Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
PLoS One. 2012;7(6):e39461. doi: 10.1371/journal.pone.0039461. Epub 2012 Jun 19.
The additional clinical value of clustering cardiovascular risk factors to define the metabolic syndrome (MetS) is still under debate. However, it is unclear which cardiovascular risk factors tend to cluster predominately and how individual risk factor states change over time.
We used data from 3,187 individuals aged 20-79 years from the population-based Study of Health in Pomerania for a network-based approach to visualize clustered MetS risk factor states and their change over a five-year follow-up period. MetS was defined by harmonized Adult Treatment Panel III criteria, and each individual's risk factor burden was classified according to the five MetS components at baseline and follow-up. We used the map generator to depict 32 (2(5)) different states and highlight the most important transitions between the 1,024 (32(2)) possible states in the weighted directed network. At baseline, we found the largest fraction (19.3%) of all individuals free of any MetS risk factors and identified hypertension (15.4%) and central obesity (6.3%), as well as their combination (19.0%), as the most common MetS risk factors. Analyzing risk factor flow over the five-year follow-up, we found that most individuals remained in their risk factor state and that low high-density lipoprotein cholesterol (HDL) (6.3%) was the most prominent additional risk factor beyond hypertension and central obesity. Also among individuals without any MetS risk factor at baseline, low HDL (3.5%), hypertension (2.1%), and central obesity (1.6%) were the first risk factors to manifest during follow-up.
We identified hypertension and central obesity as the predominant MetS risk factor cluster and low HDL concentrations as the most prominent new onset risk factor.
将心血管危险因素聚类以定义代谢综合征（MetS）的额外临床价值仍存在争议。然而，尚不清楚哪些心血管危险因素倾向于主要聚类，以及个体危险因素状态随时间如何变化。
我们使用来自基于人群的波美拉尼亚健康研究中 3187 名年龄在 20-79 岁的个体的数据，采用基于网络的方法可视化聚类的 MetS 危险因素状态及其在五年随访期间的变化。MetS 采用协调一致的成人治疗小组 III 标准定义，根据基线和随访时的五个 MetS 成分对每个个体的危险因素负担进行分类。我们使用图谱生成器来描绘 32（2^5）种不同状态，并突出显示在加权有向网络中 1024（32^2）种可能状态之间最重要的转换。在基线时，我们发现所有个体中无任何 MetS 危险因素的比例最大（19.3%），并确定了高血压（15.4%）和中心性肥胖（6.3%），以及它们的组合（19.0%）是最常见的 MetS 危险因素。分析五年随访期间的危险因素流动情况，我们发现大多数个体保持在其危险因素状态，并且低高密度脂蛋白胆固醇（HDL）（6.3%）是高血压和中心性肥胖以外最突出的附加危险因素。在基线时没有任何 MetS 危险因素的个体中，低 HDL（3.5%）、高血压（2.1%）和中心性肥胖（1.6%）是在随访期间首先出现的危险因素。
我们确定高血压和中心性肥胖是 MetS 的主要危险因素聚类，低 HDL 浓度是最突出的新发病危险因素。
