Identifying metabolic parameters related to severity and extent of periodontitis in down syndrome patients

J Periodontal Res. 2022 Aug;57(4):904-913. doi: 10.1111/jre.13028. Epub 2022 Jun 22.

Abstract

Background and objective: Systemic metabolic status and periodontitis can be related in patients with Down syndrome (DS). The objective of this study was to identify metabolic indicators (anthropometric measurements, blood pressure, and serum markers) related to severity and extent of periodontitis in DS patients.

Methods: A cross-sectional study was conducted with 49 patients with DS. Periodontal evaluation included the periodontal probing depth (PPD), clinical attachment level (CAL), gingival bleeding index (GBI), and visible plaque index (VPI). Periodontitis severity was classified by the stages system. The extent of periodontitis was assessed as the percentage of sites with CAL ≥3 mm, CAL ≥4 mm, PPD ≥4 mm, and PPD ≥5 mm. The metabolic condition of the participants was determined by analyzing anthropometric parameters, blood pressure, and serum markers. Data were analyzed using the Mann-Whitney test, Spearman's correlation coefficient, and multivariate regression analysis.

Results: Periodontitis stage 3/4 was detected in 32.7% of patients, with high values of VPI (54.6 ± 35.8) and GBI (42.4 ± 33.3). The severity of periodontitis was related to higher mean corpuscular hemoglobin (β = .291, p = .028) and mean corpuscular volume values (β = .293, p = .046). Arm circumference measurements were inversely related to CAL ≥3 mm (β = -.408, p = .023), PPD ≥4 mm (β = -.475, p = .006), and PPD ≥5 mm (β = -.443, p = .010).

Conclusions: The findings suggest that the severity and extent of periodontitis may be related to some metabolic parameters in DS patients.

Keywords: Down syndrome; biological markers; metabolic syndrome; periodontal diseases.

MeSH terms

  • Biomarkers
  • Cross-Sectional Studies
  • Down Syndrome* / complications
  • Humans
  • Periodontal Index
  • Periodontitis* / complications

Substances

  • Biomarkers