Systemic Multimorbidity Clusters in People with Periodontitis

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.

Additive Effect of Periodontal Disease and Obesity on COVID-19 Outcomes

This study aims to examine the impact of periodontal disease in obesity on COVID-19 infection and associated outcomes. This retrospective longitudinal study included 58,897 UK Biobank participants tested for COVID-19 between March 2020 and February 2021. Self-reported oral health indicators (bleeding gums, painful gums, and loose teeth) were used as surrogates for periodontal disease. Body fat levels were quantified by body mass index (BMI) and categorized as normal weight (18.5 to 24.9 kg/m²), overweight (25 to 29.9 kg/m²), and obese (≥30 kg/m²). Multivariable logistic regression and Cox proportional hazard models were used to quantify risk of COVID-19 infection, hospital admission, and mortality, adjusted for participants’ demographics and covariates. Of 58,897 participants, 14,466 (24.6%) tested positive for COVID-19 infection. COVID-19 infection was higher for participants who were overweight (odds ratio, 1.18; 95% CI, 1.12 to 1.24) and obese (odds ratio, 1.33; 95% CI, 1.26 to 1.41) as compared with those of normal weight, but infection was not affected by periodontal disease. The hospital admission rate was 57% higher (hazard ratio, 1.57; 95% CI, 1.25 to 1.97) in the obese group with periodontal disease than without periodontal disease, and admission rates increased with BMI category (normal weight, 4.4%; overweight, 6.8%; obese, 10.1%). Mortality rates also increased with BMI category (normal weight, 1.9%; overweight, 3.17%; obese, 4.5%). In addition, for participants with obesity, the mortality rate was much higher (hazard ratio, 3.11; 95% CI, 1.91 to 5.06) in participants with periodontal disease than those without. Obesity is associated with higher hospitalization and mortality rates, and periodontal disease may exacerbate this impact. The results could inform health providers, policy makers, and the general public of the importance to maintain good oral health through seamless provision of dental services and public oral health prevention initiatives.