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poplhlth exam prep > GATE Frame > Flashcards

GATE Frame Flashcards

1
Q

Numerator

A

Number of people from study population in whom dis-ease occurs

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2
Q

Denominator

A

Number of people in a study

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3
Q

Population

A

Any group of people who share a common factor

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4
Q

Quantified

A

Data that can be counted

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5
Q

Two categories of quantified data?

A

Categorical

Numerical

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6
Q

Non-observable event

A

Can’t easily observe so you measure at a point in time

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7
Q

Event

A

Counting as it occurs (eg road traffic accidents)

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8
Q

Occurrence

A

The transition from a non-diseases state to a diseased state

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9
Q

GATE

A

Graphic approach to epidemiology

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10
Q

What is dis-ease?

A

Any health-related event (death/ill health easier to measure than well-being)

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11
Q

What is epidemiology?

A

The study of how much disease

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12
Q

Occurrence of disease calculation?

A

Numerator/denominator

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13
Q

Explain gate diagram

A 
Triangle= participants 
Circle= EG/CG
Square= numerators (disease outcomes)
Time= vertical and horizontal
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14
Q

Exposure group occurrence equation

A

EGO = a/EG

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15
Q

Comparison group occurrence equation?

A

B/CG

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16
Q

Can numerical measures be recorded as categories?

A

Yes

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17
Q

Example of categorical measures?

A

High vs low salt intake

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18
Q

Examples of numerical measures

A

Average (mean)/ EG

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19
Q

Incidence?

A

Number of onsets of dis-ease occurring during a period of time (eg raindrops)

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20
Q

Can incidence be observed as it occurs?

A

Yes

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21
Q

What type of quantified measure is incidence?

A

Categorical

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22
Q

How is incidence normally written?

A

As a percentage of people with the disease in a specific period

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23
Q

Equation of incidence

A

A/EG during time

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24
Q

Example of high incidence, low prevalence?

A

Flu

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25
Q

Example of low incidence, high prevalence

A

Obesity

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26
Q

Prevalence?

A

The number of people with a disease at one point in time

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27
Q

When is prevalence used?

A

When the transition from non-diseases to diseased is not easily observable

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28
Q

How do people leave the prevalence pool?

A

By death or cure

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29
Q

What does prevalence assess?

A

The amount of disease (burden) at a point in time

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30
Q

What is prevalence not useful for?

A

Identifying the cause

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31
Q

Prevalence calculation?

A

A/EG at a point in time

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32
Q

Two types of prevalence?

A

Point (at one point)

Period (in a set time frame looking back)

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33
Q

Calculations to compare disease between groups?

A

Risk ratio

Risk difference

34
Q

Relative risk?

A

Risk ratio (ratio of occurrence)

35
Q

Relative risk/risk ratio/RR equation?

A

EGO/CGO

36
Q

Absolute risk?

A

Risk difference (difference between occurrences)

37
Q

Risk difference equation?

A

EGO-CGO with units

38
Q

No effect value RR?

A

1

39
Q

No effect value RD?

A

0

40
Q

Relative risk increase/reduction?

A

+- from 1 x 100

41
Q

Odds ratio?

A

A/b /c/d

42
Q

When is odds ratio more appropriate?

A

When disease becomes more common as two relative estimates increase

43
Q

Types of error?

A

Random

Non-random

44
Q

Other names for non-random error

A

Bias
Systematic errors
Validity problems

45
Q

Define RAMBOMAN

A 
Recruitment
Allocation
Maintenance 
Blind
Objective 
Measurement 
Analysis
46
Q

Two types of recruitment errors?

A

External validity error: study findings are not applicable

Selection bias

47
Q

Example of allocation error?

A

Confounding

48
Q

What study avoids confounding?

A

RCTs

49
Q

What do analyses involve?

A

Adjusting for confounding etc, with stratified analysis, and checking risk analyses

50
Q

What causes random error?

A

Chance

51
Q

Three types of random error

A

Random sampling error (will never be 100% representative)
Random measurement study (our ability to measure factors in the same way is subject to difference
Randomness in human nature

52
Q

How do we estimate random error?

A

With a 95% confidence interval

53
Q

Definition of a 95% confidence interval?

A

A range of values of a particular measure derived from a single study that is likely to include the true value in the underlying population

54
Q

What does a wider CI mean?

A

More random error

55
Q

Will a 99% or 95% CI have a wider interval?

A

99%

56
Q

How would you write a 95% CI?

A

There is a 95% probability that the true value of EGO in the whole population from which the study participants were recruited lies between 8 and 10

57
Q

If EGO and CGO confidence intervals do not overlap we call it?

A

Statistical significance

58
Q

What happens is the CI for RR or RD crosses the no effect line?

A

There’s too much random error to determine if there’s a real difference between EGO and CGO

59
Q

What does width of CI depend on?

A

Number of events in the study

60
Q

What is meta analysis?

A

Combining studies to generate a summary estimate of effect (and alternative to a large study)

61
Q

What type of study often uses meta analysis?

A

RTCs

62
Q

Study objective of RCTs?

A

effects of different interventions (exposure) on disease incidence in different groups

63
Q

Main application of RCTs?

A

Studying the effect of interventions (ie new therapies)

64
Q

Main design features of RCTs?

A

Longitudinal
Experimental
Participants randomly allocated to either study exposure or comparison exposure and dis-ease outcomes measured during a follow-up period

65
Q

Main strength of RCTs

A

Randomisation minimises confounding

66
Q

Main weaknesses of RCTs

A

Ethical limitations
Logistically difficult, long term follow up difficult and costly
Large studies expensive so usually too small (random error is an issue)
Maintenance error common

67
Q

Study objective of cohort studies

A

To investigate associations (effects) between risk/prognostic factors (exposures) and disease incidence in different groups of individuals

68
Q

Main application of cohort studies

A

Studying cause of dis-ease incidence or the effects of interventions

69
Q

Main design features of a cohort study

A

Longitudinal
Observational (non-experimental)
Participants allocated to exposure and comparison by measurement and disease outcomes measured during follow up

70
Q

Main strength of cohort study

A

Cheaper than RCTs
Exposure measured before outcome
Avoids recall bias
Provides clear time sequence between exposure and disease outcome

71
Q

Main weakness of cohort study

A

Confounding

Maintenance error common in long term situation

72
Q

usual objective of cross sectional studies

A

To measure disease prevalence in defined populations. To investigate associations between exposure and disease prevalence

73
Q

Main application of cross sectional studies

A

Measuring burden of disease in different populations

74
Q

Main design features of cross sectional study

A

Observational

Participants located to EG/CG by measurement and outcome is measured at the same time

75
Q

Main strengths of cross sectional study

A

Cheap
Quick
Best for assessing burden/prevalence of a population
No maintenance error as no follow up

76
Q

Main weaknesses of cross sectional study?

A

Uncertain time sequence (possible reverse causality) limits interpretation of cause and effect
Confounding common

77
Q

Study objective of ecological study

A

To investigate associations between exposures and disease prevalence or incidence in different populations

78
Q

Main application ecological study

A

Studying the causes of disease incidence and prevalence

79
Q

Main design feature of ecological study

A

Longitudinal or cross-sectional
Non-experimental or experimental
Exposure and comparison allocated to groups rather than individuals

80
Q

Main strengths of ecological studies

A

Cheap and quick
Useful when majority of some populations are exposed and others aren’t
Efficient for rare outcomes

81
Q

Main weakness of ecological studies

A

Confounding very common

poplhlth exam prep (3 decks)

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