Association of decreased hemoglobin levels with worse muscle mass and strength in community-dwelling older people
Bibliographic record
Abstract
We investigated the associations between red blood cell (RBC) count, hemoglobin (Hb) levels, muscle properties, and muscle strength in community-dwelling older adults, and examined whether RBC count and Hb levels were linked to muscle strength through muscle mass and/or quality, and whether these relationships were influenced by physical activity. The study included 85 community-dwelling older adults (39 males; mean age 75.3 ± 6.7 years). The participants visited the laboratory in the morning for venous blood sampling to analyze blood biomarkers. Quadriceps femoris muscle thickness (MT, muscle mass index) and echo intensity (EI, muscle quality index) were measured via B-mode ultrasonography, and maximum isometric knee extension strength was assessed using a dynamometer. The average daily step count was recorded for 2 weeks as an index of physical activity. Correlation and mediation analyses were used to investigate the associations between blood biomarkers and muscle properties, strength, and physical activity. The RBC count and Hb levels were positively correlated with MT and muscle strength, and negatively correlated with EI. After adjusting for age and sex, the correlations between RBC count, Hb levels, and MT and muscle strength remained significant, whereas the associations with EI disappeared. In the mediation analyses, the direct effect of RBC count and Hb levels on muscle strength was not significant, whereas the indirect effect of MT was, regardless of whether physical activity was adjusted. In community-dwelling older adults, lower RBC counts and Hb levels appear to be associated with diminished muscle mass, potentially resulting in muscle weakness.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".