Therapeutic Ketogenic Diet in Type 2 Diabetes Lowers CVD Risk at 1 year

As demonstrated in a previous article, a low carbohydrate or therapeutic ketogenic diet is a viable option for people to reduce their symptoms of Type 2 Diabetes, but does it increase the risk of cardiovascular disease such as heart attack and stroke?

Results of a peer-reviewed study of cardiovascular outcomes of people with Type 2 Diabetes (T2D) that was published at the beginning of May in the Journal of Cardiovascular Diabetology [1] found that those that followed a ketogenic diet (≤ 30 g carbohydrate per day) significantly improved in 22 of 26 cardiovascular disease risk factors, including biomarkers of cholesterol / lipoproteins, blood pressure, inflammation, and carotid intima media thickness (cIMT).

Previous published results from the same researchers and published in February of 2018 demonstrated that significant improvement of T2D symptoms was able to be achieved and sustained long term using a ketogenic diet [2,3]. A post reviewing that study can be read here.

Simply by decreasing the amount of carbohydrate in the diet over the course of a year there was not only a significant decrease in blood sugar and weight, but a dramatic improvement in lipid and lipoprotein markers associated with markers of cardiovascular risk.

The results of this most recent study do much to dispel the myth that a therapeutic ketogenic diet puts individuals at increased risk for heart attack and stroke. In fact, it reduces their risk.


Continuous Care Intervention (CCI) Group Participants

At the beginning of the study, there were 238 participants enrolled in the continuous care intervention (CCI) group and all had a diagnosis of Type 2 Diabetes (T2D) with an average HbA1c of  7.6%  ±1.5%.  They ranged in age from 46 — 62 years of age, 67% were women and 33% were men. Weight of the subjects ranged from 200 pounds to 314 pounds (117±26 kg) with an average weight of 257 pounds (117 kg) and Average Body Mass Index (BMI) was 41 kg·m-2 (class III obesity) ±9 kg·m-2, with 82% categorized as obese.  The majority of participants (87%) were taking at least 1 medication for glycemic control medication.

At the end of a year, 218 participants (83%) remained enrolled in the  continuous care intervention (CCI) group.

Intervention and Monitoring of CCI Group

Each participant in the CCI group received an Individualized Meal Plan which enabled them to attain and maintain nutritional ketosis. They also received behavioral and social support, biomarker tracking tools, and ongoing care from a health coach with medication management by a physician.

Subjects typically required <30 g·day−1 total dietary carbohydrates.

Daily protein intake was targeted to a level of 1.5 g·kg−1 based on ideal body weight and participants were coached to incorporate dietary fats until they were no longer hungry.

Other aspects of the diet were individually tailored to ensure safety, effectiveness and satisfaction, including consumption of 3-5 servings of non-starchy vegetables and sufficient mineral and fluid intake.

Participants ability to achieve and maintain nutritional ketosis was determined by subjects monitoring their blood ketone level of β-hydroxybutyrate (BHB) using a portable, handheld device. Blood glucose and β-hydroxybutyrate (BHB) levels were initially tracked daily using a combination blood glucose and ketone meter and frequency of tracking was modified by the care team based based on each individual’s needs and preferences.

Participants with high blood pressure (hypertension) were provided with an automatic home blood pressure machine (sphygmomanometer) and they were instructed to record their readings daily to weekly in the supplied app, depending on recent blood pressure control. Antihypertensive medication prescriptions were adjusted based on home blood pressure readings and reported symptoms.

Downward Adjustment and/or Discontinuation of Medications

As blood pressure came down, diuretic medication was the first antihypertensive medication to be discontinued. This was followed by beta blockers (unless the participant had a history of coronary artery disease).

Angiotensin-converting-enzyme inhibitors (ACE inhibitors) and angiotensin II receptor blockers (ARBs) were generally continued due to their known protective effect on the kidneys in those with Type 2 Diabetes.

Statin medications were adjusted to maintain a goal of LDL-P under 1000 nmol L−1 (or based on participant preference after full risk/benefit discussion with the physician).

The Usual Care (UC) Group

For comparison purposes, an independent group of patients with Type 2 Diabetes were also recruited for the study and were referred to Registered Dietitians that provided dietary advice according to the American Diabetes Association Guidelines [4].

Laboratory Assessors

Since an abnormal lipid / cholesterol profile (“atherogenic dyslipidemia”) is a known risk factor for CVD [5] and is very common in people with Type 2 Diabetes, a number of laboratory tests were conducted at the beginning of the study and the end to determine if they improved, stayed the same or got worse.

Most common in people with Type 2 Diabetes is where there are increased triglycerides (TG), decreased high-density lipoprotein cholesterol concentration (HDL-C) and increased small low-density lipoprotein particle number (small LDL-P).

The authors of this study state that evidence suggests that increased very low-density lipoprotein particle number (VLDL-P) and a large VLDL-P in particular may be one of the key underlying abnormalities in this abnormal lipid / cholesterol profile (“atherogenic dyslipidemia”) associated with T2D.

The authors also outline how higher concentrations of small LDL are often associated with increased total LDL particle number (LDL-P) and increased ApoB which is the main protein constituent of  very low-density lipoprotein (VLDL) and low-density lipoprotein (LDL). The authors provide previous study evidence that demonstrates that in people with insulin resistance and T2D, increased total LDL particle number (LDL-P) and increased ApoB may exist even with normal to low LDL-C concentrations values. For this reason, LDL-C alone was not relied on as a measure of abnormal lipid / cholesterol profile (“atherogenic dyslipidemia”) in this study as it could miss the impact of increased total LDL particle number (LDL-P) and/or ApoB.

The authors mentioned that in previous studies with carbohydrate restriction of up to 1 year, while triglycerides (TG) usually decrease and HDL-C often increase, LDL-C sometimes increased and other times decreases. The authors note that although higher LDL-C is a known risk factor for CVD, low LDL-C may also reflect higher small, dense LDL, total LDL particle number (LDL-P) or ApoB and thus be a risk factor, as well.

Since inflammation is involved at all stages of the atherosclerotic process, higher high-sensitivity C-reactive protein (CRP) and/or higher white blood cell count (WBC) were assessed as risk factors for CVD.

Finally, since high blood pressure (hypertension) is also an added risk factor for CVD in people with T2D, tighter blood pressure control was deemed to reduce the risk of DVD, stroke and other microvascular events.

Continuous Care Intervention (CCI) Group

Standard laboratory fasting blood draws of the CCI group were obtained at the start of the study (baseline), at 70 days (3 months) and at ~ 1 year follow-up.

Lipid/cholesterol-related tests included ApoB, ApoA1, total cholesterol, triglycerides, direct HDL-C concentrations and LDL was calculated using the Friedewald equation.

The LipoProfile3 algorithm was used to determine relationship of lipid subfractions to cardiovascular (CVD) risk – specifically the number of HDL particles (HDL-P) previously reported  to be associated with death, Myocardial Infarction (MI), stroke and hospitalization, HDL-C (HDL cholesterol) which is the amount of cholesterol those particles are carying, which is not associated with these negative outcomes and HDL-P subclasses [6].

Risk was also determined using the lipoprotein insulin resistance score (LP-IR) which was proposed to be associated with the homeostasis model assessment of insulin resistance (HOMA-IR) and glucose disposal rate (GDR) [7].

Finally, risk was also determined using the 10-year atherosclerotic  cardiovascular disease (ACSVD) risk score of the American College of Cardiology [8].

Carotid ultrasonography (cIMT) measure was performed at baseline and 1 year to characterize atherosclerotic risk.

The Usual Care (UC) Group

Body measurements, vital signs and fasting blood draws for the Usual Care (UC) group were obtained at the start of the study (baseline) and at 1 year using the same clinical facilities and laboratory and data collection methods. Carotid ultrasonography (cIMT) measure was also performed at baseline and 1 year to characterize atherosclerotic risk.


There were no significant difference in the baseline characteristics of the two sub groups of CCI participants (web-based on onsite-based) and no significant difference at 1 year, so for the purpose of analysis, data from both groups were combined.

As well, there were no significant difference in the baseline characteristics of the Usual Care (UC) group (which served as an observational comparison group) and the Continuous Care Intervention Group (CCI) except mean body weight and BMI were higher in the CCI versus the UC group.

The within-Continuous Care Intervention group changes in the following lipids and lipoproteins were all statistically significant and were as follows; ApoA1  [a component of high-density lipoprotein (HDL)] increase by +”‰9.8%) ApoB / ApoA1 ratio decreased by −”‰9.5% Triglycerides (TG) decreased by −”‰24.4% LDL-C increased by +”‰9.9% but LDL-particle size also increased by +”‰1.1% (that is, large fluffy LDL increased compared with small, dense LDL) HDL-C increased by +”‰18.1% total HDL-P increased by +”‰4.9% large HDL-P increased by 23.5% Triglyceride/ HDL-C ratio decreased by −”‰29.1% large VLDL-P decreased by −”‰38.9% small LDL-P decreased by −”‰20.8% There were no significant changes in total LDL-P or ApoB.

These results are impressive!

Simply by decreasing the amount of carbohydrate in the diet over the course of a year there was a dramatic improvement in lipid and lipoprotein markers associated with markers of cardiovascular risk.

In addition, the Continuous Care Intervention group had a significant reduction in; systolic blood pressure decreased −”‰4.8% diastolic blood pressure decreased −”‰4.3% C-Reactive Protein (CRP) decreased almost 40% (i.e. −”‰39.3%) white blood cell (WBC) count decreased −”‰9.1%

Below are graphs of the changes in biomarkers for the Continuous Care Intervention (CCI) group (figure 1) and the Usual Care (UC) Group;

FIGURE 1: changes in biomarkers for the Continuous Care Intervention (CCI) group


FIGURE 2: changes in biomarkers for the Usual Care (UC) group

Below is a comparative graph of the two groups, the Continuous Care Intervention (CCI) Group and the Usual Care (UG) Group

FIGURE 3: changes in biomarkers for the Continuous Care Intervention (CCI) group compared to the Usual Care (UC) group

Some Final Thoughts…

This study demonstrates that a therapeutic ketogenic diet followed over the course of 1 year significantly improved 22 of 26 cardiovascular disease risk markers in those with Type 2 Diabetes. This is huge!

The size of the study group was large and had an 83% retention rate over the course of the year – which in and by itself demonstrates that the intervention diet was one that people had no difficulty staying with in their day-to-day lives, without the use of meal replacements (shakes or bars).

While not a randomized control trial between CCI and UG groups, this study supports that a ketogenic diet is both safe and effective for periods of up to a year (and in other studies has been documented to be safe and effective for up to two-years). Not only can a well-designed ketogenic diet reverse many of the symptoms of Diabetes it can also significantly improve risk markers for cardiovascular disease.

Do you have questions about how a carefully-designed low carbohydrate or ketogenic diet can help you improve symptoms of Type 2 Diabetes and lower markers of risk factors for cardiovascular disease? Please send me a note using the ”Contact Me” form above to find out more.


  1. Nasir H. Bhanpuri, Sarah J. Hallberg, Paul T. Williams et al, Cardiovascular disease risk factor responses to a type 2 diabetes care model including nutritional ketosis induced by sustained carbohydrate restriction at 1 year: an open label, non-randomized, controlled study, Cardiovascular Diabetology, 2018, 17(56)
  2. McKenzie AL, Hallberg SJ, Creighton BC, Volk BM, Link TM, Abner MK, Glon RM, McCarter JP, Volek JS, Phinney SD, A Novel Intervention Including Individualized Nutritional Recommendations Reduces Hemoglobin A1c Level, Medication Use, and Weight in Type 2 Diabetes, JMIR Diabetes 2017;2(1):e5, URL:, DOI: 10.2196/diabetes.6981
  3. Hallberg SJ, McKenzie AL, Williams, PT et al. Diabetes Ther (2018). Effectiveness and Safety of a Novel Care Model for the Management of Type 2 Diabetes at 1 Year: An Open-Label, Non-Randomized, Controlled Study.
  4. America Diabetes Association, Lifestyle management. Diabetes Care. 2017;40 (Suppl 1):S33—S43
  5. Fruchart J-C, Sacks F, Hermans MP, Assmann G, Brown WV, Ceska R, et al. The Residual Risk Reduction Initiative: a call to action to reduce residual vascular risk in patients with dyslipidemia. Am J Cardiol. 2008;102:1K—34K.
  6. May HT,  Anderson JL, Winegar DA, Utility of high density lipoprotein particle concentration in predicting future major adverse cardiovascular events among patients undergoing angiography, Clinical Biochemistry, 2016;49(15): 1122-1126
  7. Shalaurova I, Connelly MA, Garvey WT, Otvos JD. Lipoprotein insulin resistance index: a lipoprotein particle-derived measure of insulin resistance. Metabol Syndr Relat Disord. 2014;12:422—9.
  8. Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R, et al. ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2013;2014:S49—73 (tool:!/calculate/estimate/)

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