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

Module 1 (Lectures 1-11) Flashcards

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
Q

Incidence involves what type of data? (numerical / categorical)

A

Only involves counting categorical disease events

26
Q

Prevalence involves what type of data? (numerical / categorical)

A

Either counting categorical disease events or measuring numerical disease states

27
Q

Cohort study (time and incidence / prevalence)

A

exposures measured, then disease events counted after a period of time, generally measure incidence, but can measure prevalence (at any point)

28
Q

Cross-sectional study (time and incidence / prevalence)

A

exposures and outcome measured at same point in time, only prevalence

29
Q

What determines incidence?

A

Depends only on number of events during a specified time period

30
Q

What determines prevalence?

A

Can count ‘incidence drizzle’ but miss out on ‘death drips’ and ‘cure cloud’

31
Q

Incidence (2 strengths, 1 weakness)

A

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
Q

Prevalence (2 weaknesses, 1 strength)

A

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
Q

Epidemic

A

occurrence of disease in excess of normal

34
Q

Pandemic

A

epidemic occurring in many countries

35
Q

two types of numerator when measuring prevalence

A

measure at one point in time (eg obesity) or measure by looking back (eg asthma)

36
Q

Randomly controlled trials

A

Like cohort studies, except participants are randomly allocated to EG or CG

37
Q

Double blind

A

neither participants nor investigators know which intervention was given to which participant

38
Q

two reasons why it is often not possible to do RCT

A

unethical or impractical

39
Q

Risk Difference, and if EGO = CGO

A

EGO - CGO, RD is 0

40
Q

Risk Ratio (Relative Risk), and if EGO = CGO

A

EGO ÷ CGO, RR is 1

41
Q

units of RD

A

has units eg deaths / 100 people / 5 years

42
Q

units of RR

A

no units

43
Q

Random Error

A

if error occurs by chance

44
Q

Non-Random Error

A

errors due to poor study design, processes or measurement

45
Q

RAMBOMAN

A

Recruitment, Allocation, Maintenance, Blind or Objective Measurement, ANalyses

46
Q

Questions to think about for Recruitment

A

are participants representative of whole population? what was the response rate?

47
Q

Questions to think about for Allocation

A

was allocation to EG and CG successful / accurate? were EG and CG similar or was adjustment needed?

48
Q

Questions to think about for Maintenance

A

did participants remain in initial exposure group? (most danger in long term studies)

49
Q

Questions to think about for Blind or Objective Measurement

A

was there blind or objective measurement? will validity be affected by how well EG and CG were measured?

50
Q

Confounding - what is it and how to deal with it

A

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
Q

How to reduce random error

A

Repeating

52
Q

Random Measurement error

A

participants are always moving, so identical measurements of exposures / outcomes in same / similar people can change

53
Q

Random Sampling Error

A

cannot study everybody, only a sample, so every study will have a different EGO / CGO

54
Q

95% Confidence Level (good enough definition)

A

about a 95% chance that the true value in a popl lies within the 95% confidence level (assuming no non random error)

55
Q

95% Confidence Level (actual definition)

A

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
Q

RD is statistically significant when ____

A

CI of EGO and CGO don’t overlap, if RD doesn’t overlap zero

57
Q

how to reduce random sampling error?

A

use a bigger sample

58
Q

how to reduce random measurement?

A

do more measurements

59
Q

meta-analysis

A

combination of 95% CI in 4 or more identical studies

60
Q

How many parts to epidemiological studies?

A

usually 5, sometimes only 4 ( no comparison group)

61
Q

Cross-Sectional Studies (3 pros, 1 con)

A

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
Q

Randomised Control Trials (3 Pros, 1 Con)

A

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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