The association between housing cost burden and avoidable mortality in wealthy countries: cross-national analysis of social and housing policies, 2000-2017
Bibliographic record
Abstract
BACKGROUND: It has been shown that the high cost of housing can be detrimental to individual health. However, it is unknown (1) whether high housing costs pose a threat to population health and (2) whether and how social policies moderate the link between housing cost burden and mortality. This study aims to reduce these knowledge gaps. METHODS: Country-level panel data from Organisation for Economic Co-operation and Development (OECD) countries are used. Housing cost to income ratio and age-standardised mortality were obtained from the OECD database. Fixed effects models were conducted to estimate the extent to which the housing cost to income ratio was associated with preventable mortality, treatable mortality, and suicides. In order to assess the moderating effects of social and housing policies, different types of social spending per capita as well as housing policies were taken into account. RESULTS: Housing cost to income ratio was significantly associated with preventable mortality, treatable mortality, and suicide during the post-global financial crisis (2009-2017) but not during the pre-global financial crisis (2000-2008). Social spending on pensions and unemployment benefits decreased the levels of mortality rate associated with housing cost burden. In countries with higher levels of social housing stock, the link between housing cost burden and mortality was attenuated. Similar patterns were examined for countries with rent control. CONCLUSION: Our findings suggest that housing cost burden can be related to population health. Future studies should examine the role of protective measures that alleviate health problems caused by housing cost burden.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".