Ethnicity and Socioeconomic Factors Are Associated with Poor Nutritional Status in Female Tea Plantation Workers from Rural India
Bibliographic record
Abstract
Poor nutritional status is a major challenge for rural Indian women. The objective of the present study was to determine the association between the socioeconomic and nutritional status of female tea plantation workers from West Bengal, India. Methods This cross‐sectional survey collected data on the nutritional and socioeconomic status of 246 female tea plantation workers from Panighata tea garden, West Bengal. The participants were non‐pregnant female estate workers of Adivasi and Nepali ethnic groups who were full‐time, experienced, permanently employed tea pickers. Poor nutritional status or underweight was defined as BMI <18.5 wt/ht 2 (kg/m 2 ). Results The prevalence of underweight was 57% and 17% in Adivasi and Nepali, respectively. The estimated odds (OR [95% CI]) of being underweight was 6.5 times greater in Adivasi compared to Nepali women (OR=6.5 [3.6, 11.7]; p=<0.0001). The odds of being underweight when toilet facilities were present were 70 percent lower than when the toilet facilities were not available (OR = 0.3 [0.1, 0.6]; p=0.002). Similarly, being underweight was negatively associated with the literacy of the spouse (OR = 0.3 [0.1, 0.7]; p=0.004). The effect of ethnicity on nutritional status was still significant after controlling for socioeconomic variables (OR=2.7 [1.1, 6.9]; p=0.03). Conclusions Poor socioeconomic status and exposure to poor sanitation challenge the health of rural Indian women. Ethnicity is an additional barrier affecting the nutritional status of these tea plantation workers with the Adivasi tribal population at the greatest risk for underweight. To improve women's nutritional situation in rural India, it is important to implement comprehensive nutritional, educational, and health programmes considering the ethnic diversity along with the existing rural development policies and programmes. Support or Funding Information Supported by the Mathile Institute for the Advancement of Human Nutrition and the Micronutrient Initiative
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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 | 0.001 | 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".