Cardiovascular disease and cancer: trends, risk and protective factors

Take the four measures in turn. The point of this card is that the four do not move together, and a strong answer says which moved and why.

Falling mortality with rising prevalence is the signature of successful treatment, not of a worsening problem. It converts a fatal disease into a chronic one, which is a genuine success and a permanent new cost.

That is also why “more people are diagnosed” cannot be read on its own. It can mean more disease, or the same disease found earlier, or more people alive to be diagnosed. Distinguishing those is the analysis.

Split every risk factor into non-modifiable and modifiable, because the split determines what any strategy can do.

• Non-modifiable, both conditions: age, sex, family history and inherited genetic risk, and for some cancers a specific inherited mutation. Age is the largest single risk factor for both, which is why an ageing population raises the count of cases even if nothing else changes.
• Modifiable, cardiovascular disease: tobacco smoking, high blood pressure, raised blood cholesterol, physical inactivity, poor diet including high salt intake, overweight and obesity, harmful alcohol use, diabetes, and chronic stress.
• Modifiable, cancer: tobacco smoking (by a wide margin the largest), ultraviolet radiation exposure, alcohol, overweight and obesity, poor diet and low physical activity, some infections such as human papillomavirus and hepatitis, and occupational exposures such as asbestos and diesel exhaust.

Notice how much the two lists share: smoking, alcohol, diet, activity and body weight appear in both. That overlap is the single most useful fact in this dot point, because it means one prevention effort buys reductions in two of Australia's largest causes of death at once. It is also why the leading causes of death respond to the same policies — and why the fall in smoking produced simultaneous gains in cardiovascular and cancer mortality decades later.

Two clarifications markers reward:

• Risk is probabilistic. A risk factor raises the chance; it does not determine the outcome. People with no modifiable risk factors still develop both conditions.
• Risk factors are themselves socially distributed. Smoking, poor diet and inactivity cluster by income, education and remoteness, so the “modifiable” label describes what is changeable at population level, not what any individual can simply decide.

Protective factors work at three levels, and answers that name only the first level lose marks in extended responses.

• Individual. Not smoking, regular physical activity, a diet high in vegetables, fruit, wholegrains and fibre and low in processed meat and salt, maintaining a healthy weight, limiting alcohol, sun protection, and managing blood pressure, cholesterol and blood glucose.
• Health system. Screening programs that find disease before symptoms — bowel, breast and cervical screening are the established Australian examples; vaccination that prevents cancer-causing infection, such as human papillomavirus vaccination; and access to primary care that detects and manages risk factors early.
• Structural and policy. Tobacco control, food regulation and labelling, alcohol pricing and availability, urban design that supports walking and cycling, sun-protection policies in schools and workplaces, and occupational exposure limits.

The strongest protective factors in Australian history have been structural, not individual. Tobacco control saved more lives than any individual decision to quit, because it changed the conditions under which those decisions were made.

A protective factor can also reduce harm after the condition occurs rather than preventing it. Rapid access to treatment for heart attack and stroke, cardiac rehabilitation, and follow-up care after cancer treatment all belong here, and they are a large part of why mortality has fallen while incidence has not fallen as fast.

This sub-point is the one most often skipped, and it is where the marks separating a Band 5 from a Band 6 answer sit. National improvement has not been shared equally.

• By socioeconomic position. Both conditions show a gradient: incidence, mortality and case fatality are all higher in more disadvantaged groups. Crucially, the rate of improvement has also been slower there, so the gap has widened for some measures even as the national figure improved.
• By remoteness. Outcomes worsen with remoteness. For cardiovascular events the mechanism is largely time to treatment; for cancer it is largely later stage at diagnosis, plus the cost and disruption of travelling for treatment.
• For Aboriginal and Torres Strait Islander Peoples. Higher rates, earlier onset, and poorer outcomes for both conditions, with the determinants described in Lesson 2.
• By sex. Cardiovascular disease has been more common and earlier in males, but it remains a leading cause of death in females and is under-recognised in them, partly because symptom patterns can differ from the classic presentation. Cancer patterns differ by type and by exposure history.
• By age. Both are strongly age-related, so an ageing population raises the number of cases even where age-standardised rates fall. This is why crude counts and standardised rates can tell opposite stories, and why the report you are reading has to be checked for which it uses.
• By cancer type. Survival has improved dramatically for some cancers and barely at all for others, notably those usually found late. An average across all cancers conceals that entirely.

The general lesson: improvement reaches the best-resourced groups first. A new screening program, a new medicine or a new campaign is taken up earliest by the people best placed to use it, so a successful intervention can widen a gap before it narrows it.

Pull it together, because this is the comparison an extended-response question is most likely to ask for.

• Cardiovascular disease is mostly a prevention story. The large fall in mortality came primarily from reducing exposure — less smoking, better-controlled blood pressure and cholesterol — with emergency treatment and rehabilitation adding to it. Prevention worked because a small number of modifiable risk factors account for a large share of the risk, and those factors respond to population-level policy.
• Cancer is mostly a detection-and-treatment story. Cancer is many diseases with many causes, so no single prevention measure could do for cancer what tobacco control did for heart disease — except tobacco control itself, which did exactly that for lung cancer. The rest of the gain has come from screening, earlier diagnosis and better treatment, which improve survival rather than preventing the disease.

Two consequences follow, and they are the sort of inference that earns a top band.

• The slowing of the cardiovascular mortality fall is what you would expect once the easiest exposure reductions have been achieved. Further gains need either harder policy or a focus on the groups improvement has not yet reached.
• Because cancer gains depend on detection and treatment, they are more sensitive to access than cardiovascular gains are. That is precisely why the cancer gradient by remoteness and socioeconomic position is so persistent.

For each combination, say what is most likely happening and what you would check to confirm it. No figures.

A government has funding for one initiative and must choose between: expanding an existing cancer screening program; a structural measure targeting a risk factor shared by both conditions; or improving time to treatment for cardiovascular events in regional areas.

Choose one. Say which measure would move first and which would move last, which groups would benefit soonest, and whether your choice would narrow or widen the gap in the short term. Then name the strongest argument against your own choice.