Crowding: risk factor or protective factor for lower respiratory disease in young children?
Bibliographic record
Abstract
BACKGROUND: To study the effects of household crowding upon the respiratory health of young children living in the city of São Paulo, Brazil. METHODS: Case-control study with children aged from 2 to 59 months living within the boundaries of the city of São Paulo. Cases were children recruited from 5 public hospitals in central São Paulo with an acute episode of lower respiratory disease. Children were classified into the following diagnostic categories: acute bronchitis, acute bronchiolitis, pneumonia, asthma, post-bronchiolitis wheezing and wheezing of uncertain aetiology. One control, crudely matched to each case with regard to age (<2, 2 years old or more), was selected among healthy children living in the neighborhood of the case. All buildings were surveyed for the presence of environmental contaminants, type of construction and building material. Plans of all homes, including measurements of floor area, height of walls, windows and solar orientation, was performed. Data were analysed using conditional logistic regression. RESULTS: A total of 313 pairs of children were studied. Over 70% of the cases had a primary or an associated diagnosis of a wheezing illness. Compared with controls, cases tended to live in smaller houses with less adequate sewage disposal. Cases and controls were similar with respect to the number of people and the number of children under five living in the household, as well the number of people sharing the child's bedroom. After controlling for potential confounders, no evidence of an association between number of persons sharing the child's bedroom and lower respiratory disease was identified when all cases were compared with their controls. However, when two categories of cases were distinguished (infections, asthma) and each category compared separately with their controls, crowding appeared to be associated with a 60% reduction in the incidence of asthma but with 2 1/2-fold increase in the incidence of lower respiratory tract infections (p = 0.001). CONCLUSION: Our findings suggest that household crowding places young children at risk of acute lower respiratory infection but may protect against asthma. This result is consistent with the hygiene hypothesis.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".