Jake Turicchi1, Ruairi O'Driscoll2, Michael Lowe3, Graham Finlayson2, Antonio L Palmeira4, Sofus C Larsen5, Berit L Heitmann5,6,7, James Stubbs2. 1. Faculty of Medicine and Health, School of Psychology, University of Leeds, Leeds, UK. Psjt@leeds.ac.uk. 2. Faculty of Medicine and Health, School of Psychology, University of Leeds, Leeds, UK. 3. Department of Psychology, Drexel University, Philadelphia, PA, USA. 4. Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal. 5. Research Unit for Dietary Studies, The Parker Institute, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark. 6. The Boden Institute of Obesity, Nutrition and Eating Disorder, University of Sydney, Sydney, NSW, Australia. 7. Department of Public Health, Section for General Medicine, University of Copenhagen, Copenhagen, Denmark.
Abstract
BACKGROUND: Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial. OBJECTIVE: To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention. METHODS: The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m2, age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models. RESULTS: Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR2 = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR2 = 1.2%) and 18 months (∆AdjR2 = 1.3%) and by linear methods at 18 months (∆AdjR2 = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR2 = 1.4%) and 18 (∆AdjR2 = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR2 = 2.1%) and 18 (∆AdjR2 = 3.6%) months. CONCLUSION: Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.
BACKGROUND: Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial. OBJECTIVE: To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention. METHODS: The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m2, age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models. RESULTS: Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR2 = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR2 = 1.2%) and 18 months (∆AdjR2 = 1.3%) and by linear methods at 18 months (∆AdjR2 = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR2 = 1.4%) and 18 (∆AdjR2 = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR2 = 2.1%) and 18 (∆AdjR2 = 3.6%) months. CONCLUSION: Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.
Authors: Sofus C Larsen; Jake Turicchi; Gitte L Christensen; Charlotte S Larsen; Niklas R Jørgensen; Marie-Louise K Mikkelsen; Graham Horgan; Ruairi O'Driscoll; Joanna Michalowska; Cristiana Duarte; Sarah E Scott; Inês Santos; Jorge Encantado; Antonio L Palmeira; R James Stubbs; Berit L Heitmann Journal: Front Endocrinol (Lausanne) Date: 2021-09-29 Impact factor: 5.555
Authors: C F Fagundes; L Di Thommazo-Luporini; C L Goulart; D Braatz; A Ditomaso; A Borghi-Silva Journal: Braz J Med Biol Res Date: 2022-03-21 Impact factor: 2.590