Developmental delay in the Amazon: The social determinants and prevalence among rural communities in Peru
Bibliographic record
Abstract
The consequences of poor child development are becoming increasingly recognized. Programs are being put in place around the world to improve child development by providing healthy and stimulating environments for children. However, these programs often have limited reach and little is known about the prevalence of developmental delay in under-developed communities. The current study set-out to better understand the prevalence of developmental delay in rural communities in the Amazon region of Peru. Also, it explores social determinants that are associated with any delay. Cross-sectional study by evaluating developmental delay in children under 4 years utilizing Ages and Stages Questionnaire (ASQ-3). Additionally, conducting a social determinants questionnaire answered by caretakers to identify social drivers for developmental delay. The data was analyzed with multi-variant analysis to measure association. The prevalence of developmental delay in the Amazonian communities was 26.7% (19.3% in communication, 11.4% in gross motor skills, 8% in both) (N = 596). The multivariate logistic regression analysis revealed significant associations between developmental delay and; level of education (OR 0.64, p = 0.009), age of mother during child's birth (OR 0.96, p = 0.002), visits by community health agents (OR 0.73, p = 0.013), and river as primary water source (OR 2.39, p = 0.001). The social determinants questionnaire revealed that 39% of the mothers had their first child before the age of 17, nearly half stopped going to school before the age of 12 (52%), 29% gave birth at home, 13% breast fed for less than 7 months, and 50% of the children had diarrhea in the last month. There is still a great need to improve the conditions for child development in the Amazon region of Peru. One-fourth of the children suffer from developmental delay, which will likely impede their potentials for life unless something is done. The impact of education, age of mother at birth of the child, community health agents, and access to clean drinking water were important findings. Improvements can be made in these areas to create a large, cost-effective impact on the well-being of the communities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".