Unhealthy Fat in Street and Snack Foods in Low-Socioeconomic Settings in India: A Case Study of the Food Environments of Rural Villages and an Urban Slum
Bibliographic record
Abstract
OBJECTIVE: To describe the food environment in rural villages and an urban slum setting in India with reference to commercially available unbranded packaged snacks and street foods sold by vendors, and to analyze the type and quantity of fat in these foods. DESIGN: Cross-sectional. SETTING: Two low-income villages in Haryana and an urban slum in Delhi. PARTICIPANTS: Street vendors (n = 44) were surveyed and the nutritional content of snacks (n = 49) sold by vendors was analyzed. MAIN OUTCOME MEASURES: Vendors' awareness and perception of fats and oils, as well as the type of snacks sold, along with the content and quality of fat present in the snacks. ANALYSIS: Descriptive statistics of vendor survey and gas chromatography to measure fatty acid content in snacks. RESULTS: A variety of snacks were sold, including those in unlabeled transparent packages and open glass jars. Mean fat content in snacks was 28.8 g per 100-g serving in rural settings and 29.6 g per 100-g serving in urban settings. Sampled oils contained high levels of saturated fats (25% to 69% total fatty acids) and trans fats (0.1% to 30% of total fatty acids). CONCLUSIONS AND IMPLICATIONS: Interventions need to target the manufacturers of oils and fats used in freshly prepared products to improve the quality of foods available in the food environment of low-socioeconomic groups in India.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".