Exploiting Social Networks to Mitigate the Obesity Epidemic
Exploiting Social Networks to Mitigate the Obesity Epidemic
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DOI：
10.1038/oby.2008.615
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发表时间：
2009-04-01
期刊：
影响因子：
6.9
通讯作者：
Hill, James O.
中科院分区：
文献类型：
--
作者：
Bahr, David B.;Browning, Raymond C.;Hill, James O.
尽管做出了巨大的努力，肥胖仍然是一个主要的公共卫生问题，令人惊讶的是，预防和治疗肥胖的有效策略很少。我们现在认识到，健康的饮食和活动模式很难在当前的物理环境中维持。最近，有人提出，社会环境也有助于肥胖。因此，使用基于网络的互动模型，我们模拟肥胖如何沿着社会网络传播，并预测大规模体重管理干预措施的有效性。对于各种各样的条件和网络，我们表明具有相似bmi的个体将聚集在一起形成群体，如果不加以控制，当前的社会力量将推动这些群体越来越肥胖。我们的模拟表明，许多传统的体重管理干预措施失败了，因为它们针对的是超重和肥胖个体，而没有考虑他们周围的集群和更广泛的社会网络。与朋友一起节食的流行策略被证明是一种无效的长期减肥策略，而与朋友的朋友一起节食可以通过强迫集群边界的转变而更有效。幸运的是，我们的模拟还表明，针对集群边缘的关系良好和/或体重正常的个体进行干预，可能会迅速阻止肥胖的蔓延。此外，通过改变社会力量和改变一小部分随机分布的肥胖和正常体重个体的行为，高效的网络驱动策略可以扭转当前的趋势，使大部分人口恢复到更健康的体重。
Despite significant efforts, obesity continues to be a major public health problem, and there are surprisingly few effective strategies for its prevention and treatment. We now realize that healthy diet and activity patterns are difficult to maintain in the current physical environment. Recently, it was suggested that the social environment also contributes to obesity. Therefore, using network-based interaction models, we simulate how obesity spreads along social networks and predict the effectiveness of large-scale weight management interventions. For a wide variety of conditions and networks, we show that individuals with similar BMIs will cluster together into groups, and if left unchecked, current social forces will drive these groups toward increasing obesity. Our simulations show that many traditional weight management interventions fail because they target overweight and obese individuals without consideration of their surrounding cluster and wider social network. The popular strategy for dieting with friends is shown to be an ineffective long-term weight loss strategy, whereas dieting with friends of friends can be somewhat more effective by forcing a shift in cluster boundaries. Fortunately, our simulations also show that interventions targeting well-connected and/or normal weight individuals at the edges of a cluster may quickly halt the spread of obesity. Furthermore, by changing social forces and altering the behavior of a small but random assortment of both obese and normal weight individuals, highly effective network-driven strategies can reverse current trends and return large segments of the population to a healthier weight.