A step-defined sedentary lifestyle index: <5000 steps/day
Bibliographic record
Abstract
Step counting (using pedometers or accelerometers) is widely accepted by researchers, practitioners, and the general public. Given the mounting evidence of the link between low steps/day and time spent in sedentary behaviours, how few steps/day some populations actually perform, and the growing interest in the potentially deleterious effects of excessive sedentary behaviours on health, an emerging question is "How many steps/day are too few?" This review examines the utility, appropriateness, and limitations of using a reoccurring candidate for a step-defined sedentary lifestyle index: <5000 steps/day. Adults taking <5000 steps/day are more likely to have a lower household income and be female, older, of African-American vs. European-American heritage, a current vs. never smoker, and (or) living with chronic disease and (or) disability. Little is known about how contextual factors (e.g., built environment) foster such low levels of step-defined physical activity. Unfavorable indicators of body composition and cardiometabolic risk have been consistently associated with taking <5000 steps/day. The acute transition (3-14 days) of healthy active young people from higher (>10 000) to lower (<5000 or as low as 1500) daily step counts induces reduced insulin sensitivity and glycemic control, increased adiposity, and other negative changes in health parameters. Although few alternative values have been considered, the continued use of <5000 steps/day as a step-defined sedentary lifestyle index for adults is appropriate for researchers and practitioners and for communicating with the general public. There is little evidence to advocate any specific value indicative of a step-defined sedentary lifestyle index in children and adolescents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".