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Linking the demographic, socio-economic and oral health status to oral health-related quality of life of the sudanese older adults: a cross sectional study

BACKGROUND: Oral Health-Related Quality of Life (OHRQoL) is an important measure of patients’ needs and progress. Identifying the links between clinical and non-clinical factors with OHRQoL in a specific population will facilitate the development of effective preventive strategies. The aim of the st...

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Detalles Bibliográficos
Autores principales: Salih, Mayson Ahmed, Ali, Raouf Wahab, Nasir, Elwalid Fadul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251693/
https://www.ncbi.nlm.nih.gov/pubmed/37291534
http://dx.doi.org/10.1186/s12903-023-03089-6
Descripción
Sumario:BACKGROUND: Oral Health-Related Quality of Life (OHRQoL) is an important measure of patients’ needs and progress. Identifying the links between clinical and non-clinical factors with OHRQoL in a specific population will facilitate the development of effective preventive strategies. The aim of the study was to assess the OHRQoL of Sudanese older adults, and to identify the possible relations between clinical and non-clinical predictors with OHRQoL using Wilson and Cleary model. METHODS: This cross-sectional study was conducted among older adults attending the out-patient clinics in Khartoum State’s Health Care Centers, Sudan. OHRQoL was assessed using the Geriatric Oral Health Assessment Index (GOHAI). Two modifications of Wilson and Cleary’s conceptual model were tested using structural equations modeling including: oral health status, symptom status, perceived difficulty of chewing, oral health perceptions, and OHRQoL. RESULTS: 249 older adults participated in the study. Their mean age was 68.24 (± 6.7) years. The mean GOHAI score was 53.96 (± 6.31) and trouble biting/chewing was the most commonly reported negative impact. Wilson and Cleary models showed that pain, Perceived Difficulty Chewing (PDC), and Perceived Oral Health had a direct effect on OHRQoL. In model 1, age and gender had direct effects on oral health status, while education had direct effects on OHRQoL. In model 2, poor oral health status is associated indirectly with poor OHRQoL. CONCLUSIONS: The OHRQoL of the studied Sudanese older adults was relatively good. The study partially confirmed Wilson and Cleary model as Oral Health Status was related directly to PDC and indirectly to OHRQoL through functional status.