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POPLHLTH 111 > Module 1 (Lectures 1-11) > Flashcards

Module 1 (Lectures 1-11) Flashcards

(62 cards)

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1
Q

Clinical medicine: focus, education, rights

A

Individual, biomedicine model, cure>prevention, individual rights of patient

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2
Q

Popl hlth: focus, education, rights

A

Popl (max benefit for max no. of people) epidemiology, human rights

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3
Q

Epidemiology starts with _____

A

Describing a popl

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4
Q

Frequency of a disease =

A

No. of cases of disease ÷ no. of people in popl

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5
Q

Why measure freq. of disease in diff. popl?

A

To help identify causes / determinants

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6
Q

Population

A

A group of people who share one or more common features

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7
Q

Why do we need age standardisation?

A

For meaningful comparison

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8
Q

Epidemiology (definition)

A

The study of the FREQUENCY (AND CAUSES) of disease in a POPULATION(s) at ONE POINT or over a PERIOD OF TIME

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9
Q

Epidemiology = (formula)

A

Numerator (disease) ÷ denominator (population) ÷ time

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10
Q

Describe the gate frame

A

Triangle - no of participants/populations. Circle - divided into exposure group and comparison group. Square - outcome. Arrows - time.

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11
Q

Participants

A

Triangle starts broad, gets narrower eg study setting -> eligible popl-> participants

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12
Q

EG and CG are _____ (what part of formula?)

A

Denominators

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13
Q

Disease outcomes are _____ (what part of formula?)

A

Numerators

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14
Q

Exposure Group Occurence (EGO) =

A

a ÷ EG

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15
Q

Comparison Group Occurence (CGO) =

A

b ÷ CG

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16
Q

Ecological cohort study

A

‘Popl’ of countries

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17
Q

Time is measured ____ or ____

A

Over a period of time or at one point in time

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18
Q

Incidence (definition and EGO / CGO formula)

A

When no. of disease events that occur are counted OVER A PERIOD IF TIME. E/CGO = a/b ÷ E/CG ÷ T

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19
Q

Prevalence (definition and EGO / CGO formula)

A

When no. of people with disease are counted AT ONE POINT IN TIME. E/CGO = a/b ÷ E/CG

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20
Q

Occurence / Event

A

When move from state of no disease to state of disease

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21
Q

If it is easy to measure when disease occurs, usually measure ____

A

Incidence

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22
Q

If it is hard to observe when disease occurs, then we measure if it has occurred. We measure ____

A

Prevalence

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23
Q

Numerical Data

A

Described in numbers eg heart rate

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24
Q

Categorical data

A

Described in categories eg death (yes/no)

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25
Incidence involves what type of data? (numerical / categorical)
Only involves counting categorical disease events
26
Prevalence involves what type of data? (numerical / categorical)
Either counting categorical disease events or measuring numerical disease states
27
Cohort study (time and incidence / prevalence)
exposures measured, then disease events counted after a period of time, generally measure incidence, but can measure prevalence (at any point)
28
Cross-sectional study (time and incidence / prevalence)
exposures and outcome measured at same point in time, only prevalence
29
What determines incidence?
Depends only on number of events during a specified time period
30
What determines prevalence?
Can count 'incidence drizzle' but miss out on 'death drips' and 'cure cloud'
31
Incidence (2 strengths, 1 weakness)
Strengths - only determined by disease risk in popl ('clean' measure); includes events (N), population (D) and time (T). Weakness - can be difficult to measure (need to measure events over time)
32
Prevalence (2 weaknesses, 1 strength)
Weaknesses - only includes events (N) and population (D), not time (T); determined by incidence, cure rate and death rate ('dirty' measure). Strength - relatively easy to measure ('stop time' and count)
33
Epidemic
occurrence of disease in excess of normal
34
Pandemic
epidemic occurring in many countries
35
two types of numerator when measuring prevalence
measure at one point in time (eg obesity) or measure by looking back (eg asthma)
36
Randomly controlled trials
Like cohort studies, except participants are randomly allocated to EG or CG
37
Double blind
neither participants nor investigators know which intervention was given to which participant
38
two reasons why it is often not possible to do RCT
unethical or impractical
39
Risk Difference, and if EGO = CGO
EGO - CGO, RD is 0
40
Risk Ratio (Relative Risk), and if EGO = CGO
EGO ÷ CGO, RR is 1
41
units of RD
has units eg deaths / 100 people / 5 years
42
units of RR
no units
43
Random Error
if error occurs by chance
44
Non-Random Error
errors due to poor study design, processes or measurement
45
RAMBOMAN
Recruitment, Allocation, Maintenance, Blind or Objective Measurement, ANalyses
46
Questions to think about for Recruitment
are participants representative of whole population? what was the response rate?
47
Questions to think about for Allocation
was allocation to EG and CG successful / accurate? were EG and CG similar or was adjustment needed?
48
Questions to think about for Maintenance
did participants remain in initial exposure group? (most danger in long term studies)
49
Questions to think about for Blind or Objective Measurement
was there blind or objective measurement? will validity be affected by how well EG and CG were measured?
50
Confounding - what is it and how to deal with it
when exposure is mixed with another factor that is also associated with the outcome; adjustment (do sub studies, with all confounders in one sub study), randomisation
51
How to reduce random error
Repeating
52
Random Measurement error
participants are always moving, so identical measurements of exposures / outcomes in same / similar people can change
53
Random Sampling Error
cannot study everybody, only a sample, so every study will have a different EGO / CGO
54
95% Confidence Level (good enough definition)
about a 95% chance that the true value in a popl lies within the 95% confidence level (assuming no non random error)
55
95% Confidence Level (actual definition)
in 100 identical studies using samples from the same popl, 95/100 of the 95%CI will include the true value of the popl
56
RD is statistically significant when ____
CI of EGO and CGO don't overlap, if RD doesn't overlap zero
57
how to reduce random sampling error?
use a bigger sample
58
how to reduce random measurement?
do more measurements
59
meta-analysis
combination of 95% CI in 4 or more identical studies
60
How many parts to epidemiological studies?
usually 5, sometimes only 4 ( no comparison group)
61
Cross-Sectional Studies (3 pros, 1 con)
Pros - useful for investigating prevalence of risk factor / disease, no maintenance error, relatively easy / cheap / quick. Con - not useful for studying benefits of intervention (confounding, reverse causality)
62
Randomised Control Trials (3 Pros, 1 Con)
Pros - very good if can keep maintenance error low, reduces confounding, if participants blind to intervention maintenance usually similar in EG and CG. Con - in long term studies, maintenance error can be high

POPLHLTH 111 (2 decks)

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