Consumption of Iron Supplement and Anemia Among Indonesian Adolescent Girls
Bibliographic record
Abstract
BACKGROUND: Anemia is one of nutritional problem in Indonesia, especially in society with low socioeconomic status. There are many factors that can cause anemia, including poor intake of iron rich food and also iron supplement. OBJECTIVE: This study aimed to analyze consumption of iron supplement and anemia among adolescent girls. METHODS: This research used cross sectional design involving 251 adolescent girls in Lamongan District, Indonesia. Data on iron supplement intake was measured using questionnaire, food intake was measured using food record and hemoglobin level measured by Quik-Check hemoglobinmeter (Acon Laboratories.inc). Data were analyzed using Pearson correlation test. RESULTS: The average hemoglobin level of respondents was 13.43 ± 1.4 g/dl. The prevalence of anemia among adolescent girls was 13.9%. The average student energy intake was still below the normal Nutrition Adequacy Rate for adolescent girl aged 15 – 18 years old (2125 Kcal per day). The test results using the Pearson Correlation test indicate that the only food intake variables that has significant relationship with hemoglobin levels was energy intake (p=0.02). Their current practice of consuming iron supplementation from government program as well as voluntary or purchased supplement was lacking. However, they did consume government’s iron and folic acid supplement during their junior high school years. CONCLUSION: In conclusion, the current practice in taking iron supplement and food intake among adolescent girls in Lamongan district was poor. However, the prevalence of anemia was low and it was thought to be related to the success of the iron supplement program during the participants’ junior high school (2-3 years ago).
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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 | 0.000 | 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) | 0.001 | 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".