Social epidemiology of Fitbit daily steps in early adolescence
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".