The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study.
Lancet Reg Health Eur
; 36: 100779, 2024 Jan.
Article
em En
| MEDLINE
| ID: mdl-38188278
ABSTRACT
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-lag-mortality 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.Funding:
The study was supported by the ERC Consolidator Grant EARLY-ADAPT (https//www.early-adapt.eu/), and the ERC Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Lancet Reg Health Eur
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Espanha
País de publicação:
Reino Unido