Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis
IntroductionDementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activities entails a series of collateral problems, comprising exclusion of patients fr...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Big Data |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2022.1027783/full |
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| author | Loredana Bellantuono Loredana Bellantuono Alfonso Monaco Alfonso Monaco Nicola Amoroso Nicola Amoroso Antonio Lacalamita Ester Pantaleo Ester Pantaleo Sabina Tangaro Sabina Tangaro Roberto Bellotti Roberto Bellotti |
| author_facet | Loredana Bellantuono Loredana Bellantuono Alfonso Monaco Alfonso Monaco Nicola Amoroso Nicola Amoroso Antonio Lacalamita Ester Pantaleo Ester Pantaleo Sabina Tangaro Sabina Tangaro Roberto Bellotti Roberto Bellotti |
| author_sort | Loredana Bellantuono |
| collection | DOAJ |
| description | IntroductionDementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activities entails a series of collateral problems, comprising exclusion of patients from civil rights and welfare, unpaid caregiving work, mostly performed by women, and an additional burden on the public healthcare systems. Thus, gender and wealth inequalities (both among individuals and among countries) tend to amplify the social impact of such a disease. Since at present there is no cure for dementia but only drug treatments to slow down its progress and mitigate the symptoms, it is essential to work on prevention and early diagnosis, identifying the risk factors that increase the probability of its onset. The complex and multifactorial etiology of dementia, resulting from an interplay between genetics and environmental factors, can benefit from a multidisciplinary approach that follows the “One Health” guidelines of the World Health Organization.MethodsIn this work, we apply methods of Artificial Intelligence and complex systems physics to investigate the possibility to predict dementia prevalence throughout world countries from a set of variables concerning individual health, food consumption, substance use and abuse, healthcare system efficiency. The analysis uses publicly available indicator values at a country level, referred to a time window of 26 years.ResultsEmploying methods based on eXplainable Artificial Intelligence (XAI) and complex networks, we identify a group of lifestyle factors, mostly concerning nutrition, that contribute the most to dementia incidence prediction.DiscussionThe proposed approach provides a methodological basis to develop quantitative tools for action patterns against such a disease, which involves issues deeply related with sustainable, such as good health and resposible food consumption. |
| first_indexed | 2024-04-12T03:42:39Z |
| format | Article |
| id | doaj.art-ef30e0c34e944569bd8b05ab7dcc62ec |
| institution | Directory Open Access Journal |
| issn | 2624-909X |
| language | English |
| last_indexed | 2024-04-12T03:42:39Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Big Data |
| spelling | doaj.art-ef30e0c34e944569bd8b05ab7dcc62ec2022-12-22T03:49:15ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2022-12-01510.3389/fdata.2022.10277831027783Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysisLoredana Bellantuono0Loredana Bellantuono1Alfonso Monaco2Alfonso Monaco3Nicola Amoroso4Nicola Amoroso5Antonio Lacalamita6Ester Pantaleo7Ester Pantaleo8Sabina Tangaro9Sabina Tangaro10Roberto Bellotti11Roberto Bellotti12Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Università degli Studi di Bari Aldo Moro, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyDipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyDipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, ItalyDipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyDipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyDipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, ItalyIstituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, ItalyDipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Bari, ItalyIntroductionDementia is an umbrella term indicating a group of diseases that affect the cognitive sphere. Dementia is not a mere individual health issue, since its interference with the ability to carry out daily activities entails a series of collateral problems, comprising exclusion of patients from civil rights and welfare, unpaid caregiving work, mostly performed by women, and an additional burden on the public healthcare systems. Thus, gender and wealth inequalities (both among individuals and among countries) tend to amplify the social impact of such a disease. Since at present there is no cure for dementia but only drug treatments to slow down its progress and mitigate the symptoms, it is essential to work on prevention and early diagnosis, identifying the risk factors that increase the probability of its onset. The complex and multifactorial etiology of dementia, resulting from an interplay between genetics and environmental factors, can benefit from a multidisciplinary approach that follows the “One Health” guidelines of the World Health Organization.MethodsIn this work, we apply methods of Artificial Intelligence and complex systems physics to investigate the possibility to predict dementia prevalence throughout world countries from a set of variables concerning individual health, food consumption, substance use and abuse, healthcare system efficiency. The analysis uses publicly available indicator values at a country level, referred to a time window of 26 years.ResultsEmploying methods based on eXplainable Artificial Intelligence (XAI) and complex networks, we identify a group of lifestyle factors, mostly concerning nutrition, that contribute the most to dementia incidence prediction.DiscussionThe proposed approach provides a methodological basis to develop quantitative tools for action patterns against such a disease, which involves issues deeply related with sustainable, such as good health and resposible food consumption.https://www.frontiersin.org/articles/10.3389/fdata.2022.1027783/fulldementiaeXplainable Artificial Intelligencecomplex systemsOne Healthsustainable development goalsdata science for social good |
| spellingShingle | Loredana Bellantuono Loredana Bellantuono Alfonso Monaco Alfonso Monaco Nicola Amoroso Nicola Amoroso Antonio Lacalamita Ester Pantaleo Ester Pantaleo Sabina Tangaro Sabina Tangaro Roberto Bellotti Roberto Bellotti Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis Frontiers in Big Data dementia eXplainable Artificial Intelligence complex systems One Health sustainable development goals data science for social good |
| title | Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis |
| title_full | Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis |
| title_fullStr | Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis |
| title_full_unstemmed | Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis |
| title_short | Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis |
| title_sort | worldwide impact of lifestyle predictors of dementia prevalence an explainable artificial intelligence analysis |
| topic | dementia eXplainable Artificial Intelligence complex systems One Health sustainable development goals data science for social good |
| url | https://www.frontiersin.org/articles/10.3389/fdata.2022.1027783/full |
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