摘要
目的基于对中国疾病预测研究的发展沿革、预测方法及研究瓶颈分析,旨在通过优化慢性病趋势预测模式为中国慢性病防治提供一定的理论依据。方法通过文献荟萃分析,系统梳理中国慢性病预测发展现状及瓶颈,分析优化预测模式。结果中国慢性病预测重视度不足,人群发病率预测较匮乏,方法学应用仍停留在线性或多元回归层面。从人口、经济、社会3个范畴筛选出影响因素变量构建状态空间模型,该优化模式比其他的时间序列自回归模型的拟合优度更高。结论状态空间模型用于构建特定区域的慢性病趋势预测模型,可大大提高长期预测的精度和灵敏性,为循证决策提供强有力支撑。
Objective To analyze the development,methodology,and bottleneck of research on prediction of for chronic disease prevalence trend in China and to provide a theoretical basis by optimizing prevalence prediction model prevention and control of chronic diseases.and Methods We conducted disease a meta-analysis of relevant literatures,systemically reviewed development disease status bottlenecks of chronic prevalence prediction in China,and optimized chronic models for chronic prevalence prediction.few Results There is a lack in concerns to the prediction The for disease prevalence is trend and there are a studies on prediction of chronic out disease incidence.application of methodology still restricted to linear or multiple regression.We screened with influential variants in scopes model of population,economy,and society than and then time constructed a state space model those variants.The The established demonstrated conducting a higher fitness other series autoregressive models.region Conclusion use of state space model in prevalence prediction prediction and of chronic strong disease for a specific could improve the precision and sensitivity of long term to provide evidences for evidence-based decision-making.
出处
《中国公共卫生》
CAS
CSCD
北大核心
2017年第11期1552-1555,共4页
Chinese Journal of Public Health
基金
2016年中央高校优秀青年教师计划(英才类)
中国博士后科学基金项目(2016M591719)
国家自然科学基金青年项目(71403185&71603182)
2016年度上海市卫计委科研课题(20164Y0161)
关键词
慢性病
趋势预测
瓶颈
优化模式
chronic disease
trend prediction
bottleneck
optimization model
