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Record W4387246290 · doi:10.1186/s44167-023-00029-1

Optimal domain-specific physical activity and sedentary behaviors for blood lipids among Japanese children: a compositional data analysis

2023· article· en· W4387246290 on OpenAlexaff
Tetsuhiro Kidokoro, Naruki Kitano, Natsuko Imai, Justin J. Lang, Grant R. Tomkinson, Costan G. Magnussen

Bibliographic record

VenueJournal of Activity Sedentary and Sleep Behaviors · 2023
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsChildren's Hospital of Eastern OntarioPublic Health Agency of CanadaUniversity of Ottawa
Fundersnot available
KeywordsLipid profileBody mass indexPhysical activityBlood lipidsConfidence intervalMedicineCholesterolInternal medicineEndocrinologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Optimizing childhood domain-specific physical activity (PA) and sedentary behavior (SB) for blood lipid profile is not well understood. We aimed to (1) determine the associations between accelerometer-measured PA and SB for each domain (school time and out-of-school time) with blood lipid profile and (2) estimate predicted changes in blood lipid profile with hypothetical time-reallocation between domain-specific SB and PA among Japanese children using compositional data analysis (CoDA). METHODS: This cross-sectional study included 284 children (147 boys and 137 girls) aged 9-12 years (mean age [years]: 10.1 ± 1.2 for boys, 10.0 ± 1.1 for girls; mean body mass index: 18.2 ± 3.2 for boys, 17.5 ± 2.5 for girls). Time spent in domain-specific SB, light-intensity PA (LPA), moderate-intensity PA (MPA), and vigorous-intensity PA (VPA) was assessed using accelerometry. The non-fasting lipid profile considered measures of triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and non-HDL-C levels. CoDA and isotemporal substitution model were performed to examine the associations of domain-specific PA and SB with blood lipids. RESULTS: = 0.09, 95% CI = 0.02 to 0.16) after adjusting for age, body mass index, and time spent in SB, LPA, and MPA. During the out-of-school period, a replacement of 1 min of any other behavior with VPA was associated with decreases in LDL-C in boys (predicted changes [95% CI] - 0.03 mmol/L [- 0.05 to - 0.00] for LPA), non-HDL-C in boys (predicted changes [95% CI] - 0.03 mmol/L [- 0.06 to - 0.01] for SB and LPA) and TG in boys (predicted changes [95% CI] - 0.04 mmol/L [- 0.06 to - 0.02] for SB and LPA, - 0.05 mmol/L [- 0.07 to - 0.02] for MPA) and in girls (predicted changes [95% CI] - 0.02 mmol/L [- 0.04 to - 0.00] for LPA), and increases in HDL-C in girls (predicted changes [95% CI] 0.02 mmol/L [0.00 to 0.04] for SB and LPA, 0.03 mmol/L [0.00 to 0.05] for MPA). CONCLUSIONS: Increasing out-of-school VPA might be an effective approach to improve blood lipid profiles among Japanese children.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.299
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2023
Admission routes1
Has abstractyes

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