Catharine Wang1, Erynn S Gordon2, Tricia Norkunas1, Lisa Wawak2, Ching-Ti Liu3, Michael Winter4, Rachel S Kasper2, Michael F Christman2, Robert C Green5, Deborah J Bowen6. 1. Department of Community Health Sciences, Boston University School of Public Health, Boston, Massachusetts, USA. 2. Coriell Institute for Medical Research, Camden, New Jersey, USA. 3. Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA. 4. Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts, USA. 5. Department of Medicine, Division of Genetics, Brigham and Women's Hospital, Broad Institute and Harvard Medical School, Boston, Massachusetts, USA. 6. Department of Bioethics and Humanities, University of Washington School of Medicine, Seattle, Washington, USA.
Abstract
OBJECTIVE: Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. METHODS: A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. RESULTS: A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.
RCT Entities:
OBJECTIVE: Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. METHODS: A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. RESULTS: A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.
Authors: Noel T Brewer; Alrick S Edwards; Suzanne C O'Neill; Janice P Tzeng; Lisa A Carey; Barbara K Rimer Journal: Breast Cancer Res Treat Date: 2008-09-11 Impact factor: 4.872
Authors: Kurt D Christensen; J Scott Roberts; Peter J Whitehouse; Charmaine D M Royal; Thomas O Obisesan; L Adrienne Cupples; Jacqueline A Vernarelli; Deepak L Bhatt; Erin Linnenbringer; Melissa B Butson; Grace-Ann Fasaye; Wendy R Uhlmann; Susan Hiraki; Na Wang; Robert Cook-Deegan; Robert C Green Journal: Ann Intern Med Date: 2016-01-26 Impact factor: 25.391
Authors: Timothy M Frayling; Nicholas J Timpson; Michael N Weedon; Eleftheria Zeggini; Rachel M Freathy; Cecilia M Lindgren; John R B Perry; Katherine S Elliott; Hana Lango; Nigel W Rayner; Beverley Shields; Lorna W Harries; Jeffrey C Barrett; Sian Ellard; Christopher J Groves; Bridget Knight; Ann-Marie Patch; Andrew R Ness; Shah Ebrahim; Debbie A Lawlor; Susan M Ring; Yoav Ben-Shlomo; Marjo-Riitta Jarvelin; Ulla Sovio; Amanda J Bennett; David Melzer; Luigi Ferrucci; Ruth J F Loos; Inês Barroso; Nicholas J Wareham; Fredrik Karpe; Katharine R Owen; Lon R Cardon; Mark Walker; Graham A Hitman; Colin N A Palmer; Alex S F Doney; Andrew D Morris; George Davey Smith; Andrew T Hattersley; Mark I McCarthy Journal: Science Date: 2007-04-12 Impact factor: 47.728
Authors: Susanne F Meisel; Rebecca J Beeken; Cornelia H M van Jaarsveld; Jane Wardle Journal: Obesity (Silver Spring) Date: 2014-12-17 Impact factor: 5.002
Authors: Lu Qi; Kihwa Kang; Cuilin Zhang; Rob M van Dam; Peter Kraft; David Hunter; Chih-Hao Lee; Frank B Hu Journal: Diabetes Date: 2008-07-22 Impact factor: 9.461
Authors: Gareth J Hollands; David P French; Simon J Griffin; A Toby Prevost; Stephen Sutton; Sarah King; Theresa M Marteau Journal: BMJ Date: 2016-03-15
Authors: Jennie Rose; Cris Glazebrook; Heather Wharrad; A Niroshan Siriwardena; Judy Anne Swift; Dilip Nathan; Stephen Franklin Weng; Pippa Atkinson; Joanne Ablewhite; Fiona McMaster; Vicki Watson; Sarah Anne Redsell Journal: BMC Public Health Date: 2019-03-12 Impact factor: 3.295