How do we do Public Health? - part 1

lecture 5

epidemiology

epidemiology

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

biostatistics

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

Step 1 of the 5 step approach

Define the population

Step 2 of the 5 step approach

Define and measure the health outcome and potential causes of health

Step 3 of the 5 step approach

Take a sample from the population for analysis

Step 4 of the 5 step approach

Evaluate potential causes of population health

Step 5 of the 5 step approach

Identify targets for public health action

Defining the population

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

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

Take a sample from the population

Use a small section of the population to calculate prevalence

Evaluate potential causes for health

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

Identify targets for public health action

Look at modifiable factors and what can be done

incidence

new cases

recovery

when people no longer have the disease

prevalence

the number of cases

mortality

death

cross-sectional study

participants are representative of the population defined by

person, place, and time looks at prevalence

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

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

confounding factors

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

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