Conventional Model of Obesity Effects of Dietary Glycemic Load on - - PDF document

Effects of Dietary Glycemic Load

• n Energy Expenditure:

Results from the Framingham State Food Study

Cara B. Ebbeling, PhD March 29, 2019 2019 Massachusetts Academy of Nutrition and Dietetics Annual Nutrition Convention & Exposition

Disclosure

Cara B. Ebbeling, PhD, MS

Effects of Dietary Glycemic Load on Energy Expenditure: Results from the Framingham State Food Study FINANCIAL DISCLOSURE No relevant financial relationship exists

• Biological factors strongly influence body weight

 With weight loss, hunger increases and energy expenditure decreases  Physiological adaptations defend against long term weight change

• Genetic factors are known to affect body weight

 Explain some of the variance in BMI  Cannot explain why the average person today, compared with 40 years ago, seems to be “defending” a much higher body weight

Background

Maclean et al. Am J Physiol Regul Integr Comp Physiol 2011;301:R581-600 Leibel et al. N Engl J Med 1995;332:621-8

Conventional Model of Obesity

Ludwig, Ebbeling. JAMA Intern Med 2018;178:1098-103.

Carbohydrate-Insulin Model of Obesity

Ludwig, Ebbeling. JAMA Intern Med 2018;178:1098-103.

Meta-Analysis

• f Short-Term Studies

Hall, Guo. Gastroenterology 2017;152:1718-27

JAMA  August 21, 2013

• “The

pursuit

• f

the ideal macronutrient content diet is unidimensional, ignoring 2 of the 3 major components of standard lifestyle interventions: behavioral modification and

• exercise. To consider lifestyle interventions as diets ignores

their complexity, with behavioral modification as the piece that specifically addresses adherence.”

• “The only consistent finding among the trials is that adherence

… was most strongly associated with weight loss and improvement in disease-related outcomes.”

• To evaluate dietary composition in the context of lifestyle interventions ignores the

importance of conducting trials with high internal validity before aiming to test external validity.

Outside the Study External Validity Are findings applicable in other circumstances? Inside the Study Internal Validity Is the study designed to answer the question at hand? Is there only one independent variable (i.e., dietary composition)?

• Feeding studies provide the best approach for maximizing internal validity when

evaluating the effects of diets varying in macronutrient composition.

Partnerships

Research team Food service team Assabet Valley Regional Technical High School

• Ludwig DS, Ebbeling CB. The Carbohydrate-Insulin Model of Obesity: Beyond "Calories In,

Calories Out". JAMA Intern Med 2018;178:1098-103.

• Ebbeling CB, Klein GL, Luoto PK, Wong JMW, Bielak L, Eddy RG, Steltz SK, Devlin C,

Sandman M, Hron B, Shimy K, Heymsfield SB, Wolfe RR, Wong WW, Feldman HA, Ludwig

• DS. A randomized study of dietary composition during weight-loss maintenance: rationale,

study design, intervention, and assessment. Contemp Clin Trials 2018;65:76-86.

• Wong JM, Bielak L, Eddy RG, Stone L, Lakin PR, Sandman M, Devlin C, Seger-Shippee L,

Wiroll D, Luoto PK, Klein GL, Ludwig DS, Ebbeling CB. An academia-industry partnership for planning and executing a community-based feeding study. Curr Dev Nutr 2018;2:nzy060.

• Ebbeling CB, Feldman HA, Klein GL, Wong JMW, Bielak L, Steltz SK, Luoto PK, Wolfe RR,

Wong WW, Ludwig DS. Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial. BMJ 2018;363:k4583.

Published Manuscripts ♦ (FS)2 ♦ 2018 Diverse Audience

Balance

• Technical scientific “language”
• “Lay terms”

Practitioners – Public Health Professionals – Researchers Faculty – Staff – Students – Media Study Participants – Patients– People Interested in Healthful Nutrition

Linkages

• Data collection protocols
• Reported data

Reported Data

• Numbers
• Bottom line

Framingham State Food Study: (FS)2 Specific Aim

To evaluate the effect of three diets varying widely in carbohydrate-to-fat ratio (high- carbohydrate, moderate-carbohydrate, low-carbohydrate) on energy expenditure during weight-loss maintenance, using a controlled feeding protocol. Hypothesis Total energy expenditure during weight-loss maintenance will differ among test diets through 20 weeks. Primary Outcome TEE, assessed by doubly-labeled water methodology ClinicalTrials.gov Identifier: NCT02068885 Lay Terms Energy Expenditure  Calories Burned – “Burn Rate”

Does it really matter whether calories come from carbohydrate or fat?

Practically speaking, what was the research question?

This suggests that calorie content of a diet is more important than composition. “A calorie is a calorie!”

Methods

Study Design and Dietary Interventions Primary Outcome

• Total Energy Expenditure

Secondary Outcomes

• Resting Energy Expenditure
• Physical Activity and Sedentary Time
• Skeletal Muscle Work Efficiency
• Fasting Blood Draw: 1,5-Anhydroglucitol, Ghrelin

Effect Modifier

• Insulin Secretion

(FS)2 Study Design

Assessment Period (stable body weight) START MID END PRE

High-Carbohydrate Diet – HI Carb Moderate-Carbohydrate Diet – MOD Carb Low-Carbohydrate Diet – LO Carb

• 16
• 12
• 8
• 4

4 8 12 16 20

Randomization

Weight Loss

WEEKS

Run-In Phase Weight-Loss Maintenance Test Phase

Run-in Diet

Weight Stabilization

12  2% Run-In Diet 60% Calorie Needs 45% Carbohydrate 30% Fat 25% Protein Prepared Meals

Weight Loss and Weight-Loss Maintenance

Participant AV-4198-4

65 67 69 71 73 75 77 79 81 9/14/2016 5/10/2017 PRE Anchor 76.9 kg START Anchor 67.5 kg + 2 kg  2 kg

Body Weight (kg)

12.2% weight loss

Withings Wi-Fi Scale

HI Carb MOD Carb LO Carb Targets

Consistency and Differentiation Carbohydrate (% energy) 60 40 20 Added Sugar (% total carbohydrate) 15 15 15 Fat (% energy) 20 40 60 Saturated Fat (% total fat) 35 35 35 Protein (% energy) 20 20 20

Macronutrient Composition of Test Diets

What proportion of calories came from carbohydrate vs. fat?

Dinner Example

HI Carb MOD Carb LO Carb

Herb Grilled Salmon, 55 g Leaf Spinach, 100 g Long Grain & Wild Rice, 115 g

• Greek Yogurt, non-fat, 160g

Dried cranberries, 20 g Whole Wheat Bread, 27 g

• Orange Sections, 180 g

Milk, skim, 80 g

• Herb Grilled Salmon, 90 g

Leaf Spinach, 100 g Long Grain & Wild Rice, 100 g Cheddar Cheese, 10 g

• Whole Wheat Bread, 22 g

Peanuts, 8 g Orange Sections, 165 g Milk, 2%, 120 g

• Herb Grilled Salmon, 80 g

Leaf Spinach, 100 g

• Cheddar Cheese, 15 g
• Peanuts, 33 g

Orange Sections, 95 g Milk, 3.25%, 180 g Salt, 0.3 g

Consistency and Differentiation

(FS)2 Kitchen

>160,000 meals!

• Food service staff completed:

95% of the intended spot weight checks 97% of the intended packaged menu item checks

• For completed spot weight checks, comparing actual weights with target weights:

67% of the menu items within narrow tolerance limits ±0.1 g of target for items ≤10 g and ±0.5 g for items >10 g 98% were within ±5 g deviation that would not compromise macronutrient differentiation

• For the packaged menu item checks:

99% of the take-out meals contained all intended menu items

How well did we implement the intervention?

Intervention Integrity Methods

Study Design and Dietary Interventions Primary Outcome

• Total Energy Expenditure

Secondary Outcomes

• Resting Energy Expenditure
• Physical Activity and Sedentary Time
• Skeletal Muscle Work Efficiency
• Fasting Blood Draw: 1,5-Anhydroglucitol, Ghrelin

Effect Modifier

• Insulin Secretion

Research Center

“The (FS)2 House”

days 1 14 Dose of 2H2

18O

Metabolic Period

Spot urine sample

Total Energy Expenditure

Doubly-Labeled Water Methodology Protocol

Mass number: protons + neutrons in an atom Isotopes: chemically identical, different number of neutrons (different mass)

Isotope Enrichment

99.76 0.204 16 18 O 99.985 0.015 1 2 H Doubly-Labeled Water % Natural Abundance Mass Number Element

2H2 18O

Back to Basic Chemistry!

Isotopic Label Elimination

2H2 18O

C18O2 and H2

18O 2H2O 18O 2H

• Label elimination
• Carbonic anhydrase reaction

CO2 + H2O H2CO3 H+ + HCO3

• Equilibrium between oxygen atoms in exhaled carbon dioxide and body water

provides a biochemical basis for doubly-labeled water methodology.

How do the isotopes leave the body? Participant: AV-4198-4 (START)

Disappearance Curves of 2H and 18O

Data from Spot Urine Samples

Difference in rates of disappearance Carbon dioxide production  Total Energy Expenditure

Methods

Study Design and Dietary Interventions Primary Outcome

• Total Energy Expenditure

Secondary Outcomes

• Resting Energy Expenditure
• Physical Activity and Sedentary Time
• Skeletal Muscle Work Efficiency
• Fasting Blood Draw: 1,5-Anhydroglucitol, Ghrelin

Effect Modifier

• Insulin Secretion
• Resting Energy Expenditure

Calories burned at rest

Secondary Outcomes

• Physical Activity and Sedentary Time

• Skeletal Muscle Work Efficiency

Power generated per increase in energy expenditure above resting More calories burned at a given workload Lower efficiency (a good thing)

• Ghrelin

Hormone produced primarily in the stomach Reported to lower energy expenditure and promote fat deposition

• 1,5-Anhydroglucitol

Biomeasure of compliance Marker of carbohydrate intake for people who do not have diabetes Lower is better

Effect Modification

• Occurs when the effect of the exposure on an outcome differs depending on the

level of a third variable, the effect modifier. Dietary Composition Total Energy Expenditure Insulin Secretion Exposure Outcome Effect Modifier Significant effect modification would lend support to the Carbohydrate-Insulin Model. Heated Hand Box 75 grams

• f glucose
• Oral Glucose Tolerance Test  Insulin Secretion

10 20 30 40 50 60 70 80 90 20 40 60 80 100 120

Time (minutes) Insulin (IU/mL) Insulin-30 Median Insulin-30 at PRE: 114.6 IU/mL

75-gram oral glucose load

• Insulin Secretion

Flow of Participants Through the Trial Participants Included in Statistical Analyses PRE-Weight-Loss Participant Characteristics

Participants

Provided data at END (n=48)

• Withdrawal/

dismissal (n=3) Follow-up and Analysis

• Provided data at

MID (n=50)

• Withdrawal/

dismissal (n=2) Provided data at END (n=54)

• Withdrawal/

dismissal (n=1)

• Provided data at

MID (n=56)

• Withdrawal/

dismissal (n=2)

• Withdrawal/

dismissal (n=7)

• Provided data at

MID (n=47)

• Withdrawal/

dismissal (n=1) Provided data at END (n=46) Telephone Screened (n=1,685) Completed Informational Visit (n=512) Provided Informed Consent (n=234)

• Did not meet eligibility criteria (n=148)

Provided Screening Consent (n=382)

• Did not meet eligibility criteria (n=1173)
• Did not meet eligibility criteria (n=130)

Enrollment Randomized following START assessments (n=164) MOD Carbohydrate (n=53) Allocation LO Carbohydrate (n=57) HI Carbohydrate (n=54)

• Consented but withdrew/dismissed (n=70)

Participant Flow

Average weight loss, relative to PRE body weight, for participants randomly assigned to a diet arm

N=164 10.5  1.7%

Per Protocol Analysis Included only participants achieving weight-loss maintenance ( 2 kg of START anchor weight)

N=120

Intention-to-Treat Analysis Excluded two participants 1) Developed a disqualifying medical condition, hypothyroidism 2) Provided unreliable doubly-labeled water data at START

N=162

Continuous Variables Mean  SD Age – yr 38.0  14.4 Height – cm 167.7  10.0 Weight – kg 91.5  18.2 BMI – kg/m2 32.4  4.8 TEE – kcal/d 3021  719 REE – kcal/d 1699  346 Categorical Variables N (%) Sex, Female – no. (%) 115 (70) Race – no. (%) White 128 (78) Black 17 (10) Asian 5 (3) Other 14 (9) Ethnicity, Hispanic – no. (%) 25 (15)

PRE-Weight-Loss Participant Characteristics

Randomized Sample (N=164)

Results

Biomeasure of Compliance

• Serum 1,5-Anhydroglucitol

Study Outcomes

• Total Energy Expenditure (primary)
• Resting Energy Expenditure
• Physical Activity and Sedentary Time
• Skeletal Muscle Work Efficiency
• Plasma Ghrelin

Effect Modification

• Insulin Secretion

Small P-values (typically < 0.05) provide objective evidence that differences are significant, or meaningful. Results Consistent for Other Biomeasures of Compliance

Serum 1,5-Anhydroglucitol Total Energy Expenditure

+131 kcal/d +278 kcal/d

Doubly-Labeled Water Methodology

Total and Resting Energy Expenditure

Resting energy expenditure did not differ by diet group. Total energy expenditure was significantly higher with LO.

Physical Activity and Sedentary Time

Total physical activity and sedentary time did not differ by diet group. MVPA was marginally higher with LO.

Skeletal Muscle Work Efficiency

Skeletal muscle work efficiency did not differ by diet group.

Plasma Ghrelin

Ghrelin showed a steeper decline with LO compared to HI. (possible explanation for change in total energy expenditure) Remember, ghrelin has been reported to lower energy expenditure and promote fat deposition.

Effect Modification by Insulin-30

Total Energy Expenditure

* * * Strengths

• One of the largest and longest controlled feeding studies
• Sufficient intervention duration to avoid confounding by transient metabolic

adaptations

• Power to achieve a relatively precise effect estimate for the primary outcome
• Biomeasures indicating substantial and sustained differentiation between diets
• Doubly-labeled water methodology to assess total energy expenditure
• Control for dietary protein and body weight
• Design of diets to reflect realistic and healthful examples of different macronutrient

compositions

• Some non-compliance (free-living participants)
• Generalizability: Translation to public health (self-prepared meals)

Limitations Conclusions

• Dietary composition seems to affect energy expenditure independently of body

weight.

• A low glycemic load high fat diet might facilitate weight loss maintenance beyond

the conventional focus on restricting energy intake and encouraging physical activity.

• If metabolic benefits of reduced glycemic load diets are confirmed, development of

appropriate behavioral and environmental interventions would be necessary for

• ptimal translation to public health (generalizability, external validity).

Directions for Additional Research

• Examine the effects of glycemic load on body weight, with control of energy intake
• Compare diets aiming to reduce glycemic index at prevailing carbohydrate levels

compared with restricting total carbohydrate

• Explore subgroup susceptibility based on insulin secretion and other biological

factors

• Determine whether extreme carbohydrate restriction (ketogenic diet) confers

unique advantages for obesity or specific conditions such as diabetes

• Explore the mechanisms relating dietary composition to energy expenditure

Funding

• Nutrition Science Initiative (made possible by gifts from the Laura and John Arnold

Foundation and Robert Lloyd Corkin Charitable Foundation)

• New Balance Foundation
• Many Voices Foundation
• Blue Cross Blue Shield
• National Institute of Diabetes and Digestive and Kidney Diseases

K24DK082730 to DSL

Acknowledgments

Co-Authors: Henry Feldman, Gloria Klein, Julia Wong, Lisa Bielak, Sarah Steltz, Patricia Luoto, Robert Wolfe, William Wong, David Ludwig Consultants: Helen Rasmussen, Janis Swain, Jeff Volek Framingham State University: Rita Colucci, Susanne Conley, Dale Hamel, Jonathan Lee, Daniel Magazu, Linda Vaden-Goad Sodexo: Ralph Eddy, Elizabeth Olson, Beth Winthrop Assabet Valley Regional Vocational School District: Ernest Houle, Kristopher Luoto

Leadership

SetPoint Health: David Blackburn

Study Participants

Acknowledgments

Boston Children’s Hospital: Teri Allers, Rachel Apone, Michaela Barhite, Gary Bradwin, Carissa Burton, Emily Caplan, Nicole Chenard, Kimberly Chin, Courtenay Devlin, Jillian Fergione, Maria Khan, Lesley Levitt, Amanda Gonsalves, Veronica Gragnano, Tessa Graham, Shannon Hourigan, Bridget Hron, Paul Lakin, Meghan Leary, Ethan Litman, Catherine Matero, Marlee McGurl, Carly Milliren, Anne Nero, Victoria Ravenelle, Lisa Robinson, Adrienne Salisbury, Megan Sandman, Amanda Scott, Linda Seger-Shippee, Kim Shimy, Kaitlyn Shannon, Rachael Sharpe, Caitlin Shaughnessy, Daniele Skopek, Tram Anh Tran, Benjamin Trapp, Emma van Emmerik Framingham State University: Denise Harney Sodexo: David Garufi, Renae Gauvin, Carolyn Holland, Darline Hughes, Eric Johnson, Lauren Stone, Denise Stultz Assabet Valley Regional Technical High School: Danielle Gervais, Jon Thering, Kelsey Viera, Dina Wiroll Baylor College of Medicine: Zhensheng Chen SetPoint Health: Rob O’Neill, Kristina Spellman

Staff

Thank You!