MétaCan
Menu
Back to cohort
Record W4381800129 · doi:10.1038/s41390-023-02700-4

Social epidemiology of Fitbit daily steps in early adolescence

2023· article· en· W4381800129 on OpenAlexaff
Jason M. Nagata, Sana Alsamman, Natalia Smith, Jiayue Yu, Kyle T. Ganson, Erin E. Dooley, David Wing, Fiona C. Baker, Kelley Pettee Gabriel

Bibliographic record

VenuePediatric Research · 2023
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Toronto
FundersNational Institute on Drug Abuse
KeywordsSexual orientationEthnic groupDemographyMarital statusHousehold incomeCohortGerontologyEpidemiologyPsychologyMedicinePopulationGeographySocial psychology

Abstract

fetched live from OpenAlex

Abstract Background Sociodemographic disparities in adolescent physical activity have been documented but mostly rely on self-reported data. Our objective was to examine differences in device-based step metrics, including daily step count (steps d −1 ), by sociodemographic factors among a diverse sample of 10-to-14-year-old adolescents in the US. Methods We analyzed prospective cohort data from Year 2 (2018–2020) of the Adolescent Brain Cognitive Development (ABCD) Study ( N = 6460). Mixed-effects models were conducted to estimate associations of sociodemographic factors (sex, sexual orientation, race/ethnicity, household income, parental education, and parental marital status) with repeated measures of steps d −1 over the course of 21 days. Results Participants (49.6% female, 39.0% racial/ethnic minority) accumulated an average of 9095.8 steps d −1 . In mixed-effects models, 1543.6 more steps d −1 were recorded for male versus female sex, Black versus White race (328.8 more steps d −1 ), heterosexual versus sexual minority sexual orientation (676.4 more steps d −1 ), >$200,000 versus <$25,000 household income (1003.3 more steps d −1 ), and having married/partnered parents versus unmarried/unpartnered parents (326.3 more steps d −1 ). We found effect modification by household income for Black adolescents and by sex for Asian adolescents. Conclusions Given sociodemographic differences in adolescent steps d −1 , physical activity guidelines should focus on key populations and adopt strategies optimized for adolescents from diverse backgrounds. Impact Sociodemographic disparities in physical activity have been documented but mostly rely on self-reported data, which can be limited by reporting and prevarication bias. In this demographically diverse sample of 10–14-year-old early adolescents in the U.S., we found notable and nuanced sociodemographic disparities in Fitbit steps per day. More daily steps were recorded for male versus female sex, Black versus White race, heterosexual versus sexual minority, >$100,000 versus <$25,000 household income, and having married/partnered versus unmarried/unpartnered parents. We found effect modification by household income for Black adolescents and by sex for Asian adolescents.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.172
GPT teacher head0.452
Teacher spread0.280 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePediatric ResearchSame topicObesity, Physical Activity, DietFrench-language works237,207