Association of daily sitting time and leisure-time physical activity with body fat among U.S. adults
Bibliographic record
Abstract
BACKGROUND: Prolonged sitting and reduced physical activity lead to low energy expenditures. However, little is known about the joint impact of daily sitting time and physical activity on body fat distribution. We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults. METHODS: This was a cross-sectional analysis of U.S. nationally representative data from the National Health and Nutrition Examination Survey 2011-2018 among adults aged 20 years or older. Daily sitting time and leisure-time physical activity (LTPA) were self-reported using the Global Physical Activity Questionnaire. Body fat (total and trunk fat percentage) was determined via dual X-ray absorptiometry. RESULTS: Among 10,808 adults, about 54.6% spent 6 h/day or more sitting; more than one-half reported no LTPA (inactive) or less than 150 min/week LTPA (insufficiently active) with only 43.3% reported 150 min/week or more LTPA (active) in the past week. After fully adjusting for sociodemographic data, lifestyle behaviors, and chronic conditions, prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes. When stratifying by LTPA, the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insufficiently active. In the joint analyses, inactive/insufficiently active adults who reported sitting more than 8 h/day had the highest total (female: 3.99% (95% confidence interval (95%CI): 3.09%-4.88%); male: 3.79% (95%CI: 2.75%-4.82%)) and trunk body fat percentages (female: 4.21% (95%CI: 3.09%-5.32%); male: 4.07% (95%CI: 2.95%-5.19%)) when compared with those who were active and sitting less than 4 h/day. CONCLUSION: Prolonged daily sitting time was associated with increased body fat among U.S. adults. The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 source (direct Gemma or distilled Codex), 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".