117 Using composite area-level measures as a proxy for self-report family income
Notice bibliographique
Résumé
Abstract Background Socioeconomic status (SES) is a well-established social determinant of child health. When reliable self-report family income is unavailable, area-level measures, such as median neighbourhood income, are commonly used as a proxy. However, median neighbourhood income is not a good proxy for self-report family income. Newer area-level measures, such as the Neighbourhood Equity Score (NES) and the Child and Family Inequities Score (CFIS) are composite scores comprised of indicators of well-being such as income, parental education and physical surroundings. Objectives The primary objective was to evaluate the agreement between self-report family income and three area-level measures: median neighbourhood income, NES, and CFIS. The secondary objective was to examine the association between self-report family income, NES, and CFIS with two health indicators associated with SES: overweight/obesity (BMI z-score>1) and short breastfeeding duration (<6 months). Design/Methods We conducted a cross-sectional study using data from a healthy urban Canadian cohort of young children (0-5 years) attending a scheduled health supervision visit in primary care. Parents completed a questionnaire including family income, postal code and breastfeeding duration. Research assistants measured height and weight (to calculate body mass index). Postal code was used to determine each area-level measure. Agreement between self-report family income and area-level measures was evaluated using kappa coefficients. The percentage of families accurately classified by area-level measures compared with self-report family income was calculated. Multivariable logistic regression was used to evaluate the association between self-report family income, NES, and CFIS (quintiles) with the two health indicators (present/absent). Results 5149 children were included (mean age 21 months). Agreement between self-report family income and both NES and CFIS was ‘fair’ (weighted k=0.29 for both), and agreement with median neighbourhood income was ‘poor’ (weighted k=0.09). Accurate classification between self-report family income and the three measures were: median neighbourhood income (5.6%), NES (32.2%), CFIS (32.4%). For children in the lowest vs. highest quintile, the odds (95% CI) of overweight/obesity were: self-report family income OR=2.75 (1.60-4.72), NES OR=2.02 (1.23-3.30), CFIS OR=2.04 (1.25-3.33); and having short breastfeeding duration: self-report family income OR=1.61 (1.32-1.97), NES OR=1.84 (1.50-2.25), CFIS OR=1.84 (1.46-2.31). Conclusion Agreement and accurate classification between self-report family income was strongest for composite area-level measures (NES and CFIS), compared with median neighbourhood income. Both self-report family income and composite area-level measures supported the same conclusion that lower SES was associated with poorer health outcomes. These newer measures may be more appropriate than median neighbourhood income when self-report family income is unavailable.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».