Axelson O, Steenland K
Department of Occupational Medicine, Linkoping, Sweden.
Am J Ind Med. 1988;13(1):105-18. doi: 10.1002/ajim.4700130107.
For various reasons, data on smoking are frequently missing, or only partially available, in retrospective epidemiologic studies of occupational risk factors. In such situations, indirect methods may be used to evaluate the magnitude and direction of the potentially confounding effects of smoking. Such an evaluation can be made quantitatively or qualitatively. Here we describe both approaches. A specific problem relates to case-referent studies, where sampling variation in referent selection may limit the possibility of controlling for confounding by smoking, even when smoking data are available. We present data showing that estimates of risk from occupational exposures which are not controlled for smoking may be as accurate as estimates derived after controlling for smoking, when the number of referents is relatively small. The problem of interaction is also discussed. In the absence of smoking data, the investigator has no indication of how smoking and occupation jointly affect disease risk (eg, additively or multiplicatively). The multiplicative model is usually assumed. However, if exposure and smoking act independently (additively), rate ratios are diminished. In such situations, in the presence of negative confounding by smoking, rate ratios may actually even be less than one--also when exposure and disease are strongly related.
由于各种原因，在职业风险因素的回顾性流行病学研究中，吸烟数据常常缺失或仅部分可得。在这种情况下，可使用间接方法来评估吸烟潜在混杂效应的大小和方向。这种评估可以是定量的，也可以是定性的。在此我们描述这两种方法。一个具体问题与病例对照研究有关，在病例对照研究中，即使有吸烟数据，对照选择中的抽样变异也可能限制控制吸烟混杂效应的可能性。我们提供的数据表明，当对照数量相对较少时，未对吸烟进行控制的职业暴露风险估计可能与控制吸烟后得出的估计一样准确。交互作用问题也进行了讨论。在没有吸烟数据的情况下，研究者无法得知吸烟和职业如何共同影响疾病风险（例如，相加作用或相乘作用）。通常假定为相乘模型。然而，如果暴露和吸烟独立起作用（相加作用），率比会降低。在这种情况下，在存在吸烟的负混杂效应时，率比实际上甚至可能小于1——即使暴露与疾病密切相关时也是如此。
