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Record W2110834746 · doi:10.24095/hpcdp.29.2.03

Health outcomes in low-income children with current asthma in Canada

2009· article· en· W2110834746 on OpenAlexafffundvenueabout
Teresa To, Sharon Dell, Marjan Tassoudji, C. Wang

Bibliographic record

VenueChronic diseases in Canada · 2009
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersHospital for Sick ChildrenUniversity of Toronto
KeywordsMedicineAsthmaLow incomeOddsPediatricsOdds ratioChild healthFamily medicineEnvironmental healthDemographyLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

Data collected from the Canadian National Longitudinal Survey of Children and Youth (NLSCY) in 1994/95 and 1996/97 were used to measure longitudinal health outcomes among children with asthma. Over 10 000 children aged 1 to 11 years with complete data on asthma status in both years were included. Outcomes included hospitalizations and health services use (HSU). Current asthma was defined as children diagnosed with asthma by a physician and who took prescribed inhalants regularly, had wheezing or an attack in the previous year, or had their activities limited by asthma. Children having asthma significantly increased their odds of hospitalization (OR = 2.52; 95% CI: 1.71, 3.70) and health services use (OR = 3.80; 95% CI: 2.69, 5.37). Low-income adequacy (LIA) in 1994/ 95 significantly predicts hospitalization and HSU in 1996/97 (OR = 2.68; 95% CI: 1.29, 5.59 and OR = 0.67; 95% CI: 0.45, 0.99, respectively). Our results confirmed that both having current asthma and living in low-income families had a significant impact on the health status of children in Canada. Programs seeking to decrease the economic burden of pediatric hospitalizations need to focus on asthma and low-income populations.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.329
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2009
Admission routes4
Has abstractyes

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