Shin Min-Seok, Lee Jea-Young
Department of Statistics, Yeungnam University, Gyeongsan 38541, Korea.
Healthcare (Basel). 2022 Feb 14;10(2):372. doi: 10.3390/healthcare10020372.
Metabolic syndrome can cause complications, such as stroke and cardiovascular disease. We aimed to propose a nomogram that visualizes and predicts the probability of metabolic syndrome occurrence after identifying risk factors related to metabolic syndrome for prevention and recognition. We created a nomogram related to metabolic syndrome in this paper for the first time. We analyzed data from the Korea National Health and Nutrition Examination Survey VII. Total 17,584 participants were included in this study, and the weighted sample population was 39,991,680, which was 98.1% of the actual Korean population in 2018. We identified 14 risk factors affecting metabolic syndrome using the Rao-Scott chi-squared test. Next, logistic regression analysis was performed to build a model for metabolic syndrome and 11 risk factors were finally obtained, including BMI, marriage, employment, education, age, stroke, sex, income, smoking, family history and age* sex. A nomogram was constructed to predict the occurrence of metabolic syndrome using these risk factors. Finally, the nomogram was verified using a receiver operating characteristic curve (ROC) and a calibration plot.
代谢综合征可引发并发症，如中风和心血管疾病。我们旨在提出一种列线图，该列线图能够在识别出与代谢综合征相关的风险因素后，直观呈现并预测代谢综合征发生的概率，以用于预防和识别。我们在本文中首次创建了与代谢综合征相关的列线图。我们分析了韩国国民健康与营养检查调查 VII 的数据。本研究共纳入 17584 名参与者，加权样本量为 39991680，占 2018 年韩国实际人口的 98.1%。我们使用 Rao-Scott 卡方检验确定了 14 个影响代谢综合征的风险因素。接下来，进行逻辑回归分析以构建代谢综合征模型，最终获得了 11 个风险因素，包括体重指数、婚姻状况、就业情况、教育程度、年龄、中风、性别、收入、吸烟、家族病史以及年龄*性别。利用这些风险因素构建了一个预测代谢综合征发生的列线图。最后，使用受试者工作特征曲线（ROC）和校准图对该列线图进行了验证。
