Risk Factors for Sarcopenia, Sarcopenic Obesity, and Sarcopenia Without Obesity in Older Adults

Seo-hyun Kim, C. Yi, Jin-seok Lim
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引用次数: 1

Abstract

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008–2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.
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老年人肌肉减少症、肌肉减少性肥胖和无肥胖的肌肉减少症的危险因素
背景:随着年龄的增长,肌肉不断发生变化。肌肉减少症,即肌肉质量随着年龄的增长而减少,与各种疾病、跌倒的风险和生活质量的下降有关。肥胖和肌肉减少症对老年人的疾病也有协同作用。目的:探讨肌少症、肌少性肥胖和非肥胖型肌少症的危险因素,并建立预测模型。方法:本机器学习研究使用2008-2011年韩国国家健康和营养检查调查进行分析。数据整理后,选择了5563名老年参与者,其中1169人患有肌肉减少症,538人患有肌肉减少性肥胖,631人患有肌肉减少症但没有肥胖;其余4394例正常。决策树和随机森林模型用于识别风险因素。结果:两种方法选择的肌少症危险因素分别为体重指数(BMI)和中等体力活动时间;肌肉减少型肥胖的影响因素是性别、BMI和适度体育活动的持续时间;而没有肥胖的肌肉减少症则是BMI和性别。所有预测模型的受试者工作特征曲线下面积均大于0.75。BMI可以预测肌肉减少症相关疾病。结论:应明确肌少症相关疾病的危险因素,制定肌少症相关疾病的预防方案。应利用人口数据进行数据挖掘研究,通过预测模型提高对肌少症相关疾病患者早期治疗的有效性。
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