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Lecture 3

AS.280.335 Lecture 3: Lecture 3 Notes
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3 Pages
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Fall 2016

Department
AS.280
Course Code
AS.280.335
Professor
Yager, James D.; Bressler, Joseph P.
Lecture
3

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September 8, 2016
Environmental Epidemiology
Epidemiology studies the broad relationship/association between exposure and its
related health outcome (disease)
Exposure-response relationship between frequency/intensity/duration of exposure and
frequency of health outcome is positive (upward sloping) if adverse or negative
(downward sloping) if protective
oI.e. frequency of health outcome is a linear function of frequency of exposure
In order to get exposure-response association, use epidemiologic study designs
oExperimental design (randomized controlled trials)
From the population, you apply exclusion criteria and derive a sample
Randomize subjects in a study to either get a treatment/exposure or not
in an attempt to distribute both measurable and unmeasurable factors
(i.e. age, race/ethnicity, sex, etc.) equally between the two groups
The hope is that this creates identical conditions between the two groups
(unbiased way to look at the effective exposure or treatment)
However, uniformity across all factors is very challenging and randomized
controlled trials are largely unethical (compromise on identical nature of
groups)
oThus, mostly observational design studies
oAll studies measure exposure and outcomes of interest in individuals or
populations
Confounder – a factor not accounted for that dilutes out a true association, whereas
when you adjust for it, you see an association; however, it could also amplify an
association in that when you adjust for it, the association disappears
Example: we could be introducing mercury exposure to ourselves by mercury levels in
fish; however, you also consume beneficial omega-3 fatty acids
oMercury can have an adverse relationship with my myocardial infarction as a
health outcome
oIn contrast, N-3 fatty acids could have a protective effect on myocardial
infarction
oIf you’re not measuring both of these, the you can potentially reach an
incomplete conclusion regarding the relationship between fish consumption and
myocardial function
oOnce n-3 fatty acids as a confounding factor is adjusted for, the odds ratio goes
up, meaning that there is an adverse association
1.0 is the null value for odds ratio – no effect on relationship between
exposure factor and the outcome
Values in brackets are confidence intervals – lower and upper bounds
Lower bound should be above 1
Once you adjust for fatty acids (DHA), you see an effect that is more
pronounced for mercury that you otherwise would not have seen
oLikewise, until you adjust for mercury, you really don’t see the potential
protective effect of DHA from fish consumption in the odds ratio values
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Description
September 8, 2016 Environmental Epidemiology  Epidemiology studies the broad relationship/association between exposure and its related health outcome (disease)  Exposure-response relationship between frequency/intensity/duration of exposure and frequency of health outcome is positive (upward sloping) if adverse or negative (downward sloping) if protective o I.e. frequency of health outcome is a linear function of frequency of exposure  In order to get exposure-response association, use epidemiologic study designs o Experimental design (randomized controlled trials)  From the population, you apply exclusion criteria and derive a sample  Randomize subjects in a study to either get a treatment/exposure or not in an attempt to distribute both measurable and unmeasurable factors (i.e. age, race/ethnicity, sex, etc.) equally between the two groups  The hope is that this creates identical conditions between the two groups (unbiased way to look at the effective exposure or treatment)  However, uniformity across all factors is very challenging and randomized controlled trials are largely unethical (compromise on identical nature of groups) o Thus, mostly observational design studies o All studies measure exposure and outcomes of interest in individuals or populations  Confounder – a factor not accounted for that dilutes out a true association, whereas when you adjust for it, you see an association; however, it could also amplify an association in that when you adjust for it, the association disappears  Example: we could be introducing mercury exposure to ourselves by mercury levels in fish; however, you also consume beneficial omega-3 fatty acids o Mercury can have an adverse relationship with my myocardial infarction as a health outcome o In contrast, N-3 fatty acids could have a protective effect on myocardial infarction o If you’re not measuring both of these, the you can potentially reach an incomplete conclusion regarding the relationship between fish consumption and myocardial function o Once n-3 fatty acids as a confounding factor is adjusted for, the odds ratio goes up, meaning that there is an adverse association  1.0 is the null value for odds ratio – no effect on relationship between exposure factor and the outcome  Values in brackets are confidence intervals – lower and upper bounds  Lower bound should be above 1  Once you adjust for fatty acids (DHA), you see an effect that is more pronounced for mercury that you otherwise would not have seen o Likewise, until you adjust for mercury, you really don’t see the potential protective effect of DHA from fish consumption in the odds ratio values September 8, 2016  Odds ratio decreases below one once mercury is adjusted for indicating a protective direction o Mercury was masking an inverse association between DHA levels and the risk of myocardial infarction that only became evident after the adjustment  The ability to enroll thousands of people into a study, so that you can assure the representativeness of the population of your sample to the general population is tough. o Selection bias occurs because researchers only have enough money to get a small percentage of the general population as its sample – leads to systematic diff
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