Dietary Inadequacy of Micronutrients in Adolescent Girls of Urban Varanasi: Call for Action
Bibliographic record
Abstract
Background: Adolescent girls are vulnerable to dietary inadequacy in general and micronutrients (viz, Iron, Calcium, Vitamin A and C etc) inadequacy in particular due to variety of reasons including their own food preferences. Lack of protective foods in their diet can have serious consequences. Objective: To assess dietary inadequacy of micronutrients in urban adolescent girls and to pinpoint their correlates. Methodology: A community based cross sectional study was undertaken on 400 adolescent girls (10-19 years) of urban Varanasi, selected by adopting multistage sampling technique. Their socio-demographic and personal characteristics were obtained by interviewing parents or other responsible family member. Dietary intake of subjects was assessed by 24 hours recall oral questionnaire method and their micronutrients intake was computed by using nutritive value of Indian foods. Result: In case of 72.8%, 71.2%, 88.2% and 6.2% subjects calcium, iron, Vitamin A and Vitamin C intakes were <50% of Recommended Dietary Allowances. Taking 10-14 years as reference risk of less iron intake was more (AOR; 3.66 CI: 1.30-10.30) in subjects aged 18-19 years. When Scheduled Caste was taken as reference category, risk of less iron intake was more in subjects from other caste category (AOR; 2.91, CI: 1.07-7.91). In comparison to subjects having sibling <4 risk of less calcium intake was more (AOR; 4.37 CI: 1.10-17.39) in subjects having sibling >7.With reference to vegetarians, odds of less vitamin C intake was more in nonvegetarian (AOR=2.01: CI-1.10-3.65) and eggitarian (AOR=2.53: CI-1.03-6.19). Conclusion: Micronutrients deficiency in urban adolescents is quiet predominant and calls for community based interventions to streamline micronutrients supplementation and therapeutic strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".