Factors Influencing Adolescent Development
December 29, 2017
Unit III Annotated Bibliography
December 29, 2017

Epidemiology Decoding

QUESTION 1

1. A cohort study of smoking and bladder cancer was conducted in a small island population. There were a total of 1000 people on the island. Four hundred were smokers and 600 were not. Fifty of the smokers developed bladder cancer.  Ten of the non-smokers developed bladder cancer.

· Construct a two by two table using the data given above. Be sure to label the cells and margins.

· Which measure of comparison would you use to describe the relative effect of smoking on the risk of bladder cancer?

· What is the formula for this measure of comparison?

· Calculate this measure of comparison using the given data.

· State the meaning of your answer in one sentence.

QUESTION 2

1. The following table describes hypothetical age-specific rates of heart disease in India and the United States in 2009. Also included are hypothetical age distributions for the two countries and  the entire world population.

Age Group (in years) % of Population in Age Group Heart Disease Rate per 100,000 person-years
  INDIA U.S.A. WORLD INDIA U.S.A.
< 30 60% 30% 50% 50 75
30-55 30% 40% 30% 80 150
> 55 10% 30% 20% 120 400

· Calculate the crude rate of heart disease for each of the two countries. Suppose that you want to compare the rate of heart disease in India to that in the United States. You know that age is an important risk factor for heart disease. Examine the age distribution of each country’s population.

· Should you use the two crude rates to compare the two countries? Why or why not?

· Calculate an age-adjusted rate for heart disease in each country. Use the age distribution of the entire world as your standard.

· Based on these answers, would you say that the age differences between India and the United States account for the entire difference in crude heart disease rates between the two countries?  Why or why not?

QUESTION 3

1. Recently, Australian researchers conducted a study of the relationship between optimism and colon cancer survival. Their hypothesis was that colon cancer patients who had a positive outlook on life would have a lower five-year cumulative incidence of mortality. The study included 100 recently diagnosed colon cancer patients who underwent psychological testing and were found to have a optimistic outlook on life and 100 recently diagnosed colon cancer patients who underwent the same psychological tests and were found to have a pessimistic outlook on life. By the end of five years of follow-up, 50 of the 100 patients with the optimistic outlook and 75 of the 100 patients with the pessimistic outlook had died from colon cancer.

· Set up and fill in the two by two table using these data.

· What is the prevalence of colon cancer in the study population?

· Compare the cumulative incidence of mortality in the optimistic group to the cumulative incidence of mortality in the pessimistic group using a ratio measure of association.

· State in words your interpretation of the result you found in part c.

 

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