气候变化与脑卒中死亡关系之时空流行病学研究

项目名称： 气候变化与脑卒中死亡关系之时空流行病学研究

项目编号： No.81502892

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 医药、卫生

项目作者： 齐欣

作者单位： 西安交通大学

项目金额： 18万元

中文摘要： 时空流行病学研究可为长时间大范围评价气候变化对心血管疾病影响提供新的证据，尤其是贝叶斯方法能够在调节空间自相关基础上发现影响疾病死亡率增高的气候变化阈值、并控制空间不稳定因素、评价不同变量与疾病相关程度的差异，但以往国内外鲜有报道。本研究拟利用陕西省2005-2014年脑卒中死亡登记资料，运用GIS探索不同性别和年龄人群脑卒中死亡时空分布并寻找高危聚集区域；运用时间序列分析法结合GAM和DLNM模型分析若干高危聚集区域气象及空气污染与人群脑卒中死亡之关系，并比较不同地区结果；运用贝叶斯CART模型寻找与人群死亡率时空变化相关的以上因素及社会经济因素阈值；运用贝叶斯CAR模型分析以上因素在不同时间段及地区与脑卒中死亡之关系及显著因素，全面评价气候变化影响脑卒中死亡率的时空差异，建立针对极端天气和空气污染的心血管疾病预测预警系统，为我国脑卒中防治规划提供科学依据。促进该新研究方法在国内的应用。

中文关键词： 气候变化；脑卒中；时空分析；预测预警

英文摘要： Spatiotemporal epidemiological study can provide new evidence for examining the impact of climate change on cardiovascular disease (CVD) over a long term and across large geographical areas. Bayesian spatial methods may discover the threshold of climate change affecting the increase of particular disease, control spatial instability, and evaluate the difference of associations between multi-variables and disease occurrence. Few studies have examined the above issue. This study used the registered deaths of stroke (2005-2014) in Shaanxi Province, China with involvement of population, climate, air pollution and socioeconomic factors at the county level. Geographical Information System (GIS) was applied to display the spatiotemporal variation of stroke mortality and detect high risk clusters over time and space. Time-series analysis was used to examine the lag-effect of associations of climate, air pollution variables and stroke mortality in high risk areas, using Generalized Additive Model (GAM) and distributed lag-nonlinear model (DLNM). Then we introduced a classification and regression tree (CART) model to evaluate the threshold of climate and pollution on mortality variation. The association between socio-environmental factors and stroke mortality across counties and districts over different time period were examined by Bayesian Conditional Autoregressive (CAR) Model. This study expects to examine the significant environmental factors associated with mortality of stroke across time and space in China, to help establishing a forecasting and early warning system of CVD adapting to extreme weather and air pollution, and to provide new scientific evidence for control and prevention of stroke in China. Meanwhile, this study will also promote the application of new research method in other disease study.

英文关键词： Climate change;Stroke;Spatiotemporal analysis;Forcasting and early warning