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弗吉尼亚州的肺癌患病率:通过INLA的空间邮政编码水平分析

Indranil Sahoo¹, Jinlei Zhao², Xiaoyan Deng³

¹Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA.

Current oncology (Toronto, Ont.)

|March 27, 2024

概括

弗吉尼亚州邮政编码中的肺癌率与吸烟,社会剥夺以及种族,年龄和性别等人口统计数据有关. 这些发现有助于针对癌症差异制定有针对性的公共卫生干预措施.

科学领域:

流行病学流行病学
公共卫生公共卫生
空间分析空间分析

背景情况:

肺癌 (LC) 在弗吉尼亚州 (VA) 提出了重大公共卫生挑战.
了解LC患病率驱动因素需要检查人口,环境和社会经济因素.
在邮政编码层面进行空间分析对于本地化洞察至关重要.

研究的目的:

调查弗吉尼亚州邮政编码中肺癌患病率的潜在驱动因素.
为了调整空间关联,并考虑缺少的共变量数据.
为有针对性的公共卫生干预和资源分配提供见解.

主要方法:

使用集成嵌套拉普拉斯近似法 (INLA) 的贝叶斯层次模型.
空间波桑和负二项式回归模型包含条件自回归 (CAR) 先验.
在潜伏的高斯马尔科夫随机场 (GMRF) 假设下同时归算缺失的共变量.

主要成果:

较高的吸烟指数和社会贫困指数 (SDI) 分数与较高的LC数量相关.
在有较大白人和黑人人口的邮政编码和老年人群 (≥65岁) 中观察到较高的LC流行率.
在西班牙裔人口较多的邮政编码中,LC数量较低;女性患病率高于男性.

结论:

人口和社会经济因素显著影响了弗吉尼亚州邮政编码级别的肺癌差异.
这些发现支持有针对性的公共卫生战略的需要,以解决LC患病率的变化.
实施代码在GitHub上公开提供,以便进一步研究.

关键词:

在这里,INLALA.离散响应的离散响应.肺癌是一种肺癌.缺少的共变量归算.空间数据空间数据空间数据邮政编码层面的分析分析

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