Effect of Obesity on the Work Health-Related Behaviors and Quality of Life of South African Mining Employees: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Obesity rates have increased precipitously with a significant economic impact. Aim: The aim of this study was to investigate the effect of obesity on the work health-related behaviors and quality of life (QoL) of employees of mining companies in South Africa.METHODS: Forty (40) subjects from three mining companies were assigned to three BMI categories: normal weight (18.5‒24.9 kg/m2; n = 10), overweight 25.0‒29.9 kg/m2; n = 15), and obese (≥30.0 kg/m2; n = 15). Subjects wore a BodyMedia®FIT armband for seven consecutive days, and completed: 1) the WHO QoL; and 2) the WHO Health at Work survey.RESULTS: There were significant differences in calorie expenditure (p = 0.033), activity patterns (p = 0.017), and number of steps walked daily (p = 0.018) between the overweight and obese groups. Those of normal weight reported being significantly (p = 0.041) more satisfied with their QoL and their leisure time activities and income (p = 0.017) than the obese. Almost all the significant differences with regard to work health-related behaviors were between the overweight and obese groups.CONCLUSION: Results provide preliminary support for targeting weight loss as obesity may adversely influence employees’ work health-related behaviors and QoL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".