Population Science 1 Flashcards
How does population sci sample the population ?
We use samples (statistics) to Infer the whole population
an ideal sample is Representative, Unbiased and Precise
what are key factors that contribute to population health
the demographic shape
age proportions - is it an ageing population - a population decline ?
is it a sex proportion - more men smoke
economic makeup - what is the wealth and wealth distribution of the population
behavioural and lifestyle factors - diet and exercise (more common in well of groups - positive health mindset)
where does the burden of disease fall, what does it depend on ?
it falls on working pop to pay taxes (UK)
it falls on NHS and its docs and nurses ect
it is dependent on population size - growing / shrinking
population shape - do we have an ageing population
age/sex specific rates - ie older populations leads to more dimentia
nearly all men over 70 have prostate cancer - mostly benign though
what are some global determinants of health ?
global warming / climate change
socio-demographic factors - demographic transiotion
economic transition
behavoir / culture/ lifestyle changes
population size / population shape
what is demography, epidemiology, statistics
demography, - study size and shape of populations
epidemiology, - study disease in populations
statistics - study numerical data
we can use public health policy
health promotion
and disease prevention
all of these effect the health of the population
Define Prevalence
• The proportion of people who have a disease at a given point in time.
Counts the number of people with existing disease (both OLD and NEW cases)
– Takes a “snapshot” at a given point in time
– Describes the ‘burden of disease’
Often reported as a proportion (it is not a rate!)
Define Incidence
Link Prevalence and Incidence
The number of new cases of a disease within a given
time frame.
– Focuses on NEW cases only
– Useful when monitoring epidemics
Often reported as a rate (e.g. 50 per 100,000 person
years)
incidence is the new drips of water into a bath
prevalence is the total volume of the bath water - add new drips and minus the deaths and cures
what are sources of variation due to bias and chance ?
give a couple examples of bias
Chance - random error - variation in sampling - will reduce as we increase the sample size (an increase in precision)
Bias - a systematic error - quantify by the difference between the true value and the expected value
will not reduce as we increase sample size - study has an inherent error
Bias is caused by selection bias -
study sample -external validity - take sample outside mcdonalds everyone is fat - NOT REPRESENTATIVE OF THE ENTIRE POPULATION
Group selection within a study - internal validity - groups within a study may not be comparable
healthy worker effect - only healthy people work - the ill do not - pick wide age range and people of all types
information bias - interviewer error and patient recall error
measurement error
misclassifications of parcipitants
what are the differences between relative risk, risk difference and odds ratio
Relative risk is the underlying quantity we wish to approximate
relative risk is a ratio of 2 proportions
absolute risk = a/a+b - proportion
relative risk is
(a/a+b)/(c/c+d) - diseased over total
an odds ratio is the
odds of group A disease/ odds of group B disease
odds of disease = disease / non disease - a ratio
the risk difference is the absolute risk of group A - absolute risk of group B
absolute risk = diseased / diseased + healthy (total pop)
what is the difference between absolute risk and relative risk
relative risk is a ratio of the two absolute risk proportions
absolute risk is a proportion -
absolute risk = diseased / diseased + healthy (total pop)
what does confounding factors mean ?
a confounding factor/variable is a variable that may affect the results but is not accounted for in the study
ie rate of drinking on cancer
the fact that males drink more alcohol is a confounding factor
we can adjust for known confounders
Precison vs Bias
precision - results will be grouped close together
Bias - are the results accurate
High Precision - High Bias - close results but not accurate
High Precision - Low Bias - close group results and accurate
Low Precision - High Bias - wide spread of results and not accurate
Low Precision - Low Bias - wide spread of results but no bias
what is Incidence rate ratio
used to compare two groups
incidence group A / incidence group B
