PDF(Pubmed)
Abstract：
UNASSIGNED: Greater self-monitoring of caloric intake and weight has been associated with success at both initial weight loss and long-term maintenance. Given the existence of wide variability in weight loss outcomes and the key role of self-monitoring within behavioral weight management interventions, this study examined individual variability in associations between self-monitoring and weight change and whether demographic factors could predict who may best benefit from self-monitoring.
UNASSIGNED: Participants were 72 adults with overweight or obesity (mean ± SD, age = 50.6 ± 10.3; body mass index = 31.2 ± 4.5 kg/m2; 71%Female; 83%White) enrolled in a 12-week weight loss program followed by a 40-week observational maintenance period. Participants were encouraged to self-monitor caloric intake and weight daily and to report these data via a study website each week. Multilevel mixed models were used to estimate week-to-week associations between self-monitoring and weight change, by individual and linear regressions and ANOVAs were used to explore demographic differences in these associations.
UNASSIGNED: Most participants (68%) demonstrated statistically significant negative associations between self-monitoring of either caloric intake or weight and weight change. Of these, 76% benefited from self-monitoring both caloric intake and weight, 18% from self-monitoring caloric intake only, and 6% from self-weighing only. The magnitude of associations between self-monitoring and weight change did not significantly differ by age, gender, race/ethnicity, education, or income, all ps > 0.05.
UNASSIGNED: Differences in the effectiveness of self-monitoring for weight loss were not observed by demographic characteristics. Future research should examine if other factors may predict the effectiveness of self-monitoring.
UNASSIGNED: Participants were 72 adults with overweight or obesity (mean ± SD, age = 50.6 ± 10.3; body mass index = 31.2 ± 4.5 kg/m2; 71%Female; 83%White) enrolled in a 12-week weight loss program followed by a 40-week observational maintenance period. Participants were encouraged to self-monitor caloric intake and weight daily and to report these data via a study website each week. Multilevel mixed models were used to estimate week-to-week associations between self-monitoring and weight change, by individual and linear regressions and ANOVAs were used to explore demographic differences in these associations.
UNASSIGNED: Most participants (68%) demonstrated statistically significant negative associations between self-monitoring of either caloric intake or weight and weight change. Of these, 76% benefited from self-monitoring both caloric intake and weight, 18% from self-monitoring caloric intake only, and 6% from self-weighing only. The magnitude of associations between self-monitoring and weight change did not significantly differ by age, gender, race/ethnicity, education, or income, all ps > 0.05.
UNASSIGNED: Differences in the effectiveness of self-monitoring for weight loss were not observed by demographic characteristics. Future research should examine if other factors may predict the effectiveness of self-monitoring.
摘要：
■对热量摄入和体重的更大自我监测与初始体重减轻和长期维持的成功有关。鉴于减肥结果存在广泛的变异性，以及行为体重管理干预措施中自我监测的关键作用，这项研究调查了自我监测和体重变化之间的相关性的个体差异,以及人口统计学因素是否可以预测谁可能从自我监测中获益最好.
■参与者是72名超重或肥胖的成年人（平均值±SD，年龄=50.6±10.3；体重指数=31.2±4.5kg/m2；71％女性；83％白人）参加了12周的减肥计划，然后进行了40周的观察性维持期。鼓励参与者每天自我监测热量摄入和体重，并每周通过研究网站报告这些数据。使用多级混合模型来估计自我监测和体重变化之间的每周关联，通过个体和线性回归和方差分析用于探索这些关联中的人口统计学差异.
■大多数参与者（68％）在热量摄入或体重和体重变化的自我监测之间表现出统计学上显着的负相关。其中,76%的人受益于热量摄入和体重的自我监测，18%仅来自自我监测热量摄入，只有6%来自自重。自我监测和体重变化之间的关联程度在年龄上没有显着差异，性别,种族/民族,教育,或收入，所有PS>0.05。
■根据人口统计学特征未观察到自我监测减肥效果的差异。未来的研究应该检查其他因素是否可以预测自我监控的有效性。
■参与者是72名超重或肥胖的成年人（平均值±SD，年龄=50.6±10.3；体重指数=31.2±4.5kg/m2；71％女性；83％白人）参加了12周的减肥计划，然后进行了40周的观察性维持期。鼓励参与者每天自我监测热量摄入和体重，并每周通过研究网站报告这些数据。使用多级混合模型来估计自我监测和体重变化之间的每周关联，通过个体和线性回归和方差分析用于探索这些关联中的人口统计学差异.
■大多数参与者（68％）在热量摄入或体重和体重变化的自我监测之间表现出统计学上显着的负相关。其中,76%的人受益于热量摄入和体重的自我监测，18%仅来自自我监测热量摄入，只有6%来自自重。自我监测和体重变化之间的关联程度在年龄上没有显着差异，性别,种族/民族,教育,或收入，所有PS>0.05。
■根据人口统计学特征未观察到自我监测减肥效果的差异。未来的研究应该检查其他因素是否可以预测自我监控的有效性。
