Lecture Notes Flashcards
(133 cards)
explain the:
what? who? where? when? why? so what?
of the epidemiological approach
what - case definition who - person where - place when - time why - causes/determinants
so what - prevention and control
define “epidemiology”
the study of the distribution and determinants of disease frequency
(in human populations)
what different factors come under “distribution of disease”?
time
place
person - age, gender, social class, ethnicity etc.
differentiate between a suspected, probable and confirmed case of an infectious disease (e.g. a measles outbreak)
this will be defined by the case definition.
suspected - clinical features (e.g. fever and rash)
probable - clinical features + contact with confirmed case
confirmed case - clinical features and positive microbiology, serology etc.
what is a case definition?
set of standard criteria for deciding whether or not a person has a particular disease or health related event
explain the “sufficient, necessary and component” causes model
causation is multifactoral - individual ‘causes’ = components.
if enough components are combined, disease is expressed.
combination of component causes = sufficient cause.
some factors may be “necessary” causes (i.e. cannot experience disease without them), but often need more than just one necessary cause to express disease
define prevalence
a measure of the proportion of the population that has a given disease, condition or characteristic at a given time (or time period)
define point prevalence
no. cases at a point in time, compared with the total population
define period prevalence
no. cases identified over a period of time, compared with no. people in the population over this time period.
NB - not NEW cases (that’s incidence!), just existing cases
define incidence
frequency of NEW cases in a defined population in a specified time period
define cumulative incidence (RISK)
no. NEW cases occurring over a given period of time in the population at risk at the BEGINNING of the time period
what 4 different relative measures come under the term “relative risk”
prevalence ratio
risk ratio
rate ratio
odds ratio
what does relative risk measure?
measures the strength of association between exposure and disease
how do you interpret relative risk?
avoid using “more” or “less”
it’s a ratio telling us “how many times more likely” the outcome is in the exposed group
e.g. “the exposed group has a RR 1.25 times the risk of the unexposed group”
or
the exposed group were 1.25 times more likely to (have the outcome) than the unexposed group
what are the 4 different measures of impact of a risk factor?
- attributable risk (aka excess risk)
- attributable risk fraction (or %)
- population attributable risk
- population attributable risk fraction (or %)
what is attributable risk?
the excess incidence of our outcome that can be attributed to the exposure
what does using an attributable risk fraction adjust for?
the fact that the exposed group would have had some disease anyway - AR fails to take into account the underlying, background rate.
i.e. - not all illness, even in the exposed group, will be due to the exposure
what does the attributable risk fraction tell us?
what proportion of disease IN THE EXPOSED GROUP is attributable to the exposure
what does population attributable fraction tell us?
what proportion of disease in the POPULATION that is attributable to the exposure
e.g. interpret PAF of 0.96 as “96% of (outcome) in the population are attributable to (exposure)
why is age standardisation useful?
allows comparisons to be made between two populations with different age distributions
let’s you adjust for the confounder of age
e.g. can compare rates of CVD in two populations, even if one is a significantly older population
what is a crude death rate?
death rate for the whole population, with no age (or other factor) adjustment
describe how DIRECT age standardisation works
calculate death rates for each age group in your population
apply these rates to the same age groups in a “standard population”
produces expected deaths for each age group, and can total these to get the DSR (directly standardised rate) per 1000.
e.g. total population = 1000
total expected deaths = 38.5
DSR = 38.5 deaths per 1000 population
describe how INDIRECT age standardisation works
take a set of “standard death rates”
apply these rates to your population
this produces expected deaths per age group
then you get the ratio of observed to expected deaths:
SMR = O/E
(SMR = standardised mortality ratio)
what is a cross-sectional study?
a study in which data are collected on each study participant at a single point in time
a SNAPSHOT
aka prevalence study