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Correlates of single morbidities and multimorbidity in children: A cross-sectional study

2025· article· en· W4413801465 on OpenAlexafffundabout
Alex Luther, Danielle Fearon, Ian Colman, Joel A. Dubin, Laura Duncan, Scott T. Leatherdale, Dillon T. Browne, Mark A. Ferro

Bibliographic record

VenueAnnals of Epidemiology · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsUniversity of OttawaWestern UniversityMcMaster UniversityUniversity of Waterloo
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsMedicineCross-sectional studyMultimorbidityComorbidityEnvironmental healthPediatricsPsychiatry

Abstract

fetched live from OpenAlex

This study investigated and compared correlates of multimorbidity with other single morbidity statuses (physical illness only, mental disorder only, neurodevelopmental disorder only) among children in Canada. The epidemiological sample included 33,715 children aged 5-17 years from the Canadian Health Survey of Children and Youth. Classification of children by morbidity status was based on reports from the person most knowledgeable (PMK). Multinomial logistic regression quantified associations between demographic and psychosocial characteristics and morbidity status using odds ratios (ORs) and 95 % confidence intervals (CIs). Female (OR=0.5 [0.5-0.6]) and immigrant children (OR=0.6 [0.5-0.8]) were less likely to report multimorbidity, as well as singular morbidity statuses. Older children (OR=2.3 [2.1-2.6]) were more likely to report multimorbidity. Elevated parent stress (OR:2.1 [1.7-2.5]), worse parent mental health (OR=3.0 [2.4-3.7]), and communities perceived as less safe (OR:1.5 [1.2-2.0]) were associated with higher odds of multimorbidity. Differences in magnitudes of association across morbidity statuses for child age and sex, as well as PMK mental health, and stress levels represent opportunities to identify at-risk children to aid in the prevention of multimorbidity. Strong associations between parent stress and mental health and child morbidity highlight the need to adopt integrated health services that use a family-centred model of care.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.192
GPT teacher head0.454
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2025
Admission routes3
Has abstractyes

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