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Epidemiology > Key principles of epidemiology > Flashcards

Key principles of epidemiology Flashcards

1
Q

define frequency

A

number of occurrences of an outcome within a given time period

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2
Q

two main approaches to epidemiological study

A

descriptive and analytical

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3
Q

what information does descriptive epidemiology provide?

A

distribution of health outcomes by age, population type, geography or over time.

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4
Q

what information does analytical epidemiology provide?

A

investigates which factors may be responsible for increasing or decreasing the probability of an outcome

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5
Q

difference between sufficient and component cause

A

sufficient cause refers to a factor or sort of factors that produce the outcome. the factors that form a sufficient cause are called component causes

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6
Q

for an association to be causal, the …. must occur before the ….

A

exposure then outcome

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7
Q

what can effect causality? (alternative explanation for an association)

A

chance, bias and confounding

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8
Q

what is chance and how do you reduce it?

A

possibility that there is a random error and reduced by increasing sample size, using random selection or randomisation

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9
Q

what is bias

A

refers to systematic differences between comparison groups which may misrepresent the association being investigated

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10
Q

what is confounding

A

caused when another factor, independently associated with both the outcome and exposure, influences the association being investigated

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11
Q

two approaches to analytical epidemiology

A

observation or intervention

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12
Q

difference between observational and intervention study

A

observational compares the frequency of an outcome in groups or individuals with and without the exposure of interest. invervention is an experiment - evaluates the effect of reducing a risk factor or increasing a protective factor on the frequency of an outcome.

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13
Q

define prevalence

A

the number of existing cases in a defined population at a defined point in time divided by the total number of people in that population at the same point in time - it is a proportion

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14
Q

how do you measure prevalence?

A

population surveys or cross sectional studies

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15
Q

define incidence

A

frequency of new cases in a defined population during a specified time period

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16
Q

how do you measure incidence?

A

ecological or cohort studies

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17
Q

three ways to consider incidence

A

risk, odds and incidence rate

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18
Q

define risk

A

total number of new cases in a specified time period divided by the total number of individuals at risk in the population at the start of the time period

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19
Q

how do you work out secondary attack rate

A

number of new cases among contacts in a specified time period divided by total number of contacts of a primary case in that time period

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20
Q

define odds

A

ratio of two proportions so number of new cases in a specified time period divided by number who did not become a case during that time period

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21
Q

what do you use if it is an open population rather than a closed population to work out incidence rate?

A

population time at risk

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22
Q

examples of relative measurers that use ratios

A

prevalence ratio, risk ratio, odds ratio, incidence rate ratio

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23
Q

what does relative risk measure

A

how much more likely it is that an exposed individual will develop the outcome compared with the unexposed individual

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24
Q

what studies do you use to calculate risk ratio?

A

ecological, cohort or intervention

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25
Q

how do you calculate odds ratio?

A

odds of outcome in exposed group divided by odds of outcome in unexposed group

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26
Q

what studies do you use to obtain incidence rate ratio?

A

ecological, cohort or intervention

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27
Q

when would you use incidence rate ratio over the odds ratio of exposure?

A

where people are entering and leaving the study population or have changing levels of exposure

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28
Q

if the outcome is rare, are the measures of association more similar or different?

A

more similar

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29
Q

when would you use attributable risk?

A

when you want to know the excess incidence of the outcome that we an attribute to the exposure (if we assume a causal relationship)

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30
Q

how do you work out attributable fraction?

A

attributable risk divided by incidence in exposed OR relative risk - 1 divided by relative risk

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31
Q

what is the opposite of attributable fraction? (i.e. if there’s a protective factor)

A

preventable fraction

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32
Q

how to work out the population attributable fraction?

A

the incidence in the population minus the incidence in unexposed divided by the incidence in population

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33
Q

define p value

A

the probability that an observed value or association from a sample occurred by chance alone and that it does not exist in the population from which the sample was selected

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34
Q

define confidence interval

A

the range of values, estimated from a sample, within which the true population value is likely to be found

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35
Q

if confidence interval includes 1 what can we say about the association?

A

it is not significant

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36
Q

how do you reduce bias?

A

through random selection of study participants or random allocation of individuals to comparison groups

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37
Q

different types of bias

A

selection

information

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38
Q

when does selection bias occur

A

when there is a systematic difference between the characteristics of individuals samples and the population from which the sample is taken or a systematic difference between comparison groups

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39
Q

what factors affect whether selection bias occurs?

A

the definition of the study population or comparison group
the inclusion and exclusion criteria
the rate of loss to follow up
healthy worker

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40
Q

when does information bias occur

A

when there is a systematic difference between comparison groups in the way that data is collected

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41
Q

how can information bias be introduced?

A

by those measuring the outcome (observer bias), the study participants (responder bias) or measuring tools (measurement bias) or misclassification

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42
Q

when does non differential misclassification occur?

A

occurs when both comparison groups are equally likely to be misclassified - unable to measure effectively. causes comparison groups to appear more similarly than they actually are and may lead to underestimation of the strength of association. independent of exposure or outcome

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43
Q

when does differential misclassification occur?

A

when classification of the exposure is dependent on the outcome or vice versa - due to observer or respondent bias

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44
Q

how do you reduce the effect of observer bias?

A

blinding, objective vs subjective measures

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45
Q

three ways to avoid confounding

A

randomisation - of individuals to exposure and control groups
restriction - limits the study to people who are similar in relation to the confounder
matching - selects two comparison groups to have the same distribution of potential confounders

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46
Q

how to control for confounding in the analysis

A

stratification - extension of frequency matching as it measures the association between exposure and outcome separately for each category of confounder
statistical modelling - allows us to adjust simultaneously for several confounders using multivariable regression analyses.

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47
Q

bradford hill criteria for building up evidence for a causal relationship

A

strength - the stronger the association between the exposure and outcome, the less likely the relationship is due to another factor
consistency - repeatability of the result
temporality - exposure comes before the outcome
dose-response - increased risk of outcome with increased exposure
plausibility - existence of a reasonable biological mechanism
reversibility - whether an intervention to remove the exposure results in the elimination of the outcome
coherence - consistency with other information
analogy - similarity between other established cause-effect relationships helps support the argument
specificity - the relationship is specific to the outcome of interest

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48
Q

ecological studies: what do they do

A

compare frequency of outcome an exposure at a population level

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49
Q

cross sectional studies: what do they do

A

compare prevalence of outcome with exposure status at one time point from a random sample of individuals

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50
Q

cohort studies: what do they do

A

compare the incidence of outcome in individuals with recorded differences in exposure

51
Q

case control: what do they do

A

select individuals on the basis of their outcome status and analyse whether they differ in relation to previous exposure

52
Q

intervention studies: what do they do

A

allocate a protective exposure and compare outcome between those exposed and unexposed

53
Q

Ecological study: what measures do you use? advantages and disadvantages?

A

prevalent or incident cases
easy to collect data, rapid, inexpensive
cannot show causality, high probability of confounding, ecological fallacy

54
Q

cross sectional studies: what measures do you use? advantages and disadvantages?

A

prevalent cases, prevalence ratio
easy to collect data, rapid
difficult to know if exposure preceded outcome, selection bias, confounding

55
Q

cohort studies: what measures do you use? advantages and disadvantages?

A

incident cases - risk ratio, odds ratio or rate ratio
low probability of selection bias, recall bias and confounding
loss to follow up, more expensive, more difficult as large number of participants required

56
Q

case control: what measures do you use? advantages and disadvantages?

A

no measures of outcome frequency, odds ratio of exposure
low probability of loss to follow up
high probability of selection and information bias, confounding

57
Q

intervention: what measures do you use? advantages and disadvantages?

A

prevalent or incident cases, preventable fraction
low probability of selection and information bias and confounding, satisfy temporality consideration, satisfies reversibility, can radnomize subjects to reduce effects of chance, reduce information bias
loss to follow up, more complex, expensive

58
Q

difference between statistical power and precision

A

statistical power = probability of detecting an effect if it is real
statistical precision = probability of detecting an effect if it is not real

59
Q

different types of random sampling

A

simple random sampling
systematic sampling - regular intervals
stratified sampling - equal proportion from each group
multi stage sampling - sampling frame required for high level unit and for primary sampling units within higher levels sampled
cluster sampling - also uses organisational structure but samples all or most of the primary sampling units

60
Q

if you need to exclude certain individuals what do you use when sampling?

A

exclusion and inclusion criteria

61
Q

what is informed consent?

A

participants need to give their consent to participate

62
Q

medical records, census data, health surveys, schools records are examples of what type of data collection method?

A

indirect data collection methods

63
Q

questionnaires, structured interviews and clinical examination are examples of what type of data collection method?

A

direct data collection methods

64
Q

why do we use unique identifiers?

A

so we can link all necessary data without identifying participant

65
Q

three types of quantitative variables

A

binomial - two values
categorical
continuous

66
Q

how do you usually present a meta analysis

A

forest plot

67
Q

what does a meta analysis do?

A

weights the individual estimates in relation to the sample size of each study

68
Q

when do we use direct standardisation?

A

in ecological studies to reduce confounding when we know the group specific outcome rates in the study population. the age specific rate is the incidence rates calculated separately for each group - can then add them up to give a standardised rate

69
Q

when do we use indirect standardisation?

A

calculates the expected number of cases in the study population if the age specific rates of a standard population had applied. used if we don’t know the age specific rates. the expected number of cases can then be used to calculate a standardised mortality ratio which compares the observed number of deaths to that expected in the same population.

70
Q

what is ecological fallacy?

A

in ecological studies when a mismatch arises from trying to draw conclusions about individual level epidemiological associations from a group level study

71
Q

what is mixing in ecological study interpretation?

A

geographical comparisons may suffer from migration of populations between groups

72
Q

if 95% confidence interval does not include 1, what can you say about the p value?

A

p value will be less than 5 (less than 5% chance that this association is not true)

73
Q

difference between point and period prevalence

A

point prevalence is at a specific point in time and period prevalence is over a period of time. period prevalence increases possibility of recall bias

74
Q

what are cross sectional studies at high risk of when assessing causation?

A

reverse causality

75
Q

are analytical cohort studies retrospective or prospective?

A

can be either as long as cohort defined on exposure and not outcome

76
Q

in a cohort study, if follow up times are similar what frequency measure do we use? if follow up times are different what do we use?

A

risk if similar and rate if follow up times differ

77
Q

what is the issue with case control studies and bias?

A

susceptible to information and selection bias

78
Q

how can you reduce confounding in case control studies?

A

identify controls with the same characteristics as the cases - matching

79
Q

what are nested case control studies?

A

cases are members of a cohort that have developed the outcome and control are those without the outcome. can automatically match on factors that are common to all cohort members

80
Q

in a case control study what do you need to ensure when sampling the population?

A

that they are representative of the target population in relation to the frequency of exposure, selection of cases and control are not influenced by their exposure

81
Q

why might inclusion of prevalent cases in a case control study be an issue?

A

inclusion of prevalent cases, especially chronic outcomes, can create problems for determining exposure to certain risk factors that may change over time which may lead to reverse causality. may also lead to underrepresentation of severe cases

82
Q

why can’t case control studies directly estimate prevalence or incidence of the outcome or frequency of the exposure in the general population?

A

because they don’t randomly sample the population, instead they select individuals based on their outcome status

83
Q

what is the ideal intervention study?

A

randomised controlled trial

84
Q

difference between efficacy and effectiveness?

A 
efficacy = measures the effect of the intervention under "experimental" conditions, where maximum effort is put into intervention delivery. once proven to be efficacious... 
effectiveness = measures the effect of the intervention of the intervention under routine conditions.
85
Q

what is a plausibility study?

A

evaluates the effectiveness of interventions by comparison with a historical, geographical or opportunistic control group but without randomisation.

86
Q

when might you use a plausibility study?

A

when an intervention is so complex that RCT results will be unacceptably artificial.
when an intervention is known to be efficacious or effective in small scale studies but effectiveness on a large scale must be demonstrated
when ethical concerns prevent the use of an RCT

87
Q

what is a plausibility study with a historical control group?

A

not possible to have a contemporary comparison arm so it may compare outcome frequency before and after the intervention is introduced. makes it difficult to distinguish between the effect of the intervention and any other changes that may have affected the outcome over the study period.

88
Q

what is a plausibility study with a geographical control group?

A

the use of communities or individuals as contemporary control outside the trial area may adjust for the effects of temporal changes during the course of the evaluation. however, there are likely to be differences between intervention and control. can use stepped wedge design (by introducing into population in phases)

89
Q

what is a plausibility study with a opportunistic control group?

A

involves the use of individuals or communities that should have reached the intervention but did not because the programme was unable to reach them.

90
Q

define RCT

A

the existence of a contemporary comparison group of study subjects who do not receive the intervention known as the “control” and the random allocation of study subjects to the intervention and control arms

91
Q

how is a cluster randomised controlled trial different?

A

groups of individuals are randomly allocated to the intervention and control arms

92
Q

what happens in a factorial trial?

A

two or more interventions are compared individually and in combination against a control comparison group

93
Q

what happens in a crossover design RCT?

A

each trial subject acts as its own control by receiving either the intervention or control at different points in the study, with a washout period to avoid contamination between the study periods

94
Q

different types of random allocation

A 
simple randomisation 
systemic randomisation
blocked randomisation
stratified randomisation 
matched pair randomisation
95
Q

what is simple randomisation?

A

uses number tables or a computer generated random number list

96
Q

what is systematic randomisation?

A

allocates participation to each group alternately but subject to selection bias

97
Q

what is blocked randomisation?

A

restricts the allocation list to ensure equal numbers in all study arms.

98
Q

what is stratified randomisation?

A

divides participants into subgroups or strata based on key risk factors and equal numbers of subjects from each stratum are randomly allocated to each study arm. this ensures that suspected confounders or effect modifiers of the association between intervention and outcome are equally distributed between comparison groups

99
Q

what is matched pair randomisation?

A

form of stratified random allocation that matches individuals or communities into pairs with similar baseline risks of the outcome

100
Q

what is the primary analysis of an intervention study?

A

intention to treat

101
Q

what is the efficacy of an intervention?

A

the proportion of cases that can be prevented by the intervention - also known as protective efficacy or preventable fraction and calculated by doing 1 - relative risk

102
Q

what is primary prevention and example?

A

aims to stop an outcome developing by preventing or reducing exposure to a risk factor
vaccination against an infectious disease

103
Q

what is secondary prevention and example?

A

aims to interrupt progression from early to mid-stage of the outcome by early detection and prompt treatment. e.g. blood lead screening in USA

104
Q

what is tertiary prevention and example?

A

aims to reduce complications or severity once outcome is established and symptomatic by offering appropriate treatment and intervention.
e.g. by monitoring blood glucose of those with diabetes to prevent renal disease and glaucoma

105
Q

what is screening used for?

A

to identify small numbers of individuals at high risk of an outcome

106
Q

how do you work out sensitivity?

A

the proportion of people who have the disease who are correctly identified.

107
Q

how do you work out specificity?

A

the proportion of people who do not have the condition that are correctly identified.

108
Q

what is the positive predictive value?

A

the likelihood of an outcome based on the result

109
Q

what is the negative predictive value?

A

the likelihood of no outcome based on a result

110
Q

disadvantages of screening

A 
false positives and false negatives 
potential harm (X-ray in mammography) 
good quality control needed 
specialist equipment may be required 
staff may require additional training
111
Q

WHO criteria for screening

A

the condition should be an important health problem
natural history of the condition should be well understood
there should be a recognisable latent or early stage
there should be a suitable method for detection
screening method should be acceptable to population
should be an accepted treatment for those with the condition
should be an agreed policy on who to treat
facilities for diagnosis and treatment should be available
costs of detection should be balanced inc elation to overall healthcare spending
screening should be ongoing and not one off

112
Q

what is lead time bias?

A

screening identifies an outcome earlier than it otherwise would have been identified but has no effect on outcome (so looks like prolonging)

113
Q

what is length time bias?

A

outcomes that take longer to develop to a stage where they threaten health - more likely to pick up less aggressive tumours with better prognosis leading to over-estimate of screening success.

114
Q

what is the prevention paradox?

A

where the majority of cases of a disease come from a population at low or moderate risk of that disease, and only a minority of cases come from the high risk population (of the same disease - target whole population

115
Q

what is a case definition?

A

set of standard criteria for determining whether or not a person has a particular disease or health related event

116
Q

what effect does an emerging new treatment that increases the life expectancy of HIV cases have on prevalence/incidence?

A

increased prevalence

117
Q

what effect does the discovery of a cure for DM have on prevalence/incidence?

A

decreased prevalence

118
Q

what effect does the introduction of a new malaria vaccine have on prevalence/incidence?

A

decreased incidence

119
Q

different types of bias

A 
information
selection
recall
sampling
non response
120
Q

difference between descriptive and analytical cross sectional studies

A

descriptive - collect info on frequency and distribution of health related exposures or outcomes in a defined population
analytical - investigate the association between exposure to risk factors and outcome of interest

121
Q

examples of when selection bias can occur in cross sectional, cohort, case control and intervention studies

A

cross sectional: non response
cohort: healthy worker effect, loss to follow up
case control: selection of cases and controls
intervention: systematic selection for intervention/controls

122
Q

what is validity?

A

the degree to which a measurement measures what it purports to measure

123
Q

what is reliability?

A

the degree to which the results obtained by a measurement procedure can be replicated

Epidemiology (1 decks)

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