Larvin, H orcid.org/0000-0001-7263-4182, Kang, J orcid.org/0000-0002-2770-1099, Aggarwal, VR orcid.org/0000-0003-0838-9682 et al. (2 more authors) (2022) Systemic multimorbidity clusters in people with periodontitis. Journal of Dental Research, 101 (11). pp. 1335-1342. ISSN 0022-0345
Abstract
This study aimed to identify systemic multimorbidity clusters in people with periodontitis via a novel artificial intelligence–based network analysis and to explore the effect of associated factors. This study utilized cross-sectional data of 3,736 participants across 3 cycles of the National Health and Nutrition Examination Survey (2009 to 2014). Periodontal examination was carried out by trained dentists for participants aged ≥30 y. The extent of periodontitis was represented by the proportion of sites with clinical attachment loss (CAL)≥ 3 mm, split into 4 equal quartiles. A range of systemic diseases reported during the survey were also extracted. Hypergraph network analysis with eigenvector centralities was applied to identify systemic multimorbidity clusters and single-disease influence in the overall population and when stratified by CAL quartile. Individual factors that could affect the systemic multimorbidity clusters were also explored by CAL quartile. In the study population, the top 3 prevalent diseases were hypertension (63.9%), arthritis (47.6%), and obesity (45.9%). A total of 106 unique systemic multimorbidity clusters were identified across the study population. Hypertension was the most centralized disease in the overall population (centrality [C]: 0.50), followed closely by arthritis (C: 0.45) and obesity (C: 0.42). Diabetes had higher centrality in the highest CAL quartile (C: 0.31) than the lowest (C: 0.26). “Hypertension, obesity” was the largest weighted multimorbidity cluster across CAL quartiles. This study has revealed a range of common systemic multimorbidity clusters in people with periodontitis. People with periodontitis are more likely to present with hypertension and obesity together, and diabetes is more influential to multimorbidity clusters in people with severe periodontitis. Factors such as ethnicity, deprivation, and smoking status may also influence the pattern of multimorbidity clusters.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © International Association for Dental Research and American Association for Dental, Oral, and Craniofacial Research 2022. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | oral health; periodontal diseases; big data; epidemiological factors; hypergraph; network analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Dentistry (Leeds) > Applied Health and Clinical Translation (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Dentistry (Leeds) > Oral Biology (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Dentistry (Leeds) > Oral Surgery (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Apr 2022 12:32 |
Last Modified: | 29 Mar 2023 13:46 |
Status: | Published |
Publisher: | SAGE |
Identification Number: | 10.1177/00220345221098910 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185867 |
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Filename: Systemic Multimorbidity Clusters in People with Periodontitis.pdf
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