Nutrition risk independent of body mass index is associated with cognitive performance in community-living older adults without cognitive impairment: Results from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Malnutrition is correlated with poor cognition; however, an understanding of the association between nutrition risk, which precedes malnutrition, and cognition is lacking. This study aimed to determine if nutrition risk measured with the SCREEN-8 tool is associated with cognitive performance among cognitively healthy adults aged 55+, after adjusting for demographic and lifestyle covariates. Sex- and age-stratified analyses were also explored. Baseline data from the Canadian Longitudinal Study on Aging was used. Cognition was determined using a 6-measure composite score based on four executive functions and two memory tasks, taking into account age, sex, and education. Multivariable linear regression was performed while adjusting for body mass index (BMI), lifestyle, and health covariates in the entire sample (n = 11 378) and then stratified by sex and age. Approximately half of participants were female (54.5%) aged 65+ (54.1%). Greater nutrition risk was associated with poorer cognitive performance in the entire sample (F[1, 11 368] = 5.36, p = 0.021) and among participants aged 55–64 (n = 5227; F[1, 5217] = 5.45, p = 0.020). Sex differences in lifestyle and health factors associated with cognition were apparent, but nutrition risk was not associated with cognition in sex-stratified models. Based on this analysis, there may be an association between nutrition risk and cognitive performance in older adults. When screening for either cognitive impairment or nutrition risk, complementary assessments for these conditions is warranted, as early intervention may provide benefit.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".