Dietary Intake Patterns and Nutritional Status of Food Secure and Insecure Women Garment Factory Workers in Bangladesh
Bibliographic record
Abstract
Maintaining a good dietary intake and adequate nutritional status to ensure food security is a major challenge for the garment factory workers in Bangladesh. This study was carried out using a cross-sectional survey. To determine the nutritional status of the female garment factory workers’, anthropometric measurements as calculating height, weight, body mass index (BMI), waist and hip circumference were conducted. Using a validated semi-quantitative food frequency questionnaire, the dietary intake patterns of female garment factory workers were assessed. In the cereal group, dried rice (0.18(SD 0.38), P=0.005) was preferred most by food-insecure participants. A significant mean intake of lentil (1.43(SD 0.49), P=0.020) was observed by food-secure female garment factory workers. A higher percentage was noticed in the occurrence of obese (94.4), and unhealthy waist circumference (69.4) among food-insecure female garment factory workers. Children studying in the family (adjusted b= -0.20, 95% CI, (-0.35, -0.04), P=0.013) was significantly associated with a decline in BMI of contributors in the study. Age (adjusted b= 0.30, 95%CI (0.15, 0.44), P=<0.001) and physical function (adjusted b= -0.05, 95% CI (-0.11, -0.003), P=0.04) were significantly associated with the increase or decrease in waist circumference of women garment factory workers. Anthropometric measurements (weight, body mass index, waist circumference) of female garment factory workers should be checked regularly.
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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 | 0.000 | 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".