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Enregistrement W1991036673

[Sociodemographic and environmental factors associated with sports physical activity in the urban population of Peru].

2003· article· en· W1991036673 sur OpenAlexaboutno aff
Juan A. Seclén-Palacín, Enrique R. Jacoby

Notice bibliographique

RevuePubMed · 2003
Typearticle
Langueen
DomaineMedicine
ThématiquePhysical Activity and Health
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeographyDescriptive statisticsPopulationMetropolitan areaSocioeconomicsDemographyQuarter (Canadian coin)Logistic regressionMedicineStatisticsSociology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES: To determine the frequency of sports physical activity in the urban population of Peru and to identify the sociodemographic, economic, and environmental factors associated with that activity. METHODS: This study utilized information collected by the country's National Household Survey (Encuesta Nacional de Hogares) in the second quarter of 1997. That Survey is overseen by Peru's National Institute of Statistics and Informatics (Instituto Nacional de Estadística e Informática). The Survey was based on a probabilistic, multistage sample that was stratified for all the urban areas of the country, which was divided into eight geographic regions: metropolitan Lima, northern coast, central coast, southern coast, northern mountains, central mountains, southern mountains, and jungle. In total, 14 913 homes were visited and 45 319 people at least 15 years of age were interviewed. The frequency of engaging in sports physical activity was classified as daily, every other day, weekly, or occasional. "Regular sports activity" (RSA) was defined as engaging in sports either every day or every other day. The preferences for and obstacles to sports practice were also examined. A descriptive analysis of the levels of RSA was carried out for gender, using the chi-square test. The factors associated with RSA were analyzed through conditional multiple logistic regression and analysis of residuals, multicollinearity, and interactions. The level of significance was set at P < 0.05. RESULTS: Practicing sports at least once a week was more common among men (44.5%) than among women (32.4%), and the same was true for RSA (12.8% versus 10.5%). The age group with the highest level of RSA was 50-55 years for men (20%), and 40-45 years for women (18%). RSA was most common in three geographic regions: jungle (15.3%), central mountains (12.8%), and central coast (12.1%). RSA was least common in two regions: southern mountains (9.7%) and metropolitan Lima (10.6%). The income bracket was not associated with RSA. However, other variables associated indirectly with the socioeconomic level - such as having more formal education, being employed, and having access to the Internet or cable television - and consumption of sports information were significantly and directly associated with RSA. The most frequent barriers to practicing sports were the lack of time, the lack of nearby sports infrastructure (playing fields or courts, etc.), and people's lack of interest. RSA on the part of the members of a household was significantly associated with RSA performed by the head of the household (male or female). CONCLUSIONS: RSA is limited in the urban areas of Peru. This is most true for persons who are less than 30 years old, for women, and for residents of the Lima metropolitan area. This low RSA level is a challenge for public health, and it confirms the need for promoting active lifestyles. More study is needed on the observed positive influence when the head of the household performs RSA and on the fact that RSA is more common in urban areas outside metropolitan Lima. These two findings should also be taken into consideration in designing specific interventions.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,192

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,031
Tête enseignante GPT0,237
Écart entre enseignants0,206 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations59
Publié2003
Routes d'admission1
Résumé présentoui

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