使用空间微模拟估计县级健康指标
Erich Seamon1, Mohamed Megheib1, Christopher J Williams2
1Institute for Modeling, Collaboration, and Innovation (IMCI), University of Idaho, Moscow, Idaho, United States.
概括
使用代比例拟合 (IPF) 的小面积估计揭示了爱达荷州的地理模式.
科学领域:
- 公共卫生 公共卫生
- 生物统计学 生物统计学
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 在精细的空间尺度上了解健康结果对于有针对性的干预至关重要.
- 以前的小面积估计方法可能缺乏特定健康指标的精度.
研究的目的:
- 应用代比例拟合 (IPF) 对爱达荷州健康结果的小区域估计.
- 在县级确定肥胖,超重和糖尿病的空间聚类.
主要方法:
- 代比例拟合 (IPF) 适用于2019年爱达荷州行为风险因素监测系统 (BRFSS) 数据.
- 县级美国社区调查 (ACS) 数据用于限制 (年龄,种族,性别,教育).
- 优化的建模结构确定了重要的约束因素,并对内部和外部的估计进行了验证.
主要成果:
- 外部验证的模型结果显示在人口密的县有很强的相关性 (0.790.85,p < .05).
- 在爱达荷州中南部和西南部观察到更高的肥胖和超重患病率.
- 糖尿病估计集中在爱达荷州中部的县 (古丁,林肯,米尼多卡,杰罗姆).
结论:
- IPF为爱达荷州提供可靠的县级健康结果估计.
- 确定肥胖,超重和糖尿病患病率的地理差异.
- 估计与外部来源保持一致,农村地区的间隔较大.
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