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Record W4306764874 · doi:10.3390/nu14204362

Association between Four Dietary Patterns and the Risk of Periodontal Diseases: A Systematic Review and Meta-Analysis

2022· review· en· W4306764874 on OpenAlexaboutno aff
Jae-Hun Jeong, Hyung‐Sik Kim, Dongjun Lee, Kihun Kim, Yun Hak Kim

Bibliographic record

VenueNutrients · 2022
Typereview
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
FundersNational Research Foundation of KoreaMedical Research Center, Hamad Medical Corporation
KeywordsMeta-analysisMedicineAssociation (psychology)Periodontal diseaseSystematic reviewPeriodontitisMEDLINEDentistryInternal medicineBiologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Several dietary patterns are reported as risk factors for several chronic diseases including oral diseases. However, thus far, there has been no comprehensive quantitative analysis of nutrition and periodontal diseases. METHODS: This systematic review was conducted according to the PRISMA guidelines. Cohort, case-control, and cross-sectional studies were eligible for inclusion in this study. The Newcastle-Ottawa scale was used to qualitatively assess the risk of bias in the included studies. The number of samples was used for odds ratio calculation, followed by the unadjusted value and 95% confidence interval. RESULTS: Nine papers were included for the systematic review and meta-analysis. The results of screening for database search records showed that four diet patterns (western diet, dairy product intake, sugar intake, and vitamin C intake) have enough data for meta-analysis. The risk of periodontal disease in the western-diet group and the lowest dairy product intake group was 1.05 (0.51-2.13) and 1.28 (0.89-1.84), respectively. The risk of periodontal disease in the highest sugar intake group and the lowest vitamin C intake group was 1.52 (0.79-2.91) and 1.15 (1.08-1.23), respectively. CONCLUSIONS: With aging of the population globally, the prevalence of periodontal disease increases, and the associated cost also increases. Though this study, we found foods related to the risk of periodontal disease, and we are confident that it will contribute to lowering the incidence of the disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.652
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.354
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2022
Admission routes1
Has abstractyes

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