The relationship between pubertal timing and under‐nutrition in rural Pakistan
Bibliographic record
Abstract
INTRODUCTION: Sexual development in females and males are routinely measured according to the Tanner Stages. Sparse data exist on the timing of pubertal milestones in Pakistan. To fill this gap, the age of attainment of pubertal milestones and their relationship with nutritional status was explored among children and adolescents living in the rural district of Matiari, Pakistan. METHODS: Anthropometry, nutrition biomarkers and Tanner Stage were assessed among girls aged 9.0-14.9 years (n = 723) and boys aged 10.0-15.9 years (n = 662) who were free from known disease in the rural District of Matiari, Pakistan. Median age was calculated for all Tanner Stages and menarche. Multivariable linear regressions were undertaken to determine covariates associated with the timing (age) of pubertal milestones. RESULTS: Among participants living in this rural community, the median age of puberty onset for girls was 11.9 years (95%CI:10.9; 12.5) and boys was 12.3 years (95%CI:11.5; 12.9). Age at first menarche was 12.9 years (95%CI:12.1; 13.3). Undernutrition was widespread among adolescents in this community. Thirty-seven percent of females and 27.0% of males were stunted while 20.5% of females and 31.3% of males were thin. Only 8% (n = 58) of females and 12% (n = 78) of males were free from any nutrient deficiency with most adolescents having two or three nutrient deficiencies. CONCLUSIONS: Undernutrition (stunting or thinness) was associated with relatively older ages for early puberty stages but not puberty completion. This may decrease the duration of the pubertal growth spurt and curtail potential catch-up growth that may occur during puberty. Efforts to decrease nutrient deficiencies, stunting and thinness beyond childhood should be made in rural Pakistan.
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 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 | 0.000 | 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 | 0.001 |
| 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".