The relationship between climate change, globalization and non-communicable diseases in Africa: A systematic review
Bibliographic record
Abstract
Climate change and non-communicable diseases (NCDs) are considered the 21st Century's major health and development challenges. Both pose a disproportionate burden on low- and middle-income countries that are unprepared to cope with their synergistic effects. These two challenges pose risks for achieving many of the sustainable development goals (SDGs) and are both impacted by globalization through different pathways. While there are important insights on how climate change and or globalization impact NCDs in the general literature, comprehensive research that explores the influence of climate change and or globalization on NCDs is limited, particularly in the context of Africa. This review documents the pathways through which climate change and or globalization influence NCDs in Africa. We conducted a comprehensive literature search in eight electronic databases-Web of Science, PubMed, Scopus, Global Health Library, Science Direct, Medline, ProQuest, and Google Scholar. A total of 13864 studies were identified. Studies that were identified from more than one of the databases were automatically removed as duplicates (n = 9649). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 27 studies were eventually included in the final review. We found that the impacts of climate change and or globalization on NCDs act through three potential pathways: reduction in food production and nutrition, urbanization and transformation of food systems. Our review contributes to the existing literature by providing insights into the impact of climate change and or globalization on human health. We believe that our findings will help enlighten policy makers working on these pathways to facilitate the development of effective policy and public health interventions to mitigate the effects of climate change and globalization on the rising burden of NCDs and goal 3 of the SDG, in particular.
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 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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".