AQA AS Biology

Revision Notes

3.5.9 Correlations & Causal Relationships - The Heart

Correlations & Causal Relationships - The Heart

  • Correlation is an association or relationship between variables
  • Causation occurs when one variable has an influence or is influenced by, another
  • There is a clear distinction between correlation and causation: a correlation does not necessarily imply a causative relationship

Recognising Correlations and Causal Relationships

  • Scientists present their findings from experiments in graphical and numerical forms to identify if there are relationships between risk factors and certain disease
  • Scatter diagrams are used to identify correlations between two variables to determine if a factor (such as obesity) does increase the risk of developing a disease (such as type 2 diabetes)
  • Correlation can be positive or negative
    • Positive correlation: as variable A increases, variable B increases
    • Negative correlation: as variable A increases, variable B decreases
  • If there is no correlation between variables the correlation coefficient will be 0

Types of correlation graphs, downloadable AS & A Level Biology revision notes

Image showing different types of correlation in scatter graphs

Risk factors & causal relationships for coronary heart diseases

  • Coronary heart disease (CHD) includes any condition that interferes with the coronary arteries which supply blood to the heart muscle
  • Many factors can increase the risk of developing CHD. Some factors are controllable while some factors can not be controlled
  • The main risk factors for CHD include:
    • Genetic factors, age and sex, high blood pressure, smoking, obesity and high concentrations of low-density lipoproteins (LDLs)
  • All of the risk factors for CHD can interact and affect one another
  • The causal relationship for some risk factors can be very clear
    • A diet high in LDLs will cause the lumens of blood vessels to narrow and the increase the likelihood of an atheroma developing in the coronary arteries
  • The interaction between risk factors in studies and investigations can make it hard to determine some causal relationships
  • For example, it would seem illogical that an overweight smoker would not suffer from CHD but that overweight, non-smoker would
    • The latter individual could have a strong genetic predisposition to CHD (that wasn’t picked up in the study) which when combined with high blood pressure from being overweight results in CHD
  • Therefore, it is very important when evaluating data on risk factors that you state that a factor increases or descreases the risk or that there is a correlation between a factor and an outcome but that this one factor is not necessarily the (only) cause 

Author: Lára

Lára graduated from Oxford University in Biological Sciences and has now been a science tutor working in the UK for several years. Lára has a particular interest in the area of infectious disease and epidemiology, and enjoys creating original educational materials that develop confidence and facilitate learning.
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