Exam

• Epidemiology


  The study of how much disease occurs in a population and the factors that determine differences in disease occurrence between populations
• Numerator


  The number of people from the study population in whom the disease occurs
• Denominator


  The number of people in a study population
• Age standardisation


  The process of converting the different age structures into a standard population age structure and work out the death rates
• Crude Death Rate


  The number of people who die from the disease / the size of the study population
• Age Specific Death Rate

  Comparing the deaths rates from the same age groups within the population
• GATE frame and PECOT

  • Participant Population (triangle)
  • Exposure and Comparison groups (circle)
  • Outcomes (square)
  • Time (horizontal and vertical arrows)
• Incidence


  Measured when the number of disease events that occur are counted forward from a starting point, over a period of time

  
• Prevalence


  Measured when the number of people with disease are counted at one point in time
• Risk Ratio (RR)


  EGO ÷ CGO
• Relative Risk Reduction (RRR)


  ( 1 - RR ) x 100
• Relative Risk Increase (RRI)


  ( RR - 1 ) x 100
• Risk Difference (RD)


  EGO - CGO
• Absolute Risk Reduction (ARR)


  If the risk is lower in the Exposure Group
• Absolute Risk Increase (ARI)


  If the risk is higher in the Exposure Group
• Non-random error


  • Recruitment error
  • Allocation error
  • Maintenance error
  • Blind and Objective Measurement error
  • Analyses
• Random error


  • Random sampling error
  • Random measurement error
  • Randomness in biological phenomena
  • Random allocation error
• 95% confidence intervals


  Provides a range of values that is likely to include the true value in the total population
• If the CIs for EGO and CGO do not overlap, it is reasonable to assume that EGO and CGO are statistically significantly different in the total population
• If the CIs for EGO and CGO do overlap, the study is unable to determine if EGO and CGO are statistically significantly different in the total population
• If RD does not cross the no effect line, it is statistically significant in the total population
• If RD does cross the no effect line, the study is unable to determine if RD is statistically significant in the total population
• Meta-analyses


  Where four or more similar studies are combined mathematically to produce a summary estimate of the effect
• Experimental studies


  • Participants are allocated to Exposure Group or Comparison Group by the investigators
• Observational studies


  • Participants are allocated to Exposure Group and Comparison Group by measurement
• Longitudinal studies


  • Participants are followed over time, outcomes are usually measured as they occur during the follow up period
• Cross-sectional studies


  • Participants are allocated to Exposure Group and Comparison Group by measurement, at the same time as the outcome is measured
• Cohort studies


  • Investigators measure the presence (or absence) of study exposures among the participants and allocate them in Exposure Group and Comparison Group accordingly, participants are followed over time and outcomes are counted
• Cross-sectional studies


  • Exposure Group and Comparison Group status and disease outcomes are measured cross-sectionally at the same point in time
• Randomised controlled trials


  • Similar to cohort studies, except participants are randomly allocated to Exposure Group and Comparison Group
• Prevalence


  Measures the proportion of a population with a disease or condition
• Cohort studies


  • Investigate associations between exposures and outcomes
  • Can find an association that isn't real (Reverse Causality)
  • Not a good study design for investigating causal associations
• Randomised controlled trials


  • Participants are randomly allocated to Experimental Group and Control Group
  • Main measure of disease occurrence is incidence
  • Less prone to confounding due to randomisation
  • Most valid study design for assessing the effectiveness of interventions
  • Can have practical and ethical limitations
• Ecological studies


  • Involve the comparison of groups of populations rather than individuals
  • Can be cohort or cross-sectional
  • Results are often plotted on a graph
  • Can sometimes be RCTs
  • Useful for investigating risk factor and intervention effects
  • Very prone to confounding and it is seldom possible to adjust for confounders
  • Useful when almost everyone in a population is exposed to a factor
• Causes of the causes

  The reasons that cause people to participate in certain behaviours. They may vary at different life stages and include individual, community and environmental factors.
• Dahlgren and Whitehead model

  • Three levels of influence: The Person, The Community, The Environment
  • Factors at each level can be risk or protective factors
  • Factors at different levels interact and influence each other
• Four Social Capitals


  • Natural capital
  • Social capital
  • Human capital
  • Financial/Physical capital
• Upstream interventions


  Interventions that operate at the distal (macro) level such as government policies and international trade agreements
• Downstream interventions


  Interventions that operate at the proximal (micro) level which includes treatments, disease management or behavioural factors
• Structure


  Social and physical environmental conditions/patterns (social determinants) that influence the choices and opportunities available