The use of population attributable risk to estimate the impact of prevention and early detection of type 2 diabetes on population-wide mortality risk in US males.

Abstract

The Population Attributable Risk (PAR) represents the proportion of the deaths (in a specified time) in the whole population that may be preventable if a cause of mortality were totally eliminated. This population-based measure was used to assess the potential impact of three public health interventions for type 2 diabetes (early detection + standard therapy; early detection + intensive therapy; and primary prevention) on the mortality risk from all causes and from cardiovascular (CVD) diseases. Potential reduction in mortality risks for several levels of compliance or implementation (25%, 50%, 75%, 100%) for each intervention were also estimated. Results suggest that among males aged 45-74 years, the interventions may have greater population-wide impact on total deaths among black males, and greater impact on the CVD deaths among white males. Overall, primary prevention (reduction in all-cause mortality 6.2-10.0%, and CVD mortality 7.9-9.0%) may offer greater marginal benefit than screening and early treatment (reduction in all-cause mortality 3.5-8.3%, and CVD mortality 2.8-8.6%). Often the question facing policy makers is not simply whether to but how much of an intervention is worth implementing? Estimated benefits for various intensities of intervention (as provided) may be useful to assess the likely marginal benefits of each intervention, and can be especially useful if combined with estimated marginal costs.