Evidence map›Paper›PMID 40599686›Full record

ArticleFrontiers in oral health2025

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

Amr Sayed Ghanem, Róbert Bata, Nóra Kovács, Attila Csaba Nagy

Abstract read
In one paragraph

Article in Frontiers in oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Amr Sayed GhanemDepartment of Health Informatics, Faculty of Health Sciences, University of Debrecen, Debrecen, Hungary.
Róbert BataDepartment of Health Informatics, Faculty of Health Sciences, University of Debrecen, Debrecen, Hungary.
Nóra KovácsDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Attila Csaba NagyDepartment of Health Informatics, Faculty of Health Sciences, University of Debrecen, Debrecen, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( 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.

Indexed as

disease burdenglobal burden of diseaseinequalitiesjoinpoint regressionoral cavityperiodontal diseaseperiodontitissociodemographic

Identifiers

PMID40599686
PMCPMC12209297

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.