Jacqueline F Hayes1,2, Deborah F Tate3, Mark A Espeland4, Jessica Gokee LaRose5, Amy A Gorin6, Cora E Lewis7, Elissa Jelalian1,2, Judy Bahnson3, Rena R Wing1,2. 1. Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA. 2. Weight Control and Diabetes Research Center, The Miriam Hospital, Providence, Rhode Island, USA. 3. Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 4. Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 5. Department of Health Behavior and Policy, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, USA. 6. Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut, USA. 7. Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Abstract
OBJECTIVE: Recovery from weight regain is uncommon during weight loss treatment. This study examined whether participants in a weight gain prevention intervention similarly struggle to recover following weight gains and which factors predict transitions. METHODS: This is a secondary analysis of data from the Study of Novel Approaches to Weight Gain Prevention (SNAP), a randomized controlled trial comparing two weight gain prevention interventions with a control group. Young adults (n = 599; age 18-35 years) were followed over 3 years. Markov models identified transition rates in going above and returning below baseline weight across follow-up. Logistic regressions identified predictors of transitions. RESULTS: At each time point, approximately double the number of participants who transitioned from below to above baseline transitioned from above to below. The magnitude of weight changes from baseline and the number of weight loss strategies used predicted transitions from below to above and above to below baseline weight (with opposite relationships). Infrequent self-weighing and lower dietary restraint predicted transitions below to above baseline weight. Treatment arm, demographics, calorie consumption, and physical activity generally did not predict transitions. CONCLUSIONS: Young adults engaging in weight gain prevention struggle to lose gained weight. Alternative strategies are needed to address weight gains in weight gain prevention interventions.
OBJECTIVE: Recovery from weight regain is uncommon during weight loss treatment. This study examined whether participants in a weight gain prevention intervention similarly struggle to recover following weight gains and which factors predict transitions. METHODS: This is a secondary analysis of data from the Study of Novel Approaches to Weight Gain Prevention (SNAP), a randomized controlled trial comparing two weight gain prevention interventions with a control group. Young adults (n = 599; age 18-35 years) were followed over 3 years. Markov models identified transition rates in going above and returning below baseline weight across follow-up. Logistic regressions identified predictors of transitions. RESULTS: At each time point, approximately double the number of participants who transitioned from below to above baseline transitioned from above to below. The magnitude of weight changes from baseline and the number of weight loss strategies used predicted transitions from below to above and above to below baseline weight (with opposite relationships). Infrequent self-weighing and lower dietary restraint predicted transitions below to above baseline weight. Treatment arm, demographics, calorie consumption, and physical activity generally did not predict transitions. CONCLUSIONS: Young adults engaging in weight gain prevention struggle to lose gained weight. Alternative strategies are needed to address weight gains in weight gain prevention interventions.
Authors: Paul S MacLean; Rena R Wing; Terry Davidson; Leonard Epstein; Bret Goodpaster; Kevin D Hall; Barry E Levin; Michael G Perri; Barbara J Rolls; Michael Rosenbaum; Alexander J Rothman; Donna Ryan Journal: Obesity (Silver Spring) Date: 2014-12-02 Impact factor: 5.002
Authors: Thomas A Wadden; Rebecca H Neiberg; Rena R Wing; Jeanne M Clark; Linda M Delahanty; James O Hill; Jonathan Krakoff; Amy Otto; Donna H Ryan; Mara Z Vitolins Journal: Obesity (Silver Spring) Date: 2011-07-21 Impact factor: 5.002
Authors: Jessica L Unick; Wei Lang; Samantha E Williams; Dale S Bond; Caitlin M Egan; Mark A Espeland; Rena R Wing; Deborah F Tate Journal: Int J Behav Nutr Phys Act Date: 2017-12-04 Impact factor: 6.457