Obesity and Physical Inactivity: The Relevance of Reconsidering the Notion of Sedentariness
Bibliographic record
Abstract
The population statistics of most countries of the world are indicating that industrialization and computerization have been associated with an increase in sedentariness and more recently with a significant shift from healthy weight to overweight. In general, this change in the overweight/obesity prevalence is attributed by health professionals to suboptimal diet and physical activity practices. However, recent data raised the possibility that excess weight gain might also be the outcome of changes imposed by our '24-hour', hectic lifestyle. Parallel to an increase in body weight, one has observed a reduction in sleep time and an increase in knowledge-based work (KBW) that appear as a growing necessity in a context of economic competitiveness and globalization. Sleep and cognitive work both exert a trivial effect on energy expenditure and may thus be considered as sedentary activities. However, their respective effect on energy intake is opposite. Indeed, an increase in the practice of the most sedentary activity, i.e. sleep, is associated with a hormonal profile facilitating appetite control whereas KBW appears as a stimulus favoring a significant enhancing effect on food intake. Television viewing is another example of sedentary activity that has been shown to increase the intake of high-density foods. These observations demonstrate that the modern way of living has favored a change in human activities whose impact goes well beyond what has traditionally been attributed to a lack of physical exercise. Therefore, we will need to reconsider the notion of 'sedentariness' which includes several activities having opposing effects on energy balance.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.047 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".