Identification and Prediction of High-Risk Periods for Regain After Weight Loss

 描述(申请人提供)：肥胖在美国仍然是一个严重的公共卫生问题。尽管行为疗法对减肥最初是有效的，但在这些疗法结束后，减肥的长期维持仍然很差。目前改善长期减肥维持的干预措施对体重恢复的影响在统计上是显著的，但只有轻微的影响，而且还没有人能够改变治疗结束后通常观察到的体重恢复的模式。这些结果表明，需要新的方法来保持长期的减肥效果。适应参与者的进展并在参与者体重回升的高风险时提供有针对性的干预成分的治疗方法可能是有益的，并可能有助于适应通常在干预反应中观察到的显著的个体差异。基础性的 然而，开发这些治疗方法所需的证据，包括个人何时恢复体重以及什么因素预测体重恢复，目前尚不清楚。我们建议对一个丰富的纵向数据集进行二次分析，包括从为期3个月的基于互联网的行为减肥干预收集的数据，然后是9个月的非接触性“维持期”。75名参与者(平均年龄=50.8岁，BMI=31.2，女性69%，高加索人84%)提供了每天的体重测量(使用通过蜂窝网络直接将体重发送到我们研究中心的“智能秤”)和每周的行为依从性自我报告(自我监控体重、卡路里摄入量和体力活动)和被假设影响减肥维持的心理因素(例如，压力、饥饿、与目标相关的饮食和活动行为的无聊，相互竞争的优先事项)。在干预期间，参与者的平均体重下降(±SD)为基线体重的-6.26±4.88%，随后3个月至12个月的平均体重恢复为2.98±4.55%(51%的患者在12个月时达到临床截止点，体重显著恢复)。坚持每天和每周收集数据的比例很高。体重数据集目前包括大约23,500个权重值，代表所测量的潜在日期的86%。在52周内，每周自我报告测量的平均遵从率为72%。这些数据提供了一个独特的机会，可以识别一个人的体重轨迹何时从减重转变为恢复(通过“拐点”来识别)，并描述在这些点之前的高风险时期(体重变化的模式、行为坚持和预测这些转折点的前一周的心理因素)，使我们能够开发算法来预测一个人何时接近体重恢复的高风险时间。这些结果具有明确的治疗意义，因为它们将为未来的减肥维持适应性干预提供经验基础，这可能会在个人体重回升的高风险时提供有针对性的行为干预策略。

 DESCRIPTION (provided by applicant): Obesity remains a substantial public health problem in the United States. Despite the initial effectiveness of behavioral treatments for weight loss, long-term maintenance of weight loss after the end of these treatments remains poor. Current interventions to improve long-term weight loss maintenance have statistically significant but only modest impact on weight regain, and none have been able to change the pattern of weight regain typically observed after treatment ends. These results suggest that new approaches to long-term weight loss maintenance are needed. Treatment approaches that adapt to participants' progress and that deliver targeted intervention components at times when participants are at high-risk for weight regain may be beneficial, and may help accommodate the substantial individual variability typically observed in response to intervention. The foundational evidence needed to develop these treatments, however, including when individuals regain weight and what factors predict this regain, is not available. We propose to conduct secondary analyses on a rich longitudinal dataset including data collected from a 3- month Internet-based behavioral weight loss intervention followed by a 9-month no-contact "maintenance" period. Seventy-five participants (mean age=50.8y, BMI=31.2, 69 percent Female, 84 percent Caucasian) provided daily weight measurements (using "smart scales" that sent weights directly to our research center via the cellular network) and weekly self-report of behavioral adherence (self-monitoring of weight, caloric intake, and physical activity) and psychological factors that have been hypothesized to affect weight loss maintenance (e.g., stress, hunger, boredom with goal-related eating and activity behaviors, competing priorities). During intervention, participant lost an average (±SD) of -6.26±4.88 percent of baseline weight, followed by a mean weight regain of 2.98±4.55 percent from Month 3 to 12 (51 percent met clinical cut-offs for significant weight regain at 12 months). Adherence to daily and weekly data collection was high. The weight dataset currently includes approximately 23,500 weight values representing 86 percent of potential dates measured. Average adherence to weekly self-report measures was 72 percent over the 52 weeks. These data provide a unique opportunity to identify when an individual's weight trajectory shifts from weight loss to regain (identified by an "inflection poin") and to characterize the high-risk periods prior to these points (the pattern of weight change, behavioral adherence and psychological factors from the week prior that predict these inflection points), allowing us to develop algorithms to predict when an individual is approaching a high-risk time for weight regain. These results have clear treatment implications as they will provide the empirical foundation for a future adaptive intervention for weight loss maintenance, which could provide targeted, behavioral intervention strategies at times when individuals are at high risk for weight regain.