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Pop Health 111 > Epidemiology, Gate frames & Incidence/Prevalence > Flashcards

Epidemiology, Gate frames & Incidence/Prevalence Flashcards

1
Q

What is the goal of epidemiology & basic equation used

A

Studying disease occurance in a population over time

(no. of ppl with disease) / (No. of ppl in the population)

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2
Q

What does numerator and denominator represent

A

Numerator is those with disease and prevalence is the study population sharing similar characteristics

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3
Q

Components of the Gate frame

A

Triangle - study population
Circle - EG and CG
Square - EGO and CGO
O - Outcome in square
Horizontal - One time measurement
Vertical arrow - Overtime measurement

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4
Q

What do you do when a numerical measure isn’tn converted into a categorical?

A

Calcultae the mean or median excluding c or d (No disease people from both EG and CG) as this assumes everyone has a disease

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5
Q

EGO and CGO acronym meaning

A

Exposure group occurance and Comparison group occurance

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6
Q

Incidence components

A

Easy to observe disease events measured over time via categorical measurments e.g. death

Clean measure but hard to measure as observation occurs overtime

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7
Q

Prevalence components

A

Disease occurance measured at one point in time when transition from non diseased to diseased is blurry viz categorical and numerical measures

Dirty measure (Affected by incidence, death and cure)

Easy to measure as it happens at one point in time

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8
Q

Prevalence pool

A

Leftover drizzle from incidence and size depends on drizzle rate and loss to death and cure

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9
Q

Prevalence pool

A

Leftover drizzle from incidence and size depends on drizzle rate and loss to death and cure

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10
Q

Direction of arrows for one point in time measurement

A

Horizontal

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11
Q

Direction of arrow for longitudinal study

A

Vertical

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12
Q

Direction of arrow for timeframe from the past - Prevalence study

A

Top left corner

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13
Q

Association (Comparing disease measures)

A

Intitialdisease occurance should be estimates of association

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14
Q

Relative risk

A

Ratio of occurance with no units

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15
Q

Relative risk = 1

A

No effect value - there’s no difference in the effect of E and C on outcome

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16
Q

Equation for Relative risk > 1

A

Relative risk increase = (RR -1) x 100

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17
Q

Equation for relative risk < 1

A

Relative risk reduction = (1-RR) x 100

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18
Q

Absolute risk difference

A

Difference in disease occurance with units and contains more information than RR

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19
Q

Absolute risk difference = zero

A

No risk difference thus no difference between EGO and CGO

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20
Q

Absolute risk difference < 0

A

Ideal risk difference

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21
Q

Absolute risk reduction

A

Absolute risk is lower in EG

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22
Q

Absolute risk increase

A

Absolute risk is greater in EG

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23
Q

Randomised control trial key components

A

Study the effects of ethical and practical treatments
by random allocation into EG and CG via experiments

Rarely used to discover risk factors instead more in placebo studies

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24
Q

Long term RCT

A

Harmful treatment can be used as the test is now only observational but difficult to do well due to maintenance

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25
Randomised control trial strengths
- minimise cofounding - measures incidence and prevalence - ensures participants in EG and CG are similar
26
Randomised control trial weaknesses
- Hard to recruit representative eager participants - A-lot of maintenance error - Very expensive and too small - Too small produce insufficient results due to expensive conduct
27
Non random error
Errors in study design, poor ramboman
28
Recruitment error
Study population representativness/elgibility - May be over or under representation
29
Selection bias
Recruitment error EG is recruited from a very different group to CG
30
Cofounding error
Recruitment error Studies exposures mixed with external factors effecting outcome causing a bias
31
Non response bias
Recruitment error Large proportion of eligible population don't respond and if 70% of the responders are significantly different to population
32
Allocation error
How participants were allocated into EG and CG - measurment or randomly
33
Measurement error
Allocation error EG and CG is measured incorrectly leading to wrong allocation
34
Allocation by measurment
Participants are measured objectively or subjectively to be allocated
35
Maintenance error
Mainitaining participants in alloacted groups - occurs more often in long term studies as patients can be lost to cure, death, leaving study etc
36
Compliance
Maintenance error Percentage of participants remaining in allocated group
37
Contamination
Maintenance error Percentage of participants crossing over allocatedn groups
38
Co- intervention
Maintenance error Did EG and CG recieve unequal interventions in follow up
39
Blinding
Reduces cofounding by preventing personal interpretation - single or double Objective outcomes don't need blinding
40
Adjustment
Dividie participants into strata and compare differing groups to reduce cofounding
41
Random allocation
randomly allocate into EG and CG
42
Random error
Biological variation causes participants to be moving targets
43
Random sampling error
Smaller sample the less representative of population Every sample is the best estimate of the truth of a population
44
Where does random error occur
EGO, CGO , RR and RD
45
95% confidence interval
Measure of the range and size of random error 95% chance the true value of population lies within the CI The wider the interval the more random error = 99% CI
46
Statistical signifiance
When EGO and CGO confidence intervals dont overlap the no effect line
47
RD doesn't cross no effect line
RD is statisticaly significant
48
RD overlaps no effect line
No statsitical significance in EGO AND CGO usually due too to much random error to determine a real difference
49
RR overlaps 1
No statistical signficance
50
Reducing random error
Get bigger samples to narrow the Confidence interval
51
Regression to the mean
Extreme events are often due to chance thus repeating them eventually gives less extreme results closer to the mean
52
Meta anaysis
Combine many small good studies to form one big meta study - Used especially in RCT when too much random error blurs effects of study
53
Cohort study
For unethical and unpractical studies done overtime to measure incidence and prevalence
54
Cohort study weakness
Cofounding and maintenance error
55
Cohort study strengths
- Easier to recruit representative sample - Cheaper, larger and easier - Little measurment and random error
56
Cross sectional study
Exposures and outcome measured at once for prevalence observational study
57
Cross sectional study strengths
- Easiest to recruit representative sample - More cheap and large - Ethical to study harmful treatment - No maintenenance error
58
Cross sectional study weaknesses
- Cfounding common - Reverse causality - Did outcome or exposure come first
59
Ecological study
Participants are countries thus many EG DOne via surveys usually Longitudinal or cross sectional
60
Ecological study strengths
- Large thus low random error - Very cheap - Based on already published study
61
Ecological study weaknesses
- Often unadjustable cofounding
62
Descriptive study
Dsecribes frequency of health behaviour, risks and outcomes
63
Analytical study
Analyses descriptive study results
64
Measures incidence AND prevalence
RCT and cohort studies
65
Only measures prevalence
Cross sectional studies
66
Individual participation studies
- RCT - Cohort - Cross sectional
67
Ecological studies
- RCT - Cohort - Cross sectional
68
SImilarties in study designs
- GATE and PECOT - Rambom - Random error
69
Differences in study desgins
- Not all involve EGO and CGO calculation

Pop Health 111 (5 decks)

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