Volume 30, Issue 1, Pages e3 (July 2019)

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Volume 30, Issue 1, Pages 67-77.e3 (July 2019) Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake  Kevin D. Hall, Alexis Ayuketah, Robert Brychta, Hongyi Cai, Thomas Cassimatis, Kong Y. Chen, Stephanie T. Chung, Elise Costa, Amber Courville, Valerie Darcey, Laura A. Fletcher, Ciaran G. Forde, Ahmed M. Gharib, Juen Guo, Rebecca Howard, Paule V. Joseph, Suzanne McGehee, Ronald Ouwerkerk, Klaudia Raisinger, Irene Rozga, Michael Stagliano, Mary Walter, Peter J. Walter, Shanna Yang, Megan Zhou  Cell Metabolism  Volume 30, Issue 1, Pages 67-77.e3 (July 2019) DOI: 10.1016/j.cmet.2019.05.008 Copyright © 2019 Terms and Conditions

Cell Metabolism 2019 30, 67-77.e3DOI: (10.1016/j.cmet.2019.05.008) Copyright © 2019 Terms and Conditions

Figure 1 Overview of the Study Design Twenty adults were confined to the metabolic ward at the NIH Clinical Center, where they were randomized to consumed either an ultra-processed or unprocessed diet for 2 consecutive weeks followed immediately by the alternate diet. Every week, subjects spent 1 day residing in a respiratory chamber to measure energy expenditure, respiratory quotient, and sleeping energy expenditure. Average energy expenditure during each diet period was measured by the doubly labeled water (DLW) method. Body composition was measured by dual-energy X-ray absorptiometry (DXA) and liver fat was measured by magnetic resonance imaging/spectroscopy (MRI/MRS). Cell Metabolism 2019 30, 67-77.e3DOI: (10.1016/j.cmet.2019.05.008) Copyright © 2019 Terms and Conditions

Figure 2 Ad Libitum Food Intake, Appetite Scores, and Eating Rate (A) Energy intake was consistently higher during the ultra-processed diet. Data are expressed as mean ± SE. (B) Average energy intake was increased during the ultra-processed diet because of increased intake of carbohydrate and fat, but not protein. Data are expressed as mean ± SE, and p values are from paired, two-sided t-tests. (C) Energy consumed at breakfast and lunch was significantly greater during the ultra-processed diet, but energy consumed at dinner and snacks was not significantly different between the diets. Data are expressed as mean ± SE, and p values are from paired, two-sided t-tests. (D) Both diets were rated similarly on visual analog scales (VASs) with respect to pleasantness and familiarity. Data are expressed as mean ± SE. (E) Appetitive measures were not significantly different between the diets. Data are expressed as mean ± SE. (F) Meal eating rate was significantly greater during the ultra-processed diet. Data are expressed as mean ± SE, and p values are from paired, two-sided t-tests. Cell Metabolism 2019 30, 67-77.e3DOI: (10.1016/j.cmet.2019.05.008) Copyright © 2019 Terms and Conditions

Figure 3 Body Weight and Composition Changes (A) The ultra-processed diet led to increased body weight over time whereas the unprocessed diet led to progressive weight loss. Data are expressed as mean ± SE. (B) Differences in body weight change between the ultra-processed and unprocessed diets were highly correlated with the corresponding energy intake differences. Data are expressed as mean ± SE. (C) Body fat mass increased over time with the ultra-processed diet and decreased with the unprocessed diet. Data are expressed as mean ± SE. (D) Body weight, body fat, and fat-free mass changes between the beginning and end of each diet period. Data are expressed as mean ± SE, and p values are from paired, two-sided t-tests. Cell Metabolism 2019 30, 67-77.e3DOI: (10.1016/j.cmet.2019.05.008) Copyright © 2019 Terms and Conditions

Figure 4 Glucose Tolerance and Continuous Glucose Monitoring (A) Glucose concentrations following a 75 g oral glucose tolerance test (OGTT) were not significantly different between the diets. Data are expressed as mean ± SE. (B) Insulin concentrations following the OGTT were not significantly different between the diets. Data are expressed as mean ± SE. (C) Continuous glucose monitoring throughout the study did not detect significant differences in average glucose concentrations or glycemic variability as measured by the coefficient of variation (CV) of glucose. Data are expressed as mean ± SE. Cell Metabolism 2019 30, 67-77.e3DOI: (10.1016/j.cmet.2019.05.008) Copyright © 2019 Terms and Conditions