Review of the evidence for oceans and human health relationships in Europe: A systematic map
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».