APP-ME: Addressing Place & People MicroEnvironments in weight loss disparities

 描述(由申请人提供)：多点随机对照试验表明，体重每减轻2磅，3年内患高血压的风险降低20%，3年内患2型糖尿病的风险降低32%。这相当于与戒烟相关的中风风险降低。不幸的是，在可追溯到1990年的干预试验中，黑人女性的体重减轻幅度比白人女性少50%。因此，生活方式减肥干预实际上可能会增加发病率的种族差异；黑人女性的所有5个主要死亡原因都与肥胖有关。城市贫民的肥胖率非常高，对城市贫民的肥胖症研究是国际移民组织和国土安全部的优先事项。从2006年开始，我们与美国第三大安全网健康系统合作，在其8个联邦合格健康中心实施生活方式减肥干预。与白人女性相比，这项计划也使黑人女性的体重减轻了50%。我们还进行了一项持续的减肥RCT，测试将干预措施提供给城市贫困家庭的影响。目前还没有结果，但它也是一种以人为中心的生活方式干预。为了改善减肥效果，我们成功地试验了一种新的方法来评估与体重相关行为(包括瞬间的社会互动和情绪)相一致的微环境。文献非常强调社会微环境在肥胖和减肥差异中的作用。个人往往没有意识到微环境对他们行为的影响。例如，实验表明，当我们和别人一起吃饭时，我们会多摄入70%的卡路里，而我们在很大程度上并没有意识到自己已经做到了这一点。此前的研究表明，黑人女性的社交网络对减肥的支持程度低于白人女性。这样的社交网络可能会导致更多的肥胖、食物、饮食、久坐活动，并接受这些。事实上，最近一项长达一年的研究对第一年宿舍居民的社交互动进行了客观评估，发现与其他体重增加的人互动的次数可以解释一年体重增加的三分之一。在这项拟议的研究中，我们试图评估、比较和测试社会和物理微环境以及情绪对300名城市贫困黑人和白人妇女不活动和饮食的影响。我们的目标1包括通过GPS、Bite计数器和加速计进行新颖的数据收集，以获得位置和行为数据，以及生态瞬时评估和一天重建方法的混合，以获得社交和情感数据。在我们的Aim 2随机试验中，这些数据被用来检验关于微环境和体重变化的假设。每个人的目标1数据被用来测试在每个女性的数据表明她容易受到饮食或久坐活动影响的时间和地点，与健康相关的词语和图像形式的信息是否会影响体重变化。这项工作将为下一代减肥计划提供信息，并促进我们对健康中的自动行为和健康差异的理解。

 DESCRIPTION (provided by applicant): Multi-site RCTs have shown that every 2lbs of weight loss is associated with a 20% reduction in the 3yr risk of hypertension and a 32% reduction in the 3yr risk of type 2 diabetes. This is equivalent to the stroke risk reduction associated with smoking cessation. Unfortunately, in intervention trials dating back to 1990, black women have experienced 50% less weight loss than white women. Thus, lifestyle weight loss interventions may actually increase racial disparities in morbidity; all 5 leading causes of death among black women are obesity-related. Obesity prevalence among the urban poor is very high and obesity research in the urban poor is an IOM and DHHS priority. Starting in 2006, we worked with the 3rd largest safety-net health system in the U.S. to implement a lifestyle weight loss intervention that operates in its 8 Federally Qualified Health Centers. This program too has resulted in 50% less weight loss in black relative to white women. We also have an ongoing weight loss RCT testing the impact of delivering the intervention into the homes of the urban poor. No outcomes are available yet but it too is a person-centric lifestyle intervention. With a goal of improving weight loss outcomes, we successfully piloted a novel approach to assessing micro- environments that coincide with weight-related behaviors including momentary social interactions and emotions. Literature places a very strong emphasis on the role of social micro-environments in obesity and weight loss disparities. Individuals are often unaware of the influence of micro-environments on their behavior. For example, experiments have shown that we consume up to 70% more calories when eating with others and that we are largely unaware we have done so. Previous research suggests social networks of black women are less supportive of weight loss than are those of white women. Such social networks may lead to more exposures to obesity, food, eating, sedentary activities, and acceptance of these. In fact, a recent year-long study that captured objective assessments of social interactions among first year dormitory residents found the number of interactions with weight gaining others accounted for 1/3rd of the variance in one-year weight gain. We seek in the proposed study to assess, compare, and test the influence of social and physical micro- environments and emotions on inactivity and eating in 300 urban poor black and white women. Our Aim 1 involves novel data collection via GPS, Bite Counters, and accelerometers to obtain location and behavior data and a hybrid of ecological momentary assessment and the day reconstruction method to obtain social interaction and emotion data. In our Aim 2 randomized trial, these data are used to test hypotheses about micro-environments and weight change. Each individual's Aim 1 data are used to test whether messages in the form of health-related words and images at the time and location each woman's data indicate she is vulnerable to eating or sedentary activity affect weight change. This work will inform next-generation weight loss programs and advance our understanding of automatic behaviors in health and health disparities.