Recommendations for physical activity within the general population: is this all what we need to keep us healthy?
Notice bibliographique
Résumé
In the natural habitat of our ancestors, physical activity was not a preventive intervention but a matter of survival. From our genetic pool genes were selected which were very effective in regulating food intake and utilization.1,2 This was a clear survival advantage in periods of food deprivation, because they could rely on larger previously generated energy stores. Unfortunately, our selected gene pool has not changed dramatically since then, but we are no longer faced with long periods of food deprivation, and we are no longer forced to run several miles to chase our food. In addition to this ‘old’ genotype, physical inactivity is one important risk factor for the development of several diseases. Several landmark studies around 1990 clearly documented that physical inactivity is a modifiable risk factor for cardiovascular disease and several other chronic diseases, including diabetes mellitus, cancer, obesity, hypertension, bone and joint diseases, and depression.3–5 Immediately it became evident that increasing physical activity and exercise would be a powerful tool to reduce the overall incidence of cardiovascular and even all-cause mortality. Over the years many studies in more than 100,000 individuals have clearly documented that the higher the level of physical fitness, the less likely an individual will suffer premature cardiovascular death. The importance of fitness for the risk of overall death becomes very clear in one of the landmark studies of Jonathan Myers and colleagues in 2002.6 In this trial the authors studied a total of 6213 consecutive men referred for treadmill exercise testing. Among these individuals 3679 individuals had an abnormal exercise test result or a history of cardiovascular events. The rest were classified as healthy. Comparing the relative risk of a healthy but unfit individual with a fit subject but having signs for cardiovascular disease, the risk to die from any cause was much higher for the unfit healthy individual. This clearly shows that being unfit is even worse than being overweight, having diabetes or other risk factors for premature death. Therefore, improving fitness warrants at least as much attention as other risk factors, such as body mass index (BMI), smoking, diabetes or hypertension. Moreover, improving physical activity reduces these common risk factors and therefore may potentiate its beneficial effects.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,012 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,021 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».