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Development of a health data-driven model for a thermal comfort study

机译：用于热舒适性研究的健康数据驱动模型的开发

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The objective of this study is to develop a thermal comfort model by incorporating public health datasets and influencing parameters associated with both health and thermal comfort. There are three systematic influencing parameters identified in this study: socioeconomic development, population density, and annual mean temperature. The thermal comfort neutral temperatures predicted with the new model are in good agreement with the measured field data, and the correlation coefficient is 0.91.The current study introduces large-scale spatial data and longitudinal health-temperature data from the public health field for contributing to thermal comfort research. For instance, the required numbers of intensive field experiments and modeling works regarding thermal comfort can be reduced. Moreover, studies on the impacts of certain factors (such as variations in time, gender, and age) on thermal comfort have not reached any conclusive results, mainly owing to a lack of large demographic datasets. Recent findings from the public health field indicate that there are observable variations in health-temperature data in response to climate changes. There are no significant health-temperature differences between genders, although females are more inclined to use resources for better environmental management. Other factors are also discussed in this study, such as age and the prevalence of air conditioners.
机译：本研究的目的是通过纳入公共卫生数据集和影响与健康和热舒适相关的参数来开发热舒适模型。本研究中确定了三个系统的影响参数：社会经济发展，人口密度和年平均温度。用新模型预测的热舒适性中性温度与测量的现场数据吻合良好，相关系数为0.91.目前的研究引入了来自公共卫生领域的大规模空间数据和纵向健康温度数据，以促进贡献热舒适性研究。例如，可以减少关于热舒适性的强化场实验和建模工作的所需数量。此外，关于某些因素的影响（例如时间，性别和年龄的变化）对热舒适性的影响尚未达到任何确凿的结果，主要是由于缺乏大型人口数据集。公共卫生领域最近的发现表明，响应气候变化，健康温度数据有可观察到的变化。由于女性更倾向于利用资源以实现更好的环境管理，因此不会有明显的健康温度差异。该研究还讨论了其他因素，例如空调的年龄和患病率。

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