UNDERSTANDING THE EFFECTS OF AGE, PERIOD, AND COHORT ON INCIDENCE AND MORTALITY-RATES
UNDERSTANDING THE EFFECTS OF AGE, PERIOD, AND COHORT ON INCIDENCE AND MORTALITY-RATES
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DOI：
10.1146/annurev.pu.12.050191.002233
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发表时间：
1991-01-01
影响因子：
20.8
通讯作者：
HOLFORD, TR
中科院分区：
文献类型：
--
作者：
HOLFORD, TR
以人口为基础的发病率的时间趋势通常是通过按诊断期或死亡时间直接调整来总结的。同样，年龄的影响通常以给定诊断期的特定年龄比率来表示。如果缺乏长期数据，这些方法可能是必要的，因为它们提供了一种在监测趋势时每年更新信息的自然方式，或者它们可能是汇总大量数据(7、10、11、39、45)的便利方式。然而，这些总结只能针对给定时期的年龄影响进行调整；它们隐含地忽略了队列效应。队列效应是了解许多疾病的时间趋势的重要因素。因此，使用经常忽略它的数据分析策略是不可取的。建模的另一种选择是以图形方式显示特定年龄段的比率本身。正如我在导言中指出的那样，确定队列对结核病和肺癌等疾病的影响的一些最初分析完全依赖于图形分析。虽然图表当然是解释时间趋势的重要部分，但将你的分析限制在图表上的点的印象上是错误的。例如，这样的细读不会给出特定模式的统计意义的客观指示。回归分析迫使我们认识到解释发病率的时间趋势的一个基本问题--这是一个您应该记住的问题，即使在试图理解特定年龄的发病率的时间趋势的图形显示时也应该记住这个问题。
Time trends for population-based disease rates often are summarized by using direct adjustment by period of diagnosis or death. Similarly, the effect of age often is presented graphically as age-specific rates for a given period of diagnosis. These approaches may be necessary if there is an absence of long-term data, as they provide a natural way for annually updating information when monitoring trends, or they may be a convenient way of summarizing a large amount of data (7, 10, 11, 39, 45). However, these summaries only can adjust for the effect of age in a given period; they implicitly ignore the cohort effect. The effect of cohort is an important factor in understanding time trends for many diseases. Thus, it is not advisable to use data analytic strategies that routinely ignore it. Another alternative to modeling is to give a graphical presentation of the age-specific rates themselves. As I noted in the introduction, some of the first analyses to identify the effect of cohort on diseases, such as tuberculosis and lung cancer, relied entirely on a graphical analysis. Although graphs certainly are an important part of the interpretation of time trends, it would be a mistake to limit your analysis to impressions of points on a graph. For example, such a perusal would not give an objective indication of the statistical significance of a particular pattern. Regression analysis forces us to recognize a fundamental problem with interpreting time trends in disease rates--a problem that you should remember, even when trying to understand a graphical display of time trends in age-specific rates.