Health Risks of Ionizing Radiation: - Clark University

and controls are matched according to potentially
confounding variables (age, smoking, gender, etc.).
The cases and controls are assessed to determine if
a certain risk factor like radiation is more prominent
among the cases.
Cohort studies look at things the other way
around, comparing populations based on known
exposures rather than known disease outcomes. In a
typical cohort study design an exposed population is
followed through time to see if they develop diseases
more than a non-exposed population. Cohort studies
can either be done retrospectively (looking back in
time) or prospectively (following a population into
the future).
The result of any of these epidemiological
designs is an expression of the rate of a disease in the
study population compared to some reference value,
and this could be matched controls from within the
study, national disease rates, or some other standard.
This is discussed more below.
1.7 Risk terminology
Researchers use different terms when quantifying
risk depending on study design and their own
goals and preferences. Some of these concepts can
be applied to either disease incidence or disease
mortality. The following list scratches the surface of
an epidemiologist’s glossary but should be sufficient
for our purposes:
Relative Risk (RR). The relative risk is a ratio
of disease rates in exposed and unexposed groups
without units of dimension. If, for example, the
cancer rate in an exposed population is 5 out of
10,000, and in the unexposed population the rate
is 2 out of 10,000, the relative risk would be 5
divided by 2, or 2.5. Relative risks are sometimes
given in percentages. An author may explain the
above example by saying that the RR equals 250%,
meaning that the risk in the study population is
250% of the risk in the unexposed population. A
Rate Ratio is typically equivalent to a relative risk,
particularly at low disease rates. Both incidence and
mortality can be described with a relative risk.
Excess Relative Risk (ERR) is simply the
relative risk minus 1. This number refers to the
additional risk of a disease that can be associated
with an exposure. In the example given above the
ERR would be equal to the RR (2.5) minus one, or
Introduction 9
1.5. This unit becomes more important in describing
dose-response relationships, described below.
Odds Ratio (OR). An odds ratio compares the
odds of a disease among an exposed population to the
odds of a disease among an unexposed population.
“The odds” in this case means the number of times
an event happens versus the number of times it does
not happen. In the example given above the odds
of an exposed person getting cancer are 5/9,995 =
0.00050025, because 5 out of the 10,000 had cancer
and 9,995 did not. The odds of an unexposed person
getting cancer are 2/9,998, or 0.00020004. In order
to find the odds ratio, you would divide the odds of
the exposed person by the odds of the unexposed
person. The odds ratio in this example would be
2.50075. For rare outcomes like cancer the odds
ratio is very similar to the relative risk. Odds ratios
can sometimes be difficult to interpret intuitively
although they can be mathematically beneficial.
Odds ratios are often used in case-control studies
where disease prevalence is unknown among the
general population.
Excess Absolute Risk (EAR). The excess
absolute risk describes the exact number of cases of
a disease that we should expect, without reference
to the background rate. In our example we have 5
cancer deaths, which are two more than we expected.
The EAR in this case is 2/10,000 or 0.0002. EAR,
like ERR, is often used to describe dose-response
relationships (discussed below).
Standardized Incidence Ratio (SIR) is a ratio
of the number of cases of a disease observed in the
study population to the number of cases that would
be expected in the study population. The expected
number is calculated by recreating a hypothetical
study population out of a standard reference group.
This standardization helps to eliminate differences
between the study population and the reference
group. For example, if our study population were
comprised of 70 children and 8 adults we would not
want to base our expected number on the average
US. Instead we would calculate the US incidence
among children and the US incidence among adults
and combine these rates in proportions that are
appropriate for our study group.
Standardized Mortality Ratio (SMR) is
similar to SIR but measures mortality rather than
incidence. Studies using SMRs and SIRs are usually
ecologic studies and are rarely done with enough