Hello and welcome to epidemiology. Let me
ask you a question, what does risk mean to you?
What's a risky behavior? If I start smoking,
what's my risk of getting lung cancer? If
you're a doctor and a patient asks you, how
do I decrease my risk of getting heart disease
by changing certain behaviors, how do you
compute that? How do you turn that into a
measurable concept? Well today we're going
to talk about risk and how to measure risk.
You're going to learn how to set up a contingency
table, that's a kind way that we use to display
our numbers to compute risk. You'll also learn
how to calculate what we call relative risk
and also how to calculate relative risk reduction.
And also you'll calculate absolute risk reduction,
all measurements of risk.
So, analytical epidemiology is about discovering
and describing relationships between risk
factors and outcomes. Risk factors, remember
a risk factor is an independent variable that
may change the probability of getting a certain
outcome. So we say that smoking is a risk
factor for lung cancer. So sometimes we don't
know if a behavior or a risk factor is causal
or not, we don't know if it actually causes
an outcome. The best we can say is that it's
associated with an outcome; smoking is associated
with lung cancer. We assume that it cause
lung cancer. It almost doesn't matter if it's
causal or not, we can control the outcome
by controlling the behavior or the risk factor.
So today we're going to explore what this
association means. If I say that this risk
factor is associated with an outcome, what
do you think that means? Well it means that
there is a statistical relationship between
the exposure and the outcome. We say that
there is a numerical statistical relationship
between whether or not you smoke and whether
or not you get lung cancer. So in order to