Global analysis of climate adaptation policies for promoting environmentally sustainable, decarbonised health systems: a scoping review
Bibliographic record
Abstract
Background: Climate change threatens human health and strains health systems, which must cut GHG emissions and boost resilience. While progress occurs in HICs, LMICs lack similar initiatives, limiting comparative analysis. There is little empirical evidence on climate adaptation (CA) policies and enablers, especially in LMICs. This thesis aims to address this gap by reviewing literature on global CA policies and enablers for sustainable, decarbonised health systems. Method: A scoping review of peer-reviewed and grey literature from 2005 to 2025 was conducted, following the guidelines of Arksey and O’Malley, Levac et al., and JBI. Six databases (PubMed, Web of Science, Scopus, JBI database, Overton, and WHO Global Index Medicus) were searched with relevant keywords. A deductive framework analysis mapped CA policies against the WHO’s Operational Framework and their enablers to the Ottawa Charter for Health Promotion. The protocol was registered on Open Science Framework. PRISMA-ScR and scoping review guidelines were adhered to. Results: Out of 2,632 studies, 26 studies met the inclusion criteria. 80% were published between 2023 and 2025, 42% from HICs, and 39% were original research. All 26 studies discussed ‘leadership and governance’, the most addressed component. Only 12% discussed ‘managing environmental determinants of health’. The most common enabler addressed, related to the Ottawa Charter, was ‘building healthy public policy’, and the least was ‘strengthening community action’. No studies from Nigeria or on the evaluation or implementation costs of CA policies. Conclusion: This review highlights gaps in CA policy evidence for sustainable, decarbonised health systems, stressing the need for more research across geopolitical contexts, sharing lessons, and real-world experiences. This will help shift from fragmented efforts to comprehensive strategies that build resilience and support decarbonisation and transformative health system change. Keywords – , resilience, health systems, health promotion, net zero, Nigeria, Ottawa charter, Building blocks
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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 | 0.027 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".