在韩国成年人中发现与维生素D缺乏相关的因素,使用基于机器学习和统计技术的综合分析的KNHANES数据
Hongryul Ahn1, Seungwon Kim1, Jinmyung Jung1
1Division of Data Science, College of Information and Communication Technology, The University of Suwon, Hwaseong 18323, Republic of Korea.
Nutrients
|February 26, 2025
概括
在韩国,维生素D缺乏与饮食,生活方式和生化因素有关. 机器学习确定了根据年龄和性别不同的关键关联,强调综合分析策略.
科学领域:
- 公共卫生 公共卫生
- 营养科学 营养科学
- 生物统计学 生物统计学
背景情况:
- 维生素D缺乏 (VDD) 是一个全球性健康问题,与代谢和免疫问题有关.
- 已知的危险因素存在,但大规模的综合性研究有限.
- 韩国面临着需要详细调查的VDD挑战.
研究的目的:
- 在韩国人口中确定与VDD相关的因素.
- 利用机器学习和统计分析进行全面的因素识别.
- 探索与VDD的特定年龄和性别的关联.
主要方法:
- 使用韩国国家健康和营养检查调查 (KNHANES) IX-1数据进行横截面研究.
- 应用了六个机器学习算法来识别与VDD相关的因素.
- 使用多变量回归模型,按性别和年龄分层进行详细分析.
主要成果:
- 使用CatBoost模型确定了17个与VDD相关的因素.
- 食补充剂的使用在所有年龄和性别群体中始终与VDD有关.
- 诸如HDL胆固醇,肌素,水摄入量和早餐频率等因素在年轻人中显示出显著的关联,与血尿素,葡萄糖和尿的性别特异联系.
结论:
- 在韩国,与VDD相关的关键因素是多种多样的,并且根据年龄和性别而异.
- VDD受到饮食,生活方式和生化因素的复杂相互作用的影响.
- 结合机器学习和统计分析的综合方法对于有效的VDD策略至关重要.
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