Epidemiology in Action
Unit III: Measurement and Hypothesis Testing
•
Measuring Disease Frequency
Proportions and rates
•
Comparing Disease Rates
Measures of association used to
test hypotheses
Activity:
Show What You Know
Epidemiology in Action
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Measuring Disease Frequency
Disease
Yes
Disease
No
TOTAL
Exposed
Yes
A
B
A+B
Exposed
No
C
D
C+D
TOTAL
A+C
B+D
A+C+D
In any study, one of the first steps is to gather data. The
chart above is called a Chi Square, and it is the basic
statistic used to test for the significance of any differences
noted in distribution of disease or risk.
Rates needed for epidemiological analysis can be calculated
from this basic table.
Epidemiology in Action
Chi
Square
3
Disease
Yes
Disease
No
TOTAL
Exposed
Yes
A
B
A+B
Exposed
No
C
D
C+D
TOTAL
A+C
B+D
A+C+D
A = the # who are exposed and have the disease
B=the number who are exposed and do not have the disease
C=the number who are not exposed and have the disease
D=the number of individuals who are not exposed and don’t have the disease
A+B+C+D= the total number in the population being studied
A+B=the total number exposed
C+D=the total number not exposed
A=C=the total number with disease
B+D=the total number without disease
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Measuring Disease Frequency
In epidemiology, occurrence of a condition must be
related to the “population at risk”. Common measures
of disease frequency are Prevalence rate and Incidence
rate.
Prevalence rate = the proportion of a
population that are cases at a point in time.
For example, what
PROPORTION
Of the the U.S. population
Has HIV/AIDS right now?
For current HIV/AIDS statistics, check the link below:
Source: LC,/1985,David Lance Goines.
Link: CDC - Division of HIV/AIDS Prevention - Basic Statistics
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Prevalence Rate
Prevalence Rate: the proportion of people in a population who
have a condition/attribute at a specified time.
Prevalence=number of existing cases divided by total population
For example, a hypothetical survey of 2477 persons showed that
310 were heavy smokers. The prevalence of the condition, heavy
smoking, was the number of people who smoke heavily at a
specified time divided by the total population
310 x 100 = 12.5%
2477
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Incidence Rate = rate at which NEW cases occur in a
population during a specified time period.
For example, what is the
Incidence Rate for
new cases of AIDS
in the U.S.
during the last year?
Source: LC,/1985,David Lance Goines.
For current HIV/AIDS statistics, check the link below:
Link: CDC - Division of HIV/AIDS Prevention - Basic Statistics
Epidemiology in Action
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Incidence Rate
rate at which NEW cases occur in a population during a
specified time period. For example, in a hypothetical study
of 2390 college women, 482 drank two or more glasses of
alcohol a day. Twenty-seven of the 482 two-a-day women
drinkers over a specified time period were in car accidents
related to alcohol use. The incidence rate of alcohol-related
car accidents was:
Alcohol-related car accidents
divided by two-a-day drinkers.
27
482 X 100 = 5.6%
Wartenberg, Daniel. (2000). Analytical Methods
Used by Epidemiologists.. FACSNET Reporting
Tools: online, September 27, 2002
Epidemiology in Action
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Measures Used to Show Statistical Correlation:
• Is this disease increasing in incidence?
• Is it more frequent in my area?
• Does its incidence correlate with
some suspected cause?
• Have things changed since we
introduced control measures?
Source;LC/Jerome Henry Rothstein,
1936-38
These are all questions we answer by setting two sets of
rates side by side and comparing them. Three common
measures we use to compare rates are
Relative Risk, Odds Ratio, and Attributable Risk
For information on cancer and the link to nutrition go
to: Epi Research: Nutritional Epidemiology
Epidemiology in Action
Relative Risk
• Calculated to identify differences in disease rates between
exposed and unexposed groups. It is the most common
measure of association used by epidemiologists, because it
can be estimated by a wider range of study designs.
• Relative Risk = Rate of condition among exposed divided
by rate of condition among unexposed
For example, if lung cancer mortality rate among smokers
is 131 per 100,000, and the lung cancer rate among nonsmokers is 11 per 100,000, then
Relative Risk = 131/11=11.9
Relative Risk = 1 means no difference
Relative Risk > 1
shows existence of an
association between exposure and disease,
and there is an association between
smoking and lung cancer.
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Epidemiology in Action
Odds Ratio
• Calculated to identify likelihood of exposure to risk when
comparing two groups, one with and one without disease.
• Odds Ratio = Exposure odds in disease group divided by
exposure odds in non-disease group
If the prevalence of smoking among lung cancer patients is
95 per 100, and the prevalence of smoking among people
without lung cancer is 25 per 100, then
Odds Ratio = 95/25=3.8
Ratio = 1, no association
Ratio > 1, association between
exposure and disease
…..And there is an association
between lung cancer and smoking.
Read about some interesting studies on youth and smoking at:
Epidemiology of Youth Drug Abuse - Research Findings 5/01
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Epidemiology in Action
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Based on the Odds Ratio formula, what is
the Odds Ratio for each disease status in
the famous smoking study?
Smoking and Carcinoma of the Lung
Disease
Status
# of smokers
# of
nonsmokers
Males
Lung cancer
647
(99.7%)
2
(0.3%)
Males
Controls
622
(95.8%)
27
(4.2%)
Females
Lung cancer
41
(46.7%)
19
31.7%)
Females
Controls
28
(46.7%)
32
53.3%
P-value
0.00000064
0.016
Doll R. Bradford, Hill A. Smoking and carcinoma of the lung: preliminary report. British
Medical Journal 1950, 2: 739-748.
Epidemiology of Youth Drug Abuse - Research Findings 5/01
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Attributable Risk
Attributable Risk is the proportion of exposed cases that would
not have gotten the disease if they had not been exposed.
For example: How many
MORE people will get cancer
in a town that has arsenic
contamination due to industrial
pollution?
To find out more about the link between arsenic poisoning
and cancer link to:
UC Berkeley Arsenic Research Program
Source: LC/1951
The Attributable Risk would be useful to know in this case, because
we may then be able to attribute this excess of disease to the risk
factor we’re studying.
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Attributable Risk
If we subtract the rate of disease in a population that does not have
a risk factor from the rate of disease in a population that DOES have
a risk factor, we get the Attributable Risk.
Rate of Disease/ exposed
minus
Rate of Disease/ not exposed
= Attributable Risk.
Source: LC/1951
For example: Let’s say that in a town exposed to arsenic from pollution, we find ten cases of one type of cancer in
2000 people over a 10-year period of observation. The rate, then, is 4 cases per 10,000 people per year.
Comparing the rate in this town to that estimated for the entire United States, we find that this town had an excess
of four cases per 10,000 people per year (5 cases in the town minus one case expected based on national data, per
10,000 persons per year. We may then attribute that excess to arsenic from pollution.
Wartenberg, Daniel. (2000). Analytical Methods Used by Epidemiologists.. FACSNET Reporting Tools: online, September 27, 20
Epidemiology in Action
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Show What You Know: Assignment
STEP I: Using the statistical databases we have become familiar with so
far, find REAL examples of the following things. Then, explain what
that statistic MEANS in terms of the data you are looking at.
Note: you can find them already calculated, or you can construct them by
working backward/forward with a set of data. For all examples, document
correctly where the data comes from.
1.
A chi square. You may find one already in place, or you can
construct one working backward from data you find.
2.
A prevalence rate – calculate, if necessary.
3.
An incidence rate – calculate, if necessary.
4.
An example of relative risk – calculate, if necessary.
5.
An example of odds ratio – calculate, if necessary.
6.
An example of attributable risk – calculate, if necessary.
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Show What You Know: Assignment
STEP II: Create two hypothetical studies, in which you use all of these
statistical measures (you don’t have to use all six in each studyuse each at least once in one or the other of the studies). For your
hypothetical study, identify the following: Target population, type
of study.
Useful sources for data that
measures frequency:
Office of Population Research,
Princeton University
PopNet Population Statistics