Notice bibliographique
Résumé
The world's population has doubled over the past 50 years.1 The annual growth rate of 1.3% will result in a further increase to around 9 billion by 2050. Nearly a third of this growth is attributed to three countries in South Asia—namely India (21%), Pakistan (5%), and Bangladesh (4%)—which have historic, cultural, and economic ties with the United Kingdom. According to the International Organisation for Migration, the total number of migrants worldwide increased from 84 million in 1975 to 175 million by 2000,2 and by 2050 it may have reached 230 million. Meanwhile, the global population of elderly people is increasing. By 2050 the overall growth rate of 2.4% per year will result in a threefold increase in the number of people aged 60 or older to 2 billion, with eight out of every 10 elderly people living in developing countries.3 Large demographic changes will occur in Europe.4 The current population of the European Union of 452 million will shrink to around 400 million despite its current inward migration rate. Populations in some European countries will decrease by a quarter while becoming considerably older. By 2050 the proportion of elderly people is expected to have risen from 20% to 37%, with a big impact on Europe's economies and social infrastructures. These trends in international migration and population ageing will probably increase the influx of South Asians to the United Kingdom. Many will bring elderly relatives with them given that, in Asian countries, 70% of elderly people live with their children. In the UK over the past decade the ethnic minority population has grown by 53% and now comprises 7.9% of the total population.5 South Asians, the largest ethnic minority group, now number two and a half million people and account for 50% of ethnic minority groups, with another 15% of the ethnic population described as of mixed race. Although increasing immigration may provide a welcome solution to such shrinking and ageing among Europe's populations6 it will almost certainly have a substantial impact on health services such as the NHS, because South Asians have higher rates of coronary heart disease, diabetes, hypertension, stroke, hip fractures, and renal failure.7,8 So what needs to be done? The European Union must encourage managed migration. The union needs cohesive policies for immigration and health which can respond properly to the medical needs of the migrant population. First, though, policy makers should assess the likely effects of further migration on health services before enforcing big changes in the numbers of migrants. Ill conceived and short sighted attempts to develop services could prove to be a disastrous knee jerk reaction. The UK currently allows in 150 000 migrants a year. Those in charge of developing and modernising the NHS should take account of the rapidly changing demography of the nation, understand better the needs of ethnic minority populations, and target health promotion at people in those populations who are at high risk of disease. Basic and postgraduate training for doctors, nurses, and professions allied to medicine must include learning about ethnic diversity and transcultural medicine, while academics must more widely debate and develop capacity for clinical research in transcultural medicine.9 Meanwhile, royal colleges, specialist societies, voluntary organisations, patients' groups, and community leaders could do much more to promote and share expertise on the health of people from ethnic minorities. Lastly, exchange programmes for health professionals in the UK and less developed countries would allow dissemination and adaptation of the UK's substantial knowledge in managing diseases of old age and chronic diseases, as well as of health service finance and management.
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 | 0,002 | 0,007 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».