AQA A Level Biology

Revision Notes

3.2.11 Correlations & Causal Relationships - The Lungs

Correlations & Causal Relationships - The Lungs

  • 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)
    • In this example, BMI would be on the x-axis and Incidence of Type 2 Diabetes on the y-axis
    • It is important to note that not everyone with a high BMI will develop Type 2 Diabetes, however more people with a high BMI will develop Type 2 Diabetes than those with low BMI
  • 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 lung diseases

  • A causal relationship has been proven for some risk factors relating to lung diseases
  • It is proven that smoking is a major risk factor for developing lung diseases such as emphysema
    • The chemicals in cigarettes damage the lungs and airways, making individuals more prone to developing the disease
    • This has been verified by other scientific investigations that have linked the chemicals to the damage which in turn leads to the disease
  • Risk factors that are more easily controlled and measured are more likely to have a proven causal relationship, as they can be investigated in a more scientific manner
    • For example, an individual’s exposure to smoking is much easier to quantify than their exposure to air pollution
  • When analysing data and studies it is always important to remember that risk factors interact with each other
    • For example, a smoker with asthma is likely to suffer the associated negative health side effects more quickly than a smoker without asthma
  • It is always important to remember that even though there is a correlation, this does not mean that there is a direct causal link
    • For example, in places with higher pollution, there may be more asthmatic individuals but this does not mean that pollution caused asthma as there are many other variables at play

Exam Tip

You should be able to translate information between graphical and numerical forms and extract and interpret information from charts, graphs and tables to determine risk factors.

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.
Close

Join Save My Exams

Download all our Revision Notes as PDFs

Try a Free Sample of our revision notes as a printable PDF.

Join Now
Already a member?
Go to Top