The Relationship between Food Environments and Nutritional Status of School-aged Children and Adolescents in Low- and Middle- income Countries: Evidence from Pakistan
Bibliographic record
Abstract
Food environments in low- and middle- income countries (LMICs) have undergone unprecedented changes over recent decades with the emergence of modern supply chains, coupled with shifts in consumer food choice. The accessibility and availability of cheap, ultra- processed foods have led to suboptimal diets, and a rise in the double burden of malnutrition particularly in school-aged children and adolescents (SACA). The aim of this dissertation is to improve the understanding of the food environment and its relationship with diet-related health outcomes in SACA in LMICs and advance the methodological approaches to assess and monitor food environments in such settings and population. The first study led to a comprehensive understanding of methodologies for conceptualizing and analyzing food environments in LMICs and presented a systematic, inclusive portfolio of methods and metrics for SACA, which can be used to study the relationship between the food environment, diet and nutritional outcomes. To pilot test these indicators, an empirical assessment of retail food environments in Pakistan and its relationship to adolescent nutrition outcomes was conducted. Findings from the second study suggest that in the peri-urban district of Sindh, modernization is underway with the increasing accessibility and availability of unhealthy foods as compared to healthy foods. When examining the association between food environment characteristics and nutrition outcomes in adolescents, the total number of food outlets were significantly associated to hemoglobin in both adolescent girls and boys, whereas for BMI z-score, mean total number of healthy food items was significantly associated in adolescent boys, but not girls. Finally, a systematic review and meta-analysis on the effectiveness of food environment interventions on diet-related health outcomes in SACA in LMICs was conducted. Seven randomized controlled trials (RCTs), and six quasi-experimental studies were included. A pooled analysis of RCTs indicated no significant effect of the intervention on BMI (kg/m2), (mean difference: -0.08, 95% confidence interval of -0.18, 0.02). Taken together, this body of work provides novel and necessary evidence to inform the design and development of standardized tools and future food environment interventions related to improving diet-related health outcomes in SACA in LMICs.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".