Individual and School-level Factors Associated With Non-Communicable Disease Risk Score Among Urban Schoolchildren in Lebanon: A Multi-Level Analysis
Bibliographic record
Abstract
Objectives: In the context of an advancing nutrition transition and high rates of overweight and obesity in schoolchildren in Lebanon, we explored individual and school level factors that are associated with unhealthy diets of Lebanese schoolchildren - assessed by the Global Diet Quality (GDQ) Project Non-Communicable Disease (NCD)-Risk score. Methods: A cross-sectional, cluster-randomized study recruited a representative sample of schoolchildren from grades 4-6 from 47 schools in Greater Beirut, Lebanon from Jan-May 2022. Surveys with children and school directors collected data on children’s diet, eating habits and food insecurity (FI), and school characteristics, respectively. A qualitative 24-hour dietary recall questionnaire collected data on all food consumed and grouped these into 29 categories based on the GDQ Diet Quality Questionnaire (DQQ). The DQQ NCD-Risk score reflecting dietary risk factors for NCDs was generated based on the consumption of eight food groups: soft drinks, baked sweets, other sweets, processed meat, unprocessed red meat, deep fried food, fast-food and instant noodles, and packaged ultra-processed salty snacks. FI was assessed using the Child Food Insecurity Experiences Scale. Multi-level mixed regression examined factors associated with NCD-Risk score. Results: The sample included 2,125 schoolchildren. Median NCD-Risk score was 2 (IQR=2). Availability of food outlets inside schools (Adjusted β: 0.5; 95% CI: 0.1:1), eating in front of a screen (Adjusted β: 0.2; 95% CI: 0.01:0.4) and receiving pocket money to buy food in school (Adjusted β: 0.2; 95% CI: 0.04:0.4) were associated with increased NCD-Risk score. Child-reported FI (Adjusted β: -0.3; 95% CI: -0.6:-0.05) was associated with a lower NCD-Risk score. Conclusions: Factors at the individual level (eating in front of a screen and receiving pocket money) in addition to school-level food sales were associated with the consumption of unhealthy diets in schoolchildren, whereas FI was associated with lower consumption of unhealthy diets. Interventions aiming to improve schoolchildren’s diets in this context need to consider restricting unhealthy food sales in schools, making healthy foods available and accessible in schools, and promoting healthy eating habits at home. Funding Sources: International Development Research Centre - Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".