Sociodemographic inequalities in the global burden trends and machine learning-based projections of periodontitis from 1990 to 2030 across different development levels.

Introduction: Oral diseases affect billions globally, with periodontitis contributing to significant health disparities and systemic conditions like diabetes and cardiovascular diseases.

Methods: This study utilized the GBD 2021 dataset to assess the global burden of periodontitis across 204 countries, analyzing prevalence, incidence, and DALY rates. Socioeconomic disparities were examined using the Sociodemographic Index (SDI) and Gini coefficient, while time-series analysis, regression models, and Joinpoint regression identified trends. Machine learning predicted future burden, and geospatial mapping visualized global distribution.

Results: Periodontitis burden remains highest in low-SDI regions, with significantly greater prevalence, incidence, and DALY rates compared to higher-SDI countries (p < 0.001). Global trends showed a decline until 2010 (AAPC: ASPR -0.792%, ASIR -0.719%, DALY -0.794%; all p < 0.05), followed by a temporary increase before stabilizing. Disparities widened over time, peaking around 2010. Projections suggest persistent inequalities, with low-SDI regions maintaining the highest burden and minimal expected reductions, while higher-SDI countries exhibit stable, lower rates.

Conclusion: Despite global declines, periodontitis disparities have widened, with low-SDI regions facing the highest burden and minimal improvements. Without strong public health policies integrating preventive oral health into diseases management, inequalities will persist, worsening systemic health outcomes. Urgent action is needed to ensure universal access to periodontal care and early interventions, especially in low-resource settings.