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一个贝叶斯式零膨胀空间变化系数模型,用于过度分散的二项式数据

Chun-Che Wen¹, Rajib Paul², Kelly J Hunt¹

¹Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.

Journal of the Royal Statistical Society. Series A, (Statistics in Society)

|November 20, 2025

概括

这项研究引入了一种新的统计模型,用于分析COVID-19大流行期间孕妇的心脏代谢风险因素 (CRF). 调查结果强调南卡罗来纳州特定的县有种族健康差异,建议针对性社区干预.

科学领域:

生物统计学生物统计学
流行病学流行病学
孕产妇健康孕产妇健康

背景情况:

怀孕中的心脏代谢风险因素 (CRF) 预测未来的孕产妇疾病,如中风和2型糖尿病.
由于相关的风险因素,CRF计数经常显示过度分散和零通胀.
南卡罗来纳州孕妇CRF的种族差异是一个重大的公共卫生问题.

研究的目的:

开发和应用一个时空空间统计模型来分析孕妇的CRF.
调查CRF的地理和时间趋势,重点关注COVID-19大流行期间的种族差异.
确定针对性干预措施的领域,以减少健康不平等.

主要方法:

在时空框架内开发了一个零膨胀的β-双项模型,以处理CRF计数中的过度分散和零膨胀.
纳入一个空间变化的系数模型来检查跨地理区域和时间的种族差异 (非西班牙裔白人与非西班牙裔黑人女性).
使用高效的混合马尔科夫链蒙特卡洛算法进行后置推理.

主要成果:

该模型有效地捕获了南卡罗来纳州孕妇CRF的时空模式和零通货膨胀.
分析显示,在CRF中存在显著的种族差异,这些差异因县和时间而异.
确定了特定的县 (例如,切斯特菲尔德,克拉伦登) 在种族健康差异方面表现出较小的差距.

结论:

开发的统计模型为分析流行病学研究中过度分散和零通货膨胀的复杂计数数据提供了强大的框架.
调查结果强调需要地理定制的干预措施来解决在孕产妇心脏代谢健康方面的种族不平等问题.
某些县有机会在社区层面集中努力,以减少健康差距.

关键词:

高斯马尔科夫随机场随机场.波利亚-玛数据增强技术心脏代谢风险心脏代谢风险健康差异的差异在健康上时间空间模型.在零膨胀的β-双项分布中,

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