Abstract

OBJECTIVES To identify different types of dilution bias in population-based interventions and to suggest measures for handling these methodological problems.

DESIGN Literature review plus analysis of data from a population-based intervention against cardiovascular disease in a Swedish municipality.

MAIN RESULTS The effects of an intervention on mortality and morbidity were much more diluted by non-intervening factors, dissemination to areas outside the intervention area, social diffusion, population mobility and time than by using intermediate outcome measures.

CONCLUSIONS Theoretically, changes in scientifically well documented risk factors, for example, intermediate outcome measures, should be preferred to using morbidity or mortality as outcome measures.