Low Muscle Strength Is Associated with Metabolic Risk Factors in Colombian Children: The ACFIES Study
Bibliographic record
Abstract
PURPOSE: In youth, poor cardiorespiratory and muscular strength are associated with elevated metabolic risk factors. However, studies examining associations between strength and risk factors have been done exclusively in high income countries, and largely in Caucasian cohorts. The aim of this study was to assess these interactions in schoolchildren in Colombia, a middle income Latin American country. METHODS: We measured body mass index, body composition, handgrip strength (HG), cardiorespiratory fitness (CRF) and metabolic risk factors in 669 low-middle socioeconomic status Colombian schoolchildren (mean age 11.52±1.13, 47% female). Associations between HG, CRF and metabolic risk factors were evaluated. RESULTS: HG and CRF were inversely associated with blood pressure, HOMA index and a composite metabolic risk score (p<0.001 for all) and HG was also inversely associated with triglycerides and C-reactive protein (CRP) (both p<0.05). Associations between HG and risk factors were marginally weakened after adjusting for CRF, while associations between CRF and these factors were substantially weakened after adjusting for HG. Linear regression analyses showed inverse associations between HG and systolic BP (β = -0.101; p = 0.047), diastolic BP (β = -0.241; p> = 0.001), HOMA (β = -0.164; p = 0.005), triglycerides (β = -0.583; p = 0.026) and CRP (β = -0.183; p = 0.037) but not glucose (p = 0.698) or HDL cholesterol (p = 0.132). The odds ratios for having clustered risk in the weakest quartile compared with the strongest quartile were 3.0 (95% confidence interval: 1.81-4.95). CONCLUSIONS: In Colombian schoolchildren both poorer handgrip strength/kg body mass and cardiorespiratory fitness were associated with a worse metabolic risk profile. Associations were stronger and more consistent between handgrip and risk factors than between cardiorespiratory fitness and these risk factors. Our findings indicate the addition of handgrip dynamometry to non-invasive youth health surveillance programs would improve the accuracy of the assessment of cardio-metabolic health.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".