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Block 3 > Overview Of Epidemiology - Concepts & Study Designs > Flashcards

Overview Of Epidemiology - Concepts & Study Designs Flashcards

1
Q

What is epidemiology?

A 
Epi = disease
Demos = people/population
Ology = study

So it is the STUDY of DISEASE in POPULATIONS

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2
Q

Define prevalence.

A

Number of people with a problem in a defined population at one time

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3
Q

Define incidence.

A

Number of new cases of a problem arising in a defined population in a defined period of time

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4
Q

Define mortality (event) rates.

A

Number of people dying in a defined population in a defined period of time

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5
Q

When would prevalence of a condition be constant?

A

Incidence rate = mortality rate

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6
Q

What are the 2 different approaches to causality?

A
  1. Deterministic

2. Stochastic

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7
Q

What is a deterministic approach?

A

Validation of hypothesis by systematic observations to predict with certainty future events (inevitability)

E.G. Tubercle Bacillus is the cause of TB

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8
Q

What is a stochastic approach?

A

Assessment of hypothesis by systematic observations to give risk of future events (probability)

E.G. overcrowded accommodation increases incidence of TB

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9
Q

What are the key aspects of the deterministic approach?

A
  • Newtonian thinking
  • Mechanistic, can take apart to study
  • Objective, quantifiable + certain
  • Whole is the sum of the parts
  • Very useful in thinking about a single cause for a single disease
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10
Q

What are the key aspects of the stochastic approach?

A
  • Quantum thinking
  • Whole greater than sum of parts
  • Whole not predictable from knowledge of parts
  • Probabilities cf. certainties
  • Systems theory; complexity theory where the observer influences the observed (emergent phenomena)
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11
Q

How do you determine causality?

A

Differentiating association from causation

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12
Q

What is a confounding factor?

A

Something that is associated with both the exposure and the outcome

An exposure is independently associated with the outcome after taking confounding factors into account

E.G:
Exposure = overweight
Outcome = CVD
Confounder = smoking

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13
Q

What is a mediating variable?

A

A variable through which an exposure wholly or partially exerts its effect

E.G:
Exposure = high sugar intake
Outcome = CVD
Mediator = overweight

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14
Q

What is reverse causality?

A

A 2-way causal relationship

E.G. unemployment can cause mental illness but mental illness can cause unemployment

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15
Q

How can epidemiological studies determine aetiology?

A

Good at assessing disease risk associated with individual agents determining probability making a case ‘beyond reasonable doubt’ BUT cannot prove causality

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16
Q

What is the Bradford Hill criteria for inferring causality?

A
  1. Association features: strength, specificity + consistency of association
  2. Exposure/outcome: temporal sequence, dose response + reversibility
  3. Other evidence: coherence of theory, biological plausibility + analogy
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17
Q

What is strength of association?

A

A causal link is more likely with strong associations (commonly measured by rate ratio or odds ratio) but weak associations can still be causal

Strong associations are unlikely to be explained by undetected confounding or bias however, this is not always true

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18
Q

What is specificity of association?

A

A causal link is more likely when a disease is associated with one specific factor and vice-versa however, lack of specificity does not necessarily weaken the case as current models of disease causation are multi-factorial where outcomes are caused by many factors which may or may not be inter-related

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19
Q

What is consistency of association?

A

A causal link is more likely if the association is observed in different studies and sub-groups because this is unlikely to be due to the same confounding or bias

Lack of consistency can be due to features of study design

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20
Q

What is a temporal sequence?

A

A causal link is more likely if exposure to the putative cause has been shown to precede the outcome

21
Q

What is dose response (biological gradient)?

A

A causal link is more likely if different levels of exposure to the putative factor lead to different risk of acquiring the outcome as this is unlikely to be due to unknown confounding or bias although lack of a biological gradient does not rule out a causal link (e.g. threshold effect, J-shaped or U-shaped relationship)

22
Q

What is reversibility (experiment)?

A

A causal link is very likely if removal or prevention of the putative factor leads to a reduced or non-existent risk of acquiring the outcome

Probably the strongest evidence for a causal link

23
Q

Why can reversibility be difficult to demonstrate?

A
  • Many diseases have long time lags
  • Ethical issues for a RCT of a prevention programme
  • A public health programme to remove or prevent an exposure often requires society action
24
Q

What are strong and weak study designs that can be used to demonstrate temporal sequence?

A

Optimal study designs = prospective cohort study + RCTs

Weak study designs = cross-sectional (prevalence) + case-control study

25
Q

What is the coherence of theory?

A

A causal link is more likely if the observed association conforms with current knowledge however, lack of coherence does not rule out a causal link

26
Q

What is the issue with coherence of theory?

A

Coherence with current paradigms strengthens the case for a causal link which leads to inappropriate rejection of ‘unfavoured’ associations i.e. ‘publication bias’ towards studies that support favoured theories or demonstrate that drunk/interventions work

27
Q

What is biological plausibility?

A

A causal link is more likely if a biologically plausible mechanism is likely or demonstrated

28
Q

What is analogy?

A

A causal link is more likely if an analogy exists with other diseases, species or settings as it is easier to infer than a biologically plausible mechanism

29
Q

What influences the extent to which epidemiological evidence convinces?

A

Many factors including prior beliefs and commercial interests but this is not always the case if evidence is strong enough (e.g. Thalidomide)

30
Q

What are cross-sectional surveys?

A

May be set up for a specific purpose (or not) E.G:

  • Prevalence of a specific disease
  • Investigate distribution of a specific disease in population
  • Monitoring health over time

Medium cost

31
Q

What are case-control studies?

A

Almost always set up for a specific purpose E.G. investigate suspected determinants such as outbreak investigation + determinants of rare conditions

32
Q

What are cohort studies?

A

May be set up for a specific purpose, but more often multipurpose e.g. determinants of common conditions (effects of smoking, asbestos) looking at the relative importance of different factors

33
Q

What are the 3 types of observational study?

A
  1. Cross sectional surveys
  2. Case-control studies
  3. Cohort studies
34
Q

What are the 4 types of experimental study?

A
  1. Uncontrolled studies
  2. Natural experiments
  3. Controlled studies
  4. RCTs
35
Q

What are uncontrolled studies?

A

A factor is measured, something is changed and then it is measured again

36
Q

What are the advantages and disadvantages of uncontrolled studies?

A

Adv: easy to do

Disadv:

  • Selection bias problem
  • Dont know what happens w/o intervention
37
Q

What are the advantages and disadvantages of natural experiments?

A

Adv: may be the only way to investigate some things

Disadv: issues due to unknown confounding factors

38
Q

What is bias?

A

Any trend in the collection, analysis, interpretation, publication of review of data that can lead to conclusions that are systematically different from the truth

39
Q

What is the hierarchy of evidence?

A

Systematic reviews

Experimental studies (RCTs + controlled trials)

Observational studies (cohort + case-control studies)

Descriptive studies (cross-sectional (qualitative studies))

40
Q

What are the 3 types of bias in epidemiological studies?

A
  1. Selection
  2. Information
  3. Confounding
41
Q

What is selection bias?

A

Occurs during design phase, plus execution due to admission, prevalence/incidence, detection, volunteer + loss to follow-up

42
Q

What is information bias?

A

Occurs during data collection phase due to interviewer, questionnaire, recall, diagnostic suspicion + exposure

43
Q

What is the problem with epidemiological studies?

A

Studies provide information on average effects that hide individual level variation however, for some patients it will be better not to do what is best on average for e.g. if patients have strong treatment preferences it is likely to be best to support these preferences

44
Q

When are epidemiological studies best?

A

When a single agent causes a single disease OR single treatment reverses disease

45
Q

When are epidemiological studies very good?

A

When a primary factor causes specific disease with several secondary influences

46
Q

When are epidemiological studies more limited?

A

When many different factors interact with each other in complex pathways to create the conditions in which multiple diseases are likely to arise e.g. social inequalities + health

47
Q

What are the issues with cohort studies?

A

Slow + expensive

Issues due to confounding with unknown risk factors

48
Q

What are the advantages and disadvantages of case-control studies?

A

Adv: quick + cheap

Disadv: recall + selection bias

Block 3 (40 decks)

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