Review of the evidence for oceans and human health relationships in Europe: A systematic map
Bibliographic record
Abstract
BACKGROUND: Globally, there is increasing scientific evidence of critical links between the oceans and human health, with research into issues such as pollution, harmful algal blooms and nutritional contributions. However, Oceans and Human Health (OHH) remains an emerging discipline. As such these links are poorly recognized in policy efforts such as the Sustainable Development Goals, with OHH not included in either marine (SDG14) or health (SDG3) goals. This is arguably short-sighted given recent development strategies such as the EU Blue Growth Agenda. OBJECTIVES: In this systematic map we aim to build on recent efforts to enhance OHH in Europe by setting a baseline of existing evidence, asking: What links have been researched between marine environments and the positive and negative impacts to human health and wellbeing? METHODS: We searched eight bibliographic databases and queried 57 organizations identified through stakeholder consultation. Results include primary research and systematic reviews which were screened double blind against pre-defined inclusion criteria as per a published protocol. Studies were limited to Europe, US, Australia, New Zealand and Canada. Data was extracted according to a stakeholder-defined code book. A narrative synthesis explores the current evidence for relationships between marine exposures and human health outcomes, trends in knowledge gaps and change over time in the OHH research landscape. The resulting database is available on the website of the Seas, Oceans and Public Health in Europe website (https://sophie2020.eu/). RESULTS: A total of 1,542 unique articles were included in the database, including those examined within 56 systematic reviews. Research was dominated by a US focus representing 50.1% of articles. A high number of articles were found to link: marine biotechnology and cardiovascular or immune conditions, consumption of seafood and cardiovascular health, chemical pollution and neurological conditions, microbial pollution and gastrointestinal or respiratory health, and oil industry occupations with mental health. A lack of evidence relates to direct impacts of plastic pollution and work within a number of industries identified as relevant by stakeholders. Research over time is dominated by marine biotechnology, though this is narrow in focus. Pollution, food and disease/injury research follow similar trajectories. Wellbeing and climate change have emerged more recently as key topics but lag behind other categories in volume of evidence. CONCLUSIONS: The evidence base for OHH of relevance to European policy is growing but remains patchy and poorly co-ordinated. Considerable scope for future evidence synthesis exists to better inform policy-makers, though reviews need to better incorporate complex exposures. Priorities for future research include: proactive assessments of chemical pollutants, measurable impacts arising from climate change, effects of emerging marine industries, and regional and global assessments for OHH interactions. Understanding of synergistic effects across multiple exposures and outcomes using systems approaches is recommended to guide policies within the Blue Growth Strategy. Co-ordination of research across Europe and dedicated centres of research would be effective first steps.
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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 | 0.023 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.043 | 0.050 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".