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- W3092617526 abstract "Abstract Background Heat waves (HW) will tend to have a higher impact on mortality due to climate change. The aim of this study was to develop a tailored model to predict local mortality associated to HW. Methods In this ecological study, daily temperature and daily mortality were collected from May to October of 1980 to 2017 in Coimbra, Portugal. Two definitions of HW were used: more than two consecutive days of maximum temperature (MaxT) or minimum temperature (MinT) above percentile 95 for the periods in question. Attributable general mortalities with 13 and 30 lag days were calculated and then converted to attributable general mortality rates adjusted to the resident population. Bivariate and multivariate analyses with SPSS statistics were performed with the following independent variables for each HW: MaxT, diurnal temperature variation (DTV), mean of the mean daily temperatures, month, ageing index (AI), ordinal number of the HW for that year (ONHW), duration, overlapping of another HW and existence of a public health contingency plan. Results The multivariate analyses returned a R2=0,19 for the MaxT model (MaxTM) for both 13 and 30 lag days and a R2=0,51 for the MinT model (MinTM) with 13 lag days and R2=0,45 for 30 lag days. DTV was the only variable with statistical significance in the MaxTM (p < 0,023; β = 0,44 for 13 lag days and p < 0,024; β = 0,43 for 30 lag days). In the MinTM model two variables had statistical significance: AI (p < 0,008; β = 1,72 for 13 lag days and p < 0,037; β = 0,44 for 30 lag days) and ONHW (p < 0,038; β= -0,44 for 30 lag days). Conclusions MaxTM and MinTM had different predictability potentials with different statistical significant independent variables. This may mean HW defined by MaxT have impact in a distinct way from HW defined by MinT. Further development of these models that include acclimatization indexes and causes of mortality may help local public health services to create more efficient, selective contingency plans. Key messages Minimum and maximum temperature defined heat waves may impact mortality differently. Local heat wave/mortality models may contribute to more efficient, selective contingency plans than regional models." @default.
- W3092617526 created "2020-10-15" @default.
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- W3092617526 date "2020-09-01" @default.
- W3092617526 modified "2023-09-23" @default.
- W3092617526 title "Heat waves and mortality: developing a local prediction model based on two kinds of heat waves" @default.
- W3092617526 doi "https://doi.org/10.1093/eurpub/ckaa166.091" @default.
- W3092617526 hasPublicationYear "2020" @default.
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