Associations between socio-demographics, nutrition knowledge, nutrition competencies and attitudes in community-dwelling older adults in Singapore: Findings from the SHIELD study
Bibliographic record
Abstract
Abstract Background Nutrition literacy refers to an individual’s knowledge, motivation and competencies to access, process, and understand nutrition information to make nutrition-related decisions. It is known to influence dietary habits of older adults. This cross-sectional study was designed to: (1) understand the nutrition knowledge, competencies and attitudes of community-dwelling older adults in Singapore (2) examine the differences between their nutrition knowledge, and socio-demographic factors, competencies and attitudes, and (3) identify factors associated with better nutrition knowledge in community-dwelling older adults in Singapore. Methods 400 (183 males and 217 females) nourished community-dwelling older adults aged 65 years and above took part in this study. Malnutrition Universal Screening Tool (MUST) was used to determine individuals who were at low risk of undernutrition. Nutrition knowledge, competencies, attitudes and sources of nutrition information were measured using a locally developed scale. Nutrition knowledge scores were summed to form the Nutrition Knowledge Index (NKI). Associations between NKI, competencies, attitudes and socio-demographic variables were examined using Chi-square and Fisher’s Exact tests. Factors associated with NKI were determined using a stepwise regression model with resampling based methods for model averaging. Results Bivariate analyses found significant differences in NKI scores for gender, monthly household earnings, type of housing, the self-reported ability to seek and understand nutrition information and having access to help from family/friends. Females had higher NKI scores compared to males ( p < 0.001). Compared to females, more males left food decisions to others ( p < 0.001), and fewer males reported consuming home cooked food ( p = 0.016). Differences in educational level were found for competencies like the self-reported ability to seek ( p < 0.001) and verify nutrition information ( p < 0.001). Stepwise regression analysis showed that being female, Chinese, self-reported ability to understand nutrition information and having access to help from family/friends were associated with higher NKI scores. Conclusions Our study revealed that nutrition knowledge of older males in Singapore was lower than females and more left food decisions to others. Nutrition education programs could be targeted at both the older male and their caregivers. Trial Registration This study was registered on 7 August 2017 at clinicaltrials.gov (ref. NCT03240952).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".