analysing data on illness and mortality

• correlation between a risk factor and a disease

  does NOT mean a causal relationship ecists

  many other factors will influence likelihood of disease

  these factors need to be taken into account when analysing and interpreting data
• what is describing data

  identifying trends and stating what the results show

  USE NUMBERS from data to back up descriptions
• drawing conclusions from data

  working what data shows about RELATIONSHIPS between variables (Association, correlation)

  conclusions should be limited to what data show

  CAUSAL RELATIONSHIPS CANNOT BE CONCLUDED FROM ONE DATA SET

  conclusions cannot extrapolated beyond setting of study
• evaluating validity of data

  (strengths)

  larger sample size -> valid results, sample more representative of pop

  statistical analysis -> check any differences between reslts are stat significant

  use control to compare results

  repeated studies before conclusion drawn

  control any variable not being tested

  no bias from researchers
• recognising conflicting evidence 


  evidence from ONE study not enough to conclude ONE RISK FACTOR is a risk to health or associated with particular disease

  studies SIMILAR in design would need to be analysed TOGETHER to make links (META ANALYSIS)

  similar conclusions need to be drawn from ALL STUDIES in order to accept findings

  conflicting evidence -> more reserach needed, other variables involved
• evaluating experimental design/design of studies

  . clear aim

  . representative sample (avoid selection bias)

  . sample size must be large

  . randomly select participants

  . controlled variables, more reliable and valid data

  . repeatable and reproducable method

  . use of an experimental control
• (perception of risk) what is risk?

  the chance or probability that a harmful event will occur
• the statistical chance of a harmful event occuring needs to be supported by scientific evidence gained from research
• an individual's perception of risk may be different to the actual risk of something occurring
• why can risk be OVERESTIMATED (What factors) ?

  misleading information in media

  overexposure to information

  personal experience of the associated risk

  unfamiliarity with the event

  event causing severe harm
• why can a risk be underestimated ?


  lack of information

  misunderstanding of factors that increase the risk

  lack of personal experience of risk

  unfamiliarity with event

  harm being non immediate
• analysing data on energy budgets and diet

  data on energy budgets may be given in calories, kilocalories, or kilojoules

  1 calories = 1 kilocalorie = 1 kilojoule

  adult needs 8700KJ
• energy budget

  energy input - energy output
• consequences of energy imbalance

  weight loss, weight gain, development of obesity
• energy budgets should be balanced, amount of energy taken in should be equal to amount used or transferred

  difference in energy taken in and energy used will affect an individuals weight
• weight gain 


  energy intake is higher than energy output , excess energy is converted into fats by body so person will gain weight
• development of obesity 


  if energy output remains less than intake over sustained period of time individual may become overweight and obese
• weight loss


  energy intake less than energy output, body will need to take energy from elsewhere

  fat reserves will be converted into energy, person will lose weight

  if the energy difference is large over a sustained period of time individual may become underweight
• risk factors of CVD

  high blood pressure

  obesity

  blood cholesterol

  smoking

  inactivity

  genetic inheritance
• what are 6 risk factors of cvd

  high blood pressure, obesity, blood cholesterol, smoking, inactivity, genetic inheritance