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| DOI | 10.1016/j.lanepe.2023.100779 |
| The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study | |
| 发表日期 | 2024 |
| ISSN | 2666-7762 |
| 起始页码 | 36 |
| 卷号 | 36 |
| 英文摘要 | Background Daily time -series regression models are commonly used to estimate the lagged nonlinear relation between temperature and mortality. A major impediment to this type of analysis is the restricted access to daily health records. The use of weekly and monthly data represents a possible solution unexplored to date. Methods We temporally aggregated daily temperatures and mortality records from 147 contiguous regions in 16 European countries, representing their entire population of over 400 million people. We estimated temperature -lagmortality relationships by using standard time -series quasi -Poisson regression models applied to daily data, and compared the results with those obtained with different degrees of temporal aggregation. Findings We observed progressively larger differences in the epidemiological estimates with the degree of temporal data aggregation. The daily data model estimated an annual cold and heat -related mortality of 290,104 (213,745-359,636) and 39,434 (30,782-47,084) deaths, respectively, and the weekly model underestimated these numbers by 8.56% and 21.56%. Importantly, differences were systematically smaller during extreme cold and heat periods, such as the summer of 2003, with an underestimation of only 4.62% in the weekly data model. We applied this framework to infer that the heat -related mortality burden during the year 2022 in Europe may have exceeded the 70,000 deaths. Interpretation The present work represents a first reference study validating the use of weekly time series as an approximation to the short-term effects of cold and heat on human mortality. This approach can be adopted to complement access -restricted data networks, and facilitate data access for research, translation and policy -making. |
| 英文关键词 | Temperature; Cold; Heat; Mortality; DLNM; Temporal aggregation; Weekly data; Monthly data; Time series; Climate change |
| 语种 | 英语 |
| WOS研究方向 | Health Care Sciences & Services ; Public, Environmental & Occupational Health |
| WOS类目 | Health Care Sciences & Services ; Public, Environmental & Occupational Health |
| WOS记录号 | WOS:001154198000001 |
| 来源期刊 | LANCET REGIONAL HEALTH-EUROPE
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| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/299436 |
| 作者单位 | ISGlobal; Universitat Politecnica de Catalunya; Barcelona Supercomputer Center (BSC-CNS); Pompeu Fabra University; Institut National de la Sante et de la Recherche Medicale (Inserm); CIBER - Centro de Investigacion Biomedica en Red; CIBERESP; Universite de Montpellier; Institut National de la Sante et de la Recherche Medicale (Inserm); Universite de Montpellier; Universite PSL; Ecole Pratique des Hautes Etudes (EPHE); Universite PSL; University of Geneva; Ruprecht Karls University Heidelberg; ICREA; University of London; London School of Hygiene & Tropical Medicine; University of London; London School of Hygiene & Tropical Medicine; ISGlobal |
| 推荐引用方式 GB/T 7714 | . The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study[J],2024,36. |
| APA | (2024).The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study.LANCET REGIONAL HEALTH-EUROPE,36. |
| MLA | "The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study".LANCET REGIONAL HEALTH-EUROPE 36(2024). |
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