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POPLHLTH 111 > Module 1: Distribution and Determinants of PopHlth > Flashcards

Module 1: Distribution and Determinants of PopHlth Flashcards

1
Q

What is epidemiology

A

The study of frequency/occurrence of dis-ease (N) in populations (D) over a period of time (T)
ALWAYS starts by describing a population, then count the number of cases of dis-ease that occur in the population

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2
Q

Dis-ease frequency aka…

A

Dis-ease occurrence
Dis-ease risk
Dis-ease distribution

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3
Q

Why measure the frequency of dis-ease in different populations?

A

If frequency (distribution) of dis-ease is different between 2 populations, this can help identify the causes (determinants)

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4
Q

How to calculate frequency of dis-ease

A

[Number of cases of disease] / [Number of people in population]

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5
Q

Definition of a population/group

A

A group of people who share one or more common features

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6
Q

Definition of dis-ease

A

Narrow: the absence of death, disease, or disability
Broad: the capacity to do what matters most to you

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7
Q

Numerator and denominator

A

Numerator: cases of disease
Denominator: population

Epidemiology = (N/D) / T

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8
Q

Define GATE

A

Graphical Approach To Epidemiology

A map of all epidemiological studies

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9
Q

What is PECOT

A 
The 5 parts of every epidemiological study
Participants/Population
Exposure group
Comparison group
Outcomes
Time
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10
Q

EG and CG

A

Exposure groups and Comparison groups are denominators for calculating dis-ease occurrence

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11
Q

Which ‘exposure’ can be chosen as EG or CG?

A

Any, as long as you are clear and state which group is which

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12
Q

PECOT: Outcomes

A

a & b (or c & d) are numerators

Mostly use those with dis-ease (a & b)

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13
Q

Goal of epidemiological studies is…

A

To calculate:
Exposure Group Occurrence (EGO) and
Comparison Group Occurrence (CGO)
Effects (RR and RD) in the whole population

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14
Q

Time arrows

A

Down: Over a period of time
Across: At one point in time

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15
Q

Incidence

A

Where the number of dis-ease events that occur are counted forward from a starting point over a period of time

EGO and CGO: incidence measures of occurrence

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16
Q

Prevalence

A

Where the number of people with dis-ease are counted at one point in time

EGO and CGO called prevalence measures of occurrence

Less ‘perfect’ measurement - can lose some incidence rain through cure cloud and death drops

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17
Q

When to use incidence or prevalence

A

Incidence: if easy to observe when dis-ease occurs
Prevalence: if hard to observe when dis-ease occurs, we measure IF it has occurred

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18
Q

Incidence rain drops

A

Each raindrop is a person having a dis-ease event

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19
Q

Prevalence pool

A

If too difficult to measure each raindrop in the drizzle as it falls, measure how much ‘water’ there is in the prevalence pool after the drizzle has fallen

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20
Q

Incidence and prevalence; categorical or numerical measurement?

A

Incidence:
Always involves counting categorical (yes/no) dis-ease EVENTS

Prevalence:
Involves counting categorical dis-ease EVENTS
OR
Measuring numerical dis-ease STATES

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21
Q

Cohort vs cross-sectional studies

A

Cohort - follow over time; can also measure prevalence - either at beginning or any point during the study (e.g. video and taking snapshot)
Cross-sectional - relevant dis-ease events counted at the same time - can only measure prevalence

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22
Q

Video questionnaire

A

Show video of symptom/dis-ease as some diseases may translate differently in different languages

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23
Q

Prevalence - time measured ‘backwards’?

A

Measure a period of time, e.g. if someone has had the symptom within the last 3 months

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24
Q

EG and CG - different dis-ease frequencies?

A

Could be due to medicines/drugs

If prevalence pool:
Some people may have been cured or may have died (cured cloud and death drips)

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25
Q

Randomised control trials (RCTs)

A

Like cohort studies, except participants are allocated random to EG or CG
Ideal study, but only if it’s both ethical and practical
Only done when pretty sure beneficial and not harmful

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26
Q

Benefits of RCTs

A

Participants have equal chance of being allocated to EG or CG, so any differences between the groups are likely to be due to effect of the drug they are given

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27
Q

Unblinded RCT

A

Both patients and investigators know which intervention was given to the patient

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28
Q

Single-blind RCT

A

Only investigators know which intervention was given to which participant

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29
Q

Double-blind RCT

A

Neither participants nor investigators know which intervention was given to which participant
Benefit: investigators can’t accidentally give away any hints to patients

30
Q

Risk difference

A

Difference in risks

EGO - CGO or vice versa

31
Q

Risk difference vs relative risk/risk ratio

A

Relative risk often less useful than risk difference - all decisions should be based on RD not RR alone

32
Q

Relative risk/risk ratio

A

Ratio of risks

EGO/CGO or vice versa

33
Q

Benefit of a treatment is dependent on…

A

Risk of dis-ease BEFORE treatment is started

34
Q

Error in epidemiological studies

A

Occurs when the wrong people are recruited into a study, or the right people are put in the wrong GATE frame –> EGO and CGO incorrect

35
Q

Random error

A

Error that occurs by chance

36
Q

Why do non-random errors / bias occur

A

Due to poor study design, processes, or measurements

37
Q

Study validity

A

A study with only a small amount of random or non-random error is considered to be a valid study

38
Q

Where do non-random errors occur?

A 
RAMBOMAN
Recruitment of participants into study
Allocation of participants to EG and CG + Adjustment in Analyses
Maintenance of participants in EG and CG during study period
Blind or
Objective
Measurement of Exposures/Outcomes
ANalyses
39
Q

Main ways of allocation

A

By measurement/observation

By random allocation

40
Q

Confounding

A

When exposure is mixed with another factor that is also associated with the outcome
To deal with this, divide/stratify the study into sub-studies/strata so participants with the confounder are all in one sub-study i.e. adjustment

41
Q

Cross-sectional studies and maintenance

A

There is no follow-up time in cross-sectional studies because participants aren’t followed up, so maintenance error is not a problem

42
Q

What to do if participants aren’t a representative sample of a population

A

Instead, can compare sample with other similar samples in different countries

43
Q

Risk difference and Risk ratio - units

A

RD: units (/people/time)
RR: no units

44
Q

RAMBOMAN - Maintenance

A

Did participants remain in their allocated groups (EG or CG)?
Were many participants lost to follow-up (from either EG or CG) (can’t happen in cross-sectional study as not followed over time)

45
Q

RAMBOMAN - Blind or Objective Measurement

A

If outcome is death, it’s objective
If outcome is cause of death, less objectively measured - requires personal interpretation

Measurement errors often not applicable to RCTs
Blinded studies reduce subjective measures

46
Q

Paper vs video questionnaires

A

Video questionnaires measure more objectively compared to paper questionnaires

47
Q

Ecological randomised study reduces chances of…

A

Confounding

48
Q

Extreme events are often ____ events

A

Chance/random

49
Q

Why is measuring the exact ‘truth’ not possible in biology/epidemiology?

A

The participants are moving targets, so identical measurements of exposures and outcomes in the same or similar people can change from moment to moment
Called random measurement error

50
Q

Random measurement error affects…

A

Measurement of both exposures (E and C) and outcomes (O)

51
Q

‘Identical studies’

A

Identically designed and implemented studies will never include participants with identical characteristics
‘Identical studies’ will produce different results

52
Q

Random sampling error

A

The smaller the sample, the greater the chance the sample will be different from the whole population, i.e. the greater the random sampling error

53
Q

95% confidence interval

A

A measure of the amount of random error in our estimates of EGO, CGO, RR AND RD in the whole population when you only have done one study

54
Q

95% confidence interval - actual definition

A

In 100 identical studies using samples from the same population, 95/100 of the 95% CIs will include the true value for the population

“There is about a 95% probability that the true value of EGO in the whole population of interest, from which the study participants were recruited, lies between __ and __”

55
Q

Confidence intervals describe…

A

The range of results likely to include the true result in the whole population

56
Q

Every epidemiological measure has random error which can be estimated by a…

A

Confidence interval

57
Q

Other types of confidence intervals (not 95%)

A

90% and 99%
99% CI is wider (more uncertainty); need a bigger net to catch the true effect of 99% of the time compared to 95% of the time

58
Q

If CI of CGO doesn’t overlap with CI of EGO…

A

There’s a statistically significant difference between them

59
Q

If CI of RD doesn’t overlap with no-effect line…

A

There’s a statistically significant effect

60
Q

No-effect line

A

Where EGO = CGO so RD = 0, or RR = 1

61
Q

If CI for EGO and CGO do overlap…

A

There’s probably no statistically significant difference between EGO and CGO

62
Q

How to reduce random sampling error

A

Do a bigger study; bigger sample –> less chance sample will be different from whole population –> less random sampling error –> narrower CI

63
Q

How to reduce random measurement error

A

Regression to the mean; repeat measurement/study - often results are less extreme

64
Q

Meta-analysis

A

Combining studies in a meta-analysis is the next best thing to doing a larger study and reduces random error
Mainly done using RCTs

65
Q

Reverse causality

A

Common error in cross-sectional studies, as you measure exposure and outcome at the same time

e. g. must ask if ‘diet’ was before ‘heart attack’
i. e. effect may come before cause

66
Q

Individual participant studies - confounding

A

Investigators measure as many confounding factors as they can –> adjust as much as they can

67
Q

Conservative measure bias

A

Where RR is closer to 1.0 and RD is closer to 0

68
Q

RRI and RRR

A

Relative Risk Increase = (RR - 1) x 100% = > 1

Relative Risk Decrease = (1 - RR) x 100% = < 1

69
Q

ARR and ARI

A

The RD is an Absolute Risk Reduction if the risk is lower in the EG
The RD is an Absolute Risk Increase if the risk is higher in the EG

70
Q

EGO and CGO are measures of ______

A

Occurrence

71
Q

RR and RD are measures of ____

A

Effect

POPLHLTH 111 (5 decks)

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