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Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis.

ABSTRACT: BACKGROUND:Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time. OBJECTIVE:This 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. METHODS:We 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. RESULTS:People 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). CONCLUSIONS:In 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.

SUBMITTER: Frie K

PROVIDER: S-EPMC7109615 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis.

Frie Kerstin K Hartmann-Boyce Jamie J Jebb Susan S Oke Jason J Aveyard Paul P

Journal of medical Internet research 20200317 3

<h4>Background</h4>Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time.<h4>Objective</h4>This 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.<h4>Methods</h4>We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set ...[more]

PMID: 32181749

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Project description:ObjectivesWhile bidirectional relationships exist between body weight and physical activity, direction of causality remains uncertain and previous studies have been limited by self-reported activity or weight and small sample size. We investigated the prospective relationships between weight and physical activity.DesignObservational analysis of data from the Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) study, a double-blinded randomised clinical trial of nateglinide and valsartan, respectively.SettingMultinational study of 9306 participants.ParticipantsParticipants with biochemically confirmed impaired glucose tolerance had annual measurements of both weight and step count using research grade pedometers, worn for 7 days consecutively. Along with randomisation to valsartan or placebo plus nateglinide or placebo, participants took part in a lifestyle modification programme.Outcome measuresLongitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates. Analysis was then repeated with physical activity as response value and weight as predictor value. Only participants with a response value preceded by at least three annual response values were included.ResultsAdequate data were available for 2811 (30%) of NAVIGATOR participants. Previous weight (χ(2)=16.8; p<0.0001), but not change in weight (χ(2)=0.1; p=0.71) was inversely associated with subsequent step count, indicating lower subsequent levels of physical activity in heavier individuals. Change in step count (χ(2)=5.9; p=0.02) but not previous step count (χ(2)=0.9; p=0.34) was inversely associated with subsequent weight. However, in the context of trajectories already established for weight (χ(2) for previous weight measurements 747.3; p<0.0001) and physical activity (χ(2) for previous step count 432.6; p<0.0001), these effects were of limited clinical importance.ConclusionsWhile a prospective bidirectional relationship was observed between weight and physical activity, the magnitude of any effect was very small in the context of natural trajectories already established for these variables.Trial registration numberNCT00097786.

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Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis.

Publications

Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis.

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