C Bandín1, A Martinez-Nicolas1, J M Ordovás2, J A Madrid1, M Garaulet1. 1. Faculty of Biology, Department of Physiology, University of Murcia, Murcia, Spain. 2. 1] Nutrition and Genomics Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA [2] Department of Epidemiology, Centro Nacional Investigaciones Cardiovasculares, Madrid, Spain [3] Madrid Institute for Advanced Studies in Food (IMDEA-FOOD), Madrid, Spain.
Abstract
OBJECTIVES: Some of the major challenges associated with successful dietary weight management include the identification of individuals not responsive to specific interventions. The aim was to investigate the potential relationship between weight loss and circadian rhythmicity, using wrist temperature and actimetry measurements, in women undergoing a weight-loss program, in order to assess whether circadian rhythmicity could be a marker of weight-loss effectiveness. METHODS: Participants were 85 overweight and obese women (body mass index, BMI: 30.24±4.95 kg m(-2)) subjected to a weight-reduction program. Efficacy of the treatment was defined as total weight loss, percentage of initial weight and weekly weight loss rates. Circadian rhythmicity in wrist temperature motor activity and position were analyzed using different sensors. RESULTS: Lower weight loss was related with a more flattened pattern measured as amplitude from cosinor (r=0.235, P=0.032), a higher fragmentation of rhythms determined by higher intradaily variability (IV) (r=-0.339, P=0.002), and an impaired wrist temperature circadian rhythm determined by the means of Circadian Function Index (r=0.228, P=0.038). Further analyses showed that low responders displayed lower amplitude (0.71±0.36 versus 1.24±0.62, P=0.036) and higher fragmentation of the circadian rhythm (0.24±0.11 versus 0.15±0.07, P=0.043) than high responders. Whereas we did not find significant differences in total activity rates between high responders and low responders, we found significant differences for the mean values of body position for high responders (39.12±3.79°) as compared with low responder women (35.31±2.53°, P=0.01). CONCLUSIONS: Circadian rhythms at the beginning of the treatment are good predictors of future weight loss. Further treatment should consider chronobiological aspects to diagnose obesity and effectiveness of treatments.
OBJECTIVES: Some of the major challenges associated with successful dietary weight management include the identification of individuals not responsive to specific interventions. The aim was to investigate the potential relationship between weight loss and circadian rhythmicity, using wrist temperature and actimetry measurements, in women undergoing a weight-loss program, in order to assess whether circadian rhythmicity could be a marker of weight-loss effectiveness. METHODS:Participants were 85 overweight and obesewomen (body mass index, BMI: 30.24±4.95 kg m(-2)) subjected to a weight-reduction program. Efficacy of the treatment was defined as total weight loss, percentage of initial weight and weekly weight loss rates. Circadian rhythmicity in wrist temperature motor activity and position were analyzed using different sensors. RESULTS: Lower weight loss was related with a more flattened pattern measured as amplitude from cosinor (r=0.235, P=0.032), a higher fragmentation of rhythms determined by higher intradaily variability (IV) (r=-0.339, P=0.002), and an impaired wrist temperature circadian rhythm determined by the means of Circadian Function Index (r=0.228, P=0.038). Further analyses showed that low responders displayed lower amplitude (0.71±0.36 versus 1.24±0.62, P=0.036) and higher fragmentation of the circadian rhythm (0.24±0.11 versus 0.15±0.07, P=0.043) than high responders. Whereas we did not find significant differences in total activity rates between high responders and low responders, we found significant differences for the mean values of body position for high responders (39.12±3.79°) as compared with low responder women (35.31±2.53°, P=0.01). CONCLUSIONS: Circadian rhythms at the beginning of the treatment are good predictors of future weight loss. Further treatment should consider chronobiological aspects to diagnose obesity and effectiveness of treatments.
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