Kaitlin H Wade1,2, Laura Clifford3, Andrew J Simpkin1,4, Rhona Beynon1,2, Laura Birch5, Kate Northstone2, Sarah Matthews2, George Davey Smith1,2, Julian Hamilton-Shield5, Nicholas J Timpson1,2. 1. Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK. 2. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK. 3. Department of Paediatric Respiratory Medicine, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK. 4. School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, H91 H3CY, Ireland. 5. NIHR Bristol Biomedical Research Centre Nutrition Theme, University of Bristol, University Hospitals Bristol Education & Research Centre, Bristol, BS1 3NU, UK.
Abstract
Background: Effective measurement and adaption of eating behaviours (e.g., eating speed) may improve weight loss and weight over time. We assessed whether the Mandometer, a portable weighing scale connected to a computer that generates a graph of food removal rate from the plate to which it is connected, together with photo-imaging of food, might prove a less intensive and more economical approach to measuring eating behaviours at large scale. Methods: We deployed the Mandometer in the home environment to measure main meals over three days of 95 21-year-old participants of the Avon Longitudinal Study of Parents and Children. We used multi-level models to describe food weight and eating speed and, as exemplar analyses, examined the relationship of eating behaviours with body mass index (BMI), dietary composition (fat content) and genotypic variation (the FTO rs9939609 variant). Using this pilot data, we calculated the sample size required to detect differences in food weight and eating speed between groups of an exposure variable. Results: All participants were able to use the Mandometer effectively after brief training. In exemplar analyses, evidence suggested that obese participants consumed more food than those of "normal" weight (i.e., BMI 19 to <25 kg/m 2) and that A/A FTO homozygotes (an indicator of higher weight) ate at a faster rate compared to T/T homozygotes. There was also some evidence that those with a high-fat diet consumed less food than those with a low-fat diet, but little evidence that individuals with medium- or high-fat diets ate faster. Conclusions: We demonstrated the potential for assessing eating weight and speed in a short-term home setting and combining this with information in a research setting. This study may offer the opportunity to design interventions tailored for at-risk eating behaviours, offering advantages over the "one size fits all" approach of current failing obesity interventions. Copyright:
Background: Effective measurement and adaption of eating behaviours (e.g., eating speed) may improve weight loss and weight over time. We assessed whether the Mandometer, a portable weighing scale connected to a computer that generates a graph of food removal rate from the plate to which it is connected, together with photo-imaging of food, might prove a less intensive and more economical approach to measuring eating behaviours at large scale. Methods: We deployed the Mandometer in the home environment to measure main meals over three days of 95 21-year-old participants of the Avon Longitudinal Study of Parents and Children. We used multi-level models to describe food weight and eating speed and, as exemplar analyses, examined the relationship of eating behaviours with body mass index (BMI), dietary composition (fat content) and genotypic variation (the FTO rs9939609 variant). Using this pilot data, we calculated the sample size required to detect differences in food weight and eating speed between groups of an exposure variable. Results: All participants were able to use the Mandometer effectively after brief training. In exemplar analyses, evidence suggested that obese participants consumed more food than those of "normal" weight (i.e., BMI 19 to <25 kg/m 2) and that A/A FTO homozygotes (an indicator of higher weight) ate at a faster rate compared to T/T homozygotes. There was also some evidence that those with a high-fat diet consumed less food than those with a low-fat diet, but little evidence that individuals with medium- or high-fat diets ate faster. Conclusions: We demonstrated the potential for assessing eating weight and speed in a short-term home setting and combining this with information in a research setting. This study may offer the opportunity to design interventions tailored for at-risk eating behaviours, offering advantages over the "one size fits all" approach of current failing obesity interventions. Copyright:
Authors: Anna L Ford; Cecilia Bergh; Per Södersten; Matthew A Sabin; Sandra Hollinghurst; Linda P Hunt; Julian P H Shield Journal: BMJ Date: 2009-01-05
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