Use of Quantile Regression in Determining Factors Associated with BMI Among Vulnerable Adolescents in Rivers State, Nigeria
Bibliographic record
Abstract
Body Mass Index has been investigated using the traditional regression methods which may not provide a complete picture of the effects of the independent variables when the outcome is continuous and skewed. Information on the nutritional status of vulnerable adolescents in Nigeria is scanty thereby hindering appropriate intervention by policy decision-makers. We investigated the nutritional status of vulnerable adolescents by examining their body mass index (BMI). A cross-sectional survey of vulnerable adolescents, aged 10-17 years was conducted in three local government areas in Rivers state, Nigeria. A structured questionnaire was used to gather information on the economic status, means of livelihood and accessibility to education, nutrition and health of the adolescents. Quantile regression models were fitted to the data. About 39% of the 494 adolescents were underweight, 49.8% had normal weight, 5.5% were overweight while 6.1% were obese. Age was a significant predictor of BMI for the males at the 50th quantile. Adolescent males that experienced food insecurity showed lower BMI compared to those who were food secured. Age, sex, food insecurity and household economy were determinants of BMI among vulnerable adolescents.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".