摘要
尝试引入贝叶斯样条对贝叶斯共同成分模型进行拓展,并基于1991-2011年《中国健康与营养调查》的实际数据探究高血压风险的空间变异与时间变异。研究发现:高血压风险(尤其是男性)大致呈现出北方高于南方的空间格局,且这一空间分布模式具有相对稳定性,这可能与北方各省份相似且稳定的生活方式(饮酒、膳食高盐等)有关。拓展后的SCM模型更充分地挖掘样本信息,揭示出高血压风险的空间格局及其随时间演变的规律,克服了空间分析时样本量相对不足的局限。
This paper tried to extend the existing Shared Component Model (SCM) by introducing the Bayesian spline and employed the extended model on the basis of 1991-2011 China Health and Nutrition Survey (CHNS). Results showed that the risk of hypertension (especially for males) generally showed a spatial pattern that is higher in the Northern China than that in the Southern China. Also, this pattern was relatively stable during the study period. This pattern may be related to the similar and stable lifestyle in the Northern areas, such as drinking alcohol, high salt diet, etc. The extended SCM is able to explore the sample information fully and reveal the spatial pattern and trend over time with respect of the risk of hypertension, thus overcome the limitation of limited sample size of spatial analysis.
作者
徐丽
方亚
XU Li;FANG Ya(College of Mathematics and Statistics, Guangdong Univers计y of Foreign Studies, Guangdong Guangzhou 510420, China;School of Public Health, Xiainen University, Fujian Xiamen 361102,China)
出处
《数理统计与管理》
CSSCI
北大核心
2019年第4期661-674,共14页
Journal of Applied Statistics and Management
基金
2015广东省教育厅创新强校青年创新人才类项目(自然科学类)(2015KQNCX036)
关键词
共同成分模型
贝叶斯样条
相对风险
高血压
shared component model
Bayesian spline
relative risk
hypertension
