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Record W7028341676

Fat and bone metabolism in relation to gingival inflammation in children

2014· dissertation· en· W7028341676 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicCentral European and Russian historical studies
Canadian institutionsnot available
Fundersnot available
KeywordsOsteocalcinCohortBone remodelingLean body massConfoundingBone mineralObesityCohort studyEpidemiology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Epidemiological evidence suggests an association between diseases related to fat and bone metabolism and periodontal health. Despite the extensive evidence showing these associations in adults, only a few studies have been conducted in children. We address a gap in the pediatric literature by examining the extent to which markers of gingival inflammation are associated with i) metabolic syndrome (MetS) and: ii) plasma uncarboxylated osteocalcin (unOC). As a preliminary step, we first explore the extent to which whole-body bone measurements were associated with fat mass after taking into account the effect of lean mass. Methodology: The data used in this project derives from the QUALITY cohort, an ongoing longitudinal study investigating the natural history of obesity in children of Quebec, Canada. The QUALITY cohort includes 630 Caucasian children aged 8-10 years at cohort inception, with at least one obese biological parent. Participants were systematically recruited through schools located within 75 km of Montreal and Quebec City. In this thesis, we present cross-sectional analyses from the baseline visit using multiple linear regression analyses with adjustment for potential confounding variables. Whole-body bone mineral content (BMC, g), bone area (cm2), bone mineral density (BMD, g/cm2), lean mass (kg) and fat mass (kg) were measured by dual-energy X-ray absorptiometry (DXA). MetS was defined according to the International Diabetes Federation recommendations. Plasma unOC levels were determined by enzyme-linked immunosorbent assay. Gingival inflammation was defined by the level of gingival crevicular fluid (GCF) tumour necrosis factor alpha (TNF-α) and the extent of gingival bleeding. Results: Positive associations between fat mass and whole-body DXA bone measurements, including BMC, bone area and BMD, were observed after taking into account the effect of lean mass. Specifically, a 1-kg increase in fat was associated with 9.32 g (95% confidence interval [CI]: 7.26, 11.39), 8.02 cm2 (95%CI: 6.72, 9.32) and 0.002 g/cm2 (95%CI: 0.000, 0.002), increase in whole-body BMC, bone area and BMD respectively. Boys with MetS compared to those without, had a 49.5% (95%CI: 25.72, 73.22) higher GCF TNF-α level and 13.7% (95%CI: 1.1, 26.2) more sites with gingival bleeding. Moreover, for 3 of the 5 components of MetS – waist circumference, fasting plasma triglycerides and systolic blood pressure – an increase was associated with increased GCF TNF-α level in boys. No such findings were seen in girls. A 1-ng/ml increase in plasma unOC was associated with 0.96% decrease (95% CI: -1.69, -0.23) in GCF TNF-α level. Conclusion: Our results provide novel findings showing a clustering of metabolic abnormalities, low plasma unOC and high gingival inflammation among 8-10 Caucasian children. Moreover, they suggest that fat and bone metabolism may be associated with periodontal health as early as in childhood. Documenting the association of conditions related to fat and bone metabolism with periodontal health in children may have public health implications. This may allow identification of individuals at risk of developing several related conditions long before they develop clinically and implementation of early preventive measures.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2014
Admission routes1
Has abstractyes

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