Literacy and self-rated health: Analysis of the Longitudinal and International Study of Adults (LISA)
Bibliographic record
Abstract
The relationship between education and health is well-established. The empirical literature finds that individuals with higher levels of education experience lower risks of poor health outcomes compared to individuals with less education. Outstanding to this literature is the examination of a dimension of education - literacy - and its association with health. The objective of this study was to examine the relationship between literacy (reading, numeracy) and health (self-reported health). We use data from the 2012 wave of the Canadian Longitudinal International Survey of Adults (LISA). The LISA includes rich information on health, broader sociodemographic characteristics (income, age, sex, etc.) as well as information on literacy skills from the Program for International Assessment of Adult Competencies (PIAAC). Using logistic regression, we first reaffirm the association between education and self-reported health. We then find that after controlling for measures of literacy, understood as proficiency in reading and numeracy, the magnitude of effect of education on health is reduced. Skills in literacy reduce the risk of reporting poor health, but only for the older subset of respondents (ages 40-65). Our results suggest that literacy should not be understated in empirical research on education and health, and in fact serve to sharpen our understanding of how education impacts health by drawing attention to indirect pathways.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".