Abstract
BackgroundSelf-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time.ObjectiveThis study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring.MethodsWe analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking.ResultsPeople lost weight during continuous tracking (mean −0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=−220 daily steps per time period; 95% CI −320 to −120) and physical activity tracking frequency (beta=−3.4 days per time period; 95% CI −3.8 to −3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=−6.6 days per time period; 95% CI −7.12 to −6.16), whereas daily step count on the day’s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170).ConclusionsIn the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.
Highlights
IntroductionBackground The repeated measurement and tracking of weight over time, referred to as self-monitoring, is a common component of weight loss interventions and is consistently associated with greater weight loss [1]
The repeated measurement and tracking of weight over time, referred to as self-monitoring, is a common component of weight loss interventions and is consistently associated with greater weight loss [1]. The effectiveness of this self-monitoring strategy is attributed to a self-regulation process [2,3], which posits that people who monitor their weight use the information to reflect on the effectiveness of previous actions and plan further weight loss behaviors, engaging in self-experimentation
We only present the results of the best-fitting model, which again was identified through an analysis of variance (ANOVA) and Akaike Information Criterion (AIC) comparison
Summary
Background The repeated measurement and tracking of weight over time, referred to as self-monitoring, is a common component of weight loss interventions and is consistently associated with greater weight loss [1]. Self-monitoring weight has become considerably easier with mobile phone tracking apps and smart scales These digital tracking devices increase adherence, that is, sticking to a regular frequency of monitoring, and improve weight loss outcomes [9,10], possibly because seeing progress increases motivation and keeps users on track with their goals [11]. Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time
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