Sedentary Duration and Systemic Health Burden: Nonlinear Associations with Muscle, Fat, and Vascular Phenotypes in a US Population-Based Study
Bibliographic record
Abstract
Background: Sedentary behavior (SB) is a growing public health concern associated with cardiometabolic risk; yet few studies have assessed integrated physiological responses across the muscle–fat–vascular system. Methods: This retrospective cross-sectional analysis used data from 13,637 participants (≥12 years) in the 2011–2018 National Health and Nutrition Examination Survey (NHANES). Sedentary duration (SD) was self-reported via a validated questionnaire. Outcomes included the sarcopenic index (SI), fat distribution index (FDI), and pulse pressure index (PPI). Associations were examined using multivariable linear regression and restricted cubic spline models, adjusting for sociodemographic and lifestyle factors. Subgroup analyses explored effect modification by body mass index (BMI), sex, race/ethnicity, education, and self-rated health. Results: Each additional hour/day of SD was associated with a lower SI (β = −0.004, 95% CI: −0.005 to −0.002), lower FDI (β = −0.009, 95% CI: −0.012 to −0.007), and higher PPI (β = 0.001, 95% CI: 0.000 to 0.002). The SD–SI association was nonlinear, with a threshold at 10.73 h/day: below this point, the SI declined sharply (β = −0.001, p < 0.001), while above it the slope plateaued or reversed. The FDI showed consistent adverse associations across the SD range, particularly in men and individuals with lower education. The PPI was significantly elevated with SD only among non-Hispanic Black participants. Conclusions: SD is differentially associated with muscle mass, fat distribution, and vascular function, with overlapping inflection points indicating a coordinated multisystem response to sedentary stress. These findings support targeting <10.7 h/day sedentary time as a potential intervention threshold.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".