Skin morbidity in Indigenous children in relation to housing conditions in remote communities in Northwestern Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Elevated rates of eczema and skin infections in Canadian First Nation (FN) communities are of concern to families, community leaders and healthcare professionals. AIM: To determine whether skin morbidity was associated with indoor environmental quality factors in Canadian FN children living in remote communities. METHODS: We quantified indoor environmental quality (IEQ) in the homes of FN children aged < 4 years of age living in four remote communities in the Sioux Lookout region of Northwestern Ontario, Canada. We conducted a quantitative housing inspection, including measuring surface area of mould (SAM), and monitored air quality for 5 days in each home, including carbon dioxide and relative humidity and quantified endotoxin in settled floor dust. We reviewed the medical charts of participating children for skin conditions and administered a health questionnaire. Relationships between IEQ and skin infections or eczema were evaluated using multivariable regression. RESULTS: In total, 98 children were included in the descriptive analyses, of whom 86 had complete data and were evaluated in multivariate analyses for dermatological outcomes (mean age 1.6 years). Of these 86 children, 55% had made ≥ 1 visits to the local health centre (HC) for skin and soft tissue infections and 25.5% for eczema. Unexpectedly, annualized eczema visits were inversely associated with SAM (RR = 0.14; 95% CI 0.01-0.93). There was a trend suggesting an inverse relationship between endotoxin and HC encounters for eczema and skin and soft tissue infections. CONCLUSION: Skin infections were common in this population of FN children. IEQ did not appear to be associated with skin infections or eczema. Mould exposure appeared to be inversely associated with HC encounters for eczema, possibly related to complex microorganism-host interactions occurring early in life.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".