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Centers for Disease Control and Prevention Global Health Odyssey Museum Tom Harkin Global Communications Center June 7-11, 2010

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Title: Centers for Disease Control and Prevention Global Health Odyssey Museum Tom Harkin Global Communications Center June 7-11, 2010


1
Day 3
Teach Epidemiology
Professional Development Workshop
Centers for Disease Control and PreventionGlobal
Health Odyssey MuseumTom Harkin Global
Communications Center
June 7-11, 2010
2
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3
Teach Epidemiology
Teach Epidemiology
4
Time Check 815 AM
5
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6
Teach Epidemiology
Teach Epidemiology
7
Teachers Team-Teaching Teachers (TTTT)
Authentic Assessments) (AA) - (1 Group)   Team
leads other workshop participants in the creation
and administration of survey questions about a
health-risk behavior and its distribution in
terms of person, place, and time.
After doing so, workshop participants count the
frequency of the health-risk behavior, calculate
the overall prevalence of the behavior, identify
patterns of the behavior in terms of person,
place, and time, and formulate hypotheses that
might explain those patterns.
TTTTT 10 AA
Teach Epidemiology
8
Teachers Team-Teaching Teachers (TTTT)
Infuse Epidemiology into an Existing Lesson about
Something Else (ASE) (1 Group)   Team leads
other workshop participants in portions of
selected existing lessons about something else

into which epidemiology has been infused.
Authentic Assessments) (AA) - (1 Group)   Team
leads other workshop participants in the creation
and administration of survey questions about a
health-risk behavior and its distribution in
terms of person, place, and time. After doing
so, workshop participants count the frequency of
the health-risk behavior, calculate the overall
prevalence of the behavior, identify patterns of
the behavior in terms of person, place, and time,
and formulate hypotheses that might explain those
patterns.
Teach Epidemiology
9
Enduring Epidemiological Understandings
Teach Epidemiology
10
Epi Grades 6-12
Metacognition
They can then use that ability to think about
their own thinking to grasp
how other people might learn.
They know what
has to come first,
and they can
distinguish between foundational concepts
and elaborations or
illustrations of those ideas. They realize
where people are likely to face
difficulties developing
their own comprehension,
and
they can use that understanding
to
simplify and clarify complex topics for others,
tell the right story, or raise a powerfully
provocative question. Ken Bain, What the Best
College Teachers Do
Teach Epidemiology
11
Enduring Epidemiological Understandings
Teach Epidemiology
12
Time Check 1015 AM
13
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14
Teach Epidemiology
Teach Epidemiology
15
Time Check 1030 AM
16
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17
Teach Epidemiology
Teach Epidemiology
18
Enduring Epidemiological Understandings
they can distinguish between foundational
concepts and
elaborations or illustrations of those ideas.
Ken Bain, What the Best College Teachers Do
Teach Epidemiology
19
Time Check 1100 AM
20
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21
Teach Epidemiology
Teach Epidemiology
22
Back to EU 2 and 3
  • Why study patterns of disease? Why is a
    description of the person, place, and time
    elements of a disease distribution important?

23
Epidemiologic Studies
  • Descriptive epidemiology
  • Describes patterns of disease
  • Suggests hypotheses about relationships between
    exposures and health-related conditions
  • Analytic epidemiology
  • Tests hypotheses
  • Evaluates relationships
  • Always in a search for causality
  • Knowing causation helps us to prevent and treat
    disease and promote health

24
Making Group Comparisons and Identifying
Associations
4. A hypothesis can be tested by comparing the
frequency of disease in selected groups of people
with and without an exposure to determine if the
exposure and the disease are associated. 5. When
an exposure is hypothesized to have a beneficial
effect, studies can be designed in which a group
of people is intentionally exposed to the
hypothesized cause and compared to a group that
is not exposed. 6. When an exposure is
hypothesized to have a detrimental effect, it is
not ethical to intentionally expose a group of
people. In these circumstances, studies can be
designed that observe groups of free-living
people with and without the exposure.
25
  • Boys are more likely than girls to want to go to
    this field trip.
  • What are we comparing?
  • Proportion of girls who will want to go on the
    trip to proportion of boys who will want to go on
    the trip.
  • What is the causal inference?
  • Gender ? Wanting to attend the field trip
  • This teaching epi thingit will work better for
    Ms. Smiths kids than mine.
  • What are we comparing?
  • Proportion of Smiths students who will engage
    with epidemiology to proportion of my students
    who will engage with epidemiology.
  • What is the causal inference?
  • Class ? Engagement with the science of
    epidemiology

26
Heart attacks
  • Descriptive epidemiology showed the following
    patterns
  • Increasing incidence of heart attacks in certain
    Midwestern communities
  • More heart attacks among farmworkers than
    non-farmworkers in those communities
  • More heart attacks among males than among females
  • What is your hypothesis?

27
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • How might you go about evaluating this hypothesis?

28
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using an
  • Ecologic study

29
Ecologic study of pesticide exposure and MI
  • Exposure is pesticide
  • Measured as proportion of land area devoted to
    wheat
  • Outcome is MI
  • Measured as a rate per 100,000
  • Plot data on a graph
  • What might you expect to see?

30
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31
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32
Ecologic Study
  • Key element
  • Group-level estimates
  • Quantify relationships
  • Graphical displays
  • Correlation coefficient
  • Advantages
  • Study group-level variables, e.g. policies, laws,
    community socioeconomic status
  • Use existing data sources
  • Use fewer resources (time, money, subject burden)
  • Disadvantage
  • Ecologic fallacy

33
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Cross-sectional study

34
Cross-sectional study of pesticide exposure and MI
  • Exposure is pesticide
  • Measured as pesticide application history
  • Outcome is MI
  • Measured as yes or no
  • Count responses
  • What might you expect to see?

35
Pesticides and MI
MI MI-
Pesticide
Pesticide-
200
36
Pesticides and MI
MI MI-
Pesticide 60 90 150
Pesticide- 10 40 50
70 130 200
So, is pesticide usage associated with MI?
37
Pesticides and MI
MI MI-
Pesticide 60 90 150
Pesticide- 10 40 50
70 130 200
What is the prevalence of MI? What is the
prevalence of MI among pesticide users? What is
the prevalence of MI among non-users?
38
Pesticides and MI
MI MI-
Pesticide 60 90 150
Pesticide- 10 40 50
70 130 200
What is the prevalence of MI? 70/200
35 What is the prevalence of MI among pesticide
users? 60/150 40 What is the prevalence of
MI among non-users? 10/50 20
39
Cross-sectional Study
  • Key element
  • Snapshot of one point in time
  • Quantify association
  • Prevalence ratio
  • Advantages
  • Individual data
  • Quick, cheap
  • Assess prevalence of a trait in the population
  • Disadvantages
  • Difficult to assess temporality because measure E
    and D simultaneously
  • Inefficient for E or D that are rare
  • Inefficient for D that are rapidly fatal or of
    short duration

40
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Case-control study

41
Case-control study of pesticide exposure and MI
  • Exposure is pesticide
  • Measured as pesticide application history
  • Outcome is MI
  • Measured as yes or no
  • Want to ensure that you have enough cases to do
    your study, so select for those with MI
  • Find those without MI
  • Ask them about exposures to pesticides
  • What might you expect to see?

42
Pesticides and MI
MI MI-
Pesticide
Pesticide-
100 100 200
43
Pesticides and MI
MI MI-
Pesticide 60 10 70
Pesticide- 40 90 130
100 100 200
What is the prevalence of MI?
44
Case-control Study
  • Odds probability an event will
    occur/probability that event will not occur
  • Odds of exposure in cases
  • probability of being exposed if one is a
    case/probability one was not exposed if one is a
    case
  • What is odds of exposure in controls?
  • probability of being exposed if one is a
    control/probability one was not exposed if one is
    a control
  • What is Odds Ratio?

45
Pesticides and MI
MI MI-
Pesticide 60 10 70
Pesticide- 40 90 130
100 100 200
What is the odds of exposure among the
cases? What is the odds of exposure among the
controls? What is the OR?
46
Pesticides and MI
MI MI-
Pesticide 60 10 70
Pesticide- 40 90 130
100 100 200
What is the odds of exposure among the cases?
(60/100)/(40/100) 60/40 1.5 What is the odds
of exposure among the controls? (10/90)
.11 What is the OR? 13.5
47
Case-control Study
  • Key elements
  • Compare individuals selected on the basis of
    disease status
  • Classic epidemiologic study design
  • Quantify association
  • Odds Ratio
  • Advantages
  • Can be less expensive and time-consuming than
    follow-up studies
  • Efficient for rare diseases
  • Disadvantages
  • May be resource-intensive because of need to
    screen so many
  • Difficult to assess temporality
  • Recall bias

48
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Cohort study

49
Cohort study of pesticide exposure and MI
  • Exposure is pesticide
  • Measured as pesticide application history
  • Outcome is MI
  • Measured as yes or no
  • Want to ensure that you have enough exposed
    persons to do your study, so select for those
    with pesticide exposure
  • Find those without pesticide exposure
  • Follow them up over time to ascertain MI status
  • What might you expect to see?

50
Pesticides and MI
MI MI-
Pesticide 100
Pesticide- 100
200
51
Pesticides and MI
MI MI-
Pesticide 70 30 100
Pesticide- 35 65 100
105 95 200
What is the incidence of MI among the pesticide
users? What is the incidence of MI among the
non-users? What is the risk ratio?
52
Pesticides and MI
MI MI-
Pesticide 70 30 100
Pesticide- 35 65 100
105 95 200
What is the incidence of MI among the pesticide
users? 70 What is the incidence of MI among
the non-users? 35 What is the risk ratio? 2.0
53
Cohort Study
  • Key element
  • Select based on exposure status and follow-up
    over time
  • Quantify association
  • Relative risk (risk ratio)
  • Advantages
  • Avoids the confusion about temporality
  • Ideal for rare exposures
  • Disadvantages
  • May have to screen many to get exposed group
  • Large, time-consuming, expensive especially if
    disease is relatively rare and/or slow to develop
  • Attrition may result in selection bias
  • Inefficient for rare diseases

54
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Randomized controlled trial

55
RCT study of pesticide exposure and MI
  • Exposure is pesticide
  • Measured as pesticide exposure
  • Outcome is MI
  • Measured as yes or no
  • Want to ensure maximal control over study
    parameters, so you decide who gets exposed and
    who does not
  • Follow up over time to ascertain MI status
  • What might you expect to see?

56
Pesticides and MI
MI MI-
Pesticide
Pesticide-
200
57
Pesticides and MI
MI MI-
Pesticide 70 30 100
Pesticide- 35 65 100
105 95 200
What is the incidence of MI among the pesticide
users? What is the incidence of MI among the
non-users? What is the risk ratio?
58
Pesticides and MI
MI MI-
Pesticide 70 30 100
Pesticide- 35 65 100
105 95 200
What is the incidence of MI among the pesticide
users? 70 What is the incidence of MI among
the non-users? 35 What is the risk ratio? 2.0
59
Randomized Controlled Trial
  • Key elements
  • Assign treatments to individuals and follow up to
    ascertain disease status.
  • The researcher controls primary exposure under
    study. Exposures can be treatments (drug,
    surgery) or preventive measures (water
    fluoridation, exercise regimens).
  • Ethical considerations may preclude use of this
    design.
  • Quantify association
  • Relative risk (risk ratio)
  • Advantages
  • Random assignment serves to equate groups
  • Closest to true experiment
  • Disadvantages
  • Expensive and time-consuming.
  • Subjects are often highly selected group because
    the requirements of participants can often be
    extensive.

60
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61
Enduring Understandings
A hypothesis can be tested
by
comparing the frequency of disease
in selected
groups of people with and without an exposure
to determine if the exposure and the
disease are associated.
Comparing Exposed and Unexposed
62
Enduring Understandings
When an exposure is hypothesized to have a
beneficial effect (e.g. vitamin D), studies can
be designed in which a group of people is
intentionally exposed to the hypothesized cause
and compared to a group
that is not exposed.
Intentionally Exposing
63
Enduring Understandings
When an exposure is hypothesized to have a
detrimental effect (HIV, pesticides, EMF), it is
not ethical to intentionally expose a group of
people. In these circumstances, studies can be
designed that observe groups of free-living
people with and without the exposure.
Observing Free-Living People
64
Reasons for associations
  • Confounding
  • Bias
  • Reverse causality
  • Sampling error (chance)
  • Causation

65
  • Osteoporosis risk is higher among women who live
    alone than among women who live with others.

66
Confounding
  • Confounding is an alternate explanation for an
    observed association of interest.

Number of persons in the home
Osteoporosis
Age
67
Confounding
  • Confounding is an alternate explanation for an
    observed association of interest.

Exposure
Outcome
Confounder
68
Confounding in our lives
  • MAP tests measure academic growth over time,
    independent of grade level or age.
  • Age- and gender-specific growth charts
  • Age-adjusted rates
  • Rates of lung cancer adjusted for smoking

69
Controlling confounding
  • Study design phase
  • Matching
  • Restriction
  • Random assignment
  • Study analysis phase
  • Stratification
  • Statistical adjustment

70
Reasons for associations
  • Confounding
  • Bias
  • Reverse causality
  • Sampling error (chance)
  • Causation

71
Bias
  • Errors are mistakes that are
  • randomly distributed
  • not expected to impact the MA
  • less modifiable
  • Biases are mistakes that are
  • not randomly distributed
  • may impact the MA
  • more modifiable

72
Types of bias
  • Selection bias
  • The process for selecting/keeping subjects causes
    mistakes
  • Information bias
  • The process for collecting information from the
    subjects causes mistakes

73
Selection bias
  • People who are working are likely to be healthier
    than non-workers
  • People who participate in a study may be
    different from people who do not
  • People who drop out of a study may be different
    from those who stay in the study
  • Hospital controls may not represent the source
    population for the cases

74
Information bias
  • Misclassification, e.g. non-exposed as exposed or
    cases as controls
  • Cases are more likely than controls to recall
    past exposures
  • Interviewers probe cases more than controls
    (exposed more than unexposed)

75
Birth defects and diet
  • In a study of birth defects, mothers of children
    with and without infantile cataracts are asked
    about dietary habits during pregnancy.

76
Pesticides and cancer mortality
  • In a study of the relationship between home
    pesticide use and cancer mortality, controls are
    asked about pesticide use and family members are
    asked about their loved ones usage patterns.

77
Minimize bias
  • Can only be done in the planning and
    implementation phase
  • Standardized processes for data collection
  • Masking
  • Clear, comprehensive case definitions
  • Incentives for participation/retention

78
Reasons for associations
  • Confounding
  • Bias
  • Reverse causality
  • Sampling error (chance)
  • Causation

79
Reverse causality
  • Suspected disease actually precedes suspected
    cause
  • Pre-clinical disease ? Exposure ? Disease
  • For example Memory deficits ? Reading cessation
    ? Alzheimers
  • Cross-sectional study
  • For example Sexual activity/Marijuana

80
Minimize effect of reverse causality
  • Done in the planning and implementation phase of
    a study
  • Pick study designs in which exposure is measured
    before disease onset
  • Assess disease status with as much accuracy as
    possible

81
Reasons for associations
  • Confounding
  • Bias
  • Reverse causality
  • Sampling error (chance)
  • Causation

82
Sampling error/chance
  • E and D are associated in a sample, but not in
    the population from which the sample was drawn.

83
Minimize sampling error (chance)
  • Random Selection

84
Time Check 1130 AM
85
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86
Teach Epidemiology
Teach Epidemiology
87
Time Check 1230 PM
88
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89
Teach Epidemiology
Teach Epidemiology
90
Time Check 145 PM
91
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92
Teach Epidemiology
Teach Epidemiology
93
Bupe
94
Enduring Epidemiological Understandings
Knowledge that is connected and organized, and
conditionalized to specify the context in
which it is applicable.
National Research Council , Learning and
Understanding
Teach Epidemiology
95
Associated
Association Found
Between Coffee and Pancreatic Cancer
Teach Epidemiology
96
Associated
Tied
Related
Associated
Linked
What do we mean when we say that there is an
association between two things?
Things that are associatedare linked in some way

that makes them turn up together.
Teach Epidemiology
97
Associated
Things that are associated are linked in some way

that makes them turn up together.
Teach Epidemiology
98
Associated
Suicide Higher in Areas with Guns
Smoking Linked to Youth Eating Disorders
Family Meals Are Good for
Mental Health
Study Concludes Movies Influence
Youth Smoking
Study Links Iron
Deficiency to Math
Scores
Lack of High School Diploma Tied to
US Death Rate
Study Links Spanking
to Aggression
Depressed Teens More Likely to Smoke
Snacks Key to Kids TV- Linked Obesity China
Study
Breakfast Each Day May Keep Colds Away
Pollution Linked with Birth Defects in US Study
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
Teach Epidemiology
99
Descriptive Epidemiology
Epidemiologic studies that are concerned with
characterizing the amount and distribution of
health and disease
within a population.
Teach Epidemiology
100
Analytical Epidemiology
Epidemiologic studies that are concerned with
determinants of disease and the reasons for
relatively high or low frequencies of disease in
specific population subgroups.
Teach Epidemiology
101
Hypothesis


Hypothesis
An unproven idea, based on observation or
reasoning, that can be supported or refuted
through investigation An educated guess
Teach Epidemiology
102
Making Group Comparisons and Identifying
Associations
Hypothesis
Buprenorphine will stop heroin addicts from using
heroin.
Teach Epidemiology
103
Making Group Comparisons and Identifying
Associations
Trial 1
104
Making Group Comparisons and Identifying
Associations
Trial 1
Population
500 Heroin
Addicts
Sample 100
Heroin Addicts
105
Making Group Comparisons and Identifying
Associations
Trial 1
Population
500 Heroin
Addicts
Sample 100
Heroin Addicts
21 Heroin Addicts Tested Negative for Heroin
106
Making Group Comparisons and Identifying
Associations
Trial 1
Tested Positive for Heroin
Tested Negative for Heroin
Total
Bupe
100
21
79
Teach Epidemiology
107
Making Group Comparisons and Identifying
Associations
Lord Kelvin
When you can measure what you are speaking about,
and express it in
numbers, you know something about it.
But when you cannot measure it, when you cannot
express it in numbers, your knowledge is of a
meager and unsatisfactory kind.
Teach Epidemiology
108
Making Group Comparisons and Identifying
Associations
Risk
A measure of how often an
outcome occurs in a defined population in a
defined period of time. It consists of a
numerator and a denominator.
Denominator
The numerator is the number of people in the
population or sample who experienced the outcome
and the denominator is the total number of people
in the population or sample.
Population / Sample
Teach Epidemiology
109
Making Group Comparisons and Identifying
Associations
Risk
Numerator
21 tested negative for heroin
Denominator
100 study subjects
the risk of a negative heroin test was 21 /
100 in a 10-week period
Teach Epidemiology
110
Making Group Comparisons and Identifying
Associations
Risk / Rate
A measure of how often an outcome occurs
in a defined group of people
in a
defined period of time.
The likelihood of an outcome occurring.
Teach Epidemiology
111
Making Group Comparisons and Identifying
Associations
Calculating Risk
Trial 1
Tested Positive for Heroin
Tested Negative for Heroin
Risk of Negative
Heroin Test
Total
21
Bupe
100
21
79
100
Teach Epidemiology
112
Making Group Comparisons and Identifying
Associations
Inference
Process of predicting from what is observed in a
sample to what is true for the entire population.
Teach Epidemiology
113
Making Group Comparisons and Identifying
Associations
Inference
Trial 1
Probe
Tested Positive for Heroin
Tested Negative for Heroin
Risk of Negative
Heroin Test
Total
21
Bupe
100
21
79
100
What does this tell you about the hypothesis?
Buprenorphine will stop heroin addicts from using
heroin.
Teach Epidemiology
114
Making Group Comparisons and Identifying
Associations
Control Group
People who participate in a trial,
but do not get the
treatment.
People whose results
are compared to the
group that was treated.
Teach Epidemiology
115
Making Group Comparisons and Identifying
Associations
Control Group
Tested Positive for Heroin
Tested Negative for Heroin
Risk of Negative
Heroin Test
Total
21
Bupe
100
79
21
100
Extend and label the table to include a control
group.
Teach Epidemiology
116
Making Group Comparisons and Identifying
Associations
Control Group
Tested Positive for Heroin
Tested Negative for Heroin
Risk of Negative
Heroin Test
Total
21
Bupe
100
79
21
100
No Bupe
100
Making Group Comparisons
Teach Epidemiology
117
Making Group Comparisons and Identifying
Associations
Tested Positive for Heroin
Tested Negative for Heroin
Risk of Negative
Heroin Test
Total
a
b
21
Bupe
100
79
21
100
c
d
No Bupe
100
Making Group Comparisons
Teach Epidemiology
118
Making Group Comparisons and Identifying
Associations
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
21
Bupe
100
79
21
100
No Bupe
100
Teach Epidemiology
119
Making Group Comparisons and Identifying
Associations
Contingency Table
A cross-classification of data
where categories of one
variable
are presented in rows and
categories of another variable
are
presented in columns The simplest contingency
table is the 2x2 table.
Teach Epidemiology
120
Making Group Comparisons and Identifying
Associations
Trial 1
Population
500 Heroin
Addicts
Sample 100
Heroin Addicts
21 Heroin Addicts Tested
Negative for Heroin
121
Making Group Comparisons and Identifying
Associations
Trial 2
Teach Epidemiology
122
Making Group Comparisons and Identifying
Associations
Teach Epidemiology
123
Making Group Comparisons and Identifying
Associations
Trial 2
Probe
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
124
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
125
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population
Teach Epidemiology
126
Making Group Comparisons and Identifying
Associations
Lord Kelvin
When you can measure what you are speaking about,
and express it in numbers, you know something
about it.
But when you cannot measure it, when you cannot
express it in numbers, your knowledge is of a
meager and unsatisfactory kind.
Teach Epidemiology
127
Making Group Comparisons and Identifying
Associations
Ratio
The value obtained
by dividing one
quantity by another
Teach Epidemiology
128
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
1
No Bupe
Ratio The value obtained by dividing one
quantity by another Risk Ratio The ratio of two
risks
Teach Epidemiology
129
Making Group Comparisons and Identifying
Associations
Create a formula
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
1
No Bupe
Ratio The value obtained by dividing one
quantity by another Risk Ratio The ratio of two
risks
Teach Epidemiology
130
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
1
No Bupe
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
131
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
1
No Bupe
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population
The inference here is that there is no effect of
Buprenorphine
Teach Epidemiology
132
Making Group Comparisons and Identifying
Associations
Trial 3
Teach Epidemiology
133
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
134
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
135
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population
Teach Epidemiology
136
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
0.34
No Bupe
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
137
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
0.34
No Bupe
0.34
The heroin addicts who received Bupe were ___
times as likely to test negative for heroin as
those who did not receive Bupe.
Teach Epidemiology
138
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
0.34
No Bupe
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population.
Teach Epidemiology
139
Making Group Comparisons and Identifying
Associations
Trial 4
Teach Epidemiology
140
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
141
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
142
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
3.5
No Bupe
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
143
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
3.5
No Bupe
3.5
The heroin addicts who received Bupe were ___
times as likely to test negative for heroin as
those who did not receive Bupe.
Teach Epidemiology
144
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Relative Risk
Total
Bupe
a b c d
3.5
No Bupe
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population.
Teach Epidemiology
145
Making Group Comparisons and Identifying
Associations
Trial 1
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Total
Bupe
Nothing
What do the results tell us about the hypothesis
that Buprenorphine will stop heroin addicts from
using heroin?
Teach Epidemiology
146
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Trial 3
Trial 4
Teach Epidemiology
147
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Total
Bupe
Nothing
Trial 3
Trial 4
Teach Epidemiology
148
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
No Bupe
Nothing
Trial 3
Trial 4
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
No Bupe
No Bupe
Teach Epidemiology
149
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
No Bupe
Nothing
Trial 3
Trial 4
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
No Bupe
No Bupe
Teach Epidemiology
150
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
1
No Bupe
Bupe is not associated
with having a
negative test for heroin.
Nothing
Trial 3
Trial 4
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
No Bupe
No Bupe
Teach Epidemiology
151
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
1
No Bupe
Bupe is not associated
with having a
negative test for heroin.
Nothing
Trial 3
Trial 4
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
.34
No Bupe
No Bupe
Bupe is associated with
having a positive
test for heroin!
Teach Epidemiology
152
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
1
No Bupe
Bupe is not associated
with having a
negative test for heroin.
Nothing
Trial 3
Trial 4
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
.34
3.5
No Bupe
No Bupe
Bupe is associated with
having a positive
test for heroin!
Bupe is associated with
having a negative
test for heroin.
Teach Epidemiology
153
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Total
Total
Bupe
Bupe
1
Nothing
No Bupe
Bupe is not associated
with having a
negative test for heroin.
Nothing
Trial 3
Trial 4
Compared to what?
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Risk of Negative
Heroin Test
Tested Negative for Heroin
Tested Positive for Heroin
Relative Risk
Relative Risk
Total
Total
Bupe
Bupe
.34
3.5
No Bupe
No Bupe
Bupe is associated with
having a positive
test for heroin!
Bupe is associated with
having a negative
test for heroin.
Teach Epidemiology
154
Making Group Comparisons and Identifying
Associations
Handout
Teach Epidemiology
155
Enduring Epidemiological Understandings
Knowledge that is connected and organized, and
conditionalized to specify the context in
which it is applicable.
National Research Council , Learning and
Understanding
Teach Epidemiology
156
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157
Course Objectives
By the conclusion of the course, the student will
have begun to develop an understanding of the
fundamental epidemiological concepts identified
below
3.
A hypothesis can be tested by comparing the
frequency of disease in selected groups of people
with and without an exposure to determine if the
exposure and the disease are associated. When an
exposure is hypothesized to have a beneficial
effect, studies can be designed in which a group
of people is intentionally exposed to the
hypothesized cause and compared to a group that
is not exposed. When an exposure is hypothesized
to have a detrimental effect, it is not ethical
to intentionally expose a group of people. In
these circumstances, studies can be designed that
observe groups of free-living people with and
without the exposure.
158
In the News
Suicide Higher in Areas with Guns
Smoking Linked to Youth Eating Disorders
Family Meals Are Good for
Mental Health
Study Concludes Movies Influence
Youth Smoking
Study Links Iron
Deficiency to Math
Scores
Lack of High School Diploma Tied to
US Death Rate
Study Links Spanking
to Aggression
Depressed Teens More Likely to Smoke
Snacks Key to Kids TV- Linked Obesity China
Study
Breakfast Each Day May Keep Colds Away
Pollution Linked with Birth Defects in US Study
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
159
2 x 2 Table
Suicide Higher in Areas with Guns
Total
a
b
d
c
160
2 x 2 Table
Suicide Higher in Areas with Guns
No Suicide
Total
Suicide
a
b
Areas with Guns
a
b
d
c
Areas without Guns
People who are exposed
161
2 x 2 Table
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
Total
a
b
d
c
162
2 x 2 Table
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
Drink Smoke
No Drink Smoke
Total
R-Rated Movies
a
b
d
c
No R-Rated
Movies
163
2 x 2 Table
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
Drink Smoke
No Drink Smoke
Total
a
R-Rated Movies
a
b
d
c
No R-Rated
Movies
People who are exposed and have the outcome
164
2 x 2 Table
Family Meals Are Good for Mental Health
Total
a
b
d
c
165
2 x 2 Table
Family Meals Are Good for Mental Health
No Mental Health
Mental Health
Total
Family Meals
a
b
d
c
No Family
Meals
166
2 x 2 Table
Family Meals Are Good for Mental Health
No Mental Health
Mental Health
Total
Family Meals
a
b
d
c
d
No Family
Meals
People who are not exposed and do not have the
outcome
167
2 x 2 Table
Study Links Iron Deficiency to Math Scores
Total
a
b
d
c
168
2 x 2 Table
Study Links Iron Deficiency to Math Scores
Poor Math Scores
Good Math Scores
Total
Iron Deficiency
a
b
d
c
No Iron
Deficiency
169
2 x 2 Table
Study Links Iron Deficiency to Math Scores
Poor Math Scores
Good Math Scores
Total
Iron Deficiency
a
b
d
c
d
No Iron
Deficiency
People who do not have the outcome and are not
exposed
170
2 x 2 Table
Pollution Linked with Birth Defects in US Study
Total
a
b
d
c
171
2 x 2 Table
Pollution Linked with Birth Defects in US Study
No Birth Defects
Birth Defects
Total
Pollution
a
b
d
c
No Pollution
172
2 x 2 Table
Pollution Linked with Birth Defects in US Study
No Birth Defects
Birth Defects
Total
Pollution
a
b
d
c
d
c
No Pollution
People who are not exposed
173
2 x 2 Table
Depressed Teens More Likely to Smoke
Total
a
b
d
c
174
2 x 2 Table
Depressed Teens More Likely to Smoke
No Smoke
Smoke
Total
b
Depression
a
b
d
c
d
No Depression
People who do not have the outcome
175
2 x 2 Table
Smoking Linked to Youth Eating Disorders
Total
a
b
d
c
176
2 x 2 Table
Smoking Linked to Youth Eating Disorders
No Eating Disorders
Eating Disorders
Total
Smoke
a
b
d
c
No Smoke
177
2 x 2 Table
Smoking Linked to Youth Eating Disorders
No Eating Disorders
Eating Disorders
Total
b
Smoke
a
b
d
c
No Smoke
People who are exposed and do not have the outcome
178
2 x 2 Table
Study Links Spanking to Aggression
Total
a
b
d
c
179
2 x 2 Table
Study Links Spanking to Aggression
No Aggression
Aggression
Total
a
Spanking
a
b
d
c
c
No Spanking
People who have the outcome
180
2 x 2 Table
Snacks Key to Kids TV-Linked Obesity China
Study
Total
a
b
d
c
181
2 x 2 Table
Snacks Key to Kids TV-Linked Obesity China
Study
No Obesity
Obesity
Total
Snacks
a
b
d
c
c
No Snacks
People who are not exposed and have the outcome
182
Time Check 215 PM
183
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184
Teach Epidemiology
Teach Epidemiology
185
Teachers Team-Teaching Teachers (TTTT)
Teach Epidemiology
186
Teachers Team-Teaching Teachers (TTTT)
Teach Existing Epidemiological Lessons (EL) (4
Groups)   Team leads other workshop participants

in a portion of a
selected existing epidemiological lesson.
Teach Epidemiology
187
Teach Epidemiology
Teach Epidemiology
188
Teachers Team-Teaching Teachers (TTTT)
TTTT 11 EL
Teach Epidemiology
189
Teachers Team-Teaching Teachers (TTTT)
TTTT 12 EL
Teach Epidemiology
190
Teachers Team-Teaching Teachers (TTTT)
TTTT 13 EL
Teach Epidemiology
191
Teachers Team-Teaching Teachers (TTTT)
TTTT 14 EL
Teach Epidemiology
192
Teachers Team-Teaching Teachers (TTTT)
View a News Item from an Epidemiological
Perspective (NI) (4 Groups)   Team leads other
workshop participants

in the analysis of a news item from
an epidemiological perspective.
Teach Epidemiology
193
Teach Epidemiology
Teach Epidemiology
194
Teachers Team-Teaching Teachers (TTTT)
TTTT 15 NI
Teach Epidemiology
195
Teachers Team-Teaching Teachers (TTTT)
TTTT 16 NI
Teach Epidemiology
196
Teachers Team-Teaching Teachers (TTTT)
TTTT 17 NI
Teach Epidemiology
197
Teachers Team-Teaching Teachers (TTTT)
TTTT 18 NI
Teach Epidemiology
198
Teach Epidemiology
Teach Epidemiology
199
Teachers Team-Teaching Teachers (TTTT)
TTTTT 19 ASE
Infuse Epidemiology into an Existing Lesson about
Something Else (ASE) (1 Group)   Team leads
other workshop participants

in portions of selected
existing lessons about something else

into which epidemiology has been infused.
Teach Epidemiology
200
Teach Epidemiology
Teach Epidemiology
201
Teachers Team-Teaching Teachers (TTTT)
TTTTT 20 AA
Authentic Assessments) (AA) - (1 Group)   Team
leads other workshop participants, in teams of 5,

in carrying out
cross-sectional studies among workshop
participants. Workshop participants will
create and ask questions that will allow them to
test a hypothesis about a health-related exposure
and outcome, request informed consent,
tabulate data in a 2x2
table, calculate prevalence rates of the outcome
for those with and those without the exposure,
calculate a prevalence ratio, explain whether or
not the prevalence ratio supports the hypothesis
(shows or does not show an association), and
identify possible explanations for why the
association was or was not found.
Teach Epidemiology
202
Teachers Team-Teaching Teachers (TTTT)
  • TTTT Rules
  • Teach epidemiology.
  • As a team, create a 20-minute lesson during which
    you model a way to teach epidemiology for your
    workshop colleagues.
  • Make sure your lesson develops a deeper
    understanding of an enduring epidemiological
    understanding.
  • Assume the foundational epidemiological knowledge
    from the workshop.
  • Try to get us to uncover the enduring
    epidemiological understanding.
  • End each lesson by placing it in the context of
    the appropriate enduring epidemiological
    understanding.
  • Contribute to creating a professional
    community that discusses new teacher materials
    and strategies and that supports the risk taking
    and struggle entailed in transforming practice.
  • Teach epidemiology.

Teach Epidemiology
203
Time Check 245 PM
204
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205
Teach Epidemiology
Teach Epidemiology
206
Time Check 300 PM
207
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208
Teach Epidemiology
Teach Epidemiology
209
Tours
Teach Epidemiology
210
Tours
Broadcast Studios
Teach Epidemiology
211
Tours
Emergency Operation Center
Teach Epidemiology
212
Time Check 400 PM
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