We use a stochastic age-period-cohort mortality model to analyse US data for years 1989-2015 and ages, separated by gender, educational attainment, and cause of death. The paper focuses, in particular, on the fitted cohort effect for each sub-population and cause of death with two key findings. First, causes of death with a strong or distinctively-shaped cohort effect are also causes of death with significant, controllable risk factors, and that the fitted cohort effect gives us insight into the underlying prevalence of specific risk factors (such as smoking prevalence). Second, although each sub-population and cause of death has its own distinctive model fit, there are sufficient similarities between cohort effects to allow us to postulate that there is a relatively small number of underlying controllable risk factors that drive these cohort effects. The analysis then gives us insight into the modelled cohort effect for all-cause mortality.

我们使用随机年龄段队列死亡率模型来分析1989-2015年和年龄的美国数据，并按性别，受教育程度和死亡原因进行分类。本文特别关注了每个亚群与死亡原因的拟合队列效应，并得出两个关键发现。首先，具有强烈或独特队列效应的死亡原因也是具有显着可控风险因素的死亡原因，而合适的队列效应使我们能够洞悉特定风险因素的潜在患病率（例如吸烟率）。其次，尽管每个子群体和死亡原因都有其独特的模型拟合，队列效应之间有足够的相似性，因此我们可以假设驱动这些队列效应的潜在可控危险因素相对较少。然后，该分析使我们深入了解了全因死亡率的模型队列效应。