摘要
孕期空气污染暴露对子代健康的影响备受关注,精细可行的暴露评估对明确暴露-反应关系、减少研究间的异质性尤为重要.时间调整土地利用回归（LUR）模型是近年发展的具有高时空分辨率优势的暴露评估方法.国外采用此模型探讨孕期室外空气污染健康效应的研究日益增多,而我国处于LUR模型的构建阶段,相关的流行病学研究鲜见报道.本文综述了空气污染与不良妊娠结局关联研究的Meta分析进展和异质性来源,介绍了时间调整LUR模型的构建方法和特点,系统总结了现有基于此模型的孕期空气污染暴露评估案例,并对我国LUR模型的研发应用提出展望,为在大规模空气污染健康效应研究中实施更精准、高效的孕期暴露评估提供参考.
The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression （LUR） models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.
作者
张钰娟
薛凤霞
白志鹏
Zhang Yujuan Xue Fengxia Bai Zhipeng(Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin 300211, China)
出处
《中华预防医学杂志》
CAS
CSCD
北大核心
2017年第3期265-276,共12页
Chinese Journal of Preventive Medicine
基金
国家重点基础研究发展计划（2011CB503801）
关键词
空气污染
母亲暴露
妊娠结局
异质性
土地利用回归模型
Air pollution
Maternal exposure
Pregnancy outcome
Heterogeneity
Land use regression models
