Perceived Income Adequacy Versus Household Income as a Measure of Socioeconomic Status in 6 Countries, 2022-2023 International Food Policy Study
Bibliographic record
Abstract
Objectives: Household income is a common indicator of socioeconomic status in population surveys; however, measures such as perceived income adequacy are increasingly used as alternatives. We used a multicountry dataset to explore the utility of perceived income adequacy as compared with household income, focusing on missing data rates, associations with household food security, and responses from young people versus parents. Materials and Methods: We conducted online surveys in 2022-2023 among adults (n = 50 913) and young people (aged 10-17 y; n = 23 013) as part of the International Food Policy Study in Australia, Canada, Chile, Mexico, the United Kingdom, and the United States. We used descriptive analyses to examine missing data for income adequacy and household income adjusted for household size. We used linear regression models to test the association between the income measures, their associations with household food security, and their correspondence in reported income adequacy between young people and parents. Results: The proportion of missing data was greater for household income (5.3%; n = 2688) than for income adequacy (1.0%; n = 488). Income adequacy and household income were positively correlated ( r = 0.25-0.44; P < .001 for all countries). Both measures independently predicted household food security ( P < .001 for all countries), with a stronger association observed for income adequacy. Family income adequacy reported by young people was strongly associated with parental reports ( r = 0.47-0.62; P < .001 for all). Practice Implications: Perceived income adequacy may be preferrable to traditional household income measures for assessing the effect of financial position on health-related outcomes, particularly among young people and older or retired populations, for whom household income may be difficult to report.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".