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Pop Health 111 > Module 1 > Flashcards

Module 1 Flashcards

1
Q

Numerator

A

Number of cases of disease

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2
Q

Denominator

A

Number of people in a population

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3
Q

Frequency of disease

A

(N/D)/Time

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4
Q

Population

A

A group of people who share one or more common feature

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5
Q

Epidemiology

A

The study of occurrence and causes of disease in groups or populations at one point or over a period of time

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6
Q

PECOT

A 
Population
Exposure group (E.G.)
Comparison Group (CG) 
Outcome 
Timing
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7
Q

EGO

A

Exposure group occurrence

EGO=a/E.G.

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8
Q

CGO

A

Comparison Group Occurrence

CGO=b/CG

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9
Q

Incidence

A

Number of disease events occurring over a period of time

EGO & CGO are called incidence of occurrence

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10
Q

Prevalence

A

The number of people with a disease who are counted at one point in time

EGO & CGO are called prevalence of occurrence

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11
Q

Numerical Outcomes

A

A quantifiable value e.g. Heart rate per minute

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12
Q

Categorical Outcome

A

Specific set of options e.g. Yes/no

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13
Q

Period Prevalence

A

We measure if the event has occurred during a period and not the number of occurrences

Eg. If an asthma attack has happened in the past year

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14
Q

Point Prevalence

A

Measure Prevalence of something at one point right now

Eg. Level of nicotine in blood at one point

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15
Q

Ecological Study

A

Comparing groups of populations rather than groups of individuals

Can be RCT, cross sectional, cohort

Confounding is common

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16
Q

Risk Difference - Absolute Inequalities

A

EGO-CGO

IF RD = 0 then treatment has no effect

17
Q

Risk Ratio

A

EGO/CGO

If RR = 0 effect of treatments are the same

18
Q

Relative Risk Reduction

A

If RR is less than 1

19
Q

Relative Risk Increase

A

If RR is more than 1

20
Q

R (RAMBOMAN)

A

Recruitment

Are participants a representative sample from the known population?

21
Q

A (RAMBOMAN)

A

Allocation

Was allocations accurate?
Is confounding involved?

22
Q

Confounding

A

Difference between EGO and CGO apart from the main difference being studied

To deal with confounding we divide the study into sub studies so participants with the confounded are all in one study

23
Q

M (RAMBOMAN)

A

Maintenance

If possible we randomise the population otherwise we ask about disease

Need to maintain initial exposure/comparison groups

24
Q

B (RAMBOMAN)

A

Blind

Unbound study: investigators and patients know who is taking treatment or placebo

Single blind: investigators know, patients do not

Double blind: neither investigator nor patient know

25
Q

O (RAMBOMAN)

A

Objective

Objective outcome as it is easiest to measure

E.g. Dead or alive

26
Q

M (RAMBOMAN)

A

Measurement of Outcomes

Everyone has different interpretations of subjective outcomes
- Recall Bias

27
Q

Age standardisation

A

(Disease/study population) x age standardised population

(Total of ages of age specific death rates/ age standardised population) x age standardised disease rates

28
Q

Random Error

A

Extreme events are often chance restarting of these will often produce less extreme results - regression to the mean

29
Q

Random Measurement Error

A

Identical measures of exposure/outcome in similar people can result in different outcomes over time

30
Q

Random Sampling Error

A

We can’t study everyone only a sample of the population

31
Q

95% Confidence Interval

A

A measure of the amount of random measurement/sampling error when you’ve only done one study

Reduces random error

32
Q

Cohort Study

A

Study of individuals allocated to groups over time

Observational longitudinal study

Involving incidence

Used for investigating risk factors for disease

Main errors: how accurate is allocation, maintenance error

33
Q

Cross Sectional Study

A

Study of individuals allocated to groups at the same time

Involving Prevalence

No maintenance error

Main error: confounding, reverse causality

34
Q

Randomised control Trial

A

Study of individuals randomly allocated to groups and counted over time

Involves incidence (sometimes Prevalence)

Commonly used for studying effects of drugs - reduces confounding

Main errors: having motivated volunteers, random error common

35
Q

Meta Analysis

A

A study of studies

Combining the results of a number of small studies is similar to conducting a larger study and it reduces the amount of random error

Only as good as the studies included

No effect line: if studies cross this are less statistically significant

Pop Health 111 (4 decks)

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