Effects of Meal Environment Cues on Appetite and Metabolic Responses and the Mediating Role of Mind-Body States

Awardee Recipient

  • Miguel Alonso-Alonso, MD, PhD

    Miguel Alonso-Alonso, MD, PhD

    Director of Laboratory of Bariatric and Nutritional Neuroscience and Assistant Professor of Surgery

    Beth Israel Deaconess Medical Center and Harvard Medical School

    Miguel Alonso-Alonso, MD PhD, a physician-scientist with expertise in cognitive and clinical neuroscience, is Assistant Professor of Surgery at Harvard Medical School and Beth Israel Deaconess Medical Center (BIDMC), where he directs the...


  • 2018 - Pilot Grant

Background and Significance

Nutrition is a key determinant of healthy aging. Recent estimates suggest that, at a global level, poor diet is the second highest risk factor for early death after smoking, and contributes to one in five deaths [1]. Obesity, closely associated with poor diet and overeating, increases the risk of high-morbidity and -mortality conditions, including type 2 diabetes, cardiovascular disease, cancer and dementia [2, 3]. To reduce the risk of chronic disease in the population, several organizations have developed evidence-based dietary recommendations [4-6], which are used to guide health policies and programs. However, adherence to these recommendations remains a challenge [7], the so-called ‘nutrition-behavior gap’ [8]. Current recommendations place a strong emphasis on the composition of the diet, with specific guidance on quantification of macronutrient intake and dietary patterns (i.e. what to eat), and little or no mentioning of other aspects associated with the act of eating and its immediate context (i.e. how, why or when to eat). Nutritional epidemiology, the discipline behind dietary guidelines, is robust and relies on large datasets, but it is no short of limitations [9-11]. Complementary to this angle, several lines of evidence suggest that to be able to understand food-health relationships in their full extent, we need a more holistic view that integrates other important aspects, such as food quality versus quantity [12], the impact of meal timing –chrononutrition- [13, 14] and behavioral patterns [15, 16]. Anthropologists have also highlighted the limitations of ‘metrifying nutritional advice’, stating that the way humans eat is intimately linked to complex social and cultural associations that shape attitudes to food, eating behaviors, food choice, and ultimately nutrition and health [17, 18]. There is need for new perspectives beyond nutrition that can capture holistic aspects of food and eating, closely linked to the natural way humans relate to food.

The meal is the natural unit of eating in humans [19]. Beyond food composition, the context that surrounds a meal reflects cognitive, social, and emotional idiosyncrasies, and is also an important contributor to how and what a person eats. A body of research from the fields of consumer and sensory sciences has examined how the context in which food is presented and served during a meal can influence its perception, appetite, total intake and the overall experience [20-27]. However, these studies have focused primarily on consumption, acceptability or preferences, without leveraging these effects for the promotion of health, and without addressing in detail the mechanisms that could mediate those changes. Aside from the above studies, evidence in support of the importance of meals beyond nutrition in the study of food-health associations comes from cultural observation. Asian meal traditions, particularly in nations with good indices of healthy aging,

e.g. Japan and South Korea, are characterized by a rich set of norms around food and meals that guide people on how to eat as much as on what to eat [17, 28, 29], e.g. the shokuiku food and nutrition education curriculum taught in Japanese schools [30], or the intricate rules guiding Japanese [31] and Korean [32] food arrangements. These traditions emphasize the importance of naturality, seasonality, and a sense of aesthetic balance during meals [17, 28, 31]. Whether such focus on the meal context could have an impact on health healthy aging is currently unknown. Targeting aspects of the meal related to how to eat may represent a complementary strategy to facilitate healthy nutrition in the population.

Studying postprandial glycemic responses offers a window into the cardiometabolic impact of a meal. Postprandial hyperglycemia and glycemic variability can induce oxidative stress, inflammatory responses and other deleterious effects leading to endothelial dysfunction, representing an independent risk factor for adverse cardiovascular outcomes in both diabetic and nondiabetic populations [33-35]. Despite short- term clinical trials reporting mixed effects with low-glycemic index dietary interventions [36, 37], the value of postprandial glycemic responses has gained acceptance and it is current a major target in ongoing personalized nutrition interventions [38]. Physiologically, postprandial glycemic variability is affected by preprandial glycemic levels, meal composition, gastric emptying, insulin secretion, small intestinal glucose absorption, and hepatic and peripheral glucose metabolism [39]. There is growing evidence that factors that relate to the meal context can also play a role in postprandial glycemia, such as the order of food, the use of different utensils, or mind-body states (e.g. relaxation) [40-44]. Altogether, these findings support the use of postprandial glycemic responses as quick objective markers of the potential healthiness of a meal.

In this study, we will examine for the first time whether manipulations in the meal context can trigger mind-body states that impact appetite and the potential healthiness of a meal. Surprisingly, there has been very little research done or even awareness on this topic from the nutrition/science literature. It is possible that by de-emphasizing the primary reward aspects of food with a highly elaborated context and bringing a broader, deeper view on food (e.g. seasonality, the balance between foods, the aesthetic beauty of food and containers), satiation and satisfaction can be achieved after a meal with fewer calories, thus preventing overeating. Also, if the meal context triggers attributes and associations that induce a relaxation state, this could translate into beneficial metabolic effects of the meal. To answer these questions we have designed an experimental meal manipulation taking advantage of existing knowledge from cultural studies on Asian food culture. Experiments will be conducted using a new computerized tabletop environment developed in our laboratory and measuring effects on participants with sensitive physiological and cognitive parameters.

Specific Aims

Aim 1: To investigate whether a meal served in an Asian-inspired manner with references to nature, seasonality and aesthetics can impact appetite, specifically the satiating power of the meal, and post- meal glycemic responses. To address this aim, subjects will undergo two laboratory meals on two different days, in a randomized order, and counterbalanced across subjects. One of the meals will be representative of a plain, convenient, regular meal, served with a conventional arrangement. The other meal will be designed based on elements of Asian meals, particularly inspired by the art of Japanese food arrangement, under the supervision of Prof. Bestor. We will use elements that are universal and not culturally specific. Both meals will have the same food content but will differ in the arrangement and setting. Throughout the duration of the study subjects will wear a noninvasive continuous glucose monitoring (CGM) system. We expect that the meal served in an Asian-inspired manner will have higher satiating power (defined as change in appetite rating per kcal), higher overall satisfaction and a better glycemic response profile, characterized by a slower elevation in glucose levels, lower glycemic peak and smaller area under the curve.


Aim 2: To examine whether the effects of an Asian-inspired meal on satiating power and glycemic response are mediated by changes in physiological markers indicative of autonomic responses related to relaxation (heart rate variability, respiratory rate, electrodermal activity) and cognition (fixation patterns via eye-tracking). During the abovementioned two meals subjects will also wear physiological sensors (EKG, chest belt, a wristband and eye-tracking glasses). Based on the results of Aim 1 and physiological changes detected by these sensors, we will examine the potential mediation role of relaxation and autonomic changes induced by the presence of cues at the meal. We hypothesize that the Asian-inspired meal will be associated with a relative increase in vagal tone, defined as decreased respiratory rate, increased heart rate variability and reduced electrodermal activity. This will be associated with a more focused fixation pattern during the meal, measured with eye-tracking.


  1. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet, 2017. 390(10100): p. 1345-1422.
  2. Beydoun, M.A., H.A. Beydoun, and Y. Wang, Obesity and central obesity as risk factors for incident dementia and its subtypes: a systematic review and meta-analysis. Obesity reviews : an official journal of the International Association for the Study of Obesity, 2008. 9(3): p. 204-18.
  3. Malnick, S.D. and H. Knobler, The medical complications of obesity. QJM : monthly journal of the Association of Physicians, 2006. 99(9): p. 565-79.
  4. 2015-2020 Dietary Guidelines for Americans. 2015, US Department of Health and Human Services; US Department of Agriculture Washington,
  5. Sacks, F.M., et al., Dietary Fats and Cardiovascular Disease: A Presidential Advisory From the American Heart Association. Circulation, 2017. 136(3): p. e1-e23.
  6. Millen, B.E., et al., The 2015 Dietary Guidelines Advisory Committee Scientific Report: Development and Major Conclusions. Advances in nutrition, 2016. 7(3): p. 438-44.
  7. Haack, S.A. and C.J. Byker, Recent population adherence to and knowledge of United States federal nutrition guides, 1992-2013: a systematic review. Nutrition reviews, 2014. 72(10): p. 613-26.
  8. Worsley, A., Nutrition knowledge and food consumption: can nutrition knowledge change food behaviour? Asia Pacific journal of clinical nutrition, 2002. 11 Suppl 3: p. S579-85.
  9. Willett, W., Nutritional epidemiology: issues and challenges. International journal of epidemiology, 16(2): p. 312-7.
  1. Temple, N.J., Nutrition and disease: challenges of research design. Nutrition, 2002. 18(4): p. 343-7.
  2. Kristal, A.R., U. Peters, and J.D. Potter, Is it time to abandon the food frequency questionnaire? Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2005. 14(12): p. 2826-8.
  3. Wirt, A. and C.E. Collins, Diet quality–what is it and does it matter? Public health nutrition, 12(12): p. 2473-92.
  1. Asher, G. and P. Sassone-Corsi, Time for food: the intimate interplay between nutrition, metabolism, and the circadian clock. Cell, 2015. 161(1): p. 84-92.
  2. Johnston, J.D., et al., Circadian Rhythms, Metabolism, and Chrononutrition in Rodents and. Advances in nutrition, 2016. 7(2): p. 399-406.
  1. Ma, Y., et al., Association between eating patterns and obesity in a free-living US adult. American journal of epidemiology, 2003. 158(1): p. 85-92.
  1. Mattson, M.P., et al., Meal frequency and timing in health and disease. Proceedings of the National Academy of Sciences of the United States of America, 2014. 111(47): p. 16647-53.
  2. Bestor, T.C., Cuisine and identify in contemporary Japan, in Routledge Handbook of Japanese Culture and Society, V. Bestor, T.C. Bestor, and A. Yamagata, Editors. 2011, Routledge: New York,
  3. Fischer, E.F., Beyond Nutrition: Eating, Innovation, and Cultures of Possibility, in Sight and Life.
  4. Meiselman, H.L., Dimensions of the Meal: The Science, Culture, Business, and Art of Eating. 2000, Gaithersburg, Maryland: Aspen Publishers,
  5. Spence, C. and B. Piqueras-Fiszman, The Perfect Meal: The Multisensory Science of Food and Dining. 2014, Hoboken, NJ: Wiley-Blackwell.
  6. Van Ittersum, K. and B. Wansink, Plate Size and Color Suggestibility: The Delboeuf Illusion’s Bias on Serving and Eating Behavior. Journal of Consumer Research, 2012. 39(2): p. 215-228.
  7. Meiselman, H.L., et al., Demonstrations of the influence of the eating environment on food. Appetite, 2000. 35(3): p. 231-7.
  1. Zellner, D.A., et al., Neatness counts. How plating affects liking for the taste of food. Appetite, 57(3): p. 642-8.
  1. Genschow, O., L. Reutner, and M. Wanke, The color red reduces snack food and soft drink. Appetite, 2012. 58(2): p. 699-702.
  1. Piqueras-Fiszman, B. and C. Spence, Colour, pleasantness, and consumption behaviour within a. Appetite, 2014. 75: p. 165-72.
  1. Zellner, D.A., et al., It tastes as good as it looks! The effect of food presentation on liking for the flavor of food. Appetite, 2014. 77: p. 31-5.
  2. Wadhera, D. and E.D. Capaldi-Phillips, A review of visual cues associated with food on food acceptance and consumption. Eating behaviors, 2014. 15(1): p. 132-43.
  3. Introduction to Japanese cuisine: nature, history and culture (Japanese Culinary Academy). 2015, Tokyo: Shuhari
  4. Chung, H.K., K.R. Chung, and H.J. Kim, Understanding Korean food culture from Korean. Journal of Ethnic Foods, 2016. 3: p. 42-50.
  1. Miyoshi, , N. Tsuboyama-Kasaoka, and N. Nishi, School-based “Shokuiku” program in Japan: application to nutrition education in Asian countries. Asia Pacific journal of clinical nutrition, 2012. 21(1): p. 159-62.
  2. Tsuchiya, Y., The fine art of Japanese food arrangement. 1985, Tokyo: Kodansha
  3. Chung, H.-K., et al., Aesthetics of Korean foods: The symbol of Korean culture. Journal of Ethnic Foods 2016. 3(3): p. 178-188.
  4. Blaak, E.E., et al., Impact of postprandial glycaemia on health and prevention of disease. Obesity reviews : an official journal of the International Association for the Study of Obesity, 2012. 13(10): p. 923-84.
  5. Brand-Miller, J., et al., The glycemic index and cardiovascular disease risk. Current atherosclerosis reports, 2007. 9(6): p. 479-85.
  6. Dickinson, S. and J. Brand-Miller, Glycemic index, postprandial glycemia and cardiovascular. Current opinion in lipidology, 2005. 16(1): p. 69-75.
  1. Clar, C., et al., Low glycaemic index diets for the prevention of cardiovascular disease. The Cochrane database of systematic reviews, 2017. 7: p.
  2. Sacks, F.M., et al., Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular disease risk factors and insulin sensitivity: the OmniCarb randomized clinical trial. JAMA, 2014. 312(23): p. 2531-41.
  3. Zeevi, D., et al., Personalized Nutrition by Prediction of Glycemic Responses. Cell, 2015. 163(5): p. 1079-1094.
  4. Standl, E., O. Schnell, and A. Ceriello, Postprandial hyperglycemia and glycemic variability: should we care? Diabetes care, 2011. 34 Suppl 2: p. S120-7.
  5. Shukla, A.P., et al., Food Order Has a Significant Impact on Postprandial Glucose and InsulinDiabetes care, 2015. 38(7): p. e98-9.
  1. Imai, S., et al., Eating vegetables before carbohydrates improves postprandial glucose. Diabetic medicine : a journal of the British Diabetic Association, 2013. 30(3): p. 370-2.
  1. Imai, S., et al., A simple meal plan of ‘eating vegetables before carbohydrate’ was more effective for achieving glycemic control than an exchange-based meal plan in Japanese patients with type 2 diabetes. Asia Pacific journal of clinical nutrition, 2011. 20(2): p. 161-8.
  2. Sun, L., et al., The impact of eating methods on eating rate and glycemic response in healthy Physiology & behavior, 2015. 139: p. 505-10.
  3. Wilson, T., et al., Relaxation breathing improves human glycemic response. Journal of alternative and complementary medicine, 2013. 19(7): p. 633-6.
  1. Alonso-Alonso, M., et al. Manipulating meals via human-computer interaction: applications in ingestive behavior research. Society for the Study of Ingestive Behavior (SSIB). in Annual Meeting fo the Society for ths Study of Ingestive Behavior (SSIB). 2017.
  2. Manton, S., et al., The “Smart Dining Table”: Automatic Behavioral Tracking of a Meal with a Multi- Touch-Computer. Frontiers in psychology, 2016. 7: p.
  3. Magerowski, G., et al., Neurocognitive effects of umami: association with eating behavior and food choice. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology,
  4. McCraty, R. and F. Shaffer, Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health risk. Global advances in health and medicine, 2015. 4(1): p. 46-61.
  5. Pomeranz, B., et al., Assessment of autonomic function in humans by heart rate spectral analysis. The American journal of physiology, 1985. 248(1 Pt 2): p. H151-3.
  6. Yamamoto, Y. and R.L. Hughson, Coarse-graining spectral analysis: new method for studying heart rate variability. Journal of applied physiology, 1991. 71(3): p. 1143-50.
  7. Poh, M.Z., N.C. Swenson, and R.W. Picard, A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. IEEE transactions on bio-medical engineering, 2010. 57(5): p. 1243-52.
  8. Wood, K.H., L.W. Ver Hoef, and D.C. Knight, The amygdala mediates the emotional modulation of threat-elicited skin conductance response. Emotion, 2014. 14(4): p. 693-700.
  9. Mangina, C.A. and J.H. Beuzeron-Mangina, Direct electrical stimulation of specific human brain structures and bilateral electrodermal activity. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 1996. 22(1-2): p. 1-8.
  10. Laine, C.M., et al., Behavioral triggers of skin conductance responses and their neural correlates in the primate amygdala. Journal of neurophysiology, 2009. 101(4): p. 1749-54.
  11. Tawakol, A., et al., Relation between resting amygdalar activity and cardiovascular events: a longitudinal and cohort study. Lancet, 2017. 389(10071): p. 834-845.
  12. Blundell, J., et al., Chapter 8. Measuring food intake, hunger, satiety, and satiation in the laboratory, in Handbook of assessment methods for eating behaviors and weight-related problems: measures, theory, and research, D.B. Allison and M.L. Baskin, Editors. 2009, SAGE Publications, Inc: Thousand Oaks,
  13. Stunkard, A.J. and S. Messick, The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res, 1985. 29(1): p. 71-83.
  14. Steptoe, A., T.M. Pollard, and J. Wardle, Development of a measure of the motives underlying the selection of food: the food choice questionnaire. Appetite, 1995. 25(3): p. 267-84.
  15. John, O.P. and S. Srivastava, The Big-Five trait taxonomy: history, measurement and theoretical perspectives, in Handbook of Personality: Theory and Research, L.A. Pervin and O.P. John, Editors. 1999, Guilford Press: New York. p. 102-138.
  16. Chiuve, S.E., et al., Alternative dietary indices both strongly predict risk of chronic disease. J Nutr, 2012. 142(6): p. 1009-18.
  17. Pereira, M.A., et al., A collection of Physical Activity Questionnaires for health-related research. Med Sci Sports Exerc, 1997. 29(6 Suppl): p. S1-205.
  18. Faul, F., et al., G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior research methods, 2007. 39(2): p. 175-91.
  19. Preacher, K.J. and A.F. Hayes, SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc, 2004. 36(4): p. 717-31.
  20. Preacher, K.J. and A.F. Hayes, Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 2008. 40(3): p. 879-91.