Junk Food Consumption and its Association with Anthropometric Indices among undergraduates in Nigeria
Bibliographic record
Abstract
Junk foods consumption in institutions of higher learning has increasingly become an important part of students’ diet in Nigeria. This study was carried out to determine the pattern of junk food consumption among students in higher institutions of learning and the association between the junk food consumption and anthropometric indices measuring body weight status. A total of 900 students comprising 450 male and 450 female volunteers, aged 17 to 33 years were recruited from Akanu Ibiam Federal Polytechnic Unwana, Nigeria for the study. Seventy-nine percent of the students affirmed that the actually enjoy junk food. A total of 33.89% reported eating junk food everyday while 36.44% usually eat it at school during lunch with convenience been stated as the main reason for this consumption pattern by majority (48.44%). Low prevalence of obesity was observed i.e. 1.67% and 2.44% using body mass index (BMI) and waist-hip ratio (WHR), respectively, while majority of the volunteers i.e. 81.33% and 82.78% had normal BMI and WHR, respectively. There was no significant (P > 0.05) association between consumption of junk foods, frequency of consumption and body mass index or waist-hip ratio. This study revealed that there is no body weight status danger in junk food consumption pattern among the students. Thus, students may continue in their consumption pattern of this specified junk food if it is convenient and if it may enable them to meet up with their lined-up activities in the campus.
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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) | 0.002 | 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".