The impact of body mass index (<scp>BMI</scp>) on satisfaction with work life: An international <scp>BODY‐Q</scp> study
Bibliographic record
Abstract
Obesity is a global health issue known to have a major influence on health-related quality of life (HR-QOL). HR-QOL is a concept evaluating physical and psychological health. Work life can impact HR-QOL in people with obesity. The aim of this study was to measure the association between body mass index (BMI) and satisfaction with work life. This study included participants from an international multicenter field-test study of BODY-Q scales. Recruitment took place at hospitals in Denmark, The Netherlands and USA between June 2019 and January 2020. The BODY-Q Work Life scale was used to measure work life satisfaction. The difference between BMI groups and work life satisfaction was examined using one-way analysis of variance. Multivariable linear regression analysis was used to examine the association between BMI and work life satisfaction, adjusted for significant confounders. Of 4123 participants, 2515 completed the BODY-Q Work Life scale. BMI groups showed significant difference in work life satisfaction (p < .0001). The Work Life scale mean score was 77.6 for the normal BMI group, 78.5 for the overweight group and 75.0, 68.9 and 63.8 for Class 1, 2 and 3 obesity, respectively. Furthermore, BMI was significantly associated with satisfaction with work life (adjusted regression coefficient -.962, p < .0001). Higher BMI was associated with lower work life satisfaction. This finding suggests that a reduction in BMI may have a positive influence on work life satisfaction in people with obesity.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".