Criterion-referenced mCAFT cut-points to identify metabolically healthy cardiorespiratory fitness among adults aged 18–69 years: an analysis of the Canadian Health Measures Survey
Bibliographic record
Abstract
This study aimed to develop and validate health-related criterion-referenced cut-points for the modified Canadian Aerobic Fitness Test (mCAFT), a field-based measure to predict cardiorespiratory fitness among adults (18–69 years). Criterion-referenced mCAFT cut-points were developed using nationally representative data from cycles 1 (2007–2009) and 2 (2009–2011) of the Canadian Health Measures Survey (CHMS). Receiver operating characteristic curves were used to identify age- and sex-specific cut-points for measured waist circumference, blood pressure, and high-density lipoprotein. Cut-points were validated against metabolic syndrome using a fasted subsample (n = 1093) from cycle 5 (2016–2017). For the main analyses, 4967 participants (50% women) were retained. The mCAFT cut-points ranged from 28 to 43 mL·kg–1·min–1 (area under the curve (AUC): 0.60–0.87) among men, and 23 to 37 mL·kg–1·min–1 (AUC: 0.61–0.86) among women. The likelihood of meeting the new mCAFT cut-points decreased with an increase in the presence of metabolic risk factors. In total, 54% (95% confidence interval: 42% to 67%) of Canadian adults met the new mCAFT cut-points in 2016–2017. This study developed and validated the first health-related criterion-referenced mCAFT cut-points for metabolic health among Canadian adults aged 18–69 years. These mCAFT cut-points may be useful in health surveillance, clinical, and public health settings. Novelty We developed and validated new criterion-referenced cut-points for the mCAFT to help identify adults at potential risk of poor metabolic health. These new cut-points could help support national health surveillance efforts.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".