Lower cognitive function as a risk factor for anemia among older Japanese women from the longitudinal observation in the <scp>SONIC</scp> study
Bibliographic record
Abstract
AIM: The aging-related increase in the incidence of anemia potentially affects the mortality risk. Lower cognitive function is common among older adults, and anemia is one of the causes of cognitive decline. However, to the best of our knowledge, no study has investigated whether cognitive decline is a risk factor for anemia in older people. Therefore, in this study, we used a 3-year longitudinal evaluation to examine the association of cognitive function with anemia in community-dwelling older adults. METHODS: This longitudinal study enrolled participants without anemia (diagnosed based on the World Health Organization's criteria) at baseline. Cognitive function was assessed using the Japanese version of the Montreal Cognitive Assessment. Multiple logistic regression models were used to examine the association between cognitive function at baseline and the presence of anemia 3 years later. RESULTS: Participants were in the 69-71 and 79-81 years age groups, and 974 older people (48.6% men) were enrolled, of whom 126 (12.9%) had anemia after 3 years. After adjusting, cognitive function at baseline was associated with anemia in women, but not in men. CONCLUSIONS: Older Japanese women with lower cognitive function have an increased risk for anemia 3 years later. The adoption of a lifestyle that utilizes or improves cognitive function might be important to prevent anemia in older women. Geriatr Gerontol Int 2023; 23: 334-340.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".