Secular trends in acute myocardial infarction in relation to physical activity in the general Danish population
Notice bibliographique
Résumé
Secular trends in AMI rates were analyzed in relation to physical activity levels. The population attributable risk of physical inactivity was calculated. Participants were randomly selected subjects from a suburb of Copenhagen, Denmark, screened during the years 1964-1991. Occupational physical activity and in leisure time were assessed 1964, 1974, 1976, 1982, 1987 and 1991 by self-administered questionnaire along with smoking habits and alcohol consumption. Blood pressure, weight, height and serum lipids were measured according to WHO-standards. Mortality data were obtained from death certificates, from hospital records or autopsies. Acute myocardial infarctions (AMI) 1964-1994 were included. 13.925 men and women aged 30, 40, 50 and 60 years, were drawn as random samples from a background population of 300.000 inhabitants. A cohort born in 1914 was examined in 1964 and 1974, a cohort born in 1936, was examined in 1976 and 1987; Monica (Monitoring trends and determinants in cardiovascular diseases) I cohort were examined in 1982 and 1987; MONICA II in 1986, and MONICA III in 1991. Mean physical activity level at leisure adjusted for age and sex increased over time (P < 0001). 25% of the men were sedentary, and more women reported a sedentary lifestyle than men. The overall trend was from 1964 to 1992 a decline in physical activity at work (P < 0001) in both gender and all age groups. The difference in AMI incidence rates between leisure time physical activity (LTPA) levels increased over time. No change was found in AMI rates comparing sedentary in different time periods. A remarkable decrease over time in the AMI incidence rate was found in physically active during leisure time. Population attributable risk (PAR) exceeded 40% in both genders in the late 1980s. In conclusion the difference in AMI rates between LTPA subgroups has increased over time. The low AMI rates observed among the most physically active reveal a substantial potential for the prevention of AMI through physical activity. A population attributable risk of more than 40% for physical inactivity suggests a potential for primary prevention through increased physical activity.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».