Epidemiology

Front 1

What are the characteristics of chronic diseases.

Back 1

1. Long period of symptoms
2. Residual disability and non-reversible pathologic changes
3. Special/long term rehabilitation
4. Indefinite period of treatment.

Front 2

What are the difficulties in studying chronic diseases.

Back 2

1. There is no single agent
2. Long latent period
3. Indefinite onset
4. One set of factors are initiators, others are promoters

Front 3

Differentiate between the different observational study designs.

Back 3

1. Cross-sectional
2. Case-control
3. Cohort

Front 4

What are some characteristics of Cross sectional designs?

Back 4

1. Study groups are chosen-usually on a geographic basis.
2. Participants are chosen without regard to presence of factors or diseases
3. Presence of factors and diseases at the time of the study are ascertained.
4. They are used to build hypotheses.

Front 5

What are some related concepts to Cross sectional designs?

Back 5

1. Prevalence studies (number of existing cases of a disease or health condition in a population)
2. Longitudinal studies
3. Dependent and independent variables

Front 6

What are some advantages of a Cross sectional design?

Back 6

1. Simple, easy to interpret and common
2. fast, less effort, less expensive
3. relative risk calculations possible
4. estimates of prevalence possible
5. can explore many hypotheses regarding multiple factors and outcomes

Front 7

Disadvantages of a Cross sectional design?

Back 7

1. not conclusive, you can't prove proper time sequence between exposure and disease.
2. can't calculate incidence
3. large samples needed
4. non-response bias

Front 8

What are the characteristics of Case control studies?

Back 8

1. Identify those with disease first (case)
2.Identify a comparison group (controls)
3. Ascertain and compare factor exposure histories of both groups.

Front 9

What are some related factors to Case Control study designs?

Back 9

1. Retrospective study design
2. used to test hypotheses

Front 10

How do you choose cases for a Case control study?

Back 10

1. definite diagnostic criteria
2. Determine source of cases
3. Incidence or prevalence cases
4. must be representative of those with the diseas

Front 11

How do you choose controls for a Case control study?

Back 11

1. The major methodological problem is finding appropriate comparison subjects.
2. Must come from the same source as cases. (Berksonian Bias)
3. Must be representative of those without the disease.

Front 12

What is matching in a Case Control study?

Back 12

A technique in which controls are chosen who have the same characteristics as the cases

Front 13

What are characteristics of Matching?

Back 13

1. To reduce confounding factors
2. Group or individual matching
3. Level of "closeness" of a match
4. Choosing variables on which to match
5. Determine the number of variables on which to match.
6. Matched variables not included in analysis.

Front 14

What are the advantages of a Case Control?

Back 14

1. More convincing evidence of causality
2. Fast, less expensive
3. Few subjects needed
4. good for rare diseases
5. can study many factors

Front 15

What are some disadvantages of a Case Control?

Back 15

1. Likely confounding
2. recall bias
3. non-response bias
4. Can't get relative risk
5. can't get prevalence rate
6. can't get incidence rate

Front 16

What are the sequence of a Cohort design?

Back 16

1. Choose cohort who have factor, but are not ill.
2. Choose comparison group (optional)
3. Track over time to determine disease rates in the two groups

Front 17

How do you choose cohort's?

Back 17

1. Current of historical exposure
2. Define exposure
3. Must be representative of those exposed
4. Must be free of the disease(s) under study

Front 18

Choosing a comparison group in a cohort study?

Back 18

1. Internal or external
2. Comparable to cohort group
3. Also must be free of the disease(s) under study

Front 19

What is required in a follow-up cohort study?

Back 19

1. Requires co-operation of subjects
2. Followed for long period of time
3. Many outcomes can be observed

Front 20

Advantages of a Cohort study?

Back 20

1. Most convincing and valid
2. Examines many outcomes
3. Can calculate incidence
4. Can calculate relative risk

Front 21

Disadvantages of a cohort study?

Back 21

1. Attrition
2. Longer time (more expensive)
3. Large numbers needed
4. Observation bias

Front 22

What is a cause?

Back 22

1. Merriam-Webster Dictionary: Something that brings about a result especially a person or thing that is the agent of bringing something about
2. KJ Rothman: An event, condition, or characteristic without which the disease would not have occurred
3. M Susser: Something that makes a difference

Front 23

What are the five things to consider pertaining to "association"?

Back 23

1. Could the association be due to chance
2. Could the association be due to bias
3. Could the association be due to confounding
4. To whom does the association apply (representativeness)
5. Does the association represent a cause & effect relationship

Front 24

Characteristics of a "cause"

Back 24

1. precede the effect (proximate vs. distant)
2. Can be either host or environmental factors (e.g., characteristics, conditions, actions of individuals, events, natural, social or economic phenomena)
3. Positive (presence of a causative exposure) or negative (lack of a preventive exposure)

Front 25

What is the historic development of theories of causation?

Back 25

1. Divine retribution; imbalance in body humors caused by air, water, land, stars; spontaneous generation
2. Miasma: Disease transmitted by miasmas or clouds clinging to earth’s surface
3. Germ Theory of Disease and Henle-Koch Postulates:
Most important postulate is that the microorganism must always be found with the
disease. This postulate embodies the idea of specificity of a cause. That is, a one to one relationship between an exposure and a disease.
4. Web of Causation
A paradigm for the causes of chronic diseases. Most important shift from Henle-Koch Postulates is the idea of multiple causes. Postulates were also revised for establishing causation in chronic diseases.
5. Recent Controversies
Causation cannot be established. Causal criteria should be abandoned.

Front 26

General model of causation: sufficient cause

Back 26

A set of conditions without any one of which the disease would not have occurred. (This is one whole pie.)

Front 27

General model of causation: Component cause:

Back 27

Any one of the set of conditions which are necessary for the completion of a sufficient cause. (This is a piece of the pie.)

Front 28

General model of causation: Necessary cause

Back 28

A component cause that is a member of every sufficient cause

Front 29

Attributes of a causal pie

Back 29

1. Completion of a sufficient cause is synonymous with occurrence (although not necessarily diagnosis) of disease.
2. Component causes can act far apart in time.
3. A component cause can involve the presence of a causative exposure or the lack of a preventive exposure.
4. Blocking the action of any component cause prevents the completion of the sufficient cause and therefore prevents the disease by that pathway

Front 30

Causal guidelines suggested by Sir Ab Hill: Step one

Back 30

Strength of the Association:
The larger the association, the more likely the exposure is causing the disease.

Example: Relative risk of lung cancer in smokers vs. non-smokers = 9; Relative risk of lung cancer in heavy vs. non-smokers = 20

Front 31

Causal "guidelines" suggested by Sir AB Hill: Step two

Back 31

Consistency
The association is observed repeatedly in different persons, places, times, and circumstances.

Replicating the association in different samples, with different study designs, and different investigators gives evidence of causation.
Example: Smoking has been associated with lung cancer in at least 29 retrospective and 7 prospective studies.

Note: Sometimes there are good reasons why study results differ. For example, one study may have looked at low level exposures while another looked at high level exposures.

Front 32

Causal "guidelines" suggested by Sir AB Hill: Step three

Back 32

Specificity

A single exposure should cause a single disease.

This is a hold-over from the concepts of causation that were developed for infectious diseases. There are many exceptions to this.

Front 33

Causal "guidelines" suggested by Sir AB Hill: Step four

Back 33

Temporality

The causal factor must precede the disease in time.

This is the only one of Hill's criteria that everyone agrees with.
Prospective studies do a good job establishing the correct temporal relationship between an exposure and a disease.

Example: A prospective cohort study of smokers and non-smokers starts with the two groups when they are healthy and follows them to determine the occurrence of subsequent lung cancer.

Front 34

Causal "guidelines" suggested by Sir AB Hill: Step five

Back 34

Biological gradient

A “dose-response” relationship between exposure and disease. Persons who have increasingly higher exposure levels have increasingly higher risks of disease.

Example: Lung cancer death rates rise with the number of cigarettes smoked.

Some exposures might not have a "dose-response" effect but rather a "threshold effect" below which these are no adverse outcomes.

Front 35

Causal "guidelines" suggested by Sir AB Hill: Step six/seven

Back 35

Plausibility / Coherence

Biological or social model exists to explain the association. Association does not conflict with current knowledge of natural history and biology of disease.

Example: Cigarettes contain many carcinogenic substances

Many epidemiologic studies have identified cause-effect relationships before biological mechanisms were identified. For example, the carcinogenic substances in cigarette smoke were discovered after the initial epidemiologic studies linking smoking to cancer.

Front 36

Causal "guidelines" suggested by Sir AB Hill: Step eight

Back 36

Investigator-initiated intervention that modifies the exposure through prevention, treatment, or removal should result in less disease.

Example: Smoking cessation programs result in lower lung cancer rates.

Provides strong evidence for causation, but most epidemiologic studies are observational

Front 37

Causal "guidelines" suggested by Sir AB Hill: Step nine

Back 37

Analogy

Has a similar relationship been observed with another exposure and/ or disease?

Example: Effects of Thalidomide and Rubella on the fetus provide analogy for effects of similar substances on the fetus

Front 38

What are the types of standardizing or adjusting?

Back 38

1. Stratified approach – Specific rates

2. Simple comparison with standard – Standardized Mortality Ratio

3. Direct (age) adjustment

4. Statistical adjustment – multivariate analysis

Front 39

What is a crude rate?

Back 39

number of deaths / population * 100,000

Front 40

Why is age adjustment important?

Back 40

Allows for the comparison of data from populations of different age distributions
In different counties
Over time (trends)

Front 41

Why would you use a 2000 population standard?

Back 41

All mortality data since 1999 will be age-adjusted using the 2000 standard population
The HP2010 objectives will use age-adjusted rates based on the 2000 standard population

Front 42

What are the other Benefits of Using the 2000 Standard Population

Back 42

CDC Wonder now allows for age-adjustment using the 2000 standard population
NCHS and the Chronic disease section of CDC will use the same standard for age-adjustments

Easier to explain to the public
Will no longer need to explain why some adjustments use the 1940 standard and others use the 1970 standard
The rates adjusted to the 2000 standard million will be closer to the crude rate

Front 43

'Trohoc" means...

Back 43

This disparaging term was given to case-control studies because their logic seemed backwards (trohoc is ?? spelled backwards) and they seemed more prone to bias than other designs.
No basis for this derogation.
Case-control studies are a logical extension of cohort studies and an efficient way to learn about associations.

Front 44

General definition of Case-Control study.

Back 44

A method of sampling a population in which cases of disease are identified and enrolled, and a sample of the population that produced the cases is identified and enrolled. Exposures are determined for individuals in each group.

Front 45

When is it desirable to conduct a case-control study?

Back 45

When exposure data are expensive or difficult to obtain
- Ex: Pesticide study described earlier

When disease has long induction and latent period
- Ex: Cancer, cardiovascular disease

When the disease is rare
Ex: Studying risk factors for birth defects

When little is known about the disease
Ex. Early studies of AIDS

When underlying population is dynamic
Ex: Studying breast cancer on Cape Cod

Front 46

What kinds of cases should you use for a Case-Control study?

Back 46

Incident cases

Front 47

How can the SARS outbreak be described

Back 47

When SARS was first introduced, we knew the outcome, so we wanted to look at lots of risk factors to see what the risk factors were.

Front 48

What Kind of Cases To Use for a Case-Control study?

Back 48

Always use incident cases
Closer in time to action of the etiologic agent
Determinants of survival are excluded
Reduced confusion between cause and effect of disease, i.e. changes in smoking or drinking habits due to an illness

Front 49

What do cases give you mathematically?

Back 49

Cases give you the numerators of the rates of disease in exposed and unexposed groups being compared:

Rate of disease in exposed: a/?

Rate of disease in unexposed: c/?

Front 50

What would you have if you were doing a cohort study?

Back 50

The denominators! If this were a cohort study, you would have the total population (if you were calculating cumulative incidence) or total person-years (if you were calculating incidence rates) for both the exposed and non exposed groups, which would provide the denominators for the compared rates.

Front 51

Where do you get the information for the denominators in a case control study?

Back 51

THE CONTROLS

A case-control study can be considered a more efficient form of a cohort study.

Cases are the same as those that would be included in a cohort study.

Controls provide a fast and inexpensive means of obtaining the exposure experience in the population that gave rise to the cases.

Front 52

What is a control?

Back 52

Definition: A sample of the source population that gave rise to the cases.

Purpose: To estimate the exposure distribution in the source population that produced the cases.

Front 53

How do you select controls?

Back 53

General population controls

Most often used when cases are selected from a defined geographic population

Sources: random digit dialing, residence lists, drivers’ license records

Example: Upper Cape Cancer Study

Front 54

What are the advantages of selecting controls?

Back 54

Advantages of general population controls:

Because of selection process, investigator is usually assured that they come from the same base population as the cases.

Front 55

What are the disadvantages of selecting controls?

Back 55

Disadvantages of general population controls

Time consuming, expensive, hard to contact and get cooperation; may remember exposures differently than cases

Front 56

How do you obtain exposure History?

Back 56

Accessing data
Accuracy of self reported data, confidence in the data
Recall Bias – those with a health problem recall health related events/exposures better
Response Bias – those who respond are different from those who do not

Front 57

Berksonian Bias is?

Back 57

If hospital controls are NOT from the same source as the cases, results in a selection bias

Front 58

Advantages to Hospital controls are?

Back 58

Same selection factors that led cases to hospital led controls to hospital

Easily identifiable and accessible (so less expensive than population-based controls)

Accuracy of exposure recall comparable to that of cases since controls are also sick

More willing to participate than population-based controls

Front 59

Disadvantages to Hospital controls are?

Back 59

Since hospital based controls are ill, they may not accurately represent the exposure history in the population that produced the cases

Hospital catchment areas may be different for different diseases

Front 60

What illnesses make good hospital controls?

Back 60

Those illnesses that have no relation to the risk factor(s) under study

Example: Should respiratory diseases be used as controls for a study of smoking and myocardial infarction? Do they represent the distribution of smoking in the entire population that gave rise to the cases of MI?

Front 61

Selecting special control groups?

Back 61

Special control groups like friends, spouses, siblings, and deceased individuals.

These special controls are rarely used.
Some cases are not able to nominate controls because they have few appropriate friends, are widowed, or are only or adopted children.
Dead controls are tricky to use because they are more likely than living controls to smoke and drink

Front 62

Important consideration for selecting controls: “the would criterion”

Back 62

Review: Controls are a sample of the source population that gave rise to the cases. Purpose is to provide information on the exposure distribution in the source population.

When selecting a control group consider the “WOULD CRITERION”: If a member of the control group actually had the disease under study WOULD he/she end up as a case in your study? Answer should be YES.

Front 63

Fill in the blank...

Because controls are a sample of the _____ that produced the cases, _____ of the total population is often unknown

Thus...

Back 63

population; size

Thus...you can’t get a cumulative incidence or incidence rate of disease or
calculate the measures of association using the methods that we have learned. Instead you get a number called an odds which will function as a rate

Front 64

Analysis of control studies.

Back 64

Definition of odds: the ratio of the probability of an event occurring to that of it not occurring

Example: Probability of getting a heads on one coin toss = ½ = .50. Probability of NOT getting a heads on one coin toss = ½ = .50. Odds of getting a heads on a coin toss = .5/.5 = 1:1

Front 65

Strengths of a case control study

Back 65

Efficient for rare diseases and diseases with long induction and latent period.
Can evaluate many risk factors for the same disease. So, good for diseases about which little is known

Front 66

Weaknesses of case control study

Back 66

Inefficient for rare exposures
Vulnerable to bias because of retrospective nature of study
May have poor information on exposure because retrospective
Difficult to infer temporal relationship between exposure and disease

Front 67

TP=true positive

Back 67

They had the disease

Front 68

FP=false positive

Back 68

Tested positive, but did not have the disease

Front 69

FN=false negative

Back 69

tested negative, but had the disease

Front 70

TN=true negative

Back 70

tested negative, but does have the disease

Front 71

Sensitivity

Back 71

probability that you have a positive test

P[+ test/disease]

=TP/TP+FN

Front 72

Specificity

Back 72

probability of a negative test given there is no disease

[P - test/no disease]

TN/TN=FP

Front 73

Predictive Value (positive)

Back 73

P [disease / a positive test]

TP/TP+FP

Front 74

Predictive Value (negative)

Back 74

P [No diesease/ - negative test]

=TN/TN+FN

Front 75

prevalence

Back 75

(a+c)/(a+b+c+d)

Front 76

accuracy

Back 76

(a+b)/(a+b+c+d) (usually compared to the gold standard)

Front 77

False Positive Rate

Back 77

b/(b+d)

Front 78

False Negative Rate

Back 78

c/(a+c)

Front 79

Specificity+false positive rate =

Back 79

1

Front 80

Sensitivity + false negative rate =

Back 80

1

Front 81

Draw out a Measure of Validity table

Back 81

True Diagnosis

Positive A B PPV
Negative C D NPV
Total sens. spec TOTAL

Front 82

What is a cross-sectional study?

Back 82

Also termed prevalence study; it is a type of descriptive study designed to estimate the prevalence of a disease or exposure.

Front 83

What is a cohort?

Back 83

A group of individuals who share an exposure in common and who are followed over time; one example is an age cohort.

Front 84

What is a cohort study?

Back 84

A type of study that collects data and follows a group of subjects who have received a specific exposure. The incidence of a specific disease or other outcome of interest is tracked over time. The incidence i the exposed group is compared with the incidence in groups that are not exposed, have different levels of exposure, or have different types of exposures.

Front 85

What is the definition of Sensitivity?

Back 85

the ability of the test to identify correctly all screened individuals who actually have the disease. It is defined as the number of true positives divided by the sum of true positives and false negatives.

Front 86

What is the definition of Specificity?

Back 86

the ability of the test to identify only nondiseased individuals who actually do not have the disease. It is defined a the number of true negatives divided by the sum of false positives and true negatives.

Front 87

What is the definition of Predictive Value

Back 87

the proportion of individual screened positive by the test who actually have the disease.

Front 88

What is negative predictive value?

Back 88

an analogous measure for those screened negative by the test.

Front 89

What is the definition of reliability?

Back 89

Precision; the measuring of an instrument to give consistent results on repeated trials.

Front 90

What is the definition of validity?

Back 90

Accuracy; the ability of a measuring instrument to give a true measure.

Front 91

What is the key issue in community health assessment?

Back 91

Communtiy

Front 92

The idea is not competition, but ___________

Back 92

Collaboration; collaborative information

Front 93

When you're in a metropolitian area, you will see health facilities doing what?

Back 93

collaborating health assessment

Front 94

What should you include in assessing community life and needs?

Back 94

Everything...religion, education....everything!

Front 95

What should you emphasize in doing a community assessment?

Back 95

Community Ownership

Once the data is available, communities will become aware of their health problems.

Front 96

Confidence Intervals: what does a 95% estimate

Back 96

It estimates the "true" population 95% of the time

Front 97

How are confidence intervals influenced?

Back 97

by the validity of the data and the sample size.

Front 98

P-value is

Back 98

the probability that the findings observed could have occurred by chance alone.

Front 99

True/False

Lack of statistical significance may be a reflection of insufficient statistical power to detect a meaningful association.

Back 99

True