117 Using composite area-level measures as a proxy for self-report family income
Bibliographic record
Abstract
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.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".