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1
Q

Define incidence

A

The number of new cases of a disease that has occurred.

2
Q

Define prevalence in words

A

The number of people affected by a disease at a specific time/ time frame. This counts people with existing disease as well as new cases. It however is not a rate but a proportion (denominator is persons, not persons per time).

3
Q

Describe the inter-relationships between incidence and prevalence

A

P roughly equal (I x L) where L=length of disease, when the incidence rates and rates of recovery and death are constant.
Factors that increase prevalence in a population - increase incidence (new cases), keep them alive longer.
Factors that decrease prevalence in a population - increase death (death rates) and cures (cure rate)

4
Q

Explain the purpose of age-sex standardisation

A

SMRs give a single summary measure of disease corrected for age-sex confounding. So you can compare two populations as IF their age-sex structure were the same.

5
Q

How do you interpret a standardised mortality/morbidity ratio (SMR)?

A
100= same risk in the study population as in the standard reference population
>100 = higher risk in the study population
6
Q

Why is the systematic variation in the risk of disease between groups, a useful source of information?

A

Incidence is a measure of the population’s AVERAGE RISK of disease, but there are variations in risk of disease between groups of people.
SYSTEMATIC VARIATIONS IN RISK BETWEEN PEOPLE (compare incidence rates between groups with different levels of exposure) gives us clues about the CAUSE OF DISEASE.

7
Q

Why is the systematic variation in the risk of disease between groups, sometimes a nuisance which needs to be controlled for?

A

Factors such as age and sex that systematically vary between groups are strong determinants of health but are not potential hazards that can be modified to target prevention. They can be confounding factors.

8
Q

Why is measuring the incidence important?

A

It focuses on NEW EVENTS. Useful when monitoring epidemics or when monitoring the effect of prevention programmes. Or when a disease has a very short duration e.g. stroke.

9
Q

Why is measuring the prevalence important?

A

It describe the burden of disease. It is a useful measure of the need for services.

10
Q

Define the incidence rate using words

A

Incidence rate divides the new cases observed (events) by the number of person-years (number of people observed multiplied by number of years they are observed for)

11
Q

Define the incidence rate using maths

A

incidence rate = (new events)/(person x time (years)) = events per person per year

12
Q

Define (point) prevalence using maths

A

(point) prevalence = (number of cases (new and old) in a time frame)/ population
As time frame is not in the denominator it is NOT A RATE!

13
Q

Define a cross-sectional survey

A

is a type of observational study that involves the analysis of data collected from a population, or a representative subset, at one specific point in time.

14
Q

Define control group

A

A group of subjects or conditions that is matched as closely as possible with an experimental group, but is not exposed to any experimental treatment/conditions. The results are then compared to determine the changes that may occur due to the exposure.

15
Q

Define incidence rate ratio (IRR) in words

A

Comparing the incidence rates between groups with different levels of exposure.

16
Q

Define IRR with maths

A

IRR = (Rate (exposed))/ (Rate (unexposed))

17
Q

How do you interpret an IRR?

A

If incidence rate of exposed is bigger than that of unexposed, this implies that the differences in exposure is associated with the difference in rates of disease

18
Q

What are two uses of IRR?

A

Finding out the:

  1. Cause of disease (e.g. cohort studies)
  2. Treatment effects (e.g. clinical trials).
19
Q

Define mathematically a mortality rate ratio

A

mortality rate ratio = (mortality rate A)/(mortality rate B)

This is a special case of an incidence rate where the event is death rather than onset of a disease.

20
Q

What is the difference between a rate and a ratio?

A

Rate implies ‘per unit time’ and is a measure of absolute risk
Ratio is a measure of relative risk (cf. two or more groups)

21
Q

What is a confounding factor?

A

A factor that is associated with the exposure and is also independently associated with the outcome but is not on the causal pathway.
Age is an example of a confounding factor. E.g. If a study looked at the incidence of skin cancer in a town, it could make it seem like there was a high risk of getting skin cancer if you lived in that town but in fact it was just because there is a higher than average number of elderly people living there and the risk of getting skin cancer increases with age. That would create a spurious association with skin cancer and that town.

22
Q

The analysis of death has many parallels with the analysis of what?

A

Analysis of new cases of disease e.g. IRR is used to measure deaths as the mortality rate ratio.

23
Q

What is the ‘burden of a disease’?

A

The extent to which a disease is a problem to a community.

24
Q

What does person-years mean?

A

The multiplication of the number of people observed with the number of years of observation.

25
Q

For the purpose of calculating an incidence rate, observing 50,000 people for 18 months is equivalent to observing 25,000 people for what length of time?

A

For 3 years (2 x 18 months)

26
Q

What are standardised morbidity ratios used for?

A

Comparing disease events of a population with a standard reference population, rather than comparing death rates.

27
Q

What is the standard reference population that is usually used for an SMR?

A

The whole country

28
Q

Why is it useful to know the age-sex breakdown of a population?

A

Age and sex are the strong determinants for the need of health services.
1. Immunisations are largely confined to children
2. Obstetrics services are only used by women , usually 15-44 year olds.
3. Coronary heart services, usually used by 50+
Etc…

29
Q

What is Simpson’s paradox?

A

Simpson’s paradox is a paradox in probability and statistics, in which a trend appears in different groups of data but disappears or reverses when these groups are combined.
For instance when data is viewed by age-specific mortality rates it can show one things, but when all the age categories are analysed together the trend can reverse, due to e.g. different age structures in a population.