An epidemiological study of urban and rural children in Pakistan: examining the relationship between delayed psychomotor development, low birth weight and postnatal growth failure
Bibliographic record
Abstract
BACKGROUND: Low birth weight is known to be associated with postnatal growth failure. It is not yet established that both conditions are determinants of psychomotor development. The study investigated whether or not low birth weight leads to delayed psychomotor development of a child, and whether it can be mitigated by adequate postnatal growth. METHODS: A cross-sectional study was conducted in 2002 in 15 rural and 11 urban communities of Sindh province, Pakistan. Assessment of 1234 children less than 3 years of age included Bayley's Scale of Infant Development II, socioeconomic questionnaire and anthropometry; WHO standards were used to calculate z-scores of height-for-age, weight-for-height and weight-for-age. The underlying study hypotheses were tested through multiple regression modelling. RESULTS: Out of 1219 children, 283 (23.2%) had delayed psychomotor development and 639 (52.4%) were undernourished according to the composite index of anthropometric failure. Strong negative associations with the psychomotor development index were detected between stunting and being underweight, with a larger magnitude of effect for stunting (p<0.001). The strong relationship persisted even when the analysis was restricted to non-malnourished children. The psychomotor index increased by 2.07 points with every unit increase in height-for-age z-score. CONCLUSIONS: The relationship between low birth weight and psychomotor development appears to be mediated largely by postnatal growth and nutritional status. This association suggests that among undernourished children there is significant likelihood of a group that is developmentally delayed. It is important to emphasize developmental needs in programmes that target underprivileged children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".