Worked Solutions
Module 8: Non-infectious Disease and Disorders — Worked Solutions (HSC Biology)
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Worked examples for HSC Biology Module 8: Non-infectious Disease and Disorders. Each shows where the marks are awarded, the key idea, and a full model answer explained by your choice of tutor — Stella, Ella or Cassie.
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Attempt each question first, then check your answer against the model responses. Use the tutor tabs to read the solution in the style that suits you: Stella is direct and challenging, Ella is warm and explains the why, and Cassie is concise and analytical.
These questions reward systems thinking. For homeostasis, identify the stimulus, receptor, control centre, effector and response. For epidemiology, distinguish correlation from causation and justify your reasoning with the data.
Example 1 — Negative feedback and homeostasis
Question
Using blood glucose regulation as an example, explain how negative feedback maintains homeostasis after a person consumes a high-carbohydrate meal.
Solution
Homeostasis keeps blood glucose within a narrow range, and negative feedback is the mechanism that reverses any change.
After a high-carbohydrate meal, blood glucose rises above the set point. This is the stimulus, detected by receptor cells in the pancreas.
In response, the pancreas (the control centre) secretes insulin. Insulin acts on effectors — mainly the liver and muscle cells — stimulating them to take up glucose and convert it to glycogen for storage.
As glucose is removed from the blood, the level falls back toward the set point. Once it returns to normal, insulin secretion decreases.
This is negative feedback because the response (lowering glucose) opposes and corrects the original change (rising glucose), restoring the internal balance.
The whole idea of homeostasis is keeping an internal condition — here, blood glucose — stable around a set point, even when the outside world keeps changing it. Negative feedback is how the body does that, and it always works by opposing the change.
Let's walk through it. After a high-carb meal, glucose is absorbed and blood glucose rises above the set point. That rise is the stimulus. Receptor cells in the pancreas detect it.
The pancreas then acts as the control centre and releases insulin into the blood. Insulin travels to the effectors — your liver and muscle cells — and signals them to take glucose out of the blood and store it as glycogen.
As they do this, blood glucose falls back toward the set point. And here's the self-correcting part: once glucose is back to normal, the stimulus is gone, so insulin secretion drops off.
It's called negative feedback because the response pushes the variable in the opposite direction to the change — high glucose triggers a response that lowers glucose. That's exactly what keeps the system balanced.
Negative feedback loop for blood glucose:
- Stimulus: high-carb meal → blood glucose rises above set point
- Receptor: pancreatic cells detect the rise
- Control centre / response: pancreas secretes insulin
- Effectors: liver and muscle cells take up glucose, store as glycogen
- Result: blood glucose falls to set point; insulin secretion decreases
Negative feedback = response opposes the change, restoring homeostasis.
Where the marks go
- 1 mark: Identifies the stimulus as a rise in blood glucose above the set point
- 1 mark: Identifies the pancreas detecting the change and secreting insulin
- 1 mark: Describes effectors (liver/muscle) taking up glucose and storing it as glycogen
- 1 mark: States that blood glucose returns to the set point and insulin secretion decreases
- 1 mark: Explains that the response opposes the original change (negative feedback)
Key idea
Negative feedback maintains homeostasis by triggering a response that opposes and reverses a change — rising glucose stimulates insulin, which lowers glucose back to the set point.
Example 2 — Epidemiology and causation
Question
An epidemiological study finds that the incidence of type 2 diabetes is higher in a population with low levels of physical activity than in a more active population. Explain why this correlation alone does not establish that inactivity causes type 2 diabetes, and describe what epidemiologists do to strengthen a claim of causation.
Solution
A correlation shows that two variables change together, but it does not prove one causes the other. Here, low activity and higher diabetes incidence occur together, but the association could be explained by confounding variables — for example diet, body weight, genetics or socioeconomic factors — that are linked to both inactivity and diabetes. The relationship could also run the other way, or be coincidental.
To strengthen a causal claim, epidemiologists:
- repeat studies across different, large populations to check the pattern is consistent
- control for confounding variables so other factors are accounted for
- look for a dose–response relationship (more inactivity → more disease)
- seek a plausible biological mechanism linking inactivity to insulin resistance
When the association is strong, consistent, dose-dependent and biologically plausible, the case for causation is much stronger.
This question is really about the difference between correlation and causation, which is one of the most important ideas in epidemiology.
A correlation just means two things tend to occur together — here, lower physical activity and higher rates of type 2 diabetes. The trap is assuming that "together" means "one causes the other." It might not, because of confounding variables: things like diet, obesity, genetics or socioeconomic status could independently affect both activity levels and diabetes risk. The cause-and-effect could even be reversed, or the link could simply be chance.
So how do epidemiologists build a stronger case for causation? They:
- repeat the study in large and varied populations to see if the pattern holds
- control for confounding variables so they can isolate the factor of interest
- look for a dose–response relationship — does more inactivity reliably mean more disease?
- identify a plausible biological mechanism (e.g. how inactivity contributes to insulin resistance)
When the link is strong, consistent across studies, shows a dose–response, and makes biological sense, scientists can be much more confident that the relationship is genuinely causal.
Why correlation ≠ causation:
- Correlation = variables change together, not proof of cause
- Confounding variables (diet, weight, genetics, socioeconomic) may explain both
- Direction could be reversed or association coincidental
Strengthening a causal claim:
- Repeat across large, varied populations (consistency)
- Control for confounding variables
- Establish a dose–response relationship
- Identify a plausible biological mechanism
Strong + consistent + dose-dependent + plausible → stronger case for causation.
Where the marks go
- 1 mark: States that correlation shows association but not necessarily causation
- 1 mark: Identifies confounding variables (or reverse/coincidental relationships) as alternative explanations
- 1 mark: Describes controlling for confounders and/or repeating across large populations
- 1 mark: Describes seeking a dose–response relationship and/or a plausible biological mechanism
Key idea
A correlation does not prove causation because of confounding variables; epidemiologists build a causal case through consistency, controlling confounders, dose–response and a plausible mechanism.