Association of neighborhood-level disadvantage beyond individual sociodemographic factors in patients with or at risk of knee osteoarthritis
Notice bibliographique
Résumé
OBJECTIVE: Lower socioeconomic status (SES) is a risk factor for poorer pain-related outcomes. Further, the neighborhood environments of disadvantaged communities can create a milieu of increased stress and deprivation that adversely affects pain-related and other health outcomes. Socioenvironmental variables such as the Area Deprivation Index, which ranks neighborhoods based on socioeconomic factors could be used to capture environmental aspects associated with poor pain outcomes. However, it is unclear whether the ADI could be used as a risk assessment tool in addition to individual-level SES. METHODS: The current study investigated whether neighborhood-level disadvantage impacts knee pain-related outcomes above sociodemographic measures. Participants were 188 community-dwelling adults who self-identified as non-Hispanic Black or non-Hispanic White and reported knee pain. Area Deprivation Index (ADI; measure of neighborhood-level disadvantage) state deciles were derived for each participant. Participants reported educational attainment and annual household income as measures of SES, and completed several measures of pain and function: Short-form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, and Graded Chronic Pain Scale were completed, and movement-evoked pain was assessed following the Short Physical Performance Battery. Hierarchical linear regression analyses were used to assess whether environmental and sociodemographic measures (i.e., ADI 80/20 [80% least disadvantaged and 20% most disadvantaged]; education/income, race) were associated with pain-related clinical outcomes. RESULTS: Living in the most deprived neighborhood was associated with poorer clinical knee pain-related outcomes compared to living in less deprived neighborhoods (ps < 0.05). Study site, age, BMI, education, and income explained 11.3-28.5% of the variance across all of the individual pain-related outcomes. However, the ADI accounted for 2.5-4.2% additional variance across multiple pain-related outcomes. CONCLUSION: The ADI accounted for a significant amount of variance in pain-related outcomes beyond the control variables including education and income. Further, the effect of ADI was similar to or higher than the effect of age and BMI. While the effect of neighborhood environment was modest, a neighborhood-level socioenvironmental variable like ADI might be used by clinicians and researchers to improve the characterization of patients' risk profile for chronic pain outcomes.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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) | 0,000 | 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 ».