Public Health and Health Promotion
What this domain tests
This domain tests determinants of health, levels of prevention, epidemiological measures, screening, vaccination and health-promotion strategies. Expect interpretation of rates and critical appraisal of prevention claims.
Core rules
- Determinants include biological, behavioural, social, economic, environmental and health-system factors. Social determinants such as income, education and housing produce much of the inequality in health outcomes.
- Primary prevention prevents disease before it occurs, for example vaccination and smoking prevention. Secondary prevention detects disease early, for example screening. Tertiary prevention limits disability and complications after disease is established.
- Incidence is the number of new cases in a population at risk over a period. Prevalence is all existing cases in a population at a point or period.
- Screening requires a common and serious condition, a detectable early stage, an acceptable test, effective treatment and adequate follow-up. A positive screening test is not a diagnosis.
- Herd immunity protects unvaccinated people when a high enough proportion of the population is immune.
- Health promotion enables people to increase control over their health through healthy public policy, supportive environments, community action, personal skills and reorientation of services.
- Evaluate programmes with clear outcome measures and attention to reach, equity and unintended effects.
Worked example
In a town of 10,000 adults, 300 are already known to have diabetes at the start of the year and 100 new cases are diagnosed during the year. Prevalence at the start is 300 ÷ 10,000 = 3%. Incidence during the year is 100 ÷ 9,700 at risk = approximately 10.3 per 1,000 person-years. The reasoning is to remove existing cases from the denominator for incidence and to state the time period, because incidence and prevalence answer different questions.
Traps that cost marks
- Using prevalence when the question asks about risk of developing disease.
- Confusing a positive screening test with a confirmed diagnosis.
- Ignoring lead-time bias, which makes screening appear to prolong survival without changing the time of death.
- Comparing crude rates between populations with different age structures without standardisation.
- Claiming causation from an association found in a cross-sectional survey.