Household Food Insecurity, Anemia, Malnutrition and Unfavorable Dietary Diversity among Adolescents: Quadruple Whammies in the Era of Escalating Crises in Lebanon
Bibliographic record
Abstract
Adolescence is a transitional period between childhood and adulthood. Nowadays, adolescents in Lebanon are growing during a time of unprecedented health crises and political instability. This study aimed to determine the prevalence and correlates of malnutrition, dietary diversity in adolescents’ households, and adolescents’ self-reported food insecurity in Lebanon. A national representative sample of 450 parent–adolescent dyads (parents: mean age ± standard deviation (SD) = 46.0 ± 7.0, mothers: 59.0%; adolescents: mean age ± SD = 15.0 ± 3.0, girls: 54.6%) were interviewed. Anthropometric and blood hemoglobin measurements were performed for adolescents. The Food Consumption Score, the Arab Family Food Security Scale and the Adolescent-Level Food-Security Scale were used. The overall prevalence of adolescent stunting, thinness, overweight, obesity and anemia was 6.7%, 4.7%, 19.3%, 12.9% and 16.7%, respectively. Almost 40.4% and 68% of adolescent’s households consumed undiversified diets and were food insecure, respectively. Food insecurity (FI) affected 54.0% of adolescents. Adolescents attending schools (vs. university) were eight times more likely to be stunted (p = 0.04). Boys had a 4.3 times higher thinness risk (p = 0.005) compared to girls. Households reporting an income decline since the start of the Lebanese economic crisis were three times more likely to have a thin adolescent (p = 0.01). Parental overweight/obesity (p = 0.002) and lower education level (p = 0.04) nearly doubled the risk of adolescent overweight or obesity. At a time when escalating crises in Lebanon are shifting diets for the youngest generations, the development of adolescent-responsive nutritional policies becomes a must.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".