4.8 Article

Profits and pandemics: prevention of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries

期刊

LANCET
卷 381, 期 9867, 页码 670-679

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/S0140-6736(12)62089-3

关键词

-

资金

  1. Abbott
  2. Amgen
  3. AstraZeneca
  4. GeorgeClinical
  5. GlaxoSmithKline
  6. Novartis
  7. PepsiCo
  8. Pfizer
  9. Pharmacy Guild of Australia
  10. Roche
  11. Sanofi-Aventis
  12. Servier
  13. Tanabe
  14. Australian Food and Grocery Council
  15. Bupa Australia
  16. Johnson and Johnson
  17. Merck Schering Plough
  18. United Healthcare Group
  19. Australian Research Council
  20. Medical Research Council [MR/K023195/1, MR/K023195/1B] Funding Source: researchfish

向作者/读者索取更多资源

The 2011 UN high-level meeting on non-communicable diseases (NCDs) called for multisectoral action including with the private sector and industry. However, through the sale and promotion of tobacco, alcohol, and ultra-processed food and drink (unhealthy commodities), transnational corporations are major drivers of global epidemics of NCDs. What role then should these industries have in NCD prevention and control? We emphasise the rise in sales of these unhealthy commodities in low-income and middle-income countries, and consider the common strategies that the transnational corporations use to undermine NCD prevention and control. We assess the effectiveness of self-regulation, public-private partnerships, and public regulation models of interaction with these industries and conclude that unhealthy commodity industries should have no role in the formation of national or international NCD policy. Despite the common reliance on industry self-regulation and public-private partnerships, there is no evidence of their effectiveness or safety. Public regulation and market intervention are the only evidence-based mechanisms to prevent harm caused by the unhealthy commodity industries.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据