Association Between Sex-specific Handgrip Strength and Plasma Glycated Hemoglobin Levels Among Older Adults: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVES: Adults with diabetes have 37% to 109% higher odds of sarcopenia than normoglycemic individuals. Handgrip strength (HGS) is a key marker of sarcopenia, yet its association with glycated hemoglobin (A1C), a measure of long-term glycemia, remains unclear. METHODS: We conducted a cross-sectional study of 121 outpatients ≥65 years of age (80 women, 41 men). HGS was measured 3 times per hand using a calibrated dynamometer and the mean was recorded. Low HGS was defined using cutoffs of the European Working Group on Sarcopenia in Older People. Fasting A1C, analyzed in an accredited laboratory, was categorized as normal (<5.7%), prediabetes (5.7% to 6.4%), and diabetes (≥6.5%). Correlations between A1C and anthropometric/functional measures were evaluated, and multivariate linear regression identified A1C predictors. RESULTS: =0.0015 and 0.012, respectively), but not in women. Post hoc power analysis showed that the smaller correlation between HGS and A1C in women had low statistical power, suggesting that the nonsignificant result may be due to insufficient power rather than a true absence of association. CONCLUSIONS: Lower HGS was associated with higher A1C in older men. The nonsignificant results in women are likely attributable to low statistical power.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".