Studying health risk and perceptions of riskEdexcel A-Level Biology A: Revision notes
Section 1
Analysing illness and mortality data
Morbidity is the rate of illness and mortality is the rate of death. To compare populations of different sizes, express data as a rate such as deaths per 100 000 people.
Worked example: Town X has 48 CHD deaths in a population of 32 000, so the rate is 48 ÷ 32 000 × 100 000 = 150 per 100 000. Town Y has 30 deaths in 12 500, a rate of 240 per 100 000. Town Y has fewer deaths but the higher risk, and its rate is 240 ÷ 150 = 1.6 times greater.
When interpreting data, quote figures from the table, use comparisons (such as ratios or percentage differences), and consider age, sex and lifestyle of the populations.
Do not compare raw numbers of deaths between populations of different sizes. Convert to a rate first.
Section 2
Correlation and causation
A correlation is a link between two variables. A causal relationship means a change in one directly produces the change in the other.
A correlation does not prove causation, because a confounding variable may affect both. For example, dog owners may have lower CHD death rates because they walk more, not because they own a dog.
Evidence for causation is stronger when there is a plausible mechanism, a dose-response pattern, consistent results from several studies, and an experiment or trial in which only one variable is changed.
Say 'there is a correlation' for data, and 'may be caused by' only when there is a mechanism or a controlled experiment.
Section 3
Conflicting evidence
Studies on health risk sometimes conflict. Possible reasons include different sample sizes and populations, different durations, different methods of measuring diet or lifestyle, and different outcomes (CHD events or a risk factor such as LDL cholesterol).
To judge conflicting evidence, compare sample size, duration, controls and the quality of the measurement. One study is rarely conclusive; the weight of evidence from several large, well-controlled studies is more convincing.
Section 4
Evaluating the design of risk studies
Health risk studies include cohort studies (a group followed over time), case-control studies (people with a disease compared with people without) and controlled trials.
- Sample selection: the sample must be representative of the population (random, covering ages, sexes and lifestyles). Volunteers from one group, such as a gym, are biased.
- Sample size: a larger sample reduces the effect of chance and anomalies, making results more reliable.
- Validity: the study must measure only what it claims to, so control confounding variables or match groups.
- Reliability: results should be repeatable; take repeat readings, calculate means and use statistical tests.
- Measurement: self-reported data (diet questionnaires) may be inaccurate.
Section 5
Perceptions of risk
People's perception of risk often differs from the actual risk.
Underestimating risk (for example of CHD):
- voluntary risks, such as smoking and diet, feel under personal control
- effects are long-term, with no immediate symptoms, while benefits are immediate
- optimism bias: 'it will not happen to me'
Overestimating risk (for example of violent crime or flying):
- dramatic, rare events receive heavy media coverage
- people fear risks they cannot control
Other factors include misunderstanding statistics, and the influence of family, friends and personal experience. Poor perception of risk affects lifestyle choices, so public health messages need clear data.
That's the notes covered.
Carry on to the next subtopic.
Exam questions on Studying health risk and perceptions of risk
- In a study of 5 000 adults aged 50 to 70, researchers recorded whether each person owned a dog and followed all of them for 10 years. The number of deaths from coronary heart disease (CHD) per 1 000 people per year was 2.1 for dog owners and 3.4 for people who did not own a dog.Explain why the researchers cannot conclude that owning a dog reduces the risk of CHD.2 marks
- Two towns recorded their deaths from CHD in the same year. Town X has a population of 32 000 and recorded 48 deaths from CHD. Town Y has a population of 12 500 and recorded 30 deaths from CHD.Calculate how many times greater the CHD mortality rate is in Town Y than in Town X, and suggest one factor, other than the town itself, that could explain the difference.2 marks
- A researcher wants to find out whether eating a high-salt diet raises blood pressure. She asks for volunteers at a local running club and recruits 20 of them. Ten eat a high-salt diet for four weeks and ten eat their normal diet. She measures each person's blood pressure once, at the end of the four weeks.Evaluate the way the researcher selected her sample and the size of her sample.3 marks
Written by the Exaim team, led by Shaun Daswani (Head of Upper Secondary, Improve ME Institute; MSc Financial Mathematics, Imperial College London; BSc, UCL) and Jason Daswani (operational lead, Improve ME Institute; LSE).