Residential movement patterns of families of young children with chronic conditions in Ontario, Canada: a population-based cohort study
Bibliographic record
Abstract
INTRODUCTION: Care giving for children with chronic diseases can lead to financial strain and compromised family well being. Little is known about whether these stresses lead to changes in residential movement patterns as they relate to income adequacy and proximity to care. METHODS: We compared the residential movement patterns and associated changes in neighbourhood income of children with mild to severe chronic diseases compared with those that are healthy. A cohort of infants born from 2002-2007 in Ontario, Canada was followed for 5 years and divided into those with single- or multiple- body system complex chronic conditions (CCCs); low birth weight (LBW); asthma/recurrent wheeze (A/RW) and the control group of otherwise healthy children. RESULTS: Of 598,716 children studied, 15,207 had a single CCC, 3,600 multiple CCCs, 33,206 LBW, 57,137 A/RW and 489,566 were healthy. Lowest income quintile children were most likely to move residence. Compared with healthy controls, chronic disease cohorts, apart from those with asthma, were more likely to be born in the lowest income quintile neighbourhood and to move. Among children who moved, all chronic disease cohorts were significantly more likely to move to a low income quintile neighborhood (adjusted odds ratios for all chronic disease cohorts of 1.1-1.2). There were no differences across cohorts in residential movement close to a children's hospital. CONCLUSIONS: Young children with chronic conditions, particularly those born in low income neighbourhoods, are more likely to move residence than other healthy young children. However, it does not seem that proximity to specialized care is driving this movement. Further research is required to determine if these movement patterns impact the ability of children with chronic conditions to secure health services.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".