Risk of malnutrition among orally compromised community-living, older adults in Winnipeg
Bibliographic record
Abstract
Older adults, who are malnourished but remain undíagnosed due to the similarities between aging and the symptoms of early protein-calorie malnutrition, are at risk for increased morbidity and mortality.Based on evidence that nutritional counseling is effective in changing diet, the Canadian Task Force on Preventive Health Care (1994) recommended screening for protein/calorie malnutrition for certain high-risk groups.Many dental researchers consider edentulous patients to be high-risk and therefore advocate routine dietary counseling for these patients.This assumption results in two questionable outcomes.lt suggests that treatment should be performed without diagnosis.lt will also result in precluding dentate individuals at nutritional risk from counseling.The purpose of this preliminary study was to determine the prevalence of malnutrition and risk of malnutrition in orally functional and orally compromised community-living older adults who attend a teaching facility for dental care and to assess further factors associated with risk of malnutrition.The prevalence of malnutrition was determined by using a nutritional screening tool, the Mini Nutritional Assessment.Variables associated with risk of malnutrition were determined by univariate testing from a test instrument against risk of malnutrition.Fon¡rard stepwise logistic regression was then utilized to identify the variables that made a unique contribution to a patient's odds of being at risk of malnutrition.No subjects were determined to be malnourished.Prevalence of risk of malnutrition was 11 .60/o,with prevalence for orally compromised at 13.9% and for those orally functional at 9.6%.Four variables were identified to be associated i ABSTRACT with risk of malnutrition.These variables were then adjusted due to differing age distributions in the sample population to determine the adjusted odds ratio.Subjects with dry mouths were found to be 7.724 times more at risk, those not satisfied with their chewing ability were 5.868 times more at risk, and subjects who grew up in larger urban cities were found to be 7.937 times more at risk for malnutrition.Risk increased 15.8Yo per year or 4.336 times per decade after age 65.A table was developed to assist in predicting individuals at increased risk of malnutrition.A conceptual model was also developed to assist in demonstrating risk determinants, markers, and indicators responsible for dietary intake and the role of the oral/dental complex in this process.This preliminary cross-sectional study provides information to oral healthcare providers that risk of malnutrition exists in both orally functional and orally compromised patients.Practitioners who do not wish to perform routine nutritional screening should consider screening based on the variables found to be associated with malnutrition.Modifications to a recommended diagnostic tool, the Mini Nutritional Assessment, were included to reflect these variables for the community-living older adult.I wish to express my gratitude to Dr. Tom Hassard for his endless patience, generosity with severely limited time, and genuine kindness.His actions will serye to guide me in my ultimate goal to be as gentle and empowering a role model to my students as he is for his.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".