1.2 Data and disease

The Media provides us with the latest stats and research concerning the connection between various factors & incidence of disease. Some of this info appears contradictory. So what can we believe? How can we determine if information is good or bad?

Epidemiology - study of the incidence (number of cases) and pattern of a disease with a view of finding the means of preventing and controlling it.Epidemiologists do this by collecting data on diseases and then looking for a pattern/relationship between these diseases and the factors in the lives of people who have them.

When analysing and interpreting data on disease for example a graph  TALK ABOUT:* The main pattern on the graph, is there a pattern?* Where there's a change in the graph - compare and give reasons why this change could have occurred.* Overall interpretation* Differences in the different points in the graph*FIGURES from the graph* And so what does this mean (possibly) and how do you know this?!                              ETC..

A correlation occurs when a change in one of two variables is reflected by a change in another variable 

1.2 DATA AND DISEASE

We can only suggest WHY a certain disease is being causes by something we CANNOT conclude because why because we don't have enough evidence (we would need experimental evidence in this case). e.g we cannot say " Cancer is caused by drinking alcohol", but what we should say is " The graph illustrates that a person who doesn't drink alcohol at all is less prone to developing Cancer later in life than a person who has 6 drinks of Alcohol every day." as it is a correlation NOT a cause It could be stress that makes people drink more alcohol and as a result the stress is the actual cause of the cancer. 

RECOGNISING THE DISTINCTION BETWEEN A CORRELATION AND A CASUAL RELATIONSHIP IS A NECESSARY AND IMPORTANT SKILL.

IT IS IMPORTANT TO BE CLEAR THAT A CORRELATION DOES NOT MEAN THAT THERE IS A CASUAL LINK.

Consider the following questions when deciding how reliable data is: Has the right factor been measured and have the correct questions been asked? How were the data gathered, were the methods reliable and was the right apparatus used? Do those collecting the data have a vested interest in the outcome of the research? Has the study been repeated, with the same results and conclusions, by other people?  Are there still unanswered questions?

My rough very basic answers to textbook questions (ignore if you don't have the AQA Biology AS Nelson Thornes textbook)1.People who have quit smoking for more than 30 years had a lower risk of developing lung cancer than people who have given up 1-4 years ago.Also, the more cigarettes you smoked per day before giving up, the higher your rick of developing of developing lung cancer.2.The information does not show a casual relationship between the correlations i have identified because the people in the sample may just live in cold areas where smoking occurs alot to keep themselves warm when in actual fact, it could be the over-exposure to cold that could cause a higher risk of developing Lung cancer.3.tHe Y-AXIS IS LABELLED AS THIS as it illustrates the probability of someone developing a disease based on how they live their life. This probability is measured as a number from 0 percent which means no harm and 100 percent which indicated harm will certainly occur.

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