Unveiling the lockdown effects: exploring behavior, dietary habits and weight changes in rural Egypt during COVID-19 lockdown: a cross-sectional retrospective study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 lockdown significantly impacted dietary habits and body weights globally, particularly in Egypt, where 57.03% of the population resides in rural areas, despite lack of information. The study examines the impact of COVID-19 lockdown on the weight changes of the rural Egyptian population through behavioral, physical, and dietary changes. METHODS: A cross-sectional online survey using Microsoft Forms was distributed in Delta regions in Egypt. The questionnaire used a modified version of the validated 14- items PREDIMED MedDiet Adherence Screener (MEDAS). The first part of the questionnaire addressed sociodemographic variables whereas the second one included questions related to dietary, behavioral and weight changes of participants. These changes were statistically tested for significance in relation to BMI, gender, home living, current job and family history of obesity. RESULTS: A total of 306 participated in the study (70% females, 13% obese, 95% living with family, 56% university students, and 36% with family history of obesity). Obese showed a significant increase in sweet intake whereas underweight and normal weight people displayed a significant decrease in eating desire. Both females and males showed significant increase in consumption of fruits and vegetables with significant decrease in soft drink. However, women showed a significant decrease in sport activity relative to men. Participants living with family showed an increase in sweet intake while those living alone explored an increase in meal frequency. Employers revealed a significant decrease in sport activities and people with family history of obesity reported more sleeping times than those without family history of obesity. CONCLUSION: During Covid-19 quarantine, Egyptians' eating habits improved, but daily routines were disrupted. Raising awareness about obesity and providing guidance on maintaining activity, energy, and mood is crucial for future quarantine situations.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".