L Lindholm1, M Rosén. 1. Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
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.
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.
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