Determinants of Subjective Health, Happiness, and Life Satisfaction among Young Adults (18‐24 Years) in Guyana
Notice bibliographique
Résumé
. Persistent urban-rural disparity in subjective health and quality of life is a growing concern for healthcare systems across the world. In general, urban population performs better on most health indicators compared with their rural counterparts. However, research evidence on the urban-rural disparity on perceived health, happiness, and quality of life among the young adult population is scarce in South American countries like Guyana. Therefore, in the present study we aimed to investigate whether subjective health, happiness, and quality of life differ according to place of residence among the young adult population in Guyana. METHODS: Cross-sectional data on 2,434 men and women aging between 15 and 24 years were collected from the most recent Guyana Multiple Indicator Cluster Survey conducted in 2014. Outcome variables were perceived: satisfaction about health, life, and happiness, as well as life satisfaction before and after one year from the time of the survey. The urban-rural disparity in reporting satisfaction for these indicators was assessed by multivariate regression methods and by adjusting for relevant sociodemographic factors. RESULTS: More than four-fifth of the respondents reported satisfaction with health (82.4%) and life (81.4%) and 77.9% reported being happy. A vast majority expressed improvement in life situation compared with a year ago (81.4%), and nearly all of the participants (95.4%) expect to have better life situation a year later. Multivariate analysis revealed an inverse association between rural residence and subjective health among men [OR = 0.518, 95%CI = 0.297, 0.901], and happiness [OR = 0.662, 95%CI = 0.381, 0.845] and life satisfaction [OR = 3.722, 95%CI = 1.502, 9.227] among women. Women having secondary [OR = 2.219, 95%CI = 1.209, 3.720] and higher [OR = 1.600, 95%CI = 1.041, 3.302] education also had higher odds of satisfaction with happiness. CONCLUSIONS: Our findings demonstrate the existence of significant urban-rural disparities in perceived health and quality of life among the young adult population in Guyana, especially among women. National health promotion projects should therefore take proper policy actions to address the underlying factors contributing to the urban-rural gaps in order to establish a more equitable healthcare system. Further researches are necessary to explore the underlying causes behind such disparities.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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) | 0,001 | 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 ».