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Record W4388126717 · doi:10.3389/fped.2023.1235143

Salivary uric acid across child development and associations with weight, height, and body mass index

2023· article· en· W4388126717 on OpenAlexfundno aff
Jenna L. Riis, Alexander L. Dent, Olivia Silke, Douglas A. Granger

Bibliographic record

VenueFrontiers in Pediatrics · 2023
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
FundersDuke Clinical Research InstituteEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNYU Grossman School of MedicineUniversity of North Carolina at Chapel HillNational Institutes of HealthJohns Hopkins Bloomberg School of Public HealthYork UniversityJohns Hopkins UniversityNorthwestern University
KeywordsMedicineBody mass indexObesityUric acidCohortSalivaChildhood obesityDemographyCohort studyPediatricsLongitudinal studyPhysiologyInternal medicineOverweight

Abstract

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Introduction Obesity during childhood is a serious and growing chronic disease with consequences for lifelong health. In an effort to advance research into the preclinical indicators of pediatric obesity, we examined longitudinal assessments of uric acid concentrations in saliva among a cohort of healthy children from age 6-months to 12-years ( n 's per assessment range from 294 to 727). Methods Using data from a subsample of participants from the Family Life Project (an Environmental influences on Child Health Outcomes Program cohort), we: (1) characterized salivary uric acid (sUA) concentrations from infancy to early adolescence by sex and race; (2) assessed changes in sUA levels across development; and (3) evaluated associations between sUA concentrations and measures of child weight, height, and body mass index (BMI). Across four assessments conducted at 6-, 24-, 90-, and 154-months of age, 2,000 saliva samples were assayed for UA from 781 participants (217 participants had sUA data at all assessments). Results There were no significant differences in sUA concentrations by sex at any assessment, and differences in sUA concentrations between White and non-White children varied by age. At the 90- and 154-month assessments, sUA concentrations were positively correlated with measures of child weight, height, and BMI (90-month: weight- ρ (610) = 0.13, p < 0.01; height- ρ (607) = 0.10, p < 0.05; BMI- ρ (604) = 0.13, p < 0.01; 154-month: weight- ρ (723) = 0.18, p < 0.0001; height- ρ (721) = 0.10, p < 0.01; BMI- ρ (721) = 0.17, p < 0.0001). Group based trajectory modeling identified two groups of children in our sample with distinct patterns of sUA developmental change. The majority (72%) of participants showed no significant changes in sUA across time (“Stable” group), while 28% showed increases in sUA across childhood with steep increases from the 90- to 154-month assessments (“Increasing” group). Children in the Increasing group exhibited higher sUA concentrations at all assessments (6-month: t (215) = −5.71, p < 0.001; 24-month: t (215) = −2.89, p < 0.01; 90-month: t (215) = −3.89, p < 0.001; 154-month: t (215) = −19.28, p < 0.001) and higher weight at the 24- and 90-month assessments (24-month: t (214) = −2.37, p < 0.05; 90-month: t (214) = −2.73, p < 0.01). Discussion Our findings support the potential utility of sUA as a novel, minimally-invasive biomarker that may help advance understanding of the mechanisms underlying obesity as well as further surveillance and monitoring efforts for pediatric obesity on a large-scale.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes1
Has abstractyes

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