Prevalence and Patterns of Dental Care Utilization among US-Born and Non–US Born Hispanics in the Hispanic Community Health Study/Study of Latinos
Notice bibliographique
Résumé
OBJECTIVES: Access to routine dental services is important to maintaining good oral health. The aims of this study were to describe the dental care utilization patterns of a diverse group of Hispanic/Latino men and women and assess differences in dental care utilization by perceived need for dental care and proxy measures of acculturation. METHODS: Data from 13,792 participants of the Hispanic Community Health Study were analyzed with SAS 9.4. Time since last dental visit was dichotomized into <1 and ≥1 y. Acculturation measures included the language and social subscales of the Short Acculturation Scale for Hispanics, the Multiethnic Study of Atherosclerosis nativity subscore, and immigrant generation. Survey logistic regression adjusted for demographic (age and sex) and health-related variables, estimated associations among perceived need for dental care, acculturation measures, and dental care utilization. RESULTS: About a quarter (23%) of the participants were born in the 50 US states, excluding territories, while 77% were non-US born. Overall, 74% perceived a need for dental care. Upon covariate adjustment, perceiving a need for dental care was associated with reduced odds of reporting a past-year dental visit (odds ratio, 0.32; 95% CI, 0.28 to 0.37), while there appeared to be no meaningful association between proxy measures of acculturation and past-year dental visit. Having health insurance was significantly associated with a past-year dental visit (odds ratio, 2.23; 95% CI, 1.99 to 2.49) for all groups combined and among the different Hispanic/Latino background groups. CONCLUSIONS: Acculturation affects general health and contributes to general health disparities; however, its role in dental care utilization remains questionable. Given that acculturation is a process that occurs over several years, longitudinal studies that evaluate oral health trajectories along the acculturation continuum are needed. KNOWLEDGE TRANSFER STATEMENT: The results of this study are valuable for dental public health program planning and implementation for minority groups, as it describes the varying patterns of dental care utilization among US-born and non-US born Hispanics/Latinos and identifies factors that may partly explain dental care utilization patterns, such as acculturation.
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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 | 0,004 | 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 | 0,001 |
| 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 ».