PATTERNS OF EATING IN LEAN AND OBESE HUMANS

这项提议的长期目标是应用信息 从控制食物的变量的实验室研究中获得 摄取以治疗肥胖症。我们计划进行四种类型的研究。 1)我们将研究大熊猫进食行为的微观结构 实验室通过肌电记录来自 咬肌。这些研究将展示咀嚼，一种 生物单位的进食行为，决定着食物的摄入量 入口处。我们将评估主要变量的影响，如 食物的适口性取决于咀嚼方式以及如何咀嚼方式 可以通过修改来改变摄取率。2)肌电记录 也将被用来验证口腔内传感器 我们正在开发用于动态监测咀嚼的设备 自然环境。我们将使用动态监测 咀嚼以研究瘦身和肥胖受试者的日常饮食模式 在治疗肥胖症的患者中。对这些餐点的分析 模式将帮助我们理解食物的大小和食物 频率受到控制，将帮助我们识别问题 肥胖患者的饮食模式。3)我们将继续进行实验 研究考察导致差异的变量 瘦和肥胖女性之间的饮食模式 之前观察到的。我们还将测试行为变化 肥胖症治疗项目所倡导的，例如 减缓摄入的速度，实际上有助于人们吃得更少。4) 我们将利用一系列测试来区分进食 监测瘦身者和肥胖者的行为进展 肥胖症治疗前、治疗中和治疗后的患者。我们会 检查我们的行为指标是否与其他 对患者采取的生理和心理措施(如： 静息能量消耗和在Stunkard-Messick上的得分 进食清单)。我们将确定我们的行为是否 测量有助于预测治疗结果以及是否 某些行为变化既可以促进也可以干扰 减肥。我们还将测试减肥是否会导致变化 在行为测量上。考虑到大多数人 人们减肥后会恢复全部或大部分体重，这是极其重要的 通过量身定做优化肥胖治疗的重要性 针对个别患者的减肥方案。我们希望能做到这一点 我们在实验室测试中和在 按目标对日常饮食模式进行动态监测 意思是。我们也希望监测治疗的依从性。 通过动态记录食物摄入量的养生方法。它还可能 将来有可能使用这个系统来发出肥胖信号 当病人吃得太快、太多、太频繁时。

The long-term objective of this proposal is to apply information gained from laboratory studies of the variables that control food intake to the treatment of obesity. We plan four types of studies. 1) We will study the microstructure of eating behavior in the laboratory by electromyographic recording of chews from the masseter muscle. These studies will show how chews, one of the biological units of eating behavior, determine the rate of food intake. We will evaluate the effect of major variables such as palatability of food on chewing patterns and how chewing patterns can be modified to change ingestion rate. 2) The EMG recording of chews will also be also be used to validate an intraoral sensor which we are developing for ambulatory monitoring of chews in the natural environment. We will use ambulatory monitoring of chews to study daily meal patterns in lean and obese subjects and in patients during treatment for obesity. Analysis of these meal patterns will help us to understand how meal size and meal frequency are controlled and will help us to identify problem eating patterns in obese patients. 3) We will continue laboratory studies to examine the variables that contribute to the different eating patterns between lean and obese women that we have observed previously. We will also test whether behavioral changes that are advocated by treatment programs for obesity, such as slowing the rate of ingestion, actually help people to eat less. 4) We will draw on a battery of tests that differentiate the eating behavior of lean and obese people to monitor the progress of patients before, during, and after treatment for obesity. We will examine whether our behavioral measures are related to other physiological and psychological measures on the patients (e.g. resting energy expenditure and scores on the Stunkard-Messick Eating Inventory). We will determine whether our behavioral measures help predict the outcome of treatment and whether certain behavioral changes can either promote or interfere with weight loss. We will also test whether weight loss causes changes in the behavioral measures. Given the fact that most of the people will lose weight regain all or much of it, it is extremely important to optimize the treatment of obesity by tailor-making weight loss regimens to individual patients. This we hope to do on the basis of the data we collect in laboratory tests and in ambulatory monitoring of daily eating patterns by objective means. We also hope to monitor compliance to treatment regimens with ambulatory recording of food intake. It may also be possible in the future to use this system to signal obese patients when they eat too fast, too much, and too often.