You are a budding epidemiology graduate student, spending your summer working for a “famous” epidemiologist.
You are a budding epidemiology graduate student, spending your summer working for a “famous” epidemiologist. While your boss flies off to fancy conferences in resort locations, you spend your evenings pouring over the latest data from a couple of recently-completed investigations…
Use the information from Study #1 to answer questions # 1 – 5
Study #1: A cohort study was completed investigating the association between a traditional Mexican diet versus other diets on masseter (cheek) muscle dysfunction. 1,200 healthy people eating a variety of diets other than a Mexican diet (U.S.) and 950 healthy Mexican-diet-eaters (U.S.) were followed over a 10-year period, and the cumulative incidence of masseter muscle “failure” was noted in each group. (This is a made-up disease)
There were 60 other-diet-eaters and 125 Mexican-diet-eaters whose masseter muscles failed during the study period.
Question 1: Construct a 2 X 2 table for these data. ( exposure & outcome)
Question 2: Calculate the cumulative incidence of masseter failure for the Mexican-diet-eaters and for the other-diet-eaters and interpret.
CI (Mexican diet) =
CI (Other diet) =
Question 3: Calculate the relative risk for masseter failure for Mexican-diet-eaters with other-diet-eaters as the baseline (or, unexposed) and interpret.
RR =
Question 4: Calculate the odds ratio with other-diet-eaters as the baseline (unexposed). In one short sentence, please interpret this value (please be brief and to the point).
OR =
Question 5: Calculate the attributable risk and attributable fraction of masseter failure for Mexican-diet-eating in the Mexican-diet-eaters. What can you tell them about replacing a Mexican diet with other diets?
AR =
AF =
Use the information from Study #2 to answer questions # 6
Study #2:
A matched-pair case-control study was conducted to evaluate whether type of bicycle (e.g. heavy-framed or light-framed) might cause bicycle “roll-overs”. Your boss was concerned that age and gender might be an important exposure for “roll-overs” as well, so he decided to match each case with a similarly aged control of the same gender (i.e. match on age-group and gender). Subsequent to a “roll-over” a matched control was randomly selected from a population of the same gender and age-group bicycle riders who did not roll-over.
Cases and controls were queried as to what kind of bike they rode and the answers are tabulated below:
2 X 2 Table for Matched (on age & gender of rider) Case-Control Study
Control
Heavy-framed Light-framed
Case Heavy-framed 73 34 107
Light-framed 28 45 73
101 79 180
Question 6: Calculate the appropriate measure of the strength of association for these data and interpret. (5 points)
Assume the risk exposure is “Heavy-framed” bicycles
OR matched pairs =
Use the information from Study #3 to answer questions # 7
Study #3:
A cross-sectional study was conducted to evaluate children admitted to an emergency room (ER) in the summer months for whether they were being supervised by their parents/guardians or a non-parent/guardian and whether the ER admission was for an injury or other-emergency.
All cases of children admitted to the ER were evaluated for who was supervising them and whether the admissions were due to injury or non-injury (i.e. illness).
2 X 2 Table for Cross-Sectional Study
Outcome
Injury Non-injury (i.e. illness)
Exposure Non-parent-supervised 120 80 200
Parent-supervised 89 95 184
209 175 384
Question 7a: Calculate the relative risk of summer time child ER admissions being due to injury if the child is being supervised by a non-parent/guardian versus a parent/guardian and interpret.
RR =
Question 7b: Calculate a Population Relative Risk (PRR) for this study and interpret.
Hint: review calculating PRR (slides 1-2 from lecture 11-5)
PRR =
Use the information from Study #4 to answer questions # 8 – 9
Study 4: The last study you evaluate was a cohort study that evaluated the association between chewing one or more package of gum per day and oral tumors. The study was begun in 1999 and ended in 2019 (20 years)
Outcome
Oral Tumor
No
Oral Tumor
Exposure ≥1 pack/day 85 5,500
< 1 pack/day 200 25,000
30,785
Question 8a: In order to provide guidance to policy-makers about potential policy recommendations, you want to investigate the association between chewing one or more packs of gum per day and oral tumors and this impact on public health
Please provide a measure of association between chewing one or more packs of gum per day and oral tumors (i.e. measure of association for a cohort study) and interpret. (5 points)
Hint: review calculating RR (slides4-10 from lecture 8-5)
RR =
Question 8b: To provide more information to policy-makers, you decided to estimate of the effect of chewing one or more packs of gum on gum-chewing populations (pertaining to oral tumors) by calculating AR and AF and interpret
Hint: review calculating incidence (slides 19-21) from lecture 3-2
Hint: review calculating AR (slides 8-11) and AF (slides 12-14 from lecture 11-6)
AR =
AF =
Question 8c: And finally, to provide policy-makers with another important piece of information, you estimate the effect of chewing one or more packs of gum on the entire population (pertaining to oral tumors) by calculating PAR and PAF and interpret
Assumption: your boss started this study 20 years ago and followed the nearly 31,000 people who did not have oral tumors at that time forward to the present time (and the study was miraculously perfect: no loss to follow-up and no switching of exposure groups).
Hint: review calculating PAR (slides 2-6) and PAF (slide 7 from lecture 11-7)
PAR =
PAF =
Question 9: Using the 9 criteria for causation listed in Gordis starting on page 276, please comment (in point form, very briefly) on whether not chewing ≥ 1 pack of gum per day is likely to be causally related to the risk of oral tumors. If there are shortcomings of the present study design (as noted in your list), offer a very brief solution for that problem for future designs.
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