Hanrahan L P, Mirkin I, Olson J, Anderson H A, Fiore B J
Wisconsin Department of Health and Social Services, Madison.
Am J Epidemiol. 1990 Jul;132(1 Suppl):S116-22. doi: 10.1093/oxfordjournals.aje.a115772.
Increasingly, health departments are being pressed by the public to respond to disease risk with cluster investigations in communities and neighborhoods. This is a direct result of growing concern about the role that the environment may play in disease risk. While extensive analyses directly inputing exposures or numbers at risk are often necessary to thoroughly investigate clusters, it is quite useful to perform an exploratory analysis with existing morbidity and mortality data as a first level of response. To meet this need for timely evaluation, the authors describe a user-friendly Statistical Analysis System (SAS) program called SMRFIT to automate community disease cluster evaluations. The program creates frequency tables for number at risk and number of disease outcomes for the community, balance of parent county, and balance of state. SMRFIT then constructs standardized mortality ratios, with the community compared with balance of county and balance of state referents. Poisson regression is offered as an option for the modeling of community disease rates.
卫生部门越来越受到公众的压力，要求其通过对社区和邻里进行聚集性调查来应对疾病风险。这是公众日益关注环境在疾病风险中可能发挥的作用的直接结果。虽然在彻底调查聚集性病例时，通常需要进行广泛的分析，直接输入暴露因素或危险人群数量，但利用现有的发病率和死亡率数据进行探索性分析作为第一级应对措施是非常有用的。为满足及时评估的这一需求，作者描述了一个名为SMRFIT的用户友好型统计分析系统（SAS）程序，以实现社区疾病聚集性评估的自动化。该程序为社区的危险人群数量和疾病结局数量、母县的平衡情况以及州的平衡情况创建频率表。然后，SMRFIT构建标准化死亡率，将社区与县平衡情况和州平衡情况的参照对象进行比较。泊松回归作为一种选择，用于对社区疾病发病率进行建模。
