ArticleMedicine2026
Cross-sectional analysis of periodontitis and peripheral artery disease association: Results from National Health and Nutrition Examination Survey 1999 to 2004.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Utilizing 1999 to 2004 National Health and Nutrition Examination Survey (NHANES) datasets, this cross-sectional analysis evaluates the relationship of periodontitis with peripheral arterial disease (PAD) among adults in the United States. Our investigation employed NHANES 1999 to 2004 datasets to quantify the periodontitis-PAD association. Clinical classifications applied Center for Disease Control and the American Academy of Periodontics (CDC/AAP) diagnostic thresholds. An ankle-brachial index below 0.9 in any leg defined PAD. Multivariable logistic regression quantified this relationship, complemented with stratified subgroup assessments for robustness verification. Within the cohort of 4133 individuals (mean ± standard deviation age: 56.8 ± 12.1 years; female proportion: 46.8%), periodontal disease affected 16.7% (n = 690). PAD prevalence reached 4.4% (n = 182). Comparative analysis revealed elevated PAD frequency in periodontitis subjects versus non-periodontitis controls (8.1% [56/690] vs 3.7% [126/3443]). Following comprehensive covariate adjustment, periodontitis maintained independent association with PAD (OR = 1.49; 95% CI:1.04-2.13; P-value = .03). Stratified analyses indicated absence of significant interaction effects (all interaction P-values > .05). Analysis of this nationally representative American population reveals periodontitis as an independent predictor of heightened PAD probability. Prospective investigations remain imperative to determine causality.
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