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. 2024 Feb 27;14:4752. doi: 10.1038/s41598-024-54900-5

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Clusters of predicted risk, with age fixed, unadjusted (A), adjusted for alcohol (B), body mass index (C) and multivariable adjusted at follow-up 1 (2009–2012). Getis-Ord Gi* statistic for the individuals geo-referenced at their postal address. White dots correspond to individual with values that do not exhibit spatial dependence. Red/Blue dots indicate individuals with a positive/negative Z score considering a p value < 0.05 (α = 0.05). This means that high or low values clusters, respectively, within a spatial lag of 600 m, are found closer together than expected if the underlying spatial process was random. The multivariable model (MGWR) included body mass index, alcohol consumption, living in couple, low education status, Townsend index, Swiss origin, anxiety disorder and major depressive disorder, a polygenic risk score and at follow-up 1 (2009–2012) a Mediterranean diet score, and daily moderate intensity physical activity.