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Predictive Model for Oral Status in Elderly People in a Taiwanese Nursing Home Using a High-Protein Black Soybean Koji Food. | LitMetric

With increased age, the appetite, chewing, swallowing, and digestive ability gradually decrease. Previous studies have shown that poor oral health is associated with an inadequate intake of macro and micronutrients and malnutrition. Therefore, improving the diet of elderly people and promoting nutrient absorption will help to improve the quality of life for elderly people. However, few studies have predicted their oral ability based on different food textures and other factors. The purpose of this study was to explore the correlation between oral assessment and texture parameters of high-protein black soybean koji products in elderly people in a nursing home. We used cross-sectional study design for seventy-nine residents aged 65 years and older were recruited. Three different texture of cookies, including normal cookie hardness (1.4 × 10 N/m), minced cookie hardness (4.4 × 10 N/m), and pureed cookie hardness (1.4 × 10 N/m) were provided to participants to test the oral status. An oral assessment scale was used by a dentist to evaluate the oral status of the elderly participants. Different cookie textures showed a significant positive correlation with pronunciation ( = 0.237, < 0.05), face ( = 0.371, < 0.01), tongue ( = 0.362, < 0.01), pharynx ( = 0.256, < 0.05), swallowing ( = 0.272, < 0.05), breathing ( = 0.315, < 0.01), and the total oral score ( = 0.339, < 0.01). We also used the high-protein black soybean koji products combined with elderly people's comprehensions in a predictive model that had a moderately high correlation to predict the oral status in the elderly group ( = 0.612). We concluded that the high-protein black soybean koji product was associated with the oral ability of elderly people in a nursing home in Taiwan. Our findings indicated that elderly people could immediately understand the correct food texture.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047994PMC
http://dx.doi.org/10.3389/fnut.2022.814315DOI Listing

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