Biomechanical differences between obese and healthy-weight workers in manual materials handling
Bibliographic record
Abstract
The objective of this study was to evaluate the work strategies of obese and healthy-weight workers in manual materials handling. Seventeen obese and 20 healthy-weight manual materials handlers participated in this laboratory study. The tasks consisted of transferring four boxes between a hand trolley and a conveyor. The weight of the box (15 vs. 23 kg), the handling height and the working configuration were modified to see what impact these changes had on the participants’ manual materials handling. Biomechanical measures included net moments, expressed in the pelvic system (flexion–extension, lateral bending and torsion moments), kinematics of body segments and box displacements. The results indicated that trunk and knee postures and horizontal hand distances from L5/S1 were not significantly different between the two groups. Peak moments of force around the transverse, sagittal and longitudinal axes at L5/S1 were 13.3% to 59.0% higher during box lifting and lowering for the obese than for the non-obese workers. The individuals’ body weight explained 57% of the variability in the maximal transverse moments of force at L5/S1 during the lifting of the boxes from the ground. These results suggest that the extra mass of an obese worker causes additional stress for the musculoskeletal structures of the back. These biomechanical differences potentially place obese workers at a greater risk of developing musculoskeletal problems during manual materials handling.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".