Climate change and healthy ageing: An assessment of the impact of climate hazards on older people
Bibliographic record
Abstract
Background: Climate change not only directly impacts older people's longevity but also healthy ageing, which is the process of maintaining physical and mental capacities while optimising functional abilities. The urgency to address both population ageing and climate change necessitates a rethink and assessment of the impact of climate change on older people. This includes identifying what can be done to anticipate, mitigate and adapt to climate change and engage older persons. Methods: A review of climate change and healthy ageing forms the basis of evidence in this report. We developed a comprehensive search to assess current literature, combining terms related to ageing and climate change across four major data sets and assessing articles published up to the end of 2021. Results: We summarised the current and future impact of climate change on older people and developed a framework identifying climate change impacts on older persons, recognising social and environmental determinants of healthy ageing. Major hazards and some key exposure pathways include extreme temperatures, wildfire, drought, flooding, storm and sea level rise, air quality, climate-sensitive infectious diseases, food and water insecurities, health and social care system displacement, migration, and relocation. Strategies to address climate change require interventions to improve systems and infrastructure to reduce vulnerability and increase resilience. As a heterogeneous group, older people's perceptions of climate change should be integrated into climate activism. Increasing climate change literacy among older people and enabling them to promote intergenerational dialogue will drive the development and implementation of equitable solutions. Pathways may operate via direct or indirect exposures, requiring longitudinal studies that enable assessment of exposures and outcomes at multiple time points, and analyses of cumulative impacts of hazards across the life course. Conclusions: The lack of systematic reviews and primary research on the impact of most climate hazards, except for heat, on older people is apparent. Future research should include outcomes beyond mortality and morbidity and assess how older people interact with their environment by focusing on their capacities and optimising abilities for being and doing what they value.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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 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".