A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States.
A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States.
复制标题
DOI：
10.3390/ijerph192315762
复制
发表时间：
2022-11-26
影响因子：
--
通讯作者：
Krusche, Krupali Uplekar
中科院分区：
文献类型：
--
作者：
Hu, Ming;Zhang, Kai;Nguyen, Quynh Camthi;Tasdizen, Tolga;Krusche, Krupali Uplekar
随着气候变化增加了破坏性和不可预测的极端高温事件的频率和强度，建筑环境的发展应考虑采取措施，尽量减少炎热天气下室内过热的可能性。在世界范围内，包括在发达国家和发展中国家，热浪是导致死亡的主要天气相关原因。本实证研究采用四步法对美国27个州的数据进行收集、提取和分析。从美国住房调查数据库、ResStock数据库和CDC的国家环境公共卫生跟踪网络中提取了三个住房特征类别（即一般住房条件、居住条件和住房热惯性）和八个变量。采用多元回归模型了解影响变量，采用多重共线性检验确定变量之间的相关性，然后采用logistic模型对结果进行验证。住房年龄（HA）、住房拥挤比（HCR）和屋顶状况（RC）三个变量与热相关疾病（HRI）风险指数相关。然后，利用这三个变量建立logistic回归模型，在州层面上预测热相关急诊就诊（EDV）风险和热相关死亡率（MORD）。结果表明，所提出的logistic回归模型对8个州的MORD高风险州的预测准确率为100%。总的来说，这个分析提供了额外的证据，关于住房特征变量影响HRI。研究结果还强化了建筑环境决定健康的概念，并表明在缓解气候变化加剧的健康状况的技术中应考虑建筑环境，特别是住房。
As climate change increases the frequency and intensity of devastating and unpredictable extreme heat events, developments to the built environment should consider instigating practices that minimize the likelihood of indoor overheating during hot weather. Heatwaves are the leading cause of death among weather-related causes worldwide, including in developed and developing countries. In this empirical study, a four-step approach was used to collect, extract and analyze data from twenty-seven states in the United States. Three housing characteristic categories (i.e., general housing conditions, living conditions, and housing thermal inertia) and eight variables were extracted from the American Housing Survey database, ResStock database and CDC’s National Environmental Public Health Tracking Network. Multivariable regression models were used to understand the influential variables, a multicollinearity test was used to determine the dependence of those variables, and then a logistic model was used to verify the results. Three variables—housing age (HA), housing crowding ratio (HCR), and roof condition (RC)—were found to be correlated with the risk of heat-related illness (HRI) indexes. Then, a logistic regression model was generated using the three variables to predict the risk of heat-related emergency department visits (EDV) and heat-related mortality (MORD) on a state level. The results indicate that the proposed logistic regression model correctly predicted 100% of the high-risk states for MORD for the eight states tested. Overall, this analysis provides additional evidence about the housing character variables that influence HRI. The outcomes also reinforce the concept of the built environment determined health and demonstrate that the built environment, especially housing, should be considered in techniques for mitigating climate change-exacerbated health conditions.
登录
查看更多内容
影响因子：
8.3
作者：
Adam-Poupart, Ariane;Smargiassi, Audrey;Labreche, France
通讯作者：
Labreche, France
影响因子：
6.7
作者：
Cheung, CK;Fuller, RJ;Luther, MB
通讯作者：
Luther, MB
影响因子：
4.3
作者：
Hu, Ming;Qiu, Yueming
通讯作者：
Qiu, Yueming
影响因子：
9.8
作者：
Samuelson, Holly;Baniassadi, Amir;Narula, Tushar
通讯作者：
Narula, Tushar
影响因子：
5.9
作者：
Al-Ghamdi, AS
通讯作者：
Al-Ghamdi, AS