Exam 1 (Lecture 1-13) Flashcards
(130 cards)
1
Q
Who was one of the founders of epidemiology?
A
John Snow
2
Q
Epidemiology is a public health basic science that studies the _______ and ______ of health-related states or events in specific populations to control disease/illness and promote health.
A
Distribution and Determinants
3
Q
True or False: Epidemiology deals ONLY with diseases.
A
False. Epidemiology can focus on many different things.
4
Q
Epidemiology always deals with ______, not just one individual.
A
Populations
5
Q
Epidemiologists are experts at describing and comparing groups by: (3 things)
A
1) Counting (Frequencies)
2) Dividing (Percentages)
3) Comparing
6
Q
What disease did John Snow believe was being distributed by the Broad Street pump in London?
A
Cholera
7
Q
What are the common objectives of the discipline of epidemiology? (6 things)
A
1) Identify patterns/trends
2) Determine extent of states or events
3) Study natural course of states or events
4) Identify the causes of, or risk factors for, states or events
5) Evaluate effectiveness of measures that may prevent states or events
6) Assist in developing public health policy to promote health
8
Q
Define “distribution” of disease.
A
Frequency and pattern of disease occurrences. Follows Descriptive Epidemiology = Person (Who), Place (Where), and Time (When)
9
Q
Define “determinants” of disease.
A
Factors, risk, exposure, cause, modes of transmission, etc. Follows Analytic Epidemiology = Why and How
10
Q
True of False: Disease occurrence is NOT random.
A
True
11
Q
List the 6 core functions of epidemiology.
A
1) Public health surveillance
2) Field investigation
3) Analytic studies
4) Evaluation
5) Linkages
6) Policy development
12
Q
Name this core function of epidemiology: To portray ongoing patterns of disease occurrence, so investigations, control and prevention measures can be developed and applied. i.e., Morbidity, Mortality, Birth
A
1) Public health surveillance
13
Q
Name this core function of epidemiology: Determine sources/vehicles of disease; to simplify or learn more about the natural history, clinical spectrum, descriptive epidemiology (3 W’s) and risk factors of a disease before determining interventions.
A
2) Field investigation
14
Q
Name this core function of epidemiology: Advance the information (hypotheses) generated by descriptive epidemiology techniques.
A
3) Analytic studies
15
Q
Name this core function of epidemiology: Systematically and objectively determine relevance, effectiveness, efficiency and impact of activities.
A
4) Evaluation
16
Q
Name this core function of epidemiology: Collaborate/communicate with (link to) other public health and healthcare professionals (and the public themselves).
A
5) Linkages
17
Q
Name this core function of epidemiology: Provide input, testimony, recommendations regarding disease control and prevention strategies, reportable disease regulations and health-care policy.
A
6) Policy development
18
Q
List the 3 key factors needed to compare disease frequency between groups.
A
1) # of people affected/impacted
2) Size of the source population or those at risk
3) Length of time the population is followed
19
Q
When epidemiologists rely on healthcare systems to follow regulations and report diseases or conditions, they are exhibiting (passive/active) surveillance.
A
Passive
20
Q
When public health officials go into the communities to search for new disease/condition cases, they are exhibiting (passive/active) surveillance.
A
Active
21
Q
A surveillance system that looks for pre-defined signs/symptoms of patients related to trackable-but-rare diseases is…
A
Syndromic
22
Q
Review the “Natural History of Disease Timeline” for 5 minutes.
A
See slide 5 from Descriptive Epi and Measures of Frequency.
23
Q
Time between exposure and onset of disease can be referred to as _______ or ______ period (Symptoms may or may not be starting to occur and could be diagnosed clinically).
A
Induction or Incubation
24
Q
Time between onset of disease and disease detection (symptoms or diagnosis) can be referred to as ______ period.
A
Latency
25
What is the most critical element that must be defined/delineated before any of the 'Who' of descriptive epidemiology can be acquired?
The case definition. This is a set of uniform criteria used to define a disease/condition for public health surveillance.
26
Occurrence of disease clearly in excess of normal expectancy (larger population. i.e., all of Kansas City)
Epidemic
27
An epidemic limited to a localized increase in the occurrence of disease (smaller population. i.e, all of KCU) Also called a "cluster"
Outbreak
28
The constant presence of a disease within a given area or population in excess of normal levels in other areas.
Endemic
29
An epidemic that alerts the world to the need for high vigilance (BE AWARE). Pre-pandemic label.
Emergency of International Concern
30
An epidemic spread world-wide (global health impact) Multi-national and multi-continent.
Pandemic
31
What is a graphical, time-based depiction generated during an outbreak/epidemic reflecting the # of cases by date?
An epidemic curve
32
The sentinel/index case can be classified as the (first/last) occurrence that could have caused the outbreak (unaware at time of illness) and is on the far (left/right) of the epi curve.
First; Left
33
Common/Point source on the epi curve represents that a disease was spread how? From where?
It was not spread person-to-person, it was from a common, single point source for the outbreak. (i.e., the Broad Street pump spreading cholera)
34
Propagated source on the epi curve represents that a disease was spread how?
It was spread from person-to-person.
35
Common/Point source can be either ______ or _______.
Continuous (with or without index case) or intermittent
36
What does NNDSS stand for and what do they do?
National Notifiable Diseases Surveillance System. They provide uniform criteria of nationally notifiable infections and non-infectious conditions for reporting purposes. Ran by CDC.
37
A proportion is the division of 2 (related/unrelated) numbers.
Related; The numerator is a subset of the denominator (percentage)
38
A ratio is the division of 2 (related/unrelated) numbers.
Unrelated; The numerator is not part of the denominator
39
A rate is a proportion (%) with ____ incorporated into the denominator.
Time
40
New cases of disease. (A proportion, including the "at risk" or "base" population in denominator)
Incidence; Risk; Attack Rate = # of New cases of Illness/ # of People at RISK of Illness (or in Population)
***Have to subtract out those who already have the disease or are immune from the starting population (if possible)
41
Existing cases of disease + New cases of disease. (A proportion, including the "at risk" or "base" population in denominator)
Prevalence = # of existing cases of disease/ # of persons in population. (Prevalence rate is this within a certain period of time)
***Time frames for numerator/denominator must be the same and denominator includes those already with disease AND at risk for getting disease.
42
Incidence when summed over multiple time periods.
Cumulative incidence
43
What do you use when you can't calculate the population at risk or the population isn't followed at the same time?
Incidence Rate = # of New cases of disease/ Person-time at risk for the disease (or in Population)
Also called Incidence Density when summed over multiple time periods
44
How would you express 100 person-years? (Describing unit of person-time)
100 people followed for 1 year; 10 people followed for 10 years; 1 person followed for 100 years; 25 people followed for 4 years
45
When membership of a population is based on an event and is permanent, then it's...
Fixed
46
When membership of a population is based on a condition and is transitory, then it's...
Dynamic
47
Prevalence at 8 PM on October 1st is an example of _____ prevalence.
Point
48
Prevalence from October 2018 to October 2019 is an example of _____ prevalence.
Period
49
Definition and equation for Crude Morbidity Rate.
Morbidity is the condition of being diseased. The equation is the same as prevalence, which is the # of Persons with Disease/ # of persons in the population.
50
Definition and equation for Crude Mortality Rate.
Mortality is death. The equation is # of deaths (of all causes) / # of persons in population.
51
of Persons with Cause-Specific Disease/ # of persons in population
Cause-Specific Morbidity Rate
52
of Cause-Specific Deaths/ # of persons in population
Cause-Specific Mortality Rate
53
Case-Fatality Rate is...
of cause-specific deaths / # of cases of disease
54
Cause-Specific Survival Rate is...
of cause-specific cases alive / # of cases of disease
55
Proportional Mortality Rate (PMR) is...
of cause-specific deaths / Total # of deaths in population
56
What is the ability to cause clinical disease?
Pathogenicity
57
Live Birth-Rate (usually per year) is...
of live births / 1,000 population
58
Fertility Rate (usually per year) is...
of live births / 1,000 women of childbearing age (15-44)
59
Neonatal Mortality Rate (usually per year) is...
of deaths in those <28 days of age / 1,000 live births
60
Postnatal Mortality Rate (usually per year) is...
of deaths in those > or equal to 28 days but <1 year of age / 1,000 live births
61
Infant Mortality Rate (usually per year) is...
of deaths in those <1 year of age / 1,000 live births
62
Maternal Mortality Ratio is...
of female deaths related to pregnancy / 100,000 live births
63
What does CDC stand for?
Center for Disease Control (and Prevention)
www.cdc.gov
64
What does MMWR stand for and what is it?
Morbidity and Mortality Weekly Report (run by CDC). It is a weekly epidemiological report on public health information and recommendations to CDC from state health departments.
www.cdc.gov/mmwr
65
What does WHO stand for and what is it?
World Health Organization. It is the directing and coordinating authority on international health within the United Nations system.
www.who.int
66
These keep track of individuals with certain symptoms and illnesses. They can be recorded on a voluntary basis to aid in future diagnoses of this particular illness.
Disease registry
67
Absolute differences will always ______ frequencies.
Subtract
68
Relative differences will always ______ frequencies.
Divide
69
Incidence Risk (IR)
A proportion (percentage).
Probability of Outcome in (out of) the EXPOSED = A/(A+B)
Probability of Outcome in (out of) the NON-EXPOSED = C/(C+D)
***See Table from Slide 2: Measures of Association
70
```
Absolute Risk Reduction (ARR) or
Attributable Risk (AR)
```
This defines the risk difference of the outcome attributable to exposure difference between groups. (Risk of Unexposed - Risk of Exposed)
71
Relative Risk Reduction (RRR)
(ARR) / R,unexposed
72
Number Needed to Treat (NNT) / Number Needed to Harm (NNH)
of patients needed to be treated to receive the stated benefit/harm
1 / ARR
73
```
Risk Ratio (RR)
Relative Risk (RR)
```
Ratio of the risks from 2 different groups
Risk of Outcome (in Exposed) / Risk of Outcome (in Non-exposed)
74
When interpreting ratios (RR/OR/HR), look for what 3 things?
1) Groups that are being compared (i.e., Ramipril vs. Placebo)
2) Direction of words (i.e., increased/decreased)
3) Magnitude
75
Odds is a _____ not a simple percentage.
Ratio
76
Odds are the frequency of an outcome _______ vs. NOT _______.
Occurring
77
Odds Ratio (OR) is the ratio of odds from 2 different groups. To calculate this you..
Cross-multiply
78
This is a 3rd variable (characteristic related to study subjects) that distorts an association (RR/OR/HR) between the Exposure and the Outcome.
Confounding variable
79
To be a confounder, a 3rd variable must be: (3 things)
1) Independently associated with the exposure
2) Independently associated with the outcome
3) Not directly in the causal-pathway linking Exposure and Outcome (independent)
80
The first step in testing for confounding is to...
Calculate the crude (unadjusted) measure of association between exposure and outcome (i.e., OR/RR/HR)
81
The second step in testing for confounding is to...
Calculate outcome measure of association (OR/RR) between exposure and outcome for each individual strata of the 3rd variable. Take weighted average of all strata, called "adjusted"
82
The third step in testing for confounding is to...
Compare the Crude vs. Adjusted measures of association between Exposure and Outcome
83
To calculate if it is confounding the equation is...
Crude - Adjusted / Crude
84
A variable is considered confounding if it is above what percentage?
15%
85
Name the 2 main impacts of confounders:
1) Magnitude (strength) of association
| 2) Direction of association
86
The 3 ways to control for confounding during the study design stage are:
1) Randomization (simple or stratified versions)
2) Restriction
3) Matching
87
The 2 ways to control for confounding during the analysis of data stage are:
1) Stratification (w/ Weighting)
| 2) Multivariate statistical analysis (regression analysis)
88
If the strata-specific measures of association are DIFFERENT, what do we use?
Effect Modification
89
The first step in testing for effect modification is...
Calculate crude measure of association between exposure and outcome (OR/RR)
90
The second step in testing for effect modification is...
Calculate strata-specific measures of association between exposure and outcome (OR/RR) for each strata (layers/levels) of the 3rd variable
91
The third step in testing for effect modification is...
Compare each of the strata-specific measures of association (OR/RR) between each other [while referencing the adjusted measure of association]
92
In order for an effect modification to be present, the measure of association between the highest and lowest strata must be what percent or higher?
15%
93
This can be defined as the systematic (non-random) error in study design or conduct leading to erroneous results.
Bias
94
Bias distorts the relationship (association) between _________ and ________.
Exposure; Outcome
95
T/F. You can fix a bias once it has already occurred (after study ends).
False. Pre-study considerations can minimized bias and its impact, but nothing can be done after the study.
96
When assessing biases and their potential impact, investigators understand these 3 elements of bias impact:
1) Source/Type
2) Magnitude/Strength
3) Direction
97
The 2 main categories of bias are:
1) Selection-related
| 2) Measurement-related (information/observation)
98
(Selection/Measurement) related bias has to do with any aspect in the way the researcher selects or acquires study subjects which creates a systematic difference between groups.
Selection-related
99
Dealing with bias, we (DO/DO NOT) want to do anything that is different, or creates a difference, between groups
DO NOT
100
(Selection/Measurement) related bias has to do with any aspect in the way the researcher collects information, or measures/observes subjects which creates a systematic difference between groups.
Measurement-related
101
This type of bias, which is an example of selection bias, has to deal with the idea that employed individuals tend to have lower morbidity/mortality rates than others in a population.
Healthy-worker bias
102
This type of bias, which is an example of selection bias, considers that those that wish to participate (volunteer) may be different in some way to those that don't volunteer or self-select (refusal/non-response) to participate
Self-selection/Participant (Responder) bias
103
This type of bias, which is an example of measurement bias that is subject-related, has to do with a differential level of accuracy/detail in provided information between study groups. (i.e., exposed or diseased subjects may have greater sensitivity for recalling their history, better memory; easier to remember; exaggerate responses)
Recall (Reporting) bias
104
This type of bias, which is an example of measurement bias that is subject-related, has to do with individuals that alter/modify their behavior because they are part of a study and know they are under observation.
Hawthorne effect (Observation effect)
105
This type of bias, which is an example of measurement bias that is subject-related, has to do with members of the control group accidentally, or outside of the study protocol, receive the treatment (or similar) or are exposed to the intervention being studied.
Contamination bias
106
This type of bias, which is an example of measurement bias that is subject-related, has to do with groups being interventionally studied have different compliance/adherence with study protocol/treatments.
Compliance/Adherence bias
107
This type of bias, which is an example of measurement bias that is subject-related, has to do with groups being studied having different withdrawal or lost to follow-up rates OR there are other differences between those that stay in the study and those that withdraw or are lost to follow-up.
Lost to Follow-up bias
108
This type of bias, which is an example of measurement/observation bias that is observer-related, has to do with a systematic difference in soliciting, recording, or interpreting on the part of the researcher (or their assistants). Interviewer knowledge may influence the structure or tone of questioning or interventions/treatments are not applied equally due to training or personnel differences.
Interviewer bias
109
This type of bias, which is an example of measurement/observation bias that is observer-related, has to with different evaluation, classification, diagnosis, or observation between study groups. Observers may have preconceived expectations of what they should find in examination, evaluation, or follow-up (Hawthorne-like effect from researchers perspective)
Diagnosis/Surveillance (Expectation) bias
110
This type of bias, which is an example of measurement/information bias that is screening-related, has to do with an apparent benefit from a healthcare screening due to the early detection of disease despite an unchanged clinical outcome. 'Extra time' (knowing patient's have the disease) afforded by early detection (screening) is designated as the lead-time.
Lead-Time bias
111
As a source of measurement (information/observation) bias, this type of bias is an error in classifying either disease or exposure status, or both.
Misclassification bias
112
Misclassification bias can be either _________ or ________.
Differential; Non-differential
113
In misclassification bias, _________ means there is error in both groups equally.
Non-differential
114
In misclassification bias, _________ means there is error in one group differently than the other.
Differential
115
This can be defined as a precursor event, condition, or characteristic required for the occurrence of the disease or outcome.
Cause
116
Associations are relationships between an exposure/treatment and an outcome/disease. The 3 types of Associations (relationships) are:
1) Artifactual (aka False) associations
2) Non-causal associations
3) Causal associations
117
_________ associations can arise from bias and/or confounding.
Artifactual (false)
118
__________ associations can occur in 2 different ways: 1) The disease may cause the exposure (rather than the exposure causing the disease) or 2) The disease and the exposure are both associated with a third factor (confounding)
Non-causal
119
_________ associations occur when the exposure leads to the outcome.
Causal
120
_______ cause, a type of causal association, is a set of minimal conditions/events that inevitably produce disease. A cause which precedes a disease, and if present, the disease will always occur.
Sufficient
121
________ cause, a type of causal association, is a cause which precedes a disease and must be present for the disease to occur, yet the cause may also be present without the disease occurring.
Necessary
122
________ cause (aka Risk Factor; RF), a type of causal association, is a factor/element that, if present/active, increases the probability (or likelihood) of a particular disease.
Component
123
This type of interaction occurs when the biological-interaction of 2 or more component-causes combined measure of effect is greater than the sum of the individual effects. (i.e., If gene and environmental factors acted together, infants would only get the congenital disorder if exposed to BOTH factors)
Synergism
124
This type of interaction occurs when the biological-interaction of 2 or more component-causes measure of effect is greater if either is present. (i.e., Infants would only get the congenital disorder if exposed to EITHER the gene or the environmental factor but would not get the disorder if exposed to neither)
Parallelism
125
Hill's Criteria (Guidelines) for causal inference are:
| The higher the number of criteria met, when evaluating an association, the more likely it may be causal
1) Strength
2) Consistency
3) Temporality
4) Biologic Gradient
5) Plausibility
126
________ is one of Hill's criteria that refers to the size of the measure of association (OR/RR/HR). The greater the association (ratio-value; whether below or above 1.0), the more convincing it is that the association might actually be causal.
Strength
127
________ is one of Hill's criteria that refers to the repeated observations of an association in different populations under different circumstances in different studies (not just once!) i.e., Menopausal Hormone Therapy example
Consistency (aka Reproducibility)
128
_________ is one of Hill's criteria that reflects that the cause precede the effect/outcome in time. The time-order can also be described as proximate cause (short-term interval) or distant cause (long-term interval). i.e., Studies have shown higher lung cancer rates among former smokes during first year after quitting compared to those who continue to smokes.. so continuing to smoke must decrease the risk of lung cancer. In reality, most voluntarily stop smoking because of early symptoms and signs of already-existing illness.
Temporality
129
________ is one of Hill's criteria that refers to the presence of a gradient of risk (dose-response) associated with the degree of exposure. (i.e., lights smokers are 5 times more likely to develop lung cancer than non-smokers, whereas heavy smokers are 15 times more likely than non-smokers)
Biologic Gradient
130
________ is one of Hill's criteria that refers to the presence of biological feasibility to the association, which can be understood and explained (biologically/physiologically/medically). Is the event/exposure biologically-plausible, if really true? (i.e., Infection (H. pylori) causes ulcers)
Plausibility
