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However, of that excess only 23% has been directly attributed to extreme heat. The problem with this figure is that the estimate is based on models that could present biases and limitations. We proposed to estimate the excess mortality attributable to extreme temperatures in Catalonia during the summer of 2022, and assessing how the risk of death from these extreme heat temperatures may be modified by other factors, particularly socioeconomic variables. We employed a longitudinal ecological design covering the period from 2015 to 2022, using data at the health area level. We used generalized linear mixed models for all ages and for those aged 65 and older. These models corrected for biases by using small-scale geographic units and explicitly took spatial variability into account. According to our results, during the summer months of 2022, 49.41% of excess mortality was attributable to extreme heat. Not only did heatwaves increase the risk of death, but so too did maximum temperature extremes. Effect modifiers found to increase the risk of dying on days with extreme heat were namely: being 65\u00a0years or older, high relative humidity, extreme minimum temperature, and low income. Our results suggest the following methodological considerations: (i) minimize the effects of exposure misclassification by using smaller geographic units than those typically used in other studies; (ii) explicitly take spatial variability into account by using, for example, a hierarchical Bayesian spatiotemporal models; and (iii) control for spatial and temporal dependencies.<\/jats:p>","DOI":"10.1007\/s10109-025-00475-2","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T06:55:20Z","timestamp":1758524120000},"page":"123-149","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Assessing excess mortality and heat-attributable risk during the summer of 2022 in Catalonia, Spain: a Bayesian spatiotemporal analysis"],"prefix":"10.1007","volume":"28","author":[{"given":"MariaA.","family":"Barcel\u00f3","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1882-0157","authenticated-orcid":false,"given":"Marc","family":"Saez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,22]]},"reference":[{"key":"475_CR1","unstructured":"Agencia Espa\u00f1ola de Meteorolog\u00eda (AEMET). 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All authors will disclose any actual or potential conflict of interest including any financial, personal, or other relationships with other people or organizations that could inappropriately influence or be perceived to influence their work, within three years of beginning the submitted work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}},{"value":"During the writing of the article, the authors have not used any type of AI or AI-assisted technologies.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Generative AI and AI-assisted technologies in the writing process"}},{"value":"All methods were carried out in accordance with relevant guidelines and regulations. Regarding mortality data, data usage from the Information System for Research in Primary Care (SIDIAP) is authorized by the Catalan Health Institute (ICS) and the Data Analysis Program for Health Research and Innovation (PADRIS). These public organizations ensure the protection of individuals\u2019 privacy through pseudo-anonymization of the data. For linking with other public data sources, ICS or PADRIS serves as Trusted Third Parties (TTPs) to perform the linkage process and provide the newly pseudo-anonymized dataset. In cases where access to personal data requires patient consent, the same TTPs are involved. SIDIAP does not provide re-identifiable information, implementing measures such as aggregations and deletions to maintain pseudo-anonymization. All data management adheres to legal requirements, including the General Data Protection Regulation (EU) 2016\/679 and Organic Law 3\/2018, of 5 December, which safeguards personal data and digital rights. Secure servers were used for data storage, ensuring compliance with these regulations. As patient data extracted from the database were irreversibly pseudonymized, written informed consent was not required.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}