Lindholm L, Rosén M
Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
J Epidemiol Community Health. 2000 Aug;54(8):617-22. doi: 10.1136/jech.54.8.617.
To identify different types of dilution bias in population-based interventions and to suggest measures for handling these methodological problems.
Literature review plus analysis of data from a population-based intervention against cardiovascular disease in a Swedish municipality.
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.
Theoretically, changes in scientifically well documented risk factors, for example, intermediate outcome measures, should be preferred to using morbidity or mortality as outcome measures.
识别基于人群的干预措施中不同类型的稀释偏倚，并提出处理这些方法学问题的措施。
文献综述以及对瑞典一个市政当局针对心血管疾病的基于人群的干预措施所获数据的分析。
与使用中间结局指标相比，干预对死亡率和发病率的影响更多地被非干预因素、干预区域以外地区的传播、社会扩散、人口流动和时间所稀释。
从理论上讲，与将发病率或死亡率作为结局指标相比，应优先选择科学记录良好的危险因素的变化，例如中间结局指标。
