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Record W2995705303 · doi:10.2196/14841

Step-Based Metrics and Overall Physical Activity in Children With Overweight or Obesity: Cross-Sectional Study

2019· article· en· W2995705303 on OpenAlexvenueno aff
Jairo H. Migueles, Cristina Cadenas‐Sánchez, Elroy J. Aguiar, Pablo Molina‐García, Patricio Solis‐Urra, José Mora-González, Eduardo García-Mármol, Eric J. Shiroma, Idoia Labayen, Palma Chillón, Marie Löf, Catrine Tudor‐Locke, Francisco B. Ortega

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersNational Institute on AgingEuropean Regional Development FundJunta de AndalucíaMinisterio de Economía y CompetitividadUniversidad de GranadaInstituto de Salud Carlos IIIEuropean Commission
KeywordsCadenceOverweightMedicinePsychological interventionObesityChildhood obesityPhysical therapyCross-sectional studyPublic healthDemographyPhysical activityGerontologyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: Best-practice early interventions to increase physical activity (PA) in children with overweight and obesity should be both feasible and evidence based. Walking is a basic human movement pattern that is practical, cost-effective, and does not require complex movement skills. However, there is still a need to investigate how much walking-as a proportion of total PA level-is performed by children who are overweight and obese in order to determine its utility as a public health strategy. OBJECTIVE: This study aimed to (1) investigate the proportion of overall PA indicators that are explained by step-based metrics and (2) study step accumulation patterns relative to achievement of public health recommendations in children who are overweight and obese. METHODS: A total of 105 overweight and obese children (mean 10.1 years of age [SD 1.1]; 43 girls) wore hip-worn accelerometers for 7 days. PA volumes were derived using the daily average of counts per 15 seconds, categorized using standard cut points for light-moderate-vigorous PA (LMVPA) and moderate-to-vigorous PA (MVPA). Derived step-based metrics included volume (steps/day), time in cadence bands, and peak 1-minute, 30-minute, and 60-minute cadences. RESULTS: Steps per day explained 66%, 40%, and 74% of variance for counts per 15 seconds, LMVPA, and MVPA, respectively. The variance explained was increased up to 80%, 92%, and 77% by including specific cadence bands and peak cadences. Children meeting the World Health Organization recommendation of 60 minutes per day of MVPA spent less time at zero cadence and more time in cadence bands representing sporadic movement to brisk walking (ie, 20-119 steps/min) than their less-active peers. CONCLUSIONS: Step-based metrics, including steps per day and various cadence-based metrics, seem to capture a large proportion of PA for children who are overweight and obese. Given the availability of pedometers, step-based metrics could be useful in discriminating between those children who do or do not achieve MVPA recommendations. TRIAL REGISTRATION: ClinicalTrials.gov NCT02295072; https://clinicaltrials.gov/ct2/show/NCT02295072.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.366
Teacher spread0.331 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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