Family income and health in Canada: a longitudinal study of stability and change
Bibliographic record
Abstract
BACKGROUND: Extensive research has shown strong associations between income and health. However, the health effects of income dynamics over time are less known. We investigated how stability, volatility and trajectory in family incomes from 2002 to 2011 predicted (1) fair/poor self-rated health and (2) the presence of a longstanding illness or health problem in 2012. METHODS: The data came from the 2012 wave of the Longitudinal and International Study of Adults linked to annual family income data for 2002 to 2011 from the Canada Revenue Agency. We executed a series of binary logistic regressions to examine associations between health and average family income over the decade (Model 1), number of years in the bottom quartile (Model 2) and top quartile (Model 3) of family incomes, standard deviation of family incomes (Model 4), absolute difference between family income at the end and start of the period (Model 5), and number of years in which inflation-adjusted family income went down by more than 1% (Model 6) and up by more than 1% (Model 7) from 1 year to the next. The analyses were conducted separately for women and men. RESULTS: Average family income over the decade was strongly associated with both self-rated health and the presence of a longstanding illness or health problem. More years spent in the bottom quartile of family incomes corresponded to elevated odds of fair/poor self-rated health and the presence of a longstanding illness or health problem. Steady decreases in family income over the decade corresponded to elevated odds of fair/poor self-rated health for men and more years spent in the top quartile of family incomes over the decade corresponded to elevated odds of fair/poor self-rated health for women. CONCLUSION: Previous studies of the association between family income and health in Canada may have overlooked important issues pertaining to family income stability and change that are impactful for health.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".