在劳动年龄人口中评估2型糖尿病的全球流行病学:通过可解释机器学习框架进行了为期60年的研究
Xuan Zhong1,2, Yijin Zheng3, Li Wang4
1Department of Non-Communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, China.
预计到2050年,劳动年龄人口中的2型糖尿病 (T2DM) 负担将大幅增加. 关键的驱动因素包括年龄,高血糖,BMI,空气污染和气候变化,需要有针对性的公共卫生战略.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 机器学习 机器学习
背景情况:
- 2型糖尿病 (T2DM) 是一个重大的全球健康挑战.
- 在劳动年龄人口 (WAP) 中,T2DM的负担需要特别注意,因为它对劳动力的影响.
- 了解流行病学趋势和预测因素对于有效的公共卫生干预至关重要.
研究的目的:
- 从1990年到2021年,描述T2DM负担在WAP中的流行病学趋势.
- 通过可解释的机器学习,预测到2050年的未来T2DM模式.
- 确定T2DM负担的关键驱动因素,以告知公共卫生战略.
主要方法:
- 利用了来自2021年全球疾病负担研究的颗粒状数据.
- 在WAP中使用极端梯度增强 (XGBoost) 模型用于T2DM负载预测.
- 应用了SHapley添加式解释 (SHAP) 来识别和解释驱动因素.
主要成果:
- 预计到2050年,WAP的全球T2DM事件案件将增加五倍.
- 北非/中东地区的T2DM负担增长最快.
- 社会人口指数和T2DM负担之间的反向关系正在逆转;高收入地区面临加速的速度.
- 年龄,高血糖,BMI和空气污染是关键因素;高温和酒精消费日益显著.
结论:
- 全球T2DM负担在WAP中令人担忧的趋势需要紧急关注,特别是在老龄化社会中.
- 推量身定制的WAP指南来减轻T2DM负担.
- 解决肥胖和气候变化对于有效的T2DM管理至关重要.
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