Point and interval estimates of partial population attributable risks in cohort studies: examples and software
Point and interval estimates of partial population attributable risks in cohort studies: examples and software
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DOI：
10.1007/s10552-006-0090-y
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发表时间：
2007-06-01
影响因子：
2.3
通讯作者：
Wand, H. C.
中科院分区：
文献类型：
--
作者：
Spiegelman, D.;Hertzmark, E.;Wand, H. C.
人群归因危险度（PAR）百分比的概念在公共卫生研究中得到了广泛的应用。这一数量描述了如果从目标人群中消除某种特定的接触，可以预防的疾病的比例。我们提出了获得部分PAR的点和区间估计的方法，其中估计并应用于队列研究中的一些假定可修改的决定因素对疾病负担的影响。当疾病是多因素的时，部分PAR通常必须用于量化疾病的比例，如果从目标人群中消除特定暴露或暴露组，而其他可改变和不可改变的风险因素的分布不变，则可以预防疾病。在膀胱癌发病率的风险因素的研究中说明了该方法（Michaud DS等人，新英格兰医学杂志340（1999）1390）。一个用户友好的SAS宏实现本文所述的方法可通过全球网络。
The concept of the population attributable risk (PAR) percent has found widespread application in public health research. This quantity describes the proportion of a disease which could be prevented if a specific exposure were to be eliminated from a target population. We present methods for obtaining point and interval estimates of partial PARs, where the impact on disease burden for some presumably modifiable determinants is estimated in, and applied to, a cohort study. When the disease is multifactorial, the partial PAR must, in general, be used to quantify the proportion of disease which can be prevented if a specific exposure or group of exposures is eliminated from a target population, while the distribution of other modifiable and non-modifiable risk factors is unchanged. The methods are illustrated in a study of risk factors for bladder cancer incidence (Michaud DS et al., New England J Med 340 (1999) 1390). A user-friendly SAS macro implementing the methods described in this paper is available via the worldwide web.