Slattery Martha L, Murtaugh Maureen A, Quesenberry Charles, Caan Bette J, Edwards Sandra, Sweeney Carol
University of Utah, School of Medicine, Department of Medicine, Salt Lake City, Utah 84108 USA.
Epidemiol Perspect Innov. 2007 Oct 1;4:10. doi: 10.1186/1742-5573-4-10.
Epidemiologic studies have identified a number of lifestyle factors, e.g. diet, obesity, and use of certain medications, which affect risk of colon cancer. However, the magnitude and significance of risk factor-disease associations differ among studies. We propose that population trends of changing prevalence of risk factors explains some of the variability between studies when factors that change prevalence also modify the effect of other risk factors. We used data collected from population-based control who were selected as study participants for two time periods, 1991-1994 and 1997-2000, along with data from the literature, to examine changes in the population prevalence of aspirin and non-steroidal anti-inflammatory medication (NSAID) use, obesity, and hormone replacement therapy (HRT) over time. Data from a population-based colon cancer case-control study were used to estimate effect-measurement modification among these factors. Sizeable changes in aspirin use, HRT use, and the proportion of the population that is obese were observed between the 1980s and 2000. Use of NSAIDs interacted with BMI and HRT; HRT use interacted with body mass index (BMI). We estimate that as the prevalence of NSAIDs use changed from 10% to almost 50%, the colon cancer relative risk associated with BMI >30 would change from 1.3 to 1.9 because of the modifying effect of NSAIDs. Similarly, the relative risk estimated for BMI would increase as the prevalence of use of HRT among post-menopausal women increased. In conclusion, as population characteristics change over time, these changes may have an influence on relative risk estimates for colon cancer for other exposures because of effect-measure modification. The impact of population changes on comparability between epidemiologic studies can be kept to a minimum if investigators assess exposure-disease associations within strata of other exposures, and present results in a manner that allows comparisons across studies. Effect-measure modification is an important component of data analysis that should be evaluated to obtain a complete understanding of disease etiology.
流行病学研究已经确定了一些生活方式因素，例如饮食、肥胖以及某些药物的使用，这些因素会影响结肠癌风险。然而，不同研究中风险因素与疾病关联的程度和意义有所不同。我们认为，当改变患病率的因素也会改变其他风险因素的作用时，风险因素患病率的人群趋势可以解释不同研究之间的部分变异性。我们使用了从基于人群的对照组收集的数据，这些对照组在1991 - 1994年和1997 - 2000年这两个时间段被选作研究参与者，同时结合文献数据，来研究阿司匹林和非甾体抗炎药（NSAID）的使用、肥胖以及激素替代疗法（HRT）的人群患病率随时间的变化。基于人群的结肠癌病例对照研究的数据被用于估计这些因素之间的效应测量修正。在20世纪80年代到2000年期间，观察到阿司匹林使用、HRT使用以及肥胖人群比例有显著变化。NSAIDs的使用与体重指数（BMI）和HRT相互作用；HRT的使用与体重指数（BMI）相互作用。我们估计，随着NSAIDs使用的患病率从10%变化到近50%，由于NSAIDs的修正作用，与BMI>30相关的结肠癌相对风险将从1.3变为1.9。同样，随着绝经后女性中HRT使用的患病率增加，BMI的相对风险估计值也会增加。总之，随着人群特征随时间变化，由于效应测量修正，这些变化可能会影响其他暴露因素对结肠癌的相对风险估计。如果研究者在其他暴露因素的分层内评估暴露与疾病的关联，并以允许跨研究比较的方式呈现结果，那么人群变化对流行病学研究可比性的影响可以降至最低。效应测量修正是数据分析的一个重要组成部分，应该进行评估以全面理解疾病病因。
