National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341;
National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341.
Proc Natl Acad Sci U S A. 2019 Mar 19;116(12):5420-5427. doi: 10.1073/pnas.1806393116. Epub 2019 Mar 4.
Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat-health early warning systems. We used a two-stage analysis to estimate heat-health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003-2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat-health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure-response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat-health early warning systems.
热预警系统和行动计划使用温度阈值来触发预警和风险沟通。在这项研究中，我们进行多状态分析，探索热与全因和特定病因住院之间的关联，为热健康预警系统的设计和开发提供信息。我们使用两阶段分析来估计 2003-2012 年美国 1617 个县的热指数与住院之间的热健康风险关系。第一阶段涉及县级时间序列拟泊松回归，使用分布式滞后非线性模型来估计热健康关联。第二阶段涉及多变量随机效应荟萃分析，以在更大的地理尺度（如州或气候区）上汇总县级暴露-反应关联。利用两阶段分析的结果，我们确定了与显著热归因负担相对应的热指数范围。然后，我们将这些范围与同期使用的美国国家海洋和大气管理局（NOAA）国家气象局（NWS）热警报标准进行了比较。热指数与特定病因住院之间的关联因地理位置和健康结果而异。热归因负担开始于中度热的热指数值，在某些地区，这一值低于研究期间 NWS 使用的警报范围。局部特定的健康证据可以有益地为热警报标准提供信息和校准。健康发现与传统天气预报工作的同步对于开发有效的热健康预警系统至关重要。
