The Ketogenic Diet as a Treatment for Metabolic Syndrome

Metabolic Syndrome (MetS) can be viewed as a set of symptoms of insulin resistance. Taken together, those symptoms signify a threat of heart disease, diabetes, cancer, and other diseases that appear to be different manifestations of a common cause. That common cause is likely to be insulin resistance.

This hypothesis is supported by evidence that ketogenic diets not only normalize insulin sensitivity and the symptoms of MetS, but they treat (or have promise in treating) many MetS-associated diseases.

In light of this, it seems plausible that adopting a ketogenic diet will significantly improve your chances of avoiding these diseases in the first place.

In brief

  • Metabolic Syndrome is a cluster of symptoms, not a disease. Those symptoms are useful to class together, because their association with a variety of different diseases strongly suggests a common cause. In other words, it has provided us with a compelling hypothesis.
  • If there were a common cause, then a therapy that treats that cause should help them all. Moreover, it should reduce the symptoms of Metabolic Syndrome itself. Further, treatments that work for one but not the others should be considered inferior, “band-aid” treatments.
  • A ketogenic diet improves Metabolic Syndrome. Also, for every disease associated with MetS that we have investigated, a keto diet has either been shown to help, has shown preliminary evidence in its favour, or has not been sufficiently tested to rule out.
  • This supports the hypothesis that those diseases have a common cause, and that a ketogenic diet addresses it.

What is Metabolic Syndrome?

Metabolic Syndrome is a cluster of symptoms that commonly occur together and indicate increased risk of cardiovascular disease (CVD), type 2 diabetes (T2D), cancer, and other diseases. Clinically, to be diagnosed with MetS, you have to score above (or in the case of HDL, below) a healthy threshold in at least 3 of the following 5 measurements: waist size, fasting blood glucose, blood pressure, triglycerides, and HDL. All of these are associated with insulin resistance, although some are more predictive than others [1, 2, 3] , and so metabolic syndrome might be more accurately described as insulin resistance syndrome (and it sometimes is) [4, 5].

Just as with any such measure, it can be misleading to draw a threshold at such a particular point. The cost of ignoring warning signs because they fall below a threshold may be worse than the benefit of giving a special diagnosis to those who have multiple symptoms, each of which could be recognised as warranting treatment on its own [6].

Nonetheless, it is useful to have a name for a set of associations for two reasons.

  1. It allows us to recognise the commonalities in symptoms of a variety of disease states which is suggestive of common mechanisms.
  2. It promotes the insight that any treatment that is purported to improve risk of CVD or T2D ought to have a beneficial impact on all of the associated symptoms. If it doesn’t, there is a risk that it is a band-aid solution that temporarily hides the problem rather than fixing it.

Because these symptoms so often occur together, and because they are all risk factors for a group of diseases which in turn are risk factors for each other, it is the contention of many scientists that they have a common cause. Some argue that this common cause is obesity itself. A separate cause is postulated for obesity, which then is supposed to cause the other risk factors. However, other researchers, ourselves among them, believe that obesity and the other symptoms have a common cause related to insulin signalling. For this reason, we have grouped together several diseases which appear to have insulin signalling at their root, and which have elevated risk in the presence of Metabolic Syndrome symptoms. These diseases include (but are not limited to) cardiovascular disease 7, type 2 diabetes 8, polycystic ovarian syndrome 9, Alzheimer’s disease 10, and cancer. 11.

In other words, we believe that Metabolic Syndrome is not itself a disease, but is a class of warning signs associated with the progression of several other diseases. If this is true, then when you treat the underlying cause of these symptoms, they will all normalize together, and the risk of all associated diseases will simultaneously be reduced.

Ketogenic diets treat insulin resistance and therefore are expected to treat all diseases that have Metabolic Syndrome as a symptom.

The following is just a sample of evidence showing that not only does a keto diet address the symptoms of MetS itself, but also those conditions associated with it. This is not meant to be comprehensive — there are many more supporting experiments in each category!

  • Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet12.
  • A ketogenic diet favorably affects serum biomarkers for cardiovascular disease in normal-weight men 13.
  • In addition to decreasing body weight and improving glycemia, a ketogenic diet can be effective in decreasing antidiabetic medication dosage 14 .
  • In a pilot study, a ketogenic diet led to significant improvement in weight, percent free testosterone, LH/FSH ratio, and fasting insulin in women with obesity and PCOS over a 24 week period 15.
  • An oral ketogenic compound, AC-1202, was tested in subjects with probable Alzheimer’s disease, and resulted in a significant improvement to cognitive scores 16.
  • It seems a reasonable possibility that a very-low-carbohydrate diet could help to reduce the progression of some types of cancer, although at present the evidence is preliminary 17.


  • The ketogenic diet is a powerful therapy that exerts its healing effect in a wide variety of conditions that may seem superficially unrelated.
  • These conditions are linked by their connection to insulin resistance, and therefore their association with MetS.
  • This supports not only the hypothesis that a keto diet treats MetS, but also that insulin resistance is the underlying cause of many devastating diseases, and that the way a keto diet is treating those is by intercepting and correcting the underlying cause.


1 Evidence type: observational analysis

Insulin resistance in aging is related to abdominal obesity.
Kohrt WM, Kirwan JP, Staten MA, Bourey RE, King DS, Holloszy JO.
Diabetes. 1993 Feb;42(2):273-81.

(emphasis ours)


Studies have shown that insulin resistance increases with age, independent of changes in total adiposity. However, there is growing evidence that the development of insulin resistance may be more closely related to abdominal adiposity. To evaluate the independent effects of aging and regional and total adiposity on insulin resistance, we performed hyperinsulinemic euglycemic clamps on 17 young (21-33 yr) and 67 older (60-72 yr) men and women. We assessed FFM and total and regional adiposity by hydrodensitometry and anthropometry. Insulin-stimulated GDRs at a plasma insulin concentration of approximately 450 pM averaged 45.6 +/- 3.3 FFM-1 x min-1 (mean +/- SE) in the young subjects, 45.6 +/- 10.0 FFM-1 x min-1 in 24 older subjects who were insulin sensitive, and 23.9 +/- 11.7 FFM-1 x min-1 in 43 older subjects who were insulin resistant. Few significant differences were apparent in skin-fold and circumference measurements between young and insulin-sensitive older subjects, but measurements at most central body sites were significantly larger in the insulin-resistant older subjects. Waist girth accounted for > 40% of the variance in insulin action, whereas age explained only 10-20% of the total variance and < 2% of the variance when the effects of waist circumference were statistically controlled. These results suggest that insulin resistance is more closely associated with abdominal adiposity than with age.”]

2. Evidence type: retrospective observation

Use of waist circumference to predict insulin resistance: retrospective study.
Wahrenberg H, Hertel K, Leijonhufvud BM, Persson LG, Toft E, Arner P.
BMJ. 2005 Jun 11;330(7504):1363-4. Epub 2005 Apr 15.

In the multiple regression model, waist circumference was the strongest regressor of the five significant covariates (standardised partial regression coefficients: waist circumference β1 = 0.37; log-plasma triglycerides β2 = 0.23; systolic blood pressure β3 = 0.10, high density lipoprotein cholesterol β4 = -0.09; and body mass index β5 = 0.15 (P < 0.001)).

3. Evidence type: observational analysis

Biomarkers in Fasting Serum to Estimate Glucose Tolerance, Insulin Sensitivity, and Insulin Secretion
Allison B. Goldfine, Robert W. Gerwien, Janice A. Kolberg, Sheila O’Shea, Sarah Hamren, Glenn P. Hein, Xiaomei M. Xu, and Mary Elizabeth Patti
Clinical Chemistry 57:2 326–337 (2011)

A subset of 5 markers was associated with insulin sensitivity (assessed using the dynamic CISI measure): fasting glucose, insulin, Fas ligand, complement C3, and PAI-1. As shown in Fig. 3C, 91% of variance between predicted and observed CISI values was accounted for by these 5 markers alone (P 0.0001). In addition, a bootstrap R 2 value of 0.90 (IQR 0.83–0.94) indicates that the model could be expected to perform well on an independent data set. By comparison, HOMA-IR, a widely accepted estimate of insulin resistance based on fasting glucose and insulin, explained 88% of the variance of the dynamic measure of insulin sensitivity.

4. Evidence type: observation

A.D.A.M. Medical Encyclopedia.

Metabolic syndrome; Insulin resistance syndrome; Syndrome X

5. Evidence type: observation

Diabetes Health Center Insulin Resistance and Diabetes

If you have pre-diabetes or diabetes, chances are that you’ve heard of the medical term insulin resistance syndrome or metabolic syndrome. Insulin resistance or metabolic syndrome describes a combination of health problems that have a common link — an increased risk of diabetes and early heart disease.

6. Evidence type: observation

The metabolic syndrome: is this diagnosis necessary?
Gerald M Reaven.
Am J Clin Nutr June 2006 vol. 83 no. 6 1237-1247

The goal of diagnosing the metabolic syndrome is to identify persons at increased risk of CVD. Because each component that makes up the versions of the metabolic syndrome increases CVD risk (34, 36, 37, 62, 68, 69), it seems prudent to treat any of these abnormalities that are present. Furthermore, it would not be too surprising that the more abnormalities present in any given person, the greater would be his or her risk of CVD. The question can be raised, however, as to whether identifying a person as having metabolic syndrome necessarily indicates that he or she is at greater risk of CVD than is a person who may not qualify for that designation. This did not seem to be the case when the ATP III criteria were applied to the Framingham Study database (117); a recent report pointed out that persons meeting any 2 criteria were at no less risk than were those meeting 3 criteria. Indeed, it would be possible to describe a number of prototypic clinical situations in which a person with 1 or 2 abnormalities would be at greater risk of CVD than would a patient who met the metabolic syndrome diagnostic criteria.

7. Evidence type: retrospective observation

The Metabolic Syndrome and Total and Cardiovascular Disease Mortality in Middle-aged Men.
Hanna-Maaria Lakka, MD, PhD; David E. Laaksonen, MD, MPH; Timo A. Lakka, MD, PhD; Leo K. Niskanen, MD, PhD; Esko Kumpusalo, MD, PhD; Jaakko Tuomilehto, MD, PhD; Jukka T. Salonen, MD, PhD
JAMA. 2002;288(21):2709-2716. doi:10.1001/jama.288.21.2709.

The metabolic syndrome, a concurrence of disturbed glucose and insulin metabolism, overweight and abdominal fat distribution, mild dyslipidemia, and hypertension, is associated with subsequent development of type 2 diabetes mellitus and cardiovascular disease (CVD).

The prevalence of the metabolic syndrome ranged from 8.8% to 14.3%, depending on the definition. There were 109 deaths during the approximately 11.4-year follow-up, of which 46 and 27 were due to CVD and CHD, respectively. Men with the metabolic syndrome as defined by the NCEP were 2.9 (95% confidence interval [CI], 1.2-7.2) to 4.2 (95% CI, 1.6-10.8) times more likely and, as defined by the WHO, 2.9 (95% CI, 1.2-6.8) to 3.3 (95% CI, 1.4-7.7) times more likely to die of CHD after adjustment for conventional cardiovascular risk factors. The metabolic syndrome as defined by the WHO was associated with 2.6 (95% CI, 1.4-5.1) to 3.0 (95% CI, 1.5-5.7) times higher CVD mortality and 1.9 (95% CI, 1.2-3.0) to 2.1 (95% CI, 1.3-3.3) times higher all-cause mortality. The NCEP definition less consistently predicted CVD and all-cause mortality. Factor analysis using 13 variables associated with metabolic or cardiovascular risk yielded a metabolic syndrome factor that explained 18% of total variance. Men with loadings on the metabolic factor in the highest quarter were 3.6 (95% CI, 1.7-7.9), 3.2 (95% CI, 1.7-5.8), and 2.3 (95% CI, 1.5-3.4) times more likely to die of CHD, CVD, and any cause, respectively.

Cardiovascular disease and all-cause mortality are increased in men with the metabolic syndrome, even in the absence of baseline CVD and diabetes.

8. Evidence type: retrospective observation

Risks for All-Cause Mortality, Cardiovascular Disease, and Diabetes Associated With the Metabolic Syndrome: A summary of the evidence.
Earl S. Ford, MD, MPH
Diabetes Care July 2005 vol. 28 no. 7 1769-1778

For studies that used the exact NCEP definition of the metabolic syndrome, random-effects estimates of combined relative risk were 1.27 (95% CI 0.90–1.78) for all-cause mortality, 1.65 (1.38–1.99) for cardiovascular disease, and 2.99 (1.96–4.57) for diabetes. For studies that used the most exact WHO definition of the metabolic syndrome, the fixed-effects estimates of relative risk were 1.37 (1.09–1.74) for all-cause mortality and 1.93 (1.39–2.67) for cardiovascular disease; the fixed-effects estimate was 2.60 (1.55–4.38) for coronary heart disease.

CONCLUSIONS—These estimates suggest that the population-attributable fraction for the metabolic syndrome, as it is currently conceived, is ∼6–7% for all-cause mortality, 12–17% for cardiovascular disease, and 30–52% for diabetes.

9. Evidence type: retrospective observation

Prevalence and Characteristics of the Metabolic Syndrome in Women with Polycystic Ovary Syndrome.
Teimuraz Apridonidze, Paulina A. Essah, Maria J. Iuorno and John E. Nestler.
The Journal of Clinical Endocrinology & Metabolism April 1, 2005 vol. 90 no. 4 1929-1935

The polycystic ovary syndrome (PCOS) is characterized by insulin resistance with compensatory hyperinsulinemia. Insulin resistance also plays a role in the metabolic syndrome (MBS). We hypothesized that the MBS is prevalent in PCOS and that women with both conditions would present with more hyperandrogenism and menstrual cycle irregularity than women with PCOS only.

We conducted a retrospective chart review of all women with PCOS seen over a 3-yr period at an endocrinology clinic. Of the 161 PCOS cases reviewed, 106 met the inclusion criteria. The women were divided into two groups: 1) women with PCOS and the MBS (n = 46); and 2) women with PCOS lacking the MBS (n = 60).

Prevalence of the MBS was 43%, nearly 2-fold higher than that reported for age-matched women in the general population. Women with PCOS had persistently higher prevalence rates of the MBS than women in the general population, regardless of matched age and body mass index ranges.

10. Evidence type: retrospective observation

Association of metabolic syndrome with Alzheimer disease: A population-based study.
M. Vanhanen, PhD, K. Koivisto, MD, PhD, L. Moilanen, MD, PhD, E. L. Helkala, PhD, T. Hänninen, PhD, H. Soininen, MD, PhD, K. Kervinen, MD, PhD, Y. A. Kesäniemi, MD, PhD, M. Laakso, MD, PhD and J. Kuusisto, MD, PhD
Neurology September 12, 2006 vol. 67 no. 5 843-847

Of the study subjects, 418 (43.6%) had MetS. Probable or possible AD was diagnosed in 45 subjects (4.7%). AD was more frequently detected in subjects with MetS than in subjects without MetS (7.2 vs 2.8%; p < 0.001). The prevalence of AD was higher in women with MetS vs women without the syndrome (8.3 vs 1.9%; p < 0.001), but in men with MetS, the prevalence of AD was not increased (3.8 vs 3.9%; p = 0.994). In univariate logistic regression analysis, MetS was significantly associated with AD (odds ratio [OR] 2.71; 95% CI 1.44 to 5.10). In multivariate logistic regression analysis including also apolipoprotein E4 phenotype, education, age, and total cholesterol, MetS was significantly associated with AD (OR 2.46; 95% CI 1.27 to 4.78). If only nondiabetic subjects were included in the multivariate analysis, MetS was still significantly associated with AD (OR 3.26; 95% CI 1.45 to 7.27).

11. Evidence type: review and meta-analysis

Metabolic syndrome and risk of cancer: a systematic review and meta-analysis.
Esposito K, Chiodini P, Colao A, Lenzi A, Giugliano D.
Diabetes Care. 2012 Nov;35(11):2402-11. doi: 10.2337/dc12-0336.

RESULTS: We analyzed 116 datasets from 43 articles, including 38,940 cases of cancer. In cohort studies in men, the presence of metabolic syndrome was associated with liver (relative risk 1.43, P < 0.0001), colorectal (1.25, P < 0.001), and bladder cancer (1.10, P = 0.013). In cohort studies in women, the presence of metabolic syndrome was associated with endometrial (1.61, P = 0.001), pancreatic (1.58, P < 0.0001), breast postmenopausal (1.56, P = 0.017), rectal (1.52, P = 0.005), and colorectal (1.34, P = 0.006) cancers. Associations with metabolic syndrome were stronger in women than in men for pancreatic (P = 0.01) and rectal (P = 0.01) cancers. Associations were different between ethnic groups: we recorded stronger associations in Asia populations for liver cancer (P = 0.002), in European populations for colorectal cancer in women (P = 0.004), and in U.S. populations (whites) for prostate cancer (P = 0.001).

CONCLUSIONS: Metabolic syndrome is associated with increased risk of common cancers; for some cancers, the risk differs betweens sexes, populations, and definitions of metabolic syndrome.

12. Evidence type: controlled experiment

Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet.
Volek JS, Phinney SD, Forsythe CE, Quann EE, Wood RJ, Puglisi MJ, Kraemer WJ, Bibus DM, Fernandez ML, Feinman RD.
Lipids. 2009 Apr;44(4):297-309. doi: 10.1007/s11745-008-3274-2. Epub 2008 Dec 12.


We recently proposed that the biological markers improved by carbohydrate restriction were precisely those that define the metabolic syndrome (MetS), and that the common thread was regulation of insulin as a control element. We specifically tested the idea with a 12-week study comparing two hypocaloric diets (approximately 1,500 kcal): a carbohydrate-restricted diet (CRD) (%carbohydrate:fat:protein = 12:59:28) and a low-fat diet (LFD) (56:24:20) in 40 subjects with atherogenic dyslipidemia. Both interventions led to improvements in several metabolic markers, but subjects following the CRD had consistently reduced glucose (-12%) and insulin (-50%) concentrations, insulin sensitivity (-55%), weight loss (-10%), decreased adiposity (-14%), and more favorable triacylglycerol (TAG) (-51%), HDL-C (13%) and total cholesterol/HDL-C ratio (-14%) responses. In addition to these markers for MetS, the CRD subjects showed more favorable responses to alternative indicators of cardiovascular risk: postprandial lipemia (-47%), the Apo B/Apo A-1 ratio (-16%), and LDL particle distribution. Despite a threefold higher intake of dietary saturated fat during the CRD, saturated fatty acids in TAG and cholesteryl ester were significantly decreased, as was palmitoleic acid (16:1n-7), an endogenous marker of lipogenesis, compared to subjects consuming the LFD. Serum retinol binding protein 4 has been linked to insulin-resistant states, and only the CRD decreased this marker (-20%). The findings provide support for unifying the disparate markers of MetS and for the proposed intimate connection with dietary carbohydrate. The results support the use of dietary carbohydrate restriction as an effective approach to improve features of MetS and cardiovascular risk.

13. Evidence type: non-randomized experiment

A Ketogenic Diet Favorably Affects Serum Biomarkers for Cardiovascular Disease in Normal-Weight Men.
Matthew J. Sharman, William J. Kraemer, Dawn M. Love, Neva G. Avery, Ana L. Gómez, Timothy P. Scheett, and Jeff S. Volek.
J. Nutr. July 1, 2002 vol. 132 no. 7 1879-1885

The primary objective of this study was to examine how healthy normolipidemic, normal-weight men respond to a ketogenic diet in terms of fasting and postprandial CVD biomarkers. Ketogenic diets have been criticized on the grounds they jeopardize health (8); however, very few studies have directly evaluated the effects of a ketogenic diet on fasting and postprandial risk factors for CVD. Subjects consumed a diet that consisted of 8% carbohydrate (27 kg/m2 and a clinical diagnosis of PCOS were recruited from the community. They were instructed to limit their carbohydrate intake to 20 grams or less per day for 24 weeks. Participants returned every two weeks to an outpatient research clinic for measurements and reinforcement of dietary instruction. In the 5 women who completed the study, there were significant reductions from baseline to 24 weeks in body weight (-12%), percent free testosterone (-22%), LH/FSH ratio (-36%), and fasting insulin (-54%). There were non-significant decreases in insulin, glucose, testosterone, HgbA1c, triglyceride, and perceived body hair. Two women became pregnant despite previous infertility problems.

16. Evidence type: randomized, double-blind, placebo-controlled, multicenter trial

Study of the ketogenic agent AC-1202 in mild to moderate Alzheimer’s disease: a randomized, double-blind, placebo-controlled, multicenter trial.
Samuel T Henderson, Janet L Vogel, Linda J Barr, Fiona Garvin, Julie J Jones and Lauren C Costantini.
Nutrition & Metabolism 2009, 6:31

AC-1202 significantly elevated a serum ketone body (β-hydroxybutyrate) 2 hours after administration when compared to Placebo. In each of the population groups, a significant difference was found between AC-1202 and Placebo in mean change from Baseline in ADAS-Cog score on Day 45: 1.9 point difference, p = 0.0235 in ITT; 2.53 point difference, p = 0.0324 in per protocol; 2.6 point difference, p = 0.0215 in dosage compliant. Among participants who did not carry the APOE4 allele (E4(-)), a significant difference was found between AC-1202 and Placebo in mean change from Baseline in ADAS-Cog score on Day 45 and Day 90. In the ITT population, E4(-) participants (N = 55) administered AC-1202 had a significant 4.77 point difference in mean change from Baseline in ADAS-Cog scores at Day 45 (p = 0.0005) and a 3.36 point difference at Day 90 (p = 0.0148) compared to Placebo. In the per protocol population, E4(-) participants receiving AC-1202 (N = 37) differed from placebo by 5.73 points at Day 45 (p = 0.0027) and by 4.39 points at Day 90 (p = 0.0143). In the dosage compliant population, E4(-) participants receiving AC-1202 differed from placebo by 6.26 points at Day 45 (p = 0.0011, N = 38) and 5.33 points at Day 90 (p = 0.0063, N = 35). Furthermore, a significant pharmacologic response was observed between serum β-hydroxybutyrate levels and change in ADAS-Cog scores in E4(-) subjects at Day 90 (p = 0.008).

17. Evidence type: review of experiments and case-studies

Beyond weight loss: a review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets.
A Paoli, A Rubini, J S Volek and K A Grimaldi.
European Journal of Clinical Nutrition (2013) 67, 789–796; doi:10.1038/ejcn.2013.116; published online 26 June 2013

[I]t seems a reasonable possibility that a very-low-carbohydrate diet could help to reduce the progression of some types of cancer, although at present the evidence is preliminary. In the 1980s, seminal animal studies by Tisdale and colleagues demonstrated that a ketogenic diet was capable to reduce tumour size in mice, whereas more recent research has provided evidence that ketogenic diets may reduce tumour progression in humans, at least as far as gastric and brain cancers are concerned. Although no randomized controlled trials with VLCKD have yet been conducted on patients and the bulk of evidence in relation to the influence of VLCKD on patient survival is still anecdotal, a very recent paper by Fine et al. suggests that the insulin inhibition caused by a ketogenic diet could be a feasible adjunctive treatment for patients with cancer. In summary, perhaps through glucose ‘starvation’ of tumour cells and by reducing the effect of direct insulin-related actions on cell growth, ketogenic diets show promise as an aid in at least some kind of cancer therapy and is deserving of further and deeper investigation—certainly the evidence justifies setting up clinical trials.