Cold homes and mental health harm: Evidence from the UK Household Longitudinal Study
Bibliographic record
Abstract
Cold homes are associated with a range of serious health conditions as well as excess winter mortality. Despite a comparatively mild climate cold homes are a significant problem in the UK, with a recent estimate finding that over one-quarter of low-income households had been unable to adequately heat their home in winter 2022. The magnitude of cold housing in a country that benefits from a mild climate indicates indifference towards, or acceptance of, a significant minority of people living in inadequate conditions on the part of policy makers. Cold homes are therefore a source of social harm. Recent changes to the household energy price cap, the rising cost of living, the ongoing effects of the benefit cap, and below inflation uprating to social security benefits is likely to greatly exacerbate this issue. In this research we use data from the UK Household Longitudinal Study to explore whether living in a cold home causes mental health harm. We control for mental distress and housing temperature on entry to the survey in order to account for the potentially bi-directional relationship. Multilevel discrete-time event history models show that the transition into living in a home that is not suitably warm is associated with nearly double the odds of experiencing severe mental distress for those who had no mental distress at the beginning of the survey; and over three times the odds of severe mental distress for those previously on the borderline of severe mental distress. These results show the significant costs of failing to ensure that people are able to live in homes in which they are able to live comfortably by even the most basic standards. These costs will be felt not just individually, but also more broadly in terms of increased health spending and reduced working.
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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 | 0.003 | 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 | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".