Cumulative risk and population attributable fraction in prevention

Area of Science:

• Psychology
• Public Health
• Epidemiology

Background:

• Determining optimal target populations for multirisk prevention programs is crucial for public health.
• Relative risk and population attributable fraction are key epidemiological measures for risk assessment.
• Previous approaches may not fully optimize intervention impact across diverse populations.

Purpose of the Study:

• To compare the utility of relative risk and population attributable fraction.
• To identify the most effective measure for targeting populations in psychological prevention programs.
• To inform strategies for maximizing public health benefits in risk reduction initiatives.

Main Methods:

• Comparative analysis of relative risk and population attributable fraction.
• Utilized national datasets: British Births Cohort Study (BCS) and National Longitudinal Study of Youth (NLSY).
• Examined the relationship between cumulative risk levels and population impact.

Main Results:

• Relative risk increases with cumulative risk but may target small population segments.
• Population attributable fraction plateaus at moderate cumulative risk levels, indicating broader impact.
• Interventions targeting higher proportions of the population with moderate risk yield greater public health benefits.

Conclusions:

• Population attributable fraction is a more effective measure for guiding public health interventions.
• Prevention programs should target broader segments of the population with moderate risk for maximum impact.
• This approach enhances the efficiency and effectiveness of psychological multirisk prevention strategies.