{"id":335,"date":"2026-06-08T10:16:18","date_gmt":"2026-06-08T08:16:18","guid":{"rendered":"https:\/\/ideas.stat.unipd.it\/?page_id=335"},"modified":"2026-07-20T11:44:30","modified_gmt":"2026-07-20T09:44:30","slug":"multimorbidity","status":"publish","type":"page","link":"https:\/\/ideas.stat.unipd.it\/index.php\/publications\/multimorbidity\/","title":{"rendered":"Multimorbidity"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"335\" class=\"elementor elementor-335\">\n\t\t\t\t<div class=\"elementor-element elementor-element-889528c e-flex e-con-boxed e-con e-parent\" data-id=\"889528c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-56daa1e elementor-widget elementor-widget-html\" data-id=\"56daa1e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t\t<style>\r\npa {\r\n    font-size: 18px;\r\n        text-align: justify;\r\n}\r\n\r\n@media (min-width: 1025px) {\r\n  .mio-spazio {\r\n    height: 40px;\r\n  }\r\n}\r\n\r\n<\/style>\r\n\r\n<section class=\"Research lines\">\r\n    \r\n    <div class=\"mio-spazio\"><\/div>\r\n    \r\n    \r\n    <h1>Publications on Multimorbidity<\/h1>\r\n\r\n\r\n<\/section>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb5e91b elementor-widget elementor-widget-html\" data-id=\"cb5e91b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t\t<style>\r\n\r\n.publication-list{\r\n    max-width:950px;\r\n    margin:40px auto;\r\n    font-family:Arial,sans-serif;\r\n}\r\n\r\n.publication{\r\n    border:1px solid #d9d9d9;\r\n    border-radius:10px;\r\n    margin-bottom:25px;\r\n    background:#fff;\r\n    overflow:hidden;\r\n    box-shadow:0 2px 8px rgba(0,0,0,.05);\r\n}\r\n\r\n.publication summary{\r\n    list-style:none;\r\n    cursor:pointer;\r\n    padding:22px 25px 0;\r\n}\r\n\r\n.publication summary::-webkit-details-marker{\r\n    display:none;\r\n}\r\n\r\n.pub-title{\r\n    font-size:22px;\r\n    font-weight:700;\r\n    margin-bottom:10px;\r\n    color:#222;\r\n}\r\n\r\n.pub-authors{\r\n    font-size:17px;\r\n    color:#555;\r\n    margin-bottom:10px;\r\n}\r\n\r\n.pub-journal{\r\n    font-size:15px;\r\n    color:#777;\r\n    margin-bottom:18px;\r\n}\r\n\r\n.pub-toolbar{\r\n    display:flex;\r\n    justify-content:space-between;\r\n    align-items:center;\r\n    flex-wrap:wrap;\r\n    border-top:1px solid #ececec;\r\n    margin-left:-25px;\r\n    margin-right:-25px;\r\n    padding:14px 25px;\r\n}\r\n\r\n.pub-links{\r\n    display:flex;\r\n    gap:18px;\r\n    flex-wrap:wrap;\r\n}\r\n\r\n.pub-links a{\r\n    text-decoration:none;\r\n    color:#444;\r\n    font-size:15px;\r\n}\r\n\r\n.pub-type{\r\n    font-size:13px;\r\n    font-weight:600;\r\n    color:#666;\r\n    text-transform:uppercase;\r\n    letter-spacing:.6px;\r\n    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justify-content:space-between;\r\n}\r\n\r\n}\r\n\r\n<\/style>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n<div class=\"publication-list\">\r\n\r\n<details class=\"publication\">\r\n\r\n<summary>\r\n\r\n<div class=\"pub-type\">\r\nScientific article\r\n<\/div>\r\n\r\n<div class=\"pub-title\">\r\nUnderstanding multimorbidity: insights with graphical models\r\n<\/div>\r\n\r\n<div class=\"pub-authors\">\r\nErika Banzato, Alberto Roverato, Alessandra Buja, Giovanna Boccuzzo\r\n<\/div>\r\n\r\n<div class=\"pub-journal\">\r\nBMC Medical Research Methodology \u2022 2025 \u2022 Vol. 25, Article 84\r\n<\/div>\r\n\r\n<div class=\"pub-toolbar\">\r\n\r\n<div class=\"pub-links\">\r\n\r\n<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0277953626002303\" target=\"_blank\">\r\n\ud83d\udd17 URL\r\n<\/a>\r\n\r\n<a href=\"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12874-025-02536-y.pdf\" target=\"_blank\">\r\n\ud83d\udcdd PDF\r\n<\/a>\r\n\r\n<a href=\"https:\/\/scholar.google.com\/scholar?hl=it&as_sdt=0%2C5&q=Understanding+multimorbidity%3A+insights+with+graphical+models&btnG=\" target=\"_blank\">\r\n\ud83c\udf93 Scholar\r\n<\/a>\r\n\r\n<a  >\r\n\ud83d\udcc4 DOI: 10.1186\/s12874-025-02536-y\r\n<\/a>\r\n\r\n\r\n\r\n<\/div>\r\n\r\n<div class=\"right-tools\">\r\n\r\n<button class=\"bibtex-btn\" onclick=\"copyBibtex(event,'bib22')\">\r\n    \ud83d\udccb <span>Copy BibTeX<\/span>\r\n<\/button>\r\n\r\n<div class=\"arrow\">\r\n\u25bc\r\n<\/div>\r\n\r\n<\/div>\r\n\r\n<\/div>\r\n\r\n<\/summary>\r\n\r\n<div class=\"abstract\">\r\n\r\n<h4>Abstract<\/h4>\r\n\r\n<p>\r\n\r\nBackground: The use of graphical models in the multimorbidity context is increasing in popularity due to their intuitive visualization of the results. A comprehensive understanding of the model itself is essential for its effective utilization and optimal application. This article is a practical guide on the use of graphical models to better understand multimorbidity. It provides a tutorial with a focus on the interpretation of the model structure and of the parameter values. In this study, we analyze data related to a cohort of 214,401 individuals, who were assisted by the Local Health Unit of the province of Padova (north-eastern Italy), collecting information from hospital discharge forms.\r\n<br>\r\nMethods: We explain some fundamental concepts, with special attention to the difference between marginal and conditional associations. We emphasize the importance of considering multimorbidity as a network, where the variables involved are part of an interconnected system of interactions, to correct for spurious effects in the analysis. We show how to analyze the network structure learned from the data by introducing and explaining some centrality measures. Finally, we compare the model obtained by adjusting for population characteristics with the results of a stratified analysis.\r\n<br>\r\nResults: Using examples from the estimated model, we demonstrate the key differences between marginal and conditional associations. Specifically, we show that, marginally, all variables appear associated, while this is not the case when considering conditional associations, where many variables appear to be conditionally independent given the others. We present the results from the analysis of centrality indices, revealing that cardiovascular diseases occupy a central position in the network, unlike more peripheral conditions such as sensory organ diseases. Finally, we illustrate the differences between networks estimated in subpopulations, highlighting how disease associations vary across different groups.\r\n<br>\r\nConclusion: Graphical models are a versatile tool for analyzing multimorbidity, offering insights into disease associations while controlling for the effects of other variables. This paper provides an overview of graphical models without focusing on detailed methodology, highlighting their utility in understanding network structures and potential subgroup differences, such as gender-related variations in multimorbidity patterns.\r\n\r\n<\/p>\r\n\r\n<\/div>\r\n\r\n<pre id=\"bib22\" style=\"display:none;\">\r\n@article{banzato2025understanding,\r\n  title={Understanding multimorbidity: insights with graphical models},\r\n  author={Banzato, Erika and Roverato, Alberto and Buja, Alessandra and Boccuzzo, Giovanna},\r\n  journal={BMC Medical Research Methodology},\r\n  volume={25},\r\n  number={1},\r\n  pages={84},\r\n  year={2025},\r\n  publisher={Springer}\r\n}\r\n<\/pre>\r\n\r\n<\/details>\r\n\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Publications on Multimorbidity Scientific article Understanding multimorbidity: insights with graphical models Erika Banzato, Alberto Roverato, Alessandra Buja, Giovanna Boccuzzo BMC Medical Research Methodology \u2022 2025<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":53,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-335","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/pages\/335","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/comments?post=335"}],"version-history":[{"count":8,"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/pages\/335\/revisions"}],"predecessor-version":[{"id":1397,"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/pages\/335\/revisions\/1397"}],"up":[{"embeddable":true,"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/pages\/53"}],"wp:attachment":[{"href":"https:\/\/ideas.stat.unipd.it\/index.php\/wp-json\/wp\/v2\/media?parent=335"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}