Comparison of mortality rates due to cancer of the uterus in users and non-users of supplemental estrogen revealed the following mortality rates per 100,000: Age Users of estrogen Non-users of estrogen 45-54 3.0 1.0 55-70 17.0 6.0 A valid conclusion derived from the above data concerning mortality among estrogen users is: (A) The mortality rates for cancer of the uterus are higher in estrogen users than non-users in both age groups studied A causal relationship cannot be demonstrated based on the results of a single study; the mortality rate is higher in users for both age groups. References: Friis and Sellers; pp. 110-112, 132-134 Hebel and McCarter; pp. 17-22 Kleinbaum et al.; pp.

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In a large case-control study of pancreatic cancer, 20% of the cases were found to be diabetic at the time of diagnosis, compared to 5% of a control group (matched by age, sex, ethnic group, and several other characteristics) that was examined for diabetes at the same time that the cases were diagnosed. The authors concluded that diabetes played a causal role in the development of pancreatic cancer. This conclusion: (A) Is correct (B) May be incorrect because there is no control or comparison group (C) May be incorrect because of failure to establish the time sequence between the onset of diabetes and pancreatic cancer (D) May be incorrect because of less complete ascertainment of diabetes in pancreatic cancer cases (E) May be incorrect because of more complete ascertainment of pancreatic cancer in non-diabetic people. In a large case-control study of pancreatic cancer, 20% of the cases were found to be diabetic at the time of diagnosis, compared to 5% of a control group (matched by age, sex, ethnic group, and several other characteristics) that was examined for diabetes at the same time that the cases were diagnosed. The authors concluded that diabetes played a causal role in the development of pancreatic cancer. This conclusion: (C) May be incorrect because of failure to establish the time sequence between the onset of diabetes and pancreatic cancer Case control studies cannot demonstrate the temporal relationship between an exposure and a disease.

This is a requirement for concluding causality. References: Kleinbaum et al.; pp.

22-24 Hebel and McCarter; pp. 140-141 Friis and Sellers; p. In a population of 5,000 people, 100 ate spinach contaminated with E. Coli (O157:H7) and became ill. Of the ill, 15 died. What was the case fatality rate? (C) 150 per 1,000 The numerator for case fatality is 'number of individuals dying during a specified period of time from the disease of interest' and the denominator is 'number of persons with the disease of interest.'

In this question, the numerator is 15 and the denominator is 100. 15/100 = 0.15 X 1000 = 150/1000 persons. References: Friis and Sellers; pp. 414-415 Last et al.; p.

24 Hebel and McCarter; p. 20 Kleinbaum et al.; p. A case-control study comparing ovarian cancer cases with community controls found an odds ratio of 2.0 in relation to exposure to radiation.

Which is the correct interpretation of the measure of association? (A) Women exposed to radiation had 2.0 times the risk of ovarian cancer when compared to women not exposed to radiation (B) Women exposed to radiation had 2.0 times the risk of ovarian cancer when compared to women without ovarian cancer (C) Ovarian cancer cases had 2.0 times the odds of exposure to radiation when compared to controls (D) Ovarian cancer cases had 2.0 times the odds of exposure to radiation when compared to women with other cancers. A case-control study comparing ovarian cancer cases with community controls found an odds ratio of 2.0 in relation to exposure to radiation.

Which is the correct interpretation of the measure of association? (C) Ovarian cancer cases had 2.0 times the odds of exposure to radiation when compared to controls. In a case control study, we are comparing the prevalence of exposure given disease status, therefore, we compare the prevalence of radiation among those with cancer to the prevalence of radiation among those without cancer.

We cannot use 'risk' to describe this association because risk implies probability and we are calculating odds. References: Friis and Sellers; pp. 240-241 Last et al.; p.

128 Kleinbaum et al.; pp. Double-blinded (masked) studies are an important way to: (B) Avoid observer and interviewee bias Double masking or blinding a study means that neither the patient nor the individuals involved in evaluating the outcome know the exact exposure status of any individual. This decreases the risk of observer bias because the observer does not know the true exposure. It also decreases the risk of interviewee bias because the participant doesn't know which exposure group he/she is in. References: Friis and Sellers; pp. 304-305 Last et al.; p. 18 Kleinbaum et al.; p.

26 Hebel and McCarter; p. The difference between primary and secondary prevention of disease is: (A) Primary prevention focuses on control of causal factors, while secondary prevention focuses on control of symptoms (B) Primary prevention focuses on control of acute disease, while secondary prevention focuses on control of chronic disease (C) Primary prevention focuses on control of causal factors, while secondary prevention focuses on early detection and treatment of disease (D) Primary prevention focuses on increasing resistance to disease, while secondary prevention focuses on decreasing exposure to disease. The difference between primary and secondary prevention of disease is: (C) Primary prevention focuses on control of causal factors, while secondary prevention focuses on early detection and treatment of disease Primary prevention suggest that the 'incidence' of disease is prevented.

In general, this means that the prevention has decreased the prevalence of risk factors or increased the prevalence of preventive factors thus changing the incidence of disease. In secondary prevention, disease has already occurred and the prevention program is designed to identify disease early so that treatment can be started early. References: Friis and Sellers; p. 80 Last et al.; pp.

141-142 Hebel and McCarter; p. A screening test is used in the same way in two similar populations, but the proportion of false-positive results among those who test positive in population B is higher than that among those who test positive in population A. What is the most likely explanation for this finding? (A) The specificity of the test is higher in population A (B) The specificity of the test is lower in population A (C) The prevalence of disease is higher in population A (D) The prevalence of disease is lower in population A. A screening test is used in the same way in two similar populations, but the proportion of false-positive results among those who test positive in population B is higher than that among those who test positive in population A.

What is the most likely explanation for this finding? (C) The prevalence of disease is higher in population A The number of false positives increases as the prevalence of the outcome of interest decreases. Communities with lower prevalence of outcome will have higher false-positive rates. I community B has higher false- positive rates, then it must have lower prevalence compared to population A. Therefore, population A has a higher prevalence of disease than community B. References: Friis and Sellers; pp. 382-385 Hebel and McCarter; pp.

62-63 Kleinbaum et al.; pp. 152-154 Last et al.; p. The relative risk of dying for smokers compared to non-smokers is: The death rate per 100,000 for lung cancer is 7 among non-smokers and 71 among smokers.

The death rate per 100,000 for coronary thrombosis is 422 among non-smokers and 599 among smokers. The prevalence of smoking in the population is 55%. (A) 9.1 for lung cancer and 0.30 for coronary thrombosis (B) 9.1 for lung cancer and 1.4 for coronary thrombosis (C) 10.1 for lung cancer and 8.4 for coronary thrombosis (D) 10.1 for lung cancer and 1.4 for coronary thrombosis (E) 12.4 for lung cancer and 1.7 for coronary thrombosis. The relative risk of dying for smokers compared to non-smokers is: The death rate per 100,000 for lung cancer is 7 among non-smokers and 71 among smokers.

The death rate per 100,000 for coronary thrombosis is 422 among non-smokers and 599 among smokers. The prevalence of smoking in the population is 55%. (D) 10.1 for lung cancer and 1.4 for coronary thrombosis Prevalence is not relevant to this question - so ignore the prevalence of smoking statement. The relative risk of dying from lung cancer for smokers compared to non-smokers is 71/7 = 10.1. The risk of dying from coronary thrombosis comparing smokers is 599/422 = 1.4. References: Friis and Sellers; p.

276 Kleinbaum et al.; pp. 72-73 Hebel and McCarter; pp.

29, 118 Last et al.; p. Which of the following statements is true about surveillance data?

(D) It can be used to monitor temporal trends in disease Monitoring temporal trends in disease is a primary function of surveillance systems. While surveillance historically, and perhaps more frequently, is conducted for infectious diseases, in recent years it has become increasingly important in monitoring changes in other types of conditions, such as cancer, congenital malformations, asthma, occupational exposures and diseases, and injuries and illness after natural disasters. Reference: Gordis page 54. In a cross-sectional study of peptic ulcer among men and women aged 35 to 59, 70 per 100,000 men and 95 per 100,000 women met the criteria for symptomatic peptic ulcer disease. The inference that in this age group, women are at greater risk of developing peptic ulcer is: (A) Correct (B) Incorrect because of failure to distinguish between incidence and prevalence (C) Incorrect because rates were used to compare males and females (D) Incorrect because of failure to recognize a possible cohort effect (E) Incorrect because there is no comparison or control group. A prevalence study of depression drew a sample of the residents of Houston by visiting all residence in randomly selected census tracts.

A screening test with a sensitivity of 99% and a specificity of 50% was used to identify individuals as 'likely depressed.' The study reported a prevalence of 28%. This prevalence is: (A) A true representation of depression in this population (B) Higher than expected because of the specificity of the screening test (C) Lower than expected because of the specificity of the screening test (D) Higher than expected because of the sensitivity of the test (E) Lower than expected because of the sensitivity of the test. Epidemiology could be defined as the study of distribution, determinants, and control of health-related states or events in the specified population and the application of this study to control health problems. As an epidemiologist, if required to fulfill the 'distribution' and 'determinant' components of this definition, what will this entail?

Public health infrastructure b. Information, behavior, and health skills development c.

Information dissemination to the population at risk d. Frequency, patterns, and causes of health -related events e. Prevention of health -related events. The answer correct is 0 (meaning of epidemiology). Epidemiology refers to the study of the frequency, patterns, causes, and control and prevention of diseases, disabilities, and injuries in the human population. There are two main aspects of epidemiology: (a) distribution-epidemiology evaluates the distribution of health states by age, gender, race, geography, time, etc., and (b) epidemiology seeks to examine the association and causal association between the exposure and the health-related states or events (Last, J.M. Kahi Karta Hoga Woh Mera Intezar Mp3 Song Download there. , A Dictionary of Epidemiology, 3rd ed., 1995; MacMahan, B, & Trichopoulos, D., Epidemiology, Principles & Methods, 2nd ed., 1996, p. In a survey conducted to examine the prevalence of two diseases, X and Y, in a specific population, the investigators found that the prevalence of disease X was higher than the prevalence of disease Y.

If the incidence and seasonal pattern of both diseases are similar, which of these statements are consistent with this observation? Patients die quickly from disease Ybut not diseaseX b. Patients die quickly from diseaseXbut not disease Y c. Patients recover more quickly from disease Ythan from diseaseX d. Patients recover more quickly from diseaseXthan from diseaseY e. The correct answer isE(factors influencing the prevalence of disease).Prevalence proportion does not measure disease onset but the disease status.

Whereas incidence is a measure of risk, prevalence is not because it does not take into account the duration of disease. But prevalence is related to the duration of the disease and incidence of disease. Prevalence = Incidence x Disease duration. The number of people living with a disease (prevalence) will be influenced by the rate at which a new disease develops as well asthe rate at which they are eliminated through cure (prognosis) or death (mortality).

Therefore, the prevalence will increase if incidence increasesand if there is improvement in treatment but not cure, and it will decrease if there is dramatic cure (quick recovery) (Gordis, L., Epidemiology, 3rd ed., 2004, p. 40; Aschengrau, A.,&Seage, G.R., Essentials ofEpidemiology, 2003, pp. The approach to epidemiology can be described as descriptive, which involves the analysis of disease, disability, and injury patterns by person, place, and time. During the summer of 2006, there was an outbreak of bacterial meningitis in Nocity, Illinois. If you are appointed to investigate this epidemic using adescriptive epidemiologic approach, what are the main reasons for describing this outbreak by person, place, and time? To assess the health status of the Nocity population b. To generate a hypothesis about the causal factors (causative pathogen/s) for this epidemic c.

To plan and evaluate the public health programs to manage this epidemic d. A and conly e. All of the above.

The correct answer is A (secondary attack rate). Secondary attack rate yields the index of the spread of a disease within a family, household, dormitory, dwelling unit, etc.

This measure is estimated by Number of new cases in a group - Initial case(s) / Number of susceptible persons in a group - Initial case(s). Substituting: 150 - 100 (each household had one primary case and there were 100 households) /500 - 100 (primary case) x 100 -+ 50/400 x 100 = 12.5% (Mausner, J.,& Kramer,S., Epidemiology-An Introductory Text, 2nd ed., 1985, pp. In the Framingham Heart Study (FHS), the residentsof the state of Massachusetts have been followed since the1950s to identify occurrence (heart disease) and risk factors for heart disease. This study identified high blood pressure, hyperlipidemia, stress, and physical inactivates as risk factors in heart disease. This dynamic cohort now involves the grandchildren of the original cohort. Which of the following study designs represent this study? Case cross-over b.

Ambi-directional cohort c. Retrospective cohort d. Case control e. None of the above.

The correct answer is E(study design). A design that begins with exposure(s) of interest and disease-free subjects and aimed to assess the outcome in the future by following the subjects represents a prospective cohort study. This is not a clinical trial or a broad intervention design because the subjects of the FHS were not assigned but observed. The time relation in a prospective cohort study is present and future (continuing). A case cross-over design uses the previous experience of the cases as a substitute for a control series 88 CPH EXAM QUICK REFERENCE REVIEW to estimate the person-time distribution in the source population.

Ambidirectional cohort isa design tha t is both retrospective and prospective in its observation of the outcome. Retrospective cohort (historical cohort studies) is a design in which the cohorts are identified from recorded information and the time during which they are at risk for disease occurred before the beginning of the study. Simply, retrospective study is conducted by defining the cohort and collecting information, which applies to past time. Case control is a design in which the groups of individuals are defined in terms of whether they have or have not already exper ienced the outcome under consideration, and the exposure is then measured (Elwood, J.M., Critical Appraisal of Epidemiological Studies in Clinical Trials, 2nd ed., 2003, pp. 14-35; Rothman, K.J., Epidemiology, An Introduction, 2002, p.

A study was conducted in which men (15-49 years) with testicular neoplasm and a comparable group of men (15-49 years) without testicular neoplasm were asked about their prior use of steroidal anti-inflammatory drugs. If you assume that the subjects were selected on the basis of diseaseand not exposure, and the risk as a measure of association is not directly estimated but obtained as odds ratio, this is an example of which type of design(s)? Experimenta I b. Observational c. Case control e. Download Game Ultraman Fighting Evolution 3 Untuk Pc there.

Epidemiologic designs are largely observational. Often, the critical issue restricting the conduct of experimental, clinical, or intervention trial is the ethical consideration such asassigning humans to a known carcinogen (e.g., nicotine). Which of the following statements illustrate(s) the distinction between the two designs? Investigator is'blinded' (prevented from knowing the subjects' true exposure status until the end of the study) in an experimental study but not in an observational study b. Investigator controls the subject's outcome in an experimental study but not in an observational study c. Investigator controls the subject's exposure in an experimental study but not in an observational study d.

Experimental studies are conducted with animals; observational studies are conducted with humans e. The correct answer is E (observational versus experimental design). Experimental design if feasible is considered the gold standard compared with observational studies. The active manipulation or assignment of the treatment by the investigator is the hallmark that differentiates experimental designs from observational studies.

Whereas not all experimental designs utilize blindness to minimize bias, blindness is not a feature of observational designs. Neither in observational design nor experimental ones are investigators required to manipulate the outcome. Experimental designs, like observational ones, are conducted in human as well as animal populations (Aschengrau, A.,& Seage, G.R., EssentialsofEpidemiology, 2003, pp.

Confounding is the mixing effect of an extraneous variable in the association between the predictor (independent variable) and outcome (dependent variable). A study was conducted to examine the association between pancreatic cancer and coffee drinking.

If a third variable, cigarette smoking, is assumed to be a confounder in this association, which of the following features will qualify smoking as a confounder in this association? Smoking is associated with coffee drinking in the population that produced the cases b. Smoking is an independent cause or predictor of pancreatic cancer c. Smoking is not an intermediate step in the causal pathway between coffee drinking and pancreatic cancer d. A and conly e. All of the above. The correct answer is E (internal validity of study).

Confounding is derived from Latin 'coniondere', meaning lito pourtogether;' and it indicates the conCHAPTER 2:PRINCIPLESAND METHODSOF EPIDEMIOLOGY 89 fusion of two supposedly causal variables so that part or all of the purported effect of one variable (exposure) is actually due to the other (confounder). Confounding variable is considered an extraneous variable because it competes with the independent variable in explaining the outcome.

In a study conducted to assess whether exposure (A) causesdisease (8),Cis a confounding if (a) C (smoking) is associated with A (coffee drinking) in the population that produced the cases 8 (pancreatic cancer), (b) C(smoking) is an independent cause or predictor of 8 (pancreatic cancer), or (c) C (smoking) is not an intermediate step in the causal pathway between coffee drinking (A) and pancreatic cancer (8) (Hennekens, C.H., & Buring, J.E., Epidemiology in Medicine, 1987, pp. 287-293; Gordis, L., Epidemiology, 3rd ed., 2004, pp. The correct answer is C (study validity-bias). Because men with diabetes mellitus are more heavily monitored compared to men who are not, disease ascertainment may be better in the monitored population and may introduce surveillance bias (monitoring of one population [diseased] more than the other [disease-free]). This bias may lead to erroneous estimation of the effect of the disease in the monitored population, thus inflating the point estimate (RR, OR) (Gordis, L., Epidemiology, 3rd ed., 2004, p.