Musculoskeletal fitness and body composition of Newfoundland and Labrador offshore oil and gas workers
Bibliographic record
Abstract
Musculoskeletal fitness and body composition has been well studied as it relates to an individual’s overall health in relation to non-communicable diseases such as cardiovascular disease, cancers, chronic respiratory diseases, and diabetes (World Health Organization, 2015). The objectives of this research were to investigate the current musculoskeletal fitness and body composition of the Newfoundland and Labrador (NL) Offshore Workforce and to determine how this population compares to the Canadian population. Eighty-nine men from the NL offshore workforce (mean ± standard deviation; height: 177.13 ± 6.77 cm, mass: 92.02 ± 16.07 kg, age: 42 ± 9.76 years) were included for analysis in this study. Data was collected offshore by a Definitions® wellness representative from five offshore industry companies. All measures were collected in accordance with the Canadian Physical Activity, Fitness & Lifestyle Approach Manual (Canadian Society for Exercise Physiology, 2004), the Physical Activity Training for Health manual (Canadian Society for Exercise Physiology, 2013) or Advanced Fitness Assessment And Exercise Prescription (Heyward & Gibson, 2010). Body composition measures included body mass index (BMI), waist circumference, and skin-folds. Musculoskeletal measures included push-ups, partial curl-ups, back extension, sit-and-reach, and grip strength. Participants were divided into two age groups: 20 – 39 and 40 – 59. Results from both groups showed that offshore workers have poor body composition, but have generally good musculoskeletal fitness compared to Canadian norms. However, both groups performed similarly on the musculoskeletal fitness tests. This means that a younger population has the physical strength and endurance of a population that is on average 14 years older. Overall, the results indicated the need to improve the overall body composition of the offshore workforce with ongoing development to maintain, or improve in some instances, musculoskeletal health. These results are an important starting point, whereby the Canadian Newfoundland and Labrador Offshore Petroleum Board can investigate the feasibility of offshore specific health and wellness programming that aims to improve the physical fitness of all offshore workers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".