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.

本研究旨在通过一种新的基于人工智能的网络分析来识别牙周炎患者的系统性多发病群，并探索相关因素的影响。本研究利用了 3,736 名参与者的横断面数据，这些参与者跨越了 3 个周期的全国健康和营养检查调查（2009 年至 2014 年）。牙周检查由训练有素的牙医为年龄≥30 岁的参与者进行。牙周炎的程度由临床附着损失 (CAL) ≥ 3 mm 的部位比例表示，分为 4 个相等的四分位数。还提取了调查期间报告的一系列全身性疾病。应用具有特征向量中心性的超图网络分析来识别总体人群中的系统性多病群和单一疾病影响，并在按 CAL 四分位数分层时。CAL 四分位数还探讨了可能影响系统性多发病群的个体因素。在研究人群中，前 3 位流行的疾病是高血压（63.9%）、关节炎（47.6%）和肥胖（45.9%）。在研究人群中确定了总共 106 个独特的系统性多发病群。高血压是总体人群中最集中的疾病（中心性 [C]：0.50），紧随其后的是关节炎（C：0.45）和肥胖（C：0.42）。糖尿病在最高 CAL 四分位数 (C: 0.31) 中的中心性高于最低 (C: 0.26)。“高血压，肥胖”是 CAL 四分位数中最大的加权多病群。这项研究揭示了牙周炎患者中一系列常见的全身性多发病群。牙周炎患者更容易同时出现高血压和肥胖症，而糖尿病对重度牙周炎患者的多发病群影响更大。种族、剥夺和吸烟状况等因素也可能影响多发病群的模式。