Cardiovascular Disease
Conditions
Keywords
Cardiovascular disease, Non alcoholic fatty liver, Diabetes, Almonds, Endothelium-dependent vasodilation, Fecal short chain fatty acids (SCFAs), Snacking
Brief summary
The purpose of this study is to investigate the cardio-metabolic health effects of consuming almond nuts in place of habitual (usual) snack products in adults at moderate risk of developing cardiovascular disease
Detailed description
Tree nuts are recommended in the prevention and management of cardiovascular disease (CVD) largely based on their LDL (low density lipoprotein) lowering effects, but the CVD risk reduction observed with tree nut consumption is greater than that predicted by their hypocholesterolemic effects alone. Other health benefits have also been noted by our group, such as moderation of postprandial lipemia , as well as by others such as modified postprandial glycemia , decreased blood pressure (BP) , improvement in oxidant status and weight loss. Robust evidence for the protective cardio-metabolic effects of nuts from the PREDIMED study has highlighted the association between nut consumption and decreased risk of cardiovascular events, obesity, metabolic syndrome and type 2 diabetes (T2DM). However, there is a paucity of evidence on the effects of almonds on vascular function in humans (BP and endothelium-dependent vasodilation (EDV)), although there is evidence that almonds promote nitric oxide (NO) release in animals consuming high-fat diets. Fundamental to vascular health is a well-functioning liver and there is increasing evidence to demonstrate that the accumulation of liver fat is a causative factor in the development of cardio-metabolic disorders. Non-alcoholic fatty liver disease (NAFLD) is now considered the hepatic manifestation of the metabolic syndrome (MetS); recent data has shown that it is linked to increased CVD risk via direct effects on vascular function (and EDV) independently of obesity and MetS . NAFLD is thought to affect 30% of the population in developed countries, and up to two-thirds of people with obesity and 50% of people with hyperlipidemia. Development of fatty liver, mainly attributable to obesity and elevated postprandial lipemia, is associated with increased inflammation, oxidative stress, insulin resistance, dyslipidemia and impaired EDV, and predicts risk of CVD and T2DM . Therefore, the long-term goal of this research is to understand the mechanisms underpinning how dietary change can drive favourable modification of CVD disease risk and to identify patterns in population food choices, specifically almond consumption, that tend to correlate with reduced CVD disease risk. The primary aim of this proposal is to investigate, in a randomised controlled, parallel arm, 6-wk dietary intervention (n=100) whether replacing snacks based on refined carbohydrates and poor in micronutrients/non-nutrient bioactives (NNB) with nutrient/NNB-dense, whole almond snacks can influence liver fat content (a key metabolic driver of insulin resistance and vascular dysfunction, and a hallmark of metabolic syndrome) and EDV (brachial FMD being an independent predictor of CVD events, in addition to related biomarkers of cardio-metabolic disease risk. The snacks products provide participants with 20% of their energy requirements via either whole almonds or as muffins/crackers that have been designed to mimic the average UK snack.
Interventions
Participants to consume almonds as snacks to contribute to 20% of their energy requirements daily for 4 weeks
Participants to consume muffins/crackers as snacks to contribute to 20% of their energy requirements daily for 4 weeks NB all participants will have a run in period for 2 weeks whereby muffins are consumed, this is prior to randomisation.
Sponsors
Study design
Eligibility
Inclusion criteria
Subjects will be male or female, aged between 30-70 years who regularly consume ≥2 snack products a day. A principal aim is to identify and recruit subjects with increased risk of CVD, in order to increase the sensitivity of the study subjects to dietary change. Subjects who are at above average risk for developing CVD (relative risk \>1.5) will be selected using a metabolic scoring system (scoring ≥2 points), adapted from the Framingham risk score system, as used previously by Chong et al. 2012. Subjects will give their own written informed consent.
Exclusion criteria
1. Non-snack consumers (assessed as subjects consuming \<2 snack products per day by a specific FFQ (food frequency questionnaire) at screening, adapted from the short Health Survey for England (2007) Eating Habits Questionnaire). 2. A reported history of myocardial infarction or cancer. 3. Being fitted with a heart pacemaker. 4. Presence of metal inside the body (implants, devices, shrapnel, metal particles in eyes from welding etc.). History of black-outs/epilepsy. 5. Diabetes mellitus (fasting plasma glucose \>7 mmol/L). 6. Chronic coronary, renal or bowel disease or history of cholestatic liver disease or pancreatitis. 7. Presence of gastrointestinal disorder or use of a drug, which is likely to alter gastrointestinal motility or nutrient absorption. 8. History of substance abuse or alcoholism (past history of alcohol intake \>60 units/men or 50 units/women). 9. Currently pregnant, planning pregnancy, breastfeeding or having had a baby in the last 12 months. 10. Allergy or intolerance to nuts. 11. Unwilling to follow the protocol and/or give informed consent. 12. Weight change of \> 3 kg in preceding 2 months. BMI \<18 kg/m2 (underweight) or \>40 kg/m2 (morbidly obese due to potential technical difficulties making FMD and ambulatory blood pressure (ABP) measurements). 13. Current smokers or individuals who quit smoking within the last 6 months. 14. Participation in other research trials involving dietary or drug intervention and/ or blood collection in the past 3 months. 15. Unable or unwilling to comply with study protocol. 16. The above criteria will be measured using the screening questionnaires and from physical (blood pressure, weight, height) and biochemical measurements (full lipid count, liver function test, full blood count, glucose and insulin) made during the screening visit. Participant eligibility will be assessed against the inclusion/
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Endothelium-dependent vasodilation | Baseline (week 2) | Measured via flow mediated dilation (FMD) |
| Liver fat % | Baseline (week 2) | Via MRI and magnetic resonance spectroscopy (MRS) analysis. Only a subset of 48 participants with aim of 20 per each arm to complete |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Abdominal fat | Baseline (week 2) | Via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete. |
| Muscle fat | Baseline (week 2) | Single measurement via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete.Muscle fat will be measured in the soleus muscle in the lower calf. |
| Body composition: body weight | Week 0, prior to 2 week run in | Using Tanita scales |
| Body composition: body mass index | Week 0, prior to 2 week run in | — |
| Body composition: Waist circumference | Week 0, prior to 2 week run in | — |
| Body composition: Hip circumference | Week 0 (prior to 2 week run in) | — |
| Blood pressure | Week 0 (prior to 2 week run in) | — |
| 24 hour ambulatory blood pressure | Week 2 'Baseline | — |
| 24 hour heart rate variability | Week 2 'baseline' | — |
| Fecal short chain fatty acids | Week 2 'baseline | Subset of participants, n=30 |
| Gut microbiota | Week 2 'baseline' | Subset of participants, n=30 |
| Pancreatic fat | Baseline (week 2) | Via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete. |
| Plasma adiponectin | Week 2 'Baseline' | — |
| Plasma resistin | Week 2 'baseline' | — |
| Plasma leptin | Week 2 'baseline' | — |
| Fasting insulin | week 2 'baseline' | — |
| Fasting glucose | Week 2 'baseline' | — |
| Fasting non esterified fatty acids (NEFA) | Week 2 'baseline' | — |
| Plasma Total cholesterol | Week 2 'baseline | Fasting |
| Plasma LDL cholesterol | Week 2 'Baseline' | Fasting |
| Plasma HDL cholesterol | Week 2 'Baseline' | Fasting |
| Plasma HDL:LDL ratio | Week 2 'Baseline' | Fasting |
| Plasma triglyceride concentration | Week 2 'baseline' | Fasting |
| Homeostasis model assessment estimated insulin resistance (HOMA-IR) | Week 2 'Baseline' | Fasting (calculated from insulin and glucose) |
Other
| Measure | Time frame | Description |
|---|---|---|
| Adverse events | Through study completion, average of 1.5 years. | — |
| 4 day food diaries | 4 days at screening | — |
| Snack product acceptability | Week 6 | Questionnaire for participants to rate acceptability including self-rated enjoyment, sensory aspects, gastrointestinal effects, palatability, and appetite sensations, and likelihood that they will continue to consume the almonds/muffins as a snack after the study has ended |
Countries
United Kingdom