Evidence map›Paper›PMID 42116335›Full record

ArticleMedicine2026

Analysis of oral microbiome characteristics and their correlation with oral health diseases.

Yujie Nie, Xiaohui Lin

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Yujie NieGuangdong Provincial People's Hospital's Nanhai Hospital, Foshan, Guangdong, China.ORCID 0009-0001-8779-6835
Xiaohui Lin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate the relationship between oral microbiome characteristics and oral health status, examining microbial diversity and the prevalence of specific bacterial genera. We conducted a cross-sectional study of 154 patients who underwent oral examinations at our hospital from January 2023 to December 2023. Based on routine oral examinations and medical history inquiries, patients were divided into oral health group (n = 71) and oral health disease group (n = 83). Oral samples were collected and analyzed using next-generation sequencing and bioinformatics to assess microbial diversity and abundance. Key demographic and behavioral factors were recorded, and statistical analyses determined oral microbiome characteristics with oral health. The oral health disease group had significantly higher average age, smoking rates, body mass index, alcohol use, family history of oral diseases, and worse oral health indicators (e.g., plaque, gum inflammation, calculus, periodontal status, decayed/missing teeth, and decayed, missing, and filled teeth scores). They also showed lower microbial diversity (Shannon, Chao1, and evenness indices) and reduced levels of protective bacteria (Streptococcus and Actinomyces). In contrast, the oral health group had higher flossing rates, more caries-free individuals, and greater microbial diversity. The Shannon, Chao1, and evenness indices were inversely linked to oral disease, while the Simpson Index (measuring dominance) was positively correlated. Protective bacteria were negatively linked to disease, whereas harmful bacteria (Fusobacterium and Prevotella) were positively correlated. Our findings highlight decreased microbial diversity as a significant factor in oral diseases, suggesting that maintaining a diverse oral microbiome was crucial for oral health.

Indexed as

MicrobiotaMouthMouth DiseasesOral HealthAdultBacteriaCross-Sectional StudiesDental CariesFemaleHumansMaleMiddle Ageddental carieslifestyle factorsmicrobial diversityoral healthoral microbiomeperiodontitis

Identifiers

PMID42116335
PMCPMC13166765

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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.