Sick Societies: Responding to the Global Challenge of Chronic Disease
Notice bibliographique
Résumé
The first globalization took place between the 16th and the 18th centuries as a result of improved maritime technology.During this period, as European powers colonized the Americas, Africa, and Asia, the diseases of Europe such as syphilis, smallpox, and plague travelled to the colonies, resulting in a massive scale of morbidity and mortality among the native populations.The second major globalization is now underway, due to advances in information technology, and many countries are experiencing an unprecedented rise in chronic diseases.These diseases are not only causing misery and early mortality in the world, but are also bringing an unbearable social and economic burden to societies that are unprepared for this challenge.There is urgency for understanding changes in disease patterns across the globe, and this book is a valuable addition to the knowledge of undergoing changes in morbidity.The change from infectious diseases to chronic diseases in a society has been used as an indicator of development.As societies develop, the incidence of communicable diseases decreases and that of the chronic diseases increases.The book shows that this relationship between infectious diseases and chronic diseases is no longer tenable, and the incidence of chronic diseases is on the rise everywhere.This finding is a major contribution of the book and a timely alert to policymakers.This book consists of eight chapters.Chapter 1 provides a basic understanding of the major chronic diseases that are major killers-cardiovascular diseases, cancers, respiratory diseases, and diabetes.The chapter explains how four major factors-tobacco, unhealthy diet, inactivity, and alcohol-threaten the lives of people around the globe by increasing the incidence of the major chronic diseases.Chapter 2 demonstrates how industry marketing of products related to the risk factors of chronic diseases makes unhealthy choices more economical for the consumer.The strategies followed by the food industry to market products related to the risk factors of chronic diseases include low prices, easier access, and smart marketing techniques.The chapter concludes with three country case studies: (1) Russia's free-market policies cause more than 3 million deaths related to heart disease and alcohol; (2) crashing economies in Japan, Finland, and Cuba force their populaces to return to traditional healthy eating, resulting in the reduction of chronic diseases; and (3) the elimination of traditional living in Nauru by an unsustainable development model.Chapter 3 is devoted to the social and economic costs of chronic diseases.It shows that chronic diseases are costly not only due to healthcare expenditures but also in terms of the labour market: the diseased are more likely to be low-earners or unemployed.The chapter demonstrates how chronic diseases can trap a family in intergenerational poverty.It also makes a case for government intervention and discusses the consequences of intervention.The first part of Chapter 4 deals with the management of chronic diseases, and the second part discusses prevention strategies.It argues that health management systems set up to deal with infectious diseases do not work for the management of chronic diseases.It also outlines barriers to achieving transformation of medical
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,012 |
| Communication savante | 0,013 | 0,008 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».