Risk factor assessment at the population level
To conduct sound public policy, it is necessary to assess the contribution of various risk factors (RF) at the population level. The population risk depends not only on the strength of the factor-disease association and the benefits of the intervention, but also on how widespread this risk factor (RF) is in the population.
For evaluation, indicators such as the frequency of new cases, prevalence, and population attributive risk are used. The frequency of new cases is the emergence of new cases of disease or risk factors (RF) for a certain period of time; prevalence is the proportion of people with a specific disease or risk factor (RF) at a given time.
The population attributive risk shows what amount of risk is caused by a given risk factor (RF), and depends on the proportion of people with this risk factor and on the magnitude of the associated risk.
Population attributive risk also reflects the relationship between exposure to a risk factor (RF) and a disease. Many factors linearly increase risk, so a population attributable risk can be calculated relative to the ideal standard or to an individual with a low risk.
For example, the relationship between hypertension and heart disease or cerebral stroke (MI) is linear, so a decrease in blood pressure at any elevated level reduces the risk. In contrast, the shape of the risk curve for obesity is not linear, the risk increases logarithmically, i.e. Each kilogram gained is associated with a higher risk for those who are already overweight.
Population attributive risk is an important criterion in determining the resources needed for carrying out various preventive interventions and determining priorities in measures to improve public health, such as anti-smoking campaigns. However, this chapter focuses on individual risk assessment for predicting future cardiovascular events (SSSob).