Fat from dairy foods and ‘meat’ consumed within recommended levels is associated with favourable serum cholesterol levels in institutionalised older adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract CVD is common in older adults. Consumption of ‘meat’ (beef, pork, lamb, game, poultry, seafood, eggs) and dairy foods (milk, cheese, yoghurt) is encouraged in older adults as these foods provide protein and nutrients such as essential fatty acids, Ca, Fe, Zn and vitamins A, D and B 12 required for healthy ageing. However, these foods also contain saturated fats considered detrimental to cardiovascular health. To determine the effect of their consumption on CVD risk we assessed associations between fat intake from ‘meat’ and dairy foods and serum cholesterol levels in 226 aged-care residents (mean age 85·5 years, 70 % female). Dietary intake was determined over 2 d using visual estimation of plate waste. Fat content of foods was determined using nutrition analysis software (Xyris, Australia). Fasting serum total cholesterol (TC), LDL-cholesterol and HDL-cholesterol were measured, and the TC:HDL-cholesterol ratio calculated. Associations were determined using random-effect models adjusted for CVD risk factors using STATA/IC 13.0. Total fat and saturated fat from ‘meat’ and dairy foods were associated with higher serum HDL-cholesterol levels, and dairy fat intake and number of servings were associated with a lower TC:HDL-cholesterol ratio. Every 10 g higher intake of fat and saturated fat from dairy products, and each additional serving was associated with a −0·375 (95 % CI −0·574, −0·175; P = 0·0002), a −0·525 (95 % CI −0·834, −0·213; P = 0·001) and a −0·245 (95 % CI −0·458, −0·033; P = 0·024) lower TC:HDL-cholesterol ratio, respectively. Provision of dairy foods and ‘meat’ in recommended amounts to institutionalised older adults potentially improves intakes of key nutrients with limited detriment to cardiovascular health.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it