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Technology Centre of New Jersey June 30

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Title: Technology Centre of New Jersey June 30


1
Welcome to
2
Teach Epidemiology
Young Epidemiology Scholars
Professional Development Workshop
Technology Centre of New Jersey
June 30
July 2, 2008
2
Time Check 900 AM 15 Minutes
3
YES Professional Development Workshop
Teach Epidemiology
4
Your Teach Epidemiology Stories
Welcome to
Young Epidemiology Scholars Professional
Development Workshop
Technology Centre of New Jersey, June 30 July 2
Teach Epidemiology
Teach Epidemiology
5
Identifying Patterns and Formulating Hypotheses
Enduring Epidemiological Understandings the big
ideas that reside at the heart of epidemiology
and have lasting value outside the
classroom.
they can distinguish between foundational
concepts and
elaborations or illustrations of those ideas.
Ken Bain, What the Best College Teachers Do
Teach Epidemiology
6
Identifying Patterns and Formulating Hypotheses
Enduring Epidemiological Understandings the big
ideas that reside at the heart of epidemiology
and have lasting value outside the
classroom.
they can distinguish between foundational
concepts and
elaborations or illustrations of those ideas.
Ken Bain, What the Best College Teachers Do
Teach Epidemiology
7
Identifying Patterns and Formulating Hypotheses
Enduring Epidemiological Understandings the big
ideas that reside at the heart of epidemiology
and have lasting value outside the
classroom.
they can distinguish between foundational
concepts and
elaborations or illustrations of those ideas.
Ken Bain, What the Best College Teachers Do
Teach Epidemiology
8
Time Check 915 AM 165 Minutes
9
YES Professional Development Workshop
Teach Epidemiology
10
Teach Epidemiology
Young Epidemiology Scholars
Professional Development Workshop
July 1, 2008 Diane Marie M. St. George, PhD
11
Enduring Understandings
  • 4, 5, and 6

12
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?

13
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

14
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/hypotheses?

15
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • How might you go about evaluating this hypothesis?

16
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using an
  • Ecologic study

17
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?

18
(No Transcript)
19
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

20
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Cross-sectional study

21
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?

22
Pesticides and MI
23
Pesticides and MI
So, is pesticide usage associated with MI?
24
Pesticides and MI
What is the prevalence of MI? What is the
prevalence of MI among pesticide users? What is
the prevalence of MI among non-users?
25
Pesticides and MI
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
26
Cross-sectional Study
  • Key elements
  • Snapshot of one point in time
  • Quantify association
  • Prevalence ratio
  • Advantages
  • Individual data
  • Quick, cheap
  • Assess prevalence of a trait in the population
  • Good for estimates of D not routinely brought to
    medical attention but self-diagnosed and treated
    e.g. common cold, dandruff, acne
  • 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

27
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Case-control study

28
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?

29
Pesticides and MI
30
Pesticides and MI
What is the prevalence of MI?
31
Pesticides and MI
What is the odds of exposure among the
cases? What is the odds of exposure among the
controls? What is the OR?
32
Pesticides and MI
What is the odds of exposure among the cases?
(60/100)/(40/100) 1.5 What is the odds of
exposure among the controls? (10/100)/(90/100)
.11 What is the OR? 13.5
33
Case-control Study
  • Key elements
  • Compare individuals selected on the basis of
    disease status
  • Classic epidemiologic study design
  • Important but difficult 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

34
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Cohort study

35
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?

36
Pesticides and MI
37
Pesticides and MI
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?
38
Pesticides and MI
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
39
Cohort Study
  • Key elements
  • Select based on exposure status and follow-up
    over time
  • Can be prospective or retrospective
  • 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 rare and/or slow to develop
  • Attrition may result in selection bias
  • Inefficient for rare diseases

40
Testing hypotheses about MI
  • Hypothesis Exposure to pesticides increases
    risk of MI.
  • Evaluate the hypothesis using a
  • Randomized controlled trial

41
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 that you have maximal control over
    the study parameters, so you decide who gets
    exposed and who does not
  • Follow them up over time to ascertain MI status
  • What might you expect to see?

42
Pesticides and MI
43
Pesticides and MI
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?
44
Pesticides and MI
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
45
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).
  • Quasi-experimental designs also possible.
  • 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.

46
(No Transcript)
47
Ecologic Study
  • Childhood cancer and residential electric
    consumption
  • Canada 1971-1986
  • Rank provinces by REC
  • Rank provinces by cancer rates surveillance data
  • What is exposure/risk factor/agent?
  • What is disease/health outcome?

48
Ecologic Study
49
Cross-sectional Study
  • Literacy and misunderstanding prescription drug
    labels
  • Adults in primary care clinic waiting rooms
  • Low literacy reading at 5th grade level or
    below
  • Example Take one tsp by mouth 3 times daily
  • What is exposure? Disease?

50
Cross-sectional Study2X2 Table

51
Cross-sectional Study

Please reproduce the 2X2 table on paper.
52
Cross-sectional Study
  • What proportion of adults had low literacy?
  • What proportion of adults misunderstood the
    labels?
  • What proportion of adults who had low literacy
    misunderstood the labels?
  • What proportion of adults with adequate literacy
    misunderstood the labels?
  • How did the misunderstanding of the low literate
    adults compare with that of the adequately
    literate adults?

53
Case-control Study
  • Household pesticides and Wilms tumor
  • Early age on onset suggests in utero exposures
  • 523 cases of Wilms tumor
  • 517 controlsRDD to get disease free children who
    represent the distribution of exposure in the
    population from which cases arose
  • Pesticide use in home from month before
    conception through date of diagnosis/date of
    telephone call

54
Case-control Study

55
Case-control Study

56
Case-control Study
  • What proportion of children in the population
    have Wilms tumor?

57
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?
  • What is Odds Ratio?

58
Cohort Study
  • HIV status and risk of menstrual abnormalities
  • What is exposure? disease?

59
Cohort Study

60
Cohort study
  • What is risk of amenorrhea among HIV women?
  • What is risk of amenorrhea among HIV- women?
  • What is the risk among HIV women relative to the
    risk among HIV- women?

61
Randomized Controlled Trial
  • Vitamin D supplementation and risk of falls and
    fractures among the elderly
  • 149 residential facilities in Australia
  • Randomly assigned to 2 years on calcium with or
    without Vit D or placebo
  • Double-masked
  • Study diaries maintained by caregivers
  • What is exposure? Disease?

62
RCT

63
RCT
  • What is risk of fractures among the treatment
    group?
  • What is risk of fractures among the control
    group?
  • What is RR?

64
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
65
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
66
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
67
Time Check Noon 45 Minutes
68
YES Professional Development Workshop
Teach Epidemiology
69
Time Check 1245 PM 20 Minutes
70
YES Professional Development Workshop
Teach Epidemiology
71
Enduring Understandings
Enduring Epidemiological Understandings the big
ideas that reside at the heart of epidemiology
and have lasting value outside the
classroom.
they can distinguish between foundational
concepts and
elaborations or illustrations of those ideas.
Ken Bain, What the Best College Teachers Do
Teach Epidemiology
72
Making Group Comparisons and Identifying
Associations
Epidemiologic studies that are concerned with
characterizing the amount and distribution of
health and disease
within a population.
Teach Epidemiology
73
Making Group Comparisons and Identifying
Associations
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
74
Making Group Comparisons and Identifying
Associations


Hypothesis
An unproven idea, based on observation or
reasoning, that can be supported or refuted
through investigation An educated guess
Teach Epidemiology
75
Making Group Comparisons and Identifying
Associations
Hypothesis
Buprenorphine will stop heroin addicts from using
heroin.
Teach Epidemiology
76
Making Group Comparisons and Identifying
Associations
Trial 1
77
Making Group Comparisons and Identifying
Associations
Trial 1
Population
150 Heroin
Addicts
Sample 100
Heroin Addicts
78
Making Group Comparisons and Identifying
Associations
Trial 1
Population
150 Heroin
Addicts
Sample 100
Heroin Addicts
79 Heroin Addicts Tested Positive for Heroin
79
Making Group Comparisons and Identifying
Associations
Trial 1
Tested Positive for Heroin
Tested Negative for Heroin
Total
Bupe
100
79
21
Teach Epidemiology
80
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
81
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
82
Making Group Comparisons and Identifying
Associations
Risk
Numerator
79 tested positive for heroin
Denominator
100 study subjects
the risk of a positive heroin tests is
79 / 100 per 10-week period
Teach Epidemiology
83
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
84
Making Group Comparisons and Identifying
Associations
Calculating Risk
Trial 1
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
Bupe
100
79
21
100
Teach Epidemiology
85
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
86
Making Group Comparisons and Identifying
Associations
Inference
Trial 1
Probe
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
Bupe
100
79
21
100
What does this tell you about the hypothesis?
Buprenorphine will stop heroin addicts from using
heroin.
Teach Epidemiology
87
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
88
Making Group Comparisons and Identifying
Associations
Control Group
Tested Risk of
Using Heroin
Tested Positive for Heroin
Tested Negative for Heroin
Total
79
Bupe
100
21
79
100
Extend and label the table to include a control
group.
Teach Epidemiology
89
Making Group Comparisons and Identifying
Associations
Control Group
Tested Risk of
Using Heroin
Tested Positive for Heroin
Tested Negative for Heroin
Total
79
Bupe
100
21
79
100
No Bupe
100
Making Group Comparisons
Teach Epidemiology
90
Making Group Comparisons and Identifying
Associations
Tested Risk of
Using Heroin
Tested Positive for Heroin
Tested Negative for Heroin
Total
a
b
79
Bupe
100
21
79
100
c
d
No Bupe
100
Teach Epidemiology
91
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
92
Making Group Comparisons and Identifying
Associations
Trial 1
Population
150 Heroin
Addicts
Sample 100
Heroin Addicts
79 Heroin Addicts Tested Positive for Heroin
93
Making Group Comparisons and Identifying
Associations
Trial 2
Teach Epidemiology
94
Making Group Comparisons and Identifying
Associations
Teach Epidemiology
95
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Probe
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
96
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
97
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
79
Bupe
79
21
100
or
100
a b c d
79
No Bupe
79
21
100
79
or
100
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population
Teach Epidemiology
98
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
99
Making Group Comparisons and Identifying
Associations
Ratio
The value obtained
by dividing one
quantity by another
Teach Epidemiology
100
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
79
Bupe
79
21
100
or
100
a b c d
1
79
No Bupe
79
21
100
79
or
100
Ratio The value obtained by dividing one
quantity by another Risk Ratio The ratio of two
risks
Teach Epidemiology
101
Making Group Comparisons and Identifying
Associations
Create a formula
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
79
Bupe
79
21
100
or
100
a b c d
1
79
No Bupe
79
21
100
79
or
100
Risk Ratio The ratio of two risks.
Teach Epidemiology
102
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
1
79
No Bupe
79
21
100
79
or
100
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
103
Making Group Comparisons and Identifying
Associations
Trial 2
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
1
79
No Bupe
79
21
100
79
or
100
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
104
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
?
?
Bupe
100
100
a b c d
?
?
100
No Bupe
100
Teach Epidemiology
105
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
106
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
2.08
38
No Bupe
38
62
100
38
or
100
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
107
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
2.08
38
No Bupe
38
62
100
38
or
100
2.08
The heroin addicts who received Bupe were ___
times as likely to use heroin as those who did
not receive Bupe.
Teach Epidemiology
108
Making Group Comparisons and Identifying
Associations
Trial 3
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
2.08
38
No Bupe
38
62
100
38
or
100
Inference Process of predicting
from what is
observed in a sample
to what is occurring in
the entire population.
Teach Epidemiology
109
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
?
?
Bupe
100
100
a b c d
?
?
100
No Bupe
100
Teach Epidemiology
110
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
Bupe
a b c d
No Bupe
Teach Epidemiology
111
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
0.84
94
No Bupe
94
6
100
94
or
100
Relative Risk The ratio of the risk of an
outcome among the exposed to the risk of the
outcome among the unexposed.
Teach Epidemiology
112
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
0.84
94
No Bupe
94
6
100
94
or
100
0.84
The heroin addicts who received Bupe were ____
times as likely to use heroin as those who did
not receive Bupe.
Teach Epidemiology
113
Making Group Comparisons and Identifying
Associations
Trial 4
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Relative Risk
Total
79
79
Bupe
79
21
100
or
100
a b c d
0.84
94
No Bupe
94
6
100
94
or
100
Inference Process of predicting
from what is
observed in a sample
to what is not observed
in a population.
Teach Epidemiology
114
Making Group Comparisons and Identifying
Associations
Trial 1
Tested Positive for Heroin
Tested Negative for Heroin
Tested Risk of
Using Heroin
Total
79
79
Bupe
79
21
100
or
100
a b c d
Nothing
What do the results tell us about the hypothesis
that Buprenorphine will stop heroin addicts from
using heroin?
Teach Epidemiology
115
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
Nothing
Trial 3
Trial 4
Teach Epidemiology
116
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
1
Nothing
There is no association between Bupe and heroin
use.
Trial 3
Trial 4
Teach Epidemiology
117
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
1
Nothing
There is no association between Bupe and heroin
use.
Trial 3
Trial 4
2.08
Bupe is associated with an increase in heroin use.
Teach Epidemiology
118
Making Group Comparisons and Identifying
Associations
Trial 1
Trial 2
1
Nothing
There is no association between Bupe and heroin
use.
Trial 3
Trial 4
.84
2.08
Bupe is associated with an increase in heroin use.
Bupe is associated with a decrease in heroin use.
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Associations
Trial 1
Trial 2
1
Nothing
Nothing
There is no association between Bupe and heroin
use.
Trial 3
Compared to what?
Trial 4
.84
2.08
Bupe is associated with an increase in heroin use.
Bupe is associated with a decrease in heroin use.
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Associations
Handout
6.
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Enduring Understandings
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Time Check 105 PM 15 Minutes
123
Making Group Comparisons and Identifying
Associations
The Journey
Teach Epidemiology
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Making Group Comparisons and Identifying
Associations
The Journey from Exposure to Disease
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Associations
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Associations
Epi Talk
Study Design
Procedures and methods, established beforehand,
that are followed by the investigator conducting
the study.
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Associations
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Associations
E
DZ



Time
Teach Epidemiology
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Associations
Study Design
Controlled Trial
E
DZ



Time
Teach Epidemiology
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Associations
Flow Diagram
Controlled Trial
Healthy People
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Associations
Study Design
Cohort Study



Time
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Cohort Study
Just as in the controlled trial, the
epidemiologist is also on the train during the
entire journey. But there is an important
difference. The epidemiologist is not telling
passengers what to do. Rather, the
epidemiologist is just observing them and
counting. Passengers are not being told to have
or not have an exposure, they are just living
their normal lives. The epidemiologist, on the
ride for the whole journey, just keeps observing
everyones exposures and whether or not they
develop the disease during the journey.
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Study Design
Cohort Study
E
DZ



Time
Teach Epidemiology
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Associations
Flow Diagram
Cohort Study
Healthy People
Teach Epidemiology
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Associations
Flow Diagram
Controlled Trial
Cohort Study
Healthy People
Teach Epidemiology
136
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Associations
Flow Diagram
Controlled Trial
Cohort Study
Random Assignment
Healthy People
Teach Epidemiology
137
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Associations
Epi Talk
Observational Studies
Epidemiologic studies of natural experiments in
which the investigator is not involved in the
intervention other than to record, classify,
count, and statistically analyze results.
Teach Epidemiology
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Associations
Study Design
Case-Control Study



Time
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Associations
Case-Control Study
The epidemiologist was not on the journey.
Rather, the epidemiologist is waiting at the
train station at the end of the journey. As
passengers get off the train, the epidemiologist
selects sick passengers for the case group and
selects passengers who are similar but not sick
for the control group. The epidemiologist then
asks each person in the case group and control
group questions about their exposures during the
train ride. The epidemiologist relies on
passengers memories of their exposures that
occurred during the train ride.
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Associations
Study Design
Case-Control Study
DZ
E



Time
Teach Epidemiology
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Associations
Flow Diagram
Case-Control Study
Observational Study
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Associations
Study Design
Cross-Sectional Study



Time
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Associations
Cross-Sectional Study
The epidemiologist, who has not been on the
journey, stops the train somewhere during the
trip (kind of like a train robbery) and takes a
snapshot of all the passengers by asking them
whether or not they have the exposure and whether
or not they have the disease. Then the
epidemiologist leaves the train and goes home to
analyze the data from that particular day. The
journey continues without the epidemiologist.
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Associations
Study Design
Cross-Sectional Study



Time
Teach Epidemiology
145
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Associations
Flow Diagram
Cross-Sectional Study
Observational Study
Teach Epidemiology
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Associations
Epi Talk
Controlled Trial
An epidemiologic experiment in which subjects are
assigned into groups to receive or not receive a
hypothesized beneficial intervention.
Teach Epidemiology
147
Making Group Comparisons and Identifying
Associations
Epi Talk
Cohort Study
An analytical epidemiological study design in
which the investigator selects a group of exposed
individuals and a group of unexposed individuals
and follows both groups to compare the frequency
with which the disease occurs in each group.
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Associations
Epi Talk
Case-Control Study
An analytical epidemiological study design in
which the investigator selects a group of
individuals with a disease (cases) and a group of
similar individuals without the disease
(controls) and compares the frequency with which
an exposure occurred in the cases versus the
controls.
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Associations
Epi Talk
Cross-Sectional Study
An analytical epidemiological study design in
which the investigator selects a group of
individuals and determines the presence or
absence of a disease and the presence or absence
of an exposure at the same time.
Teach Epidemiology
150
Time Check 120 PM 10 Minutes
151
Enduring Understandings
Teach Epidemiology
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Associations
Association Found
Between Coffee and Pancreatic Cancer
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Associations
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.
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Associations
Things that are associated are linked in some way

that makes them turn up together.
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Associations
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
156
Making Group Comparisons and Identifying
Associations
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
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Associations
Suicide Higher in Areas with Guns
Total
a
b
d
c
Teach Epidemiology
158
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Associations
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
Teach Epidemiology
159
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Associations
Kids Who Watch R-Rated Movies More Likely to
Drink, Smoke
Total
a
b
d
c
Teach Epidemiology
160
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
161
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Associations
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
Teach Epidemiology
162
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Associations
Family Meals Are Good for Mental Health
Total
a
b
d
c
Teach Epidemiology
163
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Associations
Family Meals Are Good for Mental Health
No Mental Health
Mental Health
Total
Family Meals
a
b
d
c
No Family
Meals
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164
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Associations
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
Teach Epidemiology
165
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Associations
Study Links Iron Deficiency to Math Scores
Total
a
b
d
c
Teach Epidemiology
166
Making Group Comparisons and Identifying
Associations
Study Links Iron Deficiency to Math Scores
Poor Math Scores
Good Math Scores
Total
Iron Deficiency
a
b
d
c
No Iron
Deficiency
Teach Epidemiology
167
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
168
Making Group Comparisons and Identifying
Associations
Pollution Linked with Birth Defects in US Study
Total
a
b
d
c
Teach Epidemiology
169
Making Group Comparisons and Identifying
Associations
Pollution Linked with Birth Defects in US Study
No Birth Defects
Birth Defects
Total
Pollution
a
b
d
c
No Pollution
Teach Epidemiology
170
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
171
Making Group Comparisons and Identifying
Associations
Depressed Teens More Likely to Smoke
Total
a
b
d
c
Teach Epidemiology
172
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
173
Making Group Comparisons and Identifying
Associations
Smoking Linked to Youth Eating Disorders
Total
a
b
d
c
Teach Epidemiology
174
Making Group Comparisons and Identifying
Associations
Smoking Linked to Youth Eating Disorders
No Eating Disorders
Eating Disorders
Total
Smoke
a
b
d
c
No Smoke
Teach Epidemiology
175
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
176
Making Group Comparisons and Identifying
Associations
Study Links Spanking to Aggression
Total
a
b
d
c
Teach Epidemiology
177
Making Group Comparisons and Identifying
Associations
Study Links Spanking to Aggression
No Aggression
Aggression
Total
a
Spanking
a
b
d
c
c
No Spanking
People who have the outcome
Teach Epidemiology
178
Making Group Comparisons and Identifying
Associations
Snacks Key to Kids TV-Linked Obesity China
Study
Total
a
b
d
c
Teach Epidemiology
179
Making Group Comparisons and Identifying
Associations
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
Teach Epidemiology
180
Enduring Understandings
Teach Epidemiology
181
Time Check 130 PM 10 Minutes
182
Enduring Understandings
Teach Epidemiology
183
Enduring Understandings
Teach Epidemiology
184
Enduring Understandings
Teach Epidemiology
185
Making Group Comparisons and Identifying
Associations
Anecdote
A story. Often used to describe a type of
evidence used in argument, as in anecdotal
evidence. Anecdotal evidence is sometimes used
to appeal to emotion rather than logic. Those
who use anecdote in this fashion suggest that a
conclusion can be reached on the basis of one
incident, rather than a careful scientific
inquiry. Anecdotal evidence is, therefore, often
used to describe a given argument disparagingly.
Teach Epidemiology
186
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Associations
Teach Epidemiology
187
Making Group Comparisons and Identifying
Associations
Absolutely nothing in the available arsenal of
anti-emetics worked at all. I was miserable and
came to dread the frequent treatments with an
almost perverse intensity. I had heard that
marijuana often worked well against nausea. I
was reluctant to try it because I had never
smoked any substance habitually (and didnt even
know how to inhale). Moreover, I had tried
marijuana twice (in the 1960s) and had hated it
. Marijuana worked like a charm . The sheer
bliss of not experiencing nausea - and not having
to fear it for all the days intervening between
treatments - was the greatest boost I received in
all my year of treatment, and surely the most
important effect upon my eventual cure.
Stephen Jay Gould

(survivor of abdominal mesothelioma)
Teach Epidemiology
188
Making Group Comparisons and Identifying
Associations
Anecdote
A particular or detached incident or fact
of
an interesting nature a biographical incident or
fragment a single passage of private
life.
Teach Epidemiology
189
Making Group Comparisons and Identifying
Associations
Transforming Anecdote to Science
Anecdote
Teach Epidemiology
190
Making Group Comparisons and Identifying
Associations
Controlled Trial
Case-Control Study
Cohort Study
Cross-Sectional Study
Teach Epidemiology
191
Making Group Comparisons and Identifying
Associations
Controlled Trial
Case-Control Study
b
a
d
c
Cohort Study
Cross-Sectional Study
Teach Epidemiology
192
Making Group Comparisons and Identifying
Associations
Laboratory
Teach Epidemiology
193
Making Group Comparisons and Identifying
Associations
Laboratory
Teach Epidemiology
194
Making Group Comparisons and Identifying
Associations
Natural Experiment
Naturally occurring circumstances
in
which groups of people within a population
have been exposed to
different levels
of the hypothesized cause of an outcome.
Teach Epidemiology
195
Making Group Comparisons and Identifying
Associations
Observational Study
An epidemiologic study of a natural experiment
in which the
investigator is not involved in the intervention
other than to record, classify,
count,
and statistically analyze results.
Teach Epidemiology
196
Making Group Comparisons and Identifying
Associations
Controlled Trial
An epidemiologic experiment
in
which subjects are assigned into groups
to receive or not receive

a hypothesized beneficial
intervention.
Teach Epidemiology
197
Making Group Comparisons and Identifying
Associations
Controlled Trial
Buprenorphine
Buprenorphine will stop heroin addicts from using
heroin.
Teach Epidemiology
198
Making Group Comparisons and Identifying
Associations
Observational Study of a Natural Experiment
Naturally occurring circumstances
in
which groups of people within a population
have been exposed to
different levels
of the hypothesized cause of an outcome.
Epidemiologic studies of natural experiments
in which the investigator
is not involved in the intervention other than to
record, classify, count,
and statistically analyze results.
Teach Epidemiology
199
Making Group Comparisons and Identifying
Associations
Teach Epidemiology
200
Time Check 140 PM 50 Minutes
201
Making Group Comparisons and Identifying
Associations
Observational Studies Part 1
Teach Epidemiology
202
Making Group Comparisons and Identifying
Associations
Teach Epidemiology
203
Making Group Comparisons and Identifying
Associations
Teach Epidemiology
204
Making Group Comparisons and Identifying
Associations
Selecting a Hypothesis
Step 1
Planning the Study
Steps 2-7
Collecting Data
Steps 8-12
Analyzing Data
Steps 13-17
Planning the Presentation
Step 18
Teach Epidemiology
205
Making Group Comparisons and Identifying
Associations
Epi Teams
Teach Epidemiology
206
Making Group Comparisons and Identifying
Associations
  • Acne
  • Auto injuries
  • Bad mood
  • Cavities
  • Cell phones
  • Class disruption
  • Chewing gum
  • Colds
  • Drinking soda
  • Eating breakfast
  • Eating candy
  • Eating high fat food
  • Eating school cafeteria food
  • Exercise
  • Foul language
  • Getting a good nights sleep
  • Good quiz scores
  • Good grades
  • Having a quiet place to study
  • Improves performance
  • Indigestion
  • Lack of regular exercise
  • Listening to music while studying
  • Listening to rap music
  • Multi-vitamins
  • Nightmares
  • Overweight
  • Poor grades
  • Poor quiz scores
  • Practicing a sport
  • Seat belts
  • Skipping breakfast
  • Studying
  • Too much talking on the telephone
  • Violent behavior
  • Watching the evening news on TV
  • Watching too much TV
  • Watching violent movies

Teach Epidemiology
207
Making Group Comparisons and Identifying
Associations
1
Teach Epidemiology
208
Making Group Comparisons and Identifying
Associations
2-7
Planning the Study
Define the exposure.
Create a question to gather data
about the exposure.
Define the outcome in the hypothesis.
Create a question to gather data
about the outcome.
Label 2 x 2 Table Sheet.
Create an informed consent statement for
participation in the observational study.
Teach Epidemiology
209
Making Group Comparisons and Identifying
Associations
Informed Consent
Voluntary consent given by a person for
participation in a study.
Participants must know and understand the study,
give consent without coercion, and know that
they can withdraw at any time.
Teach Epidemiology
210
Making Group Comparisons and Identifying
Associations
Collecting Data
Read informed consent statement and remind
class of right not to participate.
Have class label 2 x 2 Table Sheets.
Review exposure and outcome questions.
Review what cells students fit into based on
answers to exposure and outcome questions.
Instruct class to voluntarily and anonymously
place a check in the cell that identifies
their exposure and outcome for the hypothesis
being tested.
Teach Epidemiology
211
Making Group Comparisons and Identifying
Associations
Collecting Data
Teach Epidemiology
212
Making Group Comparisons and Identifying
Associations
Collecting Data
Read informed consent statement and remind
class of right not to participate.
Have class label 2x2 Table Sheets.
Review exposure and outcome questions.
Review what cells students fit into based on
answers to exposure and outcome questions.
Instruct class to voluntarily and anonymously
place a check in the cell that identifies
their exposure and outcome for the hypothesis
being tested.
Teach Epidemiology
213
Making Group Comparisons and Identifying
Associations
13-17
Analyzing Data
Sort 2 x 2 Table Sheets and complete the 2 x 2
table that was labeled in step 6.
Calculate the risks of the outcome for the
exposed and unexposed groups as fractions and
percents.
Calculate the relative risk.
Complete the statement.
Explain whether or not the data support the
hypothesis.
Teach Epidemiology
214
Making Group Comparisons and Identifying
Associations
Presentation Planning
IMRAD
Introduction Methods Results and Discussion
Teach Epidemiology
215
Making Group Comparisons and Identifying
Associations
IMRAD
Format usually followed when epidemiological
studies are published in medical journals.
Introduction Why the authors decided to do the
study,
Methods How authors did the study,
Results What the authors found, and
Discussion What the results mean.
Teach Epidemiology
216
Making Group Comparisons and Identifying
Associations
18
Step 18 Presentation Planning
IMRAD
Introduction Methods Results and Discussion
Teach Epidemiology
217
Making Group Comparisons and Identifying
Associations
Presentation Rubric
Criteria
Got It
Getting It
Will Get It Soon
Participation
Use of Epi Talk
Data Collection Methods
Risks, Relative Risk, and Inference
IMRAD
Teach Epidemiology
218
Making Group Comparisons and Identifying
Associations
Observational Studies Part 2
Teach Epidemiology
219
Making Group Comparisons and Identifying
Associations
Epi Team Presentation
Teach Epidemiology
220
Making Group Comparisons and Identifying
Associations
  • Acne
  • Auto injuries
  • Bad mood
  • Cavities
  • Cell phones
  • Class disruption
  • Chewing gum
  • Colds
  • Drinking soda
  • Eating breakfast
  • Eating candy
  • Eating high fat food
  • Eating school cafeteria food
  • Exercise
  • Foul language
  • Getting a good nights sleep
  • Good
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