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编制开放访问时间序列数据集,用于研究温度与死亡率的关联
Aurelio Tobias1,2, Chris Fook Sheng Ng3, Yoonhee Kim4
1Institute of Environmental Assessment and Water Research (IDAEA), Spanish Research Council (CSIC), Barcelona, Spain.
Data in brief
|July 29, 2024
概括
这项研究汇编了关于温度和死亡率的每日时间序列数据集. 这些资源有助于研究人员利用回归和元分析分析不同地理位置的温度死亡率关系.
科学领域:
- 环境流行病学环境流行病学
- 生物统计学 生物统计学
- 公共卫生 公共卫生
背景情况:
- 温度与死亡率的关联是公共卫生研究的一个关键领域.
- 访问标准化,地理上多样化的数据集对于强大的分析至关重要.
- 之前的研究经常使用局部数据,限制了更广泛的结论.
研究的目的:
- 为温度死亡率研究编译和呈现开放访问的每日时间序列数据集.
- 为各种地理尺度提供适合时间序列回归分析的数据.
- 为了促进温度与死亡率相关的地理差异的探索.
主要方法:
- 编制现有的每日时间序列数据集,以计算死亡率和平均环境温度.
- 包括来自多个地理聚合 (城市,地区,县) 的数据.
- 数据集准备用于时间序列回归和元分析.
主要成果:
- 现在可以获得一个全面的开放访问的每日时间序列数据集合.
- 这些数据集涵盖了各种地理位置,使得特定位置的分析成为可能.
- 这些数据支持个人位置分析和聚合元分析.
结论:
- 这个数据集汇编为研究人员,教育工作者和学生提供了宝贵的资源.
- 它有助于应用时间序列回归建模来研究温度与死亡率的关系.
- 该资源支持环境流行病学和公共卫生方面的培训和研究.
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