How do we do Public Health? - part 1

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lecture 5

Last updated 8:06 PM on 12/4/23
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21 Terms

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epidemiology

the study of the distribution and determinants of disease. This is critically important in population health science

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biostatistics

a related science focused on understanding variability in potential causes and outcomes in order to infer associations and relationships among them

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Step 1 of the 5 step approach

Define the population

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Step 2 of the 5 step approach

Define and measure the health outcome and potential causes of health

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Step 3 of the 5 step approach

Take a sample from the population for analysis

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Step 4 of the 5 step approach

Evaluate potential causes of population health

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Step 5 of the 5 step approach

Identify targets for public health action

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Defining the population

target group: age, gender, location, presence of condition, etc.

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Define and measure the health outcome and potential causes of health

Looks at what is being measured, how evidence/frameworks explain potential causes of health, uses indicators and statistics

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Take a sample from the population

Use a small section of the population to calculate prevalence

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Evaluate potential causes for health

use data to evaluate how diverse factors cause a particular health outcome

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Identify targets for public health action

Look at modifiable factors and what can be done

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incidence

new cases

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recovery

when people no longer have the disease

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prevalence

the number of cases

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mortality

death

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cross-sectional study

participants are representative of the population defined by

person, place, and time looks at prevalence

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cohort study

participants are free of the outcome of interest and followed over time for the development of that outcome, looks at prevalence of causes and incidence of health outcome

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case-control study

cases are participants with the health outcome of interest and controls are a random sample of participants from the same population that produced the cases but are free of the outcome, looks at association between cause prevalence and outcome

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confounding factors

variables that may compete with the exposure of interest (eg, treatment) in explaining the outcome of a study

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randomised trials

participants are randomized to receive the intervention or not and followed for incidence of the health outcome or disease progression, looks at effect of intervention

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