%0 Journal Article
%T Characterising individual variability in associations between self-monitoring and weight change during and after a behavioral weight management program.
%A Arroyo KM
%A Ross KM
%J Obes Sci Pract
%V 10
%N 1
%D 2024 Feb
%M 38264006
暂无%R 10.1002/osp4.699
%X <B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.<BR><B>UNASSIGNED: </B>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.