Prevalence of chronic respiratory diseases and medication use among children and adolescents in Brazil - a population based cross-sectional study
Bibliographic record
Abstract
Abstract Objectives: to describe the prevalence of chronic respiratory diseases and their pharmacological management in children and adolescents in Brazil. Methods: data from the Pesquisa Nacional de Acesso, Uso e Promoção do Uso Racional de Medicamentos no Brasil (PNAUM)(National Access Survey, Use and Promotion of Rational Use of Medicines in Brazil),a population-based cross-sectional study, were analyzed. Household surveys were conducted between September 2013 and February 2014. We included the population under 20 years of age with chronic respiratory diseases. Prevalence of disease, indication of pharmacological treatment, and their use were assessed. Results: the prevalence of chronic respiratory diseases in children aged less than 6 years old was 6.1% (CI95%= 5.0-7.4), 4.7% (CI95%= 3.4-6.4) in those 6-12 years, and 3.9% (CI95%= 2.8-5.4) in children 13 years and older. Children under 6 showed a higher prevalence of pharmacological treatment indication (74.6%; CI95%= 66.0-81.7), as well as medication use (72.6%; CI95%= 62.8-80.7). Of those using inhalers, 56.6% reported using it with a spacer. The most frequent pharmacologic classes reported were short-acting β2 agonists (19.0%), followed by antihistamines (17.2%). Conclusion: children and adolescents who report chronic respiratory diseases living in urban areas in Brazil seem to be undertreated for their chronic conditions. Pharmacological treatment, even if indicated, was not used, an important finding for decision-making in this population.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".