, the true point estimate would lie within the given interval.
- The range within which the true measure of effect lies with a stated probability, or a certain degree of assurance (95%).
- The confidence interval is calculated around the point estimate and quantifies the variability around the point estimate.
- The 1st and 2nd answers only
- All of the above
Question 34
Compensating research participants is a necessary part of the research protocol, ensures participation, and enhances the quality of the data collected.
Question 35
A cohort study of liver cancer among alcoholics was conducted. Incidence rates of liver cancer among alcoholic men are compared to a group of non-alcoholic men. Gender is a confounder in this study.
Answer
Question 36
Which of the following should be included in an informed consent process?
Answer
- An explanation of the research study
- A statement that a participant may withdraw at any time from the study
- An acknowledgement of possible risks to the participant
- Information on whom to contact for answers to questions about the research
- The 1st, 2nd, and 3rd answers only
- All of the above
Question 37
A study of the risk of pulmonary hypertension among women who take diet drugs to lose weight was undertaken. The crude relative risk of pulmonary hypertension comparing diet drug users to nonusers is 17.0, and the age-adjusted relative risk is 5.0. Age is a confounder in this study.
Answer
Question 38
Town A and Town B are both located in Massachusetts. Both towns have approximately 100,000 residents, and their own water supply. Fluoride is added to the water supply of Town A; nothing is added to the water supply of Town B. The decision to add fluoride to Town A's water, and not Town B's, was made using a random number table. Both towns are monitored and compared with regards to the occurrence of new cases of dental caries (cavities) over a 5 year period. What type of study is this?
Answer
- Individual Preventive Randomized Controlled Trial
- Community Preventive Randomized Controlled Trial
- Individual Therapeutic Randomized Controlled Trial
- Community Therapeutic Randomized Controlled Trial
Question 39
Subjects with a confirmed diagnosis of carpal tunnel syndrome were compared to a comparable group without carpal tunnel syndrome and both groups were asked about their prior occupational and recreational exposures, including hours per week of computer use. This is an example of which study design?
Answer
- Case-control study
- Prospective cohort study
- Retrospective Cohort Study
- Cross-sectional study
Question 40:
The difference between primary and secondary prevention of disease is:Answer
Primary prevention means control of causal factors, while secondary prevention means control of symptoms.
Primary prevention means control of acute disease, while secondary prevention means control of chronic disease.
Primary prevention means control of causal factors, while secondary prevention means early detection and treatment of disease.
Primary prevention means increasing resistance to disease, while secondary prevention means decreasing exposure to disease.