Doctoral Dissertation Research: Climate-Health Vulnerability: Identifying Climate Thresholds for Heat-Related Illness

高温是美国与天气有关的死亡的主要原因。气候变化的大气环流模型预测热浪的严重程度、持续时间和强度会增加，使未来人口面临更大的与热有关的疾病和死亡风险。该项目的重点是确定与热有关的疾病的地方到区域尺度模式以及控制这些模式的温度阈值。温度阈值表示气候值（例如，温度、热指数和湿度），超过这些温度，与热有关的疾病急诊入院率显著增加。识别温度阈值允许启动早期热预警系统或应急响应计划。与热有关的疾病可以很容易地通过补水或搬迁到较凉爽的环境来预防;因此，干预措施是减少与热有关的疾病的关键组成部分。这项研究还将确定高风险人群经历了不成比例的热相关疾病急诊室入院。以前的研究调查了城市中与热有关的死亡率和发病率。然而，它相对忽视了美国农村地区热量对健康的不利影响。本研究确定了城市和农村地区的高危人群和危险因素（包括那些有危险的农业和农场工人），本研究的目的是了解与热有关的疾病的时空模式，以及它们如何对应于温度阈值的空间模式。这项研究采用多学科方法来了解影响热相关疾病模式的气候，环境和人口因素。它借鉴了脆弱性理论的人类-生态学方法，地理学的空间统计和气候学的气候阈值识别，以确定气候影响与热有关的疾病的位置和因素。在方法学中明确整合可用的细粒度发病率数据、人口普查和天气数据，将是对气候-公共卫生研究的一个新贡献，并提供有关影响高发病率的环境和社会经济因素的新发现。一个广泛的阵列的时空关系被确定为不同的时间段，年龄，性别和空间位置。这些关系是通过地理信息系统（GIS）框架，一个自动化的免费软件（Python）程序，以确定温度阈值，和几个回归技术，包括地理加权回归，空间回归和多级建模。虽然设置在北卡罗来纳州，并集中在与热有关的疾病，在这项研究中使用的方法也将适用于其他气候相关的疾病（例如水传播或呼吸道疾病），也可以作为一个模型，以评估气候健康的脆弱性在其他地理位置。除了学术传播外，研究结果还将分发给北卡罗来纳州公共卫生部、卡罗莱纳州综合科学评估部、国家气象局、北卡罗来纳州农场工人部委员会和北卡罗莱纳州农场工人研究所。

Heat is the leading cause of weather-related death in the United States. General circulation models of climate change project heat waves to increase in severity, duration, and intensity, placing future populations at greater risk for both heat-related illnesses and deaths. This project focuses on identifying the local to regional scale patterns of heat-related illness and the temperature thresholds that control these patterns. Temperature thresholds represent climate values (e.g., temperature, heat index, and humidity) beyond which heat-related illness emergency department admissions increase significantly. Identifying a temperature threshold allows for the activation of an early heat warning system or emergency response plan. Heat-related illness can be easily preventable through hydration or relocation to a cooler environment; therefore, interventions are a key component in reducing heat-related illness. This study will also identify high-risk populations that experience a disproportionate number of heat-related illness emergency department admissions. Previous research has investigated heat-related mortality and morbidity in urban cities. However, it has relatively neglected adverse health effects of heat in rural US locations. This study identifies high-risk populations and risk factors in both urban and rural locations (including those with at-risk agricultural and farm workers).This objective of this study is to understand the spatiotemporal patterns of heat-related illness and how they correspond to the spatial patterns of temperature thresholds. This research employs a multidisciplinary approach to understanding the climatic, environmental, and population factors that affect patterns of heat-related illness. It draws from the human - ecological approach of vulnerability theory, spatial statistics from geography, and climate threshold identification from climatology to determine the locations and factors by which climate impacts heat-related illness. The explicit spatiotemporal integration of available fine-grained morbidity data, census, and weather data in the methodology will be a novel contribution to climate-public health research and provide new findings about the environmental and socioeconomic factors that influence high rates of heat-related illness. A wide array of spatiotemporal relationships is identified for different time periods, ages, genders, and spatial locations. These relationships are established through a geographic information system (GIS) framework, an automated freeware (python) program to identify temperature thresholds, and several regression techniques, including as geographically weighted regression, spatial regression, and multi-level modelling. Though set in North Carolina and centered on heat-related illness, the methodology utilized in this study will also be applicable to other climate-related diseases (e.g. waterborne or respiratory diseases) and can also be used as a model to assess climate-health vulnerability in other geographic locations. In addition to academic dissemination, the results will be distributed to the NC Division of Public Health, Carolina's Integrated Science Assessments, the National Weather Service, NC Farmworker Ministry Committee and the North Carolina Farmworker Institute.