终身累积风险因素可预测芬兰一项长达 50 年随访研究中的心血管疾病死亡率。
Lifetime cumulative risk factors predict cardiovascular disease mortality in a 50-year follow-up study in Finland.
机构信息
Department of Mathematics and Statistics, University of Jyvaskyla, Jyväskylä, Finland, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland and Hospital District of North Karelia, Joensuu, Finland jaakko.o.reinikainen@jyu.
Department of Mathematics and Statistics, University of Jyvaskyla, Jyväskylä, Finland, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland and Hospital District of North Karelia, Joensuu, Finland Department of Mathematics and Statistics, University of Jyvaskyla, Jyväskylä, Finland, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland and Hospital District of North Karelia, Joensuu, Finland Department of Mathematics and Statistics, University of Jyvaskyla, Jyväskylä, Finland, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland and Hospital District of North Karelia, Joensuu, Finland.
出版信息
Int J Epidemiol. 2015 Feb;44(1):108-16. doi: 10.1093/ije/dyu235. Epub 2014 Dec 12.
BACKGROUND
Systolic blood pressure, total cholesterol and smoking are known predictors of cardiovascular disease (CVD) mortality. Less is known about the effect of lifetime accumulation and changes of risk factors over time as predictors of CVD mortality, especially in very long follow-up studies.
METHODS
Data from the Finnish cohorts of the Seven Countries Study were used. The baseline examination was in 1959 and seven re-examinations were carried out at approximately 5-year intervals. Cohorts were followed up for mortality until the end of 2011. Time-dependent Cox models with regular time-updated risk factors, time-dependent averages of risk factors and latest changes in risk factors, using smoothing splines to discover nonlinear effects, were used to analyse the predictive effect of risk factors for CVD mortality.
RESULTS
A model using cumulative risk factors, modelled as the individual-level averages of several risk factor measurements over time, predicted CVD mortality better than a model using the most recent measurement information. This difference seemed to be most prominent for systolic blood pressure. U-shaped effects of the original predictors can be explained by partitioning a risk factor effect between the recent level and the change trajectory. The change in body mass index predicted the risk although body mass index itself did not.
CONCLUSIONS
The lifetime accumulation of risk factors and the observed changes in risk factor levels over time are strong predictors of CVD mortality. It is important to investigate different ways of using the longitudinal risk factor measurements to take full advantage of them.
背景
收缩压、总胆固醇和吸烟是已知的心血管疾病（CVD）死亡率预测因子。对于随着时间的推移，风险因素的终生积累和变化作为 CVD 死亡率的预测因子的影响，了解较少，尤其是在非常长的随访研究中。
方法
使用来自七国研究芬兰队列的数据。基线检查在 1959 年进行，每隔约 5 年进行七次复查。队列一直随访至 2011 年底。使用时间相关的 Cox 模型，带有定期更新的风险因素、风险因素的时间相关平均值和风险因素的最新变化，使用平滑样条来发现非线性效应，分析风险因素对 CVD 死亡率的预测效果。
结果
使用累积风险因素的模型，将其建模为随时间推移的几个风险因素测量值的个体水平平均值，比使用最新测量信息的模型预测 CVD 死亡率更好。这种差异对于收缩压似乎最为明显。原始预测因子的 U 形效应可以通过在最近水平和变化轨迹之间划分风险因子效应来解释。尽管体重指数本身并没有，但体重指数的变化预测了风险。
结论
风险因素的终生积累以及随时间推移观察到的风险因素水平的变化是 CVD 死亡率的强有力预测因子。重要的是要研究利用纵向风险因素测量值的不同方法，以充分利用它们。
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