OBESITY AND LONGITUDINAL CHANGES OF HANDGRIP STRENGTH IN OLDER ADULTS FROM DIFFERENT CONTEXTS
Bibliographic record
Abstract
It has been suggested that the amount of fat tissue may contribute to accelerated loss strength with aging. However, little is known about longitudinal associations between obesity and low muscle strength. To examine the predictive value of abdominal obesity on longitudinal changes of handgrip strength (HGS) in older men and women. Data on 803 community-dwelling older adults, between 65–74 years, were collected in 2012, 2014, 2016 in Natal (Brazil) and Saint-Hyacinthe (Canada). Sociodemographic characteristics, height, weight, waist circumference (WC) and HGS were assessed. Sex-specific linear mixed models were fitted to examine the trajectory of HGS according to quartiles of baseline WC. Among men, mean four year HGS was 2.62kg (p-value < 0.01). There was a gradient between decline of HGS and WC, with increasing decline among those with greatest waist circumference values (6.15 kg, p-value <0.001) after adjustment for age, research site, height and weight. In women, four year decline in HGS was smaller 1.0 kg (p-value < 0.01) and no association between baseline WC and decline in HGS was observed. Findings agree with previous cross-sectional research and emphasize the need for sex-specific analyses.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 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".