抗抑郁药物与其各种因素的关系,包括二氧化季节性:使用国家健康保险数据进行机器学习分析
Kwang-Sig Lee1, Hae-In Kim2, Byung-Joo Ham3
1AI Center, Korea University College of Medicine, Seoul, Republic of Korea.
Psychiatry investigation
|May 30, 2023
概括
邻里空气质量,特别是二氧化 (NO2) 的季节性,显著影响抗抑郁药物的使用. 机器学习确定了影响抗抑郁药物处方的环境和健康因素.
科学领域:
- 环境健康 环境健康
- 流行病学 流行病学
- 机器学习应用 机器学习应用
背景情况:
- 抗抑郁药物的使用是越来越严重的公共卫生问题.
- 越来越多地认识到环境因素对心理健康的影响.
研究的目的:
- 调查空气污染物,包括二氧化 (NO2) 季节性和抗抑郁药物使用之间的联系.
- 使用机器学习识别影响抗抑郁药物处方的关键因素.
主要方法:
- 利用了43,251名参与者的回顾性韩国国家健康保险服务索赔数据 (2002-2012).
- 对103个独立变量进行了分析,其中包括空气污染物 (PM2.5,PM10,NO2,O3,SO2,CO) 和人口因素.
- 使用机器学习 (随机森林) 和Cox危险比率进行变量重要性分析.
主要成果:
- 二氧化 (NO2) 季节性显示,在几个月内与抗抑郁药物使用具有统计学意义的关联.
- 最主要的预测因素包括年龄,偏头痛,睡眠障碍,肝病,运动和特定的空气污染物,如NO2和PM10在某些月份.
- 其他重要因素包括心血管疾病,喘,酒精消费,性别和社会经济指标.
结论:
- 邻里环境条件,特别是NO2季节性,与抗抑郁药物使用有很强的联系.
- 福利支持和各种健康状况也在抗抑郁药处方模式中发挥着重要作用.
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