P101 Estimating the quality of life and economic impact of arthritis in Tanzania
Notice bibliographique
Résumé
Abstract Background/Aims Musculoskeletal (MSK) disorders are one of the major causes of non-traumatic disability within the global burden of disease. A 2010 Global Burden of Disease study reported that MSK diseases account for 20% of all Years Lived with Disability (YLDs) in low/middle income countries. Significantly contributing to this MSK burden is arthritis. In Tanzania, a lack of data exists on the prevalence, quality of life, economic and societal impact of arthritis. We aim to estimate the health, economic and societal burden of arthritis in Tanzania. Methods A community-based cross-sectional survey was undertaken between January 2021 to Sept 2021 in the Kilimanjaro region of Tanzania working in partnership with the Kilimanjaro Christian Research Institute and Kilimanjaro Christian Medical Centre. Clinical screening tools, including the Gait Arms Legs Spine (GALS) and Regional Examination of the Musculoskeletal system (REMS) were used to screen people with MSK diseases and possible arthritis through a tiered system approach. Economic and quality of life questionnaires were used for a representative sample of all residents (aged over 5 years old) in selected households. Ethiopia and Zimbabwe tariffs were used for the EuroQol EQ-5D. Resource use captured out-of-pocket costs, healthcare costs, absenteeism, presenteeism & work productivity loss. Regression based analysis were undertaken to estimate differences in utility scores and resources use / costs between those presenting as REMS+/- and GALS+/-. Other explanatory variables in the model included age, occupation, marital status, gender, religion, tribe, education. Results Preliminary results on data collected to-date show that for all QoL dimensions those with a positive diagnosis had lower utility scores. Whilst the population norms are in line with utility values for that age group from other countries (30-40 years, ∼0.9 utility), those presenting with a positive diagnosis had a significant reduction in utility of ∼0.12 to 0.15 depending on what country tariff was used. A higher proportion of participants in GALS/REMS +ve groups experienced work loss (6 x more likely) and had visited healthcare facilities/hospitalisation (2.5 x more likely) compared to GALS/REMS -ve. Health-related costs reported by household financial respondents did not show a significant statistical difference albeit a likely economically significant difference (Tanzanian Shillings 13,535 vs 6,683, p = 0.05), when adjusted for age and gender. Conclusion This is the first study to estimate burden and prevalence estimates of MSK in Tanzania using valid screening tools along with estimates of preference-based quality of life, disability impacts and quantification of the economic impacts of MSK. This study quantifies the significant burden of rheumatological conditions both in terms of health and poverty. The results will be used to guide clinical health practices, intervention design, service provision, and health promotion and awareness activities both at KCMC institutional level, Kilimanjaro region and national level. Disclosure E. Grieve: None. P. Hsieh: None. E. McIntosh: None. M. Deidda: None.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».