Recent studies attempting to develop forecasting models for new migraine attack onsets, overviewing triggers and protectors, are encouraging but necessitate further improvements to produce forecasting models with high predictive accuracy. This updated review of available data holds the potential to enhance the precision of predicting a migraine attack. This study aims to evaluate how lifestyle factors affect migraine frequency in adults with episodic migraine, to contribute to the development of an effective migraine forecasting model. A comprehensive search of databases, including PubMed, ScienceDirect, Google Scholar, and Scopus, was conducted considering studies published from 2018 to December 2023, following the PRISMA guidelines. Critical evaluation was conducted using the Joanna Briggs Institute's appraisal tools. The lifestyle modifications examined in this review included dietary habits, physical activity, sleep, and stress management. Of the 36 studies analysed, which predominantly exhibited low to moderate bias, 18 investigated dietary habits, 7 explored physical activity, 11 assessed stress management, and 5 investigated sleep patterns. The evidence from these 36 studies advocates for the implementation of lifestyle modifications in migraine management. Furthermore, these outcomes carry valuable implications from the standpoint of migraine forecasting models. The most consistent results were observed in relation to specific diets, dietary supplements, and physical activity. Although trends were noted in stress management and sleep, further research is required to elucidate their influence on migraine frequency and their integration into a migraine forecasting model. This study is registered on PROSPERO (ID CRD42024511300).
Quartetti, U., Brighina, F., Gambino, G., Frinchi, M., Bellafiore, M., Tabacchi, G., et al. (2025). Forecasting migraine attacks by managing daily lifestyle: a systematic review as a basis to develop predictive algorithms [10.1097/pr9.0000000000001247].
Forecasting migraine attacks by managing daily lifestyle: a systematic review as a basis to develop predictive algorithms
Quartetti, UmbertoPrimo
;Brighina, FilippoSecondo
;Gambino, Giuditta
;Frinchi, Monica;Bellafiore, Marianna;Tabacchi, Garden;Vasto, Sonya;Accardi, Giulia;Amato, Antonella;Giardina, Marta;Mazzucco, Walter;Giglia, GiuseppeCo-ultimo
;Di Liberto, ValentinaCo-ultimo
2025-04-05
Abstract
Recent studies attempting to develop forecasting models for new migraine attack onsets, overviewing triggers and protectors, are encouraging but necessitate further improvements to produce forecasting models with high predictive accuracy. This updated review of available data holds the potential to enhance the precision of predicting a migraine attack. This study aims to evaluate how lifestyle factors affect migraine frequency in adults with episodic migraine, to contribute to the development of an effective migraine forecasting model. A comprehensive search of databases, including PubMed, ScienceDirect, Google Scholar, and Scopus, was conducted considering studies published from 2018 to December 2023, following the PRISMA guidelines. Critical evaluation was conducted using the Joanna Briggs Institute's appraisal tools. The lifestyle modifications examined in this review included dietary habits, physical activity, sleep, and stress management. Of the 36 studies analysed, which predominantly exhibited low to moderate bias, 18 investigated dietary habits, 7 explored physical activity, 11 assessed stress management, and 5 investigated sleep patterns. The evidence from these 36 studies advocates for the implementation of lifestyle modifications in migraine management. Furthermore, these outcomes carry valuable implications from the standpoint of migraine forecasting models. The most consistent results were observed in relation to specific diets, dietary supplements, and physical activity. Although trends were noted in stress management and sleep, further research is required to elucidate their influence on migraine frequency and their integration into a migraine forecasting model. This study is registered on PROSPERO (ID CRD42024511300).File | Dimensione | Formato | |
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