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Mark Hopkins on Muck Rack

Mark Hopkins

United States
As seen in: Medium, Nature, Mashable, The Conversation, Medscape, The San Diego Union-Tribune, The Canton Repository, The Greenville News, The Observer-Dispatch, Gaston Gazette and
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Articles

Associations of body composition and resting metabolic rate with homeostatic and hedonic components of appetite

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By Arwa Alruwaili, Laure Haenebalcke, Bethan Roberts, Buket Engin, Sundus Malaikah, Mark Hopkins, Graham Finlayson, James Sanders, Alice E Thackray, David Stensel, Scott Willis, James King, Hannah Trotman, Melanie Partington
| Nature Verified
Abstract While fat-free mass (FFM), fat mass (FM), and resting metabolic rate (RMR) influence energy intake, their specific roles as homoeostatic and hedonic drivers of eating—and factors moderating these relationships—are uncertain. This study examined associations of FFM, FM, and RMR with a comprehensive set of appetite-related outcomes in adults.
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The mixed-meal tolerance test as an appetite assay: methodological and practical considerations - International Journal of Obesity

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By James King, Alice E Thackray, Catia Martins, David R Broom, David Stensel, Dimitris Papamargaritis, Frank Arsenyadis, Graham Finlayson, John Blundell, Kristine Beaulieu, Mark Hopkins, Masashi Miyashita, Scott Willis
| Nature Verified
Abstract Appetite control is a topic which attracts widespread interest given its importance to energy balance and obesity. In this research area, the mixed-meal tolerance test (MM-TT) has emerged as an ‘appetite regulation assay’, facilitating the dynamic assessment of appetite parameters (e.g. subjective appetite perceptions, appetite-related hormones, food reward) in response to an individual meal.
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Predictive equation helps estimate misreporting of energy intakes in dietary surveys - Nature Food

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By R. James Stubbs, Mark Hopkins
| Nature Verified
Misreporting of dietary intake under free-living conditions in nutritional epidemiological studies can’t be easily captured. A predictive equation for total daily energy expenditure derived from the largest doubly labelled water dataset to date can help improve evaluation of the accuracy of self-reported dietary intake.
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