Publicação
TEMPERATURE-MORTALITY ASSOCIATION: PORTUGUESE EXTREME WEATHER EVENT EARLY WARNING SYSTEM
| Resumo: | Portugal is one of the European countries with a higher excess of mortality during winter, even though winters are considered relatively mild. There is also an excess of mortality during the summer. This excess mortality is associated with a larger vulnerability of the Portuguese population to non-optimal temperature exposure caused by poor housing conditions, with deficient insulation and weak energy efficiency, and an ageing population. More likely heat waves and cold spells due to climate change could result in excess deaths. Both extremely hot and cold temperatures are considered to have a significant effect on the population’s health. Public health institutions play a crucial role in assessing the impacts of such events and, subsequently, in providing adequate early warnings and suitable mitigation recommendations. The work presented here was developed within the scope of the Research and Development Project RELIABLE - Building occupant risk warning panel during extreme weather events. An update of the heat and cold health early warning systems is proposed for use in Mainland Portugal. The aim was to develop a risk indicator, active throughout the whole year, and easily understood by the entire population, with the highest possible spatial resolution. Daily data of all-cause mortality and maximum, minimum and mean temperatures was gathered from public data sources for the 1995-2020 time period. Districtspecific temperature-mortality associations were estimated using different quasi-Poisson regressions. Linear threshold Distributed Lag Models (DLM) were proposed and estimated for cold and warm semesters, where minimum temperatures were considered in autumn/winter and maximum temperatures in spring/summer, to identify worst case exposure scenarios. Additionally, Distributed Non-linear Lag Models (DLNM) were also estimated using mean temperatures as the exposure. A temperature variability term was introduced to the models to evaluate its significance. Regressions included adjustment for seasonality and long-term trends and yearly population estimates as an offset. Influenza incidence was also included in the models to improve predictive performance. Model specification was selected per district independently based on goodness-of-fit criteria. Models proposed here could serve as updates for heat and cold health early warning systems, as they provide the results to maintain a risk indicator, active throughout the whole year, and easily understood by the entire population, with the highest possible spatial resolution for the data available for Mainland Portugal. Differences between the optimum district-specific models completely justify the need for region-specific warnings.Optimum cold thresholds were found to be relatively mild temperatures when compared to optimum heat thresholds, suggesting the effects of cold temperatures on mortality start at fairly milder temperatures. Minimum mortality temperatures (MMTs) varied somewhat between districts, with the highest MMTs being recorded in the Alentejo region and the lowest in the Vila Real district. Evidence supporting the acclimatisation of the population to their own specific climates hypothesis was found. Temperature variability terms were found to be significant only in a few districts. |
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| Autores principais: | Brito, André Martins |
| Assunto: | Time series regression Temperature Mortality Heatwaves Coldwaves Prevention plans |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Portugal is one of the European countries with a higher excess of mortality during winter, even though winters are considered relatively mild. There is also an excess of mortality during the summer. This excess mortality is associated with a larger vulnerability of the Portuguese population to non-optimal temperature exposure caused by poor housing conditions, with deficient insulation and weak energy efficiency, and an ageing population. More likely heat waves and cold spells due to climate change could result in excess deaths. Both extremely hot and cold temperatures are considered to have a significant effect on the population’s health. Public health institutions play a crucial role in assessing the impacts of such events and, subsequently, in providing adequate early warnings and suitable mitigation recommendations. The work presented here was developed within the scope of the Research and Development Project RELIABLE - Building occupant risk warning panel during extreme weather events. An update of the heat and cold health early warning systems is proposed for use in Mainland Portugal. The aim was to develop a risk indicator, active throughout the whole year, and easily understood by the entire population, with the highest possible spatial resolution. Daily data of all-cause mortality and maximum, minimum and mean temperatures was gathered from public data sources for the 1995-2020 time period. Districtspecific temperature-mortality associations were estimated using different quasi-Poisson regressions. Linear threshold Distributed Lag Models (DLM) were proposed and estimated for cold and warm semesters, where minimum temperatures were considered in autumn/winter and maximum temperatures in spring/summer, to identify worst case exposure scenarios. Additionally, Distributed Non-linear Lag Models (DLNM) were also estimated using mean temperatures as the exposure. A temperature variability term was introduced to the models to evaluate its significance. Regressions included adjustment for seasonality and long-term trends and yearly population estimates as an offset. Influenza incidence was also included in the models to improve predictive performance. Model specification was selected per district independently based on goodness-of-fit criteria. Models proposed here could serve as updates for heat and cold health early warning systems, as they provide the results to maintain a risk indicator, active throughout the whole year, and easily understood by the entire population, with the highest possible spatial resolution for the data available for Mainland Portugal. Differences between the optimum district-specific models completely justify the need for region-specific warnings.Optimum cold thresholds were found to be relatively mild temperatures when compared to optimum heat thresholds, suggesting the effects of cold temperatures on mortality start at fairly milder temperatures. Minimum mortality temperatures (MMTs) varied somewhat between districts, with the highest MMTs being recorded in the Alentejo region and the lowest in the Vila Real district. Evidence supporting the acclimatisation of the population to their own specific climates hypothesis was found. Temperature variability terms were found to be significant only in a few districts. |
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