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钢铁工人肥胖的风险因素分析和风险预测研究:基于职业健康检查队列数据集的模型开发
Zekun Zhao1, Haipeng Lu1, Rui Meng1
1School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China.
Lipids in health and disease
|January 8, 2024
概括
职业和生活方式因素导致钢铁工人肥胖. 随机森林模型证明了识别有风险的个体的最佳预测性能.
科学领域:
- 职业健康 职业健康 职业健康
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 肥胖是一个全球公共卫生问题,与心脏病,糖尿病和脂质失调等慢性疾病有关.
- 虽然人口,社会经济,生活方式和遗传因素是已知的因素,但肥胖的职业风险仍未得到充分研究.
- 确定钢铁工人的特定风险因素对于有针对性的健康干预至关重要.
研究的目的:
- 研究与钢铁工人肥胖相关的职业和生活方式风险因素.
- 在这个人群中开发和比较肥胖的预测模型.
主要方法:
- 一项针对中国一家钢铁公司的5469名工人的队列研究.
- 进行了单变量和多因素分析.
- 使用XG Boost,支持矢量机 (SVM) 和随机森林 (RF) 算法进行预测建模.
主要成果:
- 确定了主要的肥胖预测因素:年龄,性别,吸烟,饮酒,饮食,体力活动,轮班工作,高温,职业压力和一氧化碳暴露.
- 随机森林模型实现了0.912的最高曲线下面积 (AUC),表明了优异的预测性能.
- 模型准确度从0.819到0.872不等,随机森林显示了最好的结果.
结论:
- 钢铁工人的肥胖是多因素的,受职业暴露和生活方式选择的影响.
- 随机森林模型在预测钢铁工人中肥胖风险方面具有重要的实际应用潜力.
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