The Impact of Consumption of Eggs in the Context of Plant-Based Diets on Endothelial Function, Diet Quality, and Cardio-Metabolic Risk Factors in Adults at Risk for Type 2 Diabetes
Study Details
Study Description
Brief Summary
Purpose To assess the impact of inclusion of 2 eggs daily for 6 weeks in an otherwise vegan diet compared to a vegan diet on cardio-metabolic risk and dietary pattern in adults at risk for type 2 diabetes.
Hypotheses In comparison with a vegan diet, the inclusion of 2 eggs daily in an otherwise vegan diet will improve or have neutral effects on endothelial function and other markers of cardio-metabolic risk in adults at risk for type 2 diabetes.
(2) In comparison with a vegan diet, the inclusion of 2 eggs daily in an otherwise vegan diet will improve diet quality and nutrient intake in adults at risk for type 2 diabetes.
(2) In comparison with a vegan diet, the inclusion of 2 eggs daily in an otherwise vegan diet will improve diet quality and nutrient intake in adults at risk for type 2 diabetes.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Specific Aims of the Proposed Project:
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To assess the impact of inclusion of 2 eggs daily for 6 weeks in an otherwise vegan diet, compared to a vegan diet, on endothelial function in adults at risk for T2DM. Specifically, to demonstrate superior or neutral effects on endothelial function with the inclusion of eggs in the context of otherwise vegan diets.
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To assess the impact of the inclusion of eggs daily for 6 weeks in an otherwise vegan diet, compared to a vegan diet, on dietary pattern and cardio-metabolic risk factors in adults at risk for T2DM. Specifically, to determine the effects on egg intake in the context of an otherwise vegan diet on diet quality and nutrient intake, lipid profile, blood pressure, insulin sensitivity and anthropometric measures.
Design:
Proposed is a randomized, single-blind, controlled, crossover trial designed with 2 treatment assignments (vegan diet plus eggs and vegan diet ) to compare the effects of 6 weeks of each treatment assignment on endothelial function, nutrient intake, diet quality, and cardio-metabolic risk factors in individuals at risk for T2DM. After a 4-week run-period of an ad libitum vegan diet, participants will be randomized to 1 of 2 possible sequence permutations and then undergo repeated measures following inclusion of 2 eggs per day in their otherwise vegan diet, or a vegan diet for 6 weeks, with a 4-week washout period between treatment assignments. The participants will continue their vegan diets during the 4-week washout period.
Background In the United States (U.S.), diabetes is a public health problem of epidemic proportions, affecting more than 30 million individuals. Only 23.1 million of these individuals are diagnosed. An estimated 84.1 million adults aged 18 years and older have prediabetes. Nearly 1 out 10 individuals with prediabetes is aware that he or she has this condition. Fifteen to thirty percent of individuals with prediabetes are likely to develop Type 2 diabetes mellitus (T2DM) within 5 years. The total medical costs, including lost work and wages, for individuals diagnosed with diabetes are estimated to be $245 billion. When compared with individuals without diabetes, individuals with diabetes have a medical cost that is more than two times higher. When compared with those without diabetes, the risk of death in individuals with diabetes is more than 50% higher. Between 90% and 95% of all diagnosed cases of diabetes are T2DM. The complications of diabetes include stroke, hypertension, cardiovascular disease (CVD), blindness, kidney disease, nervous system damage, limb amputations, and biochemical imbalances that can cause acute life-threatening events. [1] When compared with those without diabetes, the rates of cardiovascular mortality are 2 to 4 times higher among adults with diabetes.
Obese individuals are more than seven times more likely to develop T2DM when compared with healthy weight individuals. The cells become more resistant to insulin when there is more body fat. Increased insulin resistance contributes to high blood pressure, increased low density lipoprotein (LDL) cholesterol and triglycerides, and reduced levels of high-density lipoprotein (HDL) cholesterol. High blood insulin levels are associated with increased body fat. They disrupt normal metabolism of fats, increasing blood cholesterol and triglyceride levels; interfere with intercellular communication, including blood pressure-regulating signals; and stimulate the sympathetic nervous system, increasing the cardiac contractility and arterial resistance. Weight gain of as little as 10 pounds over 15 years could double an individual's insulin resistance and increase the risk of diabetes. When fat is primarily stored in the abdomen, the risk of diabetes is increased compared with when the fat is stored elsewhere. Abdominal fat wrap around organs such as the liver that play a vital role in glycemic control. Accumulation of fat around the liver blocks the action of insulin, which is needed to lower blood sugar; as a result, glucose accumulates in the blood stream.
Hyperglycemia has been linked to CVD. [Hyperglycemia stimulates a pro-atherogenic phenotype in the vessel wall of endothelial cells, vascular smooth muscle cells, inflammatory cells, fibroblasts, and platelets, leading to an atherosclerotic response. Diets with a low glycemic load have been shown to improve serum lipid profiles, reduce C-reactive protein (CRP) levels, and aid in weight management. [8] Low glycemic index diets have been associated with higher levels of HDL cholesterol, reduced CRP concentrations, and decreased risk of developing diabetes and CVD. [9] While glycemic control remains the basis of diabetes care, the co-management of cardio-metabolic risk factors and prevention of long-term consequences are also recognized as essential to improve long-term survival.
Lifestyle intervention is the cornerstone for management and prevention of T2DM. Previous studies have shown that a reduction of as little as five to seven percent in body weight can lead to significantly improved cardio-metabolic risk factors among those at risk for T2DM. Patients with T2DM or at risk for T2DM are typically advised to consume foods with a low glycemic index (i.e., a relative ranking of carbohydrates in foods based on their impact on blood glucose levels). When steps are taken to ensure adequate consumption of nutrients, plant-based diets are recommended to reduce risk of T2DM. Without careful planning, it can be difficult for those consuming plant-based diets that exclude animal foods to consume optimal amounts of protein and other nutrients Vitamin B12 is present only in animal foods while iron, zinc, copper and selenium are more bioavailable when obtained from animal food sources. Eggs are rich in vitamins and minerals such as vitamin A, B2, B5, B12, phosphorus, selenium, iron and choline and contain the highest quality protein. Additionally, eggs are satiating and therefore have the potential to regulate calorie intake and reduce body weight. Hence, the inclusion of eggs in plant-based diets has the potential to improve diet quality by increasing intake of a variety of nutrients and ensuring the correct balance of nutritious foods. While some observational studies have identified associations between egg consumption and greater risk of T2DM, experimental trials in contrast have shown that eggs may improve insulin sensitivity and some cardio-metabolic risk factors in individuals with T2DM. In order to recommend eggs as part of a plant-based diet for this population, it is imperative to establish their effects on diet quality and cardio-metabolic health in the context of plant-based diets.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Active Comparator: Egg phase: Participants will meet with a registered dietitian and receive instructions to include 2 eggs per day for 6 weeks as part of their otherwise vegan diets. |
Other: Egg included vegan phase
: Participants will meet with a registered dietitian and receive instructions to include 2 eggs per day for 6 weeks as part of their otherwise vegan diets. Participants will also receive instructions to preserve an isocaloric condition with the addition of 2 eggs in their diets. Counseling of the study participants will be based on the U.S. Department of Agriculture (USDA) healthy vegetarian meal plans, with modifications to exclude dairy products. [21] Additional resources (e.g., educational materials, recipes, etc.) for adopting and maintaining a vegan diet (with the exception of including eggs) will also be provided.
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| Placebo Comparator: Control phase: The participants will consume a vegan diet for 6 weeks. |
Other: Vegan Phase
The participants will consume a vegan diet for 6 weeks. The study dietitian will provide counseling and sample meal plans based on the USDA healthy vegetarian dietary pattern, with modifications to exclude eggs and dairy products. Additional resources (e.g., educational materials, recipes, etc.) for adopting and maintaining a vegan diet will also be provided.
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Outcome Measures
Primary Outcome Measures
- Change in Endothelial Function (EF) Assessment: [20 weeks]
EF will be assessed at each of the 4 study visits and will be measured noninvasively in the right brachial artery by a high-frequency, 10-15 MHz, vascular ultrasound transducer (Philips iU22, Philips Medical Systems, Bothell, WA) in accordance with published guidelines. Endothelial function will be measured as Flow-mediated dilatation (FMD), that is the percent change in brachial artery diameter from pre-cuff inflation to 60-seconds post-cuff release. In addition to brachial diameter at 60 seconds post-cuff release, flow after cuff deflation within the first 15 seconds will be used as an indicator of stimulus strength, hyperemic flow being the stimulus for endothelial reactivity. To account for potential variability in stimulus strength, a secondary analysis will be performed in which FMD is divided by flow at 15 seconds post-cuff deflation to create a stimulus-adjusted response measure. All brachial artery reactivity studies (BARS) will be completed prior to noon.
Secondary Outcome Measures
- Change in Diet quality: Automated Self-Administered 24-Hour Recall (ASA24) [20 weeks]
To assess differences in diet quality and help the study team track any variation in dietary pattern over the course of the study, participants will be asked at each of the 4 assessment visits to provide information on the foods and beverages that they consumed during a 3-day period (i.e., 2 weekdays and 1 weekend day). For each 3-day period, participants will complete 3 consecutive 24-hour recalls using a web-based Automated Self-Administered 24-Hour Recall (ASA24) (available from the National Cancer Institute at http://riskfactor.cancer.gov/tools/instruments/asa24/ ), which will guide them through the process of completing the recall data, and these data will be reviewed by the study dietitian. Diet quality based on the information provided will be assessed using the Alternative Healthy Eating Index 2015 (AHEI-2015). Intake of micro and macronutrients will also be assessed.
- Change in Serum Lipids [20 weeks]
Blood samples will be collected at the clinical screening and at each of the 4 study visits. Values of total cholesterol (Tchol), triglycerides (TG), and high-density lipoprotein (HDL) will be obtained by direct measurements from the participants' serum of their collected blood samples. Serum low-density lipoprotein (LDL) will be calculated using the following formula LDL = Tchol - (TG/5 + HDL). HDL:Tchol ratio will also be computed.
- Change in Body composition [20 weeks]
Body composition will be measured at the clinical screening and at each of the 4 study visits using bioelectrical impedance analysis, which uses the resistance of electrical flow through the body to estimate body fat. TheTanita SC-240 Body Composition Analyzer will be used to measure body composition. The SC-240 Body Composition Analyzer measures weight and calculates body fat%, visceral fat rating and total body water% in addition to BMI. In a multicenter European study by Deurenberg et al. [23] with adults between the ages of 18 and 70 years, the use of an impedance-based prediction equation for body fat percentage (which is the basis for the Tanita SC-240 Body Composition Analyzer function) when compared to either dual-energy X-ray absorptiometry (DXA) or densitometry (underwater weighing) - two current standards used to measure body composition - was found to provide good estimates of body fat percentage.
- Change in Body weight [20 weeks]
Body weight will be measured at clinical screening and at each of the 4 study visits Body weight will be measured to the nearest 0.5 pound using a balance-type medical scale. Subjects will be measured in the morning (fasting), unclothed with the exception of undergarments.
- Waist circumference [20 weeks]
Waist circumference will be measured at clinical screening and at each of the 4 study visits using the U.S. government standard protocol at each visit. To measure the waist circumference, the clinical research coordinator will ask the participant to stand and will place a measurement tape around the participant's middle, just above her/his hipbones, at the level of the belly button. The clinical research coordinator will ensure that the tape is horizontal around the participant's waist, and will then keep the tape snug around the participant's waist while not compressing the skin, and will measure her/his waist just after exhaling.
- Insulin Sensitivity [20 weeks]
Glucose and insulin will be measured from serum of the blood samples collected at clinical screening (glucose only) and each of the 4 study visits. Participants will be instructed to fast at least 8 hours before glucose and insulin blood draw. To assess insulin sensitivity, insulin resistance (HOMA-IR) will be calculated using values of the participants fasting glucose and insulin.
- Office Blood Pressure [20 weeks]
Systolic and diastolic BP will be measured at the clinical screening and at each of the 4 study visits using a Dinamap Monitor Pro 100 (GE Healthcare, Piscataway, NJ) after sitting for 5 minutes. Both systolic and diastolic pressures will be calculated as the mean value of 2 readings 5 minutes apart for each participant at every time point of assessment.
- Change in Physical Activity [20 weeks]
Physical activity will be determined by the Seven-Day Physical Activity Recall [PAR]. [23] The PAR is one of the most widely used physical activity assessments in exercise science and epidemiological research. The popularity of this measure stems largely from its versatility and relative ease of use for research applications. The PAR provides detail regarding the duration, intensity, and volume (energy expenditure) of physical activity and can therefore be used for a variety of applications. Because it utilizes a one-week time frame, the data from the PAR is often considered representative of typical activity patterns. [24, 25] While it requires considerable cognitive effort by the participants, the interviewer administered version can be completed in a reasonable amount of time (~20 minutes)
Eligibility Criteria
Criteria
Inclusion Criteria:
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- Male, 25-75 years or postmenopausal female 2) Non-smoker; 3) At risk for T2DM as defined by meeting at least one of the criteria listed:
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Metabolic syndrome, i.e. meet three out of five of the following criteria:
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blood pressure >130/85 mmHg or currently taking antihypertensive medication;
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fasting plasma glucose (FPG) >100 mg/dL (6.1 mmol/L);
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serum triglycerides level (TG)>150 mg/dL (1.69 mmol/L);
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high-density lipoprotein (HDL) cholesterol < 40 mg/dL (1.04 mmol/L) in men, and < 50 mg/dL (1.29 mmol/L) in women;
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overweight (BMI ≥25kg/m²) with waist circumference of more than 40 inches (102 cm) for men and more than 35 inches (88 cm) for women.
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Fasting blood glucose >100mg/dL and <126mg/dL or hemoglobin A1C 5.7-6.4 %.
Exclusion Criteria:
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- Allergy to eggs; 2) Anticipated inability to complete the study protocol for any reason; 3) Current eating disorder; 4) Unstable use of lipid-lowering or antihypertensive medications (i.e., change in dose during the three months prior to enrollment) and/or unwilling to refrain from taking medication for 12 hours prior to endothelial function scanning; 5) Regular use of high doses of vitamin E (>400IU/day) or vitamin C (>500mg/day); fish oil, flaxseed oil, omega-3 fatty acid and/or fiber supplement, unless willing to discontinue supplementation for the study duration; 6) Use of insulin, glucose-sensitizing medication, or vasoactive medication (including glucocorticoids, antineoplastic agents, some psychoactive agents, or bronchodilators);
- Unstable use of antidepressant medications (i.e., change in dose during the three months prior to enrollment; 8) Diagnosed diabetes; 9) Diagnosed sleep apnea; unless treated and have been stable with their medications for at least 3 months 10) Established cardiovascular disease (including symptomatic coronary artery disease (CAD), myocardial infarction, peripheral vascular disease, congestive heart failure, carotid stenosis); 11) Coagulopathy, known bleeding diathesis, or history of clinically significant hemorrhage; current use of warfarin or other regular use of anticoagulation; 12) Substance abuse (chronic alcoholism, other chemical dependency);
- Any unstable medical condition that would limit the ability of a subject to participate fully in the trial (e.g., cancer, AIDS, tuberculosis, psychotic disorder);
- For women: Use of hormone replacement therapy
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Yale-Griffin Prevention Research Center | Derby | Connecticut | United States | 06418 |
Sponsors and Collaborators
- Griffin Hospital
Investigators
- Principal Investigator: Valentine Yanchou Njike, MD, MPH, Yale-Griffin Prevention Reserach Center
Study Documents (Full-Text)
None provided.More Information
Publications
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- Balk EM, Earley A, Raman G, Avendano EA, Pittas AG, Remington PL. Combined Diet and Physical Activity Promotion Programs to Prevent Type 2 Diabetes Among Persons at Increased Risk: A Systematic Review for the Community Preventive Services Task Force. Ann Intern Med. 2015 Sep 15;163(6):437-51. doi: 10.7326/M15-0452. Review.
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- Centers for Disease Control and Prevention. Available from: http://www.cdc.gov/diabetes/basics/prevention.html . Accessed 05/16/2019
- Centers for Disease Control and Prevention. National Diabetes Fact Sheet: National Estimates and General Information on Diabetes and Prediabetes in the United States, 2011. Available from: http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf . Accessed 05/16/2019
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- Corretti MC, Anderson TJ, Benjamin EJ, Celermajer D, Charbonneau F, Creager MA, Deanfield J, Drexler H, Gerhard-Herman M, Herrington D, Vallance P, Vita J, Vogel R; International Brachial Artery Reactivity Task Force. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. J Am Coll Cardiol. 2002 Jan 16;39(2):257-65. Erratum in: J Am Coll Cardiol 2002 Mar 20;39(6):1082.
- Deurenberg P, Andreoli A, Borg P, Kukkonen-Harjula K, de Lorenzo A, van Marken Lichtenbelt WD, Testolin G, Vigano R, Vollaard N. The validity of predicted body fat percentage from body mass index and from impedance in samples of five European populations. Eur J Clin Nutr. 2001 Nov;55(11):973-9.
- Diabetes Prevention Program Research Group, Knowler WC, Fowler SE, Hamman RF, Christophi CA, Hoffman HJ, Brenneman AT, Brown-Friday JO, Goldberg R, Venditti E, Nathan DM. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009 Nov 14;374(9702):1677-86. doi: 10.1016/S0140-6736(09)61457-4. Epub 2009 Oct 29. Erratum in: Lancet. 2009 Dec 19;374(9707):2054.
- Dunn AL, Marcus BH, Kampert JB, Garcia ME, Kohl HW 3rd, Blair SN. Comparison of lifestyle and structured interventions to increase physical activity and cardiorespiratory fitness: a randomized trial. JAMA. 1999 Jan 27;281(4):327-34.
- Esfahani A, Wong JM, Mirrahimi A, Srichaikul K, Jenkins DJ, Kendall CW. The glycemic index: physiological significance. J Am Coll Nutr. 2009 Aug;28 Suppl:439S-445S. Review.
- Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002 Feb 7;346(6):393-403.
- Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. JAMA. 2002 May 8;287(18):2414-23. Review.
- National Institutes of Health, Digestive and Kidney Diseases. Digestive and Kidney Diseases. Available from: https://www.niddk.nih.gov/health-information/diabetes/types/prediabetes-insulin-resistance . Accessed 05/16/2019
- National Institutes of Health, Digestive and Kidney Diseases. Statistics Related to Overweight and Obesity: The Economic Costs. Available from: www.niddk.nih.gov/health/nutrit/pubs/statobes.htm#econ . Accessed 05/16/2019
- Njike VY, Ayettey R, Petraro P, Treu JA, Katz DL. Walnut ingestion in adults at risk for diabetes: effects on body composition, diet quality, and cardiac risk measures. BMJ Open Diabetes Res Care. 2015 Oct 19;3(1):e000115. doi: 10.1136/bmjdrc-2015-000115. eCollection 2015.
- Njike VY, Ayettey RG, Rajebi H, Treu JA, Katz DL. Egg ingestion in adults with type 2 diabetes: effects on glycemic control, anthropometry, and diet quality-a randomized, controlled, crossover trial. BMJ Open Diabetes Res Care. 2016 Dec 22;4(1):e000281. doi: 10.1136/bmjdrc-2016-000281. eCollection 2016.
- Pronk NP. Structured diet and physical activity programmes provide strong evidence of effectiveness for type 2 diabetes prevention and improvement of cardiometabolic health. Evid Based Med. 2016 Feb;21(1):18. doi: 10.1136/ebmed-2015-110292. Epub 2015 Oct 22.
- Reusch JE, Wang CC. Cardiovascular disease in diabetes: where does glucose fit in? J Clin Endocrinol Metab. 2011 Aug;96(8):2367-76. doi: 10.1210/jc.2010-3011. Epub 2011 May 18. Review.
- Sallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN, Paffenbarger RS Jr. Physical activity assessment methodology in the Five-City Project. Am J Epidemiol. 1985 Jan;121(1):91-106.
- Satija A, Bhupathiraju SN, Rimm EB, Spiegelman D, Chiuve SE, Borgi L, Willett WC, Manson JE, Sun Q, Hu FB. Plant-Based Dietary Patterns and Incidence of Type 2 Diabetes in US Men and Women: Results from Three Prospective Cohort Studies. PLoS Med. 2016 Jun 14;13(6):e1002039. doi: 10.1371/journal.pmed.1002039. eCollection 2016 Jun.
- Tuomilehto J, Lindström J, Eriksson JG, Valle TT, Hämäläinen H, Ilanne-Parikka P, Keinänen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M; Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001 May 3;344(18):1343-50.
- United States Department of Agriculture (USDA). USDA Food Patterns: Healthy Vegetarian Eating Pattern. 2015; Available from: https://health.gov/dietaryguidelines/2015/guidelines/appendix-5 . Accessed 08/15/2019
- Wallin A, Forouhi NG, Wolk A, Larsson SC. Egg consumption and risk of type 2 diabetes: a prospective study and dose-response meta-analysis. Diabetologia. 2016 Jun;59(6):1204-13. doi: 10.1007/s00125-016-3923-6. Epub 2016 Mar 18.
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